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International Journal of Scientific Research in Science and Technology Print ISSN: 2395-6011 Online ISSN : 2395-602X

Volume 1, Issue 5, November-December-2015 International Peer Reviewed, Open Access Journal Bimonthly Publication

Published By Technoscience Academy (The International Open Access Publisher)

Email: [email protected] Website: www.technoscienceacademy.com

Advisory/Editorial Board Dr. Manish Shorey, Bangalore, Karnataka Dr. M. K. Rameshaiah, Bangalore, Karnataka Dr. V. S. Majumdar, Pune, Maharashtra Prof. Shardul Agravat, Surendranagar, Gujarat, India Dr. Sundeep Sinha, Delhi, Gujarat, India Dr. Ashish Sharma, Delhi, Gujarat, India Prof. Vaishali Kalaria, RKU, Rajkot, Gujarat, India Prof. H. B. Jethva, L. D. College of Engineering, Ahmedabad, Gujarat, India Prof. Bakul Panchal, L. D. College of Engineering, Ahmedabad, Gujarat, India Prof. Bhavesh Prajapati, Government MCA College Maninagar, Ahmedabad, Gujarat, India Prof. Amod Pandurang Shrotri, Shivaji University, Kolhapur, Maharashtra, India Prof. Sunil Kulkarni, Datta Meghe College of Engg. Airoli,Mumbai, Maharashtra, India Prof. Atishey Mittal, S.R.M. University, NCR Campus, Modinagar, Ghaziabad, Uttar Pradesh, India Dr. Syed Umar, Dept. of Computer Science and Engineering, KL University, Guntur, Andhra Pradesh, India Dr. S. Ahmed John, Jamal Mohamed College, Tiruchirappalli, India Prof. S. Jagadeesan, Nandha Engineering College Erode, Tamil Nadu, India Dr. Faisal Talib, IIT Roorkee(PhD), Aligarh, Uttar Pradesh, India Prof. Joshi Rahul Prakashchandra, Parul Institute of Engineering & Technology, Vadodara, Gujarat, India Dr. Aftab Alam Tyagi, Department of Mathematics, SRM University NCR Campus, Uttar Pradesh, India

Dr. Sudhir Kumar, Department of Mathematics, S.D. (P.G.) College, Uttar Pradesh, India Dr. Rimple Pundir, Nagar, Uttar Pradesh, India Prof (Dr.) Umesh Kumar, Dept of Science & Technology, Govt. Women’s Polytechnic, Ranchi,Jharkhand,India Abhishek Shukla, R. D. Engineering College Technical Campus, Ghaziabad, Uttar Pradesh, India Dr. Balram Panigrahi, Soil & Water Conservation Engineering, College of Agricultural Engg. & Techn. Orissa University Of Agriculture & Technology, Bhubanmeswar, Odisha, India Dr. Anant Lalchand Chaudhari, Department of Electronics, Arts, Science & Commerce College, Chopda, Jalgaon, Maharashtra India Dr. V. Ananthaswamy, Department of Mathematics, The Madura College (Autonomous), Madurai, Tamil Nadu, India Dr. Arvind Bijalwan, Indian Institute of Forest Management (IIFM) (Ministry of Environment & Forests, Govt. of India) Bhopal, Madhya Pradesh, India Dr. Aditya Kishore Dash, Department of Environmental Engineering, Institute of Technical Education and Research (ITER), SOA University, Bhubaneswar, Odisha, India Dr. Subha Ganguly, Department of Veterinary Microbiology Arawali Veterinary College, Bajor, Rajasthan, India Dr. Shivakumar Singh, MVS Govt UG & PG College, Palamuru University, Mahabubnagr, Telangana, India Md Irfan Ahmed, Power System, Sityog Institute Of Technology Aurangabad, Bihar, India A. Dinesh Kumar, Mathematics, Dhanalakshmi Srinivasan Engineering College, Perambalur, Tamilnadu, India Shyam Lal Sharma, Mechanical Engineering, Department, AFSET, Al Falah University, Dhauj, Faridabad, India Prof (Dr.) Hardeep Singh, Electronics & Communication Engineering Department, Indo Global College of Engineering, Abhipur, District Mohali, Punjab, India S. R. Boselin Prabhu, Anna University Chennai, Tamilnadu, India

N. R. Shingala, Department of Mechanical Engineering, VVP Engineering College, Rajkot, Gujarat, India R. G. Vaghela, Mechanical Engineering, Atmiya Institute of Technology & Science, Rajkot, Gujarat, India

International Advisory/Editorial Board Prof. Sundeep Singh, Mississauga, Ontario, Canada Dr. Joseph Easton, Boston, USA Dr. M. Chithirai Pon Selvan, Mechanical Engineering, Amity University, Dubai Dr. Md. Abdullah Al Humayun, School of Electrical Systems Engineering, University Malaysia, Perlis, Malaysia Dr. V. Balaji, Bahir Dar University, Bahir Dar, Ethiopia Lusekelo Kibona, Department of Computer Science, Ruaha Catholic University (RUCU) , Iringa, Tanzania Dr. Mohamed Abdel Fattah Ashabrawy, Reactors Department, Atomic Energy Authority, Egypt Dr. Abul Salam, UAE University, Department of Geography and Urban Planning, UAE Ayisi Larbi Christian, Shanghai Ocean University, Shanghai China Md. Amir Hossain, IBAIS University/Uttara University, Dhaka, Bangladesh Dr. Amer Taqa, Department of Dental Basic Science College of Dentistry, Mosul University, Iraq Prof. Dr. H. M. Srivastava, Department of Mathematics and Statistics, University of Victoria, Victoria, British Columbia, Canada AJENIKOKO Ganiyu Adedayo, Electronic and Electrical Engineering, Ladoke Akintola University of Technology, Ogbomosho, Nigeria

Atanda Saburi Abimbola, Nigerian Stored Products Research Institute Yaba Lagos Nigeria, Nigeria Dr. A. Heidari, Ph.D., D.Sc., Faculty of Chemistry, California South University (CSU), Irvine, California, USA Dr. Entessar Al Jbawi, General Commission for Scientific Agricultural Research,Crops Research Administration, Sugar Beet Department, Baramqa, Damascus, Syria Md. Kamrul Hasan, English Language Institute, United International University Universiti Utara Malaysia, Malaysia Dr. Eng. Ramzi R .Barwari, Department of Mechanical Engineering, College of Engineering, Salahaddin University - Hawler (SUH), Erbil - Kurdistan, Iraq Kerorsa, Lubo Teferi [Environmental Law and Governance], Seoul National University; Family Dormitory. Seoul, South Korea Dr. C. Viswanatha, Department of Chemistry, Arba Minch University, Arba Minch, Ethiopia Tsunatu Danlami Yavini, Chemistry Department, Faculty Of Science, Taraba State University, Jalingo , Taraba State, Nigeria Bello Alhaji Buhari , Usmanu Danfodiyo University, Department of Mathematics, Computer Science Unit, Sokoto, Nigeria Ramzi Raphael Ibraheem AL Barwari, ANKAWA - ERBIL, Department of Mechanical Engineering, College of Engineering, Salahaddin University - Hawler (SUH), Erbil - Kurdistan Innocent E. Bello, National Space Research and Development Agency (NASRDA), Abuja, Nigeria Ang Kean Hua,Department of Environmental Sciences, Faculty of Environment Studies, Universiti Putra Malaysia, Selangor Darul Ehsan, Malaysia

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Article/Paper OPIOID Pharmacology : A Review Vivek Sharma, Sunil Dutt, Rahul Kumar, Pankaj Sharma, Athar Javed, Rajender Guleria A Review paper on Viral Mobile Communications System Dr. Deepak Singh Yadav, Rajesh Kumar Pandey Perfectly g*b-Continuous Functions S. Bharathi Ultrasonic Velocity in Potassium Sodium Tantalate Mixed System Manish Uniyal, S. C. Bhatt Assessment of Shoreline Dynamics at Bonny Island, Nigeria using Geospatial Techniques Brown Joshua, Adekunle I. A Comparison of L-moments of Probability Distributions for Extreme Value Analysis of Rainfall for Estimation of Peak Flood Discharge for Ungauged Catchments N. Vivekanandan Students' Perception to Psychological Counselling Services at Omdurman Islamic University in Khartoum State-Sudan Eldood Yousif Eldood Ahmed, Husain Abdallah Ahmed, Eman Elkheir Awad Bidirectional Speed Control of DC Motor Based on Pulse Width Modulation using Microcontroller Ayman Y. Yousef, M. H. Mostafa A Review on Analysis of Friction Stir Welding Process of Steel Vikash, Gopal Sahu, Prakash Kumar Sen, Ritesh Sharma, Shailendra Bohidar Roadside Sand Deposits as Toxic Metals' Receptacles along three Major Roads in Port Harcourt Metropolis, Nigeria Christian Mathew, K. J. Orie Review of Earth Tube Heat Exchanger Sharda Chauhan, Gopal Sahu, Prakash Kumar Sen, Shailendra Bohidar, Ritesh Sharma Status, Characterization and Conservation Practices of Local Chicken Ecotypes, Ethiopia Addis Getu, Kefyalew Alemayehu, Atnaf Alebie

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Isopropanol Fractionation of Coconut Oil into its Olein and Stearin Fractions Sanjukta Kar, Rajib Ghosh, D. K. Bhattacharyya,Minakshi Ghosh A Review of Membrane Technology for Gas Separation Sanket D. Awasare, G. S. kulkarnib, Prashant P. Patilc, S. M. Chavand, John U. Kennedy Oubagaranadine An Assessment of the Impact of Information Communication Technology on Secondary School Teachers in Kebbi State, Nigeria Nwoji J. O Effluent Treatment Plant of Sugar Wastewater – A Review Sanket D Awasare, Harshavardhan U Bhosale, NIta P Chavan PEGASIS : Power-Efficient Gathering in Sensor Information Systems Alpesh R. Sankaliya Agricultural Land Suitability Assessment using Fuzzy Logic and Geographic Information System Techniques Atijosan A, Muibi K, Ogunyemi S, Adewoyin J, Badru R, Alaga A, Shaba A Right to Life with Dignity also includes Right to Die with Dignity: - Time To Amend Article 21 of Indian Constitution and Law of Euthenesia Pyali Chatterjee Challenges Facing Secondary School Managers in Strategic Planning in Kenya Ms Annette Wanyonyi, Judah M. Ndiku, John O. Shiundu Investigation of the Optical Properties of Liquid Deposition Cuso4 thin Film Nafie A. Almuslet, Yousif H. Alsheikh Adsorption mechanism of Cu(II) ion Removal from Aqueous Solution using Acid Activated Madhuca longifolia Stem M. Elamaran, S. Arivoli, N. Ingarsal, V Marimuthu Research and Studies on Vinegar Production - A Review Sunil Jayant Kulkarni FEM Simulations of Z-axis MEMS Capacitive Energy Harvester using Various Beams Hitesh Kumar Sharma, Jit.Dutta An Investigation of Malaria Predictors Using Logistic Regression Model Abubakar Boyi Dalatu, Mukhtar Garba, Nwoji Jude Oguejiofor Transformation of Palm Oil over H3PO4 / SiO2 Catalysts NÃdia M. Ribeiro Pastura, Eduardo L. G. Filho, Renata B. P. Machado, Cynthia F. Scofield, Lucia R. Raddi de Araújo, Wilma A. Gonzalez

An Approach to Survival Analysis when Frailty is Evident Jude Nwoji Oguejiofor, AbubakarBoyi Dalatu, KabiruYanusa Gorin Dikko

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A Review of False Smut Disease in Rice Ali Sattari, H-Nohtani, HO-Nasirpour, M-Ghadami, MO-Madahinasab, KMoradi, Mo-Noorozi Brown Spot Resistance in Rice : A Review Ali Sattari, H Nohtani, Na Azhdarpoor, M Ghadami, MO Madahinasab, K Moradi, Mo Noorozi Role of biotechnology in cancer control Mahin Ghorbani, Hamed Karimi Development of Guava Probiotic Dairy Beverages : Application of Mathematical Modelling between Consumer Acceptance Degree and Whey Ratio Hamad M. N. F., M. K. El-Nemr Economic Evaluation of Selexol – Based CO2 Capture Process for a Cement Plant Using Post – Combustion Technology Tsunatu D. Yavini, Mohammed-Dabo I. Ali, Waziri S. Muhammad 3D Cartographic Model And Animation of As-built Educational Landuse of UNIBEN, Nigeria Innocent E. Bello, ISI A. Ikhuoria Sensitivity of Initial Abstraction Coefficient on Prediction of RainfallRunoff for Various Land Cover Classes of 'Ton Watershed' Using Remote Sensing & GIS Based 'Rinspe' Model Narasayya Kamuju A Review of on the Spikelet Number in Rice Ali Sattari, ZA-Jahantigh Haghighi, HO-Nohtani, MO-Noorozi, AbNokhbeh Zaeim, K-Moradi, Na-Mirzaie Amirabad Blast Disease in Rice: A Review Farshad Karamian, AM-Heydari Nezhad, Ab-Nokhbeh Zaeim, K-Moradi, AH-Drakhshan A Review for Rice Sheath Blight Disease Abdolreza Nokhbeh Zaeim, Na-Mirzaie Amirabad, Ah-Drakhshan, MoNoorozi, K-Moradi Temperature Dependence of Polarizability in Sodium Potassium Tantalate Mixed Ceramic System Manish Uniyal, H. K. Semwal, S. C. Bhatt Farmer's perception of sustainable alternatives to the use of chemical fertilizers to enhance crop yield in Bauchi state Nigeria Gizaki L. J., Alege A. A., Iwuchukwu J. C.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

OPIOID Pharmacology : A Review Vivek Sharma*, Sunil Dutt, Rahul Kumar, Pankaj Sharma, Athar Javed, Rajender Guleria Department of Pharmacology, Government College of Pharmacy, Rohru, Distt. Shimla, Himachal Pradesh, India

ABSTRACT Pain is an unpleasant sensation that originates from ongoing or impending tissue damage. Management of different types of pain (acute, postoperative, inflammatory, neuropathic cancer) is challenging and yet the most frequent issue encountered by clinicians. Pharmacological therapy is the first line of approach for the treatment of pain and opioid drugs are prescribed for acute and chronic pain of moderate/severe intensity arising from malignant and nonmalignant diseases. The opium poppy was cultivated as early as 3400BC in Mesopotamia. The term opium refers to a mixture of alkaloids from the poppy seed. Opiates are naturally occurring alkaloids such as morphine or codeine and opioid is the term used broadly to describe all compounds that work at the opioid receptors. The physiologic modulation of noxious stimuli involves a highly complex system that integrates the actions of multiple opioid receptors and endogenous opioid peptides. Opioids produce their actions at a cellular level by activating opioid receptors. These receptors are distributed throughout the central nervous system (CNS) with high concentrations in the nuclei of tractus solitarius, peri-aqueductal grey area (PAG), cerebral cortex, thalamus and substantia gelatinosa (SG) of the spinal cord. They have also been found on peripheral afferent nerve terminals and many other organs. The efficacy of centrally applied opioids is well recognized, but when applied peripherally, for example in posttraumatic and inflammatory states, their actions are less reliable. Although they are associated with addiction, dependence, tolerance and abuse liability even then their place in pain management remains undebatable and unchallenged. Keywords: Endorphins, Morphine, Opioids, Pain

I. INTRODUCTION Pain transcends the boundaries of all medical specialties and impacts almost everyone at some stage of their life. Every second patient in most hospitals suffers from pain and every third patient complains of severe pain [1]. Since pain has a tremendous impact on the patient‟s physical and psychological well-being [2], inadequate pain therapy can greatly increase healthcare costs. The International Association for the Study of Pain has called unrelieved pain “a major global healthcare problem” [3]. Adequate pain therapy improves the patient's performance of daily activities, minimise sufferings, promote recovery and earlier discharge from hospital. Providing a rapid and effective pain relief without compromising the patient‟s general condition has remained a challenge for physicians till date. World

Health Organization (WHO) has designed a pain ladder (originally established for cancer pain) that has been used successfully in many diseases. According to this model, different classes of analgesic drugs are recommended based on the intensity of pain. At the first level, patients with mild pain (1-4 on a 10 point scale) are recommended to use non-opioids such as acetaminophen, non-steroidal anti-inflammatory agents or a cox-II inhibitor. At the second level, a weak opioid such as codeine and Tramadol (TRA) should be added for treatment of patients with moderate (5-6) pain. At the third level, the weak opioid is changed to a strong opioid such as morphine. This regimen clearly states that opoids are integral and indispensable part of pain management system. Severe inflammatory pain respond better to NSAIDs than an opioid while opioids are effective for nociceptive pain. Nociceptive pain commonly arise from tissue injury or inflammation, for example trauma, burns, infection, arthritis and ischemia.

IJSRST151514 |Received: 03 November 2015 |Accepted: 11 November 2015 | November-December-2015 [(1)5: 01-11]

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Neuropathic pain is less responsive to opioids and requires the use of adjuvant medications like tricyclic antidepressants and anticonvulsants (gabapentin). Neuropathic pain occurs after damage to peripheral and central nervous system. Diabetic neuralgia, post-herpetic neuralgia and post-traumatic neuralgia are some examples. The term opiate refers to compounds structurally related to products found in opium, a word derived from opos, the Greek word for "juice". Opiate is used to describe alkaloid molecules that include morphine and codeine. While the term opioid refers to compounds having functional properties like opiates; the opioid category includes not only the opiates but also semi-synthetic non-alkaloids and even endogenous peptides. The first undisputed reference to "poppy juice" is found in the writings of Theophrastus in the third century B.C. Opium is obtained from the unripe seed capsules of the poppy plant, Papaver somniferum. The milky juice is dried and powdered to make powdered opium, which contains a number of alkaloids. Opioids can be categorized into three subgroups; 1) naturally occurring compounds (termed opiates) such as morphine and codeine) chemically modified natural compounds (semisynthetic) such as hydrocodone, buprenorphine and oxycodone) and completely artificial compounds (synthetic) such as fentanyl, tramadol and ketobemidone. Some opioids act as agonists to all kind of opioid receptors (morphine) and some act as both agonist and antagonist (buprenorphine). Morphine (the prototypical MOP-r agonist) is the main active alkaloid in opium, whereas the baine can be used as a starting point for production of semisynthetic MOP-r(mu opioid receptor) ligands Opium has been used for thousands of years, and its clinical value cannot be overstated. Although mild to moderate pain is typically treated with acetaminophen or aspirin or other nonsteroidal anti-inflammatory drugs (NSAID), but the mainstay of pain management for severe pain remains the opiates. Their effects on pain are quite intriguing. Unlike local anesthetics that relieve pain by blocking all sensory transmission, opiates selectively modulate the perception of pain without interfering with basic senstions, such as light, touch, temperature, position sense and discrimination of sharp and dull. The opioids target the subjective component of

pain, an integrated sensation and it is common for a patient to remark after taking an opiate that “the pain is still there, but it does not hurt.”[4]. The initial pharmacologic studies of opiates focused on the general effects of morphine in humans[5] which was isolated from opium in 1805 [6] and first sold by Merck in 1827, with its popularity increasing with the developmentof the hypodermic needle in 1857. Its synthesis was delayed by its complex ring structure until 1956[7]. Opioids were first used for their actions on gastrointestinal motility, as they decrease propulsive peristaltic contractions, while increasing circular muscle tone and intraluminal pressure[8]. Morphine and its derivates are used today for the treatment of acute and chronic pain. It is now understood that morphine and other opioid drugs act on an endogenous opioidergic system, which is not only involved in setting pain (nociceptive) threshold and controlling nociceptive processing but also participates in modulation of gastrointestinal, endocrine and autonomic function, as well as a possible role in cognition [9]. The modern era of opioid research came with the demonstration of opioid receptors in 1973 [10,11] using binding assays based upon stereo selectivity [12]. Althogh opioids are effective pain-relieving drugs, however they are associated with side effects and fortunately most of these are reversible. The most frequently appearing side effects are nausea, vomiting, pruritus and constipation; these also happen to be the most bothersome. Respiratory depression is uncommon at standard analgesic doses, but can however be lifethreatening. Opioids produce analgesia by actions in the CNS. They activate pain-inhibitory neurons and directly inhibit pain-transmission neurons. The pharmacology of the opioids is quite similar. They differ mainly in potency, duration of action and optimal route of administration.

II. METHODS AND MATERIAL A. Opioid Receptors The opioids were among the earliest neuropeptides identified in the nervous system [13]. Opioid receptors are most abundant in the CNS [14], but have also been localized in many peripheral tissues of the mammalian organism [15] Opioid receptors are a group of G protein-

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coupled receptors (GPCR). Each receptor consists of an extracellular N-terminus, seven transmembrane helices, three extra- and intracellular loops, and an intracellular C-terminus characteristic of the GPCRs. The opioid receptor types are approximately 70% identical with differences located at N and C termini. The greatest diversity is found in their extracellular loops.

bind to μ receptor with lower affinity [17].Two subtypes of μ receptors have been proposed: μ 1 : Has higher affinity for morphine, mediates supraspinal analgesia and is selectively blocked by naloxone.

μ 2 : Has lower affinity for morphine, mediates spinal Three major type of opioid receptor have been identified, analgesia, respiratory depression and constipating action mu (μ), delta (δ) and kappa (κ). The G-protein coupled [18]. opiate receptor-like protein (ORL1 or NOP) was included to other members of the opioid receptor family, Mu (μ) (agonist morphine) Mu receptors are found based on its structural homology (48-49% identity) to primarily in the brainstem and medial thalamus. Mu the other opioid receptors. μ-opioid receptor was receptors are responsible for supraspinal analgesia, identified in binding assays in 1973 and was cloned respiratory depression, euphoria, sedation, decreased about 20 years later. Other opioid receptors have also gastrointestinal motility and physical dependence. Mu1 been proposed, such as zeta (δ) opioid receptor, which is related to analgesia, euphoria, and serenity, while has been shown to be a cellular growth factor modulator Mu2 is related to respiratory depression, pruritus, and epsilon (ε) opioid receptor. However, efforts to prolactin release, dependence, anorexia, and sedation. locate a gene for ε- receptor have been unsuccessful and These are also called OP3 or MOR (morphine opioid epsilon-mediated effects were absent in μ/δ/ κ. It has receptors) [19]. been suggested that μ-, δ- and κ- receptors have several subtypes, μ1-3, delta1-2 and κ- 1-3. It has also been Activation of the mu opioid receptor (mu is named for postulated that μ-1 receptors produce analgesia while μ- morphine) results in: inhibition of adenylyl cyclase, 2 mediates respiratory depression. The function of the μ- closure of voltage-gated calcium channels, opening of 3 receptor is unknown. The existence of opioid receptor potassium channels and membrane hyperpolarisation subtypes has not been confirmed in either cloning (Ben Snyder, 2014). These cellular events can inhibit studies or experiments with knock out animals. neuronal firing and neurotransmitter release. All of the opioid analgesics act as agonists at the μ receptor. Mu Physiological roles for each of the opioid receptors have activation inhibits the ascending pain pathway, which not been clearly defined. Pain relief effects are mediated includes neurons passing through the dorsal horn of the by all three receptor types, but in different degree. μ- spinal cord, brainstem, thalamus and cortex. Mu agonists Receptor mediates the most potentant nociceptive effects, also activate the inhibitory descending pain pathway, accompanied however by the development of which involves sites in the brainstem. Peripheral mu dependence. δ-Receptor has lower efficacy in mediating receptors located at the site of tissue injury and pain relief but also a reduced addictive potential. κ- inflammation may also mediate analgesia (Inturissi Receptor mediates analgesic effects in peripheral tissues CE2002).Mu receptor agonism is responsible for the [15]. The nociceptinopioid receptor (NOP receptor), is euphoria associated with opioids. This effect is distinct phylogenetically related to δreceptor, μ receptor, and κ from the pain pathways and depends on the mesolimbic receptor, it does not bind the same ligands [16]. dopaminergic system [20]. μ Receptor: The receptor is characterized by its high affinity for Morphine. It is the major receptor mediating action of morphine and its congeners. Endogenous ligands for μ receptor are Endomorphins-1 and Endomorphin-2, found in mammalian brain, produce biological effects ascribed to this receptor. Other opioid peptides like -endorphins, Enkephalins and Dynorphins

Kappa (k) Receptor: is defined by its high affinity for ketocyclazocine and Dynorphin A. Norbinaltorphimine is a selective -antagonist.Two subtypes of receptors K1 and K3 are functionally important. Analgesia caused by agonist is primarily spinal (K1) or supraspinal ( K3) [17]. Kappa receptors are found in the limbic and other diencephalic areas, brain stem, and spinal cord, and are responsible for spinal analgesia, sedation, dyspnea,

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dependence, dysphoria, and respiratory depression. These are also known as OP2 or KOR (kappa opioid receptors).

phosphorylation. The MAP-kinase pathways were initially discovered to be drivenby growth factors but were also found to be involved in cross-talk between GPCR and growthfactor signaling [21]. ERKs Delta (d) (agonist delta-alanine-delta-leucine-enkephalin) (extracellular signal-regulated kinases) one of the major Delta receptors are located largely in the brain and their MAPKs,plays a central role in regulation of cellular effects are not well studied. They may be responsible for processes as proliferation, differentiation and cell-cell psychomimetic and dysphoric effects. They are also communication [22]. called OP1 and DOR (delta opioid receptors). Opioids also modulate pain perception by acting throgh Sigma (s) (agonist N-allylnormetazocine) Sigma recep- AKT or protein kinase B (PKB) signaling pathway. The tors are responsible for psychomimetic effects, dys- best known effect of activated AKT is inhibition of phoria, and stress-induced depression. They are nolonger apoptosis, programmed cell death and activation of considered opioid receptors, but rather the target sites protein syntheses. AKT is activated via a protein kinase for phencyclidine (PCP) and its analogs [19]. called PI3-kinase (PI3K) that in turn is activated by the G βγ subunits of GPCR [23,24]. PI3K can also activate ERK. Opioid receptor signaling has been associated with B. Transduction Pathways both cell proliferation and cell death in various cells The signaling pathways of opioid receptors well expressing opioid receptors [25]. understood and characterized now. The conformation changes of receptor occur when ligand binds to the It has been suggested that binding of opioid ligands receptor that replaces GDP bound to G α-subunit by triggers the same signaling pathways as in neuronal cells, GTP. The activated Gα dissociates from trimeric G- in other words modulation of cAMP, Ca2+ channels and protein complex and inhibits the adenylyl cyclase and kinases.Stimulation of opioid receptors on leucocytes thereby inhibits the formation of cAMP, which modulates proliferation, chemotaxis and cytotoxicity of subsequently activates the ion channels in the membrane. leucocytes[26,27]. Ion channels can also be regulated by direct interaction with G βγ subunits. Activation of Ca2+ channel, Within the central nervous system, activation of MOP suppresses Ca2+ influx, and thereby attenuates the receptors in the midbrain is thought to be a major excitability of neurons and/or reduces neurotransmitter mechanism of opioid-induced analgesia. Here, MOP release such as substance P and calcitonin gene-related agonists act by indirectly stimulating descending peptide (CGRP) (pro-nociceptive and pro-inflammatory inhibitory pathways which act upon the periaqueductal neuropeptides). At the postsynaptic membrane, opioid grey(PAG) and nucleus reticularis paragigantocellularis receptors mediate hyperpolarization by opening G (NRPG) with the net effect of an activation of descendprotein-coupled K+ channels thereby preventing ing inhibitory neurons. This leads to greater neuronal neuronal excitation. traffic through the nucleus raphe magnus (NRM), Opioid receptors located on the presynaptic terminals of the nociceptive C-fibers and A delta fibers, when activated by an opioid agonist, will indirectly inhibit these voltage dependent calcium channels, decreasing cAMP levels and blocking the release of pain neurotransmitters such as glutamate, substance P and calcitonin gene-related peptide from the nociceptive fibers, resulting in analgesia [19]. Opiods also modulate protein kinases. The MAP kinases signaling system comprises a series of hierarchical kinases that transduce signals through successive

increasing stimulation of 5-hydroxytryptamine and enkephalin-containing neurons which connect directly with the substantia gelatinosa of the dorsal horn. This in turn results in a reduction of nociceptive transmission from the periphery to the thalamus. Exogenous and endogenous opioids can also exert a direct inhibitory effect upon the substantia gelatinosa (in the dorsal horn) and peripheral nociceptive afferent neurones, reducing nociceptive transmission from the periphery. This series of cellular events and mechanisms produces much of the analgesic effect commonly seen following the administration of MOP agonists [28].

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C. Endogenous Neurotransmitters Morphine and its alkaloid derivatives are used extensively in the treatment of pain [29]. These compounds are the most potent class of analgesics used clinically. The high potency and specificity of morphine suggest that it may bind to specific receptors in the nervous system to induce its biological effects. In the early 1970s, several groups of researchers identified specific opioid receptors in brain and peripheral tissues [30]. While these receptors were highly sensitive tomorphine, morphine is not endogenously expressed in the body and therefore could not be the endogenous ligand for these receptors.This led to the search for the endogenous neurotransmitters at the opiate receptors. The endogenous ligands for the opioid receptors are the enkephalins, endorphins and dynorphins, encoded by separate genes. These pentapeptides vary in their affinity for the opioid receptor, but none binds exclusively to one type. A new class of highly selective u selective endogenous peptide the endomorphines has recently been described. Endomorphin-1 and endomorphin-2 are tetrapeptides structurally unrelated to the other endogenous opioid peptides. Their distribution in the central nervous system mirrors that of the mu -opioid receptors and they display extremely high affinity and selectivity for the u receptor. Their affinity for receptor binding sites is more than 1000-fold greater than for delta or kappa receptors and they are thought to be the endog-enous ligands for the u receptor [31,32]. Both the enkephalins and dynorphins are neurotransmitters in the brain involved in pain perception, cognitive functions, affective behaviors and locomotion, and they are involved in the central control of certain endocrine functions such as water balance [33]. Both peptides are widely distributed in the central nervous system (CNS) but localized to discrete neuronal pathways [34]. Betaendorphin is expressed at much lower levels in the brain and only synthesized in a few neuronal pathways in the CNS, in particular in those originating from hypothalamic nuclei. As a result, the enkephalins and dynorphins are considered the predominant central opioid peptide transmitters. Endorphins: Endorphins are endogenous opioid polypeptide compounds. They are produced by the pituitary gland and the hypothalamus in vertebrates during strenuous exercise [Partin1983], excitement, pain

and orgasm and they resemble the opiates in their abilities to produce analgesia and a sense of well-being. Endorphins work as “natural pain relievers.” They can be found in more than twenty different parts in the body, such as the pituitary glands as well as in many parts of the brain and nervous system [35, 36]. The term "endorphin" implies a pharmacological activity as opposed to a specific chemical formulation. The term endorphin is a general name for many opioid-like proteins. (It consists of two parts: endo and orphin; these are short forms of the words endogenous metersorphine which means "a morphine-like substance which is produced by the human body") [37]. Types of Endorphins: Four types of endorphins are created in the human body. They are named alpha , beta, gamma and sigma endorphins[38].The four types have different numbers and types of amino acids in their molecules; they have between 16 and 31 amino acids in each molecule. More endorphins are released in the pituitary gland during times of pain or stress. Exercise increases the endorphin release too. For the same reason, exercise results in a better mood. Endorphins are the most powerful endogenous opioid peptide neurotransmitters and are found in the neurons of both the central and peripheral nervous system. They are present abundantly in the hypothalamus and pituitary gland. They are released when the body encounters any sort of stress or pain. During severe pain the endorphins in our body cause an analgesic effect to occur, to lessen the pain that is inflicting our body. But during stress, endorphins act differently. They are released in the limbic system which reduces the extent of anxiety that our body is feeling. Not only does the opiate cause the pain to decrease it also causes the feelings of euphoria to occur as well as the release of many sex hormones [Koltyn2000]. Endorphins act through opiate receptors. endorphinshave the highest affinity for the μ 1-opioid receptor, slightly lower affinity for the μ 2 and -opioid receptors and low affinity for the 1 opioid receptors. Enkephalins: Enkephalins are pentapeptides involved in regulating nociception in the body. Discovered in 1975, two forms of enkephalin were revealed, one containing leucine ("leu") and the other containing methionine ("met"). Both are products of the proenkephalin gene [39].

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Dynorphins Dynorphins are produced in many different parts of the brain, including hypothalamus, hippocampus, midbrain, medulla, pons and the spinal cord and has many different physiological actions, depending upon their site of production. For example, dynorphins that are made in magnocellular vasopressin neurons of the supraoptic nucleus are important in the patterning of electrical activity. Dynorphins produced in magnocellular oxytocin neurons cause negative feedback inhibition of oxytocin secretion. Dynorphin produced in the arcuate nucleus and in orexin neurons of the lateral hypothalamus affects the control of appetite. Dynorphins are stored in large (80-120 nm diameter) dense-core vesicles that are considerably larger than vesicles storing neurotransmitters. These large dense-core vesicles differ from small synaptic vesicles in that a more intense and prolonged stimulus is needed to cause the large vesicles to release their contents into the synaptic cleft. Densecore vesicle storage is characteristic of opioid peptides storage [40]. Dynorphins primarily exert their effects through the opioid receptor and act as modulators of pain response, maintain homeostasis through appetite control and circadian rhythm, weight control and regulation of body temperature [18]. Beta-endorphin and the enkephalins have relatively high affinity at mu and delta receptors and much lower at kappa. The dynorphins, by contrast, have relative selectivity for kappa receptors over the mu and delta. These receptors mediate a complex, partially overlapping array of physiologic and neurobio-logic functions [41]. Beta-endorphin is a product of proopiomelanocort in which is produced primarily in the anterior pituitary of humans. It is also produced in the central nervous system and in the periphery. The mu receptors mediate both the analgesic and rewarding effects of opioid compounds (be they heroin or prescription opioids) as well astheir effects on many systems in the body, such as in thehypothalamic–pituitary–adrenal (HPA) axis, immune, gas-trointestinal (GI), and pulmonary function.

D. OPIOID Receptor Ligands Two types of ligands at opioid receptors can be differentiated in view of their chemical structure: alkaloids and peptides. 1. Alkaloids The original opiates, morphine and codeine were isolated from opium. Their structures provided the scaffolds upon which many of the current mu opiates are based. Thebaine, another major component of opium, is a valuable precursor in the synthesis of many of these derivatives. Agonists. The first known opiate alkaloid was morphine, isolated from the poppy seeds in 1803 by Seturner. The structure of morphine was elucidated 120 years later [42], and its full systematic name is: 7, 8 – didehydro -4 , 5 – epoxy – 17 - methyl - ( 5α , 6α ) – morphinan - 3, 6 diol. Morphine and other opiates are widely used in clinical practice for blockade of most severe pain syndromes or for anesthetic purposes. Morphine is primarily an agonist ligand for the μ receptor. Its affinities for δ and κ receptors are sufficiently low that it is used as a selective μ receptor ligand in pharmacological studies [43]. Antagonists. Opioid antagonists most frequently used by pharmacologists are synthetic alkaloids such as naloxone and naltrexone [44]. Naloxone, which was the first pharmacologically pure antagonist identified, is considered to be a “universal”, non-selective opioid antagonist. The action of an agonist is characterized as opioid only if its effects are “naloxone-reversible” [45]. Although naloxone and its analog naltrexone bind to all three opioid receptors, they have the highest affinity for the μ receptor [46]. 2. Peptides Kosterlitz and Hughes were the first to sequence the pent peptide enkephalins[13] which soon expanded into the following three families of peptides, each with its own precursor peptide: preproenkephalin, preprodynorphin, and b- lipotropin [47]. The “typical” opioid peptides, including enkephalins, dynorphins and β-endorphin are derived from three precursor molecules; pro-enkephalin, pro-dynorphin and

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pro- opiomelanocortin, all of which are expressed in the CNS, but their presence in peripheral tissues has also been confirmed [48]. The “atypical” opioid peptides originate from the variety of precursor proteins and carry various amino acid sequences at their N-terminal regions, only the Nterminal Tyr residue is conserved [49]. The N-terminal tetrapeptide of most atypical opioid peptides represents the minimum sequence for full opioid activity.

barrier. The two main families of drug transporters of relevance to opioid pharmacokinetics are (i) the ATP binding cassette (ABC) efflux transporters [e.g. Pglycoprotein (P-gp)], which restrict the passage and (ii) the solute carrier (SLC) influx transporters which facilitate the passage [57,58]. Distribution

After being absorbed the opioids distribute throughout the body tissue i.e. the site of main action within the The first group of “atypical” opioid peptides, central nervous system (CNS). To reach the CNS identifiedby Brantl et al. [50] in 1979 were milk protein opioids have to cross the blood–brain barrier. Fentanyl, derived β-casomorphins (β-CM), which are obtained by morphine and methadone have been shown to be proteolytic fragmentation of β-casein. Aside from substrates for the P-gp efflux transporters [59,60]. The butorphanol and nalbuphine, all clinically available clinical aspects of fentanyl have been confirmed in a opioids are mu -opioid receptor preferring agents. The k single human study, where an increased respiratory -opioid agonists, butorphanol and nalbuphine, are depression was seen in patients with a decreased P-gp limited by partial agonist activity as well as central side expression. Oxycodone is not a substrate for the P-gp effects, primarily dysphoria, sedation, and hallucinations, efflux transporters, but it is substrate for the SCL influx and arelittle used in the treatment of chronic pain. transporters thus being actively transported into the Oxycodone has only recently been suggested to be a K - brain. Most of the research elucidating the transport of opioid preferring agonist [51] and has not been opioids across the blood–brain barrier has been done in systematically examined in the treatment of chronic pain. rodents and thus caution should be taken when Thus, although there is strong preclinical evidence for extrapolating the findings to humans. However, as for efficacy of k-opioidagonists in chronic pain treatment, the absorption, this may play a role in treatment current agents are inadequate, and novel agents are heterogeneity [58]. underexperimental study in humans [52]. Metabolism Pharmacokinetics of OPOIDS Absorption After absorption most opioids undergo first pass The majority of opioids i.e. morphine, oxycodone, metabolism in the liver and here there are major hydro-morphone, methadone, ketobemidone, tramadol, differences between classes of drugs as well as tapentadol, fentanyl, sufentanil, buprenorphine and individual differences in responses to the same opioid. codeine all show a high gastrointestinal permeability, The chemical class phenylpiperidines are metabolized and thus they are readily and completely absorbed from by CYP3A4. This enzyme has many genetic the gastrointestinal tract following oral administration. polymorphisms but until recently none has been shown However, the bioavailability of fentanyl, sufentanil and to be of major clinical relevance. Within the class 4,5buprenorphine is very low and highly variable since epoxymorphinans (which additionally are alkyl esters at these opioids are subjected to high hepatic first pass the 3-phenolic hydroxyl group i.e. codeine, hydrocodone metabolism [J53-55]. As a consequence they are not and oxycodone) drugs are subject to O-dealkylation, available in pharmaceutical formulations intended for catalyzed by CYP2D6 enzymes. Opioids of the 4,5oral administration. Recent research has revealed that epoxymorphinan class are also subject to N-dealkylation. low and variable bioavailability seen after oral This results in nor-derivatives, which bind to the m administration may partly be explained by the receptors, but show lower affinities than the parent substances being substrates for transporters present in compounds. The N-dealkylation is mainly catalyzed by the intestinal epithelium [56]. Drug transporters are CYP3A4[58]. present all over the body in the gastrointestinal tract, in the kidneys, in hepatocytes and at the blood–brain

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Excretion The vast majority of opioids are excreted as metabolites though the kidneys. Thus for substances transformed to pharmacologically active metabolites, decreased kidney function may influence the overall clinical effect due to accumulation of the metabolites and this may explain differences in effects and side effects between opioids. The best described examples of clinically relevant active metabolites are morphine-6-glucuronide and morphine3-glucuronide. As stated above the 6-glucuronide is thought to be an active analgesic like the parent compound, morphine. Although the potency ratio to morphine still remains to be established it plausible that in steady-state conditions and in patients with impaired kidney function it contributes more to analgesia. Results from some studies have suggested the 3-glucuronide possess anti-analgesic and excitatory effects. However results from other studies have failed to prove that. Thus clinical relevance of accumulation of this metabolite in patients with impaired kidney function still remains controversial [61].

III. RESULT AND DISCUSSION PHARMACOLOGICAL ACTIONS OF OPIOID AGONISTS Central Nervous System Analgesia: Most effective in relieving dull, continuous and poorly localised pain arising from deeper structures, for example the gut. Less effective against superficial and sharp pain. Neuropathic pain can be very resistant, but patients may report that pain is still present, but the intensity is decreased and it no longer bothers them as much. Sedation: Drowsiness, feeling of heaviness and difficulty in concentrating are common. Sleep may occur with relief of pain, although they are not true hypnotics. Euphoria and dysphoria: Morphine and other opioids cause a sense of contentment and well-being (euphoria). If there is no pain, morphine may cause restlessness and agitation (dysphoria). Hallucination: These are more common with KOP agonists, but morphine and other MOP agonists may also cause hallucinations.

Tolerance and Dependence: Tolerance is the decrease in effect seen despite maintaining a given concentration of a drug. The mechanism is not fully understood but could involve down regulation of opioid receptors or decreased production of endogenous opioids. Dependence exists when the sudden withdrawnof an opioid, after repeated use over a prolonged period, results in various physical and psychological signs. These include; restlessness, irritability, increased salivation, lacrimation and sweating, muscle cramps, vomiting and diarrhoea. Cardiovascular System: Mild bradycardia is common as a result of decreased sympathetic drive and a direct effect on the sino-atrial (SA) node. Peripheral vasodilatation caused by histamine release and reduced sympathetic drive may result in a slight fall in blood pressure that may be significant in hypovolaemic patients. Respiratory System: Respiratory depression is mediated via MOP receptors at the respiratory centres in the brainstem. Respiratory rate falls more than the tidal volume and the sensitivity of the brain stem to carbon dioxide is reduced. Its response to hypoxia is less affected but if hypoxic stimulus is removed by supplemental oxygen then respiratory depression may be augmented. Concurrent use of other CNS depressants, for example benzodiazepines or halogenated anaesthetic, may cause marked respiratory depression. Opioids suppress cough. Codeine suppresses cough to a degree similar to morphine but has lesser analgesic activity. Morphine and diamorphine are used in paroxysmal nocturnal dyspnoea, as they produce sedation, reduce preload and depresses abnormal respiratory drive. Gastrointestinal System : Stimulation of the chemoreceptor trigger zone causes nausea and vomiting. Smooth muscle tone is increased but motility is decreased resulting in delayed absorption, increased pressure in the biliary system (spasm of sphincter of Oddi) and constipation. Endocrine System: The release of ACTH, prolactin and gonadotrophic hormone is inhibited. Secretion of ADH is increased. Ocular effects: MOP and KOP receptors in EdingerWestphal nucleus of occulomotor nerve are stimulated

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by opioids resulting in constriction of the pupils (meiosis). Histamine release and itching Some opioids cause histamine release from mast cells resulting in urticaria, itching, bronchospasm and hypotension. Itching occurs most often after intrathecal opioids Muscle rigidity Large doses of opioids may occasionally produce generalised muscle rigidity especially of thoracic wall and interfere with ventilation. Immunity: The immune system is depressed after longterm opioid abuse Effects on Pregnancy and Neonates All opioids cross the placenta and if given during labour, can cause neonatal respiratory depression. Chronic use by the mother may cause physical dependence in utero and lead to a withdrawal reaction in the neonate at birth that can be life threatening. There are no known teratogenic effects [62].

IV. CONCLUSION Opioid agonists inhibit adenylyl cyclase (decreasing cyclic AMP production), close N-type voltage-operated calcium channels, and open calcium-dependent inwardly rectifying potassium channels. This results in hyperpolarization and a reduction in neuronal excitability. Changesin intracellular Ca2+ influence the release of neuro-transmitters and modulate the activity of protein ki-nases. Opiates are one of the most valuable drugs in medicine. Their ability to alleviate pain and suffering led Thomas Sydenham, an English doctor in the nineteenth century to call them „God‟s own medicine‟. Their use to allevaiate pain dates back thousands of years. Despite their medical effectiveness they are in news for wrong reasons too that include use of these drugs on the street and the potential for addiction that has led to an „opiophobia‟ in clinical medicine. Thus their place althogh is prerequisite, and undebatable yet their precationary use is highly recommended.

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[3] Goldberg DS and McGee SJ. Pain as a global public health priority. BMC Public Health2011;11: 770. [4] Gavril W P and Ying-Xian Pan. Mu Opioids and Their Receptors: Evolution of a Concept. Pharmacol Rev.2013;65:1257–1317. [5] Martin WR.Opioid antagonists. Pharmacol Rev.1967;19:463–521. [6] Macht DI. The history of opium and some its preparations and alkaloids.JAMA.1915;477–481. [7] Gates M and Tschudi G. The synthesis of morphine. J Am Chem Soc.1956;78: 1380–1393. [8] Reisine T and Pasternak GW. Opioid analgesics and antagonists, in Goodman& Gilman‟s: The Pharmacological Basis of Therapeutics (Hardman JG and LimbirdLE, eds, ed).1996;521–556, McGraw-Hill, New York. [9] McDonald J, Lambert DG. Opioid receptors; Continuing Education in Anaesthesia, Critical Care & Pain.2005;5(1):22-25 [10] Pert A and Yaksh TL. Sites of morphine induced analgesia in the primatebrain: relation to pain pathways. Brain Res.1974; 80:135–140. [11] Simon EJ, Hiller JM, and Edelman I. Stereospecific binding of the potentnarcotic analgesic ( 3 H) Etorphine to rat-brain homogenate. Proc Natl Acad SciUSA.1973;70:1947–1949. [12] Goldstein A, Lowney LI and Pal BK. Stereospecific and nonspecific inter-actions of the morphine congener levorphanol in subcellular fractions of mousebrain. Proc Natl Acad Sci USA.1971; 68:1742–1747 [13] Hughes J, Smith TW, Kosterlitz HW et al. Identification of Two RelatedPentapeptides from the Brain with Potent Opiate Agonist Activity.Nature. 1975 ; 258:577-580. [14] Mansour A, Watson SJ. In Handbook of ExperimentalPharmacology 104/1; Herz, A.; Akil, H.; Simon, E.J.; Eds.;Springer: Berlin, 1993;79105. [15] Anna Janecka, Jakub Fichna and Tomasz Janecki. Opioid Receptors and their Ligands. Current Topics in Medicinal Chemistry. 2004; 4: 1-17 [16] Shang Y, Filizola M. Opioid receptors: Structural and mechanistic insights into pharmacology and signaling. Eur J Pharmacol. (2015), http://dx.doi.org/10.1016/j.ejphar.2015.05.012i

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[17] Tripathi KD. Opioid Analgesics andAntagonists. In Essentials of Medical Pharmacology, 6 th Edition, Jaypee Brothers.2008; 462-464. [18] Koneru A, Sreemantula Satyanarayana and Shaik Rizwan; Endogenous Opioids: Their Physiological Role and Receptors;Global Journal of Pharmacology.2009.3 (3): 149-153. [19] Trescot AM, Sukdeb D, Marion Lee and Hans Hansen. Opioid Pharmacology. Pain Physician. 2008;11: 133-153. [20] Snyder B. Revisiting old friends: update on opioid pharmacology.Aust Prescr. 2014;37:56–60. [21] Miyatake M et al., Inhibition of EGF-induced ERK/MAP kinase-mediated astrocyte proliferation by mu opioids: integration of G protein and betaarrestin 2-dependent pathways. J Neurochem. 2009; 110(2):662-74. [22] Raman M, Chen W and Cobb MH. Differential regulation and properties of MAPKs. Oncogene. 2007;26(22):3100-12. [23] Schwindinger WF et al. Synergistic roles for Gprotein gamma3 and gamma7 subtypes in seizure susceptibility as revealed in double knock-out mice. J Biol Chem. 2012; 287(10):7121-33. [24] Murga C et al. Activation of Akt/protein kinase B by G protein-coupled receptors. Arole for alpha and beta gamma subunits of heterotrimeric G proteins acting through phosphatidylinositol-3-OH kinasegamma. J Biol Chem. 1998;273(30):190805. [25] Tegeder I and Geisslinger G.Opioids as modulators of cell death and survival--unraveling mechanisms and revealing new indications. Pharmacol Rev. 2004;56(3):351-69. [26] Sharp BM. Multiple opioid receptors on immune cells modulate intracellular signaling. Brain Behav Immun. 2006; 20(1):9-14. [27] Sacerdote P E et al. Experimental evidence for immunomodulatory effects of opioids. Adv Exp Med Biol. 2003; 521: 106-16. [28] Pathan H and Williams J. Basic opioid pharmacology: an update; British Journal of Pain. 2012; 6(1):11-16. [29] Gilman A, Rall J, Nies A and Taylor P., eds. The Pharmacological Basis of Therapeutics. New York: Pergamon Press, 1990. [30] Pert C and Snyder SH. Opiate receptor: Demonstration in nervous tissue. Science. 1973;179:1011-1014.

[31] Stone LS, Fairbanks CA, Laughlin TM et al. Spinal analgesicactions of the new endogenous opioid peptides endomorphin-1 and -2. Neuroreport 1997;8:3131–5. [32] Goldberg IE Rossi GC, Letchworth SR, et al. Pharmacologicalcharacterization of endomorphin-1 andendomorphin-2 in mouse brain. J Pharmacol Exp Ther. 1998;286:1007–13. [33] Simon E. Opioid receptors and endogenous opioid peptides. Med Res Rev.1991;11:357-374. [34] Khachaturian H, Lewis M and Watson SJ. Enkephalin systems indiencephalon and brainstem ofrat. J Comp Neurol.1983; 220:310-320. [35] Chapman CL and JM De Castro. Running addiction: measurement and associatedpsychological characteristics. Journal of Sports Medicine and Physical Fitness.1990; 30: 283-290. [36] Sprenger T A, BertheleS, Platzer H, Boecker and Tolle TR. What to learn from in vivo opioidergic brain imaging? European Journal of Pain.2005; 9: 117-121 [37] Przew ocki R. Some aspects of physiology andpharmacology of endogenous opioid peptides. Polish J. Pharmacol. Pharmacy.1984; 36(2-3): 13758. [38] Dalayeun JF, Norès JM and Bergal S. Physiology of beta-endorphins. A close-up view and a review of the literature. Biomed Pharmacotherapeutics. 1993; 47(8): 311-20. [39] Comb M, Seeburg PH et al. Primary structure of the human Met-and Leu-enkephalin precursor and its mRNA.Nature.1982; 295: 663-666. [40] Day R C, Lazure A, Basak A et al.Prodynorphin processing by proprotein convertase2. Cleavage at single basic residues and enhanced processing in the presence of carboxypeptidase activity. J. Biol. Chem.1998;273(2): 829-36. [41] Gutstein H, Akil H. Opioid analgesics. In: Brunton L, Lazo L, ParkerK, eds. Goodman & Gilman‟s the pharmacological basis of therapeutics,11th ed. New York, NY: McGraw-Hill, 2005:547–590. [42] Gulland JM, Robinson R. The Morphine Group. Part I. ADiscussion of the Constitutional Problem. J. Chem. Soc. 1923;123: 980-998. [43] Takemori AE, Portoghese PS. Evidence for the Interaction ofMorphine with Kappa and Delta Opioid Receptors to InduceAnalgesia in Beta-

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funaltrexamine-treated Mice. J. Pharmacol. Exp. Ther. 1987; 243: 91-94. Blumberg H, Dayton HB. Naloxone, Naltrexone, and RelatedNoroxymorphones. Adv. Biochem. Psychopharmacol. 1973;8:33- 43. Leslie FM. Methods Used for the Study of Opioid Receptors. Pharmacol. Rev. 1987;39:197-249. Magnan J, PatersonSJ et al. TheBinding Spectrum of Narcotic Analgesic Drugs with Different Agonist and Antagonist Properties. Naunyn. Schmiedebergs. Arch. Pharmacol. 1982:319:197205. Berezniuk I and Fricker LD. Endogenous opioids, in The Opiate Receptors(Pasternak GW, ed, ed).2011;93–120, Springer, New York. Hoellt V. Multiple Endogenous Opioid Peptides. Trends in Neuroscience. 1983;6; 24-26. Teschemacher H. In Handbook of experimentalPharmacology 104/1; Herz, A.; Akil, H.; Simon, E.J.; Eds., Springer, Berlin.1993; 499528. Brantl V, Teschemacher H et al. NovelOpioid Peptides Derived From Casein (betaCasomorphins). I.Isolation from Bovine Casein Peptone. Hoppe-Seyler‟s Z. Physiol. Chem. 1979;360;1211-1216. Ross FB and Smith MT. The intrinsic antinociceptive effects of oxycodone appear to be k -opioid receptor mediated. Pain.1997;73:151–157. Thomas JM and James CE. Parmacology of Opioid and Nonopioid Analgesics in Chronic Pain States ; JPET.2001; 299:811–817. Joshi GP. Sufentanil for chronic pain management. FutNeurol.2010; 5: 791–6. Strain EC, Walsh SL, Preston KL, Liebson IA, Bigelow GE. The effects of buprenorphine in buprenorphine-maintainedvolunteers. Psychopharmacology (Berl). 1997; 129: 329–38. Poklis A. Fentanyl: a review for clinical and analytical toxicologists. J Toxicol Clin Toxicol. 1995; 33: 439–47. Kharasch ED, Hoffer C, Altuntas TG, Whittington D.Quinidine as a probe for the role of pglycoprotein in theintestinal absorption and clinical effects of fentanyl. J Clin Pharmacol. 2004; 44: 224–33. Somogyi AA, Barratt DT, Coller JK. Pharmacogenetics ofopioids. Clin Pharmacol Ther 2007; 81: 429–44.

[58] Asbjørn MD, Rasmus DJ et al. Differences between opioi s:pharmacological,experimental, clinical and economical perspectives. British Journal of ClinicalPharmacology. 2012;75:1:60– 78. [59] Wandel C, Kim R, Wood M, Wood A. Interaction ofmorphine, fentanyl, sufentanil, alfentanil, and loperamide with the efflux drug transporter Pglycoprotein. Anesthesiology. 2002; 96: 913–20. [60] Rodriguez M, Ortega I, Soengas I, Suarez E, Lukas JC,Calvo R. Effect of P-glycoprotein inhibition on methadoneanalgesia and brain distribution in the rat. J Pharm Pharmacol. 2004; 56: 367–74. [61] Osborne R, Joel S, Grebenik K, Trew D, Slevin M. Thepharmacokinetics of morphine and morphine glucuronides in kidney failure. Clin Pharmacol Ther 1993; 54: 158–67. [62] Dr mahesh trivedi, dr shafee shaikh, dr carl gwinnutt. Pharmacology of opioids – part 1anaesthesia tutorial of the week 64;atotw 64 pharmacology of opioids -part 1 12/08/2007;1-7

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

A Review paper on Viral Mobile Communications System Dr. Deepak Singh Yadav*, Rajesh Kumar Pandey Department of Computer Science & Engineering, Sachdeva Institute of Technology, Mathura, Uttar Pradesh, India ABSTRACT In this paper a research has been done to overview the viral mobile communication technology. In the modern era the GSM technology is obsolete and a new concept of viral mobile communication in the form of 3G as well as 4G CDMA in spite of GSM for the point-to-point information transportation when the network is stabilised through the research and analysis in the field of viral mobile communication. Due to this research and analysis a new perception with new conception for a new model of the viral mobile technology will be formed. Keywords: Cross Entropy, Hard handover, Soft Handover, Viral Mobile Communication.

I. INTRODUCTION Along with the development of 3G and 4G mobile communication system, neither TD-SCDMA (Time Division Synchronous code division multiple access) nor WCDMA (Wide Band Code Division Multiple access) and CDMA2000 (is also known as multi-carrier code division multiple access) can satisfy the mobile service provider and mobile subscriber (MS) with their performance [1,2], which will make new standard and technology develop constantly, supporting the system performance more mature and perfect [3]. The theory of viral mobile communication (VMC) will apply itself to solve the problem of point-to-point information transportation of MS in network [4,5,6], trying to make the MS get rid of the participation and support of the upper equipments, more making vast MS achieving point-to-point information transportation and switch[7,8]. This study introduces the viral communication theory into mobile communication system of 3G and 4G and analyses the corresponding performance. This new technique explores the enabling principles wireless communicators and will demonstrate their fundamental ability to scale and automatically configure themselves through a diverse set of applications including live voice, secure transmission, low power/ high-availability signaling, and sensors with a sense of place.

This paper is divided into eight parts. Starting with introduction (Section-I), next section covers the conception of viral mobile communication (Section-II). Moving ahead, viral architecture requirement is discussed (Section-III). After that design principles of viral architecture are discussed (Section-IV), the model of viral mobile communication are discussed (SectionV), the process of MSA soft handover communication are discussed (Section-VI), link capacity equation of the viral mobile communication network are discussed (Section - VII). Finally, conclusions summarize the last section (Section-VIII).

II. METHODS AND MATERIAL A. The Conception of Viral Mobile Communication The definition of viral mobile communication (VMC) is to apply the theory of viral communication to 3G and 4G mobile communication system without direct support of upper equipment, devoting itself to realize point-to-point information transportation and switch of MS. Its characteristics are shown below: a. b. c. d.

Mutual independency Scalability Share resources Rapid reproduction

IJSRST15152 | Received: 30 October 2015 |Accepted: 11 November 2015 | November-December-2015 [(1)5: 12-16]

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New technologies allow us to make wired and wireless devices that are ad hoc, incrementally installed and populous almost without limit. They need no backbone or infrastructure in order to work as an alternative, they use neighbours to bootstrap both bit delivery and geo location. This re-distributes privileges of communications from a vertically integrated provider to the end-user or end-device and segregates bit delivery from services. Communications can become something you do rather than something you acquire. This is very important issue in economic and social cases that include telephony, media distribution, safety and rising markets.

systems are fairly scalable, many are not viral, because they require a critical mass of adoption before any benefit is achieved [9].

The key idea is communications devices that work with no central backbone and scale almost without bound. They are based on reinterpreting the basic principles of wireless in the glow of efficiently viable digital radios that can expand spectrum capacity even as they use it. This obvious challenge is resolved by real-time RF processing that collaboratively distributes signals and reduces the power required at each node. As with the PC, this fundamental shift in architecture, moves communications intelligence from the core of a network to the ends, and builds upon a viral architecture that enables infinite growth and very much reduced costs of improvement.

Ad hoc network is a decentralized type of wireless network. The network is said to be ad hoc because it does not really pre-existing infrastructure. Scalability of a network is defined as the capability of a process, to handle growing amounts of work in a graceful manner or its ability to be distended to accommodate that growth.

Our study boundary entails conception of infrastructure free, scalable networks that preserve operating power, interoperate with existing systems, adapt to new radio techniques as they appear, and minimize the cost of functional evolution. This is practicable in the near term. We will demonstrate it through sample applications in domains as diverse as sensor nets and personal telephony. Viral communication architecture is one where elements are independent, scalable and where each new element adds capacity to the system, so that it can be adopted incrementally from a small base and gains accelerating value with scale. B. Viral Architecture Requirements We use the term viral architecture to mean a system that is adopted “virally”. Viral adoption refers to a system architecture that can be adopted incrementally, and gains momentum as it scales. The growth behaviour of such a system can be called viral growth. Although many

Figure 1: Basic architecture of viral system

For example, it can refer to the capability of a system to increase total throughput under an increased load when resources (typically hardware) are added. Each new element of a viral architecture must not reduce the capabilities of those that were there before to gain momentum, each new element must create more value from connecting into the system than from operating alone (Fig.1). That is, each adoption is a “win-win” decision the existing elements gain a little more benefit from the new element, and each new element has a stronger value proposition for joining the system. Momentum results from this process, because a reluctant adopter will eventually be attracted to adopt when the scale reaches his cost/benefit trade-off even when the architecture still has small reach. C. Design Principles of Viral Architecture There are two primary design principles that lead to a viral architecture scalability and independence [10]. The first states that viral systems have to be able to grow almost without bound, and the second requires that its elements operate autonomously, without connection to a central authority. In fundamental nature, one should be able to freely add elements and they should work without connection to a backbone. This works for

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automobiles as long as there are sufficient infrastructures, and we will show that it can work for communications and that the roadways are fundamentally infinite.

existing ones. A communications device should work indefinitely no matter what other communicators enter the environment and no matter how the underlying communications technology evolves.

 Scalability

 Independence

From the point of view of a single handed radio receiver, capacity in bits per second is limited primarily by bandwidth of signals coming into its antenna. Signals whose frequencies overlap cannot be easily distinguished, hence the notion of interference. When the bulk of information services were broadcast services and radios where expensive, this view of spectrum made intelligence.

The second criterion for a viral system is independence of operation. While this is almost understood by impression of the manner by which they scale, it is a requirement for decentralized growth. It is dictated by the applications we require independence in order to extend communications to cases for which an account or registration process simply does not apply. But more important, “de-centrality” includes a range of autonomous, distributed devices as diverse as remote However, from the perspective of electromagnetic controls for home entertainment equipment, portable and propagation in space, information capacity is unlimited. wearable health monitoring equipment, things placed in The limit is defined by the processes of detection, not the physical world such as security cameras, burglar the space itself. The technology of the receivers and the alarms, environmental sensors, thermostats, and computational architecture of the radio system, not the consumer equipment such as digital cameras, personal physics of the space, are the limits to communications recorders, and so onward. It is unreasonable to expect capacity. There are a number of methods in common use that a radio-operated TV remote control would require that prove this point. Space division multiplexing, for an account with the local cellular operator or that one example, as used in microwave and satellite links, re- would need permission to download the photo from a uses the spectrum by restricting either the direction of digital camera. Independence results from the use of a emission or requiring directivity in the receiving antenna. collaborative scheme for spectrum use. The principle is License is granted to a place, not a merely a band. The that each participant in a communication has the full fundamental nature of scalable wireless networks is capability of the network. Routing, relaying, and signal cooperation, a generalization of the phased array. regeneration are alive in each device. Sheppard’s packet repeater network design works because each node forwards packets of information on The notion is not radical and is implicit in ad-hoc behalf of each other node. Since the power needed to networks. There, the general definition is that each node reach an adjacent node is reduced by a factor equal or is a router. We likewise include routing in the devices, greater to the square of the distance, the total amount of but we extend that notion to the radio layer itself and use energy used to carry a bit from source to destination is the RF signal itself as a routing control parameter. reduced. And since the energy radiates over a narrower Rather than complicate the design, this allows viral region, the total amount of information that can be elements to literally sneak a signal around corners or simultaneously travelling in the network increases as the through gaps in the local spectral flux. nodes in the network get denser. In effect, each node is a “tower” for all of the nodes that are nearby the “cells” D. The Model of Viral Mobile Communication are defined by who wishes to communicate with whom rather than the topography or zoning requirements of the There are two kinds of call process of MS in CDMA place. mobile communication system: one is hard handover that MS only communicate with one base Secondary concerns are that a viral system be future station(BS),which means the connection of MS and BS proof and adaptable. In automobiles, the presence of is broken off firstly and connected successively. The call either new cars or new routes does not obsolesce process is shown in figure 2(MSC is the mobile switch

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center) ; the other is soft handover that the MS communicate with two or more BSs, which means the connection of MS and BSs is connected firstly and broken off successively. The call process is shown in figure 3; the corresponding zone of two segments of arc is soft handover zone. Reason of handover failure will be minimize if we consider viral mobile communication network the process of information transportation among the MSs is shown in fig 4, In the general communication processes shown in fig 2 and fig 3, MSs carry through corresponding call under certain condition viral mobile communication is needed; the algorithm of the information transportation process is given below [11].

2.

Define BSi and MSi, where i=1, 2, 3, 4;

3. The information transportation between MS1 and MS3 can be completed by MS2 indirectly or can be completed by MS4 indirectly. 4. MS1 may choose not to transport the information to corresponding BS1. 5. MS3 may choose not to transport the information to corresponding BS3. 6. Return to general communication process after the VMC finishes. E. The Process of Msa Soft Handover Communication • • • •

Soft handover is that the MSB and MSC connect to their corresponding BS1 and BS2 separately. Construct corresponding forward and backward link. Soft handover is the MSA connects to BS1 and BS2 together. The soft handover communication link of MSA and MSB shows in this figure based on above assumption.

Figure 2: Hard handover call process

Figure 5: Soft handover call process (MSA) F.

Link Capacity Equation of the Viral Mobile Communication Network

Figure 3: Soft handover call process 1.

Assume that Base Station (BS) is microcell.

The viral mobile communications system is controlled under ideal power; the reverse link equation in every cell can be written as:

W Eb Rbi  Ns 1 I  No  j 0 X j  S  S



Where

Figure 4: Viral Communication Process

N

i 1

Eb is the energy per bit, No is the noise spectral density, W is the CDMA bandwidth, Rbi is the service bit rate, N is the number of services,

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Ns is the users/cell, I is the total interference, S is the desired signal power, ƞ is the background noise, xj is the voice activity factor, In addition assume that the signal-to-noise threshold received by BS is q, q 

S



.

In the viral communication network for each cell, defining the parameter of viral mobile communication network, then the link capacity equation can be resulted from formula.

 iN1

W Rbi

 Eb   vmc  I  N o   ( N svmc  1) X j   S S N svmc  Psho N s Pvmc • In above formula, Psho is the soft handover probability of MS in microcell. • Pvmc is the probability of viral mobile communication for MS in microcell during soft handover.

III. CONCLUSION Finally, I am concluding through deep thinking as this is an under developing technology and hence there is a vast field of expansion in the field of wireless communication. Due to this technology the fundamental ability to scale and auto configuration in life voice, secure transmission, low power / high- availability signaling etc. will be possible. The communication is a very giant field and yet a great exploration is to be done and this viral mobile communicate technology will enable the principle of wireless communication which the world has to see in future and these new principles will apply to the broad band 3G and 4G mobile communication for the betterment and comfort of humanity by point-to-point information system.

IV. REFERENCES [1]

Chang Soon Kang, Ho-Shin Cho, Dan Keun Sung, “Capacity Analysis of Spectrally Overlaid Macro/Microcellular CDMA Systems Supporting Multiple Types of Traffic”, IEEE Transactions on Vehicular Technology,Vol.52, pp.333-346,March2003. [2] Zhiqiang Zhu, Junqiang Guo, Jiang Hui, “Performance Analysis of Soft Handover Based on Link Balance in Broadband CDMA Systems”,Computer Engineering and Applications, Vol.43, pp.146-148, Aug. 2007. [3] Zhu Zhiqiang, Xu Guangyin, Guo Junqiang, “Soft Handover Algorithm Analysis of Overlaid Cellular in CDMA System Based on Speed and Direction”, Proceedings of the First International Conference on Complex Systems and Applications, pp.753-756, June 2006. [4] AndyLippman,“ViralCommunications”,http://dl.media.mit. edu/viral/viral. Pdf, 2003. [5] Aggelos Bletsas, Andrew Lippman, “Efficient Collaborative (Viral) Communication in OFDM Based LANs” http://web.media.mit.edu/~aggelos/papers/bletsas_isart03.p df,2003. [6] Aggelos Bletsas, ”Low Complexity Virtual Antenna Arrays Using Cooperative Relay Selection”,IWCMC’06, pp.461— 466 ,July 2006. [7] Aggelos Bletsas, Ashish Khisti, Moe Z. Win. Opportunistic Cooperative Diversity with Feedback and Cheap Radios. IEEE Transactions on Wireless Communications, Vol.7, pp.1823—1827, May 2008. [8] Aggelos Bletsas, Hyundong Shin, M.Z.Win, “Cooperative Communications With Outage-Optimal Opportunistic Relaying”, IEEE Transactions on Wireless Communications, Vol.6, pp.1-11, Sep. 2007. [9] Andy Lippman, “Viral Communications”, dl.media.mit.edu viral. pdf , 2003. [10] Andrew Lippman David P.Reed, “Viral Communications” Media Laboratory Research, Draft May 19th, 2003. [11] Zhiqiang Zhu, Guangyin Xu, Lin Xu, Junqiang Guo, “Performance Analysis of Viral CDMA Mobile Communication Based on Cross Entropy” IEEE- 978-14244-3693-4/09, 2009.

Bibliographies Rajesh Kumar Pandey was born at Raebareli (U.P.), in India. He received the B. Tech degree in Computer Science & Engineering in 2010 from Feroze Gandhi Institute of Engineering & Technology, Raebareli (U.P.), India. Presently, he is an M.Tech student in Computer Science & Engineering from Sachdeva Institute of Technology, Mathura (U.P.), India.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Perfectly g*b-Continuous Functions S. Bharathi Department of Mathematics, Bharathiar University PG Extension Centre, Erode, TamilNadu, India

ABSTRACT The purpose of this paper is to introduce new classes of functions of g*b-irresolute function, strongly g*bcontinuous functions and perfectly g*b-continuous function in topological spaces. Some of their properties and several characterizations of these types of functions are discussed. Also we investigate the relationship between these classes of functions. Keywords: b closed sets, strongly continuous functions, g-continuous functions, b irresolute functions.

I. INTRODUCTION Several authors working in the field of general topology have shown more interest in studying the properties of generalizations of continuous and closed functions. Some of them are Arokiarani et al [1,3,4], Devi et al [5,6], Mashour et al [7]. Noiri [9] introduced strong forms of g-irresolute functions and studied their properties.. Iyappan and Nagaveni [10] introduced sgbcontinuous functions and semi generalized b-continuous maps. Recently R S Wali et al [11] introduced and studied the properties of αrω-continuous and αrωirresolute functions in topological spaces. The concept of regular continuous and Completely–continuous functions was first introduced by Arya. S. P. and Gupta.R [2]. In 1981, Munshy and Bassan [8] introduced the notion of generalized continuous (briefly g-continuous) functions which are called in as girresolute functions.

II. METHODS AND MATERIAL 2. Preliminaries We recall the following definitions which are useful in the sequel Definition 2.1 A function f : (X,τ) →(Y,) is called

(iii). perfectly g-continuous if the inverse image of every g-open set in (Y,) is both open and closed in (X,). (iv). glc-continuous if f -1 (V ) is glc-closed in (X,) for every V(Y,) (v).

irresolute if f -1 (V ) is semi-open in (X,) for each semi-open set V of (Y,),

(vi). gc- irresolute if f -1 (V ) is g-closed in (X,) for each g-closed set V of (Y,), (vii). αg- irresolute if f -1 (V ) is αg-closed in (X,) for each g-closed set V of (Y,), (viii). gs-irrresolute if f -1 (V ) is gs-closed in (X,) for each gs-closed set V of (Y,), (ix). gα-irresolute in (X,) if and only if g-irresolute in (X,α) . 3. g*b IRRESOLUTE FUNCTIONS Definition 3.2 A function f : ( X , )  (Y ,  ) is called g* b-irresolute (g*b-irresolute) if the inverse image of every g*b-closed set V of (Y,) is g*b-closed in (X,). Remark 3.3 The following examples shows that the notion of gc-irresolute functions and g*b closed irresolute functions are independent. Example 3.4 (i)Let , X  Y  {a, b, c}

Strongly continuous if f -1 (V ) is both open and

  {X ,,{a},{b},{a, b}} and   {X ,,{a},{b, c}}

closed in (X,) for each subset V of (Y,). (ii). strongly g-continuous if the inverse image of every g-open set in (Y,) is open in (X,).

Then the identity function on X is g*b-irresolute but not gc-irresolute. Example 3.5 Let , X  Y  {a, b, c}

(i).

  {X ,,{a},{b, c}} and   {X ,,{a},{b},{a, b}} .

IJSRST151411 | Received: 06 October 2015 | Accepted: 13 November 2015 | November-December-2015 [(1)5: 17-20]

17

Then the function f : ( X , )  (Y ,  ) defined by

f (a)  b , f (b)  a , f (c)  c is gc-irresolute but not

Theorem 3.12 Let (X,τ) be any topological space, (Y,  ) be a Tg*b-space and f : ( X , )  (Y ,  ) be a function.

g*b-irresolute.

Then the following are equivalent (i) f is g*b-irresolute

Remark 3.6 The irresolute functions and g*b-irresolute functions are independent and can be seen from the following example. Example 3.7 Let , X  Y  {a, b, c}

(ii)

f is g*b-continuous.

Proof: (i)  (ii): obvious (ii)  (i) Let F be an g*b-closed set in (Y,  ). Since (Y,  ) is a Tg*b-space, F is a closed set in (Y,) and by

  {X ,,{b},{a, b}} and   {X ,,{a},{a, b}} . hypothesis, f 1 ( F ) is g*b-closed in (X,τ). Therefore Then the function f : ( X , )  (Y ,  ) defined by f (a)  b , f (b)  a , f (c)  c is irresolute but not g*b-irresolute. Example 3.8 X  Y  {a, b, c} ,   {X ,  ,{a},{a, b}}

f is g*b-irresolute.

Theorem 3.13 If f : ( X , )  (Y ,  ) is bijective, bopen and g*b-continuous then f is g*b-irresolute.

.Then the   {X ,,{a}} Proof: Let V be any g*b-closed set in Y and let function f : ( X , )  (Y ,  ) defined by f (a)  b , f 1 (V )  U where U is b-open in X. Then and

f (b)  a , f (c)  c is g*b-irresolute but not irresolute.

V  f (U ) . Since f (U ) is b-open in Y and V is g*bclosed in Y , then cl(V)  f (U ) implies that Theorem 3.9 A function f : ( X , )  (Y ,  ) is g*b1 is g*b-continuous, irresolute if and only if the inverse image of every g*b- f cl (V )  U . Since f open set in (Y,  ) is g*b-open in (X,τ). Proof:Let f : ( X , )  (Y ,  ) ) be g*b-irresolute and

U be a g*b-open set in (Y,). Then U c is g*b-closed in (Y,) and since f is g*b-irresolute, f 1 (U c ) is g*bclosed in (X,). But f 1 (U c ) = ( f 1 (U ))c and so

f 1 (U ) is g*b-open in (X,).

f 1cl (V )

is

g*b-closed

in

X.

cl ( f 1cl (V ))  U

Hence .Therefore

cl ( f 1 (V ))  cl ( f 1cl (V ))  U

.

That

is cl ( f 1(V ))  U . This shows that f is g*b-irresolute. Theorem 3.14 If f : ( X , )  (Y ,  ) is bijective,

1

(U ) is g*b-open closed and irresolute then the inverse function 1 in (X,) for each open set U in (Y,). Let f be a g*b- f : (Y ,  )  ( X , ) is g*b-irresolute. Conversely, assume that f

closed set in (Y,). Then U c is g*b-open in (Y,) and by assumption f 1 (U ) is g*b-open in (X,). Since

Proof:

Let

A

be

g*b-closed

in

(X,τ).

Let ( f 1 ) 1 ( A)  f ( A)  U , where U is g-open in

1 1 f 1 (U c ) = ( f 1 (U ))c , we have f 1 ( F ) is g*b- (Y,  ). Then A  f (U ) holds. Since f (U ) is g-

closed in (X,) and so f is g*b-irresolute.

open in (X,τ) and A is g*b-closed in (X,τ),

not g*b-closed in X.

g*b-open set in (Y,) is open in (X, τ).

bcl ( A)  f 1 (U ) and hence f (bcl ( A))  U . Since f Theorem 3.10 If a function f : ( X , )  (Y ,  ) is g*b- is b-closed and bcl(A) is closed in (X,τ), f (bcl ( A)) is irresolute then it is g*b-continuous but not conversely b-closed in (Y,). Therefore bcl ( f (bcl ( A)))  U and Example 3.11 Let X  Y  {a, b, c, d} , hence bcl ( f ( A))  (U ) . Thus f (A) is g*b-closed in . Let   {X ,,{a},{b},{a, b},{a, b, c}}   (Y,) and so f 1 is g*b-irresolute. f : ( X , )  (Y ,  ) be defined by f (a)  b , f (b)  c , f (c)  d , f (d )  a . Then f is g*bDefinition 3.15 A function f : ( X , )  (Y ,  ) is called continuous but not g*b-irresolute since f 1 (b)  {a} is strongly g*b-continuous if the inverse image of every

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Theorem 3.16 If f : ( X , )  (Y ,  ) is strongly g*bcontinuous, then it is strongly g-continuous but not conversely. Example 3.17 Let , X  {a, b, c}

Proof: (i)  (ii) Follows from the Theorem 3.19. (ii)  (i) Let U be any g*b-set in (Y,). Since (Y,) is a g*b-space, U is a g*b-open subset of (Y,) and by hypothesis, f 1 (U ) is open in (X,). But (X,) is a

. Let   X ,  ,{a},{b},{a, b}   discrete space and so f 1 (U ) is also closed in (X,). f : ( X , )  (Y ,  ) be defined by f (a)  b , f (b)  a , 1 f (c)  c . Then f is strongly g-continuous but not That is f (U ) is both open and closed in (X,) and so

f is strongly continuous.

strongly g*b-continuous. Theorem 3.18 Let (X,τ)be any topological space and (Y,) be a Tg*b-space and f : ( X , )  (Y ,  ) be a function. Then the following are equivalent. (i) f is strongly g*b-continuous (ii)

Theorem 3.23 Let f : ( X , )  (Y ,  ) be a function and both (X,) and (Y,) be Tg*b -spaces. Then the following are equivalent. (i) f is strongly g*b-continuous, (ii)

f is continuous.

(iii) Theorem 3.19 If

f is continuous, f is g*b-continuous.

f : ( X , )  (Y ,  ) is strongly

continuous then it is strongly g*b-continuous but not conversely. Theorem 3.20 Let f : ( X , )  (Y ,  ) be onto, g*b-

Theorem 3.24 A function f : ( X , )  (Y ,  ) is strongly g*b-continuous if and only if the inverse image of every g*b-closed set in (Y,) is closed in (X,) If f : ( X , )  (Y ,  ) and g: (Y,)

irresolute and b-closed. If (X,) is a Tb -space, then

Theorem 3.25

(Y ,  ) is also a Tb -space.

(Z,) are strongly g*b-continuous, then their composition g  f : ( X , )  (Z , ) is also strongly

Proof: Let A be a g*b-closed subset of(Y,). Since f is g*b-irresolute,

then

f 1 ( A)

is

g*b-closed

in

(X,).Since (X,) is a Tb -space, then f 1 ( A) is a bclosed in (X,).Thus A is b-closed in (Y,) because f is surjective. Hence (Y,) is a Tb -space. Theorem

3.21

Let

f : ( X , )  (Y ,  ) is g*b-

irresolute and closed. If (X,) is almost weakly Hausdroff, then (Y,) is almost weakly Hausdroff space. Proof: Let V be any g*b-closed set in Y. Since f is g*b-irresolute, f 1 (V ) is g*b-closed in X. Since (X,) is is almost weakly Hausdroff, f 1 (V ) is closed in X, then V is closed because f is closed and onto. Hence Y is almost weakly Hausdorff space. Theorem 3.22 Let (X,) be a discrete topological space, (Y,) be a g*b-space and f : ( X , )  (Y ,  ) be a function. Then the following are equivalent. (i) f is strongly continuous (ii)

f is strongly g*b-continuous.

continuous. Proof: Let U be a g*b-open set in (Z,). Since g is strongly g*b-continuous, g 1 (U ) is open in (Y,). Since g 1 (U ) is open, it is g*b-open in (Y,). As f is also strongly

f

1

1

g*b-continuous, 1

( g (U ))  ( g  f ) (U ) is open in (X,) and so

gof is strongly continuous. Theorem 3.26 If f : ( X , )  (Y ,  ) and g: (Y,) (Z,) be any two functions then their composition g  f : ( X , )  (Z , ) is (i) Strongly g*b-continuous if g is strongly g*bcontinuous and f is strongly g*b-continuous. (ii) g*b-irresolute if g is strongly g*b-continuous and f is g*b-continuous ( or f is g*b-irresolute). (iii) Strongly g*b-continuous if g is strongly continuous and f is irresolute. (iv) Continuous if g is g*b-continuous and f is strongly g*b-continuous. We next introduce perfectly g*b-continuous functions in topological spaces.

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Definition 3.27 A function f : ( X , )  (Y ,  ) is called perfectly g*b-continuous if the inverse image of every g*b-open set in (Y,) is both open and closed in (X,). Theorem 3.28 If f : ( X , )  (Y ,  ) is perfectly g*bcontinuous then it is strongly g*b- continuous. Proof: Since f : ( X , )  (Y ,  ) is perfectly g*bcontinuous, f 1 (U ) is both open and closed in X, for every g*b-open set Y in X. Therefore f is strongly g*bcontinuous. Theorem 3.29 If f : ( X , )  (Y ,  ) is strongly continuous then it is perfectly g*b-continuous. Proof: Since f : ( X , )  (Y ,  ) is strongly continuous, f 1 (U ) is both open and closed in (X,), for every g*b-open set U in (Y,). Therefore f is perfectly g*b-continuous. We have the following implications for the above results.

III. REFERENCES [1].

[2].

[3].

[4].

spaces, Mem. Fac. Sci. Kochi Univ. Ser. A Math., 12 (1991), 5–13. [5]. R.Devi, K.Balachandran and H.Maki, Semigeneralized homeomorphisms and generalized semi-homeomorphisms in topological spaces, Indian J. Pure Appl. Math., 26(1995), 271-284. [6]. R.Devi, K.Balachandran and H.Maki, Generalized α-closed maps and α-generalized closed maps, Mem. Fac. Kochi Univ. Ser. A. Math., 14(1993), 41-54. [7]. A.S.Mashhour, I.A.Hasanein and S.N.El.Deep, α- continuous and α-open mappings, Acta. Math. Hunger., 41(1983), 213-218. [8]. B. M. Munshi and D. S. Bassan,g-continuous mappings, Vidya J. Gujarat Univ. B Sci.,24(1981), 63–68 [9]. T.Noiri, A Generalization of Some Forms of gIrresolute Functions, European journal of pure and applied mathematics vol. 2, no. 4, 2009, (473-493) [10]. continuous functions, Chaos Solitons Fractals 24 (2005), no. 2, 471 – 477. [11]. D.Iyappan and N.Nagaveni, On semi generalized b-continuous maps, semi generalized b-closed,maps in topological space, Int.Journal of Math. Analysis, vol.6, 2012, no.26, 1251-1264. [12]. R.S Wali and Prabhavati S Mandalgeri, On αrω– Continuous and αrω–Irresolute Maps in Topological Spaces, IOSR Journal of Mathematics, Volume 10, Issue 6 Ver. VI (Nov - Dec. 2014), PP 14-24.

I . Arokiarani, K.Balachandran and J.Dontchev, Some characterization of gp-irresolute and gpcontinuous maps between topological spaces, Mem. Fac. Kochi Univ. Ser. A. Math, 20(1999), 93-104. S. P. Arya and R. Gupta, On strongly continuous functions, Kyungpook Math. J. 14:131:143, 1974. I. Arokiarani, K. Barachandran and J. Dontchev, Some characterization of gp-irresolute and gpcontinuous maps between topological spaces, Mem. Fac. Sci. Kochi Univ. Ser. A Math., 20 (1999), 93–104. K. Balachandran, P. Sundarm and H. Maki, On generalized continuous maps in topological

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Ultrasonic Velocity in Potassium Sodium Tantalate Mixed System Manish Uniyal*, S. C. Bhatt Department of Physics, H.N.B.Garhwal University, Srinagar Garhwal, Uttarakhan, India

ABSTRACT Ultrasonic velocity in the ceramic pellets of material K 1-xNaxTaO3 (X=0, 0.2, 0.3, 0.4, 0.5, 0.6 & 1) have been investigated at temperature 320C and frequency 5MHz with the help of Ultrasonic c-scan system developed at NPL, New Delhi. The samples have been prepared by the conventional solid-state reaction method and sintering process. Keyword: Ultrasonic Velocity, NPL, Potassium Sodium Tantalate, PST

I. INTRODUCTION Ultrasonic testing of materials is one of the widely used methods of nondestructive testing, in which beams of high frequency sound waves generally 0.5 MHz to 25 MHz are used to detect the cracks, laminations, shrinkages, cavities and other discontinuities. Inclusion and other inhomogeneties in the material can also be detected using partial reflection or scattering of ultrasonic waves. It has high sensitivity for detecting flaws, can penetrate extremely thick sections and need access to only one surface of the testing material. We have measured the Acoustical velocity in potassium sodium tantalate mixed ceramics at 320C and at frequency 5 MHz. The propagation of ultrasonic wave in any substance has become a fundamental test to investigate its properties. The velocity and attenuation coefficients are the basic propagation constants, which are related to the microscopic structure of the materials. Potassium Sodium Tantalate (PSN) with perovskite structures are widely used for transducer applications with broad ranges of technologically important dielectric, piezoelectric, ferroelectric and electro-optic properties. Cross [1] has predicted, theoretically, the phase diagram of KTaO3-NaTaO3 mixture from phenomenological arguments. Due to the immense importance of these materials, Acoustical investigation has been carried out by several researchers [2-8]. Preparation of amorphous and nano crystalline Sodium Tantalate Oxide

photocatalysts with porous matrix structure for overall water has been investigated by Harun Tuysuz et.al. [9]. Microstructure of Sodium - Potassium niobate ceramics sintered under high alkaline vapour pressure atmosphere has been studied by Jerome Acker et.al.[10]. Fast synthesis of NaNbO3 and Na0.5K0.5NbO3 by microwave hydrothermal method was performed by Rigoberto Lopez-Juarez et.al.[11]. Synthesis, photo physical properties, and photo catalytic applications of Bi doped NaTaO3 and Bi doped Na2TaO3 nano particles was studied by Pushkar Kanhere et.al.[12]. Theoretical & experimental studies on Ceramic Samples of different ferroelectric material has been done to understand the salient features as these materials [13-17]

II. METHODS AND MATERIAL A. Preparation The raw materials used for preparing the compositions from this system were sodium carbonate, potassium carbonate and niobium pentaoxide. The starting material was dried at 2000C for one hour to remove absorbed moisture. Different compositions of K1-xNaxTaO3 for (x=0, 0.2, 0.3, 0.4, 0.5, 0.6 & 1) were prepared by weighing the sodium carbonate, potassium carbonate and niobium pentaoxide. The mixture was calcined in the platinum crucible, in air, at 9500C for 2h for carbonate removal. The pre-sintered mixture was ground and pressed into pellets of 10mm diameter. All the

IJSRST15153 | Received: 02 November 2015 | Accepted: 13 November 2015 | November-December-2015 [(1)5: 21-22]

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IV. ACKNOWLEDGEMENT

pellets were placed on a platinum crucible and sintered, in air, at 10500C for 26 h. B. Measurement In the present study we have investigated the ultrasonic velocity in pure and mixed system of Na1-xKxTaO3 where (x=0, 0.2, 0.3, 0.4, 0.5, 0.6 &1).The velocity has been measured at the transverse section of the prepared samples at frequency 5 MHz and at temperature 320C with the help of Ultrasonic c-scan system developed at NPL, New Delhi. Variation of Acoustical velocity by mixing K on NaTaO3 is tabulated in table 1 and figure 1.

The authors are thankful to Material Science Research Centre (MSRC), IIT Madras and National Physical Laboratory (NPL), New Delhi for providing laboratory facilities for sample preparation, characterization and ultrasonic velocity measurement respectively.

V. REFERENCES [1] [2] [3]

Table 1 [4]

Sample (Na1- xKxTaO3) (x=0,0.2,0.3,0.4,0.5,0.6 &1) NaTaO3 Na0.8K0.2TaO3 Na0.7K0.3TaO3 Na0.6K0.4TaO3 Na0.5K0.5TaO3 Na0.4Na0.6TaO3 KTaO3

Acoustical velocity x104 m/s 0.3026 0.2679 0.2701 0.2626 0.2526 0.2448 0.1838

[5] [6] [7] [8] [9] [10]

[11]

[12]

[13]

III. RESULT AND DISCUSSION The study of the prepared samples aimed at understanding the Acoustical velocity and mechanism that could lead of the present PST system. From above figure 1, it is observed that as soon as potassium is mixed with sodium tantalate at temperature 320C and frequency 5 MHz i.e., K on Nax K1-x TaO3, the ultrasonic velocity decreases continuously.

[14] [15] [16] [17]

L E Cross, Philos Mag. 1 (1956) 56. S C Bhatt and B S Semwal, Ind.J. Pure & app. Phys.25(1980)174. S C Bhatt and B S Semwal, Solid State Ionics, 23(1987)77. S C Bhatt, G N Baluni, U C Naithani and B S Semwal, Ind.J.Pure & app. Phys.26(1988)356. C W Garland and Donald Novotny,Phy.Rev.177,no.2(1969)971-975. E Havlin, Litov and H Sompolinsky,Phy.Rev.B 13, no.1(1976). E Litov and C W Garland, Phy.RevB 8,no.11(1970) 971-975. Harrison H.Barret,Physical Review,178, No.2(1969). Harun Tuysuz,Candace K.Chan,Nano Energy,Issue 1,2(2013)116 123. Jerome Acker, Hans Kungi, Roland Achierholz, Susan Wagner,Rudiger-A.Eichel, Michael J.Hoffmann, Journal of European Ceramic Society, Issue 16, 34(2014) 4213- 4221. Rigoberto Lopez-Jurez, R.Castaneda-Guzman, Villafuerte M E- Castrejon, Ceramic International, Issue 9,40 Part-B (2014)14757-14764. Pushkar Kanhere, Yuxin Tang, Jianwei Zheng, Zhong Chen, Journal of Physics and Chemistry of Solids,Issue 12,74 (2013)1708-1713. Manish Uniyal & S C Bhatt, Indian Journal of Pure & Applied Physics 49(2011)350 Manish Uniyal & S C Bhatt, Indian Journal of Pure & Applied Physics 50( 2012)248-251 S C Bhatt & Manish Uniyal, International Journal of materials and Chemistry, 2(2) (2012)47-50 Manish Uniyal, S C Bhatt & Gairola R P, Indian Journal of Pure & Applied Physics, 50(2012)915-917 Manish Uniyal, S C Bhatt, Indian Journal of Pure & Applied Physics, 52(2014)391-394

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Assessment of Shoreline Dynamics at Bonny Island, Nigeria using Geospatial Techniques 1*

Brown Joshua, 2Adekunle I. A

1

MSc. Geospatial and Mapping Sciences, The University of Glasgow, Scotland, UK School of Environmental Technology, Rivers State Polytechnic, Bori, Rivers State, Nigeria

2

ABSTRACT Bonny Island is a highly dynamic one as there is a high level of interplay between the forces of erosion and accretion. From previous studies by the Nigerian Institute for Oceanography and Marine Research (NIOMR), the annual rate of erosion has been put at about 20 – 35 metres along the bonny shoreline. This claim was confirmed from the present study carried out along 12 transect points of 500 metres intervals along the Finima section of the Bonny beach. Geospatial techniques were used to carry out the assessment of the state of the bonny shoreline. Satellite imageries from 1976 – 2005 were used in the study and GPS receiver was also used to acquire the shoreline position along the transect points for 2011. From the result of the study, the Finima beach area was found to have the highest rate of shoreline dynamics. Erosion dominated in this area over accretion. This area experienced a total land area loss of 458.04 hectares of land out of which erosion and accretion recorded 280.47 and 177.57 hectares respectively. By this it means erosion claimed about 61.2% of the total land area while accretion recorded a 39.8% land increase. The changes were largely attributed to the presence of oil exploration activities as prior to the commencement of this anthropogenic activities there was lesser impacts of erosion as accretion predominated the area. There is therefore a cogent need to adopt some proactive measures to protect the bonny beach, from further land loss due to erosion and the untold hardship it brings to the coastal residents. Keywords: Nigeria, Bonny Island, Shorelines Dynamics, GIS, Remote Sensing and Global Positioning System

I. INTRODUCTION

The rates of erosion at 10 stations established along the Nigerian coastline, was determined by NIOMR in 1995. Coastline change is a global phenomenon; it has been in Erosion was found to be most dominant at Bar Beach, operation for as long as the ocean and land existed. It Victoria Island, with rates ranging between 25 and 70 has occurred in varying degrees around the globe with metres per annum. Awoye beach on the low-lying some areas more vulnerable to these changes than others. Mahin mud-beach in Ondo State recorded 27 metres of Nigeria is not spared from these global phenomenon it erosion. Slight accretion was recorded at the has had its own share from the time past. The processes Ugbogoro/Escravos beach. The erosion rate for Bonny are still in operation till date. The construction of oil was also recorded it was quite high ranging between 20refineries and wells, gas and oil pipelines, storage tanks 35metres per annum near the LNG site (NIOMR, 1995). with insufficient setbacks have been a main cause for Ibe further confirmed the erosion rate at Bonny station erosion in the coastal towns of Nigeria (GEF, 2002). The to be ranging between 20-24metres annually. retreat of Nigerian shorelines threatens most of the coastal settlements, recreational grounds and oil export In Nigeria, there has not been a sustained effort in the handling facilities which are almost invariably located in study of the national coastline. This has led to the poor coastal towns such as Brass, Bonny, Ibeno-Eket, and management and continuous degradation of the nation’s coastline. The major reason for this dearth of studies in Forcados (Ibe and Antia, 1983).

IJSRST151448 | Received: 29 October 2015 | Accepted: 17 November 2015 | November-December 2015 [(1)5: 23-34]

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this all important area has been provided by Awosike, 1992. According to Awosike “Data acquisition programme for parameters such as winds, nearshore currents, bathymetry and so related to defining beach states are expensive”. Developing nations are therefore unable to provide an adequate data pool for studies on shoreline dynamics and coastal management (Hayes, 1984; Awosika, 1992). In recent time the use of geospatial techniques have been proven to be an extremely useful approach for the studies of shoreline changes, due to synoptic and repetitive data coverage, high resolution, multispectral satellite imageries and its cost effectiveness in comparison to conventional techniques. It is against this backdrop that this study employed geospatial techniques to analyse shoreline dynamics along Bonny Coastline covering a period of about 35years (1976-2011) using three sets of satellite imageries (Landsat MSS, Landsat ETM+ and Spot). Ground truthing of identified shoreline changes from the imageries were carried out to establish the extent of change. A. Objectives of the Study The aim of this research was to analyze trend of shoreline changes along the Bonny coastline over the past 30 years, using geospatial techniques. The specific objectives of this study are to:  Estimate shoreline changes (displacement and configuration) in study area over the past 30 years using geospatial models  Determine the factors responsible for the observed changes occurring along the bonny shoreline.  Produce a map of shoreline change in the area.  Recommend appropriate remediation and shoreline management best practices for the area B. Hypothesis of the Study Ho: There has been no significant change along the Bonny shoreline over the past 30 years. H1: there has been a significant change along the Bonny shoreline over the past 30 years.

C. Significance of the Study The research reveals the shoreline dynamics along the Bonny coastline in recent times. This achievement would further enhance the effective monitoring and mitigations of the changes that is ongoing in the area. Furthermore, the result of this research will provide more information for future research on shoreline dynamics. D. Assumptions of the Study The following assumptions are made for this research with the hope of all things been equal.  That the terrain would be easily accessible for the research  The finance would be made readily available at the time of the research. E. Study Area Geographic Location Bonny Island is situated at the southern edge of Rivers State in the eastern Niger Delta region of Nigeria. It was formally known as Ibani or Ubani town. It lies along the Bonny River (eastern distributaries and 6 miles upstream from the Bight of Biafra. It is located at latitude 40 26’ 57’’N and 40 31’ 42’’ longitude 70 3’ 8.1’’ and 70 9’ 38’’. The Bonny River flows in a southeasterly direction into a large body of water which also flows almost vertically and slightly southeasterly into the Bight of Bonny. It runs in between the two neighboring estuaries of the New Calabar River to the west and the Andoni River to the east. The Cawthome channel links the New Calabar channel and Bonny River estuary. Bonny covers a total land area of about 651.20km2

II. METHODS AND MATERIAL A. Research Design This study concerns itself with the assessment of the rate of shoreline dynamics at Bonny Island within 1976-2011 (i.e. 35years period). Research design as described by Baridam (2001) is “a frame-work or plan that is used as a guide in collecting and analyzing the data for a study. It is a model of proof that allows the researcher to draw inferences concerning casual relations among the variables under investigation”. With this in mind the

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study adopted the One-Shot Case Study Correlational Research Design. Some elements of judgment sampling were also employed in the cause of data collection. Data derived where analyzed using geospatial techniques to assess the rate of change in the shoreline at Bonny Island. B. Research Population and Sample Size This study was focused mainly on assessing the shoreline dynamics along the Finima Coastline in Bonny town, stretching from Amariari-Kiri area to the LNG Residential Area (RA). The study area is located at the south-western part of the Bonny Coast (Fig.1). This area covering an approximate distance of 6km was chosen purposively for the study because it was observed to have the highest rate of erosion when compared to the other parts of the Bonny shoreline. Finita-Singi settlement being the high point of erosion activities within the 6km study area was selected for the purpose of administering of questionnaire. The sample size for the study was based on the availability of data for the study in line with the study objectives. Based on availability of data especially satellite imagery the sample size was restricted to a period of 35 years. Satellite data for the year 1976 to 2005 was available in addition with the GPS transect data acquired from the field in 2011. Although data for equal year interval were not readily available due to some factors some of which include cloud cover on some of the satellite imageries which made it unfit for the accurate delineation of the shoreline of the study area.

Also the high costs of acquiring some of these satellite data were also responsible for the inconsistency in the datasets. C. Sample Design The sample design employed in this research was The Grid Cell/Transect Design. The entire shoreline area was gridded, using a grid cell of 500meter interval. A transects was placed at every 500meter interval beginning from the west bank of the southern part of the Bonny Island to the edge of the eastern bank which are all adjacent to the Atlantic Ocean. The total length of the study area was approx. 6km. A total of 12 transects was taken and measurement was carried out at each transect points within the 500meter zone. The shorelines measured include 1976, 1986, 2000, 2004 and 2005 shorelines delineated from their respective images. The 1976 shoreline was used as the baseline upon which the other shorelines were compared and measured. GPS shoreline positions for 2011 were acquired along the 500m transect locations. The Measurements took place within ArcGIS software. Fig.2 below shows the gridded shorelines of the study area.

Figure 2: shorelines of the study area showing the grid cell approach used

D. Data Collection and Processing This study employed both secondary and primary data. The following approaches were utilised to acquire the data for the analysis. 1)

Figure 1 : Finima area showing the study location from Amariari-Kiri to LNG RA beach

Geographic Information System (GIS) & Remote Sensing approach

ArcGIS 9.3 software was used to handle all the GIS processes. The shoreline data from the satellite imageries were extracted for the project. Methods such as georeferencing, creation of a geodatabase and vectorisation were all employed to generate the

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shorelines for measurement of the change. Using the 1976 shoreline as the baseline all other shorelines were measured for change along the 12 transects points. The measurement tool in ArcGIS 9.3 was used to execute the measurements. A repeated measurement was carried out and the mean was determined. This was to enhance the precision of the measure shorelines ERDAS Imagine 9.3 software was used to handle all the satellite imagery processing. The bands were stacked in the order of 4+3+2 to form false colour composite. 2)

Global Positioning Systems (GPS) Mapping

Plate 2 Photo at transect 2 (T2) showing erosion site

GPS data for the current shoreline positions were acquired from the study area using a Garmin 12 dual frequency hand-held GPS. The XY coordinates were taken at a regular interval of 500m along the Finima beach area. GPS readings were taken at the same transects points identified from the satellite imageries so as to remove any form of errors that would arise during the analysis of results. The total transect points were 12 and GPS coordinates were all taken at each of them. The data so acquired enable the mapping of the 2011 shoreline position in the ArcGIS 9.3 environment in addition to the previous shoreline positions derived from the satellite imageries. 3)

Other Data Collected

Digital photographs showing evidence of shoreline dynamics in the study area were acquired. The photographs were taken at all the 12 transect points. The pictures show areas of erosion and accretion.

Plate 3 Photo at transect 3 (T3) showing a fishing boats at Finita-Singi

The Photographs acquired along the 12 transect points are shown in Plate.1 to 12 below.

Plate 4 Photo at transect 4 (T4) showing erosion site

Plate 1 Photo at transect 1 (T1) showing erosion site

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Plate 5 Photo at transect 5 (T5) showing an estuary with active erosion

Plate 6 Photo at transect 6 (T6) showing accretion site

Plate 7 Photo at transect 7 (T7) showing erosion site

Plate 9 Photo at transect 9 (T9) showing erosion site

Plate 10 Photo at transect 10 (T10) showing erosion site

Plate 11 Photo at transect 11 (T11) showing erosion site

Plate 8 Photo at transect 8 (T8) showing active erosion site Plate 12 Photo at transect 12 (T12) showing erosion site

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he symbol (a) in the null and alternate hypothesis above represents the means of the different periods. Analysis of variance sets out to compare these means by partitioning variance of dataset from x1 and y1 was calculated into two components; viz those that are due to within sample differences and those that are due to variations between samples. Snedecor’s F statistics is then computed by comparing the variance due to the two components, also referred to as Error of sum of squares (ESS) and between variables sum of squares (BSS) respectively. Let these be represented by ESS and BSS respectively while the total variance of sum of squares is represented by TSS.

E. Statistical Analysis/Hypothesis Testing The statistical method of analysis used was the Analysis of Variance (ANOVA). The ANOVA was used to test for differences in the means of the shoreline datasets (1976-1986, 1986-2000, 2000-2005 and 2005-2011). 4)

Analysis of Variance (ANOVA)

ANOVA was used to test the hypothesis of the study. The Null hypothesis states that there is no significant change of shoreline along the Bonny Coastline over the past 30 years. The ANOVA table is shown below in Table 1. Table 1 Analysis of Variance Format for the shoreline studies

Then, TSS = ESS + BSS ESS = TSS – BSS

In the comparison of the means over the k periods the null hypothesis is stated as:

TSS = ΣΣ x2jk – (ΣΣxjk)2 jk N 2 BSS = Σ (Σ xjk) _ (Σ Σ xjk)2 jk n j k N

H0: a1 = a2 = a3 = a4 = an H1: a1 ≠ a2 ≠ a3 ≠ a4 ≠ an Table 2 Analysis of Variance Format for the shoreline studies Location

PERIODS 1976-1986

1986-2000

2000-2005

2005-2011

Erosion (m)

Accretion (m)

Erosion (m)

Accretion (m)

Erosion (m)

Accretion (m)

Erosion (m)

Accretion (m)

A

X11

Y11

X21

Y21

X31

Y31

X41

Y41

B

X12

Y12

X22

Y22

X32

Y32

X42

Y42

C

X13

Y13

X23

Y23

X33

Y33

X43

Y43

N

X1n

Y1n

X2n

Y2n

X3n

Y3n

X4n

Y4n

X = Erosion Y = Accretion Table 3 Sums of x and y and sums of square Locations

PERIODS 1976-1986

1986-2000

2000-2005

2005-2011

Erosion (m)

Accretion (m)

Erosion (m)

Accretion (m)

Erosion (m)

Accretion (m)

Erosion (m)

Accretion (m)

Sum of x ,y

∑x1

∑y1

∑x2

∑y2

∑x3

∑y3

∑x4

∑y4

Sum of x, y squared

∑x21

∑y21

∑x22

∑y22

∑x23

∑y23

∑x24

∑x24

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III. RESULT AND DISCUSSION

recorded accretions. Fig.3 below shows the chart of the shoreline changes within 1976-1986.

A. Shoreline Dynamics along Finima Coastline The data on shoreline changes along section of the Bonny Coastline is presented herein in four different epochs. The extent of shoreline changes were determined through image analyses and field measurement carried out along the 12 transect points established along the shoreline of the Finima beach area. Below are the results of the analysis carried out in the study area within the 1976-2011. 1)

Shoreline Trend Within 1976-1986 periods:

Table.3 below shows the trend of shoreline change within 1976-1986 Table 4 Showing trend of shoreline change within 19761986.

Figure 3 : shoreline change trend along Finima beach area within 1976-1986 periods The total annual change within this period was recorded as 36.6m from the result of the analysis done in the previous sections. This result agrees with the result of the research carried out by NIOMR, 1995 which showed an annual land loss of 35metres around the LNG site. The highest annual land loss was recorded at Transect T6 with 13 hectares representing 35.5%. A total of 67.5 hectares of land was gained representing 80.45% of the general shoreline change within this period. The highest point of accretion was at NLNG RA1 beach area (T12) which recorded 12.3 hectares representing 18.2% gain in land area. Overall 8 locations out of the 12 transect points experienced accretion i.e. land gain. The map below (Fig.4) shows the shoreline change within the 1976 – 1986 epochs.

From Table.3 above erosion occurred at only four locations (T6, T7, T8 and T9) this claimed 16.4 hectares of land area. The highest land loss was recorded at Transect T7 around the Finita-Singi area. The areal land loss at this point was approximately 6.5 hectares of land representing 39.6% of the total land loss within the period. Transect T6 within Finita-Singi area recorded land loss of approximately 5.9 hectares of land representing 36.0% of the total land loss within the same period. The other areas are; T8 and T9 which recorded 3.4 and 0.6 hectares land loss respectively. Besides the four locations mentioned above, the rest locations

Figure 4 : showing shoreline map of the 1975-1986 period

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2)

Shoreline Trend within 1986-2000 periods

The result of the shoreline trend within this period is presented below. Table 5 Shoreline change trend within 1986-2000

Figure 5: Shoreline change trend within 1986-2000

The result in Table.4 shows that there was no accretion within the 12 transects points measured within this epoch. All the transect points recorded a zero value which indicates no accretion. Base on this result it means this epochs was predominantly erosional. Figure.6 below shows the shoreline map of this period.

Figure 6 : showing shorelines of the two periods discussed above

The table above indicates that a total of 98.8 hectares of land was lost to erosion within this period. All the 12 transect points within this period experienced erosion unlike the previous period presented above that had more of accretion than erosion. The highest point of erosion within this period was at Transect point T5 located around Finita-Singi beach area. This recorded an approximately 12.1 hectares of land loss representing 12.3% loss. The lowest point of erosion from our data was recorded at transect T3 with a value of 2.7 hectares loss within the period. Figure.5 illustrates the shoreline erosion within this period.

3) Shoreline Trend within 2000-2005 epochs The result of the shoreline within this period is shown below. Table 6 Shoreline erosion trend within 2000-2005 periods

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The shoreline trend for this period is represented in Fig.8 which shows the variations in the positions of the various shorelines.

Figure 8 : showing the shoreline positions within 1976-2005

4)

Shoreline Trend within 2005-2011 epoch

The result of the shoreline trend within this period is presented below. From Table.5 a total of 47 hectares of land was lost to erosion within this period. The highpoint of erosion was at transects T3 around Finita-Singi area recording 10.1 hectares of land loss which represents 21.5% of the total loss. The range of the erosion was within period was between 0.8 to 10.1 hectares. This result indicates that erosion occurred at the 12 transect points along the study area. Fig.7 below shows a chart of the erosion trend within this period.

Table.6 below shows the result of the shoreline erosion trend within this period. Table 7 Shoreline Erosion trend within 2005-2011 epochs

Figure 7 : showing shoreline changes trend within 2000-2005 epoch

From Fig.7 above transect point 3 recorded the highest annual rate of erosion while T10 recorded the least annual erosion. The result presented above in Table.5 shows that there was no accretion within this period rather there were prevalence of erosion at all the transect points.

From the table above the total land loss in area within the 2005-2011 epochs was recorded as 39.1 hectares. The high point of erosion was at transects T2 which was established along Finita-Singi beach area. Meanwhile

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the lowest point was at T4 which recorded zero due to the prevalence of accretion at this station. Fig.9 below shows the shoreline erosion in a percentage bar graph. From the above result accretion occurred at only one location which was at Transect T4 along the Finima beach area. This represented a 100% of the total land accretion within this period. Fig.10 below shows the shoreline map for this period.

Figure 10: showing the shoreline positions of the different periods as obtained from the analyses

Figure 9 : showing shoreline change trend within the 20052011 epoch (Source: Author’s work)

B. Hypothesis Testing Two statistical methods were used to test for the two hypothesis of the study. The two hypotheses is briefly stated below H01: There has been no significant change along the Bonny shoreline over the past 30 years. H1: There is. Table.7 below shows the variance of ANOVA result for Hypothesis One

Table 8 Computing the variance of ANOVA

S/N

SITES

Period 1976-1986

1 2 3 4 5 6 7 8 9 10 11 12 13

Lighthouse area/ T3 Finita-Singi settlement/T4 Finita-Singi area/ T5 Finita-Singi Area/ T6 Finita-Singi Area/ T7 Finita-Singi Area/ T8 Finita-Singi Area/ T9 Finita-Singi Area/ T10 Finita-Singi Area/ T11 Near NLNG RA1 beach/ T12 NLNG RA1 beach/ T13 NLNG RA1 beach area/ T14 Total

X 7.2 10.2 10.5 10 4.7 - 5.9 - 6.5 - 3.4 - 0.6 4 8.6 12.3 83.9

1986-2000 2

X 51.84 104.04 110.25 100 22.09 -34.81 -42.25 -11.56 -0.36 16 73.96 151.29 718.45

X -10 -3.9 -2.7 -6.4 -12.1 -6.2 -7.6 -7.8 -10.1 -11.3 -11 -9.7 101.5

2000-2005 2

X -100 -15.21 -7.29 -40.96 -146.41 -38.44 -57.76 -60.84 -102.01 -127.69 -121 -94.09 911.7

X -5.9 -7.2 -10.1 -2.3 -6.3 -5.1 -3.3 -2.6 -1.4 -1.1 -0.9 -0.8 47

2005-2011 2

X -34.81 -51.84 -102.01 -5.29 -39.69 -26.01 -10.89 -6.76 -1.96 -1.21 -0.81 -0.64 281.92

X - 3.64 - 5.70 - 4.78 1.86 - 3.66 - 4.77 - 4.12 - 2.83 - 3.43 - 2.54 - 2.01 -1.62 40.96

X2 -13.25 -32.49 -22.85 3.46 -13.4 -22.75 -16.97 -8.01 -11.77 6.45 -4.04 -2.62 158.01

Source: Author’s Work

The result of the computations for the sums of squares is presented in Table.8 below.

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Table 9 ANOVA Table for shoreline dynamics at Bonny Island Square of variations

Sum of squares

Degrees of freedom 3

Mean sum of squares

about 61.2% of the total land area while accretion recorded a 39.8% land increase.

F

This changes recorded was attributed to the changes in land use in the area. As at 1976 -1986 period there was more of accretion of land around the shorelines in the 352.03 44 8.0 study area. This was because during this period there were lesser anthropogenic activities within the area. The establishment of oil multinationals such as Nigeria 513.31 47 (Source: Author’s work) Liquefied Natural Gas (NLNG) came after this epoch. The activities of these companies such as dredging and The test statistics gives a value of 45.76 while from a 95% movement of their ocean liners led to the increased rate table of the F distribution the critical value at 3 and 44 of shoreline erosion. This was confirmed by the degrees of freedom is 2.72 i.e., residents as one of the major causes of erosion in the F0.05 = 2.72 area. Between Columns (samples) Within columns (Error) Total

161.28

53.76

45.76

Decision Rule: A large maximum difference indicates a wide difference between the distributions, leading to a rejection of the null hypothesis. From the ANOVA analysis above the critical F value at 95% probability level is less than the calculated F value of 45.76. Based on the rule it means the null hypothesis which states that there is no statistically significant difference in the rate of shoreline change at Bonny Island would be rejected, because there is a statistically significant difference in the rate of shoreline changes at the Bonny Island. C. Discussions This study was concerned with the assessment of shoreline dynamics at Bonny Island using GIS and Remote Sensing techniques. The assessment of the shoreline dynamics in Bonny Island was done using satellite imageries and GPS coordinate data acquired from the field. The shoreline positions within the past 35years were determined The findings of the study reveal that there has been a great change in the shoreline position in Bonny Island over the past 35years. The Finima beach area was found to have the highest rate of shoreline dynamics. Erosion dominated in this area over accretion. This area recorded a total land area loss of 458.04 hectares of land out which erosion and accretion recorded 280.47 and 177.57 hectares respectively. By this it means erosion claimed

The study further reveals that there have been several displacements of the settlements along the shoreline in the study area due to the high rate of shoreline erosion in the area. This discovery was ascertained from the residents in the Finita-Singi fishing settlement along the Finima land area. Their response agreed with the research findings which showed a large land loss during the 35years period of investigation Generally, the research finding shows that the Bonny shoreline is a highly dynamic one and despite this fact no serious adequate measures has been put in place to regulate this impacts. And this has resulted to large loss of land over the area. The study has shown that geospatial techniques can be effectively used to assess the state of shoreline dynamics in the Bonny Island.

IV. CONCLUSION The study thus far has shown the state of the Bonny shorelines, which is a very dynamic one. The shoreline has been found to be eroding away at an annual rate of 10m-30m along the Finita-Singi beach area. It is therefore pertinent for adequate measures to be put in place to curtail these incessant changes in the shoreline of the Bonny Island. The Bonny Island is an allimportant Island to the Nigerian economy this is because it houses most of the important oil installations upon which the Nigerian Economy depends on. The study has further displayed the capabilities of GIS and Remote

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Sensing techniques in the studies of the ever dynamic Nigerian shorelines.

V. RECOMENDATIONS The Nigerian shoreline is a very dynamic one and for that reason there is the need to pay proper attention to the coastal processes ongoing along our shorelines. With the aim of controlling the impact of human activities that is changing the face of our ever dynamic shoreline. The use of geospatial techniques has proven over the years to be a more effective method of mapping and monitoring of shorelines because of its cost-effectiveness. It is with these problems in mind that the following recommendations are made.  A constant monitoring of the shorelines through geospatial techniques should be setup in Nigeria. This would enable early detection of any unprecedented changes taking place along the shorelines thereby making it possible for early arrest of such changes. Hence a monitoring unit is recommended that would have it as its responsibility to monitor our shorelines.  Funds should be made available for researches on this phenomenon; this would help make data readily available for future projects.  A conscious effort should be employed by the government either by enacting a law to control the activities within the Nigerian Shorelines. There should be an off limit as to where people are permitted to carry out any development project.

[4]

[5]

[6]

[7]

[8]

[9]

[10]

[11]

VI. REFERENCES [1]

[2]

[3]

Arkal, V. H, (2010) Coastal erosion and mitigation methods – Global state of art; Department of Applied Mechanics and Hydraulics, National Institute of Technology Karnataka, Surathkal, Mangalore 575 025, India; Indian Journal of Geo-Marine Sciences Vol. 39(4), December 2010, pp. 521-530. Awosika, L. F. (1992) Coastal erosion in West Africa: causes, effects and response options. Paper presented at an International Conference on the Rational Use of the Coastal Zone (Bordeaux, France, 30 September-3 October). Awosika, L. F. (1993) Coastline erosion in Nigeria and some other West African coastal states: regional approach to response measures. Paper presented at the

[12]

[13]

[14]

3rd Meeting of the Inter-Africa Committee on Oceanography, Sea and Inland Fisheries (Cairo, Egypt, 12-17 April). Balogun, A. P. (1995) Prediction of possible impacts of sea level rise on Victoria Island. MSc Project Report, Department of Surveying, University of Lagos, Lagos, Nigeria. Bird, E.C.F. 2000. Coastal geomorphology: an introduction. Chichester, John Wiley & Sons, 2000. Federal Ministry of Environment 1996, Environmental Impact Assessment of the Bonny Channel Dualisation Project, EIA, 1996. Ibe, A. C. (1990) Global climate change and the vulnerability of the Nigerian coastal zone to accelerated sea level rise: impacts and response measures. A lecture delivered at the 1st Federal Ministry of Science and Technology Monthly Seminar for 1990 (24 January 1990). Ibe, A. C, and Anitia, E. E (1983) Preliminary Assessment of impact of erosion long the Nigerian shoreline; Nigerian Institute for Oceanography and Marine Research; technical paper No.3 Jimmy O.A, Mofoluso F, Godstime J, Ganiyu A, Temi E.O, (2010), An Assessment of Recent Changes in the Niger Delta Coastline Using Satellite Imagery, Journal of Sustainable Development, Vol. 3 December, 2010. NDES, 2000 Hydrological Characteristics of the Niger Delta, Vol.49, NDES 2000, unpublished Scientific Research. Nwilo, P. C. & Onuoha, A. (1993) Environmental impacts of human activities on the coastal areas of Nigeria. In: Coastlines of Western Africa (ed. by L. F. Awosika & O. Magoon), American Society of Engineers. Nwilo, P. C. (1995) Sea level variations and the impacts along the Nigerian coastal areas. PhD Thesis, Environmental Resources Unit, University of Salford, Salford, UK. Pritam, C. and Prasenjit, A. (2010) Shoreline Change and Sea Level Rise Along Coast Of Bhitarkanika Wildlife Sanctuary, Orissa: An Analytical Approach Of Remote Sensing And Statistical Techniques; International Journal Of Geomatics And Geosciences Volume 1, No 3, 2010 Reide D, Walsh J.P, Cowart L, Riggs S.R, Ames D.V, Culver S.J, (2008), Shoreline change within the Albemarle-Pamlico Estuarine System, North Carolina. A white Paper Department of Geological Sciences, Thomas Harriot College of Arts and Sciences and 1Institute for Coastal Science and Policy East Carolina University Rivis, R (2005) Dynamics in Estonia Associated With Climate Change Shoreline

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Scienceand Technology

Comparison of L-moments of Probability Distributions for Extreme Value Analysis of Rainfall for Estimation of Peak Flood Discharge for Ungauged Catchments N. Vivekanandan Central Water and Power Research Station, Pune, Maharashtra, India

ABSTRACT Estimation of Peak Flood Discharge (PFD) at a desired location on a river is important for planning, design and management of hydraulic structures. For ungauged catchments, rainfall depth becomes an important input in derivation of PFD. So, rainfall depth can be estimated through frequency analysis by fitting of probability distributions to the rainfall data. In this paper, the series of annual 1-day maximum rainfall derived from daily rainfall data recorded at Una district is used to estimate the 1-day maximum rainfall adopting six probability distributions. Method of L-moments is used for determination of parameters of distributions. Goodness-of-Fit tests viz., Chi-square and Kolmogorov-Smirnov are applied for checking the adequacy of fitting of probability distributions to the recorded data. Root Mean Square Error (RMSE) is used for the selection of most suitable probability distribution for estimation of rainfall. Based on GoF test results and RMSE values, the study identifies the Extreme Value Type-1 (EV1) is better suited distribution for rainfall estimation. By applying the procedures, as described in CWC guidelines, the 1-hour value of distributed rainfall is computed from the estimated 1-day maximum rainfall using EV1 distribution and adopted for computation of PFD for ungauged catchments. The study suggests the computed PFD from rational formula could be considered for design of flood protection measures for river Swan and its tributaries joining the Beas river basin, Himachal Pradesh.

Keywords: Chi-square, Extreme Value, Kolmogorov-Smirnov, Mean Square Error, Rainfall, Peak Flood I. INTRODUCTION Estimation of Peak Flood Discharge (PFD) at a desired location on a river is important for planning, design and management of hydraulic structures such as dams, bridges, barrages and design of storm water drainage systems. These include different types of flood such as standard project flood, probable maximum flood and design basis flood. In case of large river basins, the hydrological and stream flow series of a significant duration are generally available. However, for ungauged catchments, more data is not available other than rainfall (NIH, 2011). The rainfall data is also of shorter duration and may pertain to a neighbouring basin. Rainfall depth thus becomes an important input in derivation of PFD (Singh et al., 2001). For arriving at such design values, Extreme Value Analysis (EVA) of rainfall is carried out. Out of number of probability distributions, Exponential (EXP), Extreme Value Type-1 (EV1), Extreme Value

Type-2 (EV2), Generalized Extreme Value (GEV), Generalized Pareto (GPA), and Normal (NOR) distributions are generally used in EVA of rainfall (Neslihan et al., 2010). Generally, Method of Moments (MoM) is used for determination of parameters of the distributions. But, the MoM is not giving satisfactory results though the method exists for a longer period. It is sometimes difficult to assess exactly what information about the shape of a distribution is conveyed by its moments of third and higher order; the numerical values of sample moments particularly when the sample is small, can be very different from those of the probability distribution from which the sample was drawn; and the estimated parameters of distributions fitted by the MoM are often less accurate than those obtained by other estimation procedures such as maximum likelihood method, method of least squares and probability weighted moments. To overcome this, the alternative approach, namely L-moments (LMO) is discussed in this paper and also used in EVA of rainfall (Hosking, 1990).

IJSRST151515 | Received: 15 November 2015 | Accepted: 20 November2015 | November-December2015 [(1)5: 35-41]

35

In the recent past, number of studies has been carried out by different researchers on adoption of probability distributions for Rainfall Frequency Analysis (RFA). Topaloglu (2002) reported that the frequency analysis of the largest, or the smallest, of a sequence of hydrologic events has long been an essential part of the design of hydraulic structures. Guevara (2003) carried out hydrologic analysis using probabilistic approach to estimate engineering design parameters of storms in Venezuela. Kumar and Chatterjee (2005) employed the LMO to define homogenous regions within 13 gauging sites of the north Brahmaputra region of India. Di Balldassarre et al. (2006) used the LMO for regionalization of annual precipitation in northern central Italy. Eslamian and Feizi (2007) carried out RFA using monthly maximum rainfall for an arid region in Isfahan Province (Iran) through LMO.

Error (RMSE) is used for the selection of most suitable probability distribution for estimation of rainfall. The objective of the paper is to compute PFD using rational formula for ungauged catchments of Beas River Basin (BRB) upstream of river Swan. The methodology adopted in EVA of rainfall using six probability distributions, estimation of PFD using rational formula, computation of GoF tests statistic and diagnostic index are briefly described in the ensuing sections.

Gonzalez and Valdes (2008) applied LMO for regionalization of monthly rainfall in the Jucar River basin. Yurekli et al. (2009) found GEV and 3-parameter Log-Normal (LN3) distributions (using LMO) as the regional distribution functions for the daily maximum rainfall of Cekerec watershed, Turkey. Gubareva and Gartsman (2010) analysed the extreme hydrometeorological characteristics adopting GEV, GPA, LN3 and Pearson distributions through LMO. Badreldin and Feng (2012) carried out the regional RFA for the Luanhe Basin, Hebei-China by using LMO and Cluster Techniques. But there is no general agreement in applying particular distribution for RFA for different region or country. Moreover, when different distributional models are used for modelling of rainfall data series, a common problem that arises is how to determine which model fits best for a given set of data. This can be answered by formal statistical procedures involving Goodness-of-Fit (GoF) tests and diagnostic index; and the results are quantifiable and reliable.

Theoretical Description of LMO

Qualitative assessment is made from the plots of the recorded and estimated rainfall. For quantitative assessment on rainfall within in the recorded range, Chi-square (2) and Kolmogorov-Smirnov (KS) tests are applied. A diagnostic index, say Root Mean Square

II. METHODOLOGY LMO is analogous to the conventional moments but can be estimated linear combination of order statistics, i.e., by L-statistics. LMO is less subject to bias in estimation and approximate their asymptotic normal distribution more closely in finite samples.

Method of LMO is a modification of the probability weighted moments method explored by Hosking and Wallis (1993). Parameters of the distribution are estimated by equating the sample LMO (lr) with the distribution of LMO (br). In practice, LMO must be estimated from a finite sample. Let R1N  R 2 N...R NN be the ordered sample of size N. The sample LMO is given by: (1)r  k (r  k )! bk 2 k  0 ( k!) ( r  k )! r

lr 1  

… (1)

where, l r 1 is the r+1th sample moment and bk is an unbiased estimator of k with

(i  1)(i  2).....( i  k ) R iN i  k 1 ( N  1)( N  2).....( N  k ) N

b k  N 1 

… (2)

The first two sample LMOs are expressed by:

l1  b0 and l2  2b1  b0

… (3)

Table 1 gives the details of quantile function and parameters six probability distributions considered in the study (Hosking and Wallis, 1997).

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TABLE 1 QUANTILE FUNCTION AND PARAMETERS OF SIX PROBABILITY DISTRIBUTIONS S.No. 1

Distribution EXP

Quantile function (RT) R T  ψ  μ log(1  F)

Parameters by LMO ψ (known); μ  l1

2

EV1

R T  ξ  α log( log F)

ξ  l1  0.5772157 α ; α  l2 / log 2

3

EV2

R T  αe(  ln(  ln( F)) / k

By using the logarithmic transformation of the recorded data, parameters of EV1 are initially obtained by LMO; and used to determine the parameters of EV2 from α  e ξ and k=1/(scale

4

GEV

R T  ξ  α(1   log F ) / k k

parameter of EV1). z  (2 /(3  t 3 )  (ln 2 / ln 3); k  7.8590 z  2.9554 z 2 ; α  l2k /(1  2 k )Γ(1  k ); ξ  l1  (α(Γ(1  k)  1) / k)

5

GPA

R T  ξ  α(1  1  F ) / k k

ξ  l1  l2 (k  2) ; k  (4 /(t 3  1))  3

α  (1  k)(2  k)l2 6

NOR

R T  μ  σφ1 (F)

μ  l1; σ  l 2 π

In Table 1, F(R) (or F) is the cumulative distribution function (CDF) of R; P is the probability of exceedance;

 1 is the inverse of the standard normal distribution function and φ 1  Z P  (P 0.135  (1  P) 0.135 ) / 0.1975 ;

ξ , α , k are the location, scale and shape parameters respectively; µ (or R ),  (or SR) and CS (or ) are the average, standard deviation and coefficient of skewness of the recorded rainfall data; sign(k) is plus or minus 1 depending on the sign of k ; R T is the estimated rainfall by probability distributions corresponding to return period T (in year). Goodness-of-Fit Tests GoF tests are essential for checking the adequacy of probability distributions to the series of recorded rainfall data. Out of a number GoF tests available, the widely accepted GoF tests are 2 and KS, which are used in the study. The theoretical descriptions of GoF tests statistic (Charles Annis, 2009) are as follows: 2statistic: NC

χ2  

j1

O (R)  E (R) j

j

2

... (4)

E j (R )

where, O j (R ) is the observed frequency value of j

th

class, E j (R ) is the expected frequency value of jth class and NC is the number of frequency classes. The

rejection region of 2 statistic at the desired significance level () is given by χ C2  χ12η, NCm1 . Here, m denotes the number of parameters of the distribution and χ C2 is the computed value of 2 statistic by PDF. KS statistic: KS  MaxFe R i   FD R i  N

... (5)

i1

where, Fe R i   M /(N  1) is the empirical CDF of R i and FD R i  is the computed CDF of R i (Zhang, 2002). Here, M is the rank assigned to each R i . If the computed values of GoF tests statistic given by the distribution are less than that of the theoretical values at the desired significance level () then the distribution is found to be acceptable for modelling the series of rainfall data. Diagnostic Index The selection of most suitable distribution for estimation of rainfall is performed through diagnostic index, say RMSE, which is defined by: RMSE = 1 N  R i  R *i  N

2

… (6)

i 1

Here, Ri is the recorded rainfall of ith sample and R *i is the estimated rainfall ith sample by probability distribution. The distribution having the least RMSE is considered as better suited distribution for estimation of rainfall.

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III. APPLICATION In this paper, a study on estimation of PFD for different return periods for 12 catchments of BRB upstream of river Swan is carried out. The estimated 1-day maximum rainfall obtained from the selected probability distribution through GoF tests and diagnostic index is considered as an input to estimate the PFD using CWC guidelines. The Annual 1-day Maximum Rainfall (AMR) recorded at Una district for the period of 20 years from 1995 to 2014, as presented in Figure 1, is used. The descriptive statistics such as

estimation of 1-day maximum rainfall for different return periods. Table 2 gives the 1-day maximum rainfall estimates for different return periods adopting six probability distributions. These estimates were used to develop the rainfall frequency curves and presented in Figure 2.

average rainfall ( R ), standard deviation, coefficient of variation, Coefficient of Skewness (CS) and coefficient of kurtosis of the recorded AMR are computed as 173.0 mm, 70.3 mm, 40.6 %, 0.885 and 0.378 respectively.

IV. RESULTS AND DISCUSSIONS By applying the procedures of LMO of six probability distributions, parameters were determined and used for

Figure 1: Times series plot of recorded AMR

TABLE 2 ESTIMATED 1-DAY MAXIMUM RAINFALL USING SIX PROBABILITY DISTRIBUTIONS Probability Distribution EXP EV1 EV2 GEV GPA NOR

2-year 148.7 161.0 149.1 158.8 156.6 173.0

Estimated rainfall for different return periods 5-year 10-year 20-year 50-year 100-year 221.3 276.1 331.0 403.5 458.4 225.7 268.6 309.7 362.9 402.7 208.9 261.1 323.3 426.5 524.8 223.4 268.4 313.1 373.7 421.0 233.7 278.7 314.6 351.3 372.7 232.1 262.9 288.4 317.1 336.2

Rainfall Frequency Curves (RFCs) The 1-day maximum rainfall estimates obtained from six probability distributions (using LMO) are used to develop the RFCs and presented in Figure 2. From the trend lines of the fitted curves, as presented in Figure 2, it can be seen that there is a perfect line of agreement in the upper and lower tail regions while estimating the rainfall using EV1 distribution for the data under study.

Figure 2: Plots of recorded 1-day maximum rainfall and RFCs using six probability distributions

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Analysis Based on GoF Tests For the present study, the degree of freedom (NC-m-1) is considered as one for 3-parameter distributions (GEV and GPA) and two for 2-parameter distributions (EXP,

EV1, EV2 and NOR) while computing the 2 statistic values for the data under study. The GoF tests results were computed from Eqs. (4) and (5), and given in Table 3.

TABLE 3 COMPUTED AND THEORETICAL VALUES OF GOF TESTS Probability distribution EXP EV1 EV2 GEV GPA NOR

Computed value 2.000 2.000 4.000 2.000 2.500 4.000

2 Theoretical value at 5% level 5.990 5.990 5.990 3.841 3.841 5.990

Computed value 0.149 0.090 0.163 0.091 0.099 0.120

KS Theoretical value at 5% level 0.294 0.294 0.294 0.294 0.294 0.294

From Table 3, it may be noted that the computed values of 2 and KS tests results obtained from six probability distributions are not greater than the theoretical values at 5% level of significance, and at this level, all six distributions are found to be acceptable for modelling the series of AMR recorded at Una district.

the corresponding values of other probability distributions. But, from Figure 2, it can be seen that the rainfall estimates obtained from GPA and GEV distributions are not convincible in upper tail region when compared to the rainfall estimates of EV1 distribution.

Analysis Based on Diagnostic Index

By considering the trend lines of the fitted curves by the probability distributions in the tail regions, it is identified that the EV1 is the most appropriate distribution for estimation of rainfall at Una district, which was also confirmed through GoF tests results.

For the selection of most suitable probability distribution for estimation of rainfall, the diagnostic index, say RMSE values of six probability distributions are computed from Eq. (6) and given in Table 4.

Computation of Peak Flood Discharge TABLE 4 COMPUTED VALUES OF RMSE OF SIX PROBABILITY DISTRIBUTIONS Data RMSE (mm) values using series EXP EV1 EV2 GEV GPA NOR Una 13.6 13.0 17.9 12.8 11.4 19.4

It was required to estimate PFD for 12 catchments of BRB upstream of river Swan. The area of the catchments is presented in Table 5. From an observation of catchment size and at the Google Earth of the region of these catchments it was estimated that these are small catchments that respond quickly to rainfall, tc (time of concentration)  1-hour.

From Table 4, it may be noted that the RMSE values computed from GPA, GEV and EV1 distributions are the first, second and third minimum when compared to

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TABLE 5 CATCHMENT AREA OF DIFFERENT STREAMS S.No. 1 2 3 4 5 6

Name of catchment Babchar Khad Raipur Khad Mundwara Khad Bhatoli Khad Dangah Khad Pithripur Khad

Area (km2) S.No. Name of catchment 3.750 7 Joh Khad 3.125 8 Bangi Khad 4.625 9 Kothi Khad 4.375 10 Jhakhar Khad 7.250 11 Kohwali Khad 12.000 12 Phakruwali Khad

In the absence of the short duration rainfall, say,1-hour, 2-hour, 3-hour, etc., the same was computed from estimated 1-day maximum rainfall by using conversion factors, as given in Central Water Commission (CWC) report entitled „Flood estimation report for Western Himalayas-Zone 7‟ (CWC, 1994). For the present study, the estimated 1-day maximum rainfall is multiplied with the factor of 0.425 to compute the 1-hour value of distributed rainfall and presented in Table 6. TABLE 6 1-HOUR DISTRIBUTED RAINFALL FOR DIFFERENT RETURN PERIODS 1-hour distributed rainfall (I: mm) for 25102050100year year year year year year 68.4 95.9 114.2 131.6 154.2 171.1

Area (km2) 14.500 5.500 7.250 12.250 5.250 3.750

The distributed 1-hour rainfall was used as input for computation of PFD as the catchment areas of different tributaries of BRB are in the range of 3.125 km2 to 14.5 km2. These streams are ungauged and hence the PFD for ungauged catchments is computed by using rational formula, which is given below: q = 0.278 * C I A … (7) 3 where, q is peak discharge (m /s), C is runoff coefficient, I is rainfall intensity (mm/hour) and A is catchment area (km2). By considering topography of the river basin, the value of the C is considered as 0.55 while computing the PFD. The computed PFD for 12 catchments of BRB are presented in Table 7, which could be taken as design flood for the streams.

TABLE 7 PEAK FLOOD DISCHARGE (m3/s) FOR 12 CATCHMENTS OF BRB S. No. 1 2 3 4 5 6 7 8 9 10 11 12

Name of the catchment Babchar Khad Raipur Khad Mundwara Khad Bhatoli Khad Dangah Khad Pithripur Khad Joh Khad Bangi Khad Kothi Khad Jhakhar Khad Kohwali Khad Phakruwali Khad

2-year 39.2 32.7 48.4 45.8 75.9 125.5 151.7 57.5 75.9 128.2 54.9 39.2

5-year 55.0 45.8 67.8 64.2 106.3 176.0 212.7 80.7 106.3 179.7 77.0 55.0

PFD (m3/s) for 10-year 20-year 65.5 75.5 54.5 62.9 80.7 93.1 76.4 88.0 126.5 145.9 209.5 241.5 253.1 291.8 96.0 110.7 126.5 145.9 213.8 246.5 91.6 105.7 65.5 75.5

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50-year 88.4 73.7 109.1 103.2 171.0 283.0 341.9 129.7 171.0 288.9 123.8 88.4

100-year 98.1 81.8 121.0 114.5 189.7 314.0 379.4 143.9 189.7 320.6 137.4 98.1

40

V. CONCLUSIONS The paper describes briefly the study carried out for EVA of rainfall using a computer aided procedure for determination of parameters of six probability distributions (using LMO). The selection of most suitable distribution was evaluated by GoF tests (using 2 and KS) and diagnostic index (using RMSE). By using the maximum value of 1-hour distributed rainfall, runoff coefficient and catchment area of different streams, the PFD for 12 ungauged catchments of BRB were computed through rational formula. The following conclusions are drawn from the study: i) The GoF tests results supported the use of all six probability distributions (using LMO) for modelling the series of AMR. ii) Based on GoF tests results, diagnostic index and rainfall frequency curves, EV1 distribution was found to be most suitable distribution for estimation of 1-day maximum rainfall. iii) The estimated 1-day maximum rainfall was used to compute 1-hour maximum value of distributed rainfall adopting CWC guidelines described in Flood estimation report for Western HimalayasZone 7. iv) By using the 1-hour distributed rainfall, the PFD for 12 ungauged catchments of BRB upstream of river Swan was computed from rational formula. v) The study suggested that the PFD, as given in Table 7, could be considered for design of flood protection measures for river Swan and its tributaries joining the BRB, Himachal Pradesh.

VI. ACKNOWLEDGEMENTS The author is grateful to Dr. S. K. Srivastava, Director In-charge, Central Water and Power Research Station (CWPRS), Pune, for providing the research facilities to carry out the study. The author is thankful to Dr. R. G. Patil, Scientist-D, CWPRS, for the supply of rainfall data.

[2]

[3]

[4]

[5]

[6]

[7]

[8] [9]

[10]

[11]

[12]

[13]

[14]

[15]

[16]

[17]

[18]

VII. REFERENCES [1]

Charles Annis, P.E., Goodness-of-Fit tests for statistical distributions, http://www.statistical engineering.com/ goodness.html], 2009. Central Water Commission (CWC), Flood estimation report for Western Himalayas-Zone 7, CWC Design Office Report No.: WH/22/1994, New Delhi, 1994. Di Balldassarre, G., Castellarin, A. and Brath, A., Relationships between statistics of rainfall extremes and mean annual precipitation: an application for design-storm estimation in northern central Italy, Hydrology and Earth System Sciences, 2006, Vol. 10, No. 2, pp. 589–601. Eslamian, S.S, and Feizi, H,, Maximum monthly rainfall analysis using L-Moments for an arid region in Isfahan Province, Iran, Applied Meteorology and Climatology, 2007, Vol. 46, No. 4, pp. 494-503. Gonzalez, J. and Valdes, J.B., A regional monthly precipitation simulation model based on an L-moment smoothed statistical regionalization approach, Journal of Hydrology, 2008, Vol. 348, No. 1, pp. 27-39. Gubareva, T.S. and Gartsman, B.I., Estimating distribution parameters of extreme hydrometeorological characteristics by L-Moment method, Water Resources, 2010, Vol. 37, No. 4, pp. 437–445. Guevara, E., “Engineering design parameters of storms in Venezuela”, Hydrology Days, pp. 80-91, 2003. Hosking, J.R.M, L-moments: Analysis and estimation of distributions using linear combinations of order statistics, Royal Statistical Society, Series-B, 1990, Vol. 52, No. 1, pp. 105-124. Hosking, J.R.M. and Wallis, J.R., Some statistics useful in regional frequency analysis”, Water Resources Research, 1993, Vol. 29, No. 2, pp. 271-281. Hosking, J.R.M. and Wallis, J.R., Regional frequency analysis: an approach based on L-moments, Cambridge University Press, 1997. Kumar, R. and Chatterjee, C., Regional flood frequency analysis using L-Moments for north Barhamputra region of India, Hydrologic Engineering, 2005, Vol. 10, No. 1, pp. 1–7. National Institute of Hydrology (NIH), Technical note on hydrological process in an ungauged catchment, 2011, pp. 1-163. Neslihan, S., Recep, Y., Tefaruk, H. and Ahmet, D., Comparison of probability weighted moments and maximum likeli-hood methods used in flood frequency analysis for Ceyhan river basin, Arabian Journal of Science and Engineering, 2010, Vol. 35, No. 1, pp. 49-69. Singh, R.D., Mishra, S.K. and Chowdhary, H., Regional flow duration models for 1200 ungauged Himalayan watersheds for planning micro-hydro projects, ASCE Journal of. Hydrologic Engineering, 2001, Vol. 6, No. 4, pp. 310-316. Topaloglu, F., Determining suitable probability distribution models for flow and precipitation series of the Seyhan River basin, Turkish Journal of Agriculture and Forestry, 2002, Vol. 26, No. 1, pp. 189 – 194. Yurekli, K., Modarres, R. and Ozturk, F., Regional daily maximum rainfall estimation for Cekerek Watershed by Lmoments, Meteorological Applications, 2009, Vol. 16, No. 4, pp. 435-444. Zhang, J., Powerful goodness-of-fit tests based on the likelihood ratio, Journal of Royal Statistical Society, 2002,Vol. 64, No. 2, pp. 281-294.

Badreldin, G.H.H. and Feng, P., Regional rainfall frequency analysis for the Luanhe Basin using L-moments and cluster techniques, International Conference on Environmental Science and Development, 5-7 January 2012, Hong Kong, Vol. 1, pp. 126–135.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Students' Perception to Psychological Counselling Services at Omdurman Islamic University in Khartoum State-Sudan Eldood Yousif Eldood Ahmed, 2Husain Abdallah Ahmed, 3Eman Elkheir Awad

1*

1

Department of Special Education, Faculty of Education, University of Jazan-K.S.A. Department of Psychology, Faculty of Arts, University of Omdurman Islamic-Sudan

2,3

ABSTRACT This study was conducted during (2012- 2013) in Omdurman Islamic University, Khartoum State-Sudan. The study aimed to investigating the student perception toward psychological counseling services. Researchers used descriptive methods, by applied psychological counseling services questionnaire which designed by researchers. The community of this study consisted of (950) students. Sample was chosen randomly included (61) students included male (29) and female (32). The researchers used statistical package for social sciences program (SPSS). Also, the researcher used a number of statistical processes which are: T-test for one sample, T-test for independent sample, one way analysis of variance (ANOVA). Finally, the results are following: The level of psychological counseling services according to the view of Omdurman Islamic university student, is significant differences in view of students about psychological counseling services according to the gender, no significant differences in view of students about psychological counseling services according to the place of residence, no relationship between the view of students about psychological counseling services and age variable. Key words: Perception, Psychological Counseling, Counseling Services.

I. INTRODUCTION The study of Chemba (2009) showed that the term “school counseling” broadly refers to the process of meeting the needs of students in several areas of development, such as academic, career, and personal. Experts agree that professional school counseling programmes should be “comprehensive in scope, preventative in design and developmental in nature.” counseling is that while guidance focuses on helping individuals choose what they value most, counseling focuses on helping them make changes”. Geoffrey & et al (2012) showed that counseling maintains a small yet growing presence in Jamaica as a profession. Practitioners are confronted with several societal problems. The authors provide a historical overview of Jamaica and a synopsis of the development of counseling. The emergence of counseling services through the limitations of psychiatry and psychology

sets the stage for current practices and notable involvement of guidance counselors. It is concluded that the continued growth and effectiveness of counseling is dependent on overcoming negative attitudes and economic barriers. Meral (2014) point that investigated the activities of school counselors, their perceptions of collaboration with school staff, and their feelings of efficacy when working as school counselors indicated that classroom and group guidance activities were performed regularly at the schools, especially for personal-social needs and student development. Among the responsive services, individual counseling was the activity in which the most time was spent, followed in order by consultation, crisis counseling, and referrals to outside agencies. In addition, personal-social issues and problems were most common in individual interviews and counseling, followed by educational and career issues. All the school counsellors in the study expressed that they perceived themselves as efficacious and

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attributed this perception to various counselor-related factors. Furthermore. Wyndolyn & et al (2012) indicated seven primary themes perceived by the participants, some of which included their understanding and purpose of professional school counselors and their perceptions of students who received the most support. Janeé & et al (2015) aimed at explored master's-level counseling students' (N = 804) perceptions of training in the Council for accreditation of counseling and related Educational Programs. Indicate that training perceptions and quantitative research attitudes were low to moderate. Qi & et al (2014) found that female students rated school counselors' availability significantly higher than male students did. Also, students who had received prior counseling services rated counselors significantly higher in the following areas than did students who had never received counseling services: knowledge of achievement tests, friendliness and approachability, understanding students' point of view, advocating for students, promptness in responding to requests, ability to explain things clearly, reliability to keep promises, availability, and overall effectiveness. found an interaction effect between gender and use or nonuse of counseling services. In general, students gave positive evaluations of school counselors and were satisfied with counseling services. Delila & et al (2011) participants reported positive feelings toward their school counselors, they identified specific services school counselors can offer them to optimize academic and personal/social performance. The study of Bo Young & et al (2013) attitudes toward counseling had positive effects on their WTP, whereas the year in college and social stigma had negative effects. The results provide policy makers with preliminary evidence of the monetary value of career counseling. The study of Peiwei. L & et al (2013) pointed that controlling for attitudes toward psychological help-seeking and past counseling experience, academic stress was significantly and positively related to willingness to seek counseling for academic problems. The qualitative analyses revealed positive perceptions of counseling as well as a personal reluctance to seek counseling. Renee & et al (2013) suggest student athletes have strong preferences for counselor characteristics, including familiarity with sports, gender, and age. Neeta & et al(2011) indicated no difference in perceptions of career counseling between a holistic career counseling role induction and one that included socialized male perceptions of

counseling. Tracy & et al (2011) revealed that students did not perceive that they were competent or confident conducting career counseling. Mia & et al (2014) pointed that hispanic students are overrepresented at institutions not offering counseling to their students and underrepresented in institutions offering some form of counseling. Yii-Nii (2012) pointed that counselors highlight diverse and multi-channelled counselling services as key to ever-changing students, and emphasize counseling services to match characteristics, leverage strengths, and complement weaknesses of students. In addition, counselors emphasize the importance of advocacy of counseling services and the establishment of a professional image and reputation for university counseling centers. Yilfashewa (2011) showed that students do not have sufficient knowledge on the kind and the extent of guidance counseling services offered in the university campuses. However, about 80 percent of the respondents claimed that they have favorable attitudes toward the guidance counseling services in general. In the study, examination on the differences with respect to certain variables (such as programs, sex, and locality) in perceptions and attitudes toward the guidance counseling services are vigilantly scrutinized. At the end, pertinent suggestions that would assist Ethiopian universities in the sector of guidance counseling are included. Timothy& et al (2013) found that their professional roles continue to be narrowly focused on special education-related activities, such as individualized assessment and eligibility determination. The current study focused specifically on school psychologists' provision of school-based counseling, perceptions of the importance for school psychologists to assume the responsibility of providing school-based counseling services. Sung-Kyung & et al(2014) indicated that working alliance fully mediated the relationship between client expectations of counseling success and counseling outcome. In addition, moderation of counseling expectations by working alliance on counseling outcome was supported. Fred & et al (2010) pointed that college students revealed more positive attitudes toward counseling than did South Asian students. Second, in terms of mediation, increased personal stigma, but not perceived stigma, expressed by South Asians partially mediated and accounted for 32% of the observed difference in attitudes toward counseling services. These findings support a longstanding conjecture in the literature regarding the increased significance of stigma processes on disparities

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in majority-minority help-seeking attitudes. They also suggest that efforts to reduce disparities in attitudes toward counseling for South Asian students specifically should incorporate interventions to reduce the increased stigma expressed by this community, particularly related to a desire for social distance from persons with a mental illness. Jennifer & et al (2014) showed that through in-depth interviews, the authors examined 10 master's-level counseling students' perceptions of gatekeeping. Case analysis resulted in 3 major themes pertaining to the necessity of gatekeeping, vital components, and counseling student characteristics. Brian & et al (2014) investigated college and university counseling center directors' perceptions of the adequacy of the preparation of master's-level counselors for work in college and university counseling centers. Results indicated that counselors were rated on average as prepared; however, many directors had concerns about counselors' ability to work with students presenting more severe mental health issues. Literature Review The study conducted by Nathalie (2010) pointed that the qualitative case study explored teachers' perceptions and attitudes toward counselling services and alternative programs for students with emotional and behavioural disabilities. suggested that counselling is an effective method of educating students with disabilities that allows them to gain social, communication, and problem solving skills. Teachers reported alternative programs as being successful in assuring the high school graduation of this population of students. Alternative programs were found successful when they followed untraditional graduation requirements. Students with emotional and behavioural disabilities who received such services gained confidence, academic success and ameliorated their relationships. Geoff & et al (2014) revealed that self-concealment was negatively related to attitudes toward both f2f and online counselling, while openness to experience and disclosure expectations were positively related. However, whereas self-stigma was associated with negative attitudes toward f 2f counselling, it was not related to attitudes toward online counseling. In addition, disclosure expectations accounted for f 2f attitudes more than online attitudes. Jon & et al (2014) found from the difference of actual pre counseling well-being to current well-being scores. Retrospective methods for assessing pre counselling

functioning are best suited for comparison among clients or counseling processes. Marjorie (2010) explored that teacher attitudes and characteristics relating to recognizing and identifying students' needs for family counselling and their self-reported likelihood to refer them for school-based family counseling services. Blanca (2015) point that a need to improve community college counseling services. Thus, based on the research findings and other published research, this study proposes a set of the following: (a) guidelines for applying cultura (culture) to community college counselling that can assist relationship building between students and counsellors; (b) questions that can be included in students' evaluation of counsellors; (c) counsellor interview questions that may elicit behavioural response and assess cultural competence; and (d) community college students' preferred counsellor characteristics that may be used by hiring committees. Christopher (2011) indicated that after watching a simulated video counselling session students placed greater value in video counselling, felt less discomfort with video counselling, and expected video counseling to be an effective and satisfactory approach. Byrne & et al(2014) pointed that the present study explored the use of counseling among counsellor trainees and the characteristics of consumers and nonconsumers. Approximately 61% of those surveyed reported that they had received counseling, with the majority being mental health counseling trainees. Non consumers indicated that they coped with problems in other ways but would consider counseling if they experienced trauma. Adebayo I. Onabule & et al (2013) pointed that international students experience significant stressors while studying in American colleges and universities, yet they use psychological services far less than domestic students. Factors such as previous experience with counseling, perceived effectiveness of counselling style, and nationality were found to be factors affecting international students' use of counseling services. Mine & et al (2014) indicated that five main themes: counseling Skills, Specific Skills Training Methods, Perceptions of counseling, Being a Counselor Candidate, the Learning and Teaching Process of counseling Skills. The results also showed that within the scope of systematic counseling skills training programs, using various skill training methods and instructional technologies which are integrated compatibly was effective. At the same time, the results indicated that counseling skills training provided an

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increase in professional competency and helped to develop the professional identity of counsellor candidates. Eric & et al (2012)In this qualitative study, eight school counselors participated in a series of reality play counselling trainings introducing techniques appropriate for counselling upper-grade elementary school students to enhance positive relationship building and problem solving skills. Participants were interviewed and their transcripts were analyzed using grounded theory methods which yielded four core categories: positive aspects of perceptions. Walter & et al (2015) demonstrated that being female, teaching at the elementary level, and holding special education certification are predictors of a teacher's positive perception. Sarika & et al (2014) pointed that there were few notable and significant differences in either utilization or perceptions of care, based on sociodemographic or health status characteristics. showing positive perceptions of care suggest that adolescents would be amenable to additional counseling or education services. Ghaleb (2013) pointed that this study examined teachers' attitudes and perceptions toward transition services for students with mild intellectual disability in Saudi Arabia, and also examined the relationship between teachers' attitudes regarding transition services for students with mild intellectual disability and teachers' gender and educational background. The findings indicated that teachers hold positive attitudes toward transition services. Also, this study found no differences in teachers' attitudes based on their gender. Bong & et al(2014) indicated that international students underutilized counselling services in all but one year examined, more female international students used the service than males, the majority of international students who did access counseling services were Asian, and the majority of students who accessed services kept appointments after intake sessions. Limitations and implications of the study are discussed. Lagena (2010) indicated that there is a need for further student training in career transition from the community college to employment. Results from this study indicate that the majority of community college students who responded perceive that more career counseling services would assist them in their transition into the world of work after graduation. Kathleen(2012) investigated differences in perceptions of heterosexual dating IPV and help-seeking recommendations for a friend as a function of scenario type (male perpetrator/female

victim and female perpetrator/male victim) and participant sex. The study also examined gender role attitudes and attitudes toward dating violence that have been associated with perceptions of dating showed that women were more likely than men to hold more egalitarian gender role attitudes, be less accepting of dating violence, perceive the behaviours in the dating scenario as more serious, and be more likely to recommend that a friend seek help at the counselling center. Sibel & et al (2012) pointed that positive contribution of the technology and the importance of counseling services were wished to be indicated. School counselling services were conducted to illustrate the importance of online counselling services in the study. and qualitative data analysis was done according to Thematic analysis. Nationality, Gender differences, school counsellors views about online counseling services, school counsellors students' numbers and academicians' views about online counseling services are significant variables for the study. The findings indicate that online counselling services are essential for school environment to make contribution and to provide more services to students about school counseling services. Joshua (2006) pointed that the perceptions of counselling services held by student-athletes might be changing. Time management continues to be a factor in not seeking counseling help for many student-athletes while perceptions of others and social stigma appear to be less important factors for student-athletes than they may have been in the past. Ashley & et al (2014) indicated that these services are underutilized. Perceptions have been linked to therapeutic outcomes and may potentially serve as barriers to treatment. The results of the present study illustrate a range of perceptions and highlight the value of educating future consumers and practitioners about the roles of various MHSPs in providing mental health services. Future research is proposed. Ginger & et al (2008) showed that student perceptions of program cultural ambience predicted positive cognitive attitudes toward racial diversity. Participatory instructional strategies predicted positive affective attitudes toward racial diversity. Eunju & et al (2008) indicated less exposure to counseling, less self-perceived need for counselling, greater discomfort/shame with counselling, less openness to counseling, a greater preference for a directive style, and a greater preference for a flexible counseling format. Language and cultural concerns were barriers to seeking counselling. Maynard & et al (1997) indicate that

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scenarios depicting a 15-year-old were rated as less abusive, and less responsibility was attributed to the adult, relative to vignettes involving a 7-year-old. Respondents also rated scenarios depicting opposite-sex interactions as less abusive relative to scenarios describing same-sex interactions. When vignettes depicted a 15-year-old, less blame was attributed to the adult relative to when vignettes depicted a 7-year-old with an adult of either sex, with the least amount of blame being attributed to the adult involved with an adolescent of the opposite-sex. Gender-role attitudes were not significantly related to ratings of abusiveness or attributions of responsibility and blame. Banikiotes& et al(1981) show that (a) S's ratings of comfort in disclosing was greater with female rather than male and with egalitarian rather than traditional Cs, (b) female egalitarian Cs were perceived as most expert, whereas female traditional Cs were perceived as least expert, and (c) male traditional Cs were perceived as least trustworthy. The presence of C gender and C sex role effects and the absence of effects as a function of problem type and Ss' sex role orientation are discussed. Nelson (1933) pointed that most effect sizes for gender have been small to moderate. A social psychological model of gender differences that might inform the research on counselling process and outcome is presented. Nagalakshmi & et al (2002) revealed that patients' positive perceptions of their counsellors. Bett & et al (2013) found that the perception of head teachers and teacher counsellors on the effectiveness of peer counselling among students was negative. It also found that the designation and gender of an individual does not influence their perceptions. Beidoğlu & et al (2015) revealed that the school counsellors had overall positive opinions about the use of ICT in school counselling. No significant differences were found according to gender and age. The study conducted by Repetto (2002) pointed that the first dimension relates to the attitudes of counsellors and beliefs concerning race, culture, ethnic groups, gender and sexual orientations; the need to assess prejudices and stereotypes and to develop counselling that is positive towards multiculturalism, and the way in which the values and thoughts of counsellors can affect the counselling and therapy, positive concept of self and of self-esteem, as well as the development of inter-personal relationships and mutual respect amongst students from different backgrounds. Christopher &et al (2001) expected that men who were gender-role conflicted had negative

reactions to all 3 treatment formats. Janet & et al (1989) showed that the average difference between ratings of men and women is negligible. Furthermore, although the effect sizes are not homogeneous. Ojeda & et al (2011) indicated that perceived educational barriers significantly predicted students' educational aspirations above and beyond the influence of gender, generation level, and parents' education level. Aims of Study The aims of this study to a. Explore the level of psychological counseling services according to the view of Omdurman Islamic university student. b. Know the differences in view of students about psychological counseling services according to the gender. c. Know the differences in view of students about psychological counseling services according to the place of residence. d. Know the relationship between the view of students about psychological counseling services and age variable. Question of Study 1. The question of this study, to verify their aims by answer following question are: 2. What the level of psychological counseling services according to the view of Omdurman Islamic university student? 3. What the differences in view of students about psychological counseling services according to the gender? 4. What the differences in view of students about psychological counseling services according to the place of residence? 5. What the relationship between the view of students about psychological counseling services and age variable?

II. METHODS AND MATERIAL 2.1 Method Research Approach: In a study, the researchers used descriptive method, depend on analytical technique. In addition, were consists of questionnaire adapted by the researcher.

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2.2 Study Group: It formed from male and female student in Omdurman Islamic university, Khartoum state, Sudan (800) of male and female student in Omdurman Islamic university. 2.3 Sampling: The researchers used a simply random sampling method. The sample was consist of (61) student in Omdurman Islamic university.

greater than the sig value (0.05), this is means that the level of psychological counselling services among of Omdurman Islamic university student is significant. Table 1. Showed the level of psychological counselling services according to the view of Omdurman Islamic university student. Variable

Mean Standard

Means

In order to ensure the validity and reliability of the questionnaire form, it distributed to four instructors who had completed their doctorates and this form developed in accordance with the opinions of the instructors, then pilot were conducted and the value of reliability was found. It was about (0.90) and after that, the questionnaire forms became ready for application. 2.5 Practical Procedures:

Counseling Services

70

T

Sig

value

2.4 Supervisors-Questionnaire Techniques: The questionnaire was prepared by the researchers, is formed from (20) phrases distributed into two types positive and negative phrases.

Std

58.2

12.5 36.4

0.00

3.2 What the differences in view of students about psychological counselling services according to the gender? To answer this question, the researcher used (T) test for independent sample, table (2) shows the result. When we compare the mean of male (57.7), with mean of female (58.7). I found the mean is greater than standard mean and the significant level (0.76) is greater than the sig value (0.05), this is means no significant differences of psychological counselling services according to the gender variable.

The principle of voluntarism was the pre-condition of participating in questionnaire. For the questionnaire, an explanation was prepared. The goal of the research and Table 2. Showed the differences in view of students how the study would be carried out were clearly stated about psychological counselling services according in it. In addition, it was emphasized that the identities of to the gender the participants would remain confidential. During the questionnaire, written forms were used. Questionnaire Variable N Mean Std T Value df sig took place between 1-2 weeks, and the researcher used mail 29 57.7 14.4 -0.31 59 0.8 E-mailing technique to answering the questionnaire. 2.6 Data Analysis:

female

After collecting data, the researcher used: T- test for one sample, T-test for independent samples test, one way analysis of variance (ANOVA) and pearson correlation coefficient, to examine the study hypotheses depend to SPSS program.

III. RESULTS 3.1.What the level of psychological counselling services according to the view of Omdurman Islamic university student? To answer this question, the researcher used (T) test for one sample, table (1) shows the result. When we compare the mean respectively (58.18), with standard mean (70). Researchers found the mean is greater than standard mean and the significant level (0.00) is

32

58.7 10.7

3. 3 What the differences in view of students about psychological counselling services according to the place of residence? To answer this question, the researcher used pearson correlation, table (3) shows the result. When we compare the city value (58.10), with village level (56.69). I found the it , greater than significant level (0.05), this is means that no significant differences of psychological counselling services according to the place of residence. Table 3. Shows the differences in view of students about psychological counseling services according to the place of residence.

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Variable

N

Mean

Std

city

43

58.10 12.86

village

16

56.69 10.04

T Value

df

sig

0.64

59

0.5

3.4 What the relationship between the view of students about psychological counselling services and age variable? To answer this question, the researcher used pearson correlation, table (3) shows the result. When we compare the correlation value (0.23), with standard sigma level (0.08). I found the mean is greater than significant level (0.05) this is means that, no relationship between psychological counselling services and age variable. Table 4. Showed the relationship between the view of students about psychological counselling services and age variable Variable Counselling & age

Correlation value 0.23

Sig 0.08

IV. DISCUSSION When the researcher analysed the data the results are as following: 1. The level of psychological counseling services among Omdurman Islamic university student is positive, this means psychological counseling services is good. This result is On line many studies. Walter & et al (2015) indicated that female, teaching at the elementary level, and holding special education certification are predictors of a teacher's positive perception. Qi & et al (2014) students gave positive evaluations of school counselors and were satisfied with counseling services. Nathalie (2010) pointed that counseling is an effective method of educating students with disabilities that allows them to gain social, communication, and problem solving skills. Bo Young & et al (2013) pointed that attitudes toward counseling had positive effects on their WTP. Brian & et al (2014) indicated that teachers hold positive attitudes toward transition services. Ginger & et al (2008) showed that student perceptions of program cultural ambience predicted positive cognitive attitudes toward racial diversity. Joshua(2006) suggested that the perceptions of counseling services held by studentathletes might be changing. Eric& Mary A. Clark (2012)Indicate that positive aspects of perception of counseling. Eunju& et al (2008) indicated less exposure to counseling. Marjorie (2010) indicated that teacher attitudes and characteristics relating to recognizing and

identifying students' needs for family counseling and their self-reported likelihood to refer them for schoolbased family counseling services. Delila &et al (2011) indicate that positive feelings toward their school counselors. Peiwei & et al (2013) positive perceptions of counseling as well as a personal reluctance to seek counseling. Byrne & et al (2014) showed that systematic counseling skills training programs are integrated compatibly was effective, an increase in professional competency and helped to develop the professional identity of counselor candidates. Christopher (2011) Mine & et al(2014) indicate that perceptions of counseling was effective. Amita (2014) indicated that perceptions have been linked to therapeutic outcomes and may potentially serve as barriers to treatment. Nagalakshmi & et al (2002) revealed that patients' positive perceptions of their counselors. Beidoğlu & et al (2015) revealed that the school counselors had overall positive opinions about the use of ICT in school counseling. Repetto (2002) pointed that the need to assess prejudices and stereotypes and to develop counseling that is positive towards multiculturalism. Neeta & et al (2011) indicate that influence of role induction on men's perceptions of career counseling and attitudes toward seeking professional help. Disagreement the study conducted by, Janeé & et al (2015) indicate that Training perceptions and quantitative research attitudes were low to moderate. Sigilai (2013) found that the perception of head teachers and teacher counselors on the effectiveness of peer counseling among students was negative. Bett & et al (2013) found that the perception of head teachers and teacher counselors on the effectiveness of peer counseling among students was negative. Mia & et al (2014) Hispanic students are overrepresented at institutions not offering counseling to their students and underrepresented in institutions offering some form of counseling. Yilfashewa (2011) indicate that students do not have sufficient knowledge the extent of guidance counseling services offered in the university campuses. However, about 80 % of the respondents claimed that they have favorable attitudes toward the guidance counseling services in general. Tracy & et al (2011) revealed that students did not perceive that they were competent or confident conducting career counseling. Renee & et al (2013) point that student athletes have strong preferences for counselor characteristics. Geoff & et al (2014) Indicate that negative attitudes toward counseling, it was not related to attitudes toward online counseling. Bett & et al (2013) found that the perception of head teachers and teacher counselors on the effectiveness of peer counseling among students was negative. 2. There is no significant differences in view of students about psychological counseling services according to

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the gender. On line The study conducted by Ghaleb (2013) indicate that no differences in teachers' attitudes based on their gender. Bett & et al (2013) found that the gender of an individual does not influence their perceptions. Maynard & et al (1997) indicate that Gender-role attitudes were not significantly related to ratings of abusiveness or attributions of responsibility and blame. Christopher & et al (2001) expected that men who were gender-role conflicted had negative reactions to all 3 treatment formats. Nelson, Mary(1933) pointed that most effect sizes for gender have been small to moderate. A social psychological model of gender differences that might inform the research on counseling process and outcome is presented. In addition this result is not agreed the study of, Banikiotes & et al (1981) showed the presence of counseling gender effects as a function of problem type. Qi & et al (2014) indicated that female students rated school counselors' availability significantly higher than male students did in addition point that an interaction effect between gender and use or nonuse of counseling services. Yilfashewa (2011) indicated that differences with respect to in perceptions and attitudes toward the guidance counseling services according to sex. Robert & et al (2014) indicated that more female international students used the service than males, the majority of international students who did access counseling services were Asian, and the majority of students who accessed services kept appointments after intake sessions. Kathleen (2012) showed that women were more likely than men to hold more egalitarian gender role attitudes. Walter &et al (2015) demonstrated that being female, teaching at the elementary level, and holding special education certification are predictors of a teacher's positive perception. Janet& et al (1989) showed that the average difference between ratings of men and women is negligible. Beidoğlu & et al (2015) pointed that no significant differences were found according to gender. Repetto (2002) specialists in the subject consider that multiculturalism should include differences based on gender. Sibel & et al (2012) indicate that counseling services are significant differences according to the gender variable. 3. There are significant differences in view of students about psychological counseling services according to the place of residence (culture). On line the study conducted by Shali & et al (2007) showed that the effect of this cultural difference in focus on how people remember and perceive. Repetto (2002) pointed that multiculturalism should include differences based on levels of acculturation, as well as the development of inter-personal relationships and mutual respect amongst students from different backgrounds. Gašević (2015) indicate that the respondents were in the action stage had exhibited a lesser level of resistance to treatment.

4. no relationship between the view of students about psychological counselling services and age variable. On line the study conducted by Renee & et al (2013pointed that student athletes have strong preferences for counsellor characteristics, including age. Beidoğlu & et al (2015) indicate that no significant differences were found according to age. Repetto (2002) indicate that multiculturalism should include differences based on age. Finally: As to realize the students not to the availability of psychological counselling services, researcher believe on the importance of the availability of psychological counselling services at universities, which confirms the help of psychological counselling centers in the treatment of students' problems and academic, emotional, social, and related psychological stability on campus, which is reflected a negative impact on academic performance, and academic achievement. In addition researcher fund it natural that the sexes need for psychological counselling services desperately and very an urgent as a result of the size of the problems facing the student at the university level. In addition researcher pointed that age is an impact on the nature of the students' perception of the availability of psychological counselling services, and the reason for that older students understand the importance of psychological counselling more than others. V. CONCLUSION This study was conducted during (2012- 2013) in Omdurman Islamic University, Khartoum State- Sudan. The study aimed to investigating the student perception toward psychological counseling services. Finally, the results are following: The level of psychological counseling services according to the view of Omdurman Islamic university student, is significant differences in view of students about psychological counseling services according to the gender, no significant differences in view of students about psychological counseling services according to the place of residence, no relationship between the view of students about psychological counseling services and age variable.

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VI. REFRENCES [15] [1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Engineering and Technology

Bidirectional Speed Control of DC Motor Based on Pulse Width Modulation using Microcontroller Ayman Y. Yousef*1, M. H. Mostafa2

1

Electrical Engineering Department, Faculty of Engineering at Shoubra, Benha University, Cairo, Egypt 2 Distribution Sectors, South Cairo Electrical Distribution Co., Cairo, Egypt

ABSTRACT This paper presents a design, simulation and implementation of Pulse Width Modulation (PWM) speed control system of DC motor using microcontroller (MCU). The PIC16F877A microcontroller is programmed to generate two periodic PWM signals from its Capture/Compare/PWM (CCP) modules. These output PWM signals from MCU with various duty cycle are used to controlling the speed and direction of DC motor through L293D driver chip which is used as an interface between MCU and DC motor. The PIC MCU has been programmed using flowcode software package and the complete PWM control system model has been simulated using proteus design suite software package. A hardware setup has been practically implemented for the proposed control system in order to check the simulation results and which were acceptable and satisfactory. Keywords: PIC Microcontroller, PWM Technique, CCP Module, Duty Cycle, DC Motor Driver.

I. INTRODUCTION DC motor drives are used for many speed and position control systems where their excellent performance, ease of control and high efficiency are desirable characteristics [1, 2]. The rotational speed of a DC motor is directly proportional to the mean (average) value of its supply voltage which applied to the motor terminals and by increasing this value up to its maximum value, the motor can rotate faster. Pulse-width modulation (PWM) is a digital technique used in many industrial applications mostly for controlling the motor speed by varying the amount of power delivered to the DC motor. In other words by increasing the voltage applied to the motor its speed will increases.

Figure 1: PWM time duration

The PWM means varying the ratio between the "ON" (tON) time and the "OFF" (tOFF) time durations, which called the "Duty Cycle". Then by varying the width of pulse, the motor voltage and hence the power applied to the motor can be controlled as shown in Fig. 1 which shows the ON and OFF time of simple PWM signal. The pulse period is given by:

T  TON  TOFF

(1)

Where: T is the Pulse period, TON is the ON time = Pulse width, and TOFF is the OFF time. The duty cycle is defined by the ratio of the pulse width to pulse period as:

Duty cycle 

Pulse width Pulse period

(2)

Duty cycle 

TON TON  T TON  TOFF

(3)

If the rated supply voltage of the DC motor is Vs, then the average DC output voltage fed to the motor is given by:

IJSRST151518 | Received: 18 November 2015 | Accepted: 23 November 2015 | November-December 2015 [(1)5: 52-60]

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Vaverage  Duty cycle  Vs

(4)

Therefore, the motor speed can be controlled with regularly adjusting the time of turn-on and turn-off in order to changing the average value of the motor voltage Vav and then the rotational speed of the motor can be varied. Figure 2 illustrate the timing diagram of the PWM signals for various duty cycles with supply voltage of 12V. The motor speed is slow, medium and fast with duty cycle 25%, 50%, and 75% respectively.

These modules can support PWM signals by initializing the control register and duty-cycle register. The CCP1 and CCP2 modules are identical in operation, with the exception being the operation of special event trigger. Table. 1 show the resources and interactions of the CCP modules. TABLE I CCP MODE -TIMER RESOURCES REQUIRED

CCP Mode Capture Compare PWM

Timer Resource Timer1 Timer1 Timer2

The operation of a CCP module is described with respect to CCP1, whereas CCP2 operates the same as CCP1 except where noted [4]. The CCP1 Module is comprised of two 8-bit registers: CCPR1L (low byte) and CCPR1H (high byte). The CCP1CON register controls the operation of CCP1 module as shown in Fig. 3.

Figure 2: PWM Signals with Different Duty Cycles There are three methods could achieve the adjustment of duty cycle [ 3 ]: (a) Adjust frequency with fixed pulsewidth. (b) Adjust both frequency and pulse-width. (c) Adjust pulse-width with fixed frequency which is the method chosen in this work depending on the PWM module embedded in a PIC 16F877A microcontroller. Figure 3: Block diagram of PWM mode of CCP1 module.

II. Generation of PWM using PIC16F877A The PIC16F877A has two Capture/Compare/PWM (CCP) Modules [4]. Each module (CCP1 and CCP2) contains a 16 bit register (two 8-bit registers) and can operate in one of the three different modes as:

Also, the CCP2 Module is comprised of two 8-bit registers: CCPR2L (low byte) and CCPR2H (high byte). The CCP2CON register controls the operation of CCP2 module. The special event trigger is generated by a compare match and will reset Timer1 and start an A/D conversion (if the A/D module is enabled) [4].

• 16-bit Capture register • 16-bit Compare register • PWM Master/Slave Duty Cycle register

In Pulse Width Modulation mode, the CCP1 or CCP2 pins produces up to a 10-bit resolution PWM output.

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Since the CCP1 pin is multiplexed with the PORTC data latch, the TRISC<2> bit must be cleared to make the CCP1 pin an output. Clearing the CCP1CON register will force the CCP1 PWM output latch to the default low level. This is not the PORTC I/O data latch [5]. The PWM period is specified by writing to the PR2 register and has a time base (period) and a time that the output stays high (duty cycle) [6] as shown in Fig. (4). The frequency of the PWM is the inverse of the period (1/period).

Figure 4: Microcontroller PWM output

III. DC Motor Driver In order to control the DC motor, the motor armature winding must be driven by signals which are generated by the PIC16F877A microcontroller. Since the PIC microcontroller input and output ports terminals do not source a sufficient current to the motor therefore, an integrated power driver is used. A simple and low cost L293D device was chosen to drive a small DC motor. The pin assignment and the internal schematic diagram of L293D IC device are shown in Fig. 5 and Fig. 6 respectively.

Figure 6: Internal L293D schematic diagram The L293D driver consist of four channel driver or dual H-Bridge channel and can be used to drive four motors in one direction only, or two motors bidirectional. The chip has a built-in freewheeling diodes to protect the circuit from the back EMF [7] . it can drive a motor with a maximum output voltage of 36v. It has output current of 600mA and peak output current of 1.2A per channel and 5 kHz switching frequency. It has two control inputs, one enable input and one output per each channel. The pins EN1, IN1, IN2, OUT1 and OUT2 control one of the motors while the pins EN2, IN3, IN4, OUT3 and OUT4 control the other if the driver used to control two motors. The Control inputs are used to control the direction while the enable input is used for turn the bridge ON or OFF. In addition, it has four ground center pins connected together and used as a heat sink. The device must be powered by two supply voltage; the first is the external voltage supply which also drives DC motor up to 36V and the other is +5V which is the logic supply voltage to control the IC.

IV. Control System Strategy The proposed control strategy based on PWM technique using PIC microcontroller and the L293D driver chip is shown in Fig. 7 .

Figure 5: L293D pin assignment diagram

Figure 7: Proposed PWM control strategy

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The operation of the H-Bridge is fairly simple by Identify the logic state of Enable 1, Input 1, and Input 2 pins. Enable 1 pin is responsible for the motor turn on and off, while the Input pins are used to change the speed direction of the motor by changing the voltage across its terminals. For example, if Enable 1, Input 1pins are in HIGH state, and Input 2 pin in the LOW state, the motor will rotate clockwise. On the other hand, if Enable 1, Input 2 pins are in HIGH state, and Input 1 pin in the LOW state, the motor will turn to the other direction. If Input pins are both at the same level and the Enable pin is high then the motor will stall (or break) and with the Enable pin is low the motor will freewheel. Therefore, the idea of the control depends upon the two control inputs connected to the driver channel, when the microcontroller sends a logic value 1 to the motor it will start running in a certain direction, and when the logic value is 0 it will inverse the direction. The behavior of the DC motor for various input conditions are as in the following truth table 2. TABLE II MOTOR BEHAVIOUR WITH VARIOUS INPUT CONDITIONS Motor status

Input 1

Input 2

Motor Stops or brake

Low

Low

Motor Runs (Anticlockwise)

Low

High

Motor Runs (clockwise)

High

Low

Stops or brake

High

High

V. PWM Control System Description The proposed schematic diagram of the PWM control of DC motor is designed and simulated by Proteus 7.10 professional software package. The circuit is consists of the PIC16F877A microcontroller which is the main control element of the implemented control system and other electric and electronic devices as shown in Fig. 8.

Figure 8: Schematic diagram of the PWM control of DC motor designed by Proteus software A digital LCD (4x16) connected to port B and one 7segment unit connected to port D are used to display the details of DC motor control modes of operation. The PIC will generate the PWM signals from CCP1 and CCP2 modules at port C (RC2 and RC1) to drive the DC motor and control its speed. The motor driver chip L293D is interfaced with PIC microcontroller pin RC2 and RC1 at its input terminals IN1and IN2 while its EN1 pin is connected to pin RC7 at HIGH state signal constantly. Two push button switches (button1and button2) are used to select the direction of rotation (clockwise or anticlockwise) of the DC motor. Another push button switch (button 3) is used to make the motor in brake mode. Two toggle switches (switch 4 and switch 5) are used to increase/decrease the DC motor speed. The DC motor is connected to the output pins (OUT1 and OUT2) of the L293D driver chip. A 5V/12V DC power supply is used to drive the PIC microcontroller and L293D chip by 5V, and the DC motor by 12V.

VI. Software Algorithm Implementation The software and control algorithm of the implemented PWM control system was developed using Flowcode software package. Flowcode is graphical programming software which is used to programming the PIC microcontroller. Flowcode software contains a tool to compile the designed flowchart to the hexadecimal (HEX) file. This HEX file is loaded in the

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microcontroller RAM in order to execute the control system. The software implementation of the control algorithm consists of main routine and a group of subroutines as shown in Fig. 9.

Figure 9: Structure of software implementation The program of main routine shown in Fig.(10) started by configuring the PIC microcontroller and loading it by the necessary system codes, its initialization and also call the start routine to display the motor status. The right and left direction routines are programed to generate the two PWM signals having duty cycle changing from 0 to 100% with period equals 4ms and frequency equals to 244 Hz by using of CCP1 and CCP2 PWM modules of the PIC microcontroller. These two PWM modules are configured as output pins and the PWM period is specified by writing to the PR2 register. The duty cycle 1 of the clockwise direction (right mode) and duty cycle 2 of the anticlockwise direction (lift mode) are stored in the microcontroller EEPROM. Two analogue to digital converter channels (ADC1 and ADC2) of the microcontroller are used to set the output at the target level by incrementing or decrementing the duty cycle values.

Figure 10: flowchart of the developed control algorithm. The simulation of the PWM control system with the different modes of operation using flowcode software is shown in Fig. 11. The right direction mode is simulated at duty cycle 1 equals 65% of PWM period using CCP1 module. The lift direction mode is simulated at duty cycle 2 equals 85% of PWM period using CCP2 module. The brake mode is simulated at duty cycle 3 equals 100% of PWM period using CCP1and CCP2 modules.

The duty cycle 1 is specified by writing to the CCPR1L register for CCP1 module and also the duty cycle 2 is loading to the CCPR2L register of CCP2 module. The brake mode is programed to load the CCPR1L register and CCPR2L register by duty cycle 3 which is equal to 100% of the PWM period.

Figure 11a: Start mode (CCP1 and CCP2 modules with Duty cycle = 0)

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The minimum hardware development setup of the bidirectional PWM control system of DC motor having rated voltage V =12V and current I=0.5A. is shown in Fig. 12.

Figure 11b: Right direction mode (CCP1 module with Duty cycle 1 = 65%)

Figure 12: Photograph of hardware setup connection of PIC16F877A based PWM control system of DC motor The practical implementation of the three modes of operation (right, lift, and break) of the PWM control system of DC motor with LCD, 7-segment display, L293D driver is shown in Fig. 13. Figure 11c: Lift direction mode (CCP2 module with Duty cycle 2 = 85%)

Figure 13a: Right direction mode Figure 11d: Brake mode (CCP1 and CCP2 modules with Duty cycle 3 = 100%) Figure 10: Simulation of PWM control system on flowcode software panel

VII.

Hardware System Implementation

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Figure 13b: Lift direction mode

Figure 14a: Output signals at duty cycle 25% Horizontal: 1 msec/div. Vertical; 5 volt/div. Upper Trace: PWM signal. Lower Trace: Terminal voltage (Vav = 3V).

Figure 13c: Brake direction mode Figure 13: Photograph of hardware setup connection of PWM control system with different modes of operation.

Figure 14b: Output signals at duty cycle 50% Horizontal: 1 msec/div. Vertical; 5 volt/div. Upper Trace: PWM signal. Lower Trace: terminal voltage (Vav = 6V).

VIII. Simulation and Excremental Results The simulation results of the digital PWM signals with period of 4ms and frequency of 244 Hz generated from PIC16F877A microcontroller of the proposed control system of DC motor using proteus software package are shown in Fig. 14. The output PWM signals and the corresponding DC motor terminal voltage for various values of duty cycle are shown also in Fig. 13. The chosen values of 25%, 50%, 75%, and 100% duty cycles gives motor terminal voltage as average values equals 3V, 6V, 9V, and 12V respectively.

Figure 14c: Output signals at duty cycle 75% Horizontal: 1 msec/div. Vertical; 5 volt/div. Upper Trace: PWM signal.

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Lower Trace: terminal voltage (Vav = 9V).

Figure 14d: Output signals at duty cycle 100% Horizontal: 1 msec/div. Vertical; 5 volt/div. Upper Trace: PWM signal. Lower Trace: terminal voltage (Vav = 12V).

Figure 15b: PWM signal at duty cycle = 50% Horizontal: 2 msec/div. Vertical; 10 volt/div.

Figure 13: PWM signals and DC motor terminal voltage at various values of Duty cycle. The hardware oscilloscope results of PWM signals with the same period and frequency at different values of PWM duty cycle are shown in Fig. 15.

Figure 15c: PWM signal at duty cycle = 75% Horizontal: 2 msec/div. Vertical; 10 volt/div.

Figure 15a: PWM signal at duty cycle = 25% Horizontal: 2 msec/div. Vertical; 10 volt/div.

Figure 15d: PWM signal at duty cycle = 100% Horizontal: 2 msec/div. Vertical; 10 volt/div.

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Figure 15: Photograph of PWM signals at various values of PWM duty cycle.

IX. CONCLUSION This paper has covered the design, simulation and practical implementation of a low-cost bidirectional speed control of DC motor based on PWM technique using PIC16F877A MCU. The PWM channels of the PIC microcontroller with its embedded CCP modules has been programed to generate two digital PWM signals with period 4ms and frequency of 244 Hz. The proposed control system model can control the DC motor speed and direction by varying the duty cycle of the output PWM signals. A dual H-Bridge channel built in L293D device was chosen to drive a DC motor and also used as interface between it and MCU. The PIC16F877A MCU can integrate all required functions in its single chip and therefore, it reduces the hardware setup of the overall control system. A very good agreement was achieved between the experimental and simulation results.

[6] Pallavi Papalkar and S. P. Phulambrikar, “Speed Control of DC Motor using Capture/Compare/Pulse Width Modulation Module of PIC Microcontroller” International Journal of Engineering Research & Technology,Vol. 3, Issue 9, September- 2014 [7] Push-Pull Four Channel Driver with Diodes, L293D Datasheet. [8] Shinde Krishnat Arvind, Tarate Akshay Arun, Taur Sandip Madhukar, and Prof. Jayashree Deka “Speed Control of DC Motor using PIC 16F877A Microcontroller” Multidisciplinary Journal of Research in Engineering and Technology, Volume 1, Issue 2, July- 2014 [9] Taiqiang Cao, Jianping Xu, and Shungang Xu,“ Designing DSP Based Digital Control DC Motor System ” IEEE Proceedings 2008.

X. REFERENCES [1] Sabedin A. Meha, Besnik Haziri, Loreta N. Gashi, and Behar Fejzullahu “Controlling DC Motor Speed using PWM from c# windows Application ” 15th International Research/Expert Conference” Trends in the Development of Machinery and Associated Technology, TMT 2011, Prague, Czech Republic, 12-18 September 2011. [2] Bharat Joshi, Rakesh Shrestha, and Ramesh Chaudhar “Modeling, Simulation and Implementation of Brushed DC Motor Speed Control Using Optical Incremental Encoder Feedback” Proceedings of IOE Graduate Conference, 2014. [3] Yue-Li Hu, and Wei Wang “Design of PWM Controller in a MCS-51 Compatible MCU ” IEEE Proceedings of (HDP’07) 2007. [4] PIC Microcontroller Instruction Sets, PIC16F877A Datasheet. [5] A.S.M. Bakibillah, Nazibur Rahman, Md. Anis Uz Zaman, “Microcontroller based Closed Loop Speed Control of DC Motor using PWM Technique” International Journal of Computer Applications Volume 108 – No 14, December 2014.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Engineering and Technology

A Review on Analysis of Friction Stir Welding Process of Steel Vikash, Gopal Sahu, Prakash Kumar Sen, Ritesh Sharma, Shailendra Bohidar Department of Mechanical Engineering, Kirodimal Institute of Technology, Raigarh Chhattisgarh, India

ABSTRACT Friction Stir Welding (FSW) is a solid state welding method and is common for aluminium alloys Friction Stir Welding is a novel green solid state joining process particularly used to join high strength aerospace aluminium alloys. This review paper addresses the overview of Friction stir welding which includes the basic concept of the process, microstructure formation, influencing process parameters, typical defects in FSW process and some recent applications. These welded joints have higher tensile strength to weight ratio and finer micro structure. FSW of aluminium alloys have the potential to hold good mechanical and metallurgical properties. This paper gives the review of basic concepts of Friction Stir Welding on tool design, mode of metal transfer and process parameters. It is demonstrated that FSW of aluminium is becoming an increasingly mature technology with numerous commercial applications. Keywords: Tool, FSW, Friction Stir, Processing, Steel.

I. INTRODUCTION Friction-stir welding (FSW) was patented by Thomas.et.al in 1991. The Welding Institute (TWI) of UK did experiments initially on aluminium and its alloys [1]. The process uses the non-consumable specially designed rotating tool which is inserted in to the material by giving the axial force and then translated along the joint line to make the weld [2]. TMAZ zone is formed due to thermo mechanical cycles and HAZ is the zone which is affected by the frictional heat produced by the shoulder. WN is the region formed due to the stirring action of the pin. Frictional heat produced by the tool makes the plastic deformation of material and grain boundary sliding. Excessive heat formation leads to tool wear which results in loss of material in the tool. Loss of tool material will be formed as an inclusion in the weld region. Feed rate, material flow and heat transfer favours the tool wear to emerge along the weld direction. Tool wear can be reduced by preheating the work piece [3] Friction Stir Welding is considered to be the most significant development in metal joining in a decade. In Friction Stir Welding no cover gas or flux is used, thereby making the process environmentally friendly, energy efficiency and versatility or it is a „green technology‟. The joining does not involve any use of

filler metal and therefore any aluminium alloy can be joined without concern for the compatibility of composition, which is an issue in fusion welding. In FSW no cover gas or flux is used, and does not involve any use of filler metal so that the properties of the joints are improve compare to the parent metal [4].

II. METHODS AND MATERIAL A. Benefits of Friction Stir Welding  Good mechanical properties in the as-welded condition.  Improved safety due to the absence of toxic fumes or the spatter of molten material.  Easily automated on simple milling machines lower setup costs and less training.  Can operate in all positions (horizontal, vertical, etc.), as there is no weld pool

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Tool rotation and traverse speeds

Figure 1 : Schematic diagram of friction stir welding process [6] B. Friction Stir Welding Tool FSW tool is considered as a heart of the welding process which has two primary parts namely shoulder and pin, which heats the work piece material by friction. Shoulder part of the tool frictionally heats the portion of the work piece and induces the axial downward force for welding consolidation. The FSW is emerged from a concept of drilling and hence the tool was initially used with threaded pin. The compaction of plasticized material is given by the bottom of the tool shoulder and prevents the material from escaping. The shoulder have different profile such as flat, concave, smooth or grooved, with concentric or spiral grooves[5]. FSW is considered to be the potentially useful solid state welding technique in which welding is done below the melting point of the work piece material.

Figure 2 : Schematic diagram of the FSW tool. [7]

There are two tool speeds to be considered in frictionstir welding; how fast the tool rotates and how quickly it traverses the interface. These two parameters have considerable importance and must be chosen with care to ensure a successful and efficient welding cycle. The relationship between the welding speeds and the heat input during welding is complex but, in general, it can be said that increasing the rotation speed or decreasing the traverse speed will result in a hotter weld. In order to produce a successful weld it is necessary that the material surrounding the tool is hot enough to enable the extensive plastic flow required and minimize the forces acting on the tool. If the material is too cold then voids or other flaws may be present in the stir zone and in extreme cases the tool may break. Tool Design The design of the tool is a critical factor as a good tool can improve both the quality of the weld and the maximum possible welding speed. It is desirable that the tool material is sufficiently strong, tough, and hard wearing at the welding temperature. Further it should have a good oxidation resistance and a low thermal conductivity to minimize heat loss and thermal damage to the machinery further up the drive train. C. Friction Stir Welding Process Friction stir processing is a new and unique thermo mechanical processing technique that changes the mechanical properties and microstructure of the material [8]. Friction Stir processing has been applied to Aluminium, copper, and nickel based alloys. By Friction Stir Processing the strength of the cast nickel aluminium bronze was doubled, the ductility of the Al alloys A356 was increased by five times. FSP is also used to increase the fatigue life of the fusion weld surfaces [9]. The working principle of Friction Stir Welding process is shown in Fig. 1. A welding tool comprised of a shank, shoulder, and pin is fixed in a milling machine chuck and is rotated about its longitudinal axis. The work piece, with square mating edges, is fixed to a rigid backing plate, and a clamp or anvil prevents the work piece from spreading or lifting during welding. The halfplate where the direction of rotation is the same as that

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of welding is called the advancing side, with the other side designated as being the retreating side. The rotating welding tool is slowly plunged into the work piece until the shoulder of the welding tool forcibly contacts the upper surface of the material.

low transverse feed. Defect in which the Series of small voids located in the advancing side interleaving the stir zone along the weld is known as Scalloping [b].

Figure 4: (a): Worm hole (b). Scalloping Figure 2: A Schematic Diagram Of Friction Stir Welding Process [7]

III. RESULT AND DISCUSSION A. Applications of FSW 



 

Shipping and marine industries: - Such as manufacturing of hulls, offshore accommodations, aluminium extrusions, etc. Aerospace industries: - for welding in Al alloy fuel tanks for space vehicles, manufacturing of wings, etc. Railway industries: - building of container bodies, railway tankers, etc. Land transport: - automotive engine chassis, body frames, wheel rims, truck bodies, etc.

B. Friction Stir Welding Defects Friction Stir welding is susceptible to the defects which are different from the fusion welding defects. Selection of improper welding process parameters leads to insufficient heat input, excessive heat input, abnormal stirring, and insufficient pressure underneath the shoulder which leads to the any one or more of the following defects in the friction stir welding. Worm hole [a] is the tunnel of inadequately consolidated and forged material running in the longitudinal direction which is formed due to excessive heat input due to high rotational speed,

IV. CONCLUSION The present review paper based on the basic concepts to understand formation of welding and its process parameter which functions to give such a permanent joint. Friction stir welding being a widespread interest for most of the upcoming researchers in the area of welding, it finds its importance in welding steels. Without the application of steel in industries is unimaginable. It identifies a number of areas that are worthwhile for further study. it has been suggested that higher tensile strength of these alloys, a manufacturer allow to use in the area of aerospace and automobile industries, where the high strength to weight ratio is important.

V. REFERENCES [1] Preetish Sinha, S. Muthukumaran, S.K. Mukherjee. Analysis of first mode of metal transfer in friction stir weld plates by image processing technique. journal of materials processing technology 197 (2008) 17–21. [2] K. Elangovan, V. Balasubramanian, S. Babu ,"Predicting tensile strength of friction stir welded AA6061 aluminium alloy joints by a mathematical model", Materials and Design 30, 2009, pp.188– 193. [3] Mandal A, Roy P. Modeling the compressive strength of molasses–cement sand system using design of experiments and back propagation neural networks. J Mater Process Technol 2006;180:167– 73.

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[4] R.S. Mishraa, Z.Y. Mab “Friction stir welding and processing” Materials Science and Engineering R 50 (2005) 1–78. [5] Thomas WM, Johnson KI, Wiesner CS. Friction stir welding-receved developments in tool and process technologies. Adv Eng Mater 2003;5:485– 90. [6] Prashant Prakash1, Sanjay Kumar Jha “a study of process parameters of friction stir welded aa 6061 aluminium alloy” , B.I.T Mesra , Ranchi , India Vol. 2, Issue 6, June 2013. [7] Man deep Singh Sidhu, Sukhpal Singh Catha “Friction Stir Welding – Process and its Variables: A Review” , Yadavindra College of Engineering, Punjabi University Campus, Talwandi Sabo, Bathinda, Punjab-151302, India. Volume 2, Issue 12, December 2012 [8] Rajeswari R. Itharaju,"Friction Stir Processing of Aluminum alloys", University of Kentucky, Master’s theses, 2004. [9] M.St. Weglowski, S. Dymek,"Relation between friction stir processing parameters and torque, temperature and penetration depth of the tool", Archives of civil and mechanical engineering, Vol. 13, Issue 2, 2013, pp. 186 – 191.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Scienceand Technology

Roadside Sand Deposits as Toxic Metals’ Receptacles along three Major Roads in Port Harcourt Metropolis, Nigeria Christian Mathew1*, K. J. Orie2 1

Department of Chemistry, Ignatius Ajuru University of Education, Port Harcourt, Nigeria 2 Department of Chemistry, University of Port Harcourt, Nigeria

ABSTRACT Roadside sand deposits are common sights along all roads in city centres like Port Harcourt in Nigeria. Studies have shown that, these sand deposits are receptacles for heavy metals emitted from varying sources. This study therefore, investigated the concentrations of four toxic metals Cadmium (Cd), Chromium (Cr), Lead (Pb) and Nickel (Ni) in roadside sand deposits. Three research questions were addressed using results of analyses of data obtained. Samples were collected along three major busy roads in Port Harcourt City using atomic absorption spectrophotometer, AAS. The results show that all four toxic metals except Cd were significantly available in the sand deposits with mean concentrations as follows: Cadmium 0.00 mg/kg, Chromium 2.81±2.21 mg/kg, Lead 1.09±0.70 mg/kg and Nickel 2.41±1.07 mg/kg. The detected concentrations were found to be high in relation to FEPA and WHO standards. The results also show that the mean concentrations are significantly different among the metals investigated but opposite is the case along the roads investigated. Therefore, the attention of environmental regulatory agencies is hereby drawn to this potential reservoir of environmental toxicants. The unsuspecting public, business operators, and others that depend on these roads for their livelihood are also enjoined to appreciate the dangers on these roads. Keywords: Sand Deposits, Metals Receptacles, Metal Concentrations, Busy Roadsides, Port Harcourt Metropolis and Nigeria

I. INTRODUCTION In cities of developing countries like Port Harcourt in Nigeria, roadside sand deposits are common phenomenon due to poor road construction works, dilapidated roads, poor road maintenance culture, improper disposal of silts from drainages, sand run-offs during rains,rickety automobiles, automobile wear and tear and above all poor government policies on road use and regulation of same.At the global stage, some research efforts have been carried out in most developed and developing countries on this subject of roadside metal receptacles, some of such endeavours are discussed as follows: Saeedi, Hosseinzadeh, Jamshidi and Pajooheshfar (2009)in their study,positthatheavy metals are typical road traffic source contaminants in the local ecological environments.Zehetner, Rosenfellner, Mentler and

Gerzabek (2009)were of the view that these metals are found in fuels, fuel tanks, engines and other vehicle components, catalytic converters, tires and brake pads, as well as in road surface materials.ForChristoforidis and Stamatis (2009),the concentrations of heavy metals in roadside soils are indicators of heavy metals’ accumulation through atmospheric deposition and road runoff. In views of Chen, Xia, Zhao and Zhang (2010),roadside soils are the major reservoirs of trafficrelated heavy metals and heavymetal contaminants can easily impact people residing within the vicinity of the roads via suspended dust or direct contact. According to Winther and Slento (2010),aspervehicle type, cars are the most important source of emission for all heavy metal species, followedby vans, trucks, buses and 2wheelers. By using the detailed emission factors and inventorycalculation methods established in the present

IJSRST15154 | Received: 04 November 2015 | Accepted: 24 November 2015 | November-December2015 [(1)5: 65-70]

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project, estimates of heavy metal emissionscan be made for other years than 2007. Khan, Khan and Rehman (2011) implicated traffic densities as a major source of lead and cadmium contamination of roadside sand deposit along all classes of roads in Pakistan. Luo,Yu, Zhu, and Li (2011)contend that the unprecedented pace in the last three decades in urbanization of China has a role in the metals deposition sources. Wang et al (2012) specifically implicated urbanization ages and land use as sources of heavy metals in Beijing urban soils inside the 5th ring road by even grids sampling. The results of the study revealed that the urban soils in Beijing were contaminated by Cd, Pb, Cu, and Zn. Soils in industrial areas have the highest average Cu and Zn contents, while Pb contents in park areas and Cd in agricultural areas are the highest. The accumulations of Pb and Zn in urban soils increase significantly with sampling plots approaching the city center. And Pb, Cd, and Zn contents in soils in traffic areas also tend to increase in the city center. However, residential areas have the lowest contents of all the four heavy metals. Zhang et al (2012)are of the generally opinion that most observational studies on the concentrations of heavy metals in roadside soils were focused on Cu, Zn, Cd and Pb. Clare, Zereini and Püttmann (2013)studied traffic-related trace element emissions and their uptake by plants grown in urban roadside environments in Toronto, Canadain 2010. Soil, plant tissue and plant rhizosphere samples analyzed for Cr, Mn, Cu, Ni, Cd, As, Sb and Pb show metals were more bioaccessible to O. vulgare grown in the new soil at the medium traffic volume site, compared to the aged soil at the heavy traffic location. Port Harcourt city has recently being characterized by escalated road transportation challenges due to very deplorable state of roads, poor road maintenance culture and with almost every household known to own a car on the average leading to very high traffic density in the city with no vehicular movement regulation policy of the government in operation. The city has also been characterized by consistent and persistent infrastructural decay due to over-use of same with suburbs still far from government attention. These and many more factors have resulted in the fast defacing of the city of its garden city status. Major roadsides now serve as natural receptacles for toxic metals’ loaded sands from failed portions of the same roads and from very bad roads from

other parts of the city. The city centre can hardly be differentiated from the suburbs. The overall result of these challenges is the elevated presence in the city centre of toxic metals held mainly in the roadside sand deposits and those suspended into the surrounding air by winds and spinning tyres of moving vehicles. With the teeming human commercial and domestic activities along these roads, exposure through inhalation of loaded air and direct body contact is inevitable. This study there attempted to determine the levels or concentrations of these toxic metals in some selected roads in some selected busy locations of the city given the fact these areas are known for hosting high commercial, transportation and domestic activities. Problem statement Port Harcourtis strategic to businesses of all sorts especially the Nigerian oil and gas mainstream and allied activities the city. The city’s deplorable state of infrastructure such as the road networks and the poor maintenance culture of same coupled with the escalating population challenges, it is expedient that the environment is monitored for the effects of potential pollution from such areas as the roadside sands which are established receptacles in major cities of the world for heavy and toxic metals to proportions yet established in the case of Port Harcourt. This study attempts to independently investigate possible variations in concentrations among the selected roads and metals and to establish the extent of significance of the concentrations of the metals. This is a dimension that has not been considered in available literature in similar studies in the city so as to proffer recommendations to relevant authorities and the unsuspecting teeming population of road users in the city. Research questions The following questions were addressed: 1. How significant arethe concentrations of the metals in the roadside sand deposits with respect to environmentally permissible limit, locally and globally? 2. How significant are the concentrations of metals different among the roads investigated. 3. How significant are concentrations of metal

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II. LITERATURE REVIEW Empirical studies of Toxic Metals on Roadside Sand Deposits Relevant literatures were reviewed globally and locally as follows: Ayeni, Ndakidemi, Snyman, and Odendaal (2010) conducted a study of river bank and adjacent soil samples from four different sites, Milnerton Lagoon from the lowerDiep River, Cape Town, South Africa were evaluated for ten metals among which were cadmium (Cd), lead (Pb), nickel (Ni), and chromium (Cr).The results showed that most sites were contaminated with metals evaluated.In adjacent soils, the concentration of Pb was0.97-71.7 mg/kg; Cd was 0.09.3 mg/kg;Crwas 0.3-2.1 mg/kg; and Ni was 0.02-2.6 mg/kg. Overall, Ni had the lowestconcentrations in the ecosystem. Chen,Xia,Zhao and Zhang (2010) ina detailed investigation conducted to study the heavy metal concentrations in roadside soils of Beijing,reportedthat concentrations of Cd, Cu, Pb and Zn showed a decreasing trend with increasing distance from the road while such trend was not identified in As, Cr and Ni. In addition, the concentrations of Cd, Cu, Pb and Zn were significantly positively correlated with black carbon (BC) and TOC (p<0.01). The soil samples from West 2nd Ring Road with the highest traffic volume had the highest heavy metal concentrations of the 10 roads, and Pb concentration was significantly positively correlated with traffic volumes (p<0.05). According to the soil guideline values of China, Cd was considered to have considerable contamination in roadside soils, while Cu, Pb and Zn less, but As, Ni, Cr none. The concentrations of heavy metals in roadside soils of Beijing were considered medium or low in comparison with those in other cities; this may be due to the windy and dry climate in Beijing. WintherandSlentø (2010)presentedin a report ofnew heavy metals’ emission factors for cars, vans, trucks, buses, mopedsand motorcycles for each of the emission sources’ fuel consumption, engine oil, tyre wear, brakewear and road abrasion using Arsenic (As), Cadmium (Cd),Chromium (Cr), Copper (Cu), Mercury (Hg), Nickel (Ni), Lead (Pb), Selenium (Se) and Zinc(Zn) as emission components. The following emissionsin total TSP (in brackets) is calculated for the

year 2007: As (8 kg), Cd (48 kg), Cr (197kg), Cu (51 779 kg), Hg (28 kg), Ni (158 kg), Pb (6 989 kg), Se (33 kg) and Zn (28 556 kg). Khan, KhanandRehman (2011) in a study of soil and plant samples collected from roadside sites … and reference site to investigate the contamination of soils and old common plant species with lead (Pb) and cadmium (Cd) in Peshawar City, Pakistan. Significant mean concentrations ofPb and Cd were reported to be 53.9 and 6.0 mg/kg in soils and 49.1 and 10.9 mg/kg in plants, respectively. In yet another study of sample of urban dusts collected from five locations in Owerri metropolis in May and July, Akhionbare (2011)revealed mean concentrations per dry weight of 3.00μg/g, 43.59μg/g, 15032.00 μg/g, 43.22 μg/g,78.64 μg/g and 312.29 μg/g of Cr, Cu, Fe, Ni, Pb and Zn respectively. Generally, the metals occurred in levels that are below regulatory intervention limits. Matthews-Amune and Samuel (2012)The content of Cd, Cu, Ni, Pb and Zn in the agricultural soils and cassava (Manihotesculentus) leaves from Adogo, Samples of soil and cassava leaves were collected from a site located on a highway, and another in a rural area which served as the reference site. Levels of Cd, Cu, Ni, Pb and Zn in soil and cassava leaves were found to be <0.01, 0.89±0.25, 0.18±0.03, 0.44±0.16, 0.04±0.003 and 0.13±0.0002, 0.15±0.01, 0.06±0.005, 0.07±0.004, 0.06±0.002 μg/g respectively. The levels of heavy metals in roadside agricultural soils and cassava leaves were higher as compared to reference soil levels, with Pb concentration seven times higher than level in soil and cassava leaves in reference soil. The absence of any major industry in the sampling sites the Pb metallic level indicates relation to traffic.Bada and Oyegbami(2012)in a study of roadside dusts reported that roads with higher traffic density had higher levels of metals.Yakeem and Onifade (2012) in an evaluation of concentrations of soil metals (Pb, Cd, Cr, Mn, Cu, Fe and Ni) from selected sites (Odo, Oba, Sabo and general areas) along major roads in Ogbomoso reported significantly high levels of these metals. Akpan and William (20014)in a study of traffic density effect of twenty one numbers elemental Al, Si, P, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Ga, As, Rb, Sr, Zr, Nb and Pbconcentrations in roadside soils in Calabar, Nigeria, revealed the following with concentrations (in

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ppm), ranging from 9.0±3.8 (Ga) to 192560.3±789.5 (Si) respectively were detected from ten different sample locations. Significant enrichment was obtained for Mn(7.677); Cu(5.189); Zn(5.203, 5.177 and 6.554); Ti (5.723, 5.395 and 5.00); Cr (6.901, 7.323 and 14.321); P(5.683, 5.750) and Si(6.747) respectively, indicating that their concentrations were sufficient to pose environmental problems. High concentrations of Pbin areas of high traffic density and the strong, positive and significant correlation results corroborate with results of enrichment factor, cluster analysis and counting statistics of number of vehicles plying sample locations thereby confirming heavy metals on roadside soils in Calabarto be associated with vehicular emissions.

II. METHODS AND MATERIAL Sample collection, treatment and analysis Sample collection was carried by thorough mapping of the entire stretch of each study road using high tension electric power lines’ suspension poles.Iwofe/Rumuepirikom(IR) road had 10 sample points,OluObasanjo(OO) road yielded 16 sample points and Iloabuchi(IL) road had 15 sample points totalling 31 number samples. Roadside sand deposits were grabbed from four sides of a designated sample point to make a composite out of which a sample was collected after thorough homogenization of the composite.

Collected soil samples were air-dried to constant weight and then sieved through a 500 μm stainless steel mesh wire. Samples of 0.5 g were digested in 20 ml freshly prepared aqua regia (1:3 HNO3:HCl) on a hot plate for 3 hours, then evaporated and analyzed for metal concentration. The total concentrations of Cd, Cr,Pb and Ni in filtrate were then determined using a flame atomic absorption spectrometer (Varian SpectrAA 220 FS) at wavelengths, λ: Cd = nm, Cr = nm, Pb =217.0 nm; Mn = 279.5 nm; Ni = 232.0 nm and Zn = 213.9 nm, using air acetylene flame. Data analysis Data for research question 1 was analyzed using mean and standard deviation while research questions 2 and 3 one-way ANOVA as well as a Scheffe post-hoc analysis question 3 where a significant difference was established.

III. RESULTS AND DISCUSSION Results Results of the analyses of data collected in this study are presented according to the research questions as follows: RQ1: How significant are the concentrations of the metals in the roadside sand deposits with respect to environmentally permissible limit, locally and globally?

Sample treatment and analysis Table 1: Mean metals concentration in mg/kg

N

Conc.

N

Conc.

N

Conc.

N

Conc.

FEPA (2003) Conc.

10 10 10 10

0.00 6.00 1.40 0.00

16 16 16 16

0.00 1.70 1.29 2.09

15 15 15 15

0.00 2.07 0.74 2.72

31 31 31 31

0.00±0.00 2.81±2.21 1.09±0.70 2.41±1.07

0.003 0.050 0.010 0.020

IRR Cadmium Chromium Lead Nickel

OOR

ILR

Mean±SD

WHO (1984) Conc. 0.003 0.050 0.010 0.020

Note: IRR-Iwofe/Rumuepirikom road, OOR-OluObasanjo road and ILR-Iloabuchi road FEPA-Federal Environmental Protection Agency and WHO-World Health Organization

Table 1 shows mean concentrations of the metals investigated in the three roads in Port Harcourt city. All metals except for Cd have concentrations way above the locally and globally stipulated environmentally permissible limits for the metals investigated in soil samples in the environment. The table also shows that the lowest limit of the range of the concentrations is on the higher side of the environmental limits for the metals as depicted by the measure of dispersion. Therefore, the concentrations of the metals are significantly present in the roadside sand deposit in the roads investigated. RQ2: How significant are the concentrations of metals different among the roads investigated.

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Table 2: ANOVAofdifference in metals concentration among roads Sum of Mean Df F Sig. Squares Square Between Groups 8.62 2 4.31 1.46 0.24 Within Groups 475.30 161 2.95 Total 483.93 163 Table 2 shows a one-way ANOVA of the difference in metals’ concentrations on the three roads investigated. The analysis as shown in the table have it that metals’ concentrations are not significantly different among the roads investigated with F(2,163) = 1.46 @ p =0.24 (p > 0.05). RQ3: How significant are concentrations of metals different among the metals investigated. Table 3(a): ANOVA of difference in metals’ concentrations Sum of df MeanSquare F Sig. Squares Between Groups 179.83 3 59.94 31.54 0.00 Within Groups 304.10 160 1.90 Total 483.93 163 Table 3(a)also shows a one-way ANOVA of the significant difference in concentration among thedifferent metals’ concentrations. The result F(3,163) = 31.54 @ p = 0.00 (p< 0.05) shows that there is a significant difference in the concentrations of the metals. Table3(b): ScheffePost-hoc Multiple Comparison Tests Metal (I) Cadmium (Cd)

Chromium (Cr)

Lead (Pb)

Nickel (Ni)

Metal (J) Chromium (Cr) Lead (Pb) Nickel (Ni) Cadmium (Cd) Lead (Pb) Nickel (Ni) Cadmium (Cd) Chromium (Cr) Nickel (Ni) Cadmium (Cd) Chromium (Cr) Lead (Pb)

Mean diff. (I-J) -2.88* -1.12* -1.81* 2.88* 1.76* 1.07* 1.12* -1.76* -0.69 1.81* -1.07* 0.69

Sig 0.00 0.01 0.00 0.00 0.00 0.01 0.01 0.00 0.17 0.00 0.01 0.17

*significant mean concentration difference Table 3(b) shows a post-hoc analysis of the direction and extent of the differences in concentrations of the metals. The table also shows that statistical significant mean concentration exist between Cr and Cd of 2.88 mg/kg, Ni and Cd of 1.81 mg/kg, Cr and Pb of 1.76 mg/kg,Pb and Cdof 1.12 mg/kg, and lastly between Cr and Ni of 1.07 mg/kg. The table shows a non-significant mean concentration difference between Ni and Pb of 0.69 mg/kg.

Discussion The findings of this study are discussed as follows: Metals’ Concentrations versus Environnementallimit All metals except for Cd have concentrations way above the locally and globally stipulated environmentally permissible limits for the metals investigated in soil samples in the environment. Therefore, the concentrations of the metals are significantly present in the roadside sand deposit in the roads investigated. This finding corroborates the findings of Matthews-Amune and Samuel (2012)The

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content of Cd, Cu, Ni, Pb and Zn in the agricultural soils and cassava in Adogo, Abuja;Akpan and William (20014)in a study of traffic density effect of twenty one numbers elemental Cr, Ni, and Pbconcentrations among others in roadside soils in Calabar. This finding may not be unrelated to the heavy vehicular traffic activities all the roads investigated. Metal Concentrations versus Roads The result F(2,163) = 1.46 @ p =0.24 (p > 0.05)shows a significant difference in concentration among the different metals’ concentrations.This finding does not corroborate that of Yakeem and Onifade (2012) in which Pb, Cr, and Ni correlates significantly in the different roads investigated.This finding may not be unconnected with the almost similar vehicular densities on the roads.

[4]

[5]

[6]

[7]

[8]

Metal Concentrations versus Metals The result F(3,163) = 31.54 @ p = 0.00 (p< 0.05) shows that there is a significant difference in the concentrations of the metals.Finding corroborates the works of Bada and Oyegbami (2012) in a study of Pb, Cd, Zn and Ni concentrations in roadside dusts in different traffic density Abeokuta and that ofYakeem and Onifade (2012) where Pb, Cr, and Ni correlates significantly. This finding may be due to the different levels or modes or even rates of emissions of the different metals from the different sources.

IV. CONCLUSION From the concentrations of the metals detected in the sand deposits along the three roads, further confirmation is established that the roadside sand are receptacles for metals emitted on these roads. These sands often times get airborne thus aggravating the imminence of toxic metals contamination by inhalation and direct body contact. Therefore, the need for a thorough and more detailed work is inevitable.

[9]

[10]

[11]

[12]

[13] [14]

[15]

V. REFERENCES [16] [1]

[2]

[3]

Akhionbare, S.M.O. (2011) Multivariate statistical analysis of heavy metals instreet dust of Owerri metropolis, Nigeriai.j.s.n., vol. 2(3) 2011:844-849 Akpan, I.O. and William, E.S. (20014) Assessment of elemental concentrations of roadside soils in relation to traffic density in Calabar, Nigeria. International journal of scientific & technology research volume 3, issue 9, september 2014 issn 2277-8616 1 ijstr©2014 www.ijstr.org Ayeni, O. O.;Ndakidemi, P. A.;Snyman, R. G. and Odendaal, J. P. (2010) Metal contamination of soils collected from four

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different sites along the lower Diep River, Cape Town, South Africa. International Journal of the Physical Sciences Vol. 5(13), pp. 2045-2051, 18 October, 2010 Bada, and Oyegbami (2012) Heavy Metals Concentrations in Roadside Dust of different Traffic Density. Journal of Environment and Earth Science.Volume 2, No. 8, pp54-59. ISSN 2224-3216 Chen X., Xia X.H., Zhao Y., Zhang P.(2010) Heavy metal concentrations in roadside soils and correlation with urban traffic in Beijing, ChinaJournalofHazard Mater;181:640–646. Clare, Wiseman, Zereini, F. and Püttmann, W. (2013) Trafficrelated trace element fate and uptake by plants cultivated in roadside soils in Toronto, Canada. Science of the Total Environment.Volume 442, 1 January 2013, Pages 86–95 Christoforidis A.,andStamatis, N (2009).Heavy metal contamination in street dust and roadside soil along the major national road in Kavala’s region, Greece.Geoderma;151:257– 263. Khan, S.;Khan, M.A.and Rehman, S. (2011) Lead and Cadmium Contamination of Different Roadside Soils and Plants in Peshawar City, Pakistan. Pedoshere.Elservier.Volume 21, Issue 3,Pp. 351–357 Luo, X. S.;Yu,S.;Zhu, Y. G.andLi, X. D. (2012) Trace metal contamination in urban soils of China. Science of the Total Environ. 421-422:17-30. Matthews-Amune, O. C. and Samuel, K. (2012)Investigation of heavy metal levels in roadside agricultural soil and plant samples in Adogo, Nigeria. Academia Journal of Environmental Sciences 1(2): 031-035, Academia Publishing Saeedi M., Hosseinzadeh M., Jamshidi A. and Pajooheshfar S.P.(2009) Assessment of heavy metals contamination and leaching characteristics in highway side soils, IranianEnvironmentalMonitoringandAssessment;151:231–241. Wang M., Markert B, Chen W, Peng C, Ouyang Z. (2012) Identification of heavy metal pollutants using multivariate analysis and effects of land uses on their accumulation in urban soils in Beijing, China. Environmental Monitoring Assessment;184(10):5889-5897. Winther, M. &Slentø, E. (2010) Heavy Metal Emissions for Danish Road Transport. National Environmental Research Institute, Aarhus University, Denmark.99 pp. – NERI Technical Report no. 780.http://www.dmu.dk/Pub/FR780.pdf. Yakeem, A. and Onifade, T. O. (2012) Evaluation of some Heavy Metals in Soils along Major Roads in Ogbomoso, South West Nigeria. Journal of Environment and Earth Science.Volume 2, No. 8, pp71-79. ISSN 2224-3219 Zehetner, F.;Rosenfellner, U.;Mentler, A.andGerzabek, M.H. (2009) Distribution of road salt residues, heavy metals and polycyclic aromatic hydrocarbons across a highway-forest interface. Water Air Soil Pollut;198:125–132. Zhang F.; Yan X.; Zeng C.; Zhang M.; Shrestha S.; Devkota, L. P.andYao, T. (2012) Influence of traffic activity on heavy metal concentrations of roadside farmland soil in mountainous areas. InternationalJournalofEnvironmental ResearchandPublic Health;9:1715–1731.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Review of Earth Tube Heat Exchanger Sharda Chauhan1, Gopal Sahu2, Prakash Kumar Sen3, Shailendra Bohidar4, Ritesh Sharma5 1 Student, Mechanical Engineering, Kirodimal Institute of Technology, Raigarh Chhattisgarh 2,3,4,5 Lecturer, Mechanical Engineering, Kirodimal Institute of Technology, Raigarh Chhattisgarh

ABSTRACT Earth-air heat exchangers, also called ground tube heat exchangers, are an interesting technique to reduce energy consumption in a building.They can cool or heat the ventilation air, using cold or heat accumulated in the soil. Several papers have been published in which a design method is described. Most of them are based on a discretisation of the one-dimensional heat transfer problem in the tube. Three-dimensional complex models, solving conduction and moisture transport in the soil are also found. These methods are of high complexity and often not ready for use by designers. The temperature of earth at a certain depth about 2 to 3m the temperature of ground remains nearly constant throughout the year. This constant temperature is called the undisturbed temperature of earth which remains higher than the outside temperature in winter and lower than the outside temperature in summer. When ambient air is drawn through buried pipes, the air is cooled in summer and heated in winter, before it is used for ventilation. The earth air heat exchanger can fulfill in both purpose heating in winter and cooling in summer. Keywords : Earth Tube Heat Exchanger, Renewable Energy, Ventilation

I. INTRODUCTION The Energy consumption of buildings for heating and cooling purpose has significantly increased during the decades. Energy saving are of major concern everywhere is a particular challenge in desert climates. We have been developing earth-tube heat exchanger (ETHE) for use in greenhouse in arid areas like Kutch.

Figure-1: Fully Furnished Greenhouse, Kothara-Kutch Showing Blower and Suction Duct Figure-2: Tomato being picked from Greenhouse The heat exchangers, which are receiving much attention in recent years. These simple heat exchangers are made up of a single tube (or multiple in parallel) through which a fluid is circulated. By placing the tube

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sufficiently deep (more than 1 m below the surface for a moderate climate zone such as Belgium), the fluid which is circulated can be cooled down in summer and heated up in winter. This is due to temperature lag which occurs between the surface and more profound soil layers. The Intergovernmental Panel on Climate Change (IPCC) (Pachauri and Reisinge 2007) estimates that the Earth's surface temperature has increased by 0.6°C and that human activities, such as burning fossil fuels for energy, have played a major role in climate change. Unfortunately, the world's insatiable thirst for energy will only increase as poorer countries become more industrialized. In several European countries this technique is imple-mented in private houses and office buildings. Recent examples are found in Germany and Switzerland Architects and building installation designers are often interested in installing earth-air heat exchangers, but due to lack of knowledge or design criteria, the introduction of the heat exchanger in the building design is omitted. Earth tube heat exchanger ( ETHE) is a device that enables transfer of heat from ambient air to deeper layers of soil and vice versa [14]. Since the early explanation of its use in cooling commercial buildings, there has been a considerable increase in its application [12]. For many years earth heat exchangers have been acknowledged to be useful tools for the acclimatization of buildings, both to decrease energy consumption and increase building comfort [5], [8] revealed that only a moderate climate having a large temperature difference between summer and winter is suited for earth tube heat exchangers. Different configurations of earth –to-air heat exchanger have been used in Central and Western Europe as heat suppliers during the cold season [16]. Their performance depends on the air flow rate, convective heat transfer at the tube surface, depth, dimensions and number of pipes and soil properties [6]. Since the soil transports heat slowly and have a high heat storage capacity, its temperature changes slowly depending on the depth of measurement [1].

II. METHODS AND MATERIAL A. Experiment Setup The experimental setup is an open loop flow system has been designed and fabricated to conduct experimental investigation on the temperature difference for inlet and

Outlet section, heat transfer, and coefficient of performance and fluid flow characteristics of a pipe in parallel connection.

Figure-3: ETHE before being covered The experimental data are to be used to find the increase of cooling rate for the summer (May 2014) condition, and heating rate of winter (November 2014) condition heat transfer coefficient. There are five temperature sensors located inside the pipe: 5 m, 10 m, 15 m, 20 m and 25 m away from the air inlet. In addition, there are temperature sensors buried 0.5 m, 1.0 m and 1.5 m in the ground to measure the soil temperature gradient. To clean the EAHX, a nylon cord was placed inside the tubes, which allows a cloth to be pulled through the system, removing all of the dust and debris.The experiment room and the control room are each 3.50 m × 2.75 m × 5.35m. The experiment and control rooms share a wall, and both of the rooms are connected to a larger laboratory. The walls are 18 cm thick and made from locally produced brick covered in concrete. The ceiling is made from wood slates, and the roof of the structure is corrugated steel. This is a typical construction for homes and offices in Burkina Faso. The ventilator used to draw the air through the pipes is 14 W and has a volume flow rate of 95 m3/hr. B. Advantage and Disadvantage Being result of a natural phenomenon deep ground as source and sink is available easily in most places in the world. Such a use is sustainable and equivalent to having a renewable energy source. ETHE based systems cause no toxic emission and therefore, are not detrimental to environment. Ground Source Heat Pumps (GSHPs) do use some refrigerant but much less than the conventional systems. ETHE based systems for cooling does not need water - a feature valuable in arid areas like Kutch. It is this feature that motivated our work on ETHE development. ETHEs have long life and require only low maintenance. However, initial installation costs are

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likely to be higher than the comparable conventional (refrigerant based) systems. Conventional systems can be customized easily for varied applications and industry is well developed. This is not yet the case for ground coupled systems. C. Performance of Large Diameter Earth-Air Heat Exchangers Tjelflaat [4] collected data on a 1.5 × 2 × 13.5 m (w × h × l ) EAHE serving an addition to the Media School in Grong, Norway, about 200 km north of Trondheim, which has a mean annual temperature of 5.0 °C [5]. The “hybrid” system design was intended to heavily exploit wind and stack forces to drive air flow, supplemented by a supply fan and an exhaust fan controlled by the building management system. Tjelflaat’s analysis focused on cooling performance, but Jeong [6] and Wachenfeldt [7] used the data to support validation of a simulation model of the system. One of Jeong’s simulations in [6] indicated that the EAHE raised the supply air temperature by as much as 12 °C (from −7 °C to 5 °C). However, the simulation seemed to result in a supply air (duct discharge) temperature equal to the duct surface temperatures, which were set to a constant 6.1 °C duct wall boundary condition. The duct wall temperatures used by Jeong differed from measured conditions (discussed below). This will be discussed below following the two paragraphs immediately below that address Wachenfeldt’s research. Jeong provided few details to explain this. In a second simulation of both building thermal performance and airflow, Jeong [6] reported that the EAHE raised supply air temperature by as much as 11 °C (from −7 °C to 4 °C). Although the temperature rise from the two simulations was similar, the second simulation produced a supply air temperature profile that fluctuated with the inlet air temperature. Overall, Jeong focused on the whole building simulation. Wachenfeldt [7] simulated the performance of the addition to the Media School, using data collected by [4], focusing on the simulation of the EAHE air flows. As with [4], the analysis primarily addressed cooling performance. Wachenfeldt highlighted the difficulty of predicting energy performance of natural (wind- and buoyancy-driven) ventilation systems, because of variations in airflow paths and rates, sensitive to both internal parameters and the outdoor environment. He noted the importance of fans in enhancing convective heat transfer between air and duct walls.

III. RESULT AND DISCUSSION Different soil types have a different penetration depth, related to their physical properties. For example, clay soils tend to have a smaller penetration depth, about 0.12

m, due to their higher water content. Changing the penetration depth from 0.17 to 0.12 m only shows a small effect. The same was found for the tube wall conductivity. Increasing the tube wall conductivity decreases the conductive heat transfer resistance through the tube wall. However, because the tube only has a small to negligible contribution to the total resistance (see Fig. 3) the effect is very small. The soil conductivity has a stronger impact, which is illustrated in Fig. 7. Note that the selected value of 0.3 W/m-K is an extreme condition, usually soil thermal conductivity varies around 1 - 1.5 W/m-K. Yet it is clear that for high air flow rates, the soil conductivity contributes significantly.

Figure 5: Required tube length L to reach ε = 0.8 for varying soil thermal conductivity and air flow rate. During this time period, the outside temperature and the ground temperature were recorded approximately every three hours, and the RMSE between the theoretical and measure values ranged from 0.02°C to 0.10°C. Figure 4 is a plot of the theoretical and measured temperatures during the 52-hour period. In the figure, the origin on the x-axis represents midnight on 12 May. The data clearly show the soil temperature decreasing with depth and the phase shift of the ground temperature with respect to the outside air temperature. At the hottest time of the day (11:45 to 15:00), the ground temperature was the coolest, and at the coldest time of the day (06:00 to 07:30), the ground temperature was the hottest.

IV. CONCLUSION Analytical models were developed for an EAHE and an EWHE combined with a compact water-air heat exchanger. The results show that for both types of heat exchangers, at higher flow rates the thermal resistance of the soil becomes dominant, in particular for the EWHE.

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This should always be considered in the design process. The CHE effectiveness must be as high as possible. A parameter study of louvered fin units was undertaken to obtain a value of at least 0.8. There is a strong interaction between the two heat exchangers in the EWHE case: when varying the flow rate their effectiveness show an opposite trend. On the whole the required tube installation length is larger for the EWHE compared to an EAHE, but the tubes are much smaller. A few case studies using two CHE in parallel showed further improvement of the EWHE.

V. REFERENCES [1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

[9]

Climatedata.eu. Climate Trondheim Norway Available online: http://www.climatedata.eu/ climate.php?loc=noxx0039&lang=en (accessed on 30 May 2013). [10] Jeong, Y. Modeling of a Hybrid-Ventilated Building: “Grong School”. Master’s Thesis, Concordia University, Montreal, Canada, 2002. Available online: http://spectrum.library.concordia.ca/1790/ (accessed on 20 February 2012). [11] Wachenfeldt, B.J. Natural Ventilation in Buildings Detailed Prediction of Energy Performance.Ph.D. Thesis,Norwegian University of Science and Technology: Trondheim, Norway, 2003.

Alghannam, A. O. (2012). Investigations of performance of earth tube heat exchanger of sandy soil in hot arid climate. Journal of Applied Sciences Research, 8(6): 344 3052. Benkert, St., F.D. Heidt and D. Scholer. 1997. Calculation tool for earth tube heat exchangers GAEA. Department of Physics, University of Siegen, D-57068 Siegen, Germany. De Paepe, M. and A.Janssens, (2003). Thermo hydraulic design of earth –air heat exchangers. Energy and Buildings, 35:389-397. Jenssens, A., M. Steeman, J.Desmedt, H. Hose and M. De Paepe.(2005). Energy performance of earth-air heat exchanger in a Belgian office building. AIVC 26th conference-Brussels, Belgium, pp: 15 -20. Scott, N.R., R.A. Parsons and T.A. Kochler (1965). Analysis and performance of an earth tube heat exchanger. ASAE paper no.65-840. St. Joseph, Michigan, ASAE. Sharan, G. and R. Jadhav. (2004) Performance of single pass earth-tube heat exchanger: An experimental study. Indian Institute of Management. Ahmedabad. Tudor, A. and V. Badescu. (2013).The influence of several parameters on the performance of earth to air heat exchangers into south-eastern European climates. U.P.B. Sci., Series D, vol. 75 Iss.3, 2013. Tjelflaat, P.O. The Grong School in Norway. The Hybrid Ventilation System; Norwegian University of Science and Technology: Trondheim, Norway, 2000. Available online: www.sintef.no/upload/grong%20hybrid.pdf (accessed on 30 July 2012).

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Status, Characterization and Conservation Practices of Local Chicken Ecotypes, Ethiopia 1

Addis Getu, 2 Kefyalew Alemayehu 1Atnaf Alebie

1

Department of Animal Production and Extension, University of Gondar, Faculty of Veterinary Medicine, Ethiopia 2 Bahir Dar University, Department of Animal Production and Technology, P.O. Box 21 45, Bahir Dar, Ethiopia

ABSTRACT Review work was conducted to assess the characterized and conservation methods of indigenous chickens in Ethiopia. In Ethiopia Chickens are the most wide spread and dominant poultry species. Since local chickens have good potential to adapted in different agro-ecology and provide luxurious source of family protein and income to rural poor. However, village chicken is usually kept under free ranging production system. Still those local chickens are non-descriptive type and show variations in body position, color, comb type and productivity. Indigenous chickens have characterized as; poor appearance, relatively low productivity, slow growth rate, small adult size and lays small egg. So, they are neglected from researchers, development workers and policy makers to put them in the research and development. To decrease loose of chicken genetic resource, phenotypic and genotypic characterization work were conducted. However, many chickens are lack with information about their geographical distributions and its availability. Many previous reports underlined that the breed characteristics of indigenous chickens are vary in color, comb type, body conformation and weight. High incidences of chicken diseases, mainly (NCD), coccidioses, salmonellae’s fowl pox are the major and economically important constraint for village chicken production system following feeds and predators. Further constraints are poor access to markets, weak institutions, and lack of skills and knowledge which lead to high rate of genetic erosion. According to DAD-IS and DAGR-IS, the evidences about the genetic resource of identified chickens are undocumented and unobserved as well, only small number of chickens ecotype such as Tilili, Horro, Chefe, Jarso, Tepi, Gelila, Debre-Elias, Melo-Hamusit, Gassay/Farta, Guangua, Mecha, Konso, Mandura, and Sheka are the major identified and characterized type of local chicken ecotypes in Ethiopia. Therefore, conservation practices are not common rather than aggravating the erosion of local chicken resources through random distribution of exotic chickens. Keywords: Chickens, Conservation, Indigenous

I. INTRODUCTION In Ethiopia, village chicken production systems usually kept under free range system and their feed is obtained through scavenging. The major feed resource are insects, worms, seeds and plant materials, with very small amounts of grain and table leftover supplements from the household (Tadelle and Ogle, 2000; Bogale,2008). These scavenging chickens are the most widespread which provide important source of family protein and incomes (Tadelle et al., 2003). At country level local chicken are estimated as 49.3 million (CSA, 2011). Local chickens are non-descriptive type show a large variation in body position, color, comb type and

productivity which also attributed to their widespread distribution and huge population size (Tadelle et al., 2003; Halima, 2007; Fisseha et al., 2010b). Ethiopia is the home of domestic animal migration from Asia to Africa which plaid a great impact to widespread distribution in a country (Halima, 2007). Adaptation of harsh environment and resistance to disease are the major opportunities of local chicken in Ethiopia and contributed to the national economy in general and the rural economy in particular 99.2% of meat and 99% of egg productions are contributed by local chickens with an average annual output of 72,300 and 78,000 metric tons of meat and egg production respectively (Tadelle et al., 2003; Hailemariam et al., 2006; Fessiha et al.,

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2010b). However, indigenous chickens are poor appearance, relatively low productivity, slow growth rate, small adult size and lays small egg size (Pedersen, 2002; Gondwe, 2004). Due to this effect they are not getting attention by concerned bodies (Tadelle, 2003; Mekonnen, 2007). Therefore the genetic resources in some part of Ethiopia are becoming critically endangered (Halima 2007; Dana et al 2010; Dana, 2011). Furthermore, the extensive and random distribution of exotic chicken breeds is cause of dilution in indigenous chickens (Tadelle et al., 2003). To reduce loses of chicken genetic resource, some workers have made phenotypic and genotypic characterization of indigenous chicken in some parts of Ethiopia (Tadelle, 2003; Halima, 2007; Dana et al., 2009; Dana, 2011). Therefore the objective of this paper is to assess the status, characterization and conservation practice of indigenous chicken in Ethiopia and to identify risk of their extinction.

II. METHODS AND MATERIAL Chicken Population in Ethiopia Ethiopia is one of African countries with a significant population of chicken and covers about 60% of the total population (Mekonnen et al., 1991).The domesticated poultry species are the part of livestock population. Recently, chickens are estimated to be about 49.3 millions of which 97.3%, 0 .38 % and 2.32 % of the total chickens are indigenous, hybrid and exotic respectively (CSA, 2011). This report revealed that chicken includes cocks, cockerels, pullets, laying hens, non-laying hens and chicks.

Figure 1 : Distribution of chicken population by type in Ethiopia

In Ethiopia, the rural farm households do not keep other domesticated birds (Bogale, 2008). The same study indicated that the mean number of breeding females per households was 5.4 + 2 and the overall male to female ratio of the village flocks was: 1:2.5. A. Geographical Distributions and Classification of Indigenous Chickens in Ethiopia There is no complete information about the geographical distributions of many chickens in the developing countries of the world thus some of them are commonly referred to as non-descript breeds (FAO, 2011). Ethiopian local chickens are none descriptive (none have common defined name). As a result breed characteristics of local chickens are vary in color, comb type, body conformation and body weight (Alemu & Tadelle, 1997; Meseret, 2010). The diversity of Ethiopian local chicken shows variation in morphology, color etc and their name is given based on name of place where they are found. Based on their color, the local chicken ecotype classified and named as: Tukor (black), Melata (nacked nack), Kei (red), Gebsima (mixed) and Netch (white). Based on feather morphology local chicken ecotypes are categorized as skin color (silky, white & yellow), Comp type (single, rose, pea, walnut & duplex) and Body shape (blocky, triangular & wedge) (Dana et al., 2010). Therefore Dana (2011) currently reported that local chickens are characterized by pronounced broodiness (maternal instinct), slow growth rate, late sexual maturity and low production performance. B. Importance of Poultry Productions Word poultry refers to all domesticated birds that are reared for the production of meat and eggs for human consumption as well as for economic benefits. Village chicken production systems are characterized by low input- low output levels and free range production systems (Bogale, 2008). Indigenous chicken provides relevant contributions for poverty alleviation by adapting different agro - ecology, resistance to disease and supplying high quality protein to balance the family food supply, and provide small disposable cash income in addition to the socio-religious functions that are important in the rural people’s lives under lack of supplementary feed and other managemental problems. Due to the importance of local chicken, characterizing

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and conservation of indigenous chicken genetic resource are mandatory (Tadelle, et al., 2003b). Chicken production is an appropriate and locally available resource on livestock populations. In Africa chicken population is the highest and every rural poor participated in an extensive production system (Tadelle et al., 2003b). From sub-Saharan Africa, 85% of all households keep chicken under free range/ extensive production system, with women owning 70% of it, providing insufficient animal protein in the form of meat and eggs as well as reliable source of cash income (Sonaiya and Swan, 2004; Abubakar et al., 2007). Ethiopia is one of the few African countries which have large chicken population of 60% of the total free range population in Africa (Mekonnen et al., 1991). However, the number of chicken flocks per household in most Ethiopian rural communities is small constituting an average of 7–10 mature chicken, 2–4 adult hens, a male bird (cock) and a number of growers of various ages (Tadelle and Ogle, 2000). Traditional production system of local chickens is common and characterized by their low input and low output levels no feed supplementation, small flock size and periodic devastation of the size by disease and other constraints (Tadelle and Alemu, 1997; Meseret, 2010). C. Performance of Indigenous Chicken Some workers reported that indigenous chickens are poor appearance, low performance and produce small sized eggs, slow growth rate, late maturity and slow age at first mating, small clutch size, and high mortality of chicks (Bogale, 2008; Fisseha, 2009; Meseret, 2010). In different part of Ethiopia, comprehensive report stated that phenotypic performance of local chickens are varied because of genotype, management and seasons, such as egg production performance; described in 30 to 60 eggs/hen/yr (Kidane, 1980) at WADU, 34 eggs /hen/yr (Pearson and Brannang, 1990) at Asella, 18-57 eggs/year/ hen (Halima, 2007) at Northwest Ethiopia, 20-60 eggs/3cluch/yr (Bogale, 2008) at Fogera, 10.05 ± 0.15egg/clutch 3.78 ± 0.07/yr (Fissiha, 2009) at Bure and the other recent study reported local chicken eggs laid ranges from 53-60 egg/hen/yr range of 43.2-46.96 egg weight (Fisseha et al., 2010a) at North-west Ethiopia.

D. Major Constraints of Poultry Production in Ethiopia High incidence of chicken diseases, mainly (NCD) is the first and economically important constraint for village chicken production system following by feeds (Dana and Ogle, 2000; Halima, 2007). The other comprehensive study showed that (NCD) is highly infectious and more losses than any other diseases in the tropics and it spreads rapidly through the flock and mortality could reach up to 100% (Dana et al., 2003; Serkalem et al., 2005; Nwanta et al., 2008). Among infectious diseases, salmonelloses, coccidioses and fowl pox are also considered to be the most important causes of mortality in local chicken while predators are an additional causes of loss (Eshetu et al., 2001). According to Tadelle and Ogle (2000), high mortality of chicks under village chicken production in the central highlands of Ethiopia is due to diseases, parasites, predation, lack of feed, poor housing and insufficient water supply. Further village poultry production is constrained by poor access to markets, goods and services, weak institutions, and lack of skills, knowledge and appropriate technologies (Gueye, 2003). Besbes (2009) reported that poor nutrition and health problems are the main constraints. In addition to the above extensive and random introduction of exotic breeds before appropriate characterization, utilization and conservation of indigenous genetic resources is believed to be the main cause of the loss of indigenous resource (Halima, 2007; Besbes, 2009). E. Phenotypic Chicken

Characterization

of

Indigenous

Phenotypic characterization is affected by agro-climates, ethnic groups, socio- economic, religious and cultural influences in the nature of the qualitative and quantitative traits variation (Halima, 2007). Ethiopia is gateways of domestic animals migration from Asia to Africa and it has further impact on the diversity of Ethiopian chickens (Hallima, 2007). According to FAO (2011) stated that diversified chicken characterization is identifying distinct Animal Genetic Resource /AnGR/ and describing their uniqueness in their environment within specific location and describes any measurable (quantitative trait), adaptable and observable (qualitative) nature of AnGR and evaluate effective population size

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and evaluates status their risks (FAO, 2011). Different report stated that indigenous chickens are characterized in different parts of Ethiopia; Teketel (1986) at Awassa/Sidamo; Bogale (2008) at Fogera District (based on plumage colors as, white, red, black, grayish, brown, white brownish, black brownish, and red brownish), Fissiha (2009) at Bure (characterized based on their phenotypic variations in terms of plumage color, shank length, comb type and growth performances). Based on location Tadelle (2003) at Tilili, Horro, Chefe, Jarso and Tepi, Halima (2007) at Tilili, Gelila, Debre-Elias, MeloHamusit, Gassay/Farta, Guangua and Mecha and Dana (2011) characterized at Farta, Konso, Mandura, Horro and Sheka. However, only 5 chickens are listed in DADIS (FAO, 2008) and 10 in DAGR-IS (DAGRIS, 2008) including those listed in DAD-IS. This small number represented in the databases indicates that locally adapted populations are still un documented (Dana, 2011). F. Molecular Characterization Molecular characterization is the major options for breed definition, especially populations which are not well defined to identify unique alleles. DNA-based methods are independent of environmental factors and provide useful information about genetic diversity to supported the global management of genetic resources (FAO, 2007a; 2011) and genetic conservation (Mendelsohn, 2003; Shresta, 2004). Characterization and conservation of AnGR is important for designing sustainable poverty alleviation (Toro et al., 2006). At molecular level Tadelle, Halima and Dana has been characterized the Ethiopian chickens. Livestock species are sequenced in genome prepares (Burt, 2005) and therefore provides a vast number of microsatellite markers for diversity studies. According to Halima, twenty two microsatellite markers was used based on the degree of polymorphism and genome coverage for the measurement of chicken diversity (Halima, 2007), and application in diversity studies and detailed information in North West Ethiopia. Information is not available on the genetic diversity of Ethiopian local chickens which are important to design effective selection and conservation strategies (Hlima, 2007). Molecular genetic characterization explores polymorphism (magnify and show different form) in

selected protein molecules and DNA markers to measure genetic variation at the population level. Because of the low level of polymorphism observed in proteins and hence limited applicability in diversity studies, DNAlevel polymorphisms are the markers of choice for molecular genetics characterization. Assessment of Genetic variability at the DNA level, different classes of molecular markers have been employed to study genetic diversity in chickens such as restriction fragment length polymorphisms (RFLP), random amplified polymorphic DNA (RAPD) markers, amplified fragment length polymorphisms (AFLP), mitochondrial DNA (mtDNA) markers, two types of variable number of tandem repeat (VNTR) loci (mini satellites and microsatellites), and more recently single nucleotide polymorphism (SNP) markers (Weigend and Romanov, 2001), the assessment of DNA marker polymorphism suggests that variability in DNA is a powerful tool for examining diversity within and among individuals, families and populations. In general identification and characterization of animal genetic resources requires information on their population, adaptation to a specific environment, possession of traits of current or future value and sociocultural importance, which are crucial inputs to decisions on proper utilization and conservation of AnGR (Dana, 2011).

III. RESULT AND DISCUSSION Conservation of Poultry Genetic Resources Global management of genetic resources at international level is mandatory (Gandini & Oldenbroek, 1999). Communication and information system or Domestic Animal Diversity Information System (DAD-IS) is being developed by FAO and USID during 1952, with the objective of assisting countries by providing extensive searchable databases and guidelines for better characterization, utilization and conservation of chicken genetic resources (Halima,2007). Such programmes are important because the AnGR have been faced to genetic dilution due to exotic germplasm use, changes in production systems, markets preferences, natural catastrophes, unstable policies from public and private sectors and the availability of very limited funds for conservation activities ( Rege & Gibson, 2003; Halima, 2007; Dana, 2011). It should also include the population size of the animal genetic resources, its physical

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description, adaptations, uses, prevalent breeding systems, population trends, predominant production systems, description of the environment in which it is predominantly found, indications of performance levels (meat, growth, reproduction, egg) and the genetic distinctiveness of the animal (Weigend & Romanov, 2002). This provides a basis for distinguishing among different animal genetic resources and for assessing the available diversity (FAO, 2011). However, insufficient attention has been given to evaluating these resources or to setting up realistic and optimum breeding goals for their improvement (Dana, 2011). As a result some of the animal genetic resources of Africa are endangered, and unless urgent efforts are taken to characterize and conserve, they may be lost even before they are described and documented and it is also stated that an increasing loss of genetic diversity has been observed and poultry genetic resources are considered to be the most endangered (Crawford, 1990; Halima, 2007). The majority of livestock genetic diversity is found in the developing world where

documentation is scarce and risk of extinction is highest and increasing. More particularly, it is estimated that 35 % of mammalian breeds and 63 % of avian breeds are at risk of extinction. These local chickens face genetic erosion which may lead to the loss of valuable genetic variability in specific characteristics of their unique genes and alleles pertinent to their adaptation to particular environments (Romanov et al., 1996). More over characterization, conservation and use of indigenous animal resources under low levels of input in the tropics are usually more productive than is the case with exotic breeds (Halima, 2007). Further the rule and strategy of the risk indicators of AnGR guide line established for the next conservation measures of AnGR (FAO, 2007a; 2011). So far status of animal Genetic Resource (AnGR) are classified as critical, critical-maintained, endangered, endangeredmaintained, extinct, not at risk and unknown breeds (UNEP, 2008). The important points are relevant to show indicators of the risk of the breeds are described in table 1.

Table1. Classification of AnGR based on their endangerments Groups of breeds

Extinct Critical Criticalmaintained Endangered

Total number of breeding Male Female 0 0 <5 <100

Overall population size Remark 0 <120

There is no breeding male and female Active conservation programmes

5<20

>100 <1000

>1000 or <1200

Endangered-M Not at risk Unknown

Source: (FAO, 2007a; UNEP, 2008) The above indicator is an important for sustainable management of genetic resources in respect to genetic conservation measures. Cryopreservation is an important complementary measure for the conservation of diversity in poultry as in other farm animal species. Some recent papers summarize the state of the art in long-term storage techniques for avian semen (Blesbois and Labbè, 2003). Over the past 50 years, preservation technologies have been developed for mammalian

Active conservation programmes Identified and characterized Not identify and characterize

gametes and embryos, in particular in cattle, which enable to run programs to preserve genetic materials (Gibons et al, 2006). Opportunities of Characterization and Conservation of Chicken Genetic Resource Since 2005, massively parallel DNA primer sequencing has become available and has reduced the cost of DNA sequencing (Shendure and Ji, 2008). In the next few years, even more effective sequencing systems will be

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accessible. This development will open the door for very low cost including the whole genome sequencing. The focus is now moving from the sequencing of a single individual to hundreds or even thousands of individuals. The “1000genome project” in humans which aims to sequence the genomes of approximately 1200 individuals from 3 major populations at approximately increase 4x coverage that targets 10,000 vertebrate species’ Affordable re sequencing will largely extend SNP identification. Analysis of breeds that have not been subject to selective breeding will forward the compilation of bias-free SNP panels for diversity studies. The widespread existence and importance of Copy Number Variation (CNV) on the level of gene expression (Beckman et al., 2007) and of micro RNAs on gene regulation (Shivdasani, 2006) are recent examples of unexpected discoveries. High sequencing in put will be more and more integrated with new statistical approaches (Luikart et al., 2003 ;). We expect that these new tools will stimulate the identification and understanding of variation supporting important traits, including phenotypes relevant for adaptation and sustainable operation. With regard to conservation, whole-genome sequencing will also provide more objective indications of uniqueness than any marker panel (FAO, 2007a ). In addition, adaptive variation will be included in prioritization protocols in order to ensure conservation of unique adaptive variants, thus optimizing conservation efforts both in vivo and in vitro. It is also envisaged that breeding and selection will be more and more guided by molecular analysis. Models are to be developed and customized to populations with different genetic structure (small vs large breeds) and to different purposes (genetic improvement, control of inbreeding, maintenance of diversity.

this identified small number represented in the databases indicates the shortage of data on chicken genetic resources of Ethiopia suggesting that much of the diversity that exists in the locally adapted populations still remains undocumented. Even if the above limited effort and small number of identified ecotype still didn’t include chicken genetic resource of all parts of Ethiopia like northern Amahara region of north Gonder administrative zone. The indigenous chicken genetic resource of north Gonder zone needs intensive identification, characterization properly utilization and conservation based on their risk status of extinction. Therefore based on this paper my research is highly initiated to identify and characterize distinct local chicken ecotypes in terms of physical characteristics and production systems of north western part of Ethiopia.

V.

 As a result, there is a need to design and implement a research programme to collect, conserve and improve the indigenous chickens.  Phenotypic characterization should be supported by genetic characterization of animal genetic resource.  Lack of documentation, proper utilization and conservation of local Chicken genetic resource is observed.  Researchers, developmental workers and policy makers should be give infancies for local genetic resource.  Concerned bodies should give mediate response for conservation measure after characterization and describing the risk level of local chicken in Ethiopia.

VI. REFERENCES

IV. CONCLUSION [1]

The local chicken genetic resource in Ethiopia is play significant role in poverty alleviation generation additional income and religion or cultural reason. Furthermore some worker tried to phenotypic characterization of local chicken in some parts of Ethiopia such as Tillili Tepi Medura Sheka Horo, Jerso, Farta etc. and only 10 types are recognized and documented in DAD-IS and DAGR-IS. Here in African 60% of wide spread distribution and large population size chicken population are found in Ethiopia. However,

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Abdelqader, A., Wollny, C. and Gauly, M., 2007. Characterization of local chicken production system and potential under different level of management practice in Jordan. Journal of Tropical Animal Health and Production. 39: 55–164. Akishinonomiya, F., Miyake, T., Takada, M., Shingu, R., Endo, T., Gojobori, T., Kondo, N. and Ohno, S., 1996. Monophyletic origin and unique dispersal patterns of domestic fowls. Proceedings of the National Academy of Sciences of the United States of America. 93: 6792- 795. Alemu Yami, 1995. Poultry production in Ethiopia. World’s Poultry Science Journal.51: 197- 201.

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[18] Eshetu Y, Mulualem, E., Ibrahim, H., Berhanu, A. and Aberra, K., 2001. Study of gastro-intestinal helminths of scavenging chickens in four rural districts of Amhara region, Ethiopia. Rev. Sci. tech off. Int. Epiz. 20(3): 791–796. [19] FAO, 2007a. Global Plan of Action for Animal Genetics Resources conservation, Rome, Italy. Pp: 125-128. [20] FAO, 2008. Domestic Animal Diversity–Information System (DAD-IS). [http://www.fao.org/dad-is]. The Food and Agriculture Organization of the United Nation (FAO). Rome, Italy (accessed on December 4, 2008). [21] FAO, 2011. Draft guidelines on phenotypic characterization of Animal genetic Resource. Commission on Genetic Resources for Food and Agriculture Rome. 18-22 July, 2011. 6p. [22] Fisseha M, 2009. Studies on production and marketing system of local chicken ecotypes in Bure Wereda, North west Amhara. M.Sc. Thesis, Hawassa University, Hawassa, Ethiopia. [23] Fisseha M, Abera M, and Tadelle D, 2010a. Assessment of village chicken production system and evaluation of the productive and reproductive performance local chicken ecotype in Bure district, North West Ethiopia. African Journal of Agricultural Research Vol. 5(13): 1739-1748, 4 July, 2010. [24] Fisseha M, Azage T, and Tadelle D, 2010b. Indigenous chicken production and marketing systems in Ethiopia: Characteristics and opportunities for market-oriented development. Working paper No.24; Improving Productivity and Market Success (IPMS) of Ethiopian Farmers Project, International Livestock Research Institute (ILRI). Addis Ababa, Ethiopia.66pp. [25] Gandini, G.C. & Oldenbroek, J.K., 1999. Choosing the conservation strategy. In: Genebanks and the conservation of farm animal genetic resources. Ed. J.K. Oldenbroek. DLO Institute for Animal Science and Health, the Netherlands. [26] Gibons, J., Gamange, S., Hanotte, Iñiguez L., Maillard J.C., Rischkowsky B., Semanbo D. and Toll,. 2006. “Options and Strategies for the Conservation of Farm Animal Genetic Resources”, Report of an International Workshop (7-10 November 2005, Montpellier, France), Biodiversity International, and Rome, Italy: 53 pp. [27] Gondwe, T.N.P., 2004. Characterization of local chicken in low input-low output production systems: is there scope for appropriate production and breeding strategies in Malawi? PhD thesis, Georg- ugust- niversität Göttingen, Germany. [28] Gueye, E., 2003. Poverty alleviation, food security and the well-being of the human population through family poultry in low income food-deficit countries. Senegalese Institute of Agricultural research (ISRA), B.P.2057 and Dakar-hann, Senegal. [29] Hailemariam T, Legesse D, Alemu Y, and Dana N, 2006. Adaptation of poultry breeds in the high lands of Ethiopia. Ethiopian institute of agricultural research. 26p. [30] Halima H, 2007. Phonotypic and genetic characterization of indigenous chicken populations in Northwest Ethiopia. PhD. Thesis submitted to the faculty of National and agricultural sciences department

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of animal Wild life and Grass land Sciences University of the Free State, Bloemfontein, and South Africa. Halima, H., Neser, F.W.C., Tadelle, D., Kock, A. De, Van Marle-Köster, E., 2006b. Studies on the growth performance of indigenous chicken ecotypes and RIR chicken under improved management systemin North west Ethiopia. Livest. Res. Rural Dev. 18 (6), (http://www.cipav.org.co/lrrd/lrrd18/6/hass18076.htm. Halima, H., Neser, F.W.C., Van Marle-Köster, E., Kock, A.De, 2007b. Phenotypic variation of indigenous chicken populations in northwest ethiopia. trop. anim. hlth prod. (in press). Halima, H., Neser, F.W.C., Van Marle-Köster, E., Kock, A.De, 2007a. Villagebased indigenous chicken production systems in north-west Ethiopia.Trop. Anim. Hlth Prod.39 (3):189-197. Kidane, H., 1980. Performance of F1cross breeds. Welaita Agricultural Development Unit. Animal husbandry and breeding. Welaita Sodo, Ethiopia. Bulletin No. 4. 33p. Luikart, G., England, P.R., Tallmon, D., 2003. Nat. Rev. Genet. 4:981-994. Mekonnen G/r, 2007. Characterization of smallholder poultry production and marketing system of dale, Wonsho and Loka Abaya Weredas of southern Ethiopia. M.Sc Thesis, Awassa College of Agriculture, Hawassa University. Mekonnen G/r, Teketel, F., Alemu, G., Dagnatchew, Z. and Anteneh, A., 1991.The Ethiopian livestock industry: retrospect and prospects. Proc.3rd National Livest. Improvement Conference, Institute of Agricultural Research, Addis Ababa, Ethiopia. Mendelsohn, R., 2003. The challenge of conserving indigenous domesticated animals. Ecological Economics. 45(3):501-510. Meseret M, 2010. Characterization of Village Chicken Production and Marketing System in; M.Sc thesis Submitted to the Department of Animal Science, Jimma University, College of Agriculture and Veterinary Medicine, School of Graduate Studies. Nwanta, J.A., Egege, SC., Alli-Balogun, JK. and Ezema, WS., 2008. Evaluation of prevalence and seasonality of Newcastle disease in chicken in Kaduna, Nigeria. World’s Poultry Science Journal. 64:414–416. Pedersen, C.V., 2002. Production of semi-scavenging chicken in Zimbabwe. PhD. Thesis, Royal Veterinary and Agricultural University, Copenhagen. Rege, J. E. O. and Gibson, J. P., 2003. Animal genetic resources and economic development: issues in relation to economic valuation. Ecological Economics 45 (3): 319-330. Romanov, M. N., Wezyk, S., Cywa-Benko, K. and Sakhatsky, N.I., 1996. Poultry geneticresources in the countries of Eastern Europe: History and current state. Poult. Avian Biology Rev. 7: 1-29. Serkalem Tadesse, Hagos Ashenafi, and Zeleke Aschalew, 2005. Sero-prevalence study of Newcastle disease in local chickens in central Ethiopia. International Journal of Applied Research. Vet. Med. Vol. 3, No. 1/19. Shivdasani, R.A. 2006. Blood Sampling.108:3646-3653.

[46] Shrestha, J.N.B., 2004. Conserving domestic animal diversity among composite populations. Small Ruminant Res. 56(1-3): 3-20. [47] Sonaiya, E.B. and Swan, S.E., 2004. Small-scale poultry production, technical guide manual. FAO Animal Production and Health 1. FAO (Food and Agriculture Organization of the United Nations), Rome, Italy. [48] Tadele D, 2003. Phenotypic and genetic characterization of chicken ecotypes in Ethiopia. PhD.Thesis submitted to Humboldt University, Germany. [49] Tadelle D, Alemu Y and Peters, K., 2003b. Village chicken production systems in Ethiopia: Use patterns and performance valuation and chicken products and socio- economic functions of chicken. Livestock Research for Rural Development 1(15). (Available from http://www.lrrd.org/ lrrd15/1/tadeb151.htm) (Accessed on 1 September 2010). [50] Tadelle D and Ogle, B., 2000. Nutritional Status of Village Poultry in the Central Highlands of Ethiopia as Assessed by Analyses of Crop Contents. Department of Animal Nutrition and Management, Debre Zeit Agriculture Research Centre, Debre Zeit, Ethiopia. J.Agric.Sci.17: 47-56. [51] Toro, M.A., Fernandez, J. and Caballero, A., 2006. Scientifc basis for policies in conservation of farm animal genetic resources. Proc. 8th World Congr. Genet. Appl.Livest. Prod., Belo Horizonte, MG, Brasil. [52] UNEP, 2008. Consideration of an intergovernmental science-policy platform on biodiversity and ecosystem services: objectives and functions of an intergovernmental science-policy platform on biodiversity and ecosystem services. Kuala Lumpur, 10– 12 November 2008.3P. [53] Weigend, S. & Romanov, M.N., 2002. The World watch list for domestic animal diversity in the context of conservation and utilization of poultry biodiversity. World’s Poult. Sci.58 (4): 411- 430. [54] West, B. and Zhou, B., 1998. Did chickens go north? New evidence for domestication. Journal of Archaeological Science. 15: 515-33.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Isopropanol Fractionation of Coconut Oil into its Olein and Stearin Fractions Sanjukta Kar*, Rajib Kumar Ghosh, D. K. Bhattacharyya, Minakshi Ghosh School of Community Science and Technology, Indian institute of engineering Science and Technology,Shibpur, Howrah, India

ABSTRACT The present study deals with the fractionation of coconut oil by using isopropanol as solvent and characterization of the olein and stearin fractions obtained in terms of melting properties, iodine value, saponification value and fatty acid composition. Coconut oil was fractionated with isopropanol (1:3, 1:4 and 1:5 wt/vol) at three temperatures (20°,15° and 10°C). The yields of oleins and stearins were dependent on the volume of solvent and the temperature of fractionation. Thus, 54 to 25% of oleins and 43 to 71% of stearins could be obtained when crystallized from 15°C to 10°C with the varying volume ratio of solvent (1:5 to 1:3 wt/vol.). The olein fractions displayed a distinct variation in the fatty acid compositions. Both Caprylic acid and Capric acid content increased in olein fractions from original coconut oil whereas decreased in corresponding stearin fractions. From the results, it appears that isopropanol is a good solvent to yield relatively higher amounts of medium chain triglycerides (MCT) which may be important from health and economical point of view. Coconut oil can be fractionated from isopropanol at relatively high temperatures in much less time to produce olein and stearin fractions of specific composition and properties. Keywords: Fractionation, Isopropanol, Coconut Olein, Coconut Stearin, Medium Chain Triglyceride

I. INTRODUCTION Coconut oil, traditional edible oil in India, has been receiving importance for its medium chain triglycerides content that confers health and nutritional benefits (1). In fact, the use of medium chain triglyceride rich oil or fraction in products like health margarines and in blending with other cooking oils especially in oils with long chain fatty acids demands for development of an appropriate process technology to produce very effectively medium chain triglyceride-rich fraction from coconut oil. The process that appears feasible is the adaptation of the solvent fractionation process. Fractionation is a process that uses heat to separate a substance into its components. The most widely practiced form of fractionation is that of crystallization wherein a mixture of triglycerides is seperated into two or more different melting fractions based on solubility at a given temperature. Generally under a certain specific

conditions the fractionation of coconut oil is done by fractional distillation process, Lanza process by using detergent and by solvent like acetone or hexane to yield olein and stearin fractions (2). Isopropanol, a bio-renewable solvent, is increasing in importance for vegetable oil extraction, and its use in fractionation of fats is also known (2). Saturated acidrich glycerides, having short-chain and long-chain acid moieties, are relatively less soluble in isopropanol than the corresponding glycerides with unsaturated fatty acids. As a result, a sharper fractionation is expected between the saturated acid-rich glycerides and the glycerides with unsaturated fatty acids. Also, it has been reported that isopropanol, as compared to hexane, enables fractionation to be conducted at a comparatively high temperature because of its polarity and with a lower volume of solvent. Further, time of crystallization is reported to be reduced and the loss of isopropanol is also less in comparison to n-hexane during recovery by distillation. It is already known that the boiling point of

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commercial n-hexane miscella remarkably increases with increase in the oil content of hexane miscella that requires more energy for recovery of hexane. On the other hand, isopropanol may not behave like that of hexane miscella because of its polar nature that may not behave as an ideal solvent for raising the boiling point of isopropanol miscella with the corresponding increase in oil content . Moreover it is stated that isopropanol is more eco-friendly than hexane in view of the fact that isopropanol is a food grade material and also condenses more completely compared to n-hexane (3, 4). Recent study in Brazil states that daily intake of coconut oil combined with exercise would restore baroreflex sensitivity and reduce oxidative stress, resulting in reduction in Blood pressure (5). The olein fractions are normally more enriched in medium chain triglycerides. Coconut olein yields low calorie and contains high medium chain triglyceride to prevent cholesterol production. Medium chain triglycerides allow fatty acids to be metabolized without use of the carnitine transport system (6). Oxidation of medium chain triglyceride provides 8.3 calories per gram, while long chain triglyceride provides 9.2 calories per gram (7). Medium chain triglycerides are useful in treating disorders that involve impaired or damaged lipid metabolism, including obstructive jaundice, billiary cirrhosis, pancreatitis, cystic fibrosis, celiac disease (8). It is also reported to be useful for feeding newborn infants, both to assist their initial growth and contribute to their physiological development. A mixture of medium chain monoglyceride and diglyceride was found to be an effective solvent for dissolving cholesterol gallstones in humans. (9-12). Stearins are available for use in bakery shortenings, pastry, margarine formulation. The present study deals with the fractionation of coconut oil by using isopropanol as solvent for the first time in different ratios (1:3, 1:4 and 1:5 wt/vol) at different temperatures ( 10°C,15°C and 20°C ) and characterization of the olein and stearin fractions obtained in terms of melting properties, iodine value, saponification value and fatty acid composition.

II. METHODS AND MATERIAL Coconut oil (Shalimar Chemical Works Limited) was purchased from local market, Kolkata, India.

Isopropanol (A.R Grade) and all chemicals used were MERCK, India. Fractionation of Coconut oil from Isopropanol: The coconut oil (100g.) was placed in a 1 L Stoppard conical flask (Borosil) after it was completely melted on a water bath at 50°C. Isopropanol was added in different ratio of 1:5,1:4 and 1:3 (wt/v). Each time the mixture was kept initially at 40°C for 10 min. the beaker was placed in a constant-temperature bath and stirred by a low-speed magnetic stirrer for 1 hour. The crystallization process was done at different temperatures of 20°C, 15°C and 10°C. The solid fraction was separated from the liquid fraction by filtration under vacuum. The fractions were desolventized at 80°C for 1 hour at 10 mm Hg pressure. Both the fractions were weighed and stored in a refrigerator at 4°C for further analysis. Analytical procedures Determination of Slip Melting Point Melting points were determined by the Capillary Tube Method of AOAC (13). Determination of Iodine Value Iodine values were determined by the Wijs Method of AOAC (13). Determination of Saponification Value Saponification values were determined by the method of AOAC (13). Fatty acid composition (%wt/wt) of the Coconut oil and its fractions obtained from Isopropanol fractionation Pure Coconut oil and different fractions were methylated by the simplest KOH catalyzed methanolysis method of Brockerhoff (14). About 40 mg of triglyceride was dissolved in 0.5 ml of diethyl ether and 1ml of 0.5 (N) methanolic KOH solutions was added and shaken. After 10 minutes at room temperature 1ml of 1(N) HCl was added and shaken. The methyl esters were extracted with each 1.0 ml of petroleum ether for three consecutive times. The extracts were evaporated in water bath. The sides of the tube were washed with sufficient GLC grade n-hexane to redissolve the methyl esters for GLC analysis. The gas chromatograph

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(Agilent 6890 N) was fitted with a DB Wax capillary column( 30 m x 0.32mm x 0.25µm) and FID.N2 , H2 and airflow rate were maintained at 1, 30 and 300ml/min respectively. Inlet and detector temperatures were kept at 250ºC and oven temperature was programmed at 70 ºC for 1 min holding time and then increase in temperature from 70ºC to 230ºC at a rate of 5ºC/min then holding time for 5min. Statistical Analysis Statistical analysis was performed by using analysis of variance (ANOVA) and the means were compared across groups by Tukey test. All analyses were carried out with the Origin Pro 8 and the significant differences were determined at p ≤ 0.05.

III. RESULT AND DISCUSSION Original Coconut oil was characterised in terms of Slip melting point, Iodine value, Saponification value along with fatty acid composition and the results were shown in Table 1. The fractionation of Coconut oil using isopropanol in different volume of solvent ratio (1:3, 1:4 and 1:5 wt/vol.) was carried out at different crystallization temperatures, viz. 20°, 15°, and 10°C for each at 1 h only. No fractions were obtained at 20°C temperature but fractionation was observed to be rapid and reproducible at 15°C and 10°C respectively. The yield of olein and stearin fractions obtained as included in the Table 2, depends on the ratio of oil and solvent used, and also on crystallization temperatures.

Table 1: Some analytical characteristics including Fatty acid composition of Coconut oil

Coconut oil Fatty acid (%w/w)

Slip melting point (ᵒ C) 24.40±0.36 8:0

10:0

12:0

3.72± 4.77± 51.0 ± 0.03 0.01 0.02 Results have been expressed as mean ± SD (n=3).

Iodine value

Saponification value

8.47±0.32

260.33±4.04

14:0

16:0

18:0

18:1

18:2

21.65± 0.03

9.60± 0.03

2.35± 0.01

5.47± 0.01

1.46± 0.02

Table 2: Yield %, Slip melting point, Iodine value and Saponification value of Coconut olein and stearin fractions

Yield (%w/w)

Melting point (°C)

Iodine value

Saponification value

oil:solvent (wt/v) 1:3 1:4 1:5 1:3 1:4 1:5 1:3 1:4 1:5 1:3 1:4 1:5

olein(15°C)

stearin(15°C)

olein(10°C)

stearin(10°C)

29.02± 0.42a 44.35± 0.22b 54.34± 0.43c 20.63± 0.15a 22.66± 0.58b 25.40± 0.17c 8.70± 0.17a 11.00± 0.43c 8.90± 0.26b 281.33± 3.51c 272.33± 3.79b 264.33± 3.21b

70.97± 0.42c 55.64± 0.22b 45.65± 0.43a 28.33± 0.58c 27.66± 0.29b 27.00± 0.10a 6.20± 0.26a 5.31± 0.73a 6.02± 0.32a 256.00± 4.00a 258.66± 3.51a 257.33± 1.15a

26.27± 0.26a 40.30± 0.26b 48.63± 0.31c 19.16± 0.15a 21.70± 0.26b 23.83± 0.29c 8.96± 0.06b 13.42± 0.42c 8.90± 0.26a 284.33±1.15c 283.00±2.00b 273.00±2.00a

73.72± 0.26c 59.70± 0.26b 51.36± 0.31a 28.66± 0.29c 27.93± 0.12b 27.73± 0.25a 5.99± 0.27a 7.35± 0.69c 6.02± 0.33b 254.33±2.08b 251.66±2.08a 259.66± 1.53c

Results have been expressed as mean ± SD (n=3). For all data in Table 2, Mean Values having different superscript letter in columns are significantly different (p<0.05). Values having same superscript letter in columns are not significantly different (p<0.05).

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The yield of olein fractions increases with the corresponding decrease in stearin fractions at constant temperature, as the volume of solvent increases from 1:3 to 1:5 wt/vol. This may be explained by the fact that the solubility of some of the triglycerides comprising saturated fatty acids of chain length longer than the medium chain fatty acid increases in isopropanol and olein is best separated with the higher volume of solvent (1:5 wt/vol.). The olein obtained from 1:3 wt/vol. is suitable from health point of view but 1:4 wt/vol. is considered to be better from both health and cost aspects based on the fatty acid composition that contains more Capric and Caprylic acids. Crystallization at both 15°C and 10°C temperature at constant ratio of oil and solvent shows decreasing amount of olein fractions with the subsequent increase in the corresponding stearin fractions with varying temperature from 15°C to 10°C. The melting point of olein fractions increases and corresponding stearin fractions decreases at constant temperature with the increasing volume of solvent from 1:3 to 1:5 wt/vol. In decreasing the crystallization temperature from 15°C to 10°C, melting point of olein fractions decreases and corresponding stearin fractions increases due to increased amounts of the saturated acids of higher molecular size than the medium chain triglycerides in the fractions.

The iodine value of fractions of coconut oil as shown in table 2 shows that the olein fraction has the higher amount of iodine value than the corresponding stearin fraction at constant temperature but the values have varied with different ratio of oil and solvent (1:3, 1:4 and 1:5 wt/vol.). The iodine value increases with olein fraction but decreases with stearin with lowering the crystallization temperature from 15°C to 10°C. The iodine value of olein fractions increases as expected and the highest was observed with 1:4 wt/vol. ratio at constant temperature, which may be explained by the fact that the unsaturated fatty acid containing glycerides concentrated relatively more in olein fraction while the saturated fatty acids containing glycerides concentrated in the stearin fractions. The determination of saponification value of coconut oil’s fractions were made and the values were indicated in table 2.The olein fraction obtained at 15°C using oil and Isopropanol in 1:3wt/v ratio has the saponification value of 281and the corresponding stearin fraction has the saponification value of 256 as the short chain saturated fatty acid containing glycerides were concentrated relatively more in olein fraction than the respective stearin fraction containing the long chain saturated fatty acid containing glycerides.

Table 3: Fatty acid composition (%w/w) of Coconut olein and stearin fractions obtained at 15°C with varying oil:solvent (wt/v)ratios: Fatty acids (%w/w) 8:0 10:0 12:0 14:0 16:0 18:0 18:1 18:2

olein (15°C)fractions 1:3 3.94± 0.14b 4.41± 0.01a 47.45± 0.33a 23.47± 0.06c 11.31± 0.10b 2.26± 0.14a 5.07± 0.06a 2.19± 0.07b

1:4 3.25± 0.05a 4.72± 0.03b 47.5± 0.20a 17.28± 0.07a 13.73± 0.15c 2.40± 0.01b 9.52± 0.02c 1.6± 0.01a

stearin(15°C)fractions 1:5 6.25± 0.05c 5.43± 0.05c 47.92± 0.11a 18.69± 0.09b 8.51± 0.01a 2.73± 0.01c 7.90± 0.02b 2.57± 0.07c

1:3 2.34± 0.14a 4.05± 0.09a 43.53± 0.06a 22.55± 0.09b 13.86± 0.04c 5.63± 0.05c 6.40± 0.01b 1.64± 0.07b

1:4 4.13± 0.03c 4.66± 0.09c 48.97± 0.10c 23.40± 0.02c 9.40± 0.01a 2.92± 0.03b 5.19± 0.16a 1.33± 0.05a

1:5 2.92± 0.03b 4.20± 0.04b 46.81± 0.12b 21.82± 0.03a 9.86± 0.09b 2.74± 0.05a 6.75± 0.05c 4.90± 0.05c

Results have been expressed as mean ± SD (n=3). For all data in Table 3, Mean Values having different superscript letter in rows are significantly different (p<0.05). (for olein and stearin separately)

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Table 4: Fatty acid composition (%w/w) of Coconut olein and stearin fractions obtained at 10°C with varying oil:solvent (wt/v)ratios: Fatty acids (%w/w)

8:0 10:0 12:0 14:0 16:0 18:0 18:1 18:2

olein (10°C) fractions

1:3 1.76± 0.02b 4.38± 0.03b 48.44± 0.10b 21.94± 0.07c 9.71± 0.02c 3.00± 0.05c 8.43± 0.05a 2.34± 0.10b

1:4 4.73± 0.04c 5.47± 0.04c 47.48± 0.07a 17.98± 0.05a 8.59± 0.02a 2.93± 0.02b 9.73± 0.05c 3.06± 0.10c

stearin(10°C) fractions

1:5 1.36± 0.25a 4.19± 0.02a 52.01± 0.07c 20.51± 0.22b 8.63± 0.05b 2.56± 0.06a 8.47± 0.03b 2.27± 0.07a

1:3 1.49± 0.03b 4.83± 0.02c 51.98± 0.02c 23.43± 0.06b 9.30± 0.06a 2.79± 0.02a 4.92± 0.03a 1.26± 0.02a

1:4 1.85± 0.01c 4.12± 0.07b 48.42± 0.13b 23.71± 0.12c 10.17± 0.29b 3.14± 0.24b 6.78± 0.05b 1.81± 0.02b

1:5 1.47± 0.02a 3.79± 0.59a 46.48± 0.03a 22.08± 0.14a 13.62± 0.21c 3.27± 0.03c 7.19± 0.02c 2.10± 0.17c

Results have been expressed as mean ± SD (n=3). For all data in Table 4, Mean Values having different superscript letter in columns are significantly different (p<0.05) (for olein and stearin separately). The olein fractions displayed a distinct variation in the fatty acid compositions (shown in Table 3 and Table 4). Both Caprylic acid (C8:0) and Capric acid (C10:0) content increased in olein fractions compared to original coconut oil whereas decreased in corresponding stearin fractions. The concentration of short chain saturated fatty acids was found to be increased in olein fraction with the decrease in temperature during crystallization from 15°C to 10°C, but the concentrations were found to be decreased in olein fraction as the volume of solvent increased during crystallization from 1:3wt/vol. to 1:5 wt/vol.

IV. CONCLUSION The fractionation of coconut oil from isopropanol as a solvent was done at different temperatures (10°,15° and 20°C) with different volume of solvent ratio (1:3,1:4 and 1:5 wt/vol.). The crystallization was quite prompt as isopropanol had readily formed crystals while fractionating coconut oil. It is evident from the study that coconut oil can be fractionated with the help of a bio-renewable polar solvent like isopropanol to readily produce oleins rich in medium chain fatty acids and stearin fractions. The olein fractions thus obtained can be used to formulate different food products especially spread like products enriched in medium chain fatty

acids. Isopropanol as a fractionating solvent in comparison with acetone and hexane is quite promising from industrial point of view as the recovery of isopropanol was very much convenient, temperature required for crystallization was relatively high and time involved also was much less.

V. REFERENCES [1]

[2]

[3]

[4]

[5]

Babayan VK (1981) Medium-Chain Length Fatty Acid Esters and Their Medical and Nutritional Applications. J. Am. Oil Chem Soc 58:49A–51A. Norris FA. Chap; Extraction of Fats and Oils, Bailey’s Industrial Oil and Fat Products by Daniel Swern, (1982), Vol 2,4th ed. Wiley-Interscience Publication, New York, 238-239. Pal PK, Bhattacharyya DK, Ghosh S (2000) Isopropanol fractionation of butter oil and characteristics of fractions. J Am Oil Chem Soc 77:1215-1218. Gibon V et al; Chap;Fractionation of lipids for use in food, Modifying lipids for use in food by Gunstone FD.,( 2006), Woodhead publishing limited, England, , 203-205). Sea News Circular, The Solvent Extractor’s Association of India, Feb 2015, Issue11 vol.xvii,37.

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[6]

[7]

[8]

[9]

[10]

[11]

[12]

[13]

[14]

Gopala Krishna AG, Gaurav R, Bhatnagar AS, Kumar P, Chandrashekhar P (2010) Coconut oil: Chemistry, production and its applications-A review. Indian Coconut Journal 15-27 Hoahland R, Snider GG (1943) Digestability of certain higher saturated fatty acids and triglycerides. J. Nutri 26(3): 219-225. Johnson RC, Cotter R (1986) Metabolism of medium chain triglyceride lipid emulsions. Nutr Int 2:150-158. Yamashita, M., and Y. Kadona (1982) Digestion, Absorption, and Metabolism of Medium-Chain Triglycerides, New Food Industry 24:28–33. Julius U, and Leonhardt W (1988) Elimination and Metabolism of a Fat Emulsion Containing Medium-Chain Triglycerides (Lipo-fundin MCT 10%), J. Parenteral and Enternal Nutrition 12:116–120. Batch AC, Babayan VK (1982) Medium-chain triglycerides: an update. Am J Clin Nutr 36:950– 961. Ghosh S, Bhattacharyya DK (1997) Mediumchain fatty acid-rich glycerides by chemical and lipase-catalyzed polyester–monoester interchange re-action. J Am Oil Chem Soc 74:593–595. ASSOCIATION OF OFFICIAL AGRICULTURAL CHEMISTS - AOAC (2005) Official Methods of Analysis of AOAC International, 18th Ed, Maryland: AOAC International. Brockerhoff H (1965) Stereospecific analysis of triglycerides: an analysis of human depot fat.Arch Biochem Biophys Jun;110(3):586-592.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

A Review of Membrane Technology for Gas Separation Sanket D. Awasare*a, G S kulkarnib, Prashant P. Patilc, , S.M.Chavand, John U. Kennedy Oubagaranadine a,b,c

Department of Technology , Shivaji University Kolhapur , Kolhapur, Maharashtra, India Department of Chemical Engineering, Sinhgad college of engineering, Pune, Maharashtra, India e Department of Ceramic and Cement Technology, PDA College of Engineering, Gulbarga, Karnataka, India d

ABSTRACT Membrane separation is now worldwide acknowledged as a cost-effective process to produce moderate purity streams containing up to 98 - 99.5 % nitrogen or 25-40 % oxygen. Therefore, the demand for higher product purity of membrane air separation had motivated carrying out of this study. The objective of this study is to testing a suitable membrane for gas separation, gas separation membranes are extensively used for the separation of gas. Polymeric membranes have mechanical strength, reproducibility and economical processing capacity. However they suffer from upper bound trade-off between permeability and selectivity. Inorganic membranes have high selectivity, robustness, thermal and chemical stability but these membranes are economically unfavourable due to high capital and maintenance cost. In mixed matrix membrane superior gas separation properties of inorganic membranes and economical processes ability of polymeric membranes are exploited by combining the inorganic particles in polymer matrix. In case of glassy polymer, poor distributions of dispersed phase in polymer matrix and week contact of particles in polymer matrix are the challenges in mixed matrix membrane. For rubbery polymers, poor selectivity of mixed matrix membrane is the core problem. Blending of a glassy and a rubbery polymer with amines is suggested to develop a polymeric blend membrane by coating the polymer blend with different amines of high selectivity and permeability. The developed membrane will be characterized and its performance will be evaluated for the separation of gas terms of selectivity and permeability. Keywords: Membrane Technology, Gas Separation, Rubbery Polymers, Mixed Matrix Membrane, Polymeric Membranes.

I. INTRODUCTION Gas separation is an important unit operation employed widely throughout the chemical industries. Examples include the separation of air into oxygen and nitrogen, and the removal of volatile organic compounds from effluent streams. The traditional methods used for such separations include cryogenic distillation and adsorbent bed processes. In recent times, however membranebased gas separation is becoming increasingly popular due to its inherent advantages over the more traditional methods. These include low capital and operating costs, lower energy requirements and generally ease of operation. A membrane may be simply defined as an interphase between two bulk phases [1]. During the last 30 years, the use of membranes in separation processes has grown at a very rapid pace. Presently membrane-

based processes are being used in a wide array of applications, such as microfiltration, ultrafiltration, nanofiltration, reverse osmosis and electrodialysis [1, 2]. Gas separation in membranes occurs due to differences in permeability’s of the species flowing through the membrane. With a few exceptions, membranes used for gas separation can be broadly categorized into two major classes: porous inorganic and dense polymeric. Porous membranes have a well-defined static pore structure, which depending on the formation process can be highly connected and torturous or non-connected and straight. Pores in inorganic membranes can be classified according to their size as macropores (>500A° ), mesopores (500–20A° ) or micropores (<20A° ) [3]. Across these pore size regimes, gas transport in inorganic membranes may occur via a host of four

IJSRST15141 | Received: 01 November 2015 | Accepted: 26 November 2015 | November-December 2015 [(1)5: 89-93]

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different types basic principles or mechanisms of gas separation Representation is given the figure 1:

Figure 1: Schematic diagram of transport mechanism in gas separation membranes [4]

1.1 Poiseuille Flow Poiseuille flow is also known as viscous flow. It occurs when the pore radius (r) inmembranes is larger than the mean free path (λ) of the gas penetrants. The mean freepath refers to the average distance traversed by a gas molecule during collisions and is represented by equation (2.1). During collisions, the membrane contains pores largeenough to allocate convective flow, where gas molecules collide exclusively with each other and there is no separation between the gas components. Poiseuille flow takes place when the membranes have much larger pore sizes than gas molecules which are larger than 10 μm[4-6]. (

)

Equation 2.1

Where η is the gas viscosity, P is the pressure, T is the temperature, R is the universal gas constant and M is the gas molecular weight [4].

Where Mx and My are the gas molecular weights of gas x and gas y, respectively. Membrane with Knudsen diffusion is not favorable for industrial application due to its relative low gas-pair selectivity [4-6]. 1.3 Molecular Sieving Molecular sieving mechanism is the separation based on the size discrimination between gas penetrant in the pores less than 7Å in diameter. In this transport mechanism, gases with small molecular size and high diffusion rate are able to permeate through the ultramicrospores of the polymer while the gases with large molecular size will experience a stronger repulsive force and restricted them from passing through. In general, molecular sieving is the main mechanism for inorganic separation such as zeolites and carbon molecular sieves. The porous membrane yields high permeability while the selectivity is based on the size discrimination between the gases [4-6] 1.4 Solution diffusion The solution diffusion mechanism is most profound in explaining the transportation ofgases in dense or nonporous polymeric membranes. Conceptually, this mechanism comprises of three steps. Firstly, gases adsorb into the polymer at the boundary in contact with the feed. Secondly, gas molecules diffuse across the membranes through a concentration gradient. Thirdly, gases desorb at the permeate side [4-6]

II. METHODS AND MATERIAL 2. Literature Review

1.2. Knudsen diffusion Knudsen diffusion happens when the pore size of the membrane decreases to 50-100Å in diameter. The penetrant gas flows through the membrane almost independent from each other during Knudsen diffusion. For an equimolar feed, the selectivity, α induced by Knudsen diffusion is inversely proportional to the square root of the molecular weight of the respective two gases as shown in the following equation[4-6] ⁄



Equation 2.2

Membrane technology covers all engineering approaches for the transport of substances between two fractions with the help of permeable membranes. In general, mechanical separation processes for separating gaseous or liquid streams use membrane technology. Membrane separation processes operate without heating and therefore use less energy than conventional thermal separation processes such as distillation, sublimation or crystallization, etc. The separation process is purely physical and both fractions (permeate and retentate) can be used. Cold separation using membrane technology is widely used. Membrane separation processes have a very important role in the separation industry.

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Membrane separation processes differ based on separation mechanisms and size of the separated

particles. Some of the widely used membrane processes are shown in the table 2.1 [7].

Reverse Osmosis

Materials Passed Ions and LowMolecular Weight Organics Water

Gas and Vapor Separations

Gases vapors

Vapor-Liquid Separation

Vapors

Process

Concept

Dialysis

and

Driving Force

Materials Retained

Concentration Difference

Dissolved and Suspended Material with Molecular Weight > 1000 Virtually All Suspended and Dissolved Material

Pressure Difference, Typically 100-1500 psi Pressure Difference, Typically 15-1500 psi

MembraneImpermeable Gases and Vapors

Pressure Difference and Vapor-Liquid Equilibrium

MembraneImpermeable Liquids and Vapors

2.1 What is Membrane A membrane is a selective barrier; It allows some things to pass through but stops others. Such things may be molecules, ions, or other small particles. The influent of an artificial membrane is known as the feed-stream, the liquid that passes through the membrane is known as permeate, and the liquid containing the retained constituents is the retentate or concentrate [8-9]. The ideal representation of the membrane concept is shown in the figure 2 below.

Gas Separation O2/N2

H2/Hydrocarbons H2/CO H2/N2 CO2/Hydrocarbons

H2S/Hydrocarbons H2O/Hydrocarbons He/Hydrocarbons H2O/Air He/N2 Hydrocarbon/Air Hydrocarbons streams

from

process

Application Oxygen enrichment, Nitrogen (Inert Gas) Separation Refinery hydrogen recovery Syngas ratio adjustment Ammonia purge gas Acid gas treatment enhanced oil recovery, landfill gas upgrading Sour gas treating Natural gas dehydration Helium separation Air dehydration Helium recovery Pollution control, hydrocarbon recovery Organic solvent recovery, monomer recovery

Figure 2: Idealized membrane flow concept. (Source: Internet) 2.3 Issues and Challenges in Membrane Applications

2.2 Industrial Applications of Membrane in Gas Separation Membrane separation processes have very important role in separation industry because membrane separation processes is that it operate without heating. Nevertheless, they were not considered technically important until mid-1970. The industrial gas separation is widely spread by using the membrane in last 25 years. The multiple application of gas separation Membrane is listed in Table 2.2.1[7, 16]

for Gas Separation The following issues and challenges occur membranes application for gas separation [7-9] 2.3.1 Membrane Fouling 2.3.2 High Cost 2.3.3 Concentration of Polarization 2.3.4 Lack of selectivity 2.3.5 Lack of mechanical resistance 2.3.6 Sensitivity to chemical attack 2.3.7 Membrane cleaning

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in

2.3.8 Module Design 2.4 Materials for Gas Separation Membrane The selection of material membrane is the most important factor for Gas Separation. Chemical interaction between a membrane material and a gas penetrant determined the separation efficiency of a membrane separation process [10]. The choice of material is based on the application and costeffectiveness. The most important requirements of effective separation material are:[11,12] 2.4.1. Engineering feasibility. 2.4.2. Good chemical resistance. 2.4.3. High separation efficiency with reasonable high flux. 2.4.4 Good mechanical stability. 2.4.5. High thermal stability. 2.4.6. Low cost. 2.5 Membrane used for Gas Separation 2.5.1 Polymeric Membranes Polymeric membranes perform their process by different mechanisms which are based upon the properties of membrane means physical and chemical structure, interaction between membrane, component and nature of gas [13]. It can be classified into two types: porous and non-porous [14, 16]. A porous membrane is a rigid, highly voided structure with randomly distributed interconnected pores like a conventional filter. Separation is dependent on molecular size of polymer and pore size distribution. These membranes exhibit high fluxes but they are inherently low selective. Non porous membrane also called as dense membrane consists of a dense film. Permeate molecules are first absorbed and then diffused through polymer matrix under the driving force of pressure or concentration gradient. Dense membranes are highly selective but transport of gas through the polymer medium is very low. Permeate of similar sizes can be separated by dense membranes if they have significantly different solubility in polymer. Polymeric membranes can be classified on the basis on polymer material.

Glassy Polymer At a low temperature the amorphous regions of a polymer in the glassy state, the molecules are frozen on place. They may be able to fluctuate slightly, but they do not have any segmental motion in which portions of the molecule wiggles around. Whenever the amorphous regions of a polymer are in the glassy state, it generally will be brittle, hard and rigid [14, 16]. Rubbery Polymer If the polymer is heated it eventually will reach its glass transition temperature. The molecules can start to wiggle around at this temperature. The polymer now is in its rubbery state. The rubbery state tends to softness and flexibility to a polymer. Semicrystalline solids have both crystalline and amorphous regions. Accordingly the temperature, in the amorphous regions can be either in the rubbery or glassy state. Temperature at which the transition in the amorphous regions between the glassy and rubbery state occurs is called the glass transition temperature. The amorphous portion of semi-crystalline solid contains the glass transition property. During the glass transition the crystalline portion remains crystalline. There is a general tradeoff between permeability and selectivity for polymeric membranes with rubbery polymeric membranes with high permeability and low selectivity and vice versa for glassy polymeric membranes. Despite their mechanical strength, reproducibility and economical processing capacity, dense membranes are still not much attractive because they suffer from upper bound tradeoff between permeability and selectivity [14, 16]. 2.6 Comparison of Polymeric, Inorganic and Mixed Matrix Membranes A comparison of polymeric, organic and mixed matrix membrane is given in table in terms of cost, chemical and thermal stability, and mechanical strength, compatibility to solvent, swelling, separation performance and handling. It is clear from the table that polymeric membranes are economical to fabricate and have good mechanical strength. Their separation performance and stability is moderate and these are robust in handling. Their main disadvantage lies in swelling and compatibility to solvent. However still for industrial applications polymeric membranes are preferred. Different techniques are being used to

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improve the performance of polymeric membranes to withstand required duties. Blending is a cost and time effective method to develop materials with desired properties [15, 16]. Properties

Cost Chemical and thermal stability

Polymeric membranes

Inorganic membranes

Mixed matrix membranes

Economical

High

Moderate

V. REFERENCES [1] [2] [3]

[4]

Moderate

High

High

Mechanical Strength

Good

Poor

Excellent

Compatibility to solvent

Limited

Separation Performance

Frequently Occurs

[5] [6]

Wind Range

Limited

Free of swelling

Free of swelling

[7]

[8]

Swelling

Handling

Moderate

Robust

Moderate

brittle

Exceed Robeson upper boundary Robust

III. CONCLUSION The present research addresses the current needs of having high permeability and selectivity membrane for removal of gas. The developed polymer blend membranes have improved flexibility, reduced cost, improved process ability, and enhanced selectivity and/or permeability compared to the comparable polymer membranes that comprise a single polymer. It will be possible to develop polymeric blend membrane for separating high pressure gas streams at their processing pressure. This advantage could offer cost savings that may provide a new incentive for polymeric blend membranes. This result opens a new tool for studying gas separation by polymeric blend membranes.

[9]

[10] [11] [12]

[13]

[14]

[15]

IV. ACKNOWLEDGMENT [16]

I am very thankful to Department of Technology, Shivaji University Kolhapur, who gives the financial support to me for my higher studies.

W.S.W. Ho, K.K. Sirkar (Eds.), Membrane Handbook, Van Nostrand Reinhold, New York, 1992. M. Mulder, Basic Principles of Membrane Technology, Kluwer Academic Publishers, Dordrecht, 1996. J. Karger, D.M. Ruthven, Diffusion in zeolites and other microporous solids, John Wiley & Sons Inc., New York, 1992. Yong Wai Fen, “Polymers Of Intrinsic Microporosity Based Membranes For Gas Separation”, National university of singapour ,2014 W.J. Koros, G.K. Fleming, Membrane-based gas separation, J. Membr. Sci. 83 (1993) 1 J. Karger, D.M. Ruthven, Diffusion in zeolites and other microporoussolids, John Wiley & Sons Inc., New York, 1992. Theodore T. Moore, Shilpa Damle, David Wallace and William J. Koros, “Membrane Separation”, CRC Press LLC, 2005 C.J. Geankoplis, “Transport Processes and Unit Operations”, 3rd ed., Prentice Hall, Englewood Cliffs, New Jersey, 1993. (Chapter 13) W.L. McCabe, J.C. Smith, P. Harriott, "Unit Operations of Chemical Engineering", 5th ed., McGraw-Hill, New York, 1993. (Chapter 26) T. Aoki, Macromolecular design of permselective membranes, Prog. Polym. Sci, 24 (1999) 951. K. Scott, Membrane separation technology, Scientific & Technical Information, Oxford, 1990. H.Strathmann, Membrane separation processes: Current relevance and future opportunities, AIChE Journal, 47 (2001) 1077 M.Duval, B.Folkers, M.H.V.Mulder, G.D.Desgrarnd Champs and C.A. Smolders,Adsorbent filled membranes For gas separation, properties of polymeric membranes by incorporstion of by microporous adsorbent,J. Member.Sci. vol R.Abedini and A. Nezhadmoghadam, "APPLICATION OF MEMBRANE IN GAS SEPARATION PROCESSES: ITS SUITABILITY AND MECHANISMS," Petroleum & Coal, vol. 52, pp. 69-80, 2010 A. F. Ismail, et al., "Transport and separation properties of carbon nanotube-mixed matrix membrane," Separation and Purification Technology, vol. 70, pp. 1226, 2009. Asim Mushtaq, Hilmi Bin Mukhtar, Azmi Mohd Shariff, Hafiz Abdul Mannan , A Review: Development of Polymeric Blend Membrane for Removal of CO2 from Natural Gas, IJET-IJENS Vol:13 pp 53-60 2014

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

An Assessment of the Impact of Information Communication Technology on Secondary School Teachers in Kebbi State, Nigeria Nwoji J. O Department of Computer Science, Waziri Umaru Federal Polytechnic, Birnin Kebbi, Nigeria

ABSTRACT In the world today, technology has been a powerful tool for growth, and the basis for numerous economic and social transformations. New technologies, if properly harnessed by exploiting the positive opportunities provided, is capable of bridging the development and educational divides among and within educational sector in any nation. Information Communication Technology (ICT) is one of such new technologies that have brought about digital revolution. This paper is focused on the impact of ICT on secondary school teachers in Kebbi State with Birnin kebbi as the case study. A research has been conducted making use of structured questionnaires to get the views of the teachers. A sample of eight hundred and fifty (850) questionnaires was distributed to selected secondary school teachers, out of which six hundred and eighty-five (685) copies of the questionnaires were completed and returned by the respondents. The responses from the questionnaires have been analyzed and interpreted. The findings from the result show that ICT has contributed immensely towards teaching-learning process amongst secondary school teachers in Kebbi State. Also, there is need for training and retraining of teachers, proper supervision of teachers to enhance full utilization of ICT facilities available in schools. Constant power supply should be made available to schools to further enhance steady use of the facilities. Keywords: ICT, Secondary School, Internet, Kebbi State.

I. INTRODUCTION Information Communication Technology (ICT) is the processing, storage, distribution of data and many others [1]. It is basically made up of the following components namely: electronic processing using computer, transmission of information using telecommunication equipment and dissemination of information in multimedia. These technologies are being utilized to restructure and reorganize the sphere of production, distribution and circulation [1]. The usage of ICTs in Nigeria and in African countries generally is increasing and rapidly growing. However, while there is a great deal of knowledge about how ICTs are being used in developed countries, there is no much information on how ICTs are being introduced into schools in developing countries [2].

for existing teaching methods but also seen as an important instrument to support new ways of teachinglearning process. It is being integrated into the teachinglearning process in various educational institutions in Nigeria and the world in general [10]. Though, ICT is somewhat new phenomenon in Nigeria, the application of computer have been carried out in many areas of human activities, such as medicine, domestic activities, engineering, architecture, and education [10]. It is pertinent to assess the impact of ICT in the secondary school education. For the schools to be effective, computer literacy should be established through availability of computers, computer utilization, and content competencies in the schools, as well as through teachers‟ effectiveness in the areas of teaching and learning, record keeping, supporting student academic performance, teachers job performance, school discipline and community services.

The application of ICT has transformed the learning and teaching process in which students deal with knowledge This paper focuses on the extent to which ICT has in an active, self-directed and constructive way. ICT is improved the effectiveness of education sector in Kebbi not only employed as an instrument, which can be added State with specific reference to secondary school

IJSRST151520 | Received: 23 November 2015 | Accepted: 29 November 2015 | November-December 2015 [(1)5: 94-101]

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teachers in Birnin Kebbi. A sample of eight hundred and fifty(850) questionnaires were distributed through random selection to secondary school teachers in the metropolis, out of which six hundred and eighty-five (685) copies of the questionnaires were duly answered and returned by the respondents. Hence, these data were analyzed using simple frequencies, percentages and chisquare methods. Background and Literature Research The cut throat competition facing secondary school teachers in Nigeria today requires each of them to be on the leading edge of the new technology [3]. The recent advancement in ICT components, such as computer, internet, electronic mail etc resulting in computer network, which is a connection of computers whereby data are exchanged and computing resources are shared among them as much as possible. Due to this, computer system has been applied to all field of operation; both private and public bodies have employed the use of computer in carrying out their daily business routine to replace the obsolete manual method in order to obtain high level of productivity [3]. Students that u s e ICT gain deeper understanding of complex topics and concepts, and are more likely to remember information and use it to solve problems outside the class environment [4]. In addition, students extend and deepen their knowledge, investigation, and inquiry through ICT according to needs and interest when access to information is available on multiple levels. Several researches have been conducted on the impact of ICT on secondary school teachers. [5] investigated the level of awareness of primary and secondary school teachers of Oyo state invited for a capacity building workshop of Nigeria‟s educational policy on ICT as well as its possible influence on the use of ICT for classroom teaching and learning. Data collection was done using a self-constructed and validated questionnaire titled: „Teachers awareness of Nigeria‟s educational policy on ICT‟. The data was analyzed using simple percentage, ttest and ANOVA. These studies found that only a small percentage of the respondents possess a high level of awareness of the country‟s educational policy on ICT. Also, [6] assess secondary school teachers‟ use of ICT in Oyo metropolis of Oyo state. This study examines the availability and usability of Information and

communication technology among secondary school teachers in Oyo Metropolis. The Research Design employed is the descriptive survey design. Data collected were analyzed using frequency tables and simple percentage. Results of the study showed that ICT facilities are not available in most of the schools covered. It was also observed that most teachers used in the sample for the study, are not competent in the use of ICT. [7] investigated skills challenges in adoption and use ICT in public secondary school, Kenya. The study explored teachers‟ skills that influenced the process of adoption and use of ICT in public secondary schools. It adopted a descriptive survey research design. Data collected was analyzed by use of descriptive and inferential statistical techniques after which results were presented in tables. The findings established that there was limited supply of qualified ICT teachers in Kenya. [8] conducted a study by assessing the competence of ICT of rural and urban secondary school ICT teachers for the implementation of ICT curriculum in North Eastern Nigeria. Grand mean, standard deviation and percentage were used to analyze the data. Results reveal that the competence of ICT teachers on policy, curriculum, pedagogy, technology, administration and professional development is low. Obstacles to ICT teachers‟ competences were identified as lack of hardware, software, and financial resources, lack of electricity in most rural schools and insufficient information and experience from teachers in ICT applications. Furthermore, [9] conducted a research on teachers‟ attitude towards the use of ICT as a pedagogical tool in secondary schools in Tanzania, taking Kondoa District as the case study. The data collection method involved questionnaire and interview. This study adopted the mixed method approach which considers both quantitative and qualitative as the methodological solutions. It was found that teachers have positive attitudes towards the use of ICT as a pedagogical tool but they did not integrate it in their teaching effectively. Also, low familiarity with ICT usage as a pedagogical tool among teachers was found to be a problem. Also, [10] carried out an investigation on the level of ICT awareness among secondary school teachers in Sokoto State metropolis, Nigeria. The Research Design employed is the descriptive survey design. The analysis

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of data collected was done using frequency tables, simple percentage and ANOVA. Results of the study showed that majority of secondary schools have ICT facilities but the level of ICT training to teachers is fair. However, it was observed that some teachers were not using ICT facilities in teaching and learning as a result of improper training and lack of power supply

II. METHODS AND MATERIAL

Study sample and sampling procedure The samples of this study consist of six hundred and eighty-five (685) teachers (principals inclusive) of various secondary schools in Birnin Kebbi, randomly selected under the following classes: Gender, Age group (AG), Educational qualification (EQ). Questionnaire was given to them as respondent in a fair and uniform manner in order to represent the entire population of the study.

Research design This study is a descriptive and analytical research design. A detailed questionnaire with relevant information was employed and its aim was for identification of variables and their relationship. The questionnaire was design to sample the opinions of various secondary schools teachers in Birnin Kebbi on the impact of ICT on secondary school education in Kebbi State. Individuals in the group were selected using random sampling method. The strategy is that the researcher was able to establish validation rules for the data collected for this group so that variances in the results could be controlled. Research (target) population and study area The population of this research study covers both public and private secondary school teachers in Kebbi State taking cognizance of their different background, age group and educational status. While this research intends to look at Kebbi State as a whole, data investigation was limited to Birnin kebbi the state capital for logistic reasons. Thus, it was assumed that result obtained for Birnin kebbi can be generalized for the whole of Kebbi State. Research instrument In achieving the purpose of this study, a questionnaire was designed and used to collect the primary data analyzed. The questionnaire was tagged “The assessment on the impact of information communication technology on secondary school teachers”, and questions posed related directly to the nature of data required. In testing the research questions, closed end questionnaires was used. The questionnaire was meant for teachers of various secondary schools. In the questionnaire, a point rate scale was used; Yes, No.

Validation of research instrument The content and construct validity of the research instruments was conducted by the researcher in order that the reliability of inferences drawn from such instrument is guaranteed. The validation of the questionnaire was done by one computer scientist, and one educationist. This exercise assisted in informing some of the questions in the research instrument, in other to maintain the face and content validity. The reliability of the questionnaire was then conducted through a pilot test conducted on a number of coresearchers. The questionnaire was distributed along with error log. Error log is a sheet of paper on which the participants were asked to record details of any typographical error, contest error or ambiguous language. The participants were encouraged to make suggestions as to how the questionnaire could be improved to eliminate ambiguity. Method of Data collection The researcher personally administered questionnaire to respondents from the various secondary schools visited in Birnin Kebbi through random selection of teachers. The information supplied by these respondents constitutes the primary source of information for the study. Method of Data Analysis The data collected from the study were analyzed using simple frequencies, percentages and chi-square methods.

III. RESULT AND DISCUSSION For the purpose of this research, Eight hundred and fifty

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(850) copies of questionnaires were distributed to teachers in various secondary schools in the metropolis, out of which six hundred and eighty-five (685) were completed and returned by the respondents. The data were analyzed and presented using tabular, percentage and chi-square methods for easy understanding. Table 1.0: Gender of the Respondents Gender

B.TECH 20 2.9 B.A 17 2.5 B.SC 94 13.7 B.SC ED 110 16.1 M.SC 17 2.5 M.ED 13 1.9 Total 685 100 Source: Questionnaire administered 2015

2.9 2.5 13.7 16.1 2.5 1.9 100

Frequency Percentage

Valid percentage Male 300 43.8 43.8 Female 385 56.2 56.2 Total 685 100.0 100 Source: Questionnaire administered 2015

Statistical Table 3.0, it shows that 3.4% of the entire population representing 2 3 respondents is N D holders, 2 2 % of the entire population representing 151 respondents is NCE holders, 6.1% of the entire population representing 42 respondents is HND holders, 19% of the entire population representing 130 respondents is B.Ed holders, 9.9% of the total From s t a t i s t i c a l table 1 . 0 , 43.8% of the total population representing 68 respondents is B.Ed.Tech respondents are male while the remaining 56.2% are holders, 2.9% of the entire population representing 20 females. The analysis shows that most of the respondents respondents is B.Tech holders, 2.5% of the entire are females based on the gender distribution in table 1.0 population representing 17 respondents is B.A holders, 13.7% of the entire population representing 94 Table 2.0 Age of respondents respondents is B.Sc holders, 16.1% of the entire population representing 110 respondents is holders of Age Frequency Percentage Valid B.Sc.Ed. 2.5% of the entire population representing 17 (years) percentage respondents is holders of M.Sc, while 1.9% of the entire 20-29 230 33.6 33.6 population representing 13 respondents is holders of 30-39 307 44.8 44.8 M.Ed. From the analysis, it shows that respondents whose qualifications are NCE ranks high, followed by 40-49 99 14.4 14.4 respondents with B.Ed qualifications and B.Sc,Ed, 50 and 49 7.2 7.2 respectively. above Total 685 100.0 100 Table 4.0 Marital status of respondents Source: Questionnaire administered 2015 Table 2.0, indicates that majority of the respondents fall between the ages of 30-39 representing 44.8%. This shows that a lot of the respondents are in their prime age. Table 3.0 respondents

Educational

Qualification

Qualification

Frequency

Percentage

ND NCE HND B.ED B.ED TECH

23 151 42 130 68

3.4 22 6.1 19 9.9

of

the

Valid percentage 3.4 22 6.1 19 9.9

Frequency

Percentage

Single 374 54.6 Married 311 45.4 Total 685 100 Source: Questionnaire administered 2015

Valid percentage 54.6 45.4 100

Table 4.0 shows that 54.6% of the total population representing 374 respondents is not married, while 45.4% of the population representing 311 respondents is married. This indicates that large numbers of the respondents are still single.

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Table 5.0 Teaching Experience of the Respondents Age Frequency Percentage Valid (years) percentage 0-5 243 35.5 35.5 6-10 200 29.2 29.2 11-15 132 19.3 19.3 16-20 64 9.3 9.3 21-25 27 3.9 3.9 26-30 11 1.6 1.6 31 and 8 1.2 1.2 above Total 685 100 100 Source: Questionnaire administered 2015

Table 7.0 shows that 67 respondents of the entire population representing 9.8% heard of ICT through Library, 28.5% of the total population which is 194 respondents heard of it via Media, 43.5% of the total population which is 299 respondents heard of it via Schools, 15.3% of the total population representing 103 respondents heard about it via Friends, while 2.9% of the total population heard of it via other means. This clearly indicates that considerably very high number of respondents got the awareness through schools. Table 8.0: Do you know what ICT means? Response

Frequency

Percentage

Valid percentage 94.9 5.1 100.0

The analysis in Table 5.0 shows that 35.5% of the total population representing 243 respondents with teaching experience between 0-5years constitutes the majority of the entire population.

Yes 650 94.9 No 35 5.1 Total 685 100.0 Source: Questionnaire administered 2015

Table 6.0: Have you heard of ICT before?

Table 8.0 shows that 650 respondents constituting 94.9% of the entire population knows the meaning of ICT, while only 35 respondents representing 5.1% of the population do not know what it means. This indicates that most of the Secondary School teachers in Birnin Kebbi understand the meaning of ICT.

Response

Frequency

Percentage

Yes 670 97.8 No 15 2.2 Total 685 100.0 Source: Questionnaire administered 2015

Valid percentage 97.8 2.2 100.0

Table 6.0 shows that 97.8% of the total population representing 670 respondents have heard about ICT, while 2.2% of the population, representing 15 respondents have never heard about Information Communication Technology. This indicates that the awareness of ICT amongst teachers are considerably high. Table 7.0: How did you hear about ICT? Responses

Frequency

Percentage

Library 67 9.8 Media 194 28.5 Schools 299 43.5 Friends 103 15.3 Others 22 2.9 Total 685 100.0 Source: Questionnaire administered 2015

Valid percentage 9.8 28.5 43.5 15.3 2.9 100.0

Table 9.0: Do you have Internet facilities in your school? Response Frequency Percentage Valid percentage Yes 420 61.3 61.3 No 265 38.7 38.7 Total 685 100.0 100.0 Source: Questionnaire administered 2015 Table 9.0 shows that 420 respondents which constitute 61.3% of the total population have Internet facilities in their various schools while 265 respondents representing 38.7% of the total population do not have Internet facilities in their schools. Thus, indicating that very large number of respondents have Internet facilities in school.

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Table 10.0: Do you use ICT facilities in teachinglearning process? Response

Frequency

Percentage

Valid percentage Yes 645 94.2 94.2 No 45 5.8 5.8 Total 685 100.0 100.0 Source: Questionnaire administered 2015

Response Yes No Row Total 645 0 645 Yes 0 45 45 No 645 45 685 Total Source: Questionnaire administered 2015 Chi-square statistic is estimated using the following equation. k

X 2   (oi  ei ) 2 / ei i 1

Table 10.0 shows that 94.2% of the population which where; represents 640 respondents use ICT facilities in teachingX 2  Chi-square learning process in their schools, while 5.8% of the total population representing 45 respondents do not use ICT Oi = Observed frequency facilities in teaching-learning process. This indicates that ei  expected frequency greater percentage of the respondents make use of the K = total number of cells (category) available ICT facilities in teaching-learning, in their Therefore; various schools. Table 11.0: Have you undergone any form of training on the use of ICT facilities? Response Frequency Percentage Valid percentage Yes 376 54.9 54.9 No 309 45.1 45.1 Total 685 100.0 100.0 Source: Questionnaire administered 2015 Table 11.0 shows that 54.9% of the population representing 376 respondents has undergone training on the use of some ICT facilities, while 45.1% of the total population representing 309 respondents has not undergone any form of training. This indicates that larger percentage has gone for training for some use of ICT facilities but not all apply same in teaching-learning process. Hypothesis Testing

e = (RT * CT)/GT where; RT = RowTotal CT = Column Total GT = Grand Total Table 12.0: Computations using Chi-square statistic Observed Expected

oi -ei

(oi -ei ) 2 X 2  (oi -ei ) 2 /ei

645 0 0 45

38 -42 -42 42

1444 1764 1764 1764

607 42 42 3

2.4 42 42 588 674.4

Source: Computation by Researcher 2015 The degree of freedom = d.f = (r – 1) (c – 1)  (5-1)(5-1)  16  d.f 5% significance level   = (0.05)

The hypothesis for the research is stated as follows; Table 12.0 shows that X2 calculated = 674.4, and the H0: Has ICT not improved teaching-learning process critical table ( X2 tabulated) = 26.296, at  = (0.05). among teachers? H1: Has ICT improved teaching-learning process among Decision Rule teachers? The Chi-square test is used for the hypothesis testing and Table 10.0 is used to analyze the hypothesis.

Based on the analysis, since X2 calculated = 674.4, while the critical table ( X2 tabulated) = 26.296 at 

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2 2 (0.05). This shows that ( X calculated) > ( X tabulated), therefore we reject the null hypothesis Ho, and accept the alternative hypothesis that ICT has improved teachinglearning process among secondary school teachers.

The degree of freedom = d.f = (r – 1) (c – 1)  (2-1)(2-1) 1 5% significance level   = 0.05 Table 13.0 shows that X2 calculated = 612.7, and the critical table ( X2 tabulated) = 3.841 at  = (0.05)

Hypothesis 2; Ho: Has ICT not improved teaching-learning process Decision Rule among teachers? The responses from Table 8.0 is used for analysis and Our analysis show that X2 calculated > the value on the test for the hypothesis Ho critical table ( X2 tabulated), at degree of freedom,  = Response Yes No RowTotal (0.05), we therefore reject the null hypothesis Ho, and accept the alternative hypothesis that ICT has impact on the respondents.

650 0 650 Yes 0 35 35 No 650 35 685 Total Source: Questionnaire administered 2015

IV.

Chi-square statistic is used to test the hypothesis. k

X 2   (oi  ei ) 2 / ei i 1

where; X 2  Chi-square Oi = Observed frequency ei  expected frequency K = total number of cells (category) Therefore;

e = (RT * CT)/GT where; RT = RowTotal CT = Column Total GT = Grand Total

CONCLUSION AND RECOMMENDATION

For the schools to be effective, computer literacy should be established through availability of computers, computer utilization, and content competencies in the schools, as well as through teachers‟ effectiveness in the areas of teaching-learning, record keeping, supporting student academic performance, teachers job performance, school discipline and community services. The application of ICT has transformed the learning and teaching process in which secondary school teacher‟s deal with knowledge in an active, self-directed and constructive way. ICT is not only employed as an instrument, which can be added for existing teaching methods but also seen as an important instrument to support new ways of teaching-learning process. It is being integrated into the teaching-learning process in various educational institutions in Nigeria and the world in general.

Table 13.0: Computations using Chi-square statistic Observed Expected

oi -ei

(oi -ei ) 2

650 0 0 35

32 -33 -33 -33

1024 1089 1089 1089

618 33 33 2

This research revealed that the emergence of ICT have greatly improved the teaching-learning process in many X 2  (oi -ei ) 2 /e secondary school teachers in Kebbi State, Nigeria. ICT i facilities are available in most schools. However, there is still need for more training and retraining of teachers. 1.7 Also, it is recommended that constant power supply 33 should be made available in schools so as to avail 33 teachers, more opportunity of using these facilities. 545 612.7

Source: Computation by Researcher 2015

Finally, Non-Government Organizations‟, Parents Teachers Association, Religious Organizations, etc. should provide the required ICT infrastructure in schools.

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V. REFERENCES [1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

[9]

Khan, M.I., Puyol. H.G., Kent, N.I. and Gupta, I.E. (2008). The Role of Information and Communication Technology in addressing conflict management issues. Proceedings of the 1st national Engineering Technology in addressing conflict management issues. pp 266-269. Beukes-Amiss, C.M. and Chiware, E.R.T. (2006). The impact of diffusion of ICTs into educational practices, how good or how bad? A review of the Namibia situation. Available at: http://www.dspace.unam.na:8443/dspace/bitstrea m/1995/244/impact+diffusionICTedupdf {Accessed 10 February 2007}. Ogundele, O.S., Adewale, O.S., and Alesse, B.K. (2008). Empirical Analysis of the Impact of Information technology on Secondary Education in Ondo State, Nigeria. Proceedings of the 22nd National conference of Nigeria Computer Society, Vol.19.pp.85-96. Apple Computer, (2015). The impact of Technology on students‟ achievement. Available at http://www.oten.info/conferences/jukes/ResearchS ummary.pdf. Adebowale, O. F., and Dare, N. O. (2012). Teachers‟ Awareness of Nigeria‟s Educational Policy on ICT and the use of ICT in Oyo State Secondary Schools. International journal of computing and ICT research, 6(1), 84-93. Obakhume, A. S. A. (2012). Assessment of Secondary School Teachers' Use of Information and Communication Technology (ICT) in Oyo metropolis, Nigeria. Journal Plus Education/Educatia Plus, 8(1). Mingaine, L. (2013). Skill challenges in adoption and Use of ICT in public Secondary Schools, Kenya. International Journal of Humanities and Social Science, 3(13), 61-72. Badau, K. M., & Sakiyo, J. (2013). Assessment of ICT Teachers‟ Competence to Implement the New ICT Curriculum in North Eastern Nigeria. Journal of Education and Practice, 4(27), 10-20. Ndibalema, P. (2014). Teachers‟ Attitudes towards the Use of Information Communication Technology (ICT) as a Pedagogical Tool in

Secondary Schools in Tanzania: The Case of Kondoa District. International Journal of Education and Research, 2(2), 1-16. [10] Buhari, B. A. and Nwoji J.O. (2015). Investigation on the level of ICT Awareness among Secondary School Teachers in Sokoto State, Nigeria. International Journal of Scientific Research in Science and Technology. Vol.1.issue.4.pp 105111.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Effluent Treatment Plant of Sugar Wastewater – A Review Sanket D Awasare*, Harshavardhan U Bhosale, Nita P Chavan M. Tech Student (Envi Sci & Tech), Department of Technology, Shivaji University, Kolhapur, Maharashtra, India

ABSTRACT Sugar Industry is also called sugar cane mill. The production of sugar from which is carried out. As we known the cane is cash crop. So the sugar industry is the major industry which takes part in the growth of the country. Sugar industry is one of the major industries which have been included in the polluting industries. Sugar industry wastewater has a high degree of pollution parameters. Present report thus gives the different parameter studies such as pH, BOD, COD, etc. also the study of the sugar industry Bidri – Shri Dudhganga-Vedganga Sahakari Sakhar Karkhana Ltd. The parameters permissible limits which are prescribed by the board are also studied. Keywords: Sugar Industry, cash crop, pollution parameters, BOD, COD.

I. INTRODUCTION

only creates problem but also wastes the water resource [2] . In this aspect the present study pointed out the Water is an essential part of all living organisms. In this pollutants concentration in the sugar industry effluent. connection water plays a most valuable and important Once determine the concentration of pollutants in the role in the natural cycle. Among the whole water effluents, the wastewater treatment system can also be availability, only 3% fresh water is available on the earth. modified as per the modern technology to remove the In the available fresh water sources, entries of pollutants maximum concentration of pollutants in the wastewater [5] . have been significantly increased from industries and domestic/anthropogenic activities. In this scenario the conservation strategies plays an important role in the In countries like Cuba, Jamaica and India the sugar is conservation of fresh water bodies as well as water produced from sugar cane, while in other many places quality. Huge quantity of fresh water will be consumed beetroots are used as the raw material for sugar for the production process which will be held in the production. A large volume of waste of organic nature is industry. In the mean while the amount of consumption produced during the period of production and normally of fresh water is equal to the amount of discharge of they are discharged onto land or into the nearby water wastewater as effluent [5]. Rapid urbanization and course, usually small streams, practically without industrialization in the developing countries like India pretreatment. Condition becomes worse as the stream are facing severe problems in collection, treatment and flow reaches a very low level and eventually when disposal of effluents. Unmanaged organic waste enough dilution water is not available during the period fractions from industries, municipalities and agricultural of operation. Putrefaction of polluted stream water sector decompose in the environment resulting in large caused by heave discharge of organic waste, resulting in scale contamination of land, water and air. This is the odors nuisance near the sugar industry is a very leading to serious public health problems and common phenomenon. In fact, all the concerned bodies, environmental degradation. Unfortunately, due to the both sugar industry and pollution control agencies are lack of knowledge, financial support and sometimes aware of these problems and are trying to find an unwillingness to spend on treatment of wastewater, most economical means to stop the nuisance created by the [1] of sugar industries in developing countries discharge sugar industry effluent . their wastewater without adequate treatment. This not

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II. METHODS AND MATERIAL A. Sugar Industry 2.1 Manufacturing of sugar Sugar cane is normally harvested manually in India. The sugar canes are cut into pieces and crushed in a series of rollers to extract the juice in the mill house. The milk of lime is then added to juice and heated, when all the colloidal and suspended impurities are coagulated; much of the color is also removed during this lime treatment. The coagulated juice is then clarified to remove the sludge. The sludge is further filtered through filter presses and then disposed of as solid waste. The clarified juice is then preheated and concentrated in evaporators and vacuum pans. The partially crystalized syrup from the vacuum pan known as ―massecuite‖ is then transferred to the crystallizers, where complete crystallization of sugar occurs. The messecuite is then centrifuged to separate the sugar crystals from the mother liquor. The spent liquor is discarded as ―Black Strap Molasses‖. The sugar is then dried and bagged for transport. The fibrous residue of the mill house is known as ―bagasse‖, which may be burned in the boilers or may be used as raw-materials for the production of paper products, or may be used for generation of electricity. A flow diagram of the process of manufacturing in a typical sugar industry is given in Figure 1 [1].

though small in volume, contains high BOD and suspended solids. Additional waste originates due to the leakages and spillages of juices, syrups and molasses in different sections, and also due to the handling of molasses. The periodical washing of the floor also contributes a great lot of the pollution load. Though these wastes are small in volume and are discharged intermittently, they have got a very high BOD [1]. 2.3 Effect of waste on receiving water The fresh effluent from the sugar industry decomposes rapidly after few hours of stagnation. It has been found that it causes considerable difficulties when their effluent gets an access to the water courses, particularly the small and non-perennial streams in rural areas. The rapid depletion of oxygen due to biological oxidation followed by anaerobic stabilization of the waste causes a secondary pollution of offensive odors, black color, and fish mortality. No question of the discharge of this waste into sewers is arises, as most of the sugar industries are situated in the un-sewered rural areas [1]. 3. Company Profile Shri Dudganga-Vedganga Sahakari Sakhar Karkhana Ltd., Bidri, Dist. Kolhapur was established on 10th October 1956 under the Bombay CO-operative Societies Act, 1925. The details are show below in Figure 2.

Figure 1: Flow Diagram for Sugar Manufacturing Process

2.2 Sources of wastewater Waste from mill house includes the water used as splashes to extract maximum amount of juice, and those used to cool the roller bearings. As such the mill house waste contains high BOD due to the presence of sugar and the machineries. The filter cloth used to filter the juice need cleaning. The wash water thus used produced

Figure 2 : Certificate of Registration.

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Table 1: General Information of Industry 1.

Name and location of industry

2.

Site location

3. 4. 5.

Total plot area Built-up area Area available for the use of treated sewage / trade effluent for gardening irrigation List of products / byproducts manufactured

6.

7.

List of raw materials and process chemicals with annual consumption

Shri. Dudhganga Vedganga SSK Ltd. Bidri (Mouninagar) Tal. Kagal, Dist. Kolhapur-416208. The river Dudhganga is at 2.2 km from site. 177 acres 15 acres 36 hectors

Sugar – 600-650 M.T./day Molasses – 54006000 M.T./M Bagasse – 36000 M.T./M Pressmud – 5400 M.T./M Electricity – 20 M.W./hr. Sugar cane – 5000 M.T./day Bagasse – 45 TPH Coal – 13.48 TPH

Figure 4: Process Flow Chart for the Sugar Manufacturing Process of Industry.

3.2 Water budget Daily requirement of water is given in the table below. Table 2: Water Budget For Sugar & Co-generation Cooling Mill bearing, hot liquid, pumps glands, Spray pond

Process Imbibition water, In Oliver & Emico pans

Was hing & Clea ning

Boil er

Labo rator y

Domestic

Effluent

Effluent

Effl uent

Efflu ent

Efflu ent

Effluent

3.1 Process Figure 3 shows the process flow for manufacturing of

Total effluent is treated in the State-of-the art ETP & treated effluent is used for irrigation purpose.

sugar in Dudhganga Vedganga SSK Ltd.

Efflient is treated in welldesigned septic tanks followed by soak pits.

3.3 Co-generation Project

Figure 3: Process Flow Diagram for the Sugar Manufacturing Process of Industry. Figure 4 shows the flow chart of manufacturing of sugar in Dudhganga Vedganga SSK Ltd.

In year 2014-15, a total of 76519808 units of electricity are produced from the co-generation unit of the industry. Among the produced electricity 15495423 units of electricity and for co-generation unit 6578560 units of electricity is utilized by the industry itself. The remaining 54445825 units of electricity is being exported to electricity board, from which a total of Rs. 330427000/- is the profit to the industry from the cogeneration project which is situated within the industry premises.

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III. RESULT AND DISCUSSION Effluent Treatment Plant The consumption of large volumes of water and the generation of organic compounds as liquid effluents are major environmental problems in sugarcane processing industry. The inadequate and indiscriminate disposal of this effluent in soils and water bodies has received much attention since decades ago, due to environmental problems associated to this practice. The sugar cane industry is among those industries with the largest water demands and, in addition, is an important source of nontoxic organic pollution combined with the fact that India it is second largest producer and largest consumer makes it all the more important [7]. Like any other industries, the pollution load in sugar mills can also be reduced with a better water and material economy practiced in the plant. Judicious use of water in various plant practices, and its recycle, wherever practicable, will reduce the volume of waste to a great extent [1]. The operation of the ETP is such that it will give an effluent of such standard, prescribed by the Maharashtra Pollution Control Board (MPCB). The following prescribed standard by the board or under EP Act, 1986. Dudhganga Vedganga SSK has provided an ETP. The units of the ETP are: 1) Screen Chamber cum Oil & Grease tank 2) Equalization Tank 3) Mixing Tank 4) Aeration Tank with aerator 5) Clarifier 6) Sludge Drying Bed. Table 3: Norms for Sugar Industry Sr. No.

Parameters

1. 2. 3.

pH Oil & Grease BOD (3 days 270C)

Standards Prescribed by Board Limiting concentration in mg/l, except for pH 5.5-9.0 10 100

4. 5. 6. 7. 8.

Sulphate Suspended Solids COD Chloride Total Dissolved Solids

1000 100 250 600 2100

The flow diagram of the ETP is shown in the diagram below (Figure 5).

Figure 5: Process Flow Diagram of ETP of Industry.

A. Screen chamber cum oil & grease tank The screen chamber (Bar Screen) is used to remove the large floating objects. The untreated effluent may contain large floating solids, paper etc. The screening chamber prevents these materials from choking pipe system and clogging the pumps, impellers and aberration to equipments.in this chamber, all these materials are removes by bar screen which are 10 mm wide and 50 mm deep, arranged with spacing of 20 mm between 2 adjacent bars. For removal of trapped matter frequent cleaning activities is carried out. Oil & grease chamber works for the removal of oil & grease from the influent which may cause damage to pumping unit, hazard to biological treatments. The combination of the bar screen and oil and grease chamber is provided in the ETP as shown in the Figure. B. Equalization Tank Equalization basins may be used for temporary storage of diurnal or wet-weather flow peaks. Basins provide a place to temporarily hold incoming sewage during plant maintenance and a means of diluting and distributing batch discharges of toxic or high-strength waste which might otherwise inhibit biological secondary treatment

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(including portable toilet waste, vehicle holding tanks, and septic tank pumpers). Flow equalization basins require variable discharge control, typically include provisions for bypass and cleaning, and may also include aerators. Cleaning may be easier if the basin is downstream of screening and grit removal. C. Mixing Tank Mixing tanks are generally provided for through mixing of the influent which if held in the equalization tank. The mixing is carried out with the help of mechanical stirrers.

IV. CONCLUSION The study concerned with the ETP for sugar industry. It can be concluded that, the overall performance of the effluent treatment plant was satisfactory. The individual units are also performing well and their removal efficiencies are satisfactory. The treated effluent meets the MPCB standard for discharge in inland surface water hence it can be said that the plant is working efficiently. This treatment plant is high potential for, reduction for pH, Temperature, TDS, and COD. The treated wastewater at outlet of ETP is given to the garden area of the industry. The details of the same are given in the table below.

D. Aeration Tank with aerators Table 8: List of Trees Planted in the Industrial Premises Aeration is the process by which air is circulated through, mixed with or dissolved in a liquid or substance. Hence aeration tank are provided to aerate the wastewater by the biological treatment of the waste can be carried with greater efficiency. E. Clarifier Clarifiers are settling tanks built with mechanical means for continuous removal of solids being deposited by sedimentation. A clarifier is generally used to remove solid particulates or suspended solids from liquid for clarification and (or) thickening. Concentrated impurities, discharged from the bottom of the tank are known as sludge, while the particles that float to the surface of the liquid are called scum.

F. Sludge Drying Bed The sludge drying beds are used for dewater the settled sludge. The excess sludge from the clarifier is discharged to sludge drying beds at intervals so that the concentration of MLSS is maintained in aeration tank. These are the sand beds of 250 mm of sand over about equally thick well-graded gravel layer, underlain by perforated drainage lines spaced 2.5 to 6 m apart. The bed should slope towards the discharge end at rate of 1 in 200.

Sr. No. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29.

Type of Tree Planted Rain tree Gulmohar Nilgiri Saagvan Pleta forum Glyricidia Ulta ashok Spathodia Umber Jambhul Bhendi Silver oak Jacaranda Coconut Chikku Mango Supari Fanas Limbu Kadhipatta Peru Aawala Bottle brush Bottle palm Chinch Kavati chapha Pivala chapha Badam Hirava chapha

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No. of Trees 289 185 500 600 35 349 200 4 5 83 5 80 46 900 80 112 12 20 35 25 79 9 12 53 9 1 4 1 2

106

30. 31. 32. 33. 34. 35. 36.

Papaya Aavada Bakuli Cassia Vad Christmas tree Morpankhi Total

15 5 2 215 12 7 26 4017

V. REFERENCES [1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

M Narayana Rao and Amal K Datta, ―Wastewater Treatment-Rational Methods of Design and Industrial Practices‖, Third Edition, Oxford & IBN Publishing Co. Pvt. Ltd., New Delhi, India. A S Tanksali, ―Treatment Of Sugar Industry Wastewater By Upflow Anaerobic Sludge Blanket Reactor‖, International Journal of Chem Tech Research, Vol. 5; No. 3; 2013, ISSN: 0974-4290. Abdul Rehman Memon, Suhail Ahmed Soomro and Abdul Khaliq Ansari, ―Sugar Indutry Effluent - Characteristics and Chemical Analysis‖, J. App. Em. Sc., Vol. 1; No. 2; 2006, ISSN: 1814-070X. C B Shivayogimath and Rashmi Jahagirdar, ―Treatment Of Sugar Industry Wastewater Using Electrocoagulation Technique‖, International Journal of Research in Engineering and Technology, IC-RICE Conference Issue; 2013, eISSN: 2319-1163; p-ISSN: 2321-7308. D Shiva Kumar and S Srikantaswamy, ―Evaluation Of Effluent Quality Of A Sugar Industry By Using PhysicoChemical Parameters‖, International Journal of Advanced Research in Engineering and Applied Sciences, Vol. 4; No. 1; 2015, ISSN: 2278-6252. Hampannavar U S and Shivayogimath C B, ―Anaerobic treatment of sugar industry wastewater by Upflow anaerobic sludge blanket reactor at ambient temperature‖, International Journal of Environmental Sciences, Vol. 1; No. 4; 2010, ISSN: 0976-4402. M Rais, A Sheoran, ―Treatment of Sugarcane Industry Effluents: Science & Technology issues‖, M. Rais Int. Journal of Engineering Research and Applications, Vol. 5; No. 1(Part 2); 2015, ISSN: 2248-9622. M Sunitha and Mohd Abdur Rafeeq, ―Sugar Industry Wastewater Treatment Using

Adsorption‖, Jr. of Industrial Pollution Control, Vol. 25; No. 2; 2009, ISSN: 0970-2083. [9] Mahdi Reyahi Khoram, Mahdi Safikhani And Seyed Mostafa Khezri, ―Review of Hosein Aabad Sugar Factory (HASF) Wastewater and Assessment of its Pollution Load‖, J. Appl. Sci. Environ. Manage., Vol. 17; No. 3; 2013, ISSN: 1119-8362. [10] Usha Damodharan and M Vikram Reddy, ―Impact of Sugar Industrial Treated Effluent on the Growth Factor in Sugarcane—Cuddalore, India‖, Journal of Sustainable Bioenergy Systems, Vol. 2; 2012, ISSN: 2165-4018. [11] Weqar A Siddiqui and Muhammad Waseem, ―A Comparative Study of Sugar Mill Treated and Untreated Effluent- A Case Study‖, Oriental Journal of Chemistry, Vol. 28; No. 4; 2012, ISSN: 0970-020X.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

PEGASIS : Power-Efficient Gathering in Sensor Information Systems Alpesh R. Sankaliya Electronics & Communication Engineering Department, Government Polytechnic, Dahod, Gujarat, India

ABSTRACT Sensor network consisting of nodes with limited battery power and wireless communications are deployed to collect useful information from the field. The main idea in PEGASIS is for each node to receive from and transmit to close neighbors and take turns being the leader for transmission to the BS. This approach distributes the energy load evenly among the sensor nodes in the network. Sensor nodes are randomly deployed in the sensor field, and therefore, the ith node is at a random location. The nodes will be organized to form a chain, which can either be accomplished by the sensor nodes themselves using a greedy algorithm. The algorithm to resolve the unbalanced energy consumption problem caused by long distance data transmission of some nodes in a chain formed by the greedy algorithm. Keywords: LEACH, MSC, PEGASIS, BS, Wireless Sensor Network, Greedy Algorithms

I. INTRODUCTION

In area of sensor network lot work has been done in the area of Wireless Sensor Network, but still a long way to A Wireless Sensor Network consists of a number of go. Wireless Sensor networks consist of hundreds of energy constrained sensor nodes. These nodes are thousands of low power multi-functional sensor nodes, deployed in a random fashion and can communicate operating in an unattended environment, with limited among themselves to make an ad-hoc network. The computation and sensing capabilities. Sensor nodes are sensor nodes communicate with the sink node in a equipped with small, often irreplaceable batteries with wireless faction. The wireless medium may either of limited power capacities. The use of wireless sensor radio frequencies, infrared or any other medium having networks is increasing day by day and at the same time no wired connection. The primary concern in Wireless it faces the problem of energy constraints in terms of Sensor Network (WSN) is to maximize the network limited battery lifetime. Various approaches can be lifetime as long as possible, as it is not possible to taken to save energy caused by communication in replace or recharge the batteries of thousands of sensor wireless sensor networks. One of them is to adopting nodes as they are often deployed in a remote or energy efficient routing algorithms. The routing impractical environment. If each node transmits its data algorithms in the sensor networks broadly classified into directly to the sink, some nodes that are far away from three categories: Flat, Hierarchical and Location based the sink will die much earlier than the other sensor nodes. routing. The cluster based routing holds great promise This is as a result of rapid energy depletion due to long for many-to-one and one-to-many communication distance data transmission. Consequently, this problem paradigms that are prevalent in sensor networks. This limits the use of WSN to gather data in certain regions. dissertation work includes the survey of various cluster This becomes a cause that cannot be done to gather data based routing protocols and implementation of LEACH in certain regions. Thus, a more effective use of energy routing protocol. The idea proposed in LEACH has been becomes the major challenge in WSNs. To improve an inspiration for many hierarchical routing protocols. energy efficiency, many researchers have suggested The finally it propose some modifications to improve the performance of the LEACH routing protocol. The various routing algorithms. simulation results were then analyzed based on the

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suggested evaluation metrics in order to verify their suitability for use in wireless sensor networks.

II. METHODS AND MATERIAL

Goal of LEACH: Evaluate the energy efficiency of cluster-based routing protocols such as LEACH and PEGASIS with extended conditions of general complexity of data fusion algorithm, general data compressing ratio and long distance.

A. LEACH

Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol uses the hierarchical routing for wireless sensor networks to increase the life time of the network. In a cluster based architecture one node acts as a cluster head and all other nodes in a network are the member nodes of the network. The member nodes collects the information and send their collected data to the cluster head and cluster head receives data from all these nodes, process it and send it to the destined base station. So cluster head is more energy demanding than other nodes. When a cluster head dies all other cluster member nodes become unable to communicate. LEACH incorporates randomized rotation of the cluster head position such that it rotates among the sensors to avoid draining the battery of any sensor node in the network. So, the energy load associated with being a cluster head is evenly distributed among the nodes to save the network energy. However it has a number of disadvantages, one of them is that the Cluster head directly communicates with BS ignoring the distance between CH and BS. In LEACH, it considers the energy dissipation of the receivers and concludes that multi-hop is energy efficient only in certain network topology and radio parameters of the system. The main idea of LEACH is to consider the local data fusion in each cluster to reduce the amount of redundant data that must be transmitted to BS. Each cluster head, instead of each sensor node, directly sends fusion data to BS, thus it extends the lifetime of major nodes

The nodes of wireless sensor networks, with limited computing, communicating and sensing capabilities as well as limited energy, can make the best use themselves to gather data from sensor nodes to Base Station (BS) by using excellent network topologies, optimized routing schemes or data fusion algorithms in order gain the lifetime as long as possible. In the simplest direct communication routing protocol, each sensor node directly communicates with base station. Since the distance is large, it consumes the energy quickly in most cases B. Power-Efficient Gathering in Sensor Information Systems (PEGASIS)

Lindsey et al proposed this protocol, which is an enhancement over the LEACH protocol. The main idea in PEGASIS is for each node to receive from and transmit to close neighbors and take turns being the leader for transmission to the BS. This approach distributes the energy load evenly among the sensor nodes in the network. Sensor nodes are randomly deployed in the sensor field, and therefore, the ith node is at a random location. The nodes will be organized to form a chain, which can either be accomplished by the sensor nodes themselves using a greedy algorithm starting from some node. Alternatively, the BS can compute this chain and broadcast it to all the sensor nodes. For constructing the chain, it is assumed that all nodes have global knowledge of the network and employ the greedy algorithm. The greedy approach to constructing the chain works well and this is done before the first round of communication. To construct the chain, it starts with the furthest node from the BS. To begin with this node in order to make sure that nodes farther from the BS have close neighbors, as in the greedy algorithm the neighbor distances will increase gradually since nodes already on the chain cannot be revisited.

Figure 1: LEACH

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The goals of PEGASIS are as follows: 

To minimize the transmission distance of each node



To minimize the overhead



To minimize the messages that need to be sent to the BS



To pass out the energy consumption equally across all nodes

Figure 2: Illustration of PEGASIS protocol

C. Greedy Algorithms A greedy algorithm is an algorithm that follows the problem solving heuristic of making the locally optimal choice at each stage with the hope of finding a global optimum. In many problems, a greedy strategy does not in general produce an optimal solution, but nonetheless a greedy heuristic may yield locally optimal solutions that approximate a global optimal solution in a reasonable time. Wireless Sensor Networks have found popularity in a variety of applications ranging from warfare tactics to medical sciences to oil pipelining in recent years. And such wide variety of applications has resulted in a lot of research into finding better ways of implementing these networks and maintaining them with minimal loss of energy.

Problems involved with deployment, communication and routing and many more are being considered and attempts to find better solutions made. Target Coverage Problem is another such problem that discusses about the activation and scheduling of the sensors in such a way so that the network lifetime is maximised. Now in the last chapter a conclusion was drawn regarding the nature of this problem which was found to be NP-Hard. The implications of this are that no known algorithm thus exists that can solve the problem in polynomial time and also proving us with the optimal solution. That is why most of the research has been performed for finding out better heuristic algorithms that can provide if not optimal, at least a sub optimal or near optimal solution to this problem. First we see at a simple greedy based strategy which at any point selects that sensor which is covering the maximum number of target nodes. This step is required to understand the flaws with the normal approach and in which direction one needs to think in order to define new heuristics. Then we look at the algorithm in reference and simulate that existing algorithm which aims to provide a near optimal solution to the Target Coverage Problem in polynomial time. Now the simple algorithm aims at generating a Maximum Set Cover (MSC), where the elements of the set cover are nothing but sensors that are to be activated. In any cycle, only those sensors included in the set cover are activated and rest are kept in sleep mode. The set cover is constructed so that the members of the set cover can cover all the targets and monitor them with their available energy. If there is at least one target which cannot be covered by the members of the set cover then that set cover is discarded and the operational time of that set cover is noted which is added to the total network running time, which is called the Network Lifetime of the network. An Advanced Greedy Based Heuristic Algorithm Usually the scenario is that there are a lot of sensors which are deployed in each other's vicinity and so the intersection of the set of target nodes that each of them cover can be large that is two sensors might be covering a similar set of target nodes.

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If SN1 and SN2 are two sensors having lifetime LT1 and LT2 respectively, and are covering almost similar targets then our aim should be to activate these two sensors at different cycles so that the effective time that we get is (LT1+LT2). On the other hand it is easy to notice that if both the sensors get activated at the same cycle then the time for which their mutual targets are getting covered is maximum(LT1, LT2). This need can be satisfied by using the modified heuristic of selecting that sensor that covers the maximum number of uncovered target nodes at each iteration to construct the set cover.

Figure 3: Performance of Proposed versus Existing Algorithm

III. RESULT AND DISCUSSION The simulation is based on the exact same network as the earlier one. A stationary network with a fixed number of targets and sensors randomly deployed around the targets is simulated. The range of each sensor is considered fixed and so is the initial energy of the sensor which is kept equal for all sensors without any loss of generality. After each iteration we increase the number of sensors and run the algorithm to note the new Network Lifetime. So the number of sensors is the variable parameter here. The main objective of is to record the increase in network lifetime as we increase the number of sensors. The number of sensors is increased and for every new number of sensors the network lifetime is noted. Then a graph is plotted. The formal procedure is as follows:   

The minimum number of sensors is taken to be 20. Then we assigned the sensors using the MSC heuristic algorithm and noted the network lifetime. The number of sensors was varied from 20 to 100.

IV. CONCLUSION In this paper, we describe PEGASIS, a greedy chain protocol that is near optimal for a data-gathering problem in sensor networks. PEGASIS outperforms LEACH by eliminating the overhead of dynamic cluster formation, minimizing the distance non leader-nodes must transmit, limiting the number of transmissions and receives among all nodes, and using only one transmission to the BS per round. Gathering information from a WSN in an energy effective manner is of paramount importance in order to prolong its life span. This calls for use of an appropriate routing protocol to ensure efficient data transmission through the network. In this research project, we have proposed an Amend implementation of LEACH protocol based on energy heterogeneity and optimizes it through genetic algorithm. The result of simulations conducted indicates that the proposed approach is more energy efficient and hence effective in prolonging the network life time compared to LEACH.

V. REFERENCES [1]

[2]

S. Lindsey, C. Raghavendra and K. M. Sivalingam, “Data Gathering algorithms in sensor networks using the energy metric,” in , IEEE Transactions on Parallel and Distributed Systems, vol. 13, Issue 9, pp. 924-935, Sep. 2002. Wang Linping, Cai Zhen, Bi Wu and Wang Zufeng, “Improved algorithm of PEGASIS protocol introducing double cluster heads in

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[3]

[4]

[5]

[6]

[7]

[8] [9] [10]

[11]

[12]

[13]

wireless sensor network,” in International Conference on Computer, Mechatronics, Control and Electronic Engineering (CMCE), vol. 1, pp. 148-151, Changchun, Aug. 2010. YU Yong-chang, WEI Gang, “An Improved PEGASIS Algorithm in Wireless Sensor Network,” in the proceedings of Acta Electronica Sinica, vol.36, pp.1309- 1313, July 2008. Z. Aliouat and M. Aliouat, “Efficient Management of Energy Budget for PEGASIS Routing Protocol,” in 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), pp. 516-521, Sousse, March 2012. T. Shankar, Dr. S. Shanmugavel, “Hybrid Approach For Energy Optimization In Cluster Based WSN Using Energy Balancing Clustering Protocol,” Journal of Theoretical and Applied Information Technology, vol. 49, pp. 906-921, March 2013. Performance Evaluation of Ad-hoc On demand Multipath Distance Vector Routing Protocol . P.Jammulaiah, P.Ravindranaik, Ravi Gorripati. 2013, IJWCNT, Vol. 2. Hai Liu, Pengjun Wan and Xiaohua Jia, \Maximal lifetime scheduling for sensor surveillance systems with k sensors to 1 target", IEEE Transactions on parallel and Distributed Systems, Vol. 17, No. 12, December 2006. M. Lu, J. Wu, M. Cardei and M. Li, \Energy-e cient connected coverage of discrete targets in wireless sensor networks", 2005. Laura Marie Feeney, \An Energy Consumption Model for Performance Analysis of Routing Protocols for Mobile and Ad Hoc Networks", Mobile Networks and Applications, 2000, 2000. Feng Xia, \QoS Challenges and Opportunities in Wireless Sensor/Actuator Networks" Sensors, pp. 1-4, 2008. Jennifer C. Hou, David K. Y. Yau, Chris Y. T. Ma, Yong Yang, Honghai Zhang,I Hong Hou, Nageswara S. V. Rao and Mallikarjun Shankar, \Coverage in Wireless Sensor Networks", pp. 13. M. Bani Yassein, A. Al-zou'bi, Y. Khamayseh, W. Mardini, “Improvement on LEACH Protocol

of Wireless Sensor Network (VLEACH)”, International Journal of Digital Content Technology and its Applications Volume 3, Number 2, June 2009.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Agricultural Land Suitability Assessment using Fuzzy Logic and Geographic Information System Techniques Atijosan A*1, Muibi K2, Ogunyemi S3, Adewoyin J4, Badru R5, Alaga A6, Shaba A7 1-6

COPINE, Obafemi Awolowo University Campus, Ile-Ife, Nigeria 7 NASRDA, Abuja, Nigeria

ABSTRACT Fuzzy logic and Geographical Information System (GIS) based techniques were used for land suitability evaluation and production of land suitability maps for oil palm cultivation in Ife Central Local Government Area of Osun State, Southwestern Nigeria. Land and climatic characteristics data were obtained from a previous soil fertility evaluation of Ife Central Local Government Area. Ten land and climatic characteristics fitted to membership functions were used in computing land suitability index for each point observation based on the Sematic Import (SI) model. Average membership value for cation exchange capacity (CEC) is the lowest (0.216), whereas that of pH is the highest (0.809). Computed land suitability index for oil palm in the study area ranged from 0.32 to 0.52 with a mean of 0.44. CEC, annual rainfall and months of dry season with mean membership functions of 0.21, 0.22 and 0.24 respectively are the major constraints to oil palm cultivation. Land suitability map was produced using G.I.S based techniques. The use of fuzzy logic has proved valuable for identifying major constraints to oil palm cultivation. The production of suitability maps through the use of GIS techniques will further enhance decision making and strategies in overcoming these constraints. Keywords: Fuzzy Logic, G.I.S, S.I Model, Oil Palm and Land Suitability Map

I. INTRODUCTION The need for increased production of food crops, ecofriendly practices, and optimal utilization of agricultural land/soil resources has become a major developmental issue in Africa (Panel, 2014, Ademola et.al, 2004). Much attention is now being shifted on selection of a crop which best suits a particular agricultural land area (Ogunlade et.al, 2012). Crucial to the estimation of land suitability is the matching of land characteristics with the requirement of envisaged land utilization types (Sarmadian et.al, 2014). Unfortunately most of these procedures are highly subjective. It is important to utilize techniques that minimize human bias to improve the pragmatic values of land suitability assessment. This project therefore aims at applying fuzzy logic and GIS based techniques for agricultural land suitability assessment in Ife Central Local Government Area.

The objectives of this project were to (i) apply fuzzy logic to evaluate land suitability for oil palm cultivation in Ife Central Local Government. (ii) production of land suitability map for oil palm cultivation in the study area using GIS techniques.

II. METHODS AND MATERIAL A. Study Area The study area covers Ife Central Local Government Area located in Osun State, South-western Nigeria. It lies between latitudes 7o 28’ 43.5’’N and 7o37’ 51.41’’N and spans between longitude 4o 27’ 22.5’’E and 4o35’ 40.61’’E. Figure 1, illustrates the map of the study area. The climate of the study area can be described as humid tropical. The geology of the area as reviewed by (Rahaman, 1976) includes granite gneiss and schist epidiorite. The soil of the study area is Alfisols with Ferruginous Tropical overlay in most

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cases. The soil belongs to Iwo association at series level and can be classified as OxicTropudalf by the USDA system. They are principally derived from granite and gneiss parent materials. The area is drained by a very large network of rivers such as Obudu, Opa, Esinmirin, Ominrin, Ogbe, Okun, Mokuro and other smaller tributaries (Maruf et al., 2015).

Figure 1: Map of the study area

palm cultivation were selected. Descriptive statistics for the dataset are presented in Table 1. TABLE 1 DESCRIPTIVE STATISTICS FOR LAND CHARACTERISTICS Land characteristics Climate Annual rainfall (mm) Month of dry season Relative humidity (%) Topography Slope (%) Wetness Drainage Soil physical characteristics Clay (%) Sand (%) Fertility CEC (cmol/kg) Organic carbon (%) pH

Minimum

Mean

Maximum

1150

1250

1350

4

4

4

41.8

73.9

75.9

2

7

14

1

1.4

2

5.4 34.12

27.29 56.81

61.81 77.2

0.63 0.08 5.5

3.22 0.93 6.43

6.13 1.98 7.4

C. Fuzzy Logic

Figure 2: Different membership functions and parameters used to determine membership values of land characteristics (Burrough and McDonnell 2000).

B. Data Sources Land characteristics data were obtained from a soil fertility evaluation of Ife Central Local Government Area by Alabi et al., (2012). Ten land characteristics in five (5) land quality groups considered important for oil

Fuzzy sets provide means to model the uncertainty associated with vagueness, imprecision, and lack of information regarding a problem or data (Sivanandam and Deepa, 2007). In this study, fuzzy logic was used for computing land suitability index. Further applications of fuzzy logic include water quality model development (Md et al., 2009), forecasting (Amit and Babita, 2012), land suitability and evaluation (Braimoh et al., 2004; Fang et al., 2014). A fuzzy set may be used for classification of objects where classes do not have rigidly defined boundaries (Zadeh 1965). If represents a space of objects or phenomena, then the fuzzy set is the set of ordered pairs represented mathematically as

{

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(1)

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Where is the membership function of any to by taking values within the interval [0,1], with 0 representing nonmembership and 1 representing full membership of the set (Burrough and McDonnell, 2000). Intermediate values reflect the degree of closeness of an entity to the defined class. Land suitability evaluation using fuzzy logic consists of three steps i. ii. iii.

Generation of membership values for the land characteristics Determination of weights for the membership values Combination of weighed membership values to produce a joint membership value or land suitability index,

class are of practical relevance to the envisaged land utilization type, asymmetric variants of the SI model are used. For instance organic C, CEC and relative humidity in which higher values contributes positively to crop yield, a suitable model is (3) Where is the width of the transition zone (Figure 3b). The transition zone for an asymmetric model refers to the absolute difference between the value of the property at the ideal and crossover points. Where lower values of land characteristic contribute positively to crop yield, a suitable model is

{

D. Membership Values for the Land Characteristics

There are two main techniques of deriving membership functions for fuzzy sets (Burrough 1989). These are the Similarity Relation model (SR) and the Semantic Import Model (SI). In the SR model the value of the membership function is a function of the classifier used (Ogunlade et al., 2012). SI on the other hand uses a priori membership function to assign individual land characteristics into a membership grade. SI is particularly useful in situations where the users have an expert knowledge of how to group land requirements for a specific use. As such, SI model was used in this study. The basic SI model is of the form (2) where is the land characteristic set; is the parameter that determines the shape of the function, (also called the ideal point or standard index) is the value of the property at the centre of the set and is the maximum value that can take. The lower crossover point (LCP) and the upper crossover point (UCP), corresponds to respectively in Figure 3a representing situations where the value of the land characteristics is marginal for a specified purpose. At these points, = 0.5. For example, for land characteristic clay, the %clay should not be less than 15% (LCP) and should not be more than 35% (UCP). Hence equation 2 was used for clay and sand. If only the lower or upper limits of a

(4)

⁄ }

where is the width of the transition zone (Figure 3c). If a range of values are of practical relevance to the envisaged land utilization type, a variant of the SI model is used. For instance for the land characteristic, annual rainfall in which any value from 1600-2000mm is “ ideal ” for oil palm, a suitable model is

where is the width of the transition zone below the lower boundary of the range, the lower boundary of the range, the width of the transition zone above the upper boundary of the range and the upper boundary of the range. For other values of , equation 3 applies for , whereas equation 4 applies for . Summarily, equation 1 is the generalized fuzzy set equation while equation 2 is used where a minimum and maximum value of land characteristics is marginal for crop yield (e.g. clay and sand). Equation 3 is used where higher values of the land characteristics contribute positively to crop yield for instance, organic carbon, CEC and relative humidity. Equation 4 is used where lower values of land characteristics contribute positively to crop yield, for instance months of dry season. Equation 5 is normally used where range values of land characteristics contribute positively to crop yield, for instance a pH range of 5.5-6.5 is ideal for oil palm. Membership functions for land characteristics used in this study were adapted from Sys (1985) and are presented in table 2.

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TABLE 2 LAND CHARACTERISTICS AND MEMBERSHIP FUNCTION PARAMETERS

ranking was based on literature (Sys 1985, Fugger 1999, Adzemi et al, 2013), expert opinion and their importance to oil palm production. To ensure that weights sum up to unity, the rank of land characteristics was converted to weight using equation 6 (6)



The ranking, weights and justification are summarized in table 3 TABLE 3 RANKING, WEIGHTS AND JUSTIFICATION USED IN THIS STUDY

0.9 0.8 0.7

Series1

0.6

Land characteristics

Rank

Climate

4

Weights

Annual rainfall (mm)

0.16

Month of dry season

0.16

Relative humidity (%)

0.16

Soil physical characteristics Clay (%)

3 0.15

0.5 0.4

Sand (%)

0.10

0.3 0.2 0.1 0

Figure 3: Bar chart representing the membership functions of the land characteristics

Fertility

2

CEC (cmol/kg)

0.09

Organic carbon (%)

0.09

pH

0.09

E. Determination of weights for the membership values

Justification

Climate, especially amount of rainfall is very critical to oil palm production as the cropping system is rain fed.

Clay content has a high positive correlation with chemical fertility. Appropriate proportion of soil particles prevents flooding as texture is important for water retention.

CEC determines the nutrient holding capacity of the soil. Soil organic matter is crucial to the supply of N and cations. Nutrient availability in the soil is strongly dependent on pH (Braimoh and Vlek, 2004)

F. Land suitability index (I) The choice of weights is crucial in the determination of the overall land suitability index. Choice of weight should be based on data and knowledge of the relative importance of differentiating land characteristics to crop growth (Davidson, 1994, Adzemi et al., 2013).

The overall land suitability index ( ) at each sampling point is computed using the convex combination rule, which is a linear weighted combination of membership values of each characteristic as illustrated in equation 7

Simple ranking was used to rate land characteristics from 1 (least importance) to 4 (most important). This

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0.0981

0.2979

0.9101

0.5

0.80912

0.9901

0.3229

0.44054

0.5217

∑ Where .

are the weights of the memberships values

III. RESULT AND DISCUSSION

Suitability Index (I) ∑

Statistics of membership values and land suitability index are presented in Table 4. The membership value indicates the degree of suitability at a given location with respect to land and climatic characteristic. For example, membership value of clay (μ clay) is approximately 0.69 thus indicating that suitability of the location is 69% of the ideal requirement of clay for oil palm cultivation. It also implies that averagely the study area has a limitation of 31% with respect to the ideal clay requirement for oil palm cultivation.

The limitation of land and climatic characteristics for oil palm production in the study area is in the order of CEC, annual rainfall, months of dry season, organic carbon, relative humidity, sand, clay, and pH.

Average membership value for CEC is the lowest (0.216), whereas that of pH is the highest (0.809). The suitability index of the study area ranges from 0.32 to 0.52, with a mean of 0.44. Figure 3 is a bar chart illustrating the membership function of the various land characteristics.

Figure 4: Land suitability classes/road network for the study area

Land suitability classification in agreement with FAO framework of land evaluation (FAO, 1976) was used in produce the land suitability map in figure 4. The classification used is as follows:

TABLE 4 DESCRIPTIVE STATISTICS OF MEMBERSHIP VALUES (Μ) AND LAND SUITABILITY INDEX FOR OIL PALM. Land characteristics

Minimum

Mean

Maximum

0.1813

0.22215

0.2747

0.2462

0.2462

0.2462

0.5204

0.5204

0.5204

0.0687

0.68676

1

0.2242

0.602205

0.9204

Climate

Soil physical characteristics

Figure 4 : Land suitability classes/road network for the study area

Fertility 0.1852

0.216265

0.2559

Class S1 (highly suitable): Land units with no or only slight limitations which in combination give land index values ranging from 0.75 to 1.

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Class S2 (moderately suitable): Land units with slight or moderate limitations which in combination give land index values ranging from 0.50 to 0.74. Class S3 (marginally suitable): Land units with moderate limitations or normally not more than two severe limitations which in combination give land index values ranging from 0.25 to 0.49. Order N (not suitable): Total area (sq km) of each of the classes is shown in Table 5. It can be observed from Figure 4 that oil palm cultivation in the study area can be classified into moderately suitable and marginal suitable based on FAO frame work of land classification. TABLE 5 DISTRIBUTION OF SUITABILITY CLASSES (FAO) IN SQ KM. Class

Area (sq km)

% of Total

Highly Suitable

0

0

Moderately Suitable

5.758

4.12

Marginally Suitable

134.095

95.88

Not Suitable

0

0

IV. CONCLUSION The use of fuzzy logic and GIS techniques in this study produced land suitability maps for oil palm cultivation in Ife Central Local Government Area of Osun State. Through the use of fuzzy logic, limitations of land and climatic characteristic to oil palm cultivation in the study area were evaluated. Major constraints to oil palm cultivation in the study area are in the order of CEC, annual rainfall, months of dry season, organic carbon, relative humidity, sand, clay, and pH. It is recommended that soil management techniques that will increase the CEC of the soil and also enhance the water holding capacity of the soil especially during the dry season should be adopted to enhance oil palm yield. Also the organic carbon content of the soil should be improved on. The use of fuzzy logic for land suitability evaluation has proved valuable for identifying major constraints to oil palm cultivation. The production of suitability maps through the use of GIS techniques will further enhance decision making and strategies in overcoming these constraints.

V. REFERENCES [1] Ademola, K., Paul, L., and Alfred, S. 2004. Land evaluation for maize based on fuzzy set and interpolation. Environmental Management 33(2): 226-238. doi: 10.1007/s00267-003-0171-6. [2] Adzemi, M. A. 2014. Comparison Methods of Estimation Potential Evapotranspiration for Oil Palm. Journal of Biology, Agriculture and Healthcare. ISSN 2224-3208 (Paper) ISSN 2225-093X (Online) 4(6), 45-47. [3] Amit, J., and Babita, J. 2012. Fuzzy Modelling and Similarity based Short Term Load Forecasting using Swarm Intelligence-A step towards Smart Grid. J. C. Bansal et al. (eds.), Proceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012), Advances in Intelligent Systems and Computing. doi: 10.1007/978-81-322-1041-2. [4] Braimoh, A. K., and Vlek, P. L. G. 2004. Impacts of land-cover change on soil properties in Northern Ghana, Land degradation and Development, 15: 65–74. doi: 10.1002/ldr.590. [5] Burrough, P. A., and McDonnell R.A. 2000. Principle of Geographical Information Systems. Oxford University Press, New York. [6] Burrough, P.A. 1989. Fuzzy Mathematical Models for Soil Survey and Land Eavaluation. Journal of Soil Science. 40, 477492. doi: 10.1111/j.1365-2389.1989.tb01290.x [7] Fang Q., Bryan C., Yuhong Z., Caiyun Z and Harini S. 2014. Modelling land suitability/capability using fuzzy evaluation. GeoJournal. 79:167–182. doi: 10.1007/s10708-013-9503-0 [8] FAO. 1976. A framework for land evaluation. Soils Bulletin 32. FAO, Rome. p 72. [9] Md. P. A., Sadia W., Raman Bai V., and Ijaz-ul-Mohsin (2008). Development of New Water Quality Model Using Fuzzy Logic System for Malaysia. Open Environmental Sciences, 2, 101106. doi: 10.2174/1876325100802010101 [10] Ogunlade M., Aikpokpodion P and Braimoh A. 2012. Land suitability evaluation for cocoa production in Nigeria using fuzzy methodology, Int. J. Sustain. Crop Prod. 7(3): 13-20. [11] Orewole M. O., Alaigba D.B., and Oviasu O.U. (2015). Riparian Corridors Encroachment and Flood Risk Assessment in Ile-Ife: A GIS Perspective. Open Transactions on Geosciences 2(1): 19-20. doi: 10.15764/GEOS.2015.01002 . [12] Panel, A. P. (2014). Grain, fish, money: financing Africa’s Green and Blue Revolutions. Africa Progress Report 2014. [13] Raman Bai. V., Reinier B and Mohan. S. (2009). Fuzzy logic water quality index and importance of water quality parameters. Air, Soil and Water Research 2009:2, 51–59. [14] Rahaman M. (1976). Review of the basement geology of Southwest Nigeria. Geology of Nigeria, 41–58. [15] Sivanandam, S. N., Sumathi S. and Deepa S. N. (2007) Introduction to Fuzzy Logic using MATLAB. Springer-Verlag Berlin Heidelberg. 2-4. doi: 10.1007/978-3-540-35781-0. [16] Sys C. (1985). Land evaluation. State University of Ghent, Ghent; the Netherlands. [17] Sarmadian, F., Keshavarzi, A., Rooien, A., Zahedi, G. , Javadikia, H. , & Iqbal, M. (2014). Support Vector Machines Based-Modeling of Land Suitability Analysis for Rainfed Agriculture. Journal of Geosciences and Geomatics, 2(4), 165171. doi:10.12691/jgg-2-4-4.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Right to Life with Dignity also includes Right to Die with Dignity : Time To Amend Article 21 of Indian Constitution and Law of Euthenesia Pyali Chatterjee Disha Law College Raipur, Chhattisgarh, India

ABSTRACT Article 21 of Indian Constitution grants Right to life only. According to Article 21 says, “No person shall be deprived of his life or personal liberty except according to procedure establishedby law”. Right life under Article 21 does not include Right to die. Right to life is a natural right. The question regarding Right to die first time comes before Bombay High Court in State of Maharashtra v. Maruty Sripati Dubal, 1987 Cri LJ 743. And here in this case court declared that Right to Life includes Right to die, thus making Section 309 of Indian Penal Code, 1860 which makes attempt to suicide as punishable offence unconstitutional. But Supreme Court in Gian Kaur v. State of Punjab (1996)2 SCC 648, held that Right to life does not include “Right to die” or “Right to be killed”. Right to life is a natural right and right to die is not a natural right and no one has a right to finish their life in unnatural way. It was only after the case of Aruna Ramchandra Shanbaug versus Union of India (2011) 4 SCC 454, Supreme Court in its judgment declared that Passive Euthanasia is legal in India. Here my question is whether Right to life with dignity includes Right to life with dignity. If the answer is Yes then why a cancer patients who were already in their last stage has to suffer lots till their death. In such cases active euthanasia is the only option, getting relief from the pain of cancer. A person who is already bedridden and is dependent on other for each and everything in that case how can we say that he is living with his dignity? In cancer ( last stage), most of the patients died in pathetic conditions, where neither they can bear the pain of the diseases nor their family can watch their loved one in such an intolerable pain for such a long time. In such cases death with dignity is last option for the family members as well as for the patients to finally get relived from the ultimate pain. There is a need of Active Euthanasia for such patients. Lastly, judgment of Aruna Ramchandra Shanbaug versus Union of India should be reviewed once again and medical committee should be formed to find out the cases where active euthanasia will be the ultimate option for the patients to die with dignity and without tolerant any pain. Keywords: Euthanasia, Physician assisted Suicide, Mercy killing, Right to die, Cancer

I. INTRODUCTION The term Euthanasia is derived from Greek roots “eu” means “well or good” and “thanatos” means- “death‟ means good death. “The term Euthanasia normally implies an intentional termination of life by another at the explicit request of the person who wishes to die. Euthanasia is generally defined as the act of killing an incurably ill person out of

concern and compassion for that person's suffering. It is sometimes called mercy killing, but many advocates of euthanasia define mercy killing more precisely as the ending of another person's life without his or her request. Euthanasia, on the other hand, is usually separated into two categories: passive euthanasia and active euthanasia. In many jurisdictions, active euthanasia can be considered murder or Manslaughter, whereas passive euthanasia is accepted by professional medical societies, and by the law under certain circumstances.”

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Dutch Commission on Euthanasia (1985) has defined it as: “A deliberate termination of life on an individuals‟ request, by another, in medical terminology, the active and deliberate termination of life on patients‟ request, by a doctor.” According to the definition given by Merriam Webster for Euthanasia, “the act or practice of killing or permitting the death of hopelessly sick or injured individuals (as persons or domestic animals) in a relatively painless way for reasons of mercy”. Again according to definition given in Oxford Dictionaries, Euthanasia means, “The painless killing of a patient suffering from an incurable and painful disease or in an irreversible coma”. Again according to Black‟s Law Dictionary (8th edition) euthanasia means “the act or practice of killing or bringing about the death of a person who suffers from an incurable disease or condition, esp. a painful one, for reasons of mercy “. So, from the above definition we can interpret that Euthanasia is the practice of killing one person who is sufferings from some kind of serious painful illness, so that he can get relief from his pain on the ground of mercy and sometime even it is known as mercy killing also.

II. METHODS AND MATERIAL A. Constitutional Vality of Right to Die In India Article 21 of Indian Constitution says, “No person shall be deprived of his life or personal liberty except according to procedure established by law”. Right to life under Article 21 does not include Right to die. Right to life is a natural right. Now, the question regarding Right to die first time comes before Bombay High Court in State of Maharashtra v. Maruty Sripati Dubal 1987 Cri LJ 743. And here in this case court declare that Right to Life includes Right to die, thus making Section 309 of Indian Penal Code, 1860 which makes attempt to suicide as punishable offence unconstitutional. But Supreme Court in Gian Kaur v. State of Punjab (1996)2 SCC 648, held that Right to life does not include “Right to die” or “Right to be killed”. Thus, attempt to suicide is punishable offence under section 309 of Indian Penal

Code, 1860 and it is not unconstitutional to Indian Constitution Art. 21. Right to life is a natural right and right to die is not a natural right and no one has a right to finish their life in unnatural way. Even when a petition was filed for Euthanasia, In Aruna Ramchandra Shanbaug versus Union of India (2011)4 SCC 454, Supreme Court in its judgment declared that only Passive Euthanasia is legal in India; means when a person is on ventilation in that case only, patient can be removed from the ventilation. Even in India whether it is a Voluntary Euthanasia, Involuntary Euthanasia or Non- Voluntary Euthanasia whatever the case may be is not acceptable and is illegal here and it is a punishable offence under Indian Penal Code except the passive Euthanasia. B. Right to Life With Dignity Right to life with dignity means, when a person is enjoying his life in a dignified way. Means something which is not only a mere existence and not like the way which animal used to do. Now here lies my question, that whether a person who is bed ridden and dependent on other for his every basic needs e.g. last stage cancer patients in that cases whether he can be said that the person is enjoying his life with dignity. A person, who even can‟t eat with his own hand, can‟t move from his bed, can‟t even stand or walk for washroom, in such cases we can‟t say that the person is living with dignity, even though his family members love him lots and taking proper care also but still no body will like such kind of life. Now when a person has spent most of his life without depending on other and suddenly he has to depend on other for his every basic needs, in that case he loses his self-confident, respect, independency etc which means a person is surviving without his dignity. We also know that Right to life Under Article 21 also includes Right to Privacy. Now when a person is bed ridden and he even can‟t change his own clothes or wear, in that case where is the Right to Privacy? This are certain instances which I feel that is the basic and important thing which every man do in their day today life, and no one would like to depend on other for those basic needs.

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I have seen my own aunt dying with cancer. And during her last months, she was totally bed ridden. For the first time in my life I have seen her wearing grown (nighty or maxi). I have always seen her wearing sari. She was such a lady who used to wake up early in the morning and alone she used to handle her entire house hold work till night. But during her last days, she was totally bed ridden with bed sore. And was totally dependent on other, which makes her cry every day that she is dependent on other for every basic need. Now here is my question again that, whether right to life with dignity includes right to die with pain and suffering? Right to life under Article 21 does not include right to die. But when terminally ill patients like cancer patients knows that he has only few days in his hand to enjoy his life, in that cases whether Right to die with dignity should be allowed? i.e. death with no pain and suffering. So, that he could not suffer the pain and lose his selfconfident and respect. A person who is suffering with some deadly dieses in those cases he must have the right to die with dignity. Depending on other during old age is something different but depending on other due to some deadly diseases which nobody wants in their lifetime. Even that, watching your loved ones dying with pain is also unbearable. Where person become helpless and the time becomes tough for him to watch his loved one dying with pain except one can become the silent spectator or become the witness of the last breath taken by his family member. And it is seen that blood oozes out from nose, mouth, ears and sometimes from private parts of the body in certain cases of cancer patients during their last breath which is the most painful and pathetic time of the life of the patient as well as for the loved one. As we all know that the pain which the cancer patients feel during their last breath is unbearable and that time no medicine works to reduce that pain. So, such time becomes like punishment for the loved one as well for the patient. C. Countries Where Right to Life also Include Right to Die With Dignity Recently, the California Government, Jerry Brown, has signed the California's right-to-die bill into law, allowing terminally ill citizens of the country to end their own lives with the help of their physician. According to this new law a terminally ill

patients can seek medical aid for ending their lives as long as they have been given six months or less to live by two doctors, provided a written request and two oral requests at least 15 days apart and are deemed mentally capable of making decisions about their own health. Montana, Oregon, Vermont and Washington have also legalized the practice, while aid-in-dying is currently in dispute in New Mexico's courts. The California bill was passed due to Brittany Maynard, the 29-year-old resident of San Francisco Bay Area who gained national attention for her decision to move to Oregon to take advantage of the state's longstanding aidin-dying law. Maynard had been diagnosed with terminal brain cancer, but as a California resident, could not pursue end-of-life options at home. It was in the year 2002, when Netherlands became the first country to legalize euthanasia and assisted suicide. But it imposed certain strict condition which one must check before allowing some for Euthanasia as well as for Assisted suicide i.e the patient must be suffering unbearable pain, their illness must be incurable, and the demand must be made in "full consciousness" by the patient Again Belgium becomes the second country in the world to legalize Euthanasia and it passed its law in the year 2002. The law says doctors can help patients to end their lives when they freely express a wish to die because they are suffering intractable and unbearable pain. Patients can also receive euthanasia if they have clearly stated it before entering a coma or similar vegetative state. Even in Switzerland Physician Assisted Suicide is legal.

III. RESULT AND DISCUSSION A. Active and Passive Euthenesia The Honorable Supreme Court of India in, Aruna Ramachandra Shanbaug vs. Union of India had made a clear distinction between Active and Passive Euthanasia. In Active euthanasia something is done to end the life of patient e.g. injecting the patient with a lethal substance e.g. Sodium Pentothal which causes the person to go in deep sleep in a few seconds and the person dies painlessly in sleep, thus it amounts to killing a person by a positive act in order to end suffering of a person in a

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state of terminal illness. It is considered to be a crime all over the world except where permitted by legislation. In India too, active euthanasia is illegal and a crime under Section 302 or 304 of the IPC. Physician assisted suicide is a crime under Section 306 IPC (abetment to suicide). Passive euthanasia in other hand, involves withholding of medical treatment or withholding life support system for continuance of life e.g., withholding of antibiotic where without doing it, the patient is likely to die or removing the heart–lung machine from a patient in coma. Passive euthanasia is legal even without legislation provided certain conditions and safeguards are maintained. The core point of distinction between active and passive euthanasia as noted by Supreme Court is that in active euthanasia, something is done to end the patient‟s life while in passive euthanasia, something is not done that would have preserved the patient‟s life. To quote the words of learned Judge in Aruna‟s case, in passive euthanasia, “the doctors are not actively killing anyone; they are simply not saving him”. The Court graphically said “while we usually applaud someone who saves another person‟s life, we do not normally condemn someone for failing to do so”. The Supreme Court pointed out that according to the proponents of Euthanasia, while we can debate whether active euthanasia should be legal, there cannot be any doubt about passive euthanasia as “you cannot prosecute someone for failing to save a life”. Again Passive euthanasia is further divided into voluntary and non-voluntary. Voluntary euthanasia is where the consent is taken from the patient. And in nonvoluntary euthanasia, the consent is unavailable on account of the condition of the patient for example, when he is in coma. B. Medical Treatment to Terminally ILL Patients (Protection of Patients and Medical Practitioners) Bill 2006 The preamble of the Bil starts with “A Bill to provide for the protection of patients and medical practitioners from liability in the context of withholding or withdrawing medical treatment including life support systems from patients who are terminally-ill” Under section 2 (m) of Medical Treatment to Terminally Ill Patients (Protection of Patients and

Medical Practitioners) Bill 2006,„terminal illness‟ means – (i) such illness, injury or degeneration of physical or mental condition which is causing extreme pain and suffering to the patients and which, according to reasonable medical opinion, will inevitably cause the untimely death of the patient concerned, or (ii) which has caused a persistent and irreversible vegetative condition under which no meaningful existence of life is possible for the patient. If we interpret Sec. 2 (m) (i), then I think some where the cancer patients who were in there last stage where no medicine can save their life, fall under the category of Sec. 2 (m) (i). In that case passive euthanasia should be allowed to them in the form of physician assisted suicide for the sake of their Right to life and die with dignity. This is the right time to introduced Right to die with dignity under Article 21 of Indian constitution in cases of terminally ill cases and also all the diseases which can be or which fall under the category of Sec. 2 (m) (i) should be inserted. Even it is found that more than 1300 people died every day in India due to Cancer and in 2014 near about 5 Lakhs people died due to cancer. And also the treatment of cancer is very much costly which only rich people can afford and not by the poor people. So, in that case we can imagine the situation of the family whose loved one is suffering from cancer and they are unable to provide treatment to them because of its cost. And if it is last stage then nothing can be done except bearing the pain.

IV. CONCLUSION AND SUGGESTION “Marte hain aarzoo mein marne ki Maut aati hai par nahin aati” ---- Mirza Ghalib “I'm not afraid of being dead. I'm just afraid of what you might have to go through to get there.” ----- Pamela Bone (A reputed Journalist) A person who is born in world will also die one day. This is the universal truth, where there is life there is death. Nobody can escape from death. But one thing which every man deserves in his life is Right to life as well as Right to die with dignity. No one should be deprived from this right.

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I think this is the right time when Right to die with dignity should be allowed under Article 21 for terminally ill patients. Even a medical committee should be formed to discuss and decide the diseases which can be fall under”Terminally ill” category. And for those diseases “right to die with dignity” through Physician Assisted Suicide should be allowed. So that, the terminally ill patients can dies without facing any suffering and pain.

[9]

[10]

[11] If we consider Darwin theory of “Survival of the fittest”, then we will find that in today‟s world only the rich people can survive well for their existence. And those who are poor they are born to live with misery. But death is the last stage of life which never see who is poor and who is rich. So, this last stage of life should be free of suffering and pain.

[12]

Lastly, it‟s high time to amend Article 21 of Indian Constitution and to include Right to die with dignity in it. [13]

V. REFERENCES [14] [1]

[2]

[3] [4]

[5]

[6]

[7] [8]

Pyali Chatterjee, “Thalaikoothal: The Practice of Euthanasia in the Name of Custom” European Researcher, 2014, Vol.(87), Is.2, pp. 2005-2012, DOI: 10.13187/er.2014.87.2005 Law Commission of India, “ Passive EuthanasiaA Relook”, Report no 241 http:// lawcommissionofindia.nic.in/reports/report241.pd f Mamta Rao, Constitutional Law, (Abhinandan Malik, 1st ed,2013) K.D.Gaur, Textbook On The Indian Penal Code,532 (Universal Law Publishing Co. Pvt.Ltd,4th.ed., 2009) Euthanasia, THEFREEDICTIONARY, http://legal-dictionary.thefreedictionary.com/ Voluntary+euthanasia Euthanasia, MERRIAMWEBSTER, http://www.merriam-webster.com/dictionary/ euthanasia Caesar Roy, Position Of Euthanasia In India – An Analytical Study, ( Nov. 12, 2014, 11: 50 AM) What is passive euthanasia?, NDTV(March 07, 2011 15:20 IST), http://www.ndtv.com/ article/india/what-is-passive-euthanasia-89964

Euthanasia, OXFORD DICTIONARIES, ( Nov. 10, 2014, 12: 50 PM) http:// www.oxforddictionaries.com/definition/english/eu thanasia Rakesh Dubbudu, “Aruna Shanbaug – The Woman who triggered the Euthanasia Debate in India”, https://factly.in/aruna-shanbaugeuthanasia-case-woman-who-triggered-debate-oneuthanasia-in-india/#prettyPhoto Mollie Reilly, “Right to Die Becomes Law in California”, THE HUFFING TON POST, 6th October, 2015 http://www. huffingtonpost.com/entry/right-to-diecalifornia_560c6037e4b076812700b6d8?section=i ndia Guardian staff,” Euthanasia and assisted suicide laws around the world”, THE GURDIAN, 17th July 2014, 17.04 BST http://www. theguardian.com/society/2014/jul/17/euthanasiaassisted-suicide-laws-world “1,300 Die of Cancer Every Day in India”, NDTV, 17th May 2015, 09:51 IST http://www.ndtv.com/india-news/1-300-die-ofcancer-every-day-in-india-763726

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Challenges Facing Secondary School Managers in Strategic Planning in Kenya Ms Annette Wanyonyi, Judah M. Ndiku, John O. Shiundu Masinde Muliro University of Science and Technology, Kakamega, Kenya

ABSTRACT It is a statutory requirement that public organizations in Kenya, schools included develop strategic plans. This will aid Kenya adjust to the dynamic and competitive world and realize vision 2030. However, it was established that many schools had strategic plans but their operationalization was an issue. The purpose of this study was to investigate the challenges faced by secondary school managers in strategic planning in KakamegaCounty, Kenya. The study adopted a descriptive survey design. Data were collected from a sample of 38 schools. Stratified and purposive sampling techniques were used to select schools and respondents respectively. Total study sample was 190 respondents comprising of principals, teachers and students. Questionnaires were used to collect data. Piloting of the instruments was done to ensure their validity and reliability. Data were analyzed using descriptive statistics. The findings were presented in a histogram and table. Inadequate funds emerged as the main challenge. It was recommended that apart from government funds, schools device other ways of funding strategic management processes. Keywords : Strategic Plan, Strategy, Strategy Formulation, Implementation, Monitoring and Evaluation

I. INTRODUCTION The concept strategy was first used in the military world and later in the 1920s borrowed in the business realm. In searching for the means to achieve improvement in institutions, governments and educators have looked to the quality techniques developed in business and industry to provide suitable tools. This pushed them into applying strategic planning in educational institutions (Thomson and Stickland, 2005). Strategic planning is the art, science and craft of formulating, implementing and evaluating cross-functional decisions that will enable an organization to achieve its objectives (Kalia, 2008). In schools, it is expected that strategic planning will; improve performance in curriculum and cocurriculum, provide consistency of actions, state future thinking habits, act as a tool for resource mobilization, a reference in monitoring and evaluation, enhance transparency and accountability, and encourage commitment and ownership of changes (Pearce and Robinson, 2007). While justifying the importance of

strategic planning, were (2007), argued out that institutions that embrace strategic planning run while those that don’t, walk. Without strategy the organization would be like a ship without a rudder going round in circles. This makes it imperative for schools to embrace strategic planning. Statement of the Problem Strategic planning is a process that is expected to successfully go through the three major phases, namely; strategy formulation, implementation, and evaluation and monitoring (Pitts and Lei, 2003). Strategic planning is an emerging trend in secondary schools in Kenya owing to the recommendations by the Ministry of Education that all schools develop, implement, evaluate and monitor their individual strategic plans (Were, 2007). Therefore schools have to abide by the recommendation. Nevertheless, strategic planning in schools has hardly been analyzed. If the issue of strategic planning is not

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treated with the seriousness it deserves, then despite the significant input of resources into the education sector over years, its performance will still remain disappointing. This in the long run will affect the success of the kind of education that is expected to make Kenya a globally competitive and prosperous nation. There is an urgent need to find out challenges facing school managers in managing strategic plans in secondary schools in Kakamega County, Kenya. The objective To identify the challenges faced by school managers in strategic planning in secondary schools in KakamegaCounty. Conceptual Framework This study was guided by a conceptual framework that represents the interrelationship among variables used. Various factors act in combination to determine either the success or failure of strategic planning which has three stages, namely: formulation, implementation, and evaluation and monitoring. These factors can affect strategic planning at any of the above mentioned stages hindering the completion of strategic management. The independent variable was the school based challenges in strategic management. These challenges independently or interdependently influence the strategic planning process. The dependent variable is strategic management recommendation which has to successfully pass through, formulation, implementation, and evaluation and monitoring. However, possible external challenges that may affect strategic planning in this study reveal themselves as intervening variables. Examples of such variables are external interest, political will, world inflation, and government policies. School based challenges such as inadequate resources, resistance from stakeholders, expensive consultants, high work load for teachers and inadequate knowledge in strategic management were investigated in this study. They affect the strategic planning process.

Figure 1 : A Conceptual Model of the interplay of Strategic Management in Secondary Schools

II. METHODS AND MATERIAL A. Research Methods

The study used descriptive survey design to come up with both qualitative and quantitative data. According to Kombo and Tromp (2006), the design is efficient in collecting large amounts of information. The study was carried out in the larger Kakamega district which was later divide into Kakamega South, North, East and Central. The region experiences a high rate of unemployment and half of its residents live below poverty line of less than one U.S.A dollar a day, accordingly to the United Nations classification of poverty (Provincial Commissioners Office Report, Kakamega, 2005). The study population included: 1452 teachers, 32,095 students, and 127 principals from the 127 schools both public and private (Provincial Education Office, 2008). Stratified sampling was used where schools were first grouped into strata of provincial, district, and private. This was also to establish a built in assurance that the sample accurately reflected the numerical composition of various samples of schools in the district (Cozby, 1977). The number of schools to be used in the study was determined by randomly sampling 30 % of the three categories of schools and therefore a total of 38 target secondary schools were selected as follows: five 5 private schools, 13 provincial schools and 20 district schools. The sample consisted of one principal per school, 2 teachers from the Senior Management Team (SMT), and 2 students from the prefects’ body. All respondents were selected purposively because this technique allows the researcher to use cases that have the required

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information with respect to the objectives (Mugenda and Mugenda, 1999). Hence the study sample comprised 38 school principals, 76 teachers and 76 students. Data were collected through questionnaires administered to school principals, teachers and students. To test the reliability of the research tools, test re-test method was used to calculate the correlation coefficient at 0.05. Data were analyzed quantitatively through the frequencies, means and percentages. The information was presented in the form of a histogram and a table. B. Findings Stages in Strategic Planning Before identifying the challenges faced by school managers in strategic management in secondary schools in Kakamega District, the researcher sought to find out the stages at which various schools were in the strategic management process. This process has three main phases, namely; strategy formulation, implementation and evaluation. Competence with abilities, skills and techniques in strategic management by school principals and other stakeholders will facilitate successful movement of the strategic plan from one stage to another. The results were presented in Figure 2 below.

Figure 2 : Stages in Strategic Management Source: Primary Data Out of the 33 principals in the sample, 14 (42.4%) who are the majority stated that their schools were at the implementation stage, while only 3 (9.1%) of the schools are at evaluation level. The interpretation is that majority of the schools are at the implementation level. This indicates that they have formulated strategic plans and have gone ahead to implement them. The schools at the evaluation stage 3 (9.1), have formulated and

implemented their school strategic plans and are at their final stage of strategic planning. The study revealed that there are some schools that do not have the strategic plans documents. These findings agree with were (2007), who asserted that many schools do not have strategic plans. He attributed this to lack of knowledge in strategic planning. This is controversial because the observation carried out in this district showed that all schools that were sampled had a public display of school motto, values, mission and vision displayed at the school gates and at the notice boards which is expected to reflect the presence of strategic plan documents in schools. It is not clear how these schools came up their school motto, values, mission and vision without formulating the strategic plan document. It is possible that such displays were meant to give a false impression of the presence of strategic plans in such schools and that their motto, values, mission and vision are a true reflection of what goes on in such schools. The Ministry of Education has a responsibility of making a follow up to find out if the recommendations they pass are implemented or not. The schools that were at formulation stage were all district schools. Some of these schools had the document drafted and kept it among other important school documents. These findings attests to Were (2007), who asserted that a strategic plan is of no use if it lays gathering dust on the shelves , as is the case with very many blueprints that have been prepared and released over time. Sagimo (2002), terms such a document as wish full thinking if it cannot be turned into practical activity. In 2005, the Ministry of Education gave directives that schools adopt strategic planning yet not all schools had made initiative to impress the recommendation. The drafting of the document is not enough as it will not bring any change to the school unless it is implemented. Such a school would have wasted time and human resource in coming up with unworkable document. However, most secondary schools that are at the formulation stage have five- year strategic plans with the objectives that need to be achieved within five years. It is imperative that these schools live their plans lest they are rendered outdated. Implementation stage which is a crucial stage in strategic planning process requires detailed management

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attention. In schools this stage requires skills and resources in the form of people, financial, physical and technical. It is possible that most schools are at this level because of some challenges that face school managers. This scenario can be attributed to internal and external factors as outlined in conceptual frame of this study. Such factors as understaffing of teachers, lack of enough funds, resistance from stakeholders, transfer of teachers and school principals, political will, sponsors interests among others, can delay the implementation stage. The same views were shared with Kipng’etich (2007), who in his maiden speech when launching a school’s strategic plan pointed out that the major challenge in any organization is the limitation of resources, a problem that is faced everywhere. It was revealed that most schools at this level were provincial and district schools. Evaluation stage comes after implementing a strategic plan for a specified period of time. There are few schools that are at evaluation level and all of them are provincial schools. This implies that the three schools that are at this stage started strategic planning early enough. It is important that school adopt government policies and works within a specified time to avoid delay. Challenges encountered during Strategic planning School principals, teachers and students were asked to state the challenges that are encountered by school managers in strategic management for their schools. The challenges are as presented in table 1.

Lack of enough teachers came second having been cited by 9.1% principals, 12.1% of teachers and 15.2% of the students. However, it was also noted that inadequate knowledge in strategic planning had a large share of contribution to the factors hindering strategic planning in schools whereby 24.3% of the principals, 24.2% of the teachers and 28.7% of the students agreed to it. The others factors that affected strategic planning in schools were expensive consultants cited by 12.1% of the principals and 7.6% of the teachers, high workload for teachers was identified by 6.1% of the principal and 18.2% of the teachers while resistance to change by many stakeholders was cited by 21.2% of the school principals and 10.6% of the teachers.

Table 1 : Challenges encountered in Strategic Management

There are no funds designated to fund some projects within the schools’ strategic plans and many management boards may be unable to secure funds to that effect. If schools have to develop strategic plans which are authentic they must engage stakeholders and mobilize them in the strategic planning process. The possible explanation to this kind of scenario could be that the Ministry of Education disburses funds to schools in several phases some of which delay to reach schools at the appropriate time, hence interfering with school activities and programs. The funds could also not be enough to meet all the budgeted projects in schools and therefore schools have to devise other methods of funding strategic plans.

Challenges Inadequate funds Inadequate number of teachers Inadequate knowledge Expensive consultants High work load Resistance from stakeholders Total

Principals n % 9 27.2

Teachers n % 18 27.3

Students n % 37 56.1

3

9.1

8

12.1

10

15.2

8

24.3

16

24.2

19

28.7

4

12.1

5

7.6

-

-

2 7

6.1 21.2

12 7

18.2 10.6

-

-

33

100

66

100

66

100

From the findings presented in table 1 above, inadequate funding was cited as the main challenge that constrains strategic planning in secondary schools by 27.2% principals, 27.3% teachers and 56.1% of the students.

Inadequate Funds Implementation of strategic plans in schools largely depends on the availability of funds. Most activities in public schools are funded by the government and the parents. These findings contrast the speech given by the then Minister of Education, Prof. George Saitoti who reported that that the Ministry of Education sends all the money directly to school management committees and the Board of Governors to fund school level activities (Kamotho, 2007). These funds are meant to support the implementation of school programmes especially the tuition activities.

Both private and public schools rely on parents as a source of funding school programmes. Okurut (2001) argues that schools get substantial amounts of funds from parents. However, not all parents in Kenya are able

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to pay school levies with ease owing to poverty and other factors such as diseases. Western Kenya experiences a high rate of unemployment and half of its residents live below poverty line of less than one USA dollar a day, according to the United Nations classification of poverty (Provincial Commissioners Report, Kakamega, 2005). Some parents in this region are poor and therefore they find difficulties in paying school fees in good time. However, some may be stubborn especially after their children have registered for their KCSE because they are sure that even if their children stay away from school, they will definitely sit for their secondary exams. The main concern of such parents is to see their children complete their secondary education other than pass their KCSE exams. Lack of funds is a critical challenge that needs to be addressed because for strategic planning to succeed in schools, there is need for enough funds (Njino, 2008). Inadequate Number of Teachers Teachers form the fundamental resource in every educational institution. They facilitate the teaching and learning processes, and also perform administrative tasks. Teachers have huge professional and societal expectations and their role in strategic management in schools therefore cannot be underestimated. Without adequate teachers in schools, the few present will always be overworked. To fill the gaps of staffing in schools, the Teachers Service Commission has recommended the work load for teachers including school principals to be increased and principals in particular to teach at least 18 lessons per week (Siringi Daily Nation Jan. 25, 2010). The factors contributing to teacher shortage started in the 1990s. According to Chiuri and Kiumi, (2005), the government froze teacher employment due to debt crisis, a factor that has led to candidates’ dismal performance in national examinations. Other factors contributing to teacher shortage are; dismissal from duty, retirement or resignation, access to well-paying jobs, and death without replacement. The challenge of teacher shortage has also been identified by the Ministry of Education as the first and immediate challenge facing the education sector in transforming Kenya to vision 2030 (GOK, 2007). It is therefore imperative that the issue of teacher shortage be

addressed for effective implementation of schools’ strategic plans. Lack of regular teachers has pushed some schools to employ teachers on Board of Governors terms. This comes at a time when most schools are already faced by a problem of inadequate funds. This challenge was cited by both public and private schools. However in the same region, there were some teachers who did not respond to this item and the possible explanation would be that they are ignorant of the concept of strategic planning process in their schools.

III. RESULT AND DISCUSSION Expensive Consultants Some school principals who were unable to develop their school strategic plans hired consultants. This was attributed to lack of enough knowledge in strategic planning by many school stakeholders. In Kakamega district, school principals were inducted on strategic planning for three days and those who missed the training were to be inducted by those who attended. It is possible that some despite the fact that they missed the induction course, they have not bothered to access information on strategic planning and neither have they enrolled in any courses that offer strategic planning. These findings should be an eye opener to the Ministry of Education and the training agencies in identifying the training needs for teachers and schools managers. Though the Ministry of Education conducts in-service training for teachers annually to improve delivery of quality education and management operations in schools (GOK, 2003), the subject of strategic planning has not been adequately addressed. Inadequate knowledge in strategic planning explains why majority of school managers hired consultants to develop their school strategic plans irrespective of the amount of money demanded by the consultants. Use of consultants to draw strategic plans could only be tenable by established schools while small schools would be drained off the meager financial resources they would have used for other projects. It was out of this that many small schools do not have strategic plans to date. However, it is important that school stakeholders develop their own strategic plans to create ownership of the strategic plans and to enable them use them with

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ease at the strategy implementation stage. Ideally in strategic planning; according to Were, (2007), schools should use committees made up of school stakeholders so as to save on the cost of hiring consultants since paying consultants goes beyond the means of most public schools. High Workload for Teachers It was also found out that many schools do not have strategic plans because teachers claimed to be too busy because of being bogged down by heavy work load. The issue of workload is supported by the argument by Marchington and Wilkinson (2003), who report that when there is too much work in an organization, managers and supervisors are asked to take up extra duties. Such duties for teachers in this region could be teaching extra hours, giving exams and assignments and marking, training and accompanying students in cocurriculum activities, attending meetings in schools, among other duties. All these additional duties are aimed at achieving the schools’ missions and visions. These opinions by school principals and teachers can also be attributed to the introduction of the Day Free Secondary Education, which aimed at enhancing access, equity, quality and relevance in secondary schools (GOK, 2008). This policy attracted many students into secondary schools because school fees were reduced. A large students’ body can affect the strategic planning process and other managerial issues in schools in that teachers may not find time to attend to other added responsibilities. Teachers under such strenuous working circumstances get constrained and they may easily suffer burnout or ignore some of added responsibilities such as participating in committees to develop strategic plans (Chiuri and Kiumi, 2005; Ayot and Briggs, 1992).

where there was suffering and acceptance depends on perceived benefits. The behavior to resist change attest to the arguments by (Ivancevich et al., 1997; Nzuve, 1999; Sagimo, 2002; Were, 2007), that stakeholders resist changes due to; lack of finances to effect the transformation, fear of unknown, fear that change will interfere with their lifestyles, fear of inadequate pay and failures due to need for new skills, dislike of surprise, and also dislike of imposed change or lack of being involved. The possible explanation to the school stakeholders’ resistance to accommodate strategic planning in this region could be the unwillingness to pay additional fees by some stakeholders since strategic management requires finances. Change may not have been embraced by some stakeholders because it interferes with their lifestyles and work since some, like teachers would spend most of their time in school working, learning new ideas and implementing them. Other stakeholders also resisted embracing strategic management because most of them were not involved in strategic planning process especially in the schools where consultants were used to develop the strategic plans. Strategic plans developed by consultants are preferred by the users because the experts have good understanding of the planning process and they produce timely and professional looking plan. However, its limitations are that it limits the board and staff participation and may lead to limited sense of ownership of the plan details by the main stakeholders and limited Board of Governors leadership. Lack of respect and trust in persons promoting the change process and the fear for accountability among teachers could also have led to resistance to strategic management in schools. Inadequate Knowledge in Strategic Planning

Resistance from some Stakeholders Resistance to change is a common phenomenon in all organizations. Change can be planned for, unplanned for or gradual. Change alters traditions, challenges deeply held ideas, creates fear of the unknown and it can be harmful or inconvenient. Change requires learning new ideas and accommodating them rather taxing the organizational personnel. Despite the general behavior to resist change, it can bring new advantages, relief

Failure to embrace strategic planning may also have been attributed to inadequate knowledge in strategic planning. The explanation to this finding could be that some school principals are not well versed with the concept of strategic planning and management. Although the Ministry of Education asked each school to develop a strategic plan, there was lack of knowledge in strategic management. Were, (2007) argues that strategic planning is a new concept in school management and an

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emerging trend in Kenya today and therefore principals are finding it hard to develop strategic plans because the concept requires great technical knowhow. In Kakamega district, the induction course on strategic planning and management took only 3 days. Some principals attended while others did not. Those who attended were instructed to induct those who were absent. This could possibly explain why many principals used technocrats to develop strategic plans. Those who did not hire consultants do not have strategic plans for their schools to date despite the government’s requirement that all schools should have strategic plans. However, the same region has some school principals who grasped the concept and came up with strategic plans for their schools. Thus, the three days’ workshop had some impact on strategic planning to some of the participants. This discovery agrees with Chiuri and Kiumi, (2005), who asserted that through relevant training the government can improve the competence of educational planners and mangers to enable them carry out their tasks effectively.

strategic planning process. Secondary schools should devise other means of raising additional funds in support of strategic planning. 2) Owing to resistance occasioned by teacher work load, it was recommended that the Ministry of Education revises its stand on teacher employment and provide enough teachers in schools especially the affected ones. 3) There should be capacity building of school stakeholders through training on strategic management. This would help them participate effectively in the strategic planning and implementation processes. 4) The Ministry of Education should make a follow up on the recommendation of strategic planning and ensure individual schools have strategic plan document.

VI. [1]

IV. CONCLUSION From the findings of the study, it was concluded that most schools were at the implementation stage in strategic management while a hand full of them were at evaluation. There were yet others that did not have strategic plan documents. The main challenge to strategic planning in schools was shortage of financial resources. Resistance to change especially among teachers emerged as another challenge to strategic planning. This was tied to lack of knowledge of strategic planning and the complaint that some teachers are usually over worked due to the many lessons they handle weekly. It was also concluded that lack of enough teachers and hiring consultants who turned out to be expensive made many school principals not to embrace strategic planning.

[2] [3]

[4]

[5]

[6]

[7]

V.

RECOMMENDATIONS [8]

From the above conclusions it was recommended that: 1) Considering the importance of resources in strategic planning and implementation project the Ministry of education and school managers should set aside some funds to facilitate the

[9]

REFERENCES

Ayot, H.O. & Briggs, H. (1992).Economics of Education. Nairobi. Educational Research and Publication Chiuri, L.W. &Kiumi J. K. (2005).Planning and Economics of Education. Egerton: Pangolin publishers. Cozby, P. C. (1997).Methods in behavioural Research. (7th Edition) NewYork : McGraw- Hill. Government of Kenya, (2003).Education Sector Strategic Plan (2003-2007). Nairobi: Government Printers. Government of Kenya, (2005a).Kenya Education Sector Support Programme (KESSP).Nairobi: Government Printers. Government of Kenya, (2005b).Sessional paper No. 1 2005 on policy Framework for Education , Training and Research. Nairobi: Government Printers. Government of Kenya, (2007).Kenya Vision 2030: Globally competitive and prosperous Kenya. Nairobi: Government Printers. Government of Kenya, (2008).Yardstick; Soaring to Greater Heights. Nairobi: Government Printers. Ivancevich, J. Lorenzi, P. Skinner, S. &Coresby, P .B. (1997).Management: Quality and competitive. (2nd Edition).New York: McGraw-Hill publishers Kalia, D. (2008). Business Journal Africa. Nairobi: Flagship Ventures Limited.

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[10] Kamotho, K. (2007). Education Policies. Nairobi: Oakland Media Services. [11] Kombo, D. K. & Tromp, D .L .A. (2006). Proposal and Thesis Writing. Nairobi: Pauline’s Publications Africa. [12] Marchington& Wilkinson.(2003). People Management and Development. (2nd Edition).London: Chatered Institute of Personnel and Development Publishers. [13] Mugenda, M. O. & Mugenda, G. A. (1998). Research methods: Quantitative and Qualitative Approaches. Nairobi: Acts Press. [14] Njino, J. (2008). Resource Management for Sustainable Development in Church. Eldoret: AMECEA Gaba Publishers. [15] Nzuve, N. M. S. (1999). Elements of Organizational Behaviour. Nairobi: University Press. [16] Okurut, H. E. (2001). Economics of education: Foundation of Education. Kampala: Makerereuniversity Publishers. [17] Pearce, J. A. & Robinson, R. B. (2007).Strategic Management (10th Edition). New York: McGraw -Hill Companies. [18] Pitts, A. R. & Lei, D. (2003).Strategic Management: Building and Sustaining Competitiveadvantage. Singapore: Thomson Asia Ltd. [19] Sagimo, P. (2002). Management Dynamics: Towards Efficiency, Effectiveness, and Competence & Productivity. Nairobi: East Africa Education Publishers. [20] Thompson, Gamble, Strickland, (2004). Strategy: Core Concepts, Analytical Tools. New York: McGraw- publishers. [21] Were, E. (2007). All about Preparation and Implementation of a School/College Strategic Plan.Nairobi: Shrend Publishers.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Investigation of the Optical Properties of Liquid Deposition CuSO4 Thin Film Nafie A. Almuslet*1, Yousif H. Alsheikh2 1

Department of laser Systems, Institute of laser, Sudan University of Science & Technology (www.sustech.edu) , almogranKhartoum, Khartoum, Sudan 2 Department of Applied Physics & Mathematics, Omdurman Ahlia University, Omdurman, Khartoum, Sudan

ABSTRACT Liquid Deposition was used to fabricate CuSO4 thin films on glass substrate. The thickness of the thin films was controlled via the interference fringes of diode laser (532 nm) transmitted from the thin films. The interference was used to calculate the thickness of the fabricated film. The transmission spectrum of the film with 266 nm thickness was recorded using different monochromatic light sources by measuring their intensities before and after deposition. The refractive indices and the absorption coefficients were calculated and plotted as functions of wavelengths. Keywords: thin films, interference fringes, liquid phase deposition (LPD), laser assisted deposition, optical properties of CuSO4.

I. INTRODUCTION A material is said to be a thin film when it is build up as a thin layer on a substrate by controlled condensation of the individual atomic, molecular or ionic species either directly by a physical process or through a chemical/electrochemical reaction [1]. Thin solid films are both functional and intrinsically interesting. Their most familiar use is as coatings on the lenses of optical instruments, where they reduce reflections inside the instrument and produce sharper image [2]. The deposition of thin films on a glass substrate can change physical properties of the specimen. Optical properties of a material change or affect the characteristics of light passing through it by modifying its propagation vector or intensity. Two of the most important optical properties are the refractive index and the extinction coefficient, which are generically called optical constants [3]. One important factor that has a principal effect on the characteristics of a work piece is the thickness of the fabricated film. Optical techniques for film-thickness determinations are widely used because they are applicable to both opaque and transparent films and generally yield thickness values of high accuracy [4]. A.V. Valiulis and Silickas P. in 2007,

tried to elucidate the role of the substrate during LPD (Liquid phase deposition) of TiO2 films by using Kapton with different types of surface treatments, SEM analysis showed that the deposited, LPD used for Titania deposition and characterization, given their relatively low acidity and low temperature, LPD methods are ideally suited to polymer substrates [5]. The low-cost and convenience of LPD coatings and their lack of line-of-site limitations strongly recommend their being considered as a general strategy. Moreover, the relatively mild conditions for ceramic film formation using LPD methodology makes them prime candidates for application on polymer substrates. The thickness of the Titania coating was determined by cross-sectional SEM. In interference by thin films as light strikes the surface of a film it is either transmitted or reflected at the upper surface. Light that is transmitted reaches the bottom surface and may once again be transmitted or reflected. The light reflected from the upper and lower surfaces will interfere. In general, the condition for constructive interference in thin films is:

2 t  ( 2n  1)

(maxima)

IJSRST151513 | Received : 10 November 2015 | Accepted: 15 December 2015 | November-December 2015 [(1)5: 132-136]

132

 2

Where  is the refractive index of the film, t represent

(IR 915 nm probe) THE PHOTODETECTOR:

the thickness of the film, n is the interference fringes order and  is the wavelength of the light passing through the film [6]. The general equation for destructive interference in thin films is: 2t  n

A silicon pin photodiode was used in this work for detecting the intensity of light sources.

(minima).

THE DIGITAL OSCILLOSCOPE (CRO):

In our case the path length between the two rays reflected from the upper and bottom surface of the thin film is three times the wavelength of the light source, using this and assuming the index of refraction is unity, from the first interference fringe ( n=1) ( maxima), quater wave (λ/4) of the intensity pattern monitored indicate a thickness of the film equal half of the wavelength of the light source used. In this work we utilize diode Laser (532 nm) to assit the LPD process to fabricate CuSO4 thin films and some of its optical properties were studied.

C.R.O. that was used in this work was manufactured by Tektronix Company [11]. The setup used in this work to fabricate the thin films and measuring its thickness is shown schematically in Fig. (1).

II. METHODS AND MATERIAL MATERIALS: The material used in this work was Cupper (II) Sulphate (pentahydrate). It was dissolved in distilled water.

Figure 1 : Schematic diagram of the experimental setup

EQUIPMENT'S, TOOLS AND SETUP: The light sources used in this work are listed in table (1) below [7], [8], [9] and [10].

 

Table 1: The monochromatic light sources and their wavelengths Light Source Diode Laser Sodium Vapor Lamp He-Ne Laser Diode laser Omega XP Laser (red probe) Omega XP Laser (IR 820 nm probe) Omega XP Laser

Wavelength (nm) 532 589.2 632.8 660 675 820 915







METHOD: The procedure was done according to the following sequences: The experimental setup was arranged as shown in figure (1). The sample holder was inserted in the vacuum chamber which holds the glass substrate at an angle of 45o, and was closed carefully after that. The vacuum pump was turned ON to evacuate the chamber and the pressure was measured inside the chamber after 10 minutes by the vacuum gauge. Diode laser (532 nm) was turned ON and then (Io) was measured and the signal was detected by C.R.O. The sample was deposited slowly from the burrete on the glass substrate, and then the laser intensity was detected by the C.R.O. during deposition until the appearance of the interference fringes, which indicate the desired thickness. The transmitted intensity of laser (I) was measured.

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 Thickness of thin film was calculated from the interference fringes, that equal half multiple of the wavelength of the laser wavelength.  The transmission spectrum of the fabricated thin film for this thickness was recorded using different monochromatic light sources.  The refractive index of the thin films was calculated using the measured reflectivity R and the glass refractive index μ according to: [12], [13].

 ( s 

 s [1  1

R] R

quickly stopped and the fringe was photographed as shown in figure (2-b).

1

)2

(1)

1 1 1 (  1) 2 2 Ts Ts

Figure 2-b : Interference fringe indicates the deposition where Ts represents the transmission of glass substrate. of thin film with thickness =266 nm  The absorption coefficient was deduced from the measured value of reflectivity R, transmittance T, This means that the thickness of the fabricated thin film refractive index μs, and thickness t according to : = 266 nm. [12],[13] Then the transmission intensities of different monochromatic light sources were detected after 1 (1  R) 2 (2)   deposition and the results are tabulated in table (2). t T

III. RESULT AND DISCUSSION First of all the intensity of diode laser 532 nm was monitored by CRO before deposition, the obtained intensity pattern is shown in figure (2-a).

Table 2 : Intensities before and after the deposition of thin films with thickness = 266 nm: Wavelength (nm)

Intensity after deposition I ± 0.001 (V)

532

Intensity before deposition Io± 0.001 (V) 0.295

589.2

0.144

0.138

632.8

0.275

0.268

660

0.347

0.327

675

0.380

0.371

820

0.388

0.371

915

0.420

0.414

0.293

Figure 2-a: The detected signal Diode laser 532 nm l before deposition During deposition when an interference fringes reach maximum intensity, this means that a thin film of thickness equal half of the wavelength of the laser source was fabricated. At this point the deposition was

The data in table (2) above was used to calculate the T% (T = I/I0) of the thin film. The calculated values are plotted in figure (3) as a function of wavelength.

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Transmission Percentage (T%) vs Wavelength Y-axis representTransmission Percentage, 1 unit =0.02 % X-axis represent Wavelengths , 1 unit =50 nm

1.00

Absorption coefficients vs wavelengths for 266 nm thickness of CuSO4 thin film 3

Y-axis represent the absorption coefficients, 1 unit = 1*10 cm X-axis represent wavelengths, 1 unit = 50 nm

-1

60 0.99

58

0.98

56 54

0.97

Abs.coefficient/cm

T%

-1

52

0.96

50 0.95

48 0.94

46 500

550

600

650

700

750

800

850

900

950

44 500

Wavelength/nm

550

600

650

700

750

800

850

900

950

Wavelengths/ nm

Figure 3 : Transmission spectrum of a 266 nm thickness CuSO4 thin film The relation between the calculated refractive indices using equation (1) and the wavelengths is plotted in figure (4) Refractive indices vs Wavelength for CuSO4 of thickness 266 nm Y-axis represents refractiive indices, 1 unit= 0.1 X-axis represents wavelengths, 1 unit= 50 nm

1.7

1.6

1.5 Refractive indices (n) 1.4

1.3

1.2

500

550

600

650

700

750

800

850

900

950

Wavelengths/nm

Figure 4 : The refractive index of CuSO4 thin film (266 nm) versus wavelengths The refractive index of any material in thin film profile is usually deviates from that of the bulk of the same material [14]. This is due to the void fraction typical of the thin film microstructure. The absorption coefficients calculated from equation (2) versus wavelengths using equation (2) is plotted in figure (5) below:

Figure 5 : Absorption coefficients versus wavelengths for the 266 nm thin film CuSO4 Figures (4) and (5) support the idea of using such film as an optical filter or as a reflector in specific wavelengths deduced from the transmission spectrum. The refractive indices and absorption coefficients of the fabricated thin film CuSO4 varies with wavelength, and they exhibit similarity in shape when plotted as functions of wavelengths. Optical measurement constitutes the most important means of determining the band structure of the materials. And the optical constants of thin films provide us with information concerning microscopic characteristics of the material and its determination is very important for using it in any of such devices.

IV. CONCLUSION From the results obtained, the followings can be concluded:  Thin films of CuSO4 of different thicknesses can be obtained by evacuation method.  The thickness of the deposited liquid sample can be controlled and measured via interference fringes of the transmitted laser light.  The CuSO4 can be used to produce optical components in the range from visible to IR regions it can be used to produce an optical filter in (532 nm) and as partial reflector at (660 nm).

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V. REFERENCES [1]

MA Sangamesha et al, EFFECT OF CONCENTRATION ON STRUCTURAL AND OPTICAL PROPERTIES OF CUS THIN FILMS, Journal of Research in Engineering and Technology, eISSN: 2319-1163 pISSN: 23217308 [2] Heaven Macleod A., thin films optical coatingcourse introduction in Optifab Technical Program,: http//SPIE.ORG/X1145.XML?:, 2011 [3] Jai Singh, (ed.) Optical properties of Condensed Matter and Applications, 2006 John Wiley & Sons Ltd. England. [4] Hernández M. et al., Interferometry thickness determination of thin metallic films, Superficies y Vacío (9/ Diciembre), 1999, p. 283-285 [5] A.V. Valiulis and P. Silickas, Liquid phase deposition methods monitoring techniques influence for solid substrates and thin metal oxide film properties, Journal of Achievement in Materials and Manufacturing Engineering, Volume 24 Issue 1, September 2007. [6] Physics –assignment, Interference in Thin films, 2012 http://www.physicsassignment.com/interference-in-thin-films [7] Phillips, lamps and lighting/ Philips sodium spectra lamp 93122 products information, 2015. http//www.lightinggallery.net/gallery/displayimage.php?album=2937 &pos=28&pid=98522 [8] Phywe, Helium Neon Laser Products 8181-93 Info. 2007, https://www.phywe.de/en/geraetehierarchie/physic s/modern-physics/quantum-physics/08181-93 [9] Shagghai Apolo, 1064/532 Q-switched Nd: YAG laser, Model Name HS-220 E datasheet, SN 110628003, Shanghai Apolo Medical Technology Co. Ltd. China. [10] Biotechhealth, Omega XP laser system and product datasheet, 2011 http//www.biotechhealth.co.uk. [11] PHYWE Naturwissenschaft und Technik, Digital Oscilloscope, Product info. Phywe Naturwissenschaft und Technik , 2007 Germany. [12] Elhadi S. Eltayeb ,Utilization of Different Laser Systems to Determine the Optical Properties of Chloroform and Rhodamine 6G Thin-Films in

Nanometer Scale, M.Sc. Thesis in Laser application in Physics; College of Graduate Studies-Sudan University of Science & Technology, 2007. [13] A.M.Mousa and J.P. Ponpon, Growth of Pb Te films by laser induced evaporation of pressed Pb Te pellets, Eur. Phys. J. Appl. Phys.2006 [14] Geunther Karl H., Physical and Chemical Aspects in the Application of Thin Film on Optical Element, Optical Society of America, 1984 [15] PHYWE Naturwissenschaft und Technik, Digital Oscilloscope, Product info., Phywe Naturwissenschaft und Technik , 2007,Germany.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Adsorption mechanism of Cu(II) ion Removal from Aqueous Solution using Acid Activated Madhuca longifolia Stem M. Elamaran1, S. Arivoli2*, N. Ingarsal1 and V Marimuthu3 1

Research Department of Chemistry, Raja Serfoji Govt. College (AU) Thanjavur, TamilNadu, India

2

Research Department of Chemistry, Thiru Vi Ka Govt. Arts College, Thiruvarur, TamilNadu, India

3

Department of Chemistry, Sir Issac Newton Arts and Science College, Nagapattinam, TamilNadu, India

ABSTRACT The series of batch laboratory experiment were carried out by using Acid Activated Madhuca longifolia Stem Carbon for the removal of Cu (II) ions from aqueous solution by the adsorption process. The investigation was carried out by studying the influence of initial pH, contact time, adsorbent dosage and initial concentration of Cu (II). All batch experiment was carried out of constant temperature using wrist – action shaker that operated at 200 rpm. The single component equilibrium data was analyzed by Langmuir and Freundlich isotherms. Maximum adsorption of the Cu (II) ions, i.e. > 90% has been achieved in aqueous solutions using 0.025g of AMLSC at a pH of 6.6. The kinetic process of Copper AMLSC was described by applying pseudo second order rate equation, Elovich model and intra- particles diffusion. The activated AMLSC investigated in this study carries high potential for the removal of Cu (II) ions from aqueous solution. The various thermodynamic parameters like ∆GO, ∆HO, and ∆SO and were analyzed to observe the nature of adsorption. Keywords: Cu (II), AMLSC adsorbent, batch adsorption, adsorption isotherms, kinetics and Thermodynamics.

I. INTRODUCTION Water pollution is due to the mixing of toxic metals and organic compounds excreted from industries in to the water bodies that cause serious environmental and public problems. Hence this has been becoming an alarming concern and priority of the most industrial sectors to avoid such problem. Heavy metal ions are often found in the environment as result of their wide industrial uses. They are common contaminants in waste water and many of them are known to be toxic or carcinogenic1.2. Wastewater quality can be defined by physical, chemical or biological characteristics. Wastewater generally contains toxic inorganic and organic pollutants. Inorganic pollutants consist of mineral acids, inorganic salts, finely divided metal compounds, trace elements, cyanides, nutrients and organ metallic compounds. Some of the trace elements play essential roles in biological processes, but at higher

concentrations, they may be toxic to the biota; they disturb the biochemical processes and cause hazards. These elements include metals (Cd, Cr, Co, Fe, Cu, Zn, Pd, Hg, Ni, and Ag) and metalloids (Se, As, Sb). Most of the trace elements are transition metals with variable oxidation states and coordination numbers. These metals form complexes with organics in the environment thereby increasing their mobility in the biota and manifest toxic effects. Although there are metals that have inherent ability to antagonize the essential functions of other elements, the heavy load of contaminants arising from human activity exceeds the ability of self-purification of aqueous environment. In addition, heavy metals are not biodegradable and tend to accumulate in living organisms, causing various diseases and disorders. Therefore, their presence in the environment, in particular in water, should be controlled3.4. Strict legislation on the discharge of these

IJSRST151417 | Received: 08 October 2015 | Accepted: 14 December 2015 | November-December 2015 [(1)5: 137-145]

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toxic products makes it then necessary to develop various efficient technologies for the removal of pollution from waste water. Biological treatments5.6, membrane process7, advanced oxidation process, chemical and electrochemical techniques and adsorption processes are the most widely used for removing metals and organic compounds from industrial effluents. Amongst all the treatments proposed, adsorption using sorbents is one of the most popular methods since proper design of the adsorption process will produce highquality treated effluents. In fact, adsorption is now recognized as an effective, efficient and economic method for water decontamination application and for separation analytical purposes. The adsorbents may be of mineral, organic, biological origin, activated carbons, zeolites, clays, silica beads, low-cost adsorbents (industrial byproducts, agricultural wastes and biomass) and polymeric materials are significant examples. The present study undertaken to evaluate the efficiency of an adsorbent prepared from Acid Activated Madhuca Longifoliafor removal of Cu(II) ion in aqueous solution. In order to design adsorption treatment systems, knowledge of kinetic and mass transfer processes is essential. In this work, the applicability of kinetic and mass-transfer models for the adsorption of Cu(II) ion onto Acid Activated Madhuca Longifolia was discussed in detailed manner.

II. METHODS AND MATERIAL 2.1. Adsorbent The Madhuca longifolia Stem obtained from nearby Perambalur district the stem was Carbonized with concentrated Sulphuric acid and washed with water and activated around 600°C in a muffle furnace for 5 hrs the it was taken out, ground well to fine powder and stored in a vacuum desiccators.

2.2. Chemicals All chemicals used of high purity commercially available Analar grade. 1000 mg/L of stock solution of Copper (II) (CuSO4 5 H2O) was prepared by calculated quantity weighed of Ammonium Iron (III) sulfate in 1000 ml distilled water. All experimental solutions were prepared by diluting the stock solution to the required concentration. The pH of each experimental solution was adjusted to the required initial pH value using dilute HCl (or) NaOH before mixing the adsorbent. The concentration of residual Cu(II) was determined with atomic absorption spectrophotometer (Perkin Elemer 2380). 2.3. Batch experiments The effect of various parameters on the removal of Cu(II) onto AMLSC was studied batch adsorption experiments were conducted at (30-60°C). For each experimental run, 50 ml of Cu(II) solution of known initial concentration and pH were taken in a 250 ml plugged conical flask. A 25 mg adsorbent dose is added to the solution and mixture was shaken at constant agitation speed (200 rpm) sample were withdrawn at appropriate time intervals (10-60 min) and the adsorbent was separated by filtration. The residual solutions were analyzed to determine the Cu(II) concentration15. The effect of dosage of adsorbent on the removal of Cu(II) was measured by contacting 50 ml of 50 mg/L of Cu(II) solution with 25 mg of AMLSC till equilibrium was attained. Adsorption equilibrium isotherm is studied using 25 mg of AMLSC dosage per 50 ml of Cu(II) solution. The

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initial concentration were ranged from (25 to 125 mg/L) in all sets of experiments. The plugged conical flask was shaken at a speed of 200 rpm for 60 minutes. Then the solution was separated from the mixture and analyzed for Cu(II) concentration. The adsorption capacity was calculated by using a mass equilibrium equation as follows: qe   C0  Ce  V / M  1

concern in water and wastewater treatment. Most of the solid adsorbents possess micro porous fine structure, high adsorption capacity, high surface area and high degree of surface, which consists of pores of different sizes and shapes17. The wide usefulness of AMLSC is a result of their specific surface area, high chemical and mechanical stability. The chemical nature and pore structure usually determines the sorption activity. The physico-chemical properties of the chosen adsorbent are listed in Table 1.

Where C0 and Ce being the initial Cu(II) concentration (mg/L) and equilibrium concentration, respectively V is the experimental volume of Cu(II) solution expressed in liters [L] and M is the adsorbent mass expressed in grams [g]. The Cu(II) ions percentage can be calculated as follows:

C0 –

Ct  x 100 / C0 .  2

The effect of pH on the rate of adsorption was investigated using Cu (II) concentration of 75 mg/L constant AMLSC dosage. The pH values were adjusted with dilute HCl and NaOH solution. The adsorbent adsorbate mixture was shaken at room temperature using agitation speed (200 rpm) for 60 minutes. Then the concentration of Cu (II) in solution was determined. 2.4. Batch kinetic studies The batch kinetic16 experiments were basically identical to these of adsorption equilibrium method. The aqueous samples were taken at present time intervals and the concentration of Cu (II) ions was similarly measured. The all kinetic experiments are carried out at 30, 40, 50 and 60oC at an initial concentration of 25, 50, 75, 100 and 125 mg/L. the amount of adsorption at time t, qt (mg/g) was calculated by.

qt   C0 – Ct  V / W 3

III. RESULT AND DISCUSSION 3.1 Characteristics of the adsorbent Acid Activated Madhuca Longifolia is an effective adsorbent for the abatement of many pollutant compounds (organic, inorganic, and biological) of

85

% Removal of Copper

%R 

Table 1 : Characteristics of the Adsorbent

80 75 70 65 60 55 10

20 30 40 50 Contact Time in Min

60

Fig:1- Effect of Contact Time on the Removal of Cu(II) Ion o [Cu]=50 mg/L;Temprature 30 C;Adsorbent dose=25mg/50ml

3.2 Effect of initial concentration The experimental results of adsorption of Cu(II) ions on AMLSC at various initial concentration (25, 50, 75, 100 and 125 mg/L) for Cu(II) ions in terms of equilibrium data are given in table.2. It reveals that, the actual amount of Cu(II) ions adsorbed per unit mass of AMLSC increased with increase in metal ions concentration shown in Fig.1. It means that the adsorption is highly dependent on initial concentration of metal ion. It is because of at lower concentration, the ratio of initial number of metal ions to the available surface area is subsequently the fractional adsorption

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90 85 80

3.3. Effect of contact time

75

The effect of contact time on the adsorption of Cu(II) ions on the adsorbent surface was shown in Fig.1 reveals that the curves are smooth and continuous leading to saturation, suggesting the possible mono layer coverage of the metal ions on AMLSC surface at about 40 minutes and once again there is not a big change of amount of metal ion adsorbed with time which gives an indication that of ion exchange18. 3.4 Effect of adsorbent dosage The adsorbent dosage is an important parameter, which influence the extent of metal uptake from the solution. The effect of varying doses of 25 to 125 mg of AMLSC was investigated using 50 mg/L of initial Cu(II) concentration at initial pH 6.5 shows an increase in percentage removal of Cu(II) with increase in dose of adsorbent up to a certain limit shown in Fig.2. Increase in the adsorption with increasing dose of adsorbent is expected due to the increase in adsorbent surface area and availability of more adsorption site19.

90

% Removal of Copper

3.5 Effect of pH

% Removal of Copper

become independent of initial concentration. However at high concentration the available sites of adsorption becomes fewer and hence the amount of metal ions adsorbed on the adsorbent surface is less.

70 65 60 55 50 4

5

7

Initial pH

8

9

10

Fig;3- Effect of Initial pH on the removal of Cu(II) Ion o [Cu]=50 mg/L;Temprature 30 C;Adsorbent dose=25mg/50ml

The experiment were carried out of different pH shows that there was a change in the quantity of adsorbed Cu(II) ions on the solid phase of activated AMLSC over the entire pH range of 3 to 10 for Cu(II) shown in Fig.3. The solution pH plays a major role in determining the amount of Cu(II) ions adsorption. The initial metal ion concentrations were kept constant. Adsorption of Cu(II) ions increased appreciably (1-2 times) with increase of pH from 3 to 10 and consistent with results obtained by others. The increase is partly attributed to the formation of different hydroxo species with rise in solution pH. Based on the hydrolysis constants of metal ions as defined in M 2  nH 2O

85

6

M  OH n

2 n

 nH 

80 75 70 65 60 55 0

50

100

150

200

250

Adsorbent dose in mg Fig;2- Effect of Adsorbent dose on the removal of Cu(II) Ion 0 [Cu]=50mg/L;Contact Time 60min;Temprature 30 C

and taking only primary metal species expected to be formed in the working pH range into consideration, the species distribution diagrams for Cu(II) ion is constructed and given in Fig. 3, It is evident that Fe3+ and its monohydroxo species are the predominating species up to pH ~ 9, while dihydroxo species are also formed to a significant extent above pH ~ 7.0 for Cu(II) ion. Since maximum adsorption Cu(II) ion was achieved at pH ~ 6.5, it may safely be stated that the removal of Cu(II) ion was mostly due to adsorption and not precipitation. However, precipitation of small fractions of Fe3+ even at pH ~ 6.5 on the surface by nucleation cannot be neglected. At still higher pH (>7), however, part of Fe3+ may be precipitated as dihydroxo species, which also depend upon the initial metal ion

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concentration. The other important factor, which might contribute to the higher adsorption of metal ion with increased pH, is the pHpzc of AMLSC. At any pH below pHpzc the surface of metal oxides/ oxyhydroxides is positively charged and at pH above pHpzc the surface is negative. When the solution pH exceeded pHzpc, the metal species are more easily attracted by the negatively charged surface of adsorbent, favoring accumulation of metal species on the surface and thus promoting adsorption20. 3.6 Adsorption isotherm 3.6.1 Freundlich isotherm The linear form of Freundlich isotherm20is represented by the equation

log qe  log K f  1/ n log Ce ..  4 Where qe is the amount of Cu(II) ions adsorbed per unit weight of the sorbent (mg/L), Kf is a measure of adsorption capacity and 1/n is the adsorption intensity. The value of Kf and n are calculated from the intercept and slope of the plot of log qe vs log Ce respectively. The constant Kf and ‘n’ values are given in (table-2). In general Kf value increases the adsorption capacity for a given adsorbate increases. The magnitude of the exponent 1/n gives an indication of the favorability of adsorption. The value of n>1 represents favorable adsorption condition21 (or) the value of 1/n are lying in the range of 1 to 10 confirms the favorable condition for adsorption. The adsorption co-efficient Kf of Cu(II) on activated AMLSC was found to be around 5.0 L/g. The Kf values indicates that the saturation time for adsorption of metal ion is attained quickly slue to high affinity of activated AMLSC towards adsorbate, while low Kf values indicates low adsorption rate of metal ion 22, 23. The values of 1/n were around 3.5 (mg/L) for Cu(II) ions. The high values of 1/n signifies that the forces which are exerted on the surface of AMLSC during metal ion adsorption are strong rate from the values K f and 1/n it is reveals that activated AMLSC is more efficient for removal of Cu(II) ions.

3.6.2 Langmuir isotherm The Langmuir isotherm model24 is based on the assumption that maximum adsorption corresponds to a saturated monolayer of solute molecules on the adsorbent surface. The linear form of the Langmuir isotherm equation can be described by

Ce / qe  1/ Qmb  Ce / Qm  .. 5 Where Ce (mg/L) is the equilibrium concentration of the adsorbate, qe (mg/g) is the amount of adsorbate per unit mass of adsorbent, Qm and b are Langmuir constants related to adsorption capacity and rate of adsorption respectively. Qm is the amount of adsorbate at complete monolayer coverage (mg/g) which gives the maximum adsorption capacity of the adsorbent and b (L/mg) is the Langmuir isotherm constant that relates to the energy of adsorption (or rate of adsorption). The linear plot of specific adsorption capacity Ce/qe against the equilibrium concentration (Ce). The Langmuir constant Qm and b were determined from the slope and intercept of the plot and are presented in table 2. In order to find out the feasibility of the isotherm, the essential characteristics of the Langmuir isotherm can be expressed in terms of dimensionless constant separation factor RL25, 26 by the equation

RL  1/ 1  bCo   ..  6 Where Co (mg/L) is the highest initial concentration of adsorbent and b (L/mg) is Langmuir isotherm constant. The parameter RL indicates the nature of shape of the isotherm accordingly. RL > 1 Unfavorable adsorption 0 < RL < 1 Favorable adsorption RL = 0 Irreversible adsorption RL = 1 Linear adsorption The RL values between 0 to 1 indicate favorable adsorption for all initial concentration (Co) and temperatures studied. The calculated RL values are given in table 3. The values of b were increased with increasing the dose of adsorbent for AMLSC High b values indicate high adsorption affinity the monolayer

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saturation capacity Qm were around 139 mg/L for AMLSC. 3.7. Thermodynamic treatment of the adsorption process Thermodynamic parameters associated with the adsorption, via standard free energy change (∆G0), standard enthalpy change (∆H0), and standard entropy change (∆S0) were calculated as follows. The free energy of adsorption process considering the adsorption equilibrium constant K0 is given by the equation

G  RT ln K0 .  7  Where G° is the free energy of adsorption (kJ/mol), T is the temperature in Kelvin and R is the universal gas constant(8.314 J mol/K).The adsorption distribution coefficient KO for the sorption reaction was determined from the slope of the plot of ln(qe/Ce) against Ce at different temperature and extrapolating to zero Ce according to the method suggested by Khan and Singh27 The adsorption distribution coefficient may be expressed in terms of enthalpy change (H°) and entropy change (S°) as a function of temperature

ln Ko 

 H

o

/ RT    S o / R  . 8

Where H° is the standard heat change of sorption (kJ/mol) and S° is standard entropy change (kJ/mol). The value of H° and S° can be obtained from the slope and intercept of plot of ln K0 against 1/T. The value of thermodynamic parameter calculated from equation 7 and 8 are shown in table 4. The thermodynamic treatment of the sorption data indicates that G° values were negative at all temperature. The results point out that physisorption is much more favorable for the adsorption of Cu(II) ions. The positive values of H° show the endothermic nature of adsorption and it governs the possibility of physical adsorption23. Because in the case of physical adsorption, while increasing the temperature of the system, the extent of metal ion adsorption increases, this rules out the possibility of chemisorptions 23, 24. The low H° value depicts metal ion is physisorbed onto adsorbent AMLSC.

The negative ∆G° values table 4 were conform the spontaneous nature of adsorption Cu(II) ions onto AMLSC. The lesser values of ∆G° suggest that adsorption is physical adsorption process. The positive value of ∆H° further confirms the endothermic nature of adsorption process. The positive values of ∆S° in table 4, showed increased randomness of the solid solution interface during the adsorption of Cu(II) ion onto acid activated abutilon indicum. 3.8. Adsorption kinetics The study of adsorption dynamics describes the solute up take rate and evidently this rate controls the residence time of adsorbate uptake at the solid-solution interface .The kinetics of Cu(II) ions adsorption on the AMLSC were analyzed using pseudo second-order28 Elovich29, 30 and intra-particle diffusion31 kinetic models. The conformity between experimental data and the model predicted values was expressed by the correlation co- efficient () and the values are close or equal to 1. A relatively high correlation coefficient () value indicates that the pseudo second-order model successfully describes the kinetics of Cu(II) ions adsorption. 3.8.1 The pseudo second- order equation The pseudo second-order adsorption kinetic rate equation is expressed as

dqt / dt  k2  qe  qt  ..  9  2

Where: k2 is the rate constant of pseudo second- order adsorption (g mg/min). For the boundary conditions t = 0 to t= t and qt = 0 to qt = qt the integrated form of Eq. (9) becomes: 1/  qe – qt   1/ qe  K2t . 10 This is the integrated rate law for a pseudo second-order reaction. Equation (10) can be rearranged to obtain Eq. (11),which has a linear form: t / qt  1/ k2 qe 2   (1/ qe  t . 11

If the initial adsorption rate (h) (mg g-1min-1) is :

h  k2qe2 .12

Equation (9) and (10) becomes

t / qt  1/ h  1/ qet .. 13

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The plot of (t/qt) and t of Eq. (13) should give a linear relationship from which qe and k2 can be determined from the slope and intercept of the plot, respectively. The pseudo-second order rate constants K2, the calculated h values, and the correlation coefficients () are summarized in Table (5).At all studied initial Cu(II) concentrations, the straight lines with extremely high correlation co-efficient (>0.99) were obtained. From table 5, the values of the rate constant k decrease with in increasing initial Cu(II) concentration for AMLSC carbon. This is shows that the sorption of Cu(II) ions on AMLSC follows pseudo second order kinetic model32. 3.8.2 The Elovich equation The Elovich model equation is generally expressed as

dqt / dt   exp   qt .. 14 Where; α is the initial adsorption rate (mg g-1 min-1) and β is the desorption constant (g/mg) during any one experiment. To simplify the Elovich equation. Chien and Clayton (1980) assumed t>>t and by applying boundary conditions qt = 0 at t= 0 and qt = qt at t = t Eq.(12) becomes: qt  1/  ln (a )  1/  ln t  15

If Cu(II) ions adsorption fits with the Elovich model, a plot of qt vs. ln(t) should yield a linear relationship with a slope of (1/β)and an intercept of (1/β)ln (αβ). The Elovich model parameters α, β, and correlation coefficient () are summarized in table 5. The experimental data such as the initial adsorption rate () adsorption constant (β) and the correlation co-efficient (γ) calculated from this model indicates that the initial adsorption (α) increases with temperature similar to that of initial adsorption rate (h) in pseudo-second–order kinetics models. This may be due to increase the pore or active site on the AMLSC adsorbent.

qt  kid t (1/2)  C 16 Where kid is the intra-particle diffusion rate constant (mg/g/min) and C is the constant. If the rate limiting step is intra-particle diffusion, then the graph drawn between (qt) (mg/g) verses square root of the contact time (t 1/2) should yield a straight line passing through the origin31. The slope of the will give the value of the intra-particle diffusion coefficient (kid) and correlation coefficient () indicate the fitness of this model. The value of C gives an idea about the thickness of the boundary layer. From these data the intercept value indicate that the line were not passing through origin, there are some other process affect the adsorption. But the correlation coefficient (γ) value is very high, so that the intra-particle diffusion takes place along with other process that may affect the adsorption. The values are given in table 5.

IV. CONCLUSION From the experimental data of adsorption of Cu(II) ions onto AMLSC surface The following points can be concluded. 1. AMLSC could be used as a potential adsorbent for the removal of Cu (II) ions from polluted water. 2. The initial pH’s of aqueous solutions affect the Cu (II) ion removal. On the other hand percent removal .of Cu (II) ion decreased with increasing initial concentration but increased with increasing adsorbent concentration. 3. From the experimental data’s obtained shows that the adsorption of Cu (II) ions on to AMLSC well fit with Freundlich isotherm and Langmuir isotherm. 4. The adsorption of Cu (II) ions on to activated AMLSC shows negative G° values this is indicates sorption process is physisorption. 5. The sorption of Cu (II) ions on AMLSC follows pseudo second order kinetic model and it is controlled by intra-particle diffusion. 6. The removal percentage of Cu (II) ions by the new adsorbent is fairly high.

3.8.3 The intra particle diffusion model The intra-particle diffusion model used here refers to the theory proposed by Weber and Morris31 based on the following equation for the rate constant:

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R. Van der Oost, J. Beyer and P. E. Vermeulen, Environ, Toxical, Pharm, 13, 57 (2003). S. Verbych, M. Bryk and G. Chornokur, Sep. Sci. Technol., 40, 1749 (2005). C. I. Pearce, J. T. Lloyd and J. T. Guthrie, Dyes Pigments, 58, 179 (2003). A. Cassano, R. Molinari, M. Romano and E. Drioli, J. Membr. Sci., 181, 111 (2001). R. Y. Ning, Desalination, 143, 237 (2002). Chockalingam E and Subramanian S, Chemosphere., 62 (2006) 699 – 708. Shukla S R and Pai R.S., Bioresour. Technol., 96 (2005) 1430 – 1438. Munoz R, Alvarez M T, Munoz A, Terraazas E, Guieysse B and Mattiassion B, Chemosphere., 63 (2006) 903 – 911. Badruzzaman M, Westerhoff P and Knappe D R U, Water Res.38 (18) (2004) 4002 – 4012. Bhattacharya K G and Sharma A, J.Hazard. Material.,113 (2004) 97 – 109. G. Sun and W. Shi, Ind. Eng. Chem, Res., 37 1324 (1998) S.Babel and T.A.Kurniawan, J.Hazard Mater., 97, 219 (2003). S.M. Nomanbhay and K.Palanisamy, Electronic J.Biotechnol, 8, 43 (2005). B.H.Hameed, J Hazard Mat., 162, 305-311. (2009) 17R Sudha, K Kalpana, T Rajachandrasekar and S Arivoli E J Chem., 4 (2), 238-254.2007 D I Mall, V C Srivastava, and N K Agarwal, Dyes and pigments, 69, 210-223, 2006,

[19] R Sivaraj, C Namasivayam and Kadirvelu, Waste Manage, 2001, 21, 105. [20] H. Freundlich., Z Phys. Chem., 57, 385 – 470. (1906) [21] Arivoli, S. Kinetic and thermodynamic studies on the adsorption of some metal ions and dyes on to low cost activated carbons, Ph.D., Thesis, Gandhigram Rural University, Gandhigram, (2007). [22] X Y Luo, Z X Su, G Y Zhang and X J Chang, Analyst 1992, 117, 145. [23] R Schmuhl, H M Krieg and K Keizerk, Water SA, 2001, 27, 1-7. [24] I. Langmuir., J. Am.Chem Soc., 579 1361 – 1403. (1918) [25] T.W. Weber R.K Chakravorti., J. Am. Inst. Chem. Eng.20, 228. (1974) [26] G. McKay, H. S. Blair, J. R. Gardner J. Appl. Polym. Sci. 27 3043 – 3057. (1982) [27] A.A. Khan and R.P. Singh, J. Colliod Interf Sci., 24, 33 – 42,(1987). [28] Y.S. Ho. G.McKay, Water Res. 34, 735 – 742. (2000) [29] S.H. Chien. W.R. Clayton., J Am. Soc Soil Sci.. 44, 265 – 268. (1980) [30] D.L. Spark., Kinetics of Reaction in pure and mixed system in soil physical chemistry. CRC. Press, Boca Raton. (1986) [31] W. J. Weber, J.C. Morris., J. Sanit Eng. Div. 90, 79. (1964)

TABLE: 2. EQUILIBRIUM PARAMETERS FOR THE ADSORPTION OF Cu(II) ION ONTO AMLSC

C0 25 50 75 100 125

30 C 2.249 3.749 7.019 9.770 14.00

Ce (Mg / L) 40 C 50 C 1.749 1.499 3.500 3.259 6.450 5.749 9.020 8.607 13.55 13.27

60 C 1.474 2.749 5.400 8.136 12.54

30 C 15.50 32.50 45.96 60.46 72.00

Qe (Mg / g) 40 C 50 C 16.50 17.00 33.00 33.48 47.10 48.50 61.96 62.79 72.90 73.46

60 C 17.05 34.50 49.20 63.73 74.92

30 C 77.51 81.26 76.60 75.58 72.00

Removed (%) 40 C 50 C 82.51 85.01 82.50 83.70 78.50 80.84 77.45 78.48 72.90 73.46

60 C 85.26 86.25 82.00 79.66 74.92

TABLE: 3. LANGMUIR AND FREUNDLICH ISOTHERM PARAMETER FOR THE ADSORPTION OF Cu(II) ION ONTO AMLSC TEMP. (0C) 30 40 50 60

LANGUMUIR PARAMETER Qm b 188.75 0.0461 143.13 0.0792 126.84 0.1076 127.55 0.1176

FRUENDLICH PARAMETER Kf n 9.310 1.2372 11.976 1.3783 13.951 1.4721 14.985 1.4803

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TABLE: 4. DIMENSIONLESS SEPERATION FACTOR (RL) FOR THE ADSORPTION OF Cu(II) ION ONTO AMLSC (Ci) 25 50 75 100 125

TEMPERATURE C 30C 40C 50C 60C 0.464 0.336 0.271 0.254 0.302 0.202 0.157 0.145 0.224 0.144 0.110 0.102 0.178 0.112 0.085 0.078 0.148 0.092 0.069 0.064

TABLE: 5. THERMODYNAMIC PARAMETER FOR THE ADSORPTION FOR THE ADSORPTION OF Cu(II) ION ONTO AMLSC C0 25 50 75 100 125

30 C -3117.3 -3694.9 -2987.6 -2845.5 -2379.5

G 40 C 50 C -4037.3 -4659.4 -4035.2 -4394.3 -3370.2 -3865.6 -3211.0 -3474.8 -2575.7 -2733.7

60 C -4859.6 -5084.4 -4198.2 -3779.7 -3029.1

H

S

14.71 9.957 9.537 6.449 3.982

59.39 44.84 41.33 30.74 20.95

TABLE: 6. THE KINETIC PARAMETERS FOR THE ADSORPTION OF Cu(II) ION ONTO AMLSC C u0

25

50

75

10 0

12 5

Tem p C 30 40 50 60 30 40 50 60 30 40 50 60 30 40 50 60 30 40 50 60

PSEUDO SECOND ORDER qe 15.712 17.812 17.784 17.787 35.883 36.129 36.482 36.976 48.989 50.715 52.742 52.347 64.923 66.417 67.063 68.023 76.944 77.993 78.162 79.910

k2 0.0160 0.0097 0.0165 0.0175 0.0034 0.0038 0.0044 0.0049 0.0037 0.0040 0.0034 0.0050 0.0037 0.0035 0.0037 0.0037 0.0022 0.0021 0.0023 0.0021

 0.9940 0.9953 0.9971 0.9991 0.9984 0.9975 0.9983 0.9997 0.9965 0.9974 0.9963 0.9946 0.9958 0.9919 0.9946 0.9986 0.9975 0.9977 0.9980 0.9974

h 3.947 3.069 5.204 5.551 4.406 4.980 5.792 6.706 8.901 10.41 9.519 13.62 15.50 15.22 16.59 17.08 12.80 12.91 13.94 13.36

ELOVICH MODEL  7.072 8.244 4.028 7.655 4.530 6.718 1.077 2.520 6.177 5.072 2.174 8.905 5.154 5.212 7.149 8.181 4.698 4.677 7.661 5.335

 3.562 4.787 7.172 7.557 2.003 2.097 2.201 2.427 1.997 1.837 1.576 1.856 1.362 1.336 1.369 1.370 1.162 1.145 1.212 1.133

 0.9921 0.9914 0.9931 0.9954 0.9912 0.9961 0.9943 0.9917 0.9981 0.9917 0.9937 0.9928 0.9914 0.9925 0.9916 0.9935 0.9974 0.9941 0.9913 0.9924

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INTRAPARTICLE DIFFUSION Kid C  0.018 0.9924 1.8780 0.141 0.9942 1.6600 0.088 0.9914 1.7693 0.083 0.9923 1.7797 0.176 0.9918 1.5833 0.164 0.9924 1.6144 0.151 0.9917 1.6478 0.132 0.9934 1.6925 0.120 0.9917 1.6583 0.126 0.9920 1.6708 0.144 0.9916 1.6514 0.119 0.9914 1.7070 0.132 0.9911 1.6501 0.132 0.9921 1.6582 0.127 0.9934 1.6746 0.124 0.9921 1.6850 0.133 0.9932 1.6061 0.133 0.9922 1.6112 0.124 0.9981 1.6313 0.131 0.9954 1.6260

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Research and Studies on Vinegar Production-A Review Sunil Jayant Kulkarni Chemical Engineering Department, Datta Meghe College of Engineering, Airoli, Navi Mumbai Maharashtra, India

ABSTRACT Vinegar is the product obtained exclusively through biotechnological processes such as double fermentation, alcoholic and acetic fermentation of liquids or other substances of agricultural origin. There are various types of vinegars obtained from various sources such as wine fruit and berry, cider, alcohol, grain, malt, beer and honey. Vinegar is used as a food additive and also it acts as effective preservative against food spoilage. Various investigators have carried out investigations on vinegar production from various raw materials such as fruits, fruit peels, and many other agricultural feed stocks. The present review summarizes research and studies carried out on vinegar production from various raw materials. Keywords: Fermentation, Yield, Fruit Waste, Treatment, Properties.

I. INTRODUCTION Chemical and biochemical engineering is ever evolving field because of the technological advancements and scope for cost reduction. Obtaining the product by using environmental friendly method is the need of chemical industry. The process can be optimized by studying effect of various parameters on it. Also use of alternative raw material can optimize the process. Investigations on production of ethanol have been reported by using different raw materials [1, 2, 3, 4]. Production of glucose, starch has also been reported[5,6]. Products such as lactic acid, citric acid are also of interest and investigation has been reported on research on them[7,8,9,10,11,12]. Vinegar is one important product mainly in food industry. It is widely used as preservative.Various investigators have carried out research on production of vinegar by using different raw materials and at different operating conditions. The present review summarizes review on research and studies on production of vinegar from various raw materials.

II. REVIEW ON PRODUCTION OF VINEGAR Minh investigated Fermentation of star fruit juice to produce vinegar using the yeast saccharomyces cerevisiae and acetobacter aceti bacteria [13]. He used

Star fruits collected in rural area of Tra Vinh province, Vietnam. He observed that at ethanol concentration of 10%, the acetic acid formation was maximum. At pH value of 3.5 fermentation was optimum. According to his studies, the most common technology used in the vinegar industry is the feed-back method to increase the speed of the acetic acid biological reaction. Vinegar Production from pineapple wastes was carried out by Roda et.al.[14]. Their research was aimed at completely processing pineapple wastes into vinegar which may be then used as dressing, food preservative, and disinfectant. They cut and chopped the fruit waste then divided it into samples of peel and core. Then distilled water was added. For changing sugar yield, they arranged physical treatments in order to disaggregate the fibrous structure followed by enzyme treatments to breakdown cellulose polymers and to hydrolyze sucrose. Also invertage was added. They obtained more than 100 g of reducing sugars per kg of fresh peels and about 330 g of reducing sugars per kg of fresh core.Praveena and Estherlydia carried out studies on phytochemical screening and antioxidant capacities of vinegar made from peel and fruit of pineapple [15]. They produced vinegar from the peel and fruit of pineapple, sugar and starter culture. They assessed the phytochemical properties and antioxidant activity of pineapple peel vs fruit vinegar. They obtained yellow colored vinegar from the pineapple fruit mixture. They observed that the

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antioxidant content of peel vinegar (2077 mg acetate equivalence/100 ml) was higher compared to that of fruit vinegar. They concluded that pineapple peel vinegar can be produced in large scale and marketed for its therapeutic effects.Dabija and Hatnean summarized research concerning the quality of vinegar made from apples, Florina assortment, harvested from Suceava county area[16]. Their study indicated that apple vinegar is obtained through double fermentation.They also found that the quality of vinegar depends on the factors such as the raw material used, the technological process adopted, the technological equipment supplied, acetic bacteria species used etc. An investigation intended at enhancement in the acetic acid production and the antioxidant activities (AOA) of Roselle vinegar using mixed culture fermentation was carried by Kongkiattikajorn[17].He produced the Roselle wine in a batch reactor. He determined total phenolics, total anthocyanins, and antiradical activity (1-1 diphenyl-2picryl hydrazyl radical-scavenging (DPPH) method).He observed that acetification increased the total anthocyanin content, total polyphenols and antioxidant activities. He concluded that fermentation is a better method for obtaining higher antioxidant activity of Roselle products. Decomposed Fruits were used for screening of acetic acid producing microorganisms by Diba et.al.[18]. They collected acetic acid bacteria capable of growing at 30˚C - 37˚C from various decomposed fruits. They isolated 42 microorganisms and checked their growth in YPG medium containing various ethanol concentrations at different time point at 37˚C.They determined acetic acid production rates by titration method. Their analysis indicated that their collection contained huge amount of acetic acid producing bacteria. Krusong and Vichitraka investigated simultaneous pineapple vinegar fermentation interaction between acetic acid bacteria and yeast[19].They observed that there are two biological interactions between yeast and AAB in this simultaneous pineapple vinegar fermentation. Commensalism, occurred during the early stage of fermentation as yeast-M30 provided alcohol to AABWK for further oxidation. During simultaneous pineapple vinegar fermentation (SPVF), it was observed that there was a positive effect of oxygen on yeast- M30’s ability to produce more ethanol. MacKay et.al. Carried out studies on potential of chemicals and pharmaceuticals

obtained from wood feedstocks, including a food additive, with a focus on activities currently taking place in Maine[20].According to them, there is renewed interest in using wood and carbohydrates as a feedstock. Concerns about oil and gas feedstock prices, carbon emissions, and declining levels of non-renewable resources are driving factors for developing interest in chemicals and pharmaceuticals from woody biomass. According to their studies a substantial amount of research remains on the optimal way to produce chemicals and pharmaceuticals. Kumbha et.al. studied biodegradation of the vinegar effluents by mixed culture bacteria isolated from the soil[21].According to their studies, acetic acid in the vinegar plant effluent contaminates the water and soil and erodes if the effluent is released into the soil.They used aerobic biodegradation to remove biodegradable matter. They analyzed samples for vinegar concentration, DO, salinity, electrical conductivity. They concluded that the aerobic biodegradation by using fluidized bed reactor was an appropriate approach to treat vinegar effluents. Byarugaba-Bazirake et.al. used banana peels, which had adequate starch remaining in them, to process the vinegar[22]. They separated the extract from pieces, boiled to gelatinize the starch by muslin-cheese cloth, and fermented by adding wine yeast. Their study indicated that matooke peels can be used as an ideal substrate for production good quality vinegar.Budak et.al studied functional properties of vinegar[23]. They carried out review of research on these fermented products. It indicated numerous reports of health benefits derived by consumption of vinegar components. They discussed vinegar history, production, varieties, acetic acid bacteria, and functional properties of vinegars. According to these studies acetic acid is the dominant flavor compound in vinegar. It also found to have the potent bioactive effects which may benefit human health. The therapeutic properties of vinegar include antibacterial activity, blood pressure reduction, antioxidant activity, reduction in the effects of diabetes, and prevention of cardiovascular disease.

III. CONCLUSION Vinegar is very important food preservative in food industry. The vinegar can be obtained various raw materials such as various fruits and fruit peels. Various agricultural waste materials can also be used as raw

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materials. It was observed during various investigations that enzymatic treatments of pineapple wastes had a significant effect on the saccharification process. Also review indicated that Pineapple peel vinegar had comparatively high total phenol content and antioxidant activity. Apple vinegar was also obtained through classical methods by few investigators. It was also found that that fermentation is a better method for obtaining higher antioxidant activity of Roselle products. It can be concluded that, to produce chemicals and pharmaceuticals in optimal way, still substantial amount of research is needed.

IV.REFERENCES [1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

[9]

Patanjali Varanasi, Priyanka Singh, Manfred Auer, Paul D Adams, Blake A Simmons,and Seema Singh(2013), Survey Of Renewable Chemicals Produced From Lignocellulosic Biomass During Ionic Liquid Pretreatment, Biotechnology for Biofuels, 6, (14), 1-9. Sunil J. Kulkarni, Nilesh L. Shinde, Ajaygiri K. Goswami(2015), A Review on Ethanol Production from Agricultural Waste Raw Material,International Journal of Scientific Research in Science,Engineering and Technology, 1(4),231-233. Ajay Kumar Singh, Sanat Rath, Yashab Kumar, Harison Masih, Jyotsna K. Peter, Jane C. Benjamin, Pradeep Kumar Singh, Dipuraj, Pankaj Singh(2014), Bio-Ethanol Production from Banana peel by Simultaneous Saccharification and Fermentation Process using cocultures Aspergillums Niger and Saccharomyces cerevisiae, Int.J.Curr.Microbiol.App.Sci,3(5), 84-96. Nibedita Sarkar, Sumanta Kumar Ghosh, Satarupa Bannerjee, Kaustav Aikat(2012),Bioethanol Production From Agricultural Wastes: An Overview, Renewable Energy, 37, 19-27. Veena Ramachandran, Nisha Pujari, Tanmay Matey, Sunil Kulkarni(2014), Enzymatic Hydrolysis of Cassava using wheat seedlings, International Journal of Science, Engineering and Technology Research (IJSETR), 3(5), 1216-1219. Veena Ramachandran, Nisha Pujari, Tanmay Matey, Sunil Kulkarni(2013), Enzymatic Hydrolysis for Glucose-A Review, International Journal of Science, Engineering and Technology Research (IJSETR), 12(10), 1937-1942. Abesh Bera, Siddhartha Verma and Suneetha V(2013), Estimation And Economic Analysis Of Citric Acid Extracted From Vegetative Wastes Collected From Vellore, Der Pharmacia Lettre, 5(3), 58-64. Se-Kwon Kim, Pyo-Jam Park, and Hee-Guk Byun, Continuous Production of Citric Acid from Dairy Wastewater Using Immobilized Aspergillus niger ATCC 9142, Biotechnol. Bioprocess Eng., 7, 89-94. Pratik Bezalwar, Ashok V. Gomashe, Harshal M.Sanap and Pranita A. Gulhane(2013), Production and Optimization of Citric Acid by Aspergillus niger using Fruit Pulp Waste, Int.J.Curr. Microbiol. App.Sci., 2(10), 347-352.

[10] Miloud Hadadji and Ahmed Bensoltane(2006), Growth and

[11]

[12]

[13]

[14]

[15]

[16]

[17]

[18]

[19]

[20]

[21]

[22]

[23]

lactic acid production by Bifidobacterium longum and Lactobacillus acidophilus in goat’s milk, African Journal of Biotechnology, 5(6),505-509. Ramesh Chandra Ray, Piyush Sharma and Smita Hasini Panda(2009), Lactic acid production from cassava fibrous residue using Lactobacillus plantarum MTCC 1407, Journal of Environmental Biology, 30(5) ,847-852. Nguyen Phuoc Minh(2014), Investigation Of Lactic Acid Fermentation From Corn By-Product Using L. Casei And L. Plantarum Strain, International Journal Of Multidisciplinary Research And Development, 1(3),92-100. Nguyen Phuoc Minh(2014), Utilization Of Ripen Star Fruit For Vinegar Fermentation, International Journal Of Multidisciplinary Research And Development, 1(4),82-93. Arianna Roda, Dante Marco De Faveri, Roberta Dordoni, Milena Lambri(2014),Vinegar Production From Pineapple Wastes –Preliminary Saccharification Trials, Chemical Engineering Transactions, 37, 607-612 Jasmine Praveena, R. And Estherlydia, D.(2014), Comparative Study Of Phytochemical Screening And Antioxidant Capacities Of Vinegar Made From Peel And Fruit Of Pineapple (Ananas Comosus L.), Int J Pharm Bio Sci 5(4),(B) 394 – 403 Adriana Dabija, Cristian Aurel Hatnean(2014), Study Concerning The Quality Of Apple Vinegar Obtained Through Classical Method, Journal Of Agroalimentary Processes And Technologies, 20(4), 304-310. Jirasak Kongkiattikajorn(2014), Antioxidant Properties Of Roselle Vinegar Production By Mixed Culture Of Acetobacter Aceti And Acetobacter Cerevisiae, Kasetsart J. (Nat. Sci.), 48, 980 – 988. Farzana Diba, Fahmida Alam, Ali Azam Talukder(2015), Screening Of Acetic Acid Producing Microorganisms From Decomposed Fruits For Vinegar Production, Advances In Microbiology, 5, 291-297. Warawut Krusong And Assanee Vichitraka(2010), An Investigation Of Simultaneous Pineapple Vinegar Fermentation Interaction Between Acetic Acid Bacteria And Yeast, As. J. Food Ag-Ind., 3(01), 192-203. Donald G. Mackay Barbara J.W. Cole Raymond C. Fort Amy Mares(2009), Potential Markets For Chemicals And Pharmaceuticals From Woody Biomass In Maine, Forest Research, Forest Research LLC, 20 Godfrey Drive, Orono, Maine 04473, Website: Www.Forestresearchllc.Com Subba Rao Kumbha, V Ramanjaneyulu And AVN Swamy(2014), Aerobic Biodegradation Of Vinegar Containing Waste Water By Mixed Culture Bacteria From Soil In Fluidised Bed Reactor, Int. Journal Of Engineering Research And Applications, 4(9), Version 1, 110-113. G.W Byarugaba-Bazirake, W Byarugaba And M Tumusiime And D.A Kimono(2014), The Technology Of Producing Banana Wine Vinegar From Starch Of Banana Peels, African Journal Of Food Science And Technology,5(1),1-5. Nilg¨Un H. Budak, Elif Aykin, Atif C. Seydim, Annel K. Greene, And Zeynep B. Guzel-Seydim(2014), Functional Properties Of Vinegar, Journal Of Food Science, 79(5), 757765.

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FEM Simulations of Z-axis MEMS Capacitive Energy Harvester using Various Beams Hitesh Kumar Sharma*, Jit Dutta Materials Research Centre, Malaviya National Institute of Technology, Jaipur, Rajasthan, India

ABSTRACT This paper represents the Finite element modeling of Z-axis MEMS capacitive energy harvester and analysis of spring constant of various type of springs, used in MEMS capacitive energy harvesting system and its effect at the resonance frequency. In this paper, FEM simulations of MEMS capacitive energy harvester along with three different types of springs are carried out using COMSOL Multiphysics tool. The theory of spring constant is discussed along with mathematical model. For simulations, three flexure springs (Linear, single serpentine, double serpentine) of width 12µm and thickness 8µm is used. The length of the spring for linear beam and single serpentine beam is used 264 um and for double serpentine beam is 330 µm. The dimension of the capacitive plate is used 2000 µm × 2000 µm with thickness of 8 µm. This plate is used with three different types of springs, 3-D model is meshed and appropriate boundary conditions are applied to calculate the spring constant. Keywords: Spring Constant, COMSOL Multiphysics Tool, MEMS Capacitive Energy Harvester.

I. INTRODUCTION In our daily life, various types of undesired vibrations are present. These vibrations can effectively be converted into the electrical energy by some capacitive means. Of course; the generated power is of very small amount (µw) but still this is very effective in small power applications to drive some devices as Gyroscope, Accelerometer used in the field of Micro-Electro Mechanical System (MEMS) [4]. This paper represents the FEM simulation to calculate Eigen frequency for such type of “self-powered devices” which are necessary to operate at low frequency. One of the important key factors of this type of low frequency devices is spring constant. This spring constant creates a major effect during the calculation of the Resonance frequency.

Figure 1: (a) shows the schematic of MEMS capacitive energy harvester and (b) shows the 1-DOF resonator with spring constant K, Mass M, and a damper D.

II. METHODS AND MATERIAL When a plate is placed parallel to a wall and moves towards the wall, then due to the mechanical movement of the plate, there is a change of capacitance between the plate and the wall and this capacitance is measured by some means and it is used to drive micro power devices as shown in fig. 1. The MEMS capacitive energy harvester is based on the same principal. This schematic shows the single air cavity MEMS capacitive energy harvester.

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The spring used in the MEMS capacitive energy harvester has a significant effect at the Eigen frequency of the structure and can reduce to an appropriate value by proper choice of the springs as desired in MEMS inertial sensor. Spring constant of linear rectangular spring is defined as [1]:

=√

(1)

Where, = natural frequency of the linear rectangular spring Figure 3: Z-axis MEMS capacitive energy harvester with (a) linear beam, (b) single serpentine spring, and (c) double serpentine spring.

Figure 2 : Schematic layout of serpentine flexure snake spring

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TABLE I FREQUENCY OF MEMS CAPACITIVE ENERGY HARVESTER USING DIFFERENT BEAMS

Figure 4: Frequency analysis of various type of beams using FEM (a) linear beam, (b) single serpentine spring, and (c) double serpentine spring used in Z-axis MEMS capacitive energy harvester.

̅

̅

Where, ̅

Material

Linear Spring

Nickel

Eigen Frequency (KHz) 4.97

Single Serpentine Spring

Nickel

3.47

Double Serpentine Spring

Nickel

2.13

TABLE II FREQUENCY AND SPRING CONSTANT OF THE BEAMS Spring

Length (µm)

Frequency (KHz)

Spring Constant (N/m)

Linear

264

92.08

76

(5)

Single Serpentine

264

54.80

26.55

(5)

Double Serpentine

330

21.02

5.17

(4)

̅

(

MEMS capacitive energy harvester using various spring

(6)

)

, E = young modulus of elasticity, I

moment of inertia. III. RESULT AND DISCUSSION SIMULATIONS AND RESULT For Eigen frequency measurement of MEMS capacitive energy harvester, we have taken a plate with a dimension of 2000µm × 2000µm and the resonance frequency is measured with three different types of springs.

Linear and single serpentine springs have the length of 264 µm and double serpentine has 330 µm of length with a width and thickness of 12 µm and 8 µm respectively. 350 300 250 200

Length

150

Frequency

100

Spring constant

50 0 1

2

3

Figure 5: Bar graph of springs. 1 shows linear spring, 2 Single serpentine, and 3 double serpentine flexure spring

A lower resonance frequency can be achieved by using serpentine springs as compared to the linear spring. The

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double serpentine spring has lower value of spring [3] constant which causes the resonance frequency of Z-axis MEMS capacitive energy harvester is reduced as shown in Table (1). These three springs are also analyzed individually to calculate the to evaluate the spring constants as shown in spring constant which values is closer to the analytical values, calculated by equation (2) [4] and (6). Solid mechanics solver in COMSOL multiphysics is used table 2. The FEM simulations of frequency analysis of MEMS capacitive energy harvester with three different springs are shown in fig. (3) [5] and (4) respectively. It is evident from fig.3 that resonance frequency indeed reduced in flexure serpentine spring.

IV. CONCLUSION

[6]

D. V. Bambill, S.J.Escanes, C. A. Rossit (2003), “Forced vibrations of a clamped-free beam with a mass at the free end an external periodic distribution acting on the mass with applications in ships’ structures, Ocean Engineering 30:10651077 Jianxiong Zhu (2015), “Design, Analysis and Dynamic Phenomenon of MEMS Capacitive Power Harvester”, University of MissouriColumbia G. K. Fedder (1994), “Lumped parameter modeling” in Simulation of Microelectromechanical Systems, Department of Electrical Engineering and Computer Sciences, University of California at Berkeley COMSOL Multiphysics Tool

FEM simulations for estimating the effect of various springs used in Z-axis MEMS capacitive energy harvester as well the spring constant is carried using COMSOL multiphysics tool. The theory of spring constant is discussed along with mathematical model. For simulations one capacitive plate of 2000 µm × 2000µm and three different springs are taken. The 3-D model is then meshed and appropriate boundary conditions are applied to calculate the effect of spring constant. The simulations results are also compared with analytical results.

V. ACKNOWLEDGEMENT The authors are thankful to department of Materials Research Centre, Malaviya National Institute of technology for providing facilities and support to carry out this research work.

VI. REFERENCES [1]

[2]

Mounika Reddy, G. V. Sunil Kumar (2013), “Design and Analysis of Microcantilevers with various shapes using COMSOL multiphysics software”, IJETAE volume 3, issue 3 Giuseppe Barillaro, AntonioMolfese, Andrea Nannini and Francesco Pieri (2005), “Analysis, Simulation and relative performances of two kinds of serpentine springs”, J. Micromech. Microeng. 15:736-746

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

An Investigation of Malaria Predictors Using Logistic Regression Model Abubakar Boyi Dalatu1, Mukhtar Garba1, Nwoji Jude Oguejiofor2 1

2

Department of Statistics, Waziri Umaru Federal Polytechnic Birnin Kebbi, Nigeria Department of Computer Science, Waziri Umaru Federal Polytechnic Birnin Kebbi, Nigeria

ABSTRACT Although malaria is a disease which is considered the most deadly killer especially to children less than 5 years mainly of African countries, there exists no statistical model for the analysis of its predictors for the case of Kebbi State. In this work a logistic regression model using maximum likelihood estimation is proposed. The application of the model using Kebbi State malaria data established that there is significant relationship between malaria status and such predictors as fever, temperature greater than or equal to 37.5 degree, headache, convulsions, cold, cough or sweating, etc. While age, sex, backache and vomiting are not good predictors of malaria. Doctors, medical practitioners and researchers will find this model useful in predicting malaria prevalence. Keywords : Logit Function, Logistic regression, Maximum Likelihood Estimation

I. INTRODUCTION Logistic regression or logit regression is a type of probabilistic statistical classification model that is used to predict a binary response from a binary predictor. Logistic regression is used for predicting the outcome of a categorical dependent variable based on one or more predictor variables (features).

We also write z as the linear sum --------------(1.3) Where the x‘s are independent variables of interest, and the ‘s are constant terms representing unknown parameters. We also define the inverse of the logistic function, the logit:

An explanation of logistic regression begins with an explanation of the logistic function, which always takes on values between zero and one i.e. (0 and 1):

------------(1.4) And equivalently:

Hosmer D.W and Lemeshow S. (2000) -----(1.1) viewing t as a linear function of an explanatory variable x (or of a linear combination of explanatory variables), the logistic function can be written as:

----------------(1.2)

---------------(1.5)

Whose log value gives the logit, describes the odds for a malaria patient with independent variables specified by x. Logistic regression uses the Maximum Likelihood Estimation method to estimate the model coefficients. This method yields values of α and β which maximize the probability of obtaining the observed set of data. Conceptually, it works as follows:

This will be interpreted as the probability of the dependent variable equaling a "malarial" rather than a non-malarial.

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First construct a likelihood function which expresses the probability of the observed data as a function of the unknown parameters α and β.

The log-likelihood is

--(1.14) For univariate case, the contribution to the likelihood function for a given value of the predictor X, is

Also using the fact that;

-------------------(1.15)

The joint probability of the data (the likelihood) is given Kleinbaum et al, (1994) --(1.6) by Thus when Y = 1, the contribution is: when Y = 0, the contribution is: Since the sample observations are assumed to be ------------------------------- (1.16) independent, the likelihood function for the data set is just the product of the individual contributions: ----------------------------- (1.17) For estimation, we will work with the log-likelihood ------------------------ (1.7) A more tractable version of this function is obtained by taking the natural logarithm of the likelihood function, called the Log Likelihood function: -------- (1.8) To find the values of the parameters that maximize the above function, we differentiate this function with respect to α and β and set the two resulting expressions to zero. An iterative method is used to solve the equations and the resulting values of α and β are called the maximum likelihood estimates of those parameters. The same approach is used in the multiple predictor case where we would have (p+1) equations corresponding to the p predictors and the constant α. We have that;

----------------------------------------------- (1.9) Also ----------- (1.10) -------------------------------- (1.11)

--------------- (1.18) The maximum likelihood estimate (MLE) of p is the value that maximizes l (equivalent to maximizing L). The first derivative of l with respect to p is

--------------------- (1.19) And is referred to as the score function. To calculate the MLE of p, we set the score function, U (p) equal to 0 and solve for p. In this case, we get an MLE of p that is Agresti, (1996)

-----------------------------(1.20)

II. METHODS AND MATERIAL A. Wald Test The Wald test statistic is a function of the difference in the MLE and the hypothesized value, normalized by an estimate of the standard deviation of the MLE.

Menard, (1995) ---------------------- (1.21)

Therefore ----------------------- (1.12) The likelihood for n observations is then

Kleinbaum et al, (1994) --------------------------------------------------- (1.13)

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B. Likelihood Ratio Tests The likelihood ratio test (LRT) statistic is the ratio of the likelihood at the hypothesized parameter values to the likelihood of the data at the MLE(s). The LRT statistic is given by

temperature-dependent, process-based model of malaria growth transmitted in the UK, based on environmental and demographic data. D. Methodology i. Data Collection

The data used in this study were obtained as secondary ------------ (1.22) data from Kebbi State epidemic control department, a For large n, L with degrees of freedom equal to the regional World Health Organization (WHO) Health Service directorate Kebbi State. number of parameters being estimated. For the binary outcome discussed above, if the hypothesis is

ii. Organization of Data From the data (see appendix A), the following variables were derived that is coded as: Malaria status (1= patient has malaria and 0 = patient has no malaria).

------- (1.23) Any of either backache or vomiting (1 = YES 0 = NO). ------------ (1.24) And the LRT statistic is

Ages (between 1-20years=1, 21-40years=2, 40years and above=3) Sex (1 = male, 0 = female).

Menard, (1995) ------------------------------------------(1.25)

C. Literature Review Riedel et al. (2010) used logistic regression models to develop geographical patterns and predictors of malaria risk in Zambia. Their survey was carried out by the Zambian Ministry of Health and partners with the objective of estimating the coverage of interventions and malaria related burden in children less than five years. De La Cruz et al. (2006) used logistic regression among other tests to identify factors associated with bed net use in Ghana among children less than five years of age and to compare the characteristics of mothers whose children use bed nets (doers) with those whose children do not (non-doers). Lindsay et al. (2010) assessed the future threat from vivax malaria in the United Kingdom using two markedly different modeling approaches. They used logistic-regression model to predict historical malaria incidence between 1917 and 1918 and simple

Fever less than 7days i.e. 2 to 3 days (1 = YES, 0= NO). Temperature ≥ 37.5°C (1 = YES, 0 = NO) Others (any of headache, convulsions, cold, cough or sweating, etc.) (1 = YES, 0 = NO). iii. Descriptive Statistics It was observed that out of five hundred (500) number patients on the data collected about four hundred and sixty six (466) representing 93.2% were malarial patients and about thirty four (34) representing 6.8% were not malarial patients but rather other related diseases. Moreover, out of 500 number of patients on the data collected about two hundred and twenty three (233) representing 46.6% were female and about two hundred and sixty seven (267) representing 53.4% were males. Data also showed that about two hundred and eighty two (282) representing 56.4% were between the age of 1-20 years, one hundred and one (101) representing 20.2% were between the age of 20-40 years, while, one hundred and seven (107) representing 23.4% were between the age of 40 and above. About 37 (7.4%) of

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the patients have no fever while 463 (92.6%) patients have fever. Also out of 500 total number of the data collected, 42 (8.4%) patients have either backache, vomiting or all while 458 (91.6%) doesn’t have either any, Also 54 (10.8%) patients do not have temperature greater than 37.5 degree while 446 (89.2%) patients have temperature greater than 37.5 degree, Also about 276 (55.2%) of the patients experience others, (i.e. either headache, convulsions, cold, cough or sweating, etc.) While 224 (44.8%) of the patients do not experience others (i.e. either headache, convulsions, cold, cough or sweating, etc.).

III. RESULT AND DISCUSSION The following are the output for the analysis of data Table 1.0 : Logistic Regression Predicting Likelihood of Malaria.

shows that these predictors were not important to be included in the model. Hence the predictor’s age, sex and backache and vomiting were not relevant in predicting malaria. A. Interpretation of The ODDS Ratios As in Table 1.0 the strongest predictor of the outcome of malaria patient was fever, recording an odds ratio of 1493.212 (95 % C.I. = 90.687 - 24586.528). This indicated that patients who had been checked and referred as having fever is likely to estimate the success of malaria as to those who were not referred, controlling for all other factors in the model. The odds ratio 45.344 (95% C.I. = 1.436 - 1431.954) for others (either any of headache, convulsions, cold, cough or sweating, etc.) indicating that for every treatment per patient, there were more malaria due to a pain in the head lasting for some time caused by changes in pressure in the blood vessels leading to and from the brain, controlling for other factors in the model. Again, the odds ratio with respect to temperature greater than or equal to 37.5 degree was 20.814 (95% C.I. = 1.687 - 256.749 ) meaning that more of the malaria was estimated by temperature greater than or equal to 37.5 degree compared to temperature less than 37.5 degree, holding other factors constant. B. Findings

It can be noted from Table 1.0 that the predictors such as fever, temperature greater than or equal to 37.5 degree and others (either any of headache, convulsions, cold, cough or sweating, etc.) with the significance values 0.000, 0.018, and 0.030 respectively are each less than α = 0.05. Therefore we reject the null hypothesis (H0) and conclude that there is enough evidence to show that these variables (predictors) are each not equal to zero at 95% confidence interval. This means that these predictors are each important to be included in the final model. Therefore, we can conclude that these predictors are relevant in predicting malaria in Kebbi State. From the same table, it is revealing to note that, the predictor‘s age, sex, backache and vomiting were dropped from the model. Since the p-values 0.947, 0.529 and 0.866 were each greater than α = 0.05, we fail to reject the null hypothesis and conclude that there is sufficient evidence to indicate that each of the predictor’s age, sex, backache and vomiting are each equal to zero. This

This research indicates that there is a linear relationship between malaria and predictors such as fever, temperature greater than or equal to 37.5 degree and others (either any of headache, convulsions, cold, cough or sweating, etc.). The overall logistic model obtained was: Logit (P(y=1)) = -2.617 + 7.309fever + 3.036temperature + 3.814others Again, for test of significance of the coefficients of the predictors, the study found that the predictors; age, sex, backache and vomiting were not good predictors of malaria. However, the covariates; fever, temperature greater than or equal to 37.5 degree and others (either headache, convulsions, cold, cough or sweating, etc.) malaria.

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IV. CONCLUSION The study provides evidence of the predictors which influence malaria among children’s and adults both males and females in Kebbi State metropolis. Based on the data obtained, about 99.6% were correctly predicted in the model when the relevant factors were added to predict malaria. The model indicates that fever contributes more among other factors, in terms of influencing malaria due to pain in the head lasting for some time caused by changes due to pressure in the blood vessels leading to and from the brain, controlling other factors in the model. It was also observed that temperature at the excess of 37.5o were at higher chances of malaria in patient, even after adjusting for fever. Therefore based on the analysis from data collected, we therefore, conclude that predictors which actually influence malaria are fever, temperature greater than or equal to 37.5 degree and others (i.e. either headache, convulsions, cold, cough or sweating, etc.).

[3] Hosmer D.W and Lemeshow S. (2000). Applied Logistic Regression. 2nd ed. New York, USA: John Wiley and Sons. [4] Kleinbaum D. G. and Klein M. (1994). 2nd ed. Logistic Regression: A Self-Learning Text. John Wiley and Sons Publishers, New York. pp 15-26. [5] Lindsay S.W., David G. H., Robert A. H., Shane A. R., and Stephen G. W. (2010). Assessing the future threat from vivax malaria in the United Kingdom using two markedly different modeling approaches. Malaria Journal. Vol. 9, Issue 1. pp 70-79. [6] Menard, S. (1995). Applied Logistic Regression Analysis. Sage Publications. Series: Quantitative Applications in the Social Sciences, pp. 106. [7] Riedel N., Penelope V. J. M. M., Laura G., Elizabeth C. K., Victor M. and Rick W. S. (2010). Geographical patterns and predictors of malaria risk in Zambia: Bayesian geo-statistical modeling of the 2006 Zambia national malaria indicator survey. Malaria Journal. Vol. 9. pp 37.

V. RECOMMENDATIONS Malaria is a very dangerous disease and using mosquito treated nets are the best solution to avoid it especially now that mosquitoes are developing resistance to drugs. Efforts should be made to eliminate favorable habitats where anopheles can produce eggs. Cleaning of our environment can also help in reducing cases of malaria. In the light of the above it is recommended that Doctors and Clinics should adopt the use of models designed by this research to detect prevalence of malaria among people, so that adequate measures for prevention and control of malaria can be taken early enough to avert danger of the full manifestation of the disease.

VI. REFERENCES [1] Agresti, A. (1996). An Introduction to Categorical Data Analysis. John Wiley and Sons, Inc. http://lib.stat.cmu.edu/datasets/agresti [2] De La Cruz N., Benjamin C., Kirk D., Bobbi G., Natasha I., Stephen A., and Robb D. (2006). Who sleeps under bed nets in Ghana; A doer/non-doer analysis of malaria prevention behaviors. Malaria Journal. Vol. 5, issue 1. pp 61-65.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Transformation of Palm Oil over H3PO4 / SiO2 Catalysts

Nídia M. Ribeiro Pastura1,2*, Eduardo L. G. Filho1, Renata B. P. Machado1, Cynthia F. Scofield2, Lucia R. Raddi de Araújo2, Wilma A. Gonzalez1 1

Dep. de Engenharia Química, Instituto Militar de Engenharia / Rio de Janeiro, RJ; Brazil, [email protected]* 2 Dep. Físico-Química ,Universidade do Estado do Rio de Janeiro / Instituto de Química Rio de Janeiro, RJ, Brazil.

ABSTRACT This paper presents the results obtained in the catalytic cracking of palm oil using phosphoric acid in different percentages (12, 24 and 30% w/w) impregnated on silica. The reaction products were analyzed by gas chromatography, infrared spectrometry, nuclear magnetic resonance and as the acid value. The acidic and textural properties of the catalysts were obtained by analyzes of adsorption/desorption of N2 (BET method), temperature programmed desorption of NH3 (NH3 TPD) and total acidity by Hammett indicators. Keywords : Palm Oil, Cracking, Phosphoric Acid, Silica, Biofuel.

I. INTRODUCTION The study of the conversion of vegetable oils through thermal and/or catalytic cracking can be used as a promising possibility to obtain alternative chemicals and liquid fuels, where the selectivity of the reaction products is strongly influenced by the nature of the catalysts. The main constituents of vegetable oils are fatty acid triglycerides which can be decomposed by cracking into a mixture of saturated hydrocarbons, unsaturated aromatic hydrocarbons, ketones, aldehydes and carboxylic acids. The selectivity of these reactions depends on the catalyst being used. In order to generate a mixture of hydrocarbons with carbon chains similar to those of diesel and/or gasoline, the ideal is to select catalysts with properties that favour the reaction of decarboxylation and/or hydrodeoxygenation [1-5]. The objective of this work was to study the cracking reaction of palm oil using phosphoric acid catalysts supported on silica and check its efficiency in biofuel production process. The catalytic system H3PO4/SiO2 had been previously tested by the authors [6] in soybean oil cracking with very promising results. For the present study, two processes were evaluated: thermal cracking

of crude palm oil and catalytic reforming of this product obtained from the thermal cracking. The catalysts were characterized in order to correlate their activities with their textural and acidic properties. The reaction products were evaluated by acidity measurements, gas chromatography, infrared spectroscopy and 13C NMR. In relation to emissions, the absence of sulfur in vegetable oil makes the product derived from it more appropriate than the petroleum derivatives. In addition, the cracking has great applicability in places requiring lower production volume and having lower availability of skilled labor.

II. METHODS AND MATERIAL Preparation of Catalysts H3PO4/SiO2 catalysts were prepared by impregnation of silica with phosphoric acid solution (wet point method). The silica support was dried in an oven at 383K for 12h, cooled in a desiccator to room temperature for the impregnation of phosphoric acid solution. The amounts of H3PO4 loadings were 12, 24 and 30% wt%. After impregnation, the catalyst was dried in an oven at 383K for about 12 hours.

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BET Surface Area and Pore Size Distribution

Gas chromatography analysis

The BET surface area, pore volume and average pore diameter were calculated from N2 adsorption / desorption isotherms at liquid N2 temperature (77K), using a surface area and pore size analyzer ASAP 2000 from Micromeritics. The pore size distribution was obtained from the desorption isotherm, using the BJH model. Before measurements, the samples were degassed at 473K for 16 hours in N2 gas flow to remove physisorbed water.

The products distribution was obtained by gas chromatography using a HP 5890 series II Model equipment, using a fused silica capillary column and H2 as carrier gas. The oven temperature was programmed from 313K to 543K in a total of 60 min of analysis.

Temperature Programmed Desorption of Ammonia (NH3 TPD) This technique was used to investigate the surface acidity characteristics of the supported materials. Analyzes were performed in a multipurpose unit with a thermal conductivity detector and the amount of sample used was approximately 0.2 g. Initially, the samples were pretreated at 623 K, and the He gas flow rate of 30 mL min-1 for 1 hour. The procedure was then the adsorption of ammonia (2.91% NH3/He, 30 ml min-1) at 423K. In sequence, desorption was monitored using a heating rate of 2.5 K min-1 to final temperature of 723K. Total Acidity from Hammett Method The catalyst previously dried was placed in contact with a non-aqueous solvent (heptane) and then a Hammett indicator was added to this prepared suspension. Subsequently, the sample was titrated with n-butylamine until restoration of the basic colour of the indicator. The titrant volume consumption is used to estimate the total acidity of the sample. Catalytic test This process was conducted in two stages, both in a batch reactor. First stage: thermal cracking of crude palm oil at 623K, for 5 hours (aiming to carboxylic acid formation). Second stage: 20g of the product obtained from first stage was subjected to reform reaction in the presence of 5 g of catalyst at 623K during 1 hour (aiming to hydrocarbon formation). The reaction products were analyzed by gas chromatography, acidity index, infrared spectroscopy and 13C NMR.

Acidity index (AI) The obtained product was diluted in cyclohexane and titrated with a 0.1 M KOH in ethanolic solution, using phenolphthalein as the indicator. The acidity index of the sample is calculated by the number of mmols of KOH consumed in the titration. Infrared Spectroscopy The analysis of the reaction products was evaluated qualitatively by Fourier transform infrared (FTIR) using a Perkin Elmer Spectrum One equipment in the wavenumber region of 4000-450 cm-1. Carbon Nuclear Magnetic Resonance 13C NMR Carbon Nuclear Magnetic Resonance 13C NMR spectra were recorded on a Varian 300 MHz instrument and reported in ppm relative to deuterochloroform (77.23 ppm).

III. RESULT AND DISCUSSION A. Specific surface area and total acidity

The textural properties of the solid materials (support and H3PO4/SiO2 catalysts) obtained by the BET method and the total acidity obtained by the Hammett method are given in Table I. TABLE I TEXTURAL PROPERTIES OF THE CATALYSTS Catalyst

SiO2 (support) 12% H3PO4/SiO2 24% H3PO4/SiO2

Sg Vp (m2 g-1) (cm3 g-1)

Dp (Å)

274

0.060

74

Total Acidity (mmol g-1) 0.03

220

0.058

78

1.11

202

0.068

62

2.23

Sg Specific surface area; Vp Pore volume; Dp Pore diameter

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From Table I, it is observed that the impregnation with phosphoric acid caused a reduction in the specific surface area, probably due to the increase of the average pore size (12%) and to a partial pore blockage caused by the incorporation of the acid (24%). Furthermore, the increased content of H3PO4 favoured the total acidity of the solid. B. Temperature Programmed Desorption of

Ammonia (NH3-TPD) NH3-TPD profiles for the different materials prepared are shown in Figure 1. The distribution obtained for all samples exhibits a single maximum desorption peak at around 473-523K, indicating that the acid sites have only weak acid strength. There was a shift, though very small, of the maximum NH3 desorption temperature to higher values and an increase in peak intensity with the introduction of higher levels of phosphoric acid, suggesting that an increment in phosphoric acid concentration increased the acid site density.

The liquid product obtained in the thermal cracking with pure silica had an acidity index of 83.8 mg KOH/g sample, indicating the formation of a large amount of fatty acids. However, impregnating the support with a moderate Brönsted acid caused a decrease by more than 25% in the acid value, due to formation of products other than fatty acids for the samples impregnated with phosphoric acid. These results are summarized in Table II where the AI values represent the medium results obtained from at least two reactions for each catalyst. TABLE II ACIDITY INDEX (AI) OF THE CRUDE OIL, THE RAW MATERIAL (CRACKED OIL) AND THE CATALYTIC CRACKING PRODUCTS. Sample Crude oil Cracked oil SiO2 12% HP/SiO2 24% HP/SiO2 30% HP/SiO2

AI 7.5 37.3 83.8 61.8 69.8 76.9

The infrared spectroscopy allows checking the transformation of the palm oil by detecting the characteristic bands of the functional groups. Vegetable oils are composed of esters of higher fatty acids (triglycerides) that may be in saturated or unsaturated forms. The esters have two characteristic absorption bands from the axial C=O (1750- 1735 cm-1) and C-O (1300-1100 cm-1) deformations.

Figure 1 : Temperature Programmed Desorption of Ammonia (NH3-TPD) profiles for different catalysts.

C. Cracking Process

In order to obtain a raw material with reproducible characteristics, thermal cracking of crude palm oil was accompanied by measuring the variation of the acidity index with time. It was found that after 5 hours at 623K in the cracking batch reactor at reflux, the acidity index remained almost constant at 37.3 mg KOH/g sample. Thus, this product was used as a raw material for all the catalytic tests.

A comparison of the infrared spectra corresponding to crude palm oil and its products after the catalytic cracking is showed in Figure 2. It indicates changes in the oil structure with the disappearance of the ester characteristic bands. On the other hand, a strong band appeared around 1712 cm-1 characteristic of the presence of saturated carboxylic acid. No C=O absorptions stretch were observed at 1725 cm-1 and 1720 cm-1 indicating the absence of aldehyde or ketone. Furthermore, in comparison with the crude palm oil, there was the appearance of a band at around 1450 cm-1, which can be attributed to the presence of the CH2 group. The results of NMR 13C also indicates, by the absence of signals in the 180 ppm region characteristic of the

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carboxyl group, that compounds like aldehydes and ketones were not formed (Figure 3). The 13C NMR spectra also confirms the free fatty acid presence observed by the signal at 24.73 ppm that corresponds to CH2 radical at ß position related to carboxyl group.

(A)

(B) Figure 2: IR spectra: (A) - Crude palm oil; (B) – Product of the catalytic cracking using 12% HP/SiO2 catalyst.

distribution of hydrocarbons obtained by chromatography analysis is presented in Table III.

gas

TABLE III CARBON CHAIN PRODUCT DISTRIBUTION OBTAINED BY GAS CHROMATOGRAPHY (CX INDICATES THE NUMBER OF CARBON ATOMS IN THE MOLECULE). Carbon chain

SiO2

12% HP/SiO2

24% HP/SiO2

30% HP/SiO2

C5-C12 C13-C18 >C18

15.04 47.82 37.12

12.04 33.60 54.36

4.67 36.07 59.28

9.16 41.44 49.37

From Table III, it is observed that pure silica favoured the formation of hydrocarbons in the C13-C18 range. On the other hand, catalysts impregnated with phosphoric acid favoured the formation of products derived from the polymerization reaction in the C18-C24 range. The generation of these high molecular weight compounds, which must have already been produced in the first step of the process, caused partial blocking of the catalyst, impairing thereby the second process step. Taking into account only the product distribution, the compounds in the C18 to C24 range could be used as biolubricants, while the compounds in the C5-C12 and C13-C18 ranges could be used as substitutes for gasoline and diesel oil, respectively. Therefore, the acidity of the catalyst (and/or the specific area) may be used as a criterion to drive the reaction to the desired product.

IV. CONCLUSION A catalyst prepared by impregnating a moderate Brönsted acid over the silica support generated a mixture of hydrocarbons and fatty acids from the catalytic reforming of palm oil. The values of the acidity index for these products exceed those of the thermally cracked oil. Aldehydes or ketones, usual products obtained from vegetable oils degradation reaction, were identified, neither by infrared spectroscopy nor by 13C NMR.

Figure 3: NMR 13C spectrum for 12% HP/SiO2 catalyst

The analysis of the liquid product indicates that it consists of free fatty acid and hydrocarbon mixture. The

The chromatography results showed some variation of the carbon chain product distribution. Silica was more selective in products with carbon chain of C13 to C18, which have a structure similar to diesel. On the other hand, the use of H3PO4/SiO2 catalysts led to products

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with a carbon chain greater than C18 regardless of the concentration of H3PO4 used.

V. REFERENCES [1]

[2]

[3]

[4]

[5]

[6]

S. Gong, A. Shinozaki, M. Shi, E. W. Qian. 2012. Energy & Fuels, 26, 2394−2399. ISSN NO: 0887-0624 DOI:10.1021/ef300047a L. Jęczmionek, K. Porzycka-Semczuk. 2014. Fuel, 131, 1-5. ISSN NO: 0016-2361 DOI: 10.1016/j.fuel.2014.04.055 E. Santillan-Jimenez, T. Morgan, J. Shoup, A. E. Harman-Ware, M. Crocker. 2014. Catalysis Today, 237, 136-144. ISSN NO: 0920-5861 DOI: 10.1016/j.cattod.2013.11.009 A.V. Bridgwater. 2003. Chemical Engineering Journal, 91, 87-102. ISSN NO: 1385-8947 DOI: 10.1016/S1385-8947(02) 00142-0. Y. S. Ooi, R. Zakaria, A. R. Mohamed, S. Bhatia. 2004. Biomass and Bioenergy, 27, 477-484. ISSN NO: 09619534 DOI: 10.1016/j.biombioe.2004.03.003. R. Frety, M. G. C. Rocha, S. T. Brandão, L. A. M. Pontes, J. F. Padilha, L. E. P. Borges, W. A. Gonzalez. 2011. Journal of the Brazilian Chemical Society, 22, 1206-1220. ISSN NO: 0103-5053 DOI: 10.1590/S0103-50532011000700003.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

An Approach to Survival Analysis when Frailty is Evident Jude Nwoji Oguejiofor1, AbubakarBoyi Dalatu2, KabiruYanusa Gorin Dikko2 1

Department of Computer Science, Waziri Umaru Federal Polytechnic Birnin Kebbi, Nigeria 2 Department of Statistics, Waziri Umaru Federal Polytechnic Birnin Kebbi, Nigeria

ABSTRACT The problem with survival estimation using traditional life-table method alone is not only grouping of survival times, but also its insensitivity to existence of frailty in population. In this work, an approach has been proposed for the analysis of time from infection to occurrence of an event vis-à-vis the contributions of frailty along with some covariates. The approach involves the use of nonparametric product limit otherwise known as the Kaplan-Meier (KM) to estimate individual survivals and the use of frailty estimation method to estimate the hazard. In a simulation, the life-table and product limit methods were compared using the standard error estimates and plots of the empirical survivor function. While empirical estimates did not show significant differences, the product limit plot is more informative than the life table plots. The result of hazard estimation shows that event is largely caused by the baseline hazard with significant contribution from frailty and little contribution from age. There is also significant association between individual’s events possibly as a result of frailty. This procedure will find wider application in survival estimation in a population-based setting. Keywords : Survival Estimation, Empirical Survivor Function Plot, Frailty

I. INTRODUCTION Survival data are summarized through the estimate of survival function and hazard function. Several nonparametric methods which do not require any specific assumption about the underlying distribution of survival time have been discussed by several authors during the past six decades or so Ramadurai et al( 2011). Many researchers have written reports about life table. Berkson et al(1950), Gehan, (1969). Petoet al (1976) has published an outstanding review of statistical methods related to clinical trials. The development of the field that have had the most thoughtful impact on clinical trials are the Kaplan-Meier (Product limit) (1958) method for estimating the survival function. A method developed by Mantel (1966) was used to compare two survival patterns in the life table analysis. This method was used by Myers (1969) to analyze the survival experience for male patients with localized cancer of rectum diagnosed in Connecticut from 1935 – 1944 and 1945 – 1954.

2.0 Existing Work 2.1 The Empirical Survivor Function The survivor function S (t ) , is the probability that an individual survives for a time greater than or equal to t. The function can be estimated Number of Individuals with survival times  t Sˆ  t   Number of Individuals in the data set (2.1)

or

Sˆ (t )  1  Fˆ (t ) , where Fˆ (t) is the empirical

cumulative distribution function, that is, the ratio of the total number of individuals alive at time t to the total number of individuals in the study. The estimated

Sˆ (t ) is assumed to be a constant between two adjacent death times, and so a plot of Sˆ (t ) survivor function

against t is a step-function. The function which decreases immediately after each observed survival time.

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2.2

Life-Table estimate of the survivor function

The life-table estimate of the survivor function is obtained by first dividing the period of observation into series of time intervals. Suppose that in the jth interval,

and all preceding intervals, and leads to the KaplanMeier estimate of the survivor function, which is given by k n d  Sˆ *  t     j j   nj  j 1  

'

the probability of death is estimated by dj/ n j , so that the corresponding survival probability is

(n'j  d j ) / n'j . now

consider the probability that an individual survives

For t( k )  t  t( k 1), k  1, 2,...., r , with Sˆ (t )  1 for t  t(1) , and where t(r+1) is taken to be ∞. However, this method

' beyond time tk , k  1, 2,........, m, that is, until sometime alone cannot be used to estimate patients survival

after the start of the kth interval. This will be the product of the probabilities that an individual survives beyond the start of the kth interval and through each of the k – 1 preceding intervals, and so the life-table estimate of the survivor function is given by k

S *(t )   ( j 1

n dj ' j

n

' j

)

t  t  t , k  1, 2,........, m. ' k

' k 1

On the assumption that censoring occur uniformly over the intervals. A graphical estimate of the survivor function will then be a step-function with constant values of the function in each time interval. However, life table method requires grouping of survival times which may lead to loss of information and possible biasness. The method only finds the estimates of the survivor function. It does not address such important aspects as randomness and covariate effects.

alongside the influence of covariates and frailty at a particular event time t. The standard error for the Kaplan-Meier estimate is given by 1





Se Sˆ  t 

2   dj  k  t k   t  t k 1  Sˆ  t    for(2.2) n n  d j  1   j j j    

(2.4) While the standard error (se) of the life table estimate is given by 1

 

Se Sˆ  t 

 k  2 di  S *  t    , Collet (2003)   n n  d j  1   j j j    (2.5)

II. METHODS AND MATERIAL 3.0 Methodology

2.3 Kaplan Meier (product-limit) estimate of the survivor function

3.1 Simulation study

To obtain the Kaplan- Meier estimate, a series of time intervals is constructed, as for the life-table estimate. However, each of these intervals is designed to be such that one death time is contained in the interval, and this death time is taken to occur at the start of the interval. We now make the assumption that the deaths of the individuals in the sample occur independently of one another. Then, the estimated survivor function at any time, t, in the kth constructed time interval from t(k) to t(k+1) , k = 1, 2, …., r, where t(j+1)is defined to be ∞, will be the estimated probability of surviving beyond t(k). This is actually the probability of surviving through the

A situation similar to real population-based is here simulated from which data in appendix B2 is generated; a sample of which is presented below. The covariates used in the simulation are; id, time, status, age, sex, and frail. The id is exponentially distributed with parameter 0.05, time is also exponentially distributed with parameter 0.01, status has a poisson distribution with parameter 0.76, age is exponentially distributed with parameter 0.02, sex has poisson distribution with parameter 1.74, and finally the frail having a gamma distribution with mean fixed to one (1) for identify ability (which is a constraint in frailty estimation, Rotolo et al (2012)) and variance 0.47.

interval from

t( k ) to

t( k )  t  t( k 1), k  1, 2,...., r, with Sˆ (t )  1 for t  t(1)

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The simulation now gives a survival data set from a population with exponentially distributed baseline hazard (due to the distribution of the survival times) and gamma distributed frailty condition.

stated earlier Collet (2003), Rotolo et al (2012) for identifiability. Its variance is then  . The associated Laplace transform is given by

Below is a sample from the 500 generated survival data.

and it is easy to show that, for q  1,

1 

L  s   1   s  , 

s  0,

q 1  q q  L q   s    1 1   s   1  l  L  s  .  l 0 

(3.3) Each observation corresponds to α, the variable id being the patient’s code. The time (in days) from infection of an event or censoring is stored in time, while status is 1 when event has occurred and 0 for censored observations. Two other covariates may contribute: age, the age of the patient in years, and sex, being 1 for males and 2 for females. The variable frail is the frailty value for each individual which is assumed to have a gamma distribution. The hazard of event (presented in frailty model form) will be modeled as a function of the patient’s age and sex. An R package parfm function is used to do the analysis. 3.2.0

Estimation of Frailty

q

able to compute higher order derivatives L

3.2.1

A

likelihood)





q 1 1 q  log  1 L q   s     q   log 1   s    log 1  l    l 0

, Rotolo et al (2012)

(3.4)

For the Gamma distribution, the Kendall’s Tau Hougaar et al (2000), which measures the association between any two event times from the same cluster in the multivariate case, can be computed as



   0,1  2

(3.5)

III. RESULT AND DISCUSSION

Estimates of  ,  ,  are obtained by maximizing the marginal log-likelihood; this can be easily done if one is

Laplace transformed up to

Therefore, in equation (1.5), we have (i.e. the log-

4.1 Plots of the Empirical Survivor Function Using the Product-Unit (K-M) Method

  of the

q  max d1,..., ds 

Gamma Frailty

gamma

frailty

term

is

a

random

variable

z ~ Gam   with probability density function *

f  z 

1

1





 z

1

exp  u /   ,  1  

  0,

(3.1)

where    is the gamma function. It corresponds to a Gamma distribution Gam  ,  with

 fixed to 1 as

Fig. 4.1: KM Plot of Empirical Survivor Function, when sample size n = 50

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Fig. 4.2: KM Plot of Empirical Survivor Function, when sample size n = 100

(in

days)

Fig 4.2a. plot of the survivor function; sample size n=50

(in

Fig. 4.3: KM Plot of Empirical Survivor Function, when sample size n = 285

days)

Fig 4.2b ; plot of the survivor function; Sample size n=500; interval length is 29

(In days)

Fig. 4.4: KM Plot of Empirical Survivor Function, when sample size n = 500 4.2 Plots of the Empirical Survivor Function Using the Life-table Method

(in

days)

Fig 4.2c. plot of the survivor function, sample size n=500 ; interval length is 50

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(in days)

Fig 4.2d. plot of the survivor function, sample size n=500 ; interval length is 100

4.3

Discussion

When the sample size is at n  50, n  100 the empirical survivor function (esf) plot using K-M method displays good fit(fig 4.1, 4.2, 4.3, and 4.4). It shows decreasing step function behavior with survival function value (1) one at zero (0) survival time. As the survival time increases, the survivor function decreases with constant values between two adjacent death times. The plot of the function display similar behavior and pattern even with large samples as in n  500 and n  285 . The plot of the function maintained it defined characteristics i.e. decreasing step function. On the other hand, when sample size is not large such as n=50, the life-table plot displays the decreasing, step function behavior (fig 4.2a ). But when sample size is large as n=500, the life-table plot though displays decreasing behavior, it is less informative about event times, i.e. it does not show the character of being constant between two adjacent event times. Moreover, when sample size is large, if intervals are not long enough, the life-table curve will be less meaningful.

A comparative look at the results of the survivor estimates table 4.1 using the two methods (from results of the simulation) shows that when the number of patients at risk are 437, 405, 206 and 176, the respective life table survival estimates are 0.950, 0.913, 0.642 and 0.583; while that of K – M are 0.932, 0.910, 0.606 and 0.549 respectively. The standard error, which is an essential aid for interpretation of precision, for the said values are; 0.009, 0.013, 0.024 and 0.025 for the life table estimation. While the K–M has 0.012, 0.013, 0.025 and 0.026, which does not show much difference between the survival estimates of the methods and so is the case with the standard error estimates. 4.4 Result of the frailty estimation alongside other covariates Frailty – Gamma Baseline hazard – Exponential Loglikelihood – 1625.279

Table 4.1: Comparison of some survival estimates and their standard error (from the results of the simulation ) The frailty is estimated alongside age and sex. The result (4.4) shows that age could have a significant impact on of life-table vs Kaplan-Meier (product limit) the hazard of total blindness given the frailty while it is not affected by sex. The heterogeneity parameter  i.e. the frailty is estimated at 0.005 leading to a Kendall’s tau equal to 0.002, a value which indicates a very close association between two event times (in this case event between two individuals) in the cluster. The conclusion

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therefore is that event in this study is largely caused by the baseline hazard and frailty. The frailty has a gamma distribution evidently because the generated data is a mixture of exponentially distributed times with Poisson status or censoring indicators. The baseline hazards has exponential distribution due to the fact that the survival times (observations) are generated exponentially.

IV. CONCLUSION

[6]

[7]

[8]

The form of the estimated survivor function and the shape of its plot in life table method is sensitive to the choice of intervals. Though the survival estimates and the standard error estimates obtained using the two methods did not show much differences where the numbers at risk are equal, the empirical survival plot using Kaplan-Meier method is more informative, i.e. it tells more about event times and displays the good feature of being constant between two adjacent event times. Also in the simulated population with exponentially distributed baseline hazard and gamma frailty, the event of interest is found to be largely caused by the baseline hazard with significant contribution of frailty and the covariate age. The covariate sex was not found to have any influence on the occurrence of the event.

[9]

V. REFERENCES

[14]

[1]

[2]

[3]

[4] [5]

Ardino, V., De Angelis, R., Francis, S. and Grande, E. (2007).Methodology for Estimation of Cancer Incidence Survival and Prevalence in Italian Regions. Tumore 93: 337 – 344. Berkson, J. and Gage, R. P. (1952).Survival Curve for Cancer Patients Following Treatment. Journal of The American Statistical Association, 47: 501 – 515. Baili, P., Micheli, A., Angelis, R. D., Weir, H. K., Francis, S., Santaguilic, M., Hakulinen, T., Quaresma, M., Coleman, M. P., and the Concord working group (2008). Life Tables for Worldwide Comparison of Relative Survival for Cancer (Concord Study).Tumori, 94: 658 – 668. Collet D (2003). Modeling Survival Data in Medical Research. Chapman & Hall/CRC Cox DR (1972). “Regression Models and Lifetables” Journal of the Royal Statistical Society Series B (Methodological) 34(2) 187 – 220.

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[17]

Dickman, P. W. (2010). An Introduction and Some Recent Development in Statistical Methods for Population-Based Cancer Survival Analysis. Statistical Methods for Population-Based Cancer Survival Analysis. Milan. Dickman PW, Hakilinen I (2001). Population Based Cancer Survival Analysis. Chapman & Hall. Duchateau L, Janssen P (2008). The Frailty Model. Springer-Verlag Duchateau L, Janssen P, Lindsey P, Legrand C, Nguti R, Sylvester R (2002). “The Shared Frailty Model and the Power of Heterogeneity Tests in Multicenter Trials.” Computational Statistics and Data Analysis, 40(3), 603 – 620. doi:10.1016/S0167-9473(02)00057 – 9. Geham, E. H. (1969). Estimating Survival Functions From the Life Table. Journal of Chronic Diseases, 21: 629 – 694. Hanagal D (2011). Modelling Survival Data using frailty models. Chapman & Hall/CRC Press. Taylor and Francis Group, LCC. Hougaard P (1995). “Frailty Models for Survival Data.” Lifetime Data Analysis,1(3), 255 – 273. doi:10.1007/BF00985760. Hougaard P (2000). Analysis of Multivariate Survival Data. Springer-Verlag. Kaplan, E. L., Meier, P. (1958). Nonparametric Estimation From Incomplete Observations. J Am. Stat. Association.55: 457 – 81. Mantel N (1966). Evaluation of Survival Data and Two New Rank Order Statistics Arising in its Consideration. Cancer Chemotherapy Report, 50, 163 – 170. Peto, R., Pike, M. C., Armitage, P., Breslow, N. E., Cox, D. R., Howard, S. V., Mantel, N., McPherson, K., Peto, J. and Smith, P. G. (1976). Design and Analysis of Randomised Critical Trials Requiring Prolonged Observation of Each Patient. Introduction and Design. British Journal of Cancer. 34: 585 – 612. Ramadurai, M. and Ponnuraja, C. (2011).Nonparametric Estimation of the Survival Probability of Children Affected by TB Meningitis. Journal of Arts and Science and Commerce. 2231 – 4172.

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[18] Ravichandran, K., AlHandam, N., Al Dyab, A. (2006). Asian Pacific Journal of Cancer Prevention. Vol. 6. [19] Rotolo F, Munda M (2012). Parfm; Parametric Frailty Models. R package version 0.66, URL http://CRAN.R-project.org/package=parfm [20] Therneau TM, Grambsch PM (2000). Modeling Survival Data:Extending the Cox Model. Springer-Verlag. [21] Vaupel JW, Manton KG, Stallard E (1979). “The Impact of Heterogeneity in Individual Frailty on the Dynamics of Mortality.” Demography, 16(3), 439 – 454. [22] Wang ST, Klein JP, Moeschberger ML (1995). “Semi-parametric Estimation of Covariate Effects Using the Positive Stable Frailty Model.” Applied stochastic models and data analysis, 11(2), 121 – 133. [23] Wienke A (2010). Frailty Models in Survival Analysis. Chapman & Hall CRC Biostatistics Series. Taylor and Francis. doi: 10.1201/9781420073911.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

A Review of False Smut Disease in Rice Ali

Sattari1,

H-Nohtani2, HO-Nasirpour3, M-Ghadami4, MO-Madahinasab5, K- Moradi6, Mo-Noorozi7 1 Phd. student of Dept. of Agronomy and Plant Breeding, Faculty of Agriculture, Zabol University, Iran 2M.Sc. Dept. of Agronomy and Plant Breeding, Faculty of Agriculture, Zabol University, Iran 3 M.Sc. student Dept. of Agronomy and Plant Breeding, Faculty of Agriculture, Zabol University, Iran 4 Phd. student of Dept. of Agronomy and Plant Physiology, Faculty of Agriculture, Zabol University, Iran 5 Deptartment of Agronomy, Payame Noor University, Iran 6 Phd. student of Dept. of Agronomy and Plant Physiology, Faculty of Agriculture, Zabol University, Iran 7 Tanin Keshtzar Sabz Agricultural Research, Service and Production Cooperative Company, Iran

ABSTRACT False smut disease is caused by Ustilaginoidea virens (Cooke) Takahashi on rice. It has become a serious pathogen in almost all rice-growing areas in the world . The fungus over winters in soil by means of sclerotia and chlamydospores. Sclerotia produce ascospores, which are primary source of infection to rice plants, whereas secondary infection may come from air-borne chlamydospores. a precise assessment method to evaluate the severity of the disease was developed. The ‘yield representative’ (YR) based on ‘mean floret wt.’ and ‘filled grain %’ was simulated for the precise disease severity assessment of rice false smut disease. Different fungicides or bio-control agents against false smut were applied at different times before heading on a susceptible rice variety. three dsRNA segments from the rice false smut fungus Ustilaginoidea virens,the causal agent of a serious disease in rice, with molecular size ranging from 1.3 to 5 Kb, were isolated and named as dsRNA-L, dsRNA-M, and dsRNA-S. To investigate population genetics, it is necessary to find markers that are polymorphic, such as multilocus DNA fingerprinting, random amplified polymorphic DNA (RAPD) or amplified fragment length polymorphism (AFLP). Keywords: False Smut Disease, Ustilaginoidea Virens, Chlamydospores, Precise Assessment

I. INTRODUCTION False smut pathogen, Ustilaginoidea virens (Cooke) Takahashi (teleomorph Villosiclava virensTanaka) on rice was first described by Cooke in 1878 from Tirunelveli, Tamil Nadu in India. Earlier it was regarded as a minor disease, occurring sporadically in certain regions, but now epidemics of the disease are also being reported (Rush et al., 2000; Singh and Pophaly, 2010). It is an important devastating disease causing yield losses from 1.01 to 10.91% (Atia, 2004). Disease incidence of 10-20% and 5-85% respectively has been reported from Punjab and Tamil Nadu on different rice cultivars (Ladhalakshmi et al., 2012). In recent years, its outbreak might be possibly due to high input cultivation, increased use of hybrid varieties, and climate change (Lu et al., 2009). The fungus over winters in soil by

means of sclerotia and chlamydospores. Sclerotia produce ascospores, which are primary source of infection to rice plants, whereas secondary infection may come from air-borne chlamydospores (Ashizawa et al., 2010). Infection results in one or more kernels on mature heads of plants being replaced by globose, yellowishgreen, velvety smut balls. When smut balls burst open, powdery dark green spores are released (Atia, 2004). The rice false smut balls are then formed in the infected rice spikelets (Hu et al., 2014; Tang et al., 2013). The recent widespread cultivation of hybrid rice and heavy application of nitrogenous fertilizer have been considered as being responsible for the increased rice false smut disease (Guo et al., 2012; Zhang et al., 2014). This disease results in yield loss, polluted rice grains, and even more important, generating toxins poisoning to humans and domestic animals (Koiso et al., 1994; Zhou

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et al., 2012). Two kinds of mycotoxins, namely ustiloxins and ustilaginoidins, have been isolated and identified from rice false smut pathogen (Lu et al., 2014; Zhou et al., 2012). To analyze ustiloxins, some methods have been developed,which includes high-performance liquid chromatography (HPLC)and liquid chromatography–mass spectrometry (LC–MS) (Ji, Cao,Xu, Yin, & Shi, 2012; Miyazaki, Matsumoto, Uchihara, &Morimoto, 2009; Shan et al., 2012). Mycoviruses are widespread among a variety of fungi throughout the major fungus taxonomic groups, including Ascomycetes, Basidiomycetes, and Deuteromycetes (Nuss, 2005), Recently, with the increasing discovery of novel mycoviruses, the classification of the mycovirus has been updated (Chiba, 2009; Liu, 2009). The dsRNA segment diversity presented in one fungal host is very common, and the various sizes of the dsRNA segments may be the result of multipartite viral genomes of coinfecting viruses, or the defective products of virus replication and satellite RNA (Herrero, 2012).

II. METHODS AND MATERIAL A. Isolation technique and culture conditions of false smut pathogen In recent years, its outbreak might be possibly due to high input cultivation, increased use of hybrid varieties, and climate change (Lu et al., 2009). The fungus overwinters in soil by means of sclerotia and chlamydospores. Sclerotia produce ascospores, which are primary source of infection to rice plants, whereas econdary infection may come from air-borne chlamydospores (Ashizawa et al., 2010). Infection results in one or more kernels on mature heads of plants being replaced by globose, yellowish-green, velvety smut balls. When smut balls burst open, powdery dark green spores are released (Atia, 2004).he conditions for successful isolation of pathogen in axenic cultures have been standardized and the growth conditions were optimized. The fastest growth rate was achieved with potato sucrose agar medium having a pH of 6.0 at an incubation temperature of 27°C. Dark incubation was also found highly conducive for the growth of fungus compared to incubation in light. These conditions could be useful for the best isolation of the pathogen for different studies. Beside morphological identification, the identity of the fungal pathogen was confirmed

through ITS sequencing which showed up to 98 % identity with U. virens in NCBI-BLAST analysis (Mathew et al., 2015). B. Precise Disease Severity Assessment for False Smut Disease Standard Evaluation System (SES) of IRRI (2002), is the most referred disease severity assessment system. Recently, six scales for evaluation of the rice cultivars against false smut in the field were built based on average diseased grains per panicle (ADGPP), which agreed with SES for Rice of International Rice Research Institute (Li et al. 2011). a precise assessment method to evaluate the severity of the disease was developed. The ‘yield representative’ (YR) based on ‘mean floret wt.’ and ‘filled grain %’ was simulated for the precise disease severity assessment of rice false smut disease (Urmila et al., 2015). C. Integrated Approach to Control False Smut in Hybrid Rice It has become one of the most important rice diseases in China due to the large-scale expansion of high-yielding rice varieties, over use of chemical fertilizers and more frequent irrigation (Zhou et al., 2004; Lu et al., 2009). Chemical fungicides such as simeconazole (Tsuda et al, 2006) and bio-control agents, for example, Bacillus subtilis (Liu et al., 2007) were reported to be effectively against the disease. Conventional field trials are the major method for evaluating resistance (Sonoda et al., 1992; Kurauchi et al., 2006), and quantitative resistance to false smut disease has been observed among rice varieties (Fujita et al., 1990; Sonoda et al., 1992; Kurauchi et al., 2006; Li et al., 2008a, b, 2011). In China. When Neixiangyou 8156 and Nei5you 317 were sprayed with 2.5% Wenquning at 4.5 L/hm 2for two times at 6 d before and 1 d after heading, respectively, the control efficiencies of Nei5you 317 and Neixiangyou 8156 were respectively 100% and 82.24% compared to that of Gangyou 725. Satisfactory control effects had also obtained by single spray of 2.5% Wenquning at 4.5 L/hm 2 at 5–6 d before heading. Therefore, less susceptible hybrid rice in combination with spraying Wenquning at 5–6 d before heading was suggested for the disease control (Liang 2014).

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D. Simple and rapid detection of rice false smut pathogen Ustilaginoidea virens

UV6 and UV7), while Cluster II consisted of three isolates (UV2, UV3 and UV4) ( Mathew, 2014).

It is crucial to detect the RFS pathogenU. virensrapidly in rice seeds before export because the presence of the spore on the rice grain may affect the quality. Isolations on nutrient media and morphological examinations are the conventional methods for detection and identification ofU. Virens (Zhou et al., 2003). These methods are time-consuming and complicated and therefore there is a need to develop a simple and rapid detection tecA method for simple and rapid detection of Ustilaginoidea virensin rice seeds was developed based on specific polymerase chain reaction (PCR). To design the specific primers for detection of U. virens, the comparison was made on 5.8S rDNA intra- and interspecific variations in nucleotide sequences of U. Virens and other pathogenshnique to identify the pathogen in rice seeds. The development of the simple and rapid detection technique using specific primers will be applicable for direct identification of U. virensin rice seeds to screen large numbers of samples .(Yu et al., 2014).

III. RESULT AND DISCUSSION

E. Morphological and molecular characterization of Ustilaginoidea virens isolates The fungus forms chlamydospores and sclerotia late in the season which fall in the soil and may survive the winter. Sclerotia germinate to produce ascocarp containing ascospores, which are the primary source of infection to rice plants, whereas secondary infection may come from airborne chlamydospores. In infected plants mature head is replaced by velvety smut balls which are globose and yellowish green. When the smut balls burst open, powdery dark green spores are released (Atia,2004). Based on colony characters isolates of U. virens were grouped into three groups. The maximum colony diameter was observed in isolate UV3 (40 mm) while minimum was in UV7 (25 mm). The width of the hyphae in different isolates varied from 1.26-2.81 µm. The maximum width of the hypha was 2.81 µm in UV4 isolate and minimum in UV3 (1.26 µm). The genetic diversity of the eight isolates of U. virens, by random amplified polymorphic DNA (RAPD) marker using nine primers, revealed a considerable level of genetic variation. The dendrogram showed two main clusters; cluster I comprised of five isolates (UV1, UV5, UV8,

Complete genome sequence and organization of a novel virus from the rice false smut fungus Ustilaginoidea virens causing false smut disease in rice, is a destructive pathogenic fungus of rice, which was first reported in the Tirunelveli district of Tamil Nadu state, India (Cooke, 1978). three dsRNA segments from the rice false smut fungus Ustilaginoidea virens,the causal agent of a serious disease in rice, with molecular size ranging from 1.3 to 5 Kb, were isolated and named as dsRNA-L, dsRNA-M, and dsRNA-S. The complete nucleotide sequences of dsRNA-M and dsRNA-S were determined and analyzed. The dsRNA-M putatively encodes an RNA-dependent RNA polymerase, which is similar to that of the partitiviruses in the family Partitiviridae. Although the protein encoded by dsRNAS showed less similarity to the typical coat protein of the virus in the family Partitiviridae, the structural analysis results indicated that the dsRNA-S might function as the capsid protein. the virus is Ustilaginoidea virens partitivirus 2-Uv0901, a new member, but distantly related to the newly proposed genus Gammapartitivirus with a distinct sequence pattern of capsid protein (Jie et al., 2014). Genetic analysis of the population structure of the rice false smut fungus To investigate population genetics, it is necessary to find markers that are polymorphic, such as multilocus DNA fingerprinting, random amplified polymorphic DNA (RAPD) or amplified fragment length polymorphism (AFLP). Genetic diversity research on V. virens based on Rep-PCR, RAPD and AFLP technology has found no significant genetic variation between populations from different geographical regions (Zhou et al., 2008) or from different hosts (Li et al., 2012). Species-specific markers such as simple sequence repeat (SSR) or single nucleotide polymorphism (SNP) are considered robust for detailed genotypic assessment of fungi and have become more commonly used to assess genetic diversity (Dutech et al., 2007). These markers are highly reproducible (Santana, 2009), and they allow genotyping

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directly with DNA extracted from diseased plant tissue, by passing the requirement for isolation of the pathogen from diseased plant tissues, and avoiding the problem of inaccurate identification results from DNA of mixed species extracts (Rouxel, 2012). Currently, three SNP markers hav ebeen developed and used to assess genetic diversity of V. virens (Sun et al., 2013), and researchers found significant genetic diversity and differentiation among populations of the pathogen in five major ricegrowing regions of China. By use of the three SNP markers, Wang et al. (2014) further speculated that geographical factors influence V. virenspopulations more than rice cultivars. However, because the development of SNP markers is costly and timeconsuming, SSR markers may be a more economical and rapid method for genetic diversity studies using species specific marker (Dutech et al., 2007). Because of the complexity and the requirement that genome sequences are known in advance, there have been no SSR markers to data reported for V. virens.

IV. REFERENCES [1] Ashizawa T, Takahashi M, Moriwaki J, Hirayae K. 2010. Quantification of the rice false smut pathogen U.virens from soil in Japan using real-time PCR. European J. Plant Pathol. 128: 221-2 [2] Atia MMM. 2004. Rice false smut (U. viren) in Egypt. J. Plant.Dis. Prot. 111: 71-82. [3] Chiba S, Salaipeth L, Lin YH, Sasaki A, Kanematsu S, Suzuki N.2009. A novel bipartite double-stranded RNA mycovirus from the white root rot fungus Rosellinia necatrix: molecular and biological biological characterization, taxonomic considerations,and potential for biological control. J. Virol.83, 12801–12812. [4] Cooke MC. 1978. Some extra-European fungi. Grevillea 7, 13–15. [5] Dutech C, Enjalbert J, Fournier E, Delmotte F, Barre`s B, Carlier J, Tharreau D, Giraud T. 2007. Challenges of microsatellite isolation in fungi. Fungal Genetics and Biology 44, 933-949. [6] Fujita Y, Sonoda R, Yaegashi H. 1990. Evaluation of the false smut resistance in rice. Ann Rep Plant Prot North Jpn, 41: 205. (in Japanese with English abstract). [7] Guo X, Li Y, Fan J, Li L, Huang F, Wang W. 2012. Progress in the study of false smut disease in rice. Journal of Agricultural Science and Technology A, 2,1211–1217. [8] Herrero N, Duenas E, Moraga EQ, Zabalgogeazcoa I. 2012. Prevalence and diversity of viruses in the

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[21] Liu HQ, Fu YP, Jiang DH, Li GQ, Xie J, Peng YL, Yi XH, Ghabrial SA. 2009. A novel mycovirus that is related to the human pathogen hepatitis E virus and Rubi-like viruses. J. Virol.83,1981–1991. [22] Liu YL, Chen ZY, Zhou MG, Zhang J, Song FP, Liu YZ, Luo CP. 2007. Analysis on antifungal and antibacterial activities of Bacillus subtilisstrain Bs916 and its extract. Chin J Pest Sci, 9(1): 92–95. (in Chinese with English abstract). [23] Lu D, Yang X Q, Mao J H, Ye H L, Wang P, Chen Y P, He Z Q,Chen F. 2009. Characterising the pathogenicity diversity of Ustilaginoidea virensto hybrid rice in China. J Plant Pathol, 91(2): 443–451. [24] Lu DH, Yang XQ, Mao JH, Ye HL, Wang P, Chen YP, He ZQ, Chen F. 2009. Characterizing the pathogenicity diversity of U. virens in hybrid rice in China. J. Plant Pathol. 91: 443-451. [25] Lu S, Tian J, Sun W, Meng J, Wang X, Fu X et al., 2014. Bis-naphtho-c-pyrones from fungi and their bioactivities.Molecules, 19, 7169–7188. [26] Mathew S, Baite RK, Sharma T, prameela D, sharma K. Morphological and molecular characterization of Ustilaginoidea virensisolates causing false smut of rice in India. Indian Phytopath.67 (3) : 222-227. [27] Miyazaki S, Matsumoto Y, Uchihara T, Morimoto K. 2009. High-performance liquid chromatographic determination of ustiloxin A in forage rice silage. The Journal of Veterinary Medical Science, 71, 239–241. [28] Nuss DL. 2005. Hypovirulence: mycoviruses at the fungal-plant interface. Nat. Rev. Microbiol. 3, 632– 642. [29] Rouxel M, Papura D, Nogueira M, Machefer V, Dezette D, Richard-Cervera S, Carrere S, Mestre P, Delmotte F. 2012. Microsatellite markers for the characterization of native and introduced populations of Plasmopara viticola, the causal agent of grapevine downy mildew. Applied and Environmental Microbiology 78, 6337-6340. [30] Rush MC, Shahjahan AKM., Jones JP. 2000. Outbreak of false smut of rice in Louisiana. Plant Dis. 84:100. [31] Santana QC, Coetzee MPA, Steenkamp ET, Mlonyeni OX, Hammond GNA, Wingfield MJ, Wingfield BD. 2009. Microsatellite discovery by deep sequencing of enriched genomic libraries. Biotechniques 46, 217223. [32] Shan T, Sun W, Liu H, Gao S, Lu S, Wang M, et al., 2012. Determination and analysis of ustiloxins A and B by LC-ESI–MS and HPLC in false smut balls of rice. International Journal of Molecular Sciences, 13, 11275–11287. [33] Singh AK, Pophaly DJ. 2010. An unusual rice false smut epidemic reported in Raigarh District, Chhattisgarh. International Rice Research Notes 35: 1-3. [34] Sonoda R, Fujita Y, Yaegashi H. 1992. Varietal difference in resistance of rice to false smut. Ann

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Brown Spot Resistance in Rice : A Review Ali

Sattari1,

H-Nohtani2, Na-Azhdarpoor3, M-Ghadami4, MO-Madahinasab5, K- Moradi6, Mo- Noorozi7 Phd. student of Dept. of Agronomy and Plant Breeding, Faculty of Agriculture, Zabol University, Iran 2 M.Sc. Dept. of Agronomy and Plant Breeding, Faculty of Agriculture, Zabol University, Iran 3 M.Sc. student Dept. of Agronomy and Biotechnology, Faculty of Agriculture, Zabol University, Iran 4 Phd. student of Dept. of Agronomy and Plant Physiology, Faculty of Agriculture, Zabol University, Iran 5 Deptartment of Agronomy, Payame Noor University, Iran 6 Phd. student of Dept. of Agronomy and Plant Physiology, Faculty of Agriculture, Zabol University, Iran 7 Tanin Keshtzar Sabz Agricultural Research, Service and Production Cooperative Company, Iran 1

ABSTRACT Rice is suffering from several fungal diseases among them brown spot caused by Bipolaris oryzae is important. Rice brown spot (BS) is a chronic disease that affects millions of hectares of rice. Chaetomium cochliodes proved to be a new antagonistic fungus against brown leaf spot of rice. BS is by far one the strongest yield reducers amongst rice diseases today. Analysis of brown-spot infected control plants suggested that C.miyabeanus represses plant photosynthetic processes and nitrate reduction in order to trigger premature senescence and cause disease. Biological products formulated from Ch cochliodes were tested to control brown leaf spot of rice. Host plant resistance to disease is an effective and economical way to manage BS. Spot formation has been analyzed mainly using mutants. Many mutants exhibiting spontaneous cell death have been reported in various plants, including Arabidopsis, maize, barley, and rice.Three rice genes, Spl7, Spl11, and Spl18, have been cloned and characterized. BS is conventionally perceived as a secondary problem that reflects rice crops that experience physiological stresses, e.g. drought and poor soil fertility, rather than a true infectious disease. Keywords : Brown Spot, Bipolaris Oryzae, Chaetomium Cochliodes, Biological Products

I. INTRODUCTION Brown spot disease, caused by the fungus Bipolaris oryzae (Breda de Haan) Shoemaker, is one of the most destructive diseases in rice and is of great importance in several countries. Brown spot is still widely reported in India (Chakrabarti, 2001; Reddy et al., 2011), as well as in some parts of south and southeastern Asia (Savary et al., 2000a,b). The pathogen affects millions of hectares worldwide every year and yield losses in relative terms vary widely from 4 to 52% (Barnwal et al., 2013). The second most abundant element in the Earth’s crust, silicon (Si) can comprise up to 70% of the soil mass in the form of silicate minerals and water-soluble orthosilicic acid. orthosilic acid is readily taken up by the plant roots and loaded into the xylem by a specific transporter system (Ma and Yamaji, 2006). Via the xylem, silicic acid is transported to the shoots, where it

is constantly polymerized either as silica in the cell or as an insoluble, subcuticular silica layer outside the cell. To date, dozens of studies have documented the ability of Si to enhance plant growth and yield and it is the only nutrient that is not detrimental when accumulated in excess (Epstein and Bloom, 2009). The important diseases occur in susceptible variety of rice are rice blast caused by Magnaporthe grisea (Pyricularia oryzae) and brown leaf spot caused by Drechslera oryzae (Helminthosporium oryzae). Kanokmedhakul et al.(2006) stated that Ch globosum could produce antimycobacterial anthraquinone chromanone compound and disktopiperazine alkaloid and antifungal Azaphilones from Ch cupreum ncluding bis-spiroAzaphilones and azaphilones from Ch cochliodes (Thohinung et al., 2010). research during the previous two decades indicates another potential option for rice disease management through the use of biocontrol

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agents (Mina et al., 2013; Gade, 2013; Ramteke et al., 2011; Balai et al., 2013). A several biocontrol agents namely Pseudomonas fluroscence, Bacillus subtilis, Trichodermaspp. have been found effective against major rice diseases caused by fungal pathogens. (Vasudevan et al., 2002). The present investigation was undertaken for the management of Brown spot disease of rice by using safer fungicides and some bioagents. Disease diagram sets have been developed to aid in visual assessments of plant disease severity (Godoy et al., 2006; Lima et al., 2011; Spolti et al., 2011; Yadav et al., 2013). Typically, disease diagrams display the particular pattern of lesions of a specific disease on the unit of assessment and each diagram of the set represents a specific severity as percentage (James, 1971). Then, the rater uses the diagram set as a guide to estimate severity to the nearest percentage, which still requires that the rater interpolates and extrapolates to assign an appropriate value to the specimen (Madden et al., 2007).

II. METHODS AND MATERIAL Importance of Brown Spot Brown spot is still widely reported across India (Reddy et al., 2010) and more generally in the South and SouthEast Asian countries (Savary et al., 2000a). It causes yield losses that, on average, are in the range of 10 % of the attainable yield wherever it occurs (Savary et al., 2000b,2006) in the lowlands of tropical and subtropical Asia. Therefore, BS is by far one the strongest yield reducers amongst rice diseases today. Further, there is indication that BS is becoming more frequent and severe as drought is becoming more frequent (Savary et al., 2005), perhaps due to increased variability in rainfall. Host Plant Resistance (HPR) Host plant resistance to disease is an effective and economical way to manage BS. However, breeding efforts have emphasized acute diseases such as leaf blast and bacterial blight rather than chronic diseases such as BS (Savary et al., 2011) despite the importance of BS.

Biological Control of Brown Spot Seed treatments with Trichoderma viride or T.harzianum have reduced disease by 70 % (Biswas et al., 2010). Over 70 % disease reduction has been achieved too from the use of selected Pseudomonas spp. isolates (Joshi et al., 2007;Ludwigetal, 2009). Direct foliar application. Harzianum has also been reported to reduce the disease intensity and significantly improve grain yield, total grain carbohydrate and protein, in addition to a significant improvement in the total photosynthetic pigments in rice leaves (Abdel-Fattah et al., 2007). Red-Light-Induced Resistance to Brown Spot When the leaves were kept under natural light or in the dark. The protective effect was also observed in intact rice plants inoculated with B. oryzae; the plants survived under red light, but most of them were killed by infection under natural light or dark condition. Red light did not affect fungal infection in onion epidermis cells or heat-shocked leaves of rice, and it did not affect cellulose digestion ability; this suggested that the protective effect is due to red-light-induced resistance. In addition, the degree of protection increased as the red light dosage increased, regardless of the order of the red light and natural light period, indicating that red-lightinduced resistance is time dependent.the results suggest that the tryptophan and phenylpropanoid pathways are involved in the red-light-induced resistance of rice to B. oryzae (Roxana et al., 2014). Primary metabolism plays a Role in Molding SiliconInducible Brown Spot Resistance Analysis of brown-spot infected control plants suggested that C. miyabeanus represses plant photosynthetic processes and nitrate reduction in order to trigger premature senescence and cause disease. In Si-treated plants, however, these pathogen-induced metabolic alterations are strongly impaired, suggesting that Si alleviates stress imposed by the pathogen. Interestingly, Si also significantly increased photorespiration rates in brown spot-infected plants. Even though photorespiration is often considered a wasteful process, recent studies indicate that this metabolic bypass also enhances resistance during abiotic stress and pathogen attack by protecting the plant’s photosynthetic

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machinery. In view of these findings,our results favor a scenario whereby Si enhances brown spot resistance by counteracting C. miyabeanus-induced senescence and cell death via increased photorespiration. Moreover, our results shed light onto the mechanistic basis of Siafforded disease control and support the view that in addition to activating plant immune responses, Si also can reduce disease severity by interfering with pathogen virulen (Jonas et al., 2015). Bio-formulation of Chaetomium Cochliodes for Controlling Brown Leaf Spot of Rice Crude extracts from Ch cochliodes using hexane, ethyl acetate and methanol at 1,000 ppm could significantly inhibited the inoculum production of rice pathogen 93.85 per cent which ED50 value was 66.45 ppm when compared to the control (0 ppm). Ch cochliodes was formulated in different forms for applying to control brown leaf spot of rice. Biological products formulated from Ch cochliodes were tested to control brown leaf spot of rice caused by D oryzae. Result showed that biopowder formulation gave significantly highest to control leaf spot and highest plant growth when compared to the non-treat control, followed by applying crude extract of Ch cochliodes, benlate and spore suspension of Ch cochliodes. Moreover, bio-powder formulation gave significantly increased in plant growth over 44 % and followed by crude extract of Ch cochliodes, spore suspension of Ch cochliodes and benlate ( Kasem,2014). Characterization of the Rice Canopy Infested with Brown Spot Disease Based on the field hyperspectral data from the analytical spectral devices (ASD) spectrometer, we characterized the spectral properties of rice canopies infested with brown spot disease and selected spectral regions and bands sensitive to four severity degrees (severe, moderate, light, and healthy). The results show that the curves’ variation on the original and the first- and second-order derivative curves are greatly different, but the spectral difference in the near-infrared region is the most obvious for each level. Specifically, the peaks are located at 822, 738, and 793 nm, while the valleys are located at 402, 570, and 753 nm, respectively. The sensitive regions are between 430-520, 530-550, and

650-710 nm, and the bands are 498, 539, and 673 nm in the sensitivity analysis, while they are in the ranges of 401-530, 550-730 as well as at 498 nm and 678 nm in the continuum removal (Zhao, 2012).

III. RESULT AND DISCUSSION Management of brown spot disease For the management of the disease an experiment was conducted at Instructional Farm, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, Nadia, West Bengal during 2010-11 and 2011-12 by using Trichoderma viride isolate 5 @ 100 kg, 200kg and 400 kg per ha, as basal application with FYM @1.2 ton at final land preparation, Seed treatment with Bavistin @ 1g/kg of seeds, Drenching of Bavistin @ 1g/litre of water as basal application, Spraying of Bavistin @ 1g/litre of water for three times at an interval of 15 days starting from 30 days after sowing, Seed treatment with Bavistin @ 1g/kg of seeds + Drenching of Bavistin @ 1g/litre of water as basal application + Spraying of Bavistin @ 1g/litre of water for three times at an interval of 15 days starting from 30 days after sowing and Seed treatment with [email protected] 2g/kg of seed (Sarkar, 2014). Chromosomal locations of a gene underlying heat‑accelerated brown spot formation Spot formation has been analyzed mainly using mutants. Many mutants exhibiting spontaneous cell death have been reported in various plants, including Arabidopsis, maize, barley, and rice (Lorrain et al. 2003). Three rice genes, Spl7, Spl11, and Spl18, have been cloned and characterized (Mori et al., 2007; Yamanouchi et al., 2002; Zeng et al., 2004), and Spl5 has been fine-mapped (Babu et al., 2011). Spl5, Spl11, and Spl18have been suggested to play important roles in disease resistance (Babu et al. 2011; Mori et al., 2007; Zeng et al., 2004). On the other hand, lesions in spl7mutant plants are likely necrotic rather than directly associated with HR cell death, and are caused by environmental stresses such as high temperature (Yamanouchi et al., 2002). Spl7encodes a heat stress transcription factor (HSF), which is crucial for increasing plant tolerance to cell death in response to high temperature (Yamanouchi et al., 2002). HSFs bind to heat shock elements in the

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promoters of heat shock protein (HSP) genes and transcriptionally induce heat stress response (Wu, 1995).

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Role of Biotechnology in Cancer Control Mahin Ghorbani1*, Hamed Karimi2 1

Department of Biotechnology, Fergusson College, F.C. Road, Pune, Maharashtra, India Department of Information Technology, Payam noor university of Farokh-shahr , Farokh-shahr, Chaharmahl va bakhtiari, Iran

2

ABSTRACT Cancer control including predictive diagnosis, differential diagnosis, early detection, cancer progression control and proper treatment with biotechnology techniques has assumed a central emphasis in cancer research and treatment. Biotechnology as a modern science with high accuracy ,more efficiency power and analysis ability at bimolecular level provided researchers with detailed information about causes , biomarkers, related pathways, genes, factors , targets and anticancer ligands for control of different types of cancers to provide individualized therapy for compensation of disadvantages, incomplete ability of treatment and side effects of conventional methods of cancer therapy such as chemotherapy and radiotherapy. In this paper we have focused on biotechnology techniques for cancer control and discussed the role of each technique with example and the importance of each technique during control stages of cancer. The techniques are discussed here are such as Gene profiling, Genome analysis and Cell Culture, We hope this review will be helpful for researcher to understand the need and importance of biotechnology in conduction of cancer research programs, also This basic information provides opportunities for the researchers to expand and support the research area with their suggestive, feasible ideas and development of applicable new techniques for better cancer control with biotechnology. Keywords: Biotechnology, Cancer Control, Gene profiling, Genome analysis, Cell Culture.

I. INTRODUCTION Even with recent development and progression in diagnosis and treatment, cancer has remained a major cause of death. It is reported that cancer is the second main cause of death after heart disease. .Every year over 10 million people in the world detected with cancer and high percentage of this report die as a result of unsuccessful treatment of the disease. [1,2] Success percentage in cancer therapy is restricted due to difficulties in detection, late appearance of cancer and unavailability of differential therapy [3] Biotechnology contribution in cancer research has widely broken such restrictions and played significant role in developing new ways of cancer control and prevention . Cancer is a disease characterized by variation of the genome and the proteome. These alternations allow the cancerous cells to avoid normal cellular control mechanisms and to initiate growing unregulated. The major aim of cancer research programs conducted with biotechnology

methods is to determine these molecular errors and use this observation to develop appropriate differential diagnostic, proper treatment and prevention diets .[4,5] Biotechnology has helped researchers to understand cancer in different ways such as Gene profiling, Genome analysis, cell culture, culturing transgenic cell lines and specially identification of new biomarkers for detection of risk and progression of cancer. Available technologies in biotechnology help scientists to understand cause of cancer and the behavioral way of cancerous tissue in different environments. They also provide information about the factors increasing the growth rate of the cancers and the growth reducing factors as well .[4] Here we reviewed helpful technologies in biotechnology for cancer research to understand significance and need of the biotechnology in cancer therapy.

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II. METHODS AND MATERIAL Gene expression Profiling: It is a technique for measuring the expression level of large number of genes simultaneously ,used for classification of tumors and identification of specific alleles that increase the risk of developing cancer due to carrying genetic defect via inheritance in individuals which gives them a susceptibility to develop cancer over the lifetime. The most applicable gene expression profiling techniques are used by biotechnologists are, DNA sequencing, In situ hybridization, Real time PCR and gene mapping.[4,5] DNA sequencing is a determination process of the proper order of nucleotides: adenine, guanine, cytosine, and thymine—within strand of DNA. This method is widely used in cancer research programs for detection of oncogenic DNA sequences. DNA sequencing of cancer –related genes is done for discovery of biomarkers. DNA sequences variants, single nucleotide change , small insertions and small deletions are detected using DNA sequencing .These DNA sequences variations are present in cancerous tissues while are absent in normal healthy tissues of the same individual. [5, 6]So detection of such oncogenic DNA sequence variants are key factors for development of new treatment .As the products of oncogenic DNA sequences are abnormal so they can serve as targets for pharmacologic prevention and the technique is continuously applicable for discovery of biomarkers until completion of observation of spectrum of DNA variation in cancerous tissues.[6] The use of DNA sequencing and its role in identification of mutations in cancer is discussed here in the form of an example: one requirement for tumor formation is somatic mutations in nuclear genome, but sequence of somatic mutations in mitochondrial genome are not well understood. Using sequencing methods: genomic and transcriptomic sequencing, scientists identified somatic mitochondrial mutations across 527 tumors and 14 cancer types. They have found that there is a particular strength against deleterious coding mutations, demonstrating requirement of functional mitochondria in tumor cells. They also observed a strong mutational strand bias as the major source of mutations .So using this method; they have showed mtDNA function in cancer. [7]

In situ hybridization is another biotechnology technique widely used in cancer research programs. In this technique, localization of a specifics DNA, RNA sequence in a section of tissue (in situ) is done by using a labeled complementary DNA, RNA or probe. Using this method is helpful for the scientists to analysis expression of genes and their roles in development and progression of specific cancers.[4,6] For example, analysis of expression of AC3-33 gene which encodes a secretary protein that has inhibitory activity towards EIK1 transcriptional activity through ERK1/2 pathway by in situ RNA hybridization determined the role of AC3-33 gene in development and progression of some specific cancers. In this research, the result showed variation in expression level of AC3-33 across different tissues. Positive expression of the gene exhibited in squamous cell carcinoma of the esophagus, adenocarcinoma of the rectum, hepatocellular carcinoma, squamous cell carcinoma (SCC) of the lung, canceradjacent normal hepatic tissue, clear cell carcinoma of the kidney, invasive ductal carcinoma of the breast, SCC of the uterine cervix and cancer-adjacent normal kidney tissue while negative expression of the gene exhibited in adenocarcinoma of the stomach and colon, canceradjacent normal esophageal tissue, cancer-adjacent normal gastric tissue, cancer-adjacent normal colon tissue, cancer-adjacent normal rectal tissue, serous adenocarcinoma of the ovary and cancer-adjacent normal ovarian tissue.This technique helped in classification of tissues based on expression of AC3-33 gene into two groups positive and negative expression which lead in development of cancerous and normal cells respectively.[7] Real time PCR is another profiling expression technique which has broad application in analysis and study of cancers. This technique is advanced form of polymerase chain reaction used for amplification and simultaneously detection or quantification a targeted DNA sequence .In this technique, general principle of PCR are applied and detection of amplified DNA is carried out while the reaction progress is in real time. Real time PCR is one of the central focus for cancer research programs .[5,6]For example, for expression of drug targets such as beta –tubulins which are targets for anticancer drugs in cancerous cells, scientists developed a method using RT-PCR for determination of mRNA expression of eight human beta tubulin isotypes which

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encode class I, IIa, IIb, III, IVa, IVb, V, and VI and applied it to 21 healthy tissues and 79 tumor samples from seven cancer types. On the basis of expression pattern using RT-PCR they have found that non – tumoral tissues, TUBB (I), TUBB2C (IVb), and TUBB6 (V) were ubiquitous, TUBB1(VI) was hematopoietic cell-specific, and TUBB2A (IIa), TUBB2B (IIb), TUBB3 (III), and TUBB4 (IVa) showed high expression level in brain. In tumoral tissues, exhibition of most isotypes showed an alternation of expression pattern in specific tumor types. In overall expression of TUBB3 was increased while TUBB6 expression highly decreased in most tumors. Thus,non-tumoral tissues showed distribution of a complex tubulin isotypes which showed contribution to the toxicity profile of the drugs and significant alternations of specific isotypes in tumors stand for representation of markers for response to anticancer drugs.[9] Real –Time PCR assay also used for classification of tumours. For example scientists applied RT-PCR for classification of 30 main tumor types and 54 histological subtypes from 92 gene set.[10] Gene mapping, is another biotechnology method for determination of location of genes, gap and related distances between gens on a chromosome. The main goal of gene mapping in cancer projects is positioning of genetic markers related to cancers onto their respective locus on the genome. Gene mapping aims to identify markers related to the specific cancer and individual so it provides personalized cancer therapy .Also it helps in early detection of cancer, identification of high-risk cancer patients and finding molecular markers that can predict therapy responses. [4, 5,6] For example scientists conducted a large scale analysis project of breast cancer in European ancestry population including 37954 patients with 2900 deaths from the cancer. This project genotyped 20000 to 90000 single nucleotide polymorphisms (SNPs) across the genome .Using genotyping method, they identified one new locus named rs2059614 at 11q24.2) associated with survival in ER-negative breast cancer cases and a second locus (rs148760487 at 2q24.2 was also identified in association with genome-wide statistical significance in initial analyses, this association was similar in ERnegative and ER-positive cancer cases.[11] Genome analysis: includes determination, measurement and comparison genomic elements such as DNA

sequences, Gene expression, regulatory and functional elements at genomic rate. [4,6] Microarray analysis: The most applicable technique of genome analysis is microarray used for comparison level of expression of thousand genes simultaneously. This technique helps the scientists to understand which gene is turned on or off in presence or absence of cancer. The microarray analysis helps in identification of known genes playing role in cancer which in turn lead in identification of new target for cancer treatment. To understand the level of expression of genes in cancer cell line, Real time PCR is used which gives analytical information about quantify change of gene expression .[4,5,6]For example ,gene microarray analysis of lncRNA and mRNA expression profiles in patients with hypopharyngeal squamous cell carcinoma showed involvement of lncRNAs in development an progression of many types of cancers . In this method the researchers investigated differences in expression profiles of lncRNA and mRNA between three pairs of HSCC tissues and adjacent non-cancerous tissues by gene microarray analysis method. The result showed that In HSCC tissues significant upregulation of 669 lnRNAs and downregulation of 630 lnRNAs as compared to expression levels in adjacent non-cancerous tissues. Moreover, significant upregulation of 684 mRNAs and downregulationof 748 mRNAs in HSCC tissue observed. For confirmation of microarray results the scientists selected two differentially expressed lnRNAs (AB209630, AB019562) and 2 differentially expressed mRNAs (SPP1, TJP2) and applied qRT-PCR technique. The qRT-PCR results were the same as microarray analysis. The analysis showed distribution of the differentially expressed lncRNAs and mRNAs on each of the chromosomes (X and Y chromosomes) .based on the analysis, 71mRNAs involved in molecular functions were downregulated in cancerous cells. These results provide understanding the mechanism of underlying HSCC cancer genesis and also help in identification of new anticancer targets and detectable biomarkers for the disease. [12] Cell culture: The process of growing the cells outside of their environment under controlled condition is called cell culture. Eukaryotic cells including human cancerous cells have potential to culture outside the human body under controlled condition in incubators. Identified gene

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played role in cancer can be introduced to a cell line and subsequent changes and effects studied and analyzed by growing these cells in cell culture. In this technique, the gene first cloned and after insertion in plasmid vector, amplifies in bacteria. The vector is then transferred into mammalian cells using one of the cell transfection methods such as liposomes .Incubation of these cells is done at human body temperature and supplied with appropriate nutrients. By comparison the gene expression in these cells with controlled cells , researchers can identify the change appeared in the cells due to inserted gene.[6,13] For example secretion of autocrine hGH in the breast is essential for development of normal breast during puberty but increased levels of autocrine hGH observed in breast cancer. Scientists used tissue culture for analysis of this difference in levels of hGH in breast cancer development. Their finding has shown that secretion of hGH from breast cancer cells led in increasing growth rates and as a result the cells are more but hGH secreted from pituitary gland into the blood stream then to the tissue culture does not show increasing of cell growth. So this difference was helpful for them to find out causing molecules of breast cancer development .For further investigation, application of Microarray and PCR technologies together was used. [13, 14].

III. RESULT AND DISCUSSION Biotechnology introduced as an important filed of research and study for cancer treatment as it develops targeted therapy. Analysis of cancer at molecular level is possible through biotechnology techniques. Cancer caused by variation of the genome and the proteome. These variations allows the cancerous cells to inhibit normal mechanism of control and to start growing uncontrolled .The major goal of biotechnology in study of cancer is to determine these molecular errors and using this knowledge , provide differential diagnostic and prevention diets. Biotechnology has assumed a significant place in cancer therapy and analysis. Using biotechnology techniques and combination of these techniques in different ways help scientists in identification of new markers , prediction of high risk cancer cases , detection of new targets and discovery of anticancer drugs which ultimately led in individualized therapy . Base on the objective of the cancer project, different methods in single or in combination are applied

for investigation of cancer project’s aim. In this paper we, reviewed main techniques of biotechnology which are categorized in three groups such as Gene profiling, Genome analysis, Cell Culture. Each of these analysis method group, include several techniques for example gene profiling has several techniques such as RT-PCR, gene mapping, DNA sequencing method, in situ hybridization etc. Genome analysis mainly applies Microarray techniques such as RNA microarray and DNA microarray techniques and cell culture using culturing cell lines of cancerous cells and normal cells for comparison and study of the cancer. These techniques are applied in combination forms for different research projects such as classification of tumors , identification new genetic markers, Identification of new oncogenic DNA sequence in cancer like mtDNA function in cancer ,classification of tissues based on expression of genes like expression of AC3-33 gene, classified tissues into two groups positive and negative expression tissue groups which lead in development of cancerous and normal cells respectively, Identification of drug targets by Real time PCR like identification of beta –tubulin as target for anticancer drugs, identification of new locus using genotyping methods like rs2059614 at 11q24.2) associated with survival in ER-negative breast cancer cases and locus (rs148760487 at 2q24.2 in association with genome-wide statistical significance , investigation of new down regulation class in cancer by RT-PCR like HLA class I down regulation in breast cancer [15].Identification of role of many sequences in cancer development using microarray technology like role of lncRNAs in development and progression of many types of cancers, identification of new targets for anti-cancer drugs like cyclin dependent kinases by combination of biotechnology methods [16] Determination of expression level of hormones and their role in cancer using tissue culture technology like determination of increased levels of autocrine hGH in breast cancer. Hence biotechnology provides different opportunities in research area for cancer study due to its broad area of research and availability of techniques. Using these techniques along with professional knowledge of biotechnology and it's principles could improve cancer therapy and overcome disadvantage of conventional methods of cancer therapy. We hope biotechnologists will develop more techniques and discovery items in order to decrease the cause of death and to limit

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suffering percentage of cancerous patients .However cancer due to its complicated nature needs more time to completely analyzed but biotechnology provides a fast and promising way of therapy to reach the destination "complete therapy ".The biotechnology community encourages scientists to do their best in utilization of biotechnology's facilities in order to cover all aspects of cancer research such as treatment, prevention and prediction.

IV. CONCLUSION By increasing new technologies in biotechnology such as PCR, Microarray technology, RFLP and so on and generation of several targets for drug such as CDKs, ion channels, GPCRs and aquaporins also Biomarkers , biotechnology can be broadly used in cancer treatment for targeted therapy which gives more efficiency and accuracy results than other conventional methods. In combination with bioinformatics method for investigation and detection of cancer materials, more efficiency and rapid result can be obtained. For example by detection of SNPs using bioinformatics methods or gene finding or detection of biochemical pathways related to cancer. Biotechnology can be utilized any animal models like mouse and zebrafish. So application of biotechnology in cancer control using developed methods and material can be achieved valuable results in short time.[16-25]

[6]

[7]

[8]

[9]

[10]

[11]

[12]

[13] [14]

V. REFERENCES [1]

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[3]

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Anand P et al Cancer is a preventable disease that requires major lifestyle changes. Pharm Res. 2008 Sep; 25 (9):2097-116. Haggar FA, Boushey RP.Colorectal cancer epidemiology: incidence, mortality, survival, and risk factors. Clin Colon Rectal Surg. 2009 Nov;22(4):191-7. Ling CQ. Problems in cancer treatment and major research of integrative medicine. Zhong Xi Yi Jie He Xue Bao. 2003 Sep;1(3):168-70. Kewal K. Jain,Applications of Biotechnology in OncologySpringer, 2014. 885 p. Daniel H. Palmer,Lawrence S. Young, Vivien Mautner,Cancer gene-therapy: clinical trials . Trends in biotechnology 2006 24(2) p76–82,

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Farwell LM, Joshi VA.DNA sequencing of cancer-related genes for biomarker discovery. Methods Mol Biol. 2009;520:205-20. Stewart JB, et al .Simultaneous DNA and RNA Mapping of Somatic Mitochondrial Mutations across Diverse Human Cancers. PLoS Genet. 2015 Jun 30;11(6):e1005333. Hu F et al .Analysis of AC3-33 gene expression in multiple organ cancer and adjacent normal tissue by RNA in situ hybridization. Oncol Lett. 2015 Jun;9(6):2795-2798. Leandro-García LJ et al .Tumoral and tissuespecific expression of the major human betatubulin isotypes. Cytoskeleton (Hoboken). 2010 Apr;67(4):214-23. Erlander MG, Ma XJ, Kesty NC, Bao L, Salunga R, Schnabel CA.Performance and clinical evaluation of the 92-gene real-time PCR assay for tumor classification. J Mol Diagn. 2011 Sep; 13(5):493-503. Guo Q et al Identification of Novel Genetic Markers of Breast Cancer SurvivalJ Natl Cancer Inst. 2015 Apr 18;107(5).djv081 Zhou J et al ,.Gene microarray analysis of lncRNA and mRNA expression profiles in patients with hypopharyngeal squamous cell carcinoma. Int J Clin Exp Med. 2015 Apr 15;8(4):4862-82. Cree IA. Principles of cancer cell culture. Methods Mol Biol. 2011;731:13-26 Michael J. Waters* and Becky L. ConwayCampbel.The oncogenic potential of autocrine human growth hormone in breast cancer. Proc Natl Acad Sci U S A. 2004 Oct 19; 101(42):14992-3. Palmisano GL et al Investigation of HLA class I downregulation in breast cancer by RT-PCR. Hum Immunol. 2001 Feb;62(2):133-9. Ghorbani M, Karimi H, 'Role of Microarray Technology in Diagnosis and Classification of Malignant Tumours', International Journal of Scientific Research in Science and Technology(IJSRST), 1(3):117-121, July-August 2015 Ghorbani M and Karimi H. Cyclin-Dependent Kinases as valid targets for cancer treatment. Journal of Pharmacy Research 2015,9(6),377-382 Ghorbani M , Karimi H , 'Ion Channels Association with Diseases and their Role as

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Therapeutic Targets in Drug Discovery', International Journal of Scientific Research in Science and Technology(IJSRST), 1(3):6569,July-August 2015. Ghorbani M , Karimi H , 'Role of Aquaporins in Diseases and Drug Discovery', International Journal of Scientific Research in Science and Technology(IJSRST),1(3):60-64, July-August 2015 20Mahin Ghorbani, Hamed Karimi, 'Role of GProtein Coupled Receptors in Cancer Research and Drug Discovery', International Journal of Scientific Research in Science and Technology (IJSRST),1(3), pp.122-126 , July-August 2015. Mahin Ghorbani, Hamed karimi, 'Role of Biomarkers in Cancer Research and Drug Development', International Journal of Scientific Research in Science and Technology(IJSRST),1(3), pp.127-132, JulyAugust 2015 Ghorbani M ,Karimi H ,Ten Bioinformatics Tools for Single Nucleotide Polymorphisms , American Journal of Bioinformatics ;2014:3(2):45-48 Mahin Ghorbani, Hamed Karimi, 'Bioinformatics Approaches for Gene Finding ', International Journal of Scientific Research in Science and Technology (IJSRST),1(4),12-15, SeptemberOctober 2015. Mahin Ghorbani, Hamed Karimi, 'Bioinformatics Methods for Biochemical Pathways and System Biology Analysis', International Journal of Scientific Research in Science and Technology (IJSRST),1(4) ,75-79, September-October 2015. Mahin Ghorbani ,Iranian traditional medicine for treatment of type II diabetes, anxiety and hypertension with introduction of zebrafish model system for their screening, International Journal of Herbal Medicine, ,2014, 2(5),13-19.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Development of Guava Probiotic Dairy Beverages : Application of Mathematical Modelling between Consumer Acceptance Degree and Whey Ratio Hamad, M. N. F.*1, M. K. El-Nemr2 1

* Dairy Department, Damietta University/Faculty of Agriculture, Damietta, Egypt Agricultural Engineering Department, Damietta University/Faculty of Agriculture, Damietta, Egypt

2

ABSTRACT Twenty One guava probiotic dairy beverages (Lactobacillus aciophilus LA-5 "2% vol/vol" "T1", Bifidobacterium bavidium "2% vol/vol" "T2" and Lactobacillus aciophilus LA-5 "1% vol/vol" and this ratio in Bifidobacterium bavidium "T3") were produced using 0, 20, 35, 50, 65, 80 and 100% (vol/vol) (unsalted whey) which is a product of Ras cheese manufacturing in their formulations and the same percentage interchangeably with cow's milk. The adding of whey had effected on pH values in T 1 treatments. The highest pH values (5.039 to 5.173) recorded in the T2 treatments, while less values (4.083 to 4.246) recorded in T1 treatments, but in "T3 treatments" were a medium values (4.313-4.627±0.012). The effect of adding whey on counts of B. bavidium in "T2" treatments and L. aciophilus in "T2 and "T3" treatments were highly significant (p≤0.001), while, non-significant effect (p=0.609) of adding whey was showed on B. bavidium ("T3" treatments). In T1, T2 and T3 treatments, the higher values of consumer acceptance degree were 7.267, 7.567 and 7.767 out (9), respectively at 35% whey, while lower values 5 was showed at 0% and 80% whey in T1 treatments, and (3.233 and 3.867) at 100% whey in T 2 treatments" and T3 treatments. Mathematical Modelling was created to describe the relationship between consumer acceptance degree (C) and the whey ratio (W) at each type of the previously mentioned starters. Sinusoidal modelling was resulted with a standard error ranging between (0.38 or 0.40). This study is utilized to improve the product, the production of quality products, different consumer degrees and use of dairy wastes "whey", giving an economic value. Keywords : Guava, mathematical modelling, probiotic, consumer acceptance degree

I. INTRODUCTION Guava (Psidium gujava L.) is widely distributed throughout Egypt. Damietta governorate is considered one of the main districts of guava production in Egypt. The Guava is a soft thin-skinned fruit, sweet in taste and white flesh and many seeds within. It is very susceptible to physical damage. Also, it is highly perishable of ten with potential shelf life of only 2-3 days. Most guava yield are marketed by street vendors. Three days later, the remained fruits have sever decay disorders and become useless. Guava fruit were contains 80% moisture, 20% dry matter, 1% ash, 0.7% fat and 1.5% protein. It is a rich source of Vitamin C and contains other nutraceutical components such as vitamin A, vitamin B1, B2, niacin and pantothenic acid. In addition, it also contains a fair amount of phosphorous, calcium, iron, potassium and sodium [1], broad spectrum of

phytochemicals including polysaccharides, essential oils [2 and 3], alkaloids, glycosides, steroids [4], tannins, triterpenes, lectins, fatty acids, dietary fiber, manganese, oxalic and malic acids [5], phenolic compounds [6]. It's contain both major classes of antioxidant pigments such as carotenoids and polyphenols [7]. Its combination with probiotic fermented dairy food like yoghurt, curd and shrikhand will develop high value commodities to increase application of guava in the area of functional foods [8]. Conversion of whey into soft beverages is one of the most attractive avenues for utilization of whey for dairy industry. [9] developed beverage from paneer whey and guava. Here product diversification using whey as a partial replacement of water without much change in quality is quite [10]. Such beverages may be beneficial for the people suffering from gastro-intestinal tract disorders and can be used as

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therapeutic soft drinks. The popularity of yogurt products continues to grow; manufacturers are continuously investigating value-added ingredients such as prebiotics and probiotics to entice health-conscious consumers. Probiotics are referred to as ―live microorganisms, which when administered in adequate amounts confer a health benefit on the host‖ [11]. Lactobacillus and Bifidobacteria species are the most common types of probiotics. Prebiotics are classified as ―non-digestible food ingredients that beneficially affect the host by selectively stimulating the growth and/or activity of one or a limited number of bacteria in the colon, and thus improve host health‖ [12]. Currently, the most widely accepted prebiotics include fructooligosaccharides and galactooligosaccharides [13]. When prebiotics are combined with probiotics, their relationship is classified as synbiotic. This combination can improve the survival rate of the probiotics and provide additional health benefits to the host [14]. Whey contains more than half the solids present in the original whole milk including 20% of the proteins and most of the lactose, minerals and water soluble vitamins. There has been increased recognition that the proteins and lactose in whey are voluble nutrients which should not be wasted [15]. In Egypt, most of the whey produced is from Domiati cheese processing (salted whey) little amounts are produced from Ras cheese processing (unsalted whey).

characterized according to moisture content, pH, acidity, ash and soluble solids (Table 1). The other part was stored in a freezer at the temperature of -18°C. until it was used in the experiments. TABLE 1 PHYSCO-CHEMICAL COMPOSITION OF GUAVA PULP pH

Acidity

4.34

0.25

Soluble solids 7.7

Black spaces Non

Color

Y&M

T.C

Good

Nil

Nil

TABLE 2 CHEMICAL COMPOSITION IN COW'S MILK AND UNSALTED WHEY

Cow’s milk Unsalted whey

Cow’s milk Unsalted whey

F (%) 3.50

F/DM (%) 29.12

TS (%) 12.02

pH value 6.71

Acidity

0.80

10.66

7.50

6.14

0.14

SNF (%) 8.52 6.15

Lactose (%) 4.32 4.22

0.16

Salt (%) -0.05

TP (%) 3.41 1.1

Pasteurized milk (3.5% fat, 12.02% total solid content, 6.71 pH value and 3.41% total protein) obtained from dairy department, Faculty of Agriculture, Damietta University, Damietta, Egypt, and sweet Ras cheese (unsalted) whey (El-Ghazy laboratory, Elsawalem, Damietta), which was obtained during the production of Ras fresh cheese by the enzymatic coagulation process before the salting step (fat 0.80%, pH 6.14, total solids The main objectives of this study were (1) to produce an 7.50% and total protein 1.1%), heating to 65°C. to guava probiotic dairy beverages similar to commercial denatured of coagulation enzymes, were used to products that will serve as a basis of comparison for formulate the probiotic beverages (Table 2). fermented milk with added pulp guava, probiotic Starter culture (Lactobacillus acidophilus LA-5, cultures and sweet whey (unsalted whey) resulted from Bifidobacterium bavidium) were obtained from Ch. Ras cheese manufacturing, (2) Access to the best Hansen's laboratories, Danmark. Sugar "Elmarwa" ingredients between the two types of probiotic bacteria "white Sugar", Elmarwa Company for Treading& (Lactobacillus aciophilus and Bifidobacterium bavidium, Distribution, Damietta, Egypt. and (3) Creating a mathematical model describing the relation between consumer acceptance degree and whey Processing of guava probiotic dairy beverage Formulations: ratio at each starter. Twenty One beverages were formulated, containing 0 (control), 20, 35, 50, 65, and 80% (vol/vol) whey, with the remaining volume made up with milk, table (3). Materials: Preliminary experiments indicated that these whey Guava (Psidium guajava L.) pulps were obtained in a concentrations were appropriate for sensory tests. Sugar Masr Italia for food Industries at a factory of fruit pulp in Damietta El-Jadida city, Damietta Governorate, Egypt. was added to the probiotic beverage at a concentration Both fruit pulps were homogenized and repacked in low of 10% (wt/vol) and the mixtures were heat-treated at density polyethylene bags. One part of the samples was 83°C for 15 min. After cooling the mixtures to 46°C, the

II. METHODS AND MATERIAL

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fruit "Guava pulp" preparation was added at 5% (wt/vol), fermentation process, which was stopped by cooling to the probiotic starter culture inoculum at 2% (vol/vol) 5-8°C. The beverages were stored under refrigeration (Table 3). The mixture was kept at 45°C for the until the consumer test. TABLE 3 PROCESSING OF THE PROBIOTIC BEVERAGE FORMULATIONS EACH 1000 ML

Treatments Milk (L.) 830 664 539.5 T1 415 290.5 166 ---830 664 539.5 T2 415 290.5 166 ---830 664 539.5 T3 415 290.5 166 ----

Whey (L.) ---166 290.5 415 539.5 664 830 ---166 290.5 415 539.5 664 830 ---166 290.5 415 539.5 664 830

Whey (%) 0 20 35 50 65 80 100 0 20 35 50 65 80 100 0 20 35 50 65 80 100

Guava (ml) 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50

Starter (ml) 20 ml L. aciophilus

20 ml B. bavidium

10 ml L. aciophilus + 10 ml B. bavidium

Sugar (gm) 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100

Total 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000

T1: Probiotic beverage with 2% L. aciophilus, T2: Probiotic beverage with 2% B. bavidium, T3: Probiotic beverage with 1% L. aciophilus and 1% B. bavidium

Physico-chemical and Microbiological Analyses:

Mathematical Modelling:

Total solids (TS%), fat, total nitrogen (TN%), lactose content, soluble nitrogen (SN%) and non-protein nitrogen (NPN%) of milk and cheese samples were determined according to [16], the pH was determined with a digital pH meter (Hanna AT 4817). Salt contents of samples were estimated using Volhard method according to [17]. The titrable acidity of guava bulp was estimated by [18]. The Brix percentage of the guava pulp

Curve expert© 1.3 program was used to model the relationship between the product quality (Independent variable) and whey ratio (dependent variable) for the three types of starter. The average of whey treatments for the three types of starter were used to fit the curve of the consumer acceptance degree which describes product quality. Sinusoidal fit was resulted with a correlation factor 98.59%. Referring to the previous result the sinusoidal fit was chosen to fit the curves which describe the relationship between the product quality and whey ratio at each starter type. Each curve will be fitted to model consumer acceptance degree (C) as a function of whey ratio (W).

was determined using the refractometer to estimate soluble solids. Total bacterial count (T.C.) of Guava pulp was

determined according to [19]. Yeast and Mold (Y&M) were determined to according [19]. The enumeration of L. acidophilus LA-5 was carried out in duplicate using de Man, Rogosa, and Sharpe agar supplemented with 0.15% (wt/vol) of bile salts obtained from (El-Gomhoria co., Mansoura, Egypt), incubating anaerobically for 3 days at 37°C [20]. Live strain in B. bavidium was inoculated in (MRS) broth supplemented with 0.05% (w/v) cysteine hydrochloride at 37°C under anaerobic conditions for 24 h [19]. Colifom bacteria count according to the method described by [19].

Statistical Analysis: Data were analyzed using [21] computer program, GLM analysis of variance (ANOVA). Differences between means were detected by Duncan’s Multiple Range Test [22]. Consumer Test: Thirty consumers "staff members, graduate and undergraduate students, workers and employees of

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Faculty of Agriculture, Damietta University, Egypt" were randomly selected and invited to take part in the test [23]. The samples were presented at 5±3°C, served in polystyrene cups coded with 3-digit numbers, following the sample presentation design in balanced complete blocks [24] aimed at decreasing the carryover and first-order effects, served 30-50 ml samples to each consumer. Participants were instructed to drink water between samples to cleanse the palate. They evaluated the samples acceptance using a 9-point hybrid hedonic scale [25], where 1 = disliked extremely, and 9 = liked extremely. The consumer test was carried out after samples refrigerated.

4.086±0.009 (20%, whey) to 4.246±0.020 (100%, whey), while the counts of starter were at range from 29.333±0.882 X105 (100%, whey) to 57.333±0.333 X105 (20%, whey). Also, in the second experiment "T2 treatments", the effect of adding whey on the pH values and counts of B. bavidium X106 starter was found to be highly significant (p≤0.001). Higher value of pH and counts of B. bavidium was recorded as 5.173±0.012 (100%, whey) and 87.000±1.732 X106 (0%, whey), respectively, while the lower value was 5.039±0.013 (0%, whey) and 70.333±4.631 X106 (100%, whey), respectively. On the other hand, the third experiment "T3 treatments" included both of L. aciophilus and B. bavidium as starters. Adding whey during the different stages had highly significant effect (p<0.001) on pH values and L. aciophilus starter, pH values ranged from 4.313±0.049 (100%, whey) to 4.627±0.012 (65%, whey), while the values of L. aciophilus Starter ranged from 5.667±1.333 X105 (65%, whey) to 21.667±4.055 X105 (0%, whey), in contrast; non-significant effect (p=0.609) of adding whey was showed on B. bavidium X106 starter. With respect to L. acidophilus count, all beverages presented values>8 log cfu/ml, indicating a probiotic level sufficient to provide consumer benefits and to compensate a possible reduction caused by passage through the gastrointestinal tract [26]. In accordance Figure 1 : Fitting of Whey ratio- consumer acceptance degree curve with Egyptian legislation, the whey beverages showed probiotic counts >7 cfu/100 ml of product. The whey III. RESULTS AND DISCUSSION content did not interfere in the viability of probiotics in the dairy beverages (p>0.05), indicating no limit in the pH and Microbiological Values: capacity of the probiotic strain to metabolize the Based on the results, we concluded that the beverages peptides present in the whey. These results confirmed met the standards for human consumption according to the technological application of fresh whey from Minas the Egyptian legislation, thus allowing their use in Frescal cheese as a means to develop probiotic bacteria sensory tests. Table (4) shows the pH values, L. [27]. Moreover, our findings were comparable to those acidophilus and B. bavidium counts in whey probiotic of other studies involving dairy beverages [28] and to beverages. The pH values varied from 4.083±0.009 to results obtained for other dairy products processed from 5.173±0.012, the highest pH values (5.039±0.013 to cheese whey [29 and 30] and other dairy foods, such as 5.173±0.012) when the treatments using of B. bavidium yogurts [31], cheese [32 and 33], and ice cream [34 and T2 treatments", while the less values (4.083±0.009 to 35]. All samples were free counts of yeasts and molds 4.246±0.020) in the using of L. acidophilus "T1 and coliforms may be the hygienic or sanitary conditions treatments", but in treatments using L. acidophilus and B. during the process. bavidium "T3 treatments" were a medium values Consumer Test: (4.313±0.049 to 4.627±0.012). From the first experiment "T1 treatments" that included the L. aciophilus as a Table 5 shows the acceptance of the probiotic whey starter, only. It’s clear that adding whey during the beverages containing different levels of whey in three different stages from 0% up to 100% had highly experiments "T1, T2 and T3 treatments". The lower value significant (p<0.001) effect on the values of pH and L. (5.000±0.179) of the consumer acceptance of guava aciophilus starter. pH values were at range from International Journal of Scientific Research in Science and Technology (www.ijsrst.com)

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probiotic dairy beverages with different whey contents polluting substances, the use of cheese whey meets the in the first experiment "T1 treatments" was showed at 0% needs of the food industry. and 80%, whey, while higher value was 7.267±0.117 at 35%, whey. In the second T2 treatments" and third "T3 An analysis of the results presented by the different treatments" experiment lower value of consumer mathematical modelling allowed for the selection of two acceptance (3.233±0.213 and 3.867±0.150, respectively) probiotic beverage formulations: the first, determined by was recorded at 100%, whey, while higher value was analysis of the consumer acceptance degree, contained 0 7.567±0.092 and 7.767±0.104, respectively at 35%, to 100% cheese whey in its formulation, and the second, determined by the best consumer acceptance degree, whey. contained 35 and 50% unsalted whey, respectively. Whey content had an effect on consumer acceptance (p<0.05): maximum acceptance was observed for the Figure (2) describes the deviation between sensor degree beverage with 35% whey (mean score of 7.0 on the 9- and resulted values of models. Standard error of the point hedonic scale). Greater amounts of whey resulted three models varied between 0.38 and 0.40 which means in lower consumer acceptance: samples with 65 and 80% the predicted values is close to the experimental whey presented mean scores of 5.7 and 5.2, respectively obtained values [40] Cosine function has the property of [36]. This results was agreement of [37 and 38]. Previous describing the behavior of a curve that describes a studies reported the use of survival analysis in relationship has the trends of both decrease and increase development of dairy products. [39] used survival [41]. analysis to estimate the shelf life of probiotic yogurts. Thus, we tried to create a mathematical modelling to The consumer acceptance indicated values of 35% and describe the relation between the consumer's acceptance 50% whey in the formulations, respectively. degree and whey-added ratio for both types of starters, Nevertheless, considering the elevated nutritional quality while meeting current demands of the dairy industry. of the whey, the need to reduce the costs of the formulation, and the need to minimize the emission of TABLE 4 PH VALUES AND PROBIOTIC MICROBIAL COUNTS (LOG CFU/ML; MEANS±SD) OF GUAVA PROBIOTIC DAIRY BEVERAGES WITH DIFFERENT WHEY CONTENTS

Whey (%)

pH

L. aciophilus X 105

B. bavidium X 106

54.333±1.202a 57.333±0.333a 45.333±0.333b 44.333±1.453cb 39.667±2.906c 58.333±2.603a 29.333±0.882d <0.001

-

-

87.000±1.732a 85.667±2.963a 81.333±2.333ab 79.000±1.732abc 74.333±2.963bc 73.667±2.333bc 70.333±4.631c <0.001

21.667±4.055a 18.333±2.333ab 15.667±1.333abc 10.333±1.202cd

32.333±1.202 33.667±1.764 29.667±1.202 31.333±4.910

T1 cd

0 20 35 50 65 80 100 P-value

4.093±0.009 4.086±0.009d 4.160±0.012b 4.096±0.009cd 4.126±0.012cb 4.083±0.009d 4.246±0.020a <0.001

0 20 35 50 65 80 100 P-value

5.039±0.013d 5.080±0.012d 5.160±0.006ab 5.107±0.009cd 5.133±0.009cb 5.093±0.009d 5.173±0.012a <0.001

0 20 35 50

4.337±0.022d 4.450±0.031c 4.550±0.021ab 4.530±0.025cb

T2

T3

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4.627±0.012a 4.550±0.025ab 4.313±0.049d <0.001

65 80 100 P-value

5.667±1.333d 18.333±1.202ab 11.667±1.202bcd <0.001

35.333±3.756 30.333±2.603 28.333±1.453 0.609

T1: Probiotic beverage with 2% L. aciophilus, T2: Probiotic beverage with 2% B. bavidium, T3: Probiotic beverage with 1% L. aciophilus and 1% B. bavidium

TABLE 5 AVERAGE CONSUMER ACCEPTANCE OF GUAVA PROBIOTIC DAIRY BEVERAGES WITH DIFFERENT WHEY CONTENTS

Whey (%) 0 20 35 50 65 80 100 5.000±0.179 5.900±0.139 7.267±0.117 6.867±0.115 5.667±0.130 5.000±0.179 3.700±0.204 T1 5.367±0.169 6.367±0.122 7.567±0.092 7.033±0.102 5.867±0.115 5.233±0.149 3.233±0.213 T2 5.700±0.174 6.700±0.137 7.767±0.104 7.633±0.162 6.233±0.133 4.467±0.124 3.867±0.150 T3 * T1: Probiotic beverage with 2% L. aciophilus, T2: Probiotic beverage with 2% B. bavidium, T3: Probiotic beverage with 1% L. aciophilus and 1% B. bavidium ** Evaluated on a 9-point hybrid hedonic scale from 1 = disliked extremely to 9 = liked extremely.

TABLE 6 MATHEMATICAL MODELLING OF CONSUMER ACCEPTANCE DEGREE AS A FUNCTION OF WHEY RATIO

Starter T1 T2 T3

Formula C=5.3444539+1.635956*cos(0.047459805W-1.8955734) C=-27.949858+35.123374*cos(0.010003013W-0.49273582) C=5.7246037+2.5126344*cos(0.063559216W-2.7262609)

Correlation factor, % 97.53 98.16 98.14

Standard error 0.38 0.40 0.38

T1: Probiotic beverage with 2% L. aciophilus, T2: Probiotic beverage with 2% B. bavidium, T3: Probiotic beverage with 1% L. aciophilus and 1% B. bavidium C: The consumer acceptance degree, W: whey ratio percentage interchangeably with cow's milk

A C Figure 2: Curve fitting of consumer acceptance degree as a function of whey ratio at three types of starters A) T1 B) T2 C) T3

IV.CONCLUSION

B

pH values in whey probiotic beverages between 4.083±0.009 to 5.173±0.012, the highest pH recorded in T2 treatments, while the less values in T1 treatments, but in T3 treatments were a medium values. - Higher numbers of B. bavidium in beverages were recorded as 87.000±1.732 X106 (0%, whey), while the lower numbers were 70.333±4.631 X106 (100%, whey). On the other hand, the numbers of L. aciophilus ranged from 5.667±1.333X105 (65%, whey) to 21.667±4.055 X105 (0%, whey).

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-

-

-

The lower value (5.000±0.179) of the consumer acceptance of beverages in T1 treatments were showed at 0% and 80%, whey, while higher value was 7.267±0.117 at 35%, whey. In T2 and T3 treatments recorded lower value of consumer acceptance (3.233±0.213 and 3.867±0.150, respectively) at 100%, whey, while higher value were 7.567±0.092 and 7.767±0.104, respectively at 35%, whey. In attempt to create a mathematical modelling to describe the relation between the consumer's acceptance degree and whey-added ratio for both types of starters, while meeting current demands of the dairy industry, we created a mathematical models listed. Generally, the whey content had an effect on consumer acceptance (p<0.05): maximum acceptance was observed for the beverage with 35% whey.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Economic Evaluation of Selexol – Based CO2 Capture Process for a Cement Plant Using Post – Combustion Technology Tsunatu D. Yavini.*1, Mohammed-Dabo I. Ali.2, Waziri S. Muhammad2 1

Chemistry Department, Taraba State University, Jalingo – Taraba, Nigeria Chemical Engineering Department, Ahmadu Bello University, Zaria – Kaduna, Nigeria

2

ABSTRACT This research work focuses on the economic evaluation of post-combustion technology to capture CO2 from a based Cement Plant using a physical absorption solvent called Dimethyl Ether Polyethylene Glycol-DEPG (Selexol). The low cost Selexol absorption unit captured 97% of the CO2 with 98% purity by mole of the CO2 through absorption into a 0.37 mole CO2/mole Selexol lean loading of the physical solvent. A detailed cost estimation of the CO2 postcombustion unit of the plant was carried out in order to evaluate the economic performance of the process and cost of CO2 captured, the additional utility costs associated with this technology. The CO2 capture cost per tonne of CO2 captured was found to be $58 (₦9,333). The Total Operating Cost was estimated at $27,542,469 (₦4.5Billion) and the Total Capital cost was estimated at $19,222,886 (₦3.08 Billion). The raw material cost was the highest cost in the CO2 capture process with a value of $19,500,000 (₦3.1 Billion) representing 71% of the total operating cost. Sensitivity analysis cases of the impact of absorber temperature, pressure and absorber inlet gas temperature on liquid and vapour flow, percentage CO2 recovery, energy consumption, annual operating and capital costs and cost of CO2 captured were studied. The overall result of the analysis shows that Selexol has proven to be thermally, chemically stable and commercially justifiable under the operating conditions used. Keywords: Absorption, Carbon Capture, Costs, Post-Combustion, Selexol, Sensitivity.

I. INTRODUCTION Anthropogenic CO2 emissions are being increasingly viewed as a problem by policy makers in Nigeria, and it is reasonable to expect that they may be regulated in the future. The Cement Industry emits large amounts of CO2 into the atmosphere (i.e. about 900 kg of CO2 per tons of cement produced) with the industry facing a sharp increase in cement demand worldwide for years to come as well as prospect of climatic change mitigation policies that could call for reduction in emissions of greenhouse gases. Hence, the proportion of CO2 released or emitted per unit cement produced could adversely have effects on the environment. Monoethanol amine (MEA) is more energy – intensive for CO2 capture to take place [1], hence contribute to the overall cost of the capture process. It is also highly corrosive on equipments and easily degraded by acid gases.

Against this backdrop, it becomes increasingly important to consider building flexibility into Cement Plant design such that they can be retrofitted, both from a technical and economical perspective, to capture CO2 (Rubin [2]. The International Energy Agency (IEA) estimated that, to have a 50% reduction in global CO2 emissions by 2050 (which is widely believed to be equivalent to reducing the increase in global temperature by 2 degrees), the available Carbon Capture and Sequestration (CCS) techniques should receive nearly one-fifth of GHG emissions from the power and industrial sectors. By 2050, as estimated by IEA, the cost of reducing climate change without CCS could be around 70% higher than with CCS. Already it will be around 40% by 2030 as estimated [3]. Therefore, CCS is currently the

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only option for decarbonizing the steel, chemical and cement industries. This process has been reported to have the ability of reducing annual carbon dioxide emissions by 9 – 16 billion tonnes worldwide by 2050 [4]. Cement industry has been one of the world’s largest industrial sources of CO2 emissions. It accounts for about 1.8 Gt/year CO2 emission in recent years [3]. Improved energy efficiency, replacing fossil fuels with wastes which may be regarded as ‘carbon neutral’, increasing the cement : clinker ratio by increasing the use of additives, and use of biomass have been over the years, the substantial means of reducing CO2 emissions per tonne of cement in the cement industry. The scope for further reductions by these means has become limited, yet there is an increasing need to reduce this emission to avoid any further increase in the contribution to anthropogenic climate change. Thus CCS enables the usage of well – established technologies with almost the same base infrastructure and significantly lowers CO2 emissions. Also, CCS in cement industry enables the reduction of other pollutants such as SOX, NOX, and particulate matters. Despite all these advantages, the bottlenecks concerning CCS calls for the feasibility of the technology in question. These bottlenecks include: the missing regulations, health, safety and environmental risks of CCS and the possibility of public acceptance with the technology being relatively energy-consuming and cost-intensive. This research study is motivated by the desire to mitigate global warming, by capturing CO2 emissions from Cement Plant. Thereby help to accomplish the goals set out by the Kyoto Protocol. CO2 is captured with the intention of being stored. The analysis of CO2 storage is beyond the scope of this research study.

II. METHODS AND MATERIAL 1.1 The Emissions Reduction Challenge: The CO2 Emission Reduction Challenges by 2020 has no definite answer on what the reductions will be by this set year, particularly because it is not only a scientific and economic choice, but also a societal choice. However, it is possible to use science and economics to begin to frame the scope of the challenge.

Assumptions: 1. The world commits to a pathway of stabilizing atmospheric concentrations at twice pre-industrial levels. 2. Economic and population growth occurs, increasing the demand for cement significantly in developing countries and at a slower pace in developed countries. 3. The cement industry meets society’s demand for increased amounts of products. 4. All industries follow a theoretically minimum cost approach to reduce CO2 emissions. 5. The world first slows the rate of growth of CO2 emissions and then begins decreasing global emissions all the while simultaneously allowing for economic growth. 6. The fraction of CO2 emissions that the cement industry’s contributes to total global fossil fuels and industrial CO2 emissions is never higher than it is today (Ken et al., 2003). Implications for 2020: 1. By 2020, global demand for cement will have increased by 115 to 180% over 1990 levels. In the highest growth scenarios, the developed countries demand increases an estimated 13% with the remainder of the growth coming from developing economies. Demand in developing countries grew 55% during the 1990s. 2. If the cement industry contributes to the stabilization of atmospheric greenhouse gas concentrations, in accordance with the assumptions above, this would require reducing the CO2 generated per tonne of cement by 30 to 40% over 1990 levels, on average across the entire global industry. 3. The industry would need to develop alternative cement formulations and new technologies to prepare for future reductions that are far more challenging, which by 2050 approach 50% reductions in CO2 generated per tonne of cement over 1990 levels, on average across the industry [5]. This research work is limited to the economic evaluation of CO2 capture process for flue gas from a Cement Plant (Ashaka Cement Plc) involving flue gas analysis of the plant which will be used as the basis for the plant design using Aspen Hysys. Equipment sizing and cost of CO2

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captured will be estimated using Aspen Process Economic Analyzer. The results obtained from both the simulation and economic analysis will be used for the sensitivity analysis to test the robustness, stability and performance of the Selexol-Based CO2 capture process. Hence, determine how economical and reliable the CO2 capture process will be; based on the operating conditions. 1.2

The Post – Combustion Capture Technology Concept for CO2 Capture of the Cement Plant

The research team proposed the post-combustion capture technology for a cement plant that combines the possible measures which will significantly reduce the high costs displayed by the normal state-of-the-art chemical solvent, MEA – based post combustion capture in some cement plants with the physical solvent SelexolTM considering the cost of capturing one ton of CO2. The schematic diagram of the Selexol-Based CO2 capture process for the plant is presented in Figure 1 using Aspen Hysys software. As depicted in Figure 1, the plant flue gas from the rotary-kiln after calcination of the limestone to form clinkers is physically treated in the Selexol-Based absorption unit, where most of the CO2 content of the flue gas is separated, while the remaining content of the flue gas is released into the atmosphere through the clean-gas exit on the absorber. Cement production is both energy and emissions intensive: 60–130 kg of fuel and 110 kWh of electricity are required to produce a ton of cement, leading to emissions of around 900 kg CO2/t [8]. The production of cement releases greenhouse gas emissions both directly and indirectly: the heating of limestone releases CO2 directly, while the burning of fossil fuels to heat the kiln indirectly results in CO2 emissions. The direct emissions of cement occur through a chemical process called calcination. Calcination occurs when limestone, which is made of calcium carbonate, is heated, breaking down into calcium oxide and CO2. This process accounts for ≈50% of all emissions from cement production [2, 6]. Indirect emissions are produced by burning fossil fuels to heat the kiln. Kilns are usually heated by coal, natural gas, or oil, and the combustion of these fuels produces additional CO2 emissions, just as they would in producing electricity. This represents around 40% of

cement emissions. Finally, the electricity used to power additional plant machinery, and the final transportation of cement, represents another source of indirect emissions and account for 5-10% of the industry’s emissions [7]. The CO2 capture plant was designed to remove 97% of the CO2 from flue gas stream coming from the flue stack of the cement plant. The flue gas goes through the cooler to be cooled to 40oC from 180oC. The flue gas leaves the cooler 1 with a pressure and temperature of 100kPa and 40oC which is the appropriate for the absorber’s performance. The flue gas from the cooler 1 enters the bottom of the absorber and the lean Selexol (33.4 wt. %) with a CO2 loading of 0.37 mole CO2/mole Selexol enters from the top of the column counter-currently at a pressure of 100kPa and 27.99oC. It is very important to keep the lean Selexol solution temperature as low as possible for two crucial reasons: (i) to reduce Selexol and water make – up and (ii) to increase the CO2 capture efficiency. The number of stages for the absorber obtained in this research is 10, to achieve a rich SelexolCO2 loading of 0.4 mole CO2/mole Selexol and 97% recovery. Clean gas from the top of the absorber is now released into the atmosphere since it has now met the standard limits set by World Bank and USEPA. The absorber operates at a temperature of 50oC and a pressure of 2360 kPa. This pressure enhances the absorption rate because from Henry’s law of CO2 solubility in physical solvents shows that as the partial pressure of the gas increases, absorption also increases, which made the absorber pressure to be set at ≈ 2360 kPa.The entire process within the absorber is an exothermic process where Selexol reacts physically with CO2 in the column. This interaction between the solvent and gas forms a weak bond between the compounds at higher pressure which can be regenerated physically by reduction in pressure within Flash Tanks in series so that the CO2 would be released. The rich Selexol from the bottom of the absorber goes to the rich Selexol valve to reduce the pressure from 2403 kPa to 1800 kPa. The rich Selexol then flows into the GASFLASH where it is separated into vapour and liquid phases, with the vapour containing about 0.9980 mol-fraction of CO2 while the rich Selexol flows from the bottom to VALVE2 where the pressure is further reduced from 1800 kPa to 980.7

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Figure 1: Aspen Hysys Simulation Process Flow Diagram for the Selexol Capture Unit for the Cement Plant

kPa. This continues till the rich Selexol finally enters LP FLASH where it operates at 98.07 kPa (≈ atmospheric pressure) to release virtually all the CO2 absorbed within the rich Selexol. The separation in this Low Pressure Flash Tank composed of about 0.9814 mol-fraction of CO2 which is then compressed in COMPRES2 to increase the pressure from atmospheric to 1961 kPa which meet with other CO2 streams coming from FLASHGAS1 and COMPGAS2 for onward separation of liquid traces in a separation tank to allow CO2 captured or produced to be compressed depending on its utilization. This research made provision for the CO2 to be compressed to a pressure of 1800 kPa and temperature of 179.7oC for the pipeline transportation which is out of the scope for this study. Type and amount of packing are selected so that the maximum recovery is obtained using the minimum consumption of the solvent - Selexol. The flue-gas composition for the base case is shown in Table 1.

Table 1: Cement Plant Flue Gas Composition for Process Simulation using Aspen Hysys Parameters Kiln Operating at Highest Capacity Temperature (oC) 180 Pressure (Bar) 1 Mole Flow (kmol/hr) 1210.26 Mass Flow (kg/hr) 53,243.55 Volume Flow (m3/hr) 252,000 Mass Flow, kg/hr: CO2 52,999.659 SO2 2.588 NO2 191.372 O2 49.930 Mole Flow, kmol/hr: CO2 1204.5 SO2 0.0404 NO2 4.1603 O2 1.5603 Mass Fraction: CO2 0.99540 SO2 0.00005 NO2 0.00359 O2 0.00094 Mole Fraction: CO2 0.99520 SO2 0.00003 NO2 0.00344 O2 0.00129

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2.0 Economic Evaluation and Analysis 2.1 Sizing and Cost Evaluation Using Aspen Process Economic Analyzer Aspen process Economic Analyzer which was formerly known as Icarus Process Evaluator is an integral part of the Aspen Hysys Software package that was designed to automatically prepare the detail designs, estimates and carryout the investment analysis of the process plant simulated using Aspen Hysys with information supplied from the simulation result or the equipment sized. Sizing or mapping can be done either by mapping one equipment at a time or all equipments at once in the APEA.

The basic assumptions made for this research work were based on the international standards criteria which have been developed for Cement Plant with CO2 capture process from its flue gas. These key parameters for the Selexol-Based CO2 Capture Process are summarized in Table 2. Table 2: Key Parameters for Economic Evaluation of Selexol-Based CO2 Capture Process

The total cost of the CO2 capture unit was evaluated when the cost of each component is estimated. This is necessary because the Aspen Process Economic Analyzer uses those costs together with information from simulation results and other specifications to evaluate the total capital investment cost (CAPEX) and total operating cost (OPEX) automatically. The development of a new CO2 capture plant cannot be complete without the plant cost analysis. Hence, this aspect describes the cost analysis of a Selexol-Based CO2 Capture Process for Ashaka Cement plant flue gases with the plant operating at its maximum capacity. The CO2 capture cost analysis was evaluated for the designed process with 97% recovery and 98% purity by mole of the CO2 with a CO2 lean loading of 0.37 mole CO2/mole Selexol, since it was observed that, at a lean loading of 0.37%, the maximum and best CO2 absorption in the column was obtained. In order to test the robustness, stability and performance of the capture unit results obtained from the simulation, a number of sensitivity analyses were carried out for the capture process. The key inputs are Capital Costs, Operating Costs and CO2 Capture Costs. Aspen Process Economic Analyzer was used for the cost analysis with the total cost, involving both operating and capital costs transformed to N/tonne of CO2 captured. 2.2 Basic Assumptions for the Costing of the Capture Unit

III. RESULTS AND DISCUSSION 3.1 Capital and Operating Costs Allocation for the Selexol-Based CO2 Capture Process for the Cement Plant Total operating cost for the Selexol-CO2 capture process includes all expenses such as costs for producing the products, selling the products, and recovering of capital cost. This cost is subdivided into Manufacturing costs and General Expenses. Manufacturing costs are all expenses connected to production; this cost is sometimes called Operating Cost or Production Cost. Summaries of these costs are presented in Table 3.

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Table 3: Capital and Operating Costs Allocation of the Selexol-Based CO2 Capture Process for the Cement Plant Capital Cost Components: Total Direct Cost Total Indirect Cost Working Capital CO2 Drying System Grand Total Capital Cost Annual Capital Cost Salvage Value (20% CAPEX) Annual Salvage Value Operating Cost Components: Total Variable Production Cost Operating Cost (at Second Year) Annual Operating Cost (across 20 years; annuity factor of 14.3%) 3.2

Cost ($)

Cost (N)

8,780,266 3,770,899 640,162 6,031,559 19,222,886 1,747,535 3,844,577 69,901

1,404,842,560 603,343,840 102,425,920 965,049,440 3,075,661,760 279,605,600 615,132,320 11,184,160

21,872,570 24,096,648

3,499,611,200 3,855,463,680

27,542,469

4,406,795,040

Table 4 shows the various costs incurred for the CO2 Capture Unit, as can be seen, the total annual CO2 captured (tonne) was obtained by calculating 97% recovery of the CO2 from the rich selexol, accounting for 504,356 tonne CO2 captured from the annual total of 519,955 tonnes. From the calculation, a value of $58 (₦9,280) was obtained as the cost of capturing one tonne of CO2 from Ashaka Cement Plant flue gases. Table 4: Calculated CO2 Capture Cost of the Capture Plant for the Cement Plant

3.3 Sensitivity Analysis

CO2 Captured Cost

The cost of CO2 captured for the case study will be calculated based on the total costs the plant incur based on calculated values obtained during the analysis (i.e. the total annual costs; TAC). To calculate this aspect of cost analysis, Table 4 shows the annual operating cost, annual capital cost, annual salvage value, total annual cost and the CO2 capture cost per tonne of CO2 captured for the capture plant design for the Cement plant [8]. The total annual cost (TAC) for the Selexol-Based CO2 Capture Plant for Ashaka Cement Plant is calculated thus: Total Annual Cost = Annual Capital Cost + Annual Operating Cost + Annual Salvage Value

The effect of Absorber Inlet Gas Temperature on percentage CO2 recovery, Energy Consumption, Annual Operating Cost, Annual Capital Cost and Cost of CO2 Captured was studied. A case study has been performed in order to investigate economic performance when changing the flue gas inlet temperature into the absorber. This was achieved by keeping the flue gas inlet pressure and number of stages constant. The CO2 recovery was specified at 97% and the carbon dioxide product purity at 98% by mole. The Net liquid flow and Net Vapour flow profiles varies depending on the absorber column temperature, and the total CO2 removal efficiency. CASE 1: Sensitivity of Liquid and Vapour Flows to Absorber Temperature and Pressure Figure 2 and 3 shows the sensitivity of the Net liquid and net vapour flows to the change in absorber column temperature and pressure. As can be depicted from the graphs; as the absorber column temperature increases, the net liquid and vapour flows increases steadily with net vapour forming plateau around 51.8oC while net liquid increases steadily with increasing temperature.

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The effect of absorber column pressure on the net liquid flow and net vapour flow was studied. Figure 4.14 shows that as the column pressure varies, the net liquid flow (selexol) increases steadily, this is evidenced that, at higher pressure, the more ability for physical solvent (selexol) to absorb carbon dioxide effectively and efficiently.

Figure 4 : Results of Percentage CO2 Removal and Energy Consumption as a function of Inlet Flue Gas Temperature.

Case 3(a): Sensitivity of Capital Cost and Operating Cost to Absorber Inlet Gas Temperature.

Figure 2: Results of Net Liquid flow and Net Vapour flow as a function of Column Temperature.

Figure 3: Results of Net Liquid flow and Net Vapour flow as a function of Column Pressure.

Figure 5 shows the summary of annual capital cost and annual operating cost as a function of absorber inlet gas temperature. As can be observe, at low inlet temperature of 30oC, the annual capital cost and operating cost are all maximal and at inlet temperature of 40oC, the capital cost and operating cost are minimal. Reason being that, as the temperature increases, the less the ability of physical solvent (Selexol) to absorb the CO2 leading to lower circulation of the solvent, hence decreasing the diameter of the absorber and consequently the direct cost, indirect cost and fixed capital cost decreases as evidenced in Figure 5. It was also observed that, at 40oC inlet gas temperature, both the annual capital and annual operating costs were minimum which signifies that, the process was best operated at this temperature; operation above this temperature increases these costs as evidenced in the graph.

CASE 2: Sensitivity of CO2 Removal and Energy Consumption to Absorber Inlet Gas Temperature The effect of inlet flue gas temperature on the CO2 removal across the column and energy consumption was studied, it was observed that as the temperature increases the capture rate decreases. This is evidenced that at higher temperature, physical solvent performance decreases while the energy consumption increases linearly from its lowest value at 0.684 up to 0.7027kJ/kg CO2 at temperatures of 30 and 55oC respectively. This signifies that, as temperature increases, less CO2 is captured, as shown in Figure 4.

Figure 5: Results of Annual Capital Cost and Annual Operating Cost as a function of Inlet Flue Gas Temperature.

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Case 3(b): Sensitivity of CO2 Removal and Cost of CO2 Captured per tonne to Absorber Inlet Gas Temperature.

Figure 7 compares the different results in terms of cost per tonne of CO2 captured for both the amine and selexol case which ranges from $48 (₦7,680) to €59.9 (₦10,728) per tonne of CO2 captured.

Figure 6 shows the CO2 capture cost per tonne of CO2 captured at absorber inlet gas temperature from 30oC to CO2 capture from an existing cement plant was studied 55oC. As can be seen from the figure, the absorber inlet by [1] with the conventional amine stripping approach. gas temperature that gives the minimum CO2 capture The cost of CO2 captured however, for the amine case cost per tonne of CO2 captured for a CO2 recovery of 97% was reported to be $54 (₦8,640) with CO2 composition is 40oC which correspond to a cost of $58.33 (₦9,333) in the flue gas to be 31.8% on molar basis. CO2 capture per tonne of carbon dioxide captured and the capture from an existing coal fired power plant was studied by cost is maximum at absorber inlet gas temperature of [10] using chemical solvent amine as well as an 30oC which corresponds to CO2 capture cost of $58.90 upcoming alternative commonly known as O2/CO2 (₦ 9,424) per tonne of CO2 captured. It could be recycles combustion. The cost of CO2 captured however, deduced from the figure also, that higher CO2 removal for the amine absorption process was $55 (₦8,800) with ability of the process correspond to higher cost of the CO2 composition of 14.6% on molar basis in the flue gas. capture. The process shows a deviation from this fact Alston Case [11] as studied have higher capital cost and after absorber inlet gas temperature of 40oC, indicating lower operating cost, reported a CO2 capture cost of $53 that, as the CO2 removal ability of the process decreases, (₦8,480) per tonne of CO2 captured. [12] operated a the CO2 capture cost per tonne increases, signifying that, fixed plant size of 290 tonnes/day, observed increase in at higher temperature(s), the physical solvent ability to total plant cost with CO2 consumption of 13% on molar absorb the CO2 decreases, hence leading to larger basis, with that above conditions, the CO2 capture cost absorber diameter which in turn increases fixed capital was approximately $48/tonne CO2 captured (₦7,680). cost, direct costs and indirect costs. [9] Studied the CO2 capture process of a dry-feed cement plant in NE Scotland, UK based on the use of post-combustion amine scrubbing using monoethanolamine (MEA) and found out the cost of CO2 captured to be €59.6 (₦10,728) per tonne of CO2 captured. [13] Studied the assessment of the value of retrofitting cement plant for carbon capture with a case study of a cement plant in Guangdong, China, using a Post-Combustion, MEA process, with 85% capture rate of 2.15 million tonnes of CO2 captured. The study found out the cost of CO2 captured to be $70 (₦11,200) per tonne of CO2 emissions avoided. Figure 6: Results of CO2 Removal and Cost of CO2 Captured per tonne as a function of Inlet Flue Gas Temperature.

3.4 Comparison of CO2 Captured Cost with Other Research Work Research works have been carried out in this field of study for decade which involves design and costing of CO2 Capture Process for fossil fuel-based power plants. Such as gas, biomass, coal, pet coke e.t.c. The results from these studies were used for comparison with data obtained in this study. Figure 7: Comparison of CO2 Capture Cost

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IV. CONCLUSION CO2 released by Ashaka Cement plant was reduced from 4.86% to 0.13% compared to world standard (0.05%). The CO2 capture cost per tonne of CO2 captured was found to be $58 (₦9,333). The Total Operating Cost was estimated at $27,542,469 (₦4.5Billion) and the Total Capital cost was estimated at $19,222,886 (₦3.08 Billion). The raw material cost was the highest cost in the CO2 capture process with a value of $19,500,000 (₦3.1 Billion) representing 71% of the total operating cost. The capture cost obtained in this study was within the range obtained by other researchers, i.e. between ₦7,680 to ₦11,200. The cost of Post-Combustion CO2 capture at Ashaka Cement Plant using Selexol is expected to be slightly higher than at a power plant, reason, basically due to lower economies of scale and the need to install FGD, NOx reduction and Dust control devices. Finally, both minimum and maximum capture cost, energy consumption and maximum annual cost per annum to be paid should be considered, hence this will lead to the best Cement Plant, putting into consideration, carbon price development and regulatory requirement during the plant’s lifetime.

work and the Chemical Engineering Department, A.B.U. Zaria, TetFund Abuja, DSK Foundation, Wukari – Taraba State and Federal Scholarship Board, Abuja for the technical and funding they have provided that has aided greatly in the completion of this research

VI. REFERENCES [1].

[2].

[3].

[4].

Competing Interests The authors declare that they have no competing interests.

[5].

Authors’ Contributions The work was carried out in collaboration between all authors. Tsunatu D. Yavini. designed the study, carried out the simulation of the capture unit, performed the data analysis and revised the manuscript. Ibrahim A. Mohammed-Dabo supervised the economic evaluation aspect and wrote and revised the manuscript. Saidu M. Waziri provided valuable suggestions for the sensitivity analysis and interpreted the graphs and revised the manuscript. All authors read and approved the final manuscript.

[6].

V. ACKNOWLEDGEMENT

[9].

The researchers wish to acknowledge the management of Ashaka Cement Company Plc, Gombe for granting them the opportunity to use their plant for our research

[7].

[8].

Nazmul – Hassan, S.M., (2005): Techno Economic Study of CO2 Capture Process for Cement Plant. Research Project, Department of Chemical Engineering. University of WaterlooOntario, Canada. Rubin, E.S., and Rao, A.B. (2002): A Technical, Economic and Environmental Assessment of Amine – Based CO2 Capture Technology for Power Plant Greenhouse Gas Control. Annual Technical Progress Report. U.S Department of Energy/Control for Energy and Environmental Studies, Carnegie Mellon University, Pittburgh. IEA, (2007): Tracking Industrial Energy Efficiency and CO2 Emissions, OECD/IEA, Paris, France. IEA WPFF (2005): Challenges for Large-Scale CO2 Utilization and Sequestration. IEA Working Party on Fossil Fuels, Task Force on Zero Emissions Technology Strategy, Washington DC, March 19, 2012. WBCSD-World Business Council for Sustainable Development (2001): CO2 Emission Monitoring and Reporting Protocol for the Cement Industry. Version 1.5, Geneva, Switzerland. Rubenstein, M. (2012): Emission from the Cement Industry. The Global Network for Climate Solutions (GNCS FACTSHEETS). The Earth Institute, Columbia University. WRI, (2005): Navigating the Numbers: Greenhouse Gas Data and International Climate Policy. World Resource Institute. pp. 72 – 74. James, L.R., David, D.B and Sabah, U.R (1986): Engineering Economics, 1st Canadian Edition. McGraw-Hill, Ryerson Limited. pp. 40 – 64. Barker D.J., Turner S.A, Napier – Moore P.A., Clark, M. and Davison J.E (2007): CO2 Capture in the Cement Industry. Energy Procedia 1, GHGT – 9, Elsevier; Science Direct. Pp. 87-94.

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[10]. Singh, D., Croiset, E., Douglas, P.L., and Douglas, M.A. (2003): Techno-Economic Study of CO2 Capture from an existing Coal-Fired Power Plant: MEA Scrubbing vs. O2/CO2 Recycle Combustion. Energy Coversion Management, (44), pp. 3073 – 3091. [11]. Nsakala, N.Y., Marion, J., Bozzuto, C., Liljedahl, G., and Palkes, M. (2001): Engineering Feasibility of CO2 Capture on an existing U.S Coal – Fired Power Plant. Final Report, Vol. I, ALSTOM Power Inc. U.S.A [12]. Mariz, C.L.(1998): Carbon Dioxide Recovery, Large Scale Design Trends. The Journal of Canadian Petroleum Technology (37), pp. 42 – 47 [13]. Xi, L. and Jia, L. (2012): Assessing the Value of Retrofitting Cement Plant for Carbon Capture: A Case study of a Cement Plant in Guangdong, China, Energy Conversion and Management, Elsevier (64). pp. 454 – 465.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

3D Cartographic Model And Animation of As-built Educational Landuse of UNIBEN, Nigeria Innocent E. Bello*1, Isi A. Ikhuoria2 *1

National Space Research and Development Agency (NASRDA), Abuja, Nigeria 2

University of Benin (UNIBEN), Benin City, Nigeria

ABSTRACT The study focuses on 3-Dimensional (3D) cartographic modelling of built facility. A shift from 2-Dimensional (2D) to 3D cartographic animation recently emerged to solve problems of geodata perception and analysis. As a proof of concept, 3D of UNIBEN educational landuse was modelled from Shuttle Radar Topographic Mission (SRTM) Digital Elevation Model (DEM) data draped on GeoEye satellite image to give a 3D impression using ArcScene 10.1 Software. The height of each building was extruded from digitized footprint. From the 2D and 3D image maps produced, a campus navigation simulation and animation are geovisualized. Results of the study show that, besides the open land area of the university campus, staff residential quarters had the highest land use, followed by academic (lecture theatres and staff offices) and students‟ hostels respectively. The Faculty of Arts/Social Sciences had the highest building height of 16m and 5 floors respectively. The structural query of the 372 mapped building structures reveals 29 of them were 13m high. From the 3D as-built model, spatial information on each building (name, number of floor, height, use and spatial references) are obtained. From flight simulation, the 3D geovisualization of different perspective views of the campus revealed the huge beauty and spatial organisation hitherto unavailable in a traditional 2D map. The study is recommended for the implementation of a campus-wide efficient sustainable spatial planning and electronic street guide. Keywords: 3D Animation, As-Built Mapping, Facility Management, Geovisualization, Spatial Analysis

I. INTRODUCTION As used in this study, a map is a graphic representation (static or interactive) or scale model of spatial concepts or universe of discourse. Incorporated in a map is also the understanding that it is a "snapshot" of an idea, a single picture, and a selection of concepts from a constantly changing database of geographic information [15]. While maps are considered model of geographic realities, the International Cartographic Association (ICA) in 1995 described cartography as the art, science and technology of studying and making map [10]. Two dimensional (2D) maps are orthogonal (x, y), while three dimensional (3D) maps integrate height (z) thus regarded as a better way of representing reality than 2D maps [2]. Rendering 3D maps in a digital and animated form is an emerging trend in cartography. „The introduction of on-screen maps and their corresponding

databases resulted in a split between these functions. To cartographers it brought the availability of database technology and computer graphics techniques that resulted in a new and alternative presentation options such as 3D and animated maps‟ [12]. Applying 3D in facility mapping (FM) or as-built mapping enhances effective facility and infrastructural management. Conceptually, as-built map shows the spatial and graphical representations of the existing facilities and infrastructure within an area of interest. Thus, the concept of Facilities Mapping of built environment „is the process of digitally identifying and mapping facilities and infrastructure with the explicit goal to improve operational management and planning tasks such as dispatching, inventory, and maintenance‟ [24].

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To unimaginable extent, maps have such multiplicity of uses as anything that can be spatially conceived can be mapped and, thus, have nearly unrestricted potential utility. The introduction of computer graphics [5] in mapping has created a more robust platform for Geographic Information Systems (GIS) that has led to a different dimension from 2D orthogonal representation of geographic reality to 3D representation [17]. The making of maps from Remotely Sensed Images such as multi-spectral images (e.g., GeoEye, NigeriaSat-2, IKONOS, SPOT), Laser, and other terrain measuring sources such as SONAR and SRTM as source of height information have all created the added advantage of rapidly producing maps in a way usually impossible [14]. In facility mapping of geographic phenomena such as building infrastructure, the relatively accurate coordinates (x,y) are basic requirements in order to work with them in a GIS environment. The shift or outright embrace of 3D modeling or 3D geovisualization (geovisual analytics) of geographic phenomena helps to better appreciate the phenomena being represented because of the additional height information as against the 2D orthogonal topographic mapping. Today, the concept of „geovisual analytics‟ [21] and „information visualization‟ [3], [22], & [19], have both become a popular multi scenario mapping in 3D animation tool because it offers interactive access to multiple alternative graphic representations that stimulate (visual) thinking about geospatial patterns, relationships and trends, and as such supports knowledge construction [13]. In Cartographic animation and geovisualization, Dykes, MacEachren and Kraak stressed that geovisual analytics integrates approaches from scientific visualization, digital maps, image analysis, information visualization, exploratory data analysis (EDA) and GIS to provide theory, methods and tools for visual exploration, analysis, synthesis and presentation of geospatial data [6]. Studies on 3D facility and built-environment mapping abound in literature. For instance, Tamada et al., in 1994 [20] developed an efficient 3D facility management system based on the spatial data structure (MD-tree). In the system, 3D objects in a city are semi-automatically generated from 2D-maps by using appropriate rules. This corroborates with the capability of modeling a walkthrough facility for efficient emergency

management in a 3D cartographic environment as argued by kwan and Lee [13]. In remote sensing applications, Navatha, Venkata-Reddy and Pratap developed a 3D Modelling of NIT Warangal Campus Using GIS and High Resolution Satellite Data [18]. A similar study was done by Amhar et al., on the generation of true orthophotos using a 3D building model in conjunction with a conventional Digital Terrain Model (DTM) [1]. Ideally, usual orthophotos do not place general 3D objects (buildings, bridges, etc) on their geometrically correct positions because conventional algorithms are based on 2.5D DTM thus limiting significantly the possibility of describing the real 3D shape of the objects and inhibiting the correct calculation of visibility. Unlike Amharet al., [1], Frueh, Jain and Zakhor in 2005 developed a set of data processing algorithms for generating textured facade meshes of cities from a series of vertical 2D surface scans and camera images [8]. This is obtained by a laser scanner and digital camera while driving on public roads under normal traffic conditions and detecting dominant buildings. Applying the above steps to a large set of data of downtown Berkeley with several million 3D points, Frueh et al., were able to obtain a texture-mapped 3D model. Geovisualization work of Harrower and Fabrikant [9] is noteworthy. In Nigeria for example, Isioye, Aliyu and Nzelibe [11] carried out a 3D modeling of part of Ahmadu Bello University main campus in Nigeria using GIS and Google Earth satellite data. Generating shape file for the extracted buildings from a georeferenced image, the height of each building was added to the database as an additional field from which the extrusion of the height of the digitized buildings in ArcMap were carried out using ArcScene/ArcGIS software. A texture map of the senate building was carried out using the Google sketch up software. The developed 3D model was analyzed using attributes representing the characteristics and functionality of infrastructural facilities and resources of the campus. This reiterates the efficacy of rendering geographic reality in 3 dimensions. From previous studies, we may infer that the various 3D modeling of geospatial data, especially building and their façade in particular, are carried out using relevant

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integrated modeling or mapping technologies such as CADD, GIS, GPS, among others. Although all maps should have a legend to explain their contents, it is even more important to obey cartographic law for an animation [12] especially when dealing with educational facility maps. In addition, relevant studies on visualization of time series data, animated cartography and scientific visualization respectively includes those of Monmonier [16], Campbell et al., [2]; DiBiase et al., [4], and more recently, Harrower and Fabrikan‟s study on the role of animation in geovisualization [9]. The above authors‟ researches reiterate the emerging role of animation cartography in effectively and efficiently communicating reality especially to amateurs in geoinformation. Some examples of facilities include utilities (gas, water, telephone, and electricity), airport siting, transport planning and building infrastructure. In the past, when the need for facility map arose, a team of surveyors and draftsmen would combine skills to develop such a map. The steps for a successful operational strategy is based, among others, on facility mapping system which enhances the collection and integration of information on organizational assets such as building infrastructure parameters like number of floors, height and usage. The core of the FM system is, therefore, built around computer- aided drafting and design (CADD), Geographic Information Systems/Sciences (GIS) and Global Positioning Systems (GPS) technologies especially for georeferencing base images for mapping. Regardless of ambiguity in terminologies uses, terms such as AM/FM (automated mapping/facilities management) and network management systems are essentially the same technology. The major advantages of FM are that it facilitates quick database update, query and information that are useful for resource allocation, service dispatching, inventory, and maintenance. Nevertheless, analytical studies such as network analysis and catchment area analysis are possible with FM systems. GPS also play a major role in facility management because it is useful for geo-location of facilities aimed at effective management. It also

enhances the visualization of spatial and temporal information in a GIS [7]. 1.1 Statement of problem and Justification for the Study To demonstrate the geospatial significance of emerging trends in cartographic animation, we used Ugbowo Campus of University of Benin, Benin City, Nigeria being one of the oldest campuses among the Federal Government owned Universities in Nigeria. The campus has vast land resources and less than half of it has been fully developed for human habitation and academic purposes. More so, there is currently a dearth of requisite spatial dataset and format for effective facility and infrastructure management, and the spatial planning of the available land space for quality building development. The traditional cadastral maps currently available to the university only show the land area and planned uses in two dimensions (x, y). It is hoped that a 3D as-built and facility map of the campus will cartographically provide a complete model of the visual dimensions of man-made features, enhance better interpretation and comprehension of dimensions of features, increase capacity of rendering of buildings and mapped features in three dimensions, etc. Administratively, it will better serve areas such as navigation, city aesthetics and spatial planning, documentation of cadastral information, and street guides, etc. Therefore, developing a 3D as-built map for the campus will provide vital dataset currently not available for the efficient spatial planning, electronic campus street guide, and infrastructural development and management of the citadel of learning. Cartographic animation gives a better impression that last longer in the memory of the viewer [2]. 1.2

Aim and Objectives

The study aims at developing a 3D digital database and cartographic model for managing a built environment. The specific objectives are to: i. map and carry out the spatial analysis of landuse activities in the campus; ii. produce 2D and 3D as-built maps of the study area; iii. carry out a 3D rendition of the building infrastructures and account for the angular

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iv.

perspective parameters used for navigation animation; and Validate the positional accuracy of mapped facilities using Google Earth platform.

1.4 The Study Area The University of Benin (UNIBEN) is one of Nigeria's federal universities founded in 1970. It is located in Benin City; Edo State, Nigeria. The study area (Figure 1) spans between Longitudes 5036‟24.8” E to 5037‟55.4” E and Latitudes 6023‟33.4” N and 6024‟27.3” N respectively.

Figure 2 : Methodology Workflow using Unified Modeling Language (UML)

Figure 1: The Map of the Study Area (Source: Author, 2014) The university started as an Institute of Technology and was accorded the status of a full-fledged University by National Universities Commission (NUC) on 1st of July 1971(www.uniben.edu) [23]. The University has grown spatially and structurally over the years hence the need to have a digital cartographic profile for effective infrastructure management.

II. METHODS AND MATERIAL 2.1 Study Methodology Workflow The workflow methodology used in this study is illustrated in figure 2. The vector data (facility map) was captured as digital landscape model (DLM) and features cartographically symbolized as digital cartographic model (DCM) as shown in Figure 2. 2.2 Data Collection and Sources The data for this research were obtained mainly from two sources: primary (plate 1) and secondary sources (figure 3). The primary sources of data collection include field work and discussions with architects. During the fieldwork, direct field observations and inventorying of buildings and other facilities together with their corresponding height/depth and number of floors information were undertaken (plate 1).

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Plate 1: Observation of building heights

Figure 3b: 3D drape image on DEM resampled

The data was further computerized and integrated into the digitized data (shapefiles) generated from the georeferenced image using ground control points of Digital Globe image (GeoEye) obtained from online Google Earth image platform (figure 3). The UTM, WGS84, Zone 31 parameters were used as these correspond with the primary projection information used in Google Earth.

2.3 Data Analysis and Presentation Techniques The shape files were digitized from the boundaryclipped rectified image (sigma 0.10228, based on 1st order polynomial [affine] transformation). Table 1 shows the generated datasets.

Plate 2: Sample photo views of the mapped buildings (Source: fieldwork, 2014)

Figure 3a : Georeferencing interface

Having generated the shape files, their attribute information such as building height, number of floors and attribute names were entered accordingly. Table 1: Description of generated shapefile datasets Layer Shape Description Point Flowers planted within the Flower University line All roads including tarred, Road earth and footpaths Polygon The study area extent Boundary Polygon The various uses to which Landuse UNIBEN land area is put such as administrative, religious, academic, sports, health center, special centers, plantation, library, SUG, UDSS School, Banks or commercial, open land, Staff quarters, and students hostels. Polygon All building facilities such Building as faculties, departments, lecture hall, quarters, special, auditorium, bank buildings. Landmarks polygon These include facilities such as football pitch, swimming pool, petrol station and basketball pitch

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For the terrain information, the SRTM raster DEM data was used to generate elevation model from which the satellite image was draped to model the surface of the study area. All the above were done using ArcMap. The study area landuse and 2D maps were visualized and their cartographic marginal information such as the north arrow, the scale bar, legend, coordinate system and the producer information were also done using ArcMap layout view. For the 3D building foot print rendition, the shapefiles were geovisualized using ArcScene 3D geovisualization environment of ArcGIS 10.1 software. The vertical exaggeration of each building was multiplied by 3 „scale factor‟ for spontaneous recognition of height above terrain. The various buildings were assigned colours based on their height. The 3D point graphic symbol for flower was also used to give the flowers a 3D perception while the swimming pools‟ depths were extruded using negative values below the normal terrain level. To appreciate the general 3D facilities mapping, all the layers were overlayed on the 3D drape image as their respective base height. To validate the spatial alignment and positional accuracy of the generated dataset, the shape files were converted using the Keyhole Markup Language (KML) conversion toolbox – „layer to kml’ in ArcGIS software environment. A 500 scale range was used for all the datasets converted while the boundary shape file was used as the layer “extent properties”. The 3D facilities simulation and navigation animation was carried out using the Animation Toolbar in ArcScene. Each respective scenes for animation and their corresponding angular perspective parameters such as display time, name of camera key frame, targets X, Y and Z, Azimuth, inclination, and roll were captured using the capture button and stored using the ArcScene Animation Manager. The final file was exported and saved using .AVI extension for video. The resulted animation was played using the animation control player as well as the Window Media player as alternative video player software. The result is currently published online for visualization and validation of concept.

III. RESULT AND DISCUSSION 3.1 Landuse pattern of University of Benin, Ugbowo Campus. For administrative and planning purposes, the use to which a piece of land is put is aimed at maximizing landuse benefit. Knowledge of these use(s) with respect to landmass is indispensable. Figure 4 shows the landuse map of the study area with the building facilities overlayed on top. From figure 5, we can deduce that open land landuse is the highest landuse closely followed by staff quarters (senior and junior put together) while academics and students‟ hostel follows sequentially. It is obvious from the landuse map that proper planning need to be done in order to maximize the potentials of the available land. 3.2 2D facility and image map visualization of the study area Result of the as-built map of the study area shows that out of the total 3442302m2 landmass, building infrastructures occupy about 282531m2. (See figures 5 and 6 respectively). 3.3 3D renditions of the building infrastructures, angular perspective parameters and time duration for navigation animation Result of the 3D building infrastructure mapping (figures 9 and 10) shows that, the tallest building in the citadel of learn is the faculty of Social Sciences and Arts office buildings with a record of 16m height. This is closely followed by the Auditorium with 14m while for the 13m height buildings we have the school of medicine, faculty of law, hall 2, 3 and the blocks of flats. For example, resulting from the SQL query, out of the 372 buildings mapped, only 29 of them have building height of 13 meters above the terrain (figure 9).

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Figure 4: 2D Landuse Map of University of Benin Ugbowo main Campus

Figure 7: 2D As-built Map of UNIBEN Ugbowo Campus

Graph of Landuse 0 Banks or commercial Special Centres Health Centre Plantation SUG Staff Quarters

Uses

UDSS School Religious

200,000

400,000

600,000

800,000

137,389.804 Sports 143,945.396 Administrative 922,234.491 Open Land 275,217.603 Student Hostel 633,007.289 Academics 9,997.421 Library 19,514.243 Auditorium 44,747.745 Religious 93,037.109 UDSS School 900,957.676 Staff Quarters 9,333.374 SUG 106,894.113 Plantation 54,951.47 Health Centre 39,244.395 Special Centres 51,830.337 Banks or commercial

Auditorium Library Academics Student Hostel Open Land Administrative Sports

Figure 5: Bar Graph of Land Use Extent (m2) in Ugbowo Campus

Figure 8: Image Map of UNIBEN Ugbowo Campus

Figure 9: Overlay of Extruded 3D building Facilities on Satellite Image Figure 6: SQL Result of Map Query of all buildings height > 13m

3.4 Positional Accuracy validation of UNIBEN facility map using Google Earth viewer Figure 10 shows that the KML converted geovisualized data fell in their appropriate locations in Google Earth based layer thus validating reliability and the positional accuracy of the modeled 3D dataset for further use.

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Figure 10: KML 3D Data Positional Accuracy Validation in Google Earth

3.5 Demonstration of 3D cartographic animation of the mapped areas in a geo visualization environment Plate 3 and figure 11 show the photograph and the 3D simulated textural view of the auditorium respectively. Figure 12 shows a snap shot of the simulated navigation animation which is available on the World Wide Web online (see http://youtu.be/ZuNTeYj0kuk) for perspective view.

Plate 3: Façade photo view of auditorium

Figure 11: 3D Cartographic Texture Map rendition of the auditorium and environ

Figure 12: A Bird view snapshot of 3D flight navigation animation of UNIBEN Ugbowo Campus in ArcGIS-ArcScene. (NOTE: Animation video web link available here: Click http://youtu.be/ZuNTeYj0kuk).

IV. CONCLUSION In this study, we demonstrated the capability of ArcGIS (ArcMap and ArcScene modeling tools) in the generation, integration and geovisualization of geospatial data generated from high resolution image and height information from GPS and SRTM in both 2D and 3D animated cartographic models. The study also demonstrates the mapping capabilities of the facility mapping system which makes possible multiple ways of generating focused maps from a single and consistent database as we were able to migrate from ArcMap to ArcScene GIS environment yet using the same centralized database. From the 3D as-built model, spatial information on each building (name, number of floor, height, use and spatial references) are obtained. From flight simulation, the 3D geovisualization of different perspective views of the campus revealed the huge beauty and spatial organisation hitherto unavailable in a traditional 2D map. The study is recommended for the implementation of a campus-wide efficient sustainable spatial planning and electronic street guide. Based on the findings from this study, built environment administrators, planners, geographers, and in particular campus authorities, should be able to provide useful information on facility access, use and resource allocations as well as infrastructure maintenance aimed at administrative excellence. The National University Commission (NUC) should adopt the study model for all Nigerian Universities so as to have a „click-of-the-button‟ digital reach and view of University‟s infrastructural landuse.

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V. ACKNOWLEDGEMENTS Special thanks to Prof. L. M. Ojigi of NASRDA for offering useful advice and contributions in the refinement of this work. Many thanks to Mr. Austine Igbinoba, Benin City and Miss Tina U. Onothoja of Southern Illinois University, Edwardsville, USA for participating in the fieldwork data generation.

VI. REFERENCES Amhar, F., Jansa, J. and Ries, C. 1998. „Generation of True Orthophotos using A 3d Building Model in conjunction with a conventional DTM‟. Part 4 "GISBetween Visions and Applications", Stuttgart. IAPRS, vol. 32, pp. 16-22. [2] Campbell, C. S. and Egbert, S. L. 1990. „Animated Cartography/Thirty Years of scratching the surface‟. Cartographica, vol. 27, no. 2, pp. 24–46. [3] Card, S. K., Mackinlay, J. D. and Shneiderman, B. 1999. „Readings in Information Visualization: Using Vision to think‟. San Francisco: Morgan Kaufmann. [4] DiBiase, D., MacEachren, A. M., Krygier, J. B. and Reeves, C. 1992. „Animation and the role of map design in scientific visualization‟. Cartography and Geographic Information Systems, vol.19, no. 4, pp. 201–214. [5] Dransch, D. 1997. „Computer-Animation in der Kartographie: Theorie und Praxis‟. Heidelberg, Springer, 145 Seiten. [6] Dykes, J., MachEachren, A. M. and Kraak, M. J. 2005. „Exploring Geovisualization‟. Amsterdam, Elsevier. [7] Egenhofer, M. J. and Gollege, R. G. (Eds) 1998. „Spatial and temporal reasoning in geographic information systems‟. Oxford, Oxford University Press. [8] Frueh, C., Jain, S. and Zakhor, A. 2005. „Data Processing Algorithms for Generating Textured 3D Building Facade Meshes from Laser Scans and Camera Images‟. International Journal of Computer Vision, vol. 61, no. 2, pp. 159-184. [9] Harrower, M. and Fabrikant, S. 2008. „The role of map animation in geographic visualization‟. In: M. Dodge and M. Turner (Eds) Geographic visualization: Concepts, tools and applications. New York, WileyBlackwell. [10] ICA 1995. 10th General Assembly of the International Cartographic Association, Barcelona, Spain, 3 September. [11] Isioye, O.A., Aliyu, Y. A. and Nzelibe, I. 2012. „3D Modeling of part of Ahmadu Bello University Main Campus using Geoinformation Technology‟ In: O. Fabiyi and B. Ayeni (Eds.) Geospatial Technologies and Digital Cartography for National Security, Tourism and Disaster Management. Proceedings of Joint Conference

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of GEOSON & NCA. RECTAS, Obafemi Awolowo University Campus, Nigeria. 19 – 22 November. Pp. 107 – 117. Kraak, M. and Ormeling, F. 2010. „Cartography: Visualisation of Spatial Data‟. Third Edition. England, Pearson Education. Kwan, M. and Lee, J. 2005. „Emergency response after 9/11: The potential of real-time 3D GIS for quick emergency response in micro-spatial environments. Computers, Environment and Urban Systems, vol. 29, no. 2, pp. 93-113. Matthew, L.M. 2011. „Analysis of Viewshed Accuracy with Variable Resolution LIDAR Digital Surface Models and Photogrammetrically-Derived Digital Elevation Models‟. Department of Geography. An M.Sc. Thesis submitted to the faculty of the Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA. Merriam, D. F. 1996. „Kansas 19th century geologic maps‟. Kansas Academy of Science, Transactions, vol. 99, pp. 95-114. Monmonier, M. 1990. „Strategies for the visualization of geographic time-series data. Cartographica, vol. 27, no. 1, pp. 30–45. Murata, M. 2004. „3D-GIS Application for Urban Planning based on 3D City Model‟. ESRI Conference Proceeding. Navatha, Y., Venkata Reddy, K. and Pratap, D. 2011. „3D Modelling of NIT Warangal Campus Using GIS and High Resolution Satellite Data‟. International Journal of Earth Sciences and Engineering, vol. 4, no. 6, pp. 355358. Spence, R. 2007. „Information visualization design for interactions‟. 2rd edition. Harlow, Addison Wesley/ACM Press Books. Tamada, T., Nakamura, Y. and Takeda, S. 1994. „An efficient 3D object management and interactive walkthrough for the 3D facility management system‟. 20th International Conference on Industrial Electronics, Control and Instrumentation (IECON), 5-9 September. Bologna. 3 : 1937-1941. DOI: 10.1109/IECON.1994.398114 Thomas, J.J. and Cook, C. A. 2005. „Illuminating the path: The research and development agenda for visual analytics‟. Washington, IEEE press. Ware, C. 2004. „Information visualization: Perception for design‟. San Francisco, Morgan Kaufmann Publishers. Wikipedia, na. University of Benin. Accessed July 27, 2013 from http://en.wikipedia.org/wiki/

University_of_Benin_(Nigeria) [24] World Geography 2010. Facilities Mapping. Accessed July 18, 2013 from http://world-geography.org/230-fac ilities-mapping.html

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Sensitivity of Initial Abstraction Coefficient on Prediction of RainfallRunoff for Various Land Cover Classes of ‘Ton Watershed’ Using Remote Sensing & GIS Based ‘Rinspe’ Model Narasayya Kamuju Central Water and Power Research Station, Pune, Maharashtra, India

ABSTRACT Rainfall, Runoff, Infiltration are most important parameters in water balance equation of any hydrological problems. Among these parameters the real prediction of surface runoff is the crucial task. Many hydrologic models are available to estimate surface runoff from precipitation data. The development of a GIS based model that would make it possible to assess the surface runoff accurately and efficiently. On the basis of this requirement a model called „Runoff, Infiltration and Nonpoint Source Pollution Estimation‟ (RINSPE) was developed for estimating runoff, infiltration and nonpoint source pollution in the Ton river catchment based on the different land cover type distribution within the catchment. The Curve Number method for estimating direct runoff from rainstorms is now widely used in engineering design, post-event appraisals, and environmental impact estimation. In the present investigation the Initial Abstraction coefficient in the Curve Number method considered with 2 different scenarios by assuming „λ‟ value as 0.2 for general conditions and 0.3 for Indian conditions to run RINSPE model. The results reveal that the surface runoff of 860.79 mm occurred with a loss of 62.93 mm in the form of infiltration for scenarios: 1. The most occupied area in the Ton watershed is forest which is having a runoff of 656 mm with 124mm infiltration and a very slight variation in prediction of runoff and infiltration for scenario: 2 for the same land cover classes. In the present study the results reveals that „λ‟ value is 0.2 of Ia gave minute higher runoff values than „λ‟ value with 0.3. This experimental investigation makes sure that, higher the initial abstraction lowers the runoff and vice versa. Keywords: RINSPE, Initial Abstarction, precipitation, Runoff, Soil texture, Initial Loss

I. INTRODUCTION

the land. Surface runoff sends 7% of the land based precipitation back to the ocean to balance the processes Runoff is what occurs when rain is not absorbed by the of evaporation and precipitation [6]. The rate of runoff ground on which it falls and so then flows downhill. The flow depends on the ratio of rainfall intensity to the most important factor in determining the quantity of infiltration rate. If the infiltration rate is relatively low, runoff that will result from a given storm event is the such as when a soil is crusted or compacted, and the percent imperviousness of the land cover. Other factors rainfall intensity is high, then the runoff rate will also be include soil infiltration properties, topography, high. Infiltration is the initial process of water entering vegetative cover, and prevailing site conditions [11]. the soil at the ground surface from precipitation or Oceans make up 71% of the Earth's surface and the solar anthropogenic sources, which plays a major role in radiation received here powers the global evaporation runoff [12]. Infiltration is a direct loss that governs the process. In fact, 86% of the Earth's evaporation occurs volume and rate of runoff, and thus it controls the shape over the oceans, while only 14% occurs over land. Of of the runoff hydrograph [10]. Infiltration depends on the total amount of water evaporated into the atmosphere, the type of land use, soil type (texture class), vegetative precipitation returns only 79% to the oceans and 21% to cover, porosity and hydraulic conductivity, degree of

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soil saturation, soil stratification, drainage conditions, depth to water table, and intensity and volume of rainfall. The amount of rainwater that runs off during / immediately after a rainfall event depends heavily on the amount of rainfall, „initial abstraction‟, and the type and condition of ground it lands on. Development of a GIS based runoff model is a challenging task because of the complexities involved in the urban set up. However attempts were made in Birmingham, UK to develop GIS models for estimating direct or precipitation recharge, indirect recharge through seepage from surface water bodies, indirect recharge through mains leaks and indirect recharge through sewer leaks in a city on a regional scale [7],[8] and the same approach was used in the development of this model as applied to the Western Cape‟s Kuils-Eerste river catchment in South Africa. In this project, GIS based model namely „Runoff Infiltration and Nonpoint Source Pollution Estimation‟ (RINSPE) for estimating runoff and infiltration from various land use/ land cover types was developed for an urbanised and agricultural catchment. The model was developed taking into consideration that the model needed to be sophisticated enough to account for the routing of all precipitation in the form of surface runoff, infiltration and pollution loading. In order to estimate these parameters, some suitable method for estimating the areal distribution of rainfall losses through infiltration and runoff had to be chosen first in designing the model [9]. Notwithstanding this, there are other possible models that can be adopted and include the following: i) the rational method, ii) SCS CN method, iii) Horton‟s model for infiltration capacity, and iv) Green-Ampt infiltration model etc [5]. After considering various available methods for infiltration and runoff estimation, the United States Department of Agriculture, Soil Conservation Service (SCS, now known as the Natural Resources Conservation Service, or NRCS) Runoff Curve Number (CN) method was chosen. A. Study Area The study area is located in the western part of Doon valley, Dehradun district and Uttarakhand state in India.

The sub-watershed „Ton Watershed‟, which is a Subbasin in „Asan‟ watershed, is selected to run the RINSPE model. The Ton watershed is upper part of Asan River, which is called as Ton river in earlier days of the local people [2]. The Asan river is tributary of Yamuna River. Geographical location of the study area covers a total of approximately 150 km2 and lies between 77o45‟33” and 77o57‟46”and 30o24‟39” and 30o29‟05” as shown in Fig.1. The study area having large area under hilly tract. The climate is humid to sub-tropical varying from valley to the high mountain ranges of Himalayas. During rainy season 1625 mm rainfall is observed in the year. The area has a favourable climate for the growth of abundant vegetation due to reasonably good rainfall & elevation Dense & moderate mixed forest, shrubs, agriculture crops. Soils of the study area are found to be derived from alluvium parent material. These were observed, well to excessively drain with low to medium permeability and having texture sandy loam to clay loam with low to medium productivity.

Figure 1: Location Map of Ton Watershed

B. Data Required GIS based runoff and infiltration estimation using the NRCS Curve Number method normally requires the spatial inputs such as land use / land cover map, soil type/hydrologic soil group map, rainfall distribution map and values of initial abstraction or initial losses for each type of land use / land cover with attributes of specific group types and group codes. The preparation of each map is described in detail as fallows.

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i.

Preparation of Land Use/Land Cover Map:

catchment as shown in Fig.3. There are 6 verities of soil textural classes are identified from Ton watershed.

A Landsat TM satellite image acquired on 14 Nov 2004 was downloaded from website to prepare land cover classes grid map. There are 7 basic classes are identified under „supervised classification‟ with ground truth data in Ton watershed as shown in Fig.2. The basic classes are Agricultural crops, Fallow, Forest, Scrubland, Settlements, Dry river bed, water and Tea gardens. The highest land cover class of 94.27 km2 area covered under forest land. The lowest area of 0.01 km2 covered under water body. Agricultural crops covered an area of 2.89 km2, fallow land covered 6.27 km2 area, settlements covered an area of 3.78 km2 and scrub, dry river bed, and Tea Gardens covered 35.54, 4.70, 2.68 km2 area respectively.

Figure 3: Soil Map of Ton Watershed

Figure 2: Land use –Land Cover Classification of Ton Watershed

ii. Preparation of Hydrologic Soil Group (HSG) map Soil data gathered from textural properties of soils covered in the Ton watershed. The hydrologic soil groups (HSG) were derived from the Land Type data by reclassifying the soil textures present in it. Accordingly a soil thematic layer prepared by using soil data available from Ton watershed. A polygonised soil map prepared based on the types of soils covered in the

These are Loam, Silt Loam, Sandy Loam, Sandy clay Loam, Gravelly clay loam, Loam to Sandy Clay Loam. The higher portion of the catchment covered with Loamy soils and a least area of soils are covered with loam to sandy clay loam. Querying the attribute table and identifying and selecting correct textures (by making a link between the land type units and a corresponding field in the attribute table) from such an attribute table were difficult and time consuming. The soil classes reveal that 38.31% of area covered under HSG of D, and the lowest percent of area of 15.31covered under B type of HSG. The textural classification shows that an area of 90 km2 covered under loam sands, least area of 8.54 km2 covered under loam to clay loam type of textural class. iii. Preparation of Rainfall distribution grid map Daily rainfall data collected from a Self-recording rain gauge available at Poanta Sahib Village which is covered under Ton watershed for about 30 years from 1980 to 2009. In order to prepare Rainfall grid map, IDW method used from spatial analyst tool available in ArcGIS environment. The rain fall grid map of Ton watershed is shown in Fig.4.

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land use and soil types [11].This model is relatively simple requiring few input parameters, and has been widely applied in the fields of soil physics and hydrology [13]. The method is an empirically based one, and is applicable to the situation in which amounts of rainfall, runoff, and infiltration are of interest [4]. The USDA NRCS curve method predicts direct surface runoff using the following equation:

Q

Figure 4: Rainfall Distribution Map of Ton Watershed

iv. Curve Number (CN) and Initial Loss (Ia) Values The input values of CN and „Ia‟ were identified for the different land use / land cover types and HSG combinations through a literature search done on the Internet and from other sources. The CN values of each land class with code values are prepared in excel sheet and converted into Text (tab limited) format to prepare a „CN‟ text file. Similarly for Ia values corresponding land cover types are prepared by considering „λ‟ value as 0.2 and 0.3 for different text files prepared like CN text file as input files for the application of RINSPE model.

II. METHODS AND MATERIAL It was decided to use the NRCS Curve Number (CN) method for a quick estimation of runoff and infiltration taking place in the identified study area. It is important to note that surface runoff and infiltration in any location can be estimated through the following equation: Surface Runoff = Rainfall – Initial abstraction – Infiltration The NRCS curve number method is an empirical description of infiltration. It combines infiltration with initial losses (interception and detention storage) to estimate the rainfall excess, which would appear as runoff. The model was developed to provide a consistent basis for estimating the amounts of runoff under varying

P  I a 2

P  I a  S 

In which: Q = Total rainfall excess (runoff) for storm event (mm or inches), P = Total rainfall for storm event (mm or inches), Ia = Total initial loss or “initial abstraction” (inches), S = Potential maximum retention capacity of soil at beginning of storm or maximum amount of water that will be absorbed after runoff begins (inches). S, also called the retention parameter, is a statistically derived parameter related to the initial soil moisture content or soil moisture deficit [3]. The value of S is determined based on the type of soil and the amount and kind of plants covering the ground (cover types). This is derived through its relationship to the value of the NRCS runoff curve number (CN). A curve number is a numerical description of the impermeability of the land in a watershed. This number varies from 0 (100 % rainfall infiltration) to 100 (0 % infiltration –e.g., road/concrete). The following relation relates the value of S to the curve number.

S

1000  10 CN

CN = runoff curve number (0-100, based on the soil and land use information). CN is determined through several factors. The most important are the hydrologic soil group (HSG), the ground cover type, treatment, hydrologic condition, the antecedent runoff condition (ARC), and whether impervious areas are connected directly to drainage systems, or whether they first discharge to a pervious area before entering the drainage system. Soils are

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extremely important in determining the runoff curve number. Soils are generally classified into four Hydrological Soil Groups (HSG): A, B, C, and D, according to how well the soil absorbs water after a period of prolonged wetting. The whole methodology illustrated in the form of flow chart as shown in Fig.5

SCS-CN Equation for Indian Conditions: Values of „λ‟ varying in the range of 0.1 ≤ λ ≤ 0.4 have been documented in a number of studies from various geographical locations, which included USA and many other countries. For use in Indian conditions λ = 0.1 and 0.3 subject to certain constraints of soil type and AMC type has been recommended [3]. Based on the available theory regarding „Ia‟ in SCS-CN equation the present investigation carried by taking into consideration of ‘λ‟ value. The main tenet of this paper is to run RINSPE model in 2 scenarios by considering „λ‟ value as fallows. Scenario 1: assuming the „λ‟ value is 0.2 for general condition Scenario 2: assuming the „λ‟ value as 0.3 for Indian condition Overview of RINSPE Model

The „Runoff, Infiltration and Non-point Source Pollution Estimation‟ model implemented in ArcView Figure 5: Methodology of RINSPE Model Application GIS 3.2 platform through Avenue programming and its extension Spatial Analyst was selected for the estimation The terms „initial abstraction or initial surface loss of runoff and infiltration. RINSPE model was developed incorporates rainfall loss due to interception, as one of the deliverables of a Water Research evaporation from surface during rainfall events, Commission funded research project on assessment of depression and detention storages. The value of „Ia‟ non-point source pollution in the Kuils-Eerste River depends greatly on the cover types (the verity of plants catchments of Western Cape [1]. RINPSE is an eventcovering the soil or land use), the kind of soil based/annual based model that can estimate runoff & (hydrologic soil groups, hydrologic condition and its infiltration (using the NRCS CN method) and the treatment) and antecedent soil moisture of the area being pollutant loading from different land cover within a studied. For a given drainage basin, the values of „Ia‟ are catchment. With this model, using digital elevation data, highly variable, but generally are correlated with soil land use/ land cover type grid data and rainfall data and cover parameters. A major limitation for applying together with attribute tables covering chemical the SCS model lies in that the values of the parameter „Ia‟ characteristics, surface water runoff and pollutant must be evaluated with field data for each specific site as loading in surface runoff waters was calculated and fallows. various maps displaying the distribution of these parameters were generated. The Interface of RINSPE Ia = λ * S Model for Runoff and Infiltration Estimation is shown in Where Fig. 6. Ia = Initial abstraction S = Potential maximum retention λ = a constant Values of λ: on the basis of extensive measurements in small size catchments SCS (1985) adopted λ=0.2 as standard value [3].

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modeling of runoff and infiltration was done for two scenarios as mentioned in the methodology.

IV. RESULT AND DISCUSSION

Figure 6: Interface of RINSPE Model for Runoff and Infiltration Estimation.

III. RINSPE MODEL APPLICATION The major outputs from the model are distribution of surface runoff, infiltration, pollutant concentration and loading distribution, for each chosen pollutant. In this paper pollution parameters are not considered because, the main intention of this paper is to estimate runoff. However, applying the tool in other regions may require the preparation of land use input data in the required format. The RINSPE model has the advantage of its ability to assign more realistic individual initial abstraction/initial loss values for a particular land use / land cover underlain by a certain type of hydrologic soil using a table, thus providing more accurate estimation of runoff and infiltration. The input maps of land use / land cover and HSG were processed /converted into grid maps and were combined as one grid map of land use and HSG in the RINSPE model. An input table of Curve Number Values for different LUSE- HSG combinations for Antecedent Moisture Condition (AMC) II and initial abstraction „Ia‟ values for different land use / land cover units were prepared. The Curve Number (CN) grid was prepared in RINSPE model by running the programs for combining the HSG grid with the Land Use / Land Cover grid, for assigning the LUSE-HSG codes and finally querying and assigning CN values from the input table prepared for the LUSE-HSG codes. Later the grids of land use, CN and rainfall were combined together and initial abstraction or initial loss values were assigned through a map query done in RINSPE model. The submenu of “Runoff and Infiltration Depth” implements this step and finally calculates runoff and infiltration values. The

The results obtained from this modeling exercise Scenarios 1 are shown in Table 1 and Figures 7 & 8. The results reveals that the volume of annual rainfall lost as initial loss from the catchment is 88.266 ML or 0.0882 GM3.The initial loss (initial abstraction) predicted for the Scenario-1 in a year using the annual rainfall grid ranges from 415.866–1238.49. The total annual volume of surface runoff (direct runoff) is 104021 ML or 0.104 Gm3 (because of space constraint not shown in Table:1). The runoff depths ranges from 106.76-489.64 m3 as the rainfall received in the Northern part is low, the infiltration and runoff observed are also low in that region. The mean initial loss predicted by the model is 2.9296 mm, mean infiltration is 62.93 mm and the mean surface runoff is 860.79 mm. The summarized depths (mm) of annual rainfall, initial loss, infiltration and runoff based on scenario-1 and their respective percentage values are shown in Table:1. All type of Forest category has got the lowest runoff percentage of 83.94 % of rainfall received whereas the Water Bodies and river bed categories have got maximum runoff percentages (100% and 96.25% of rainfall respectively). The highest infiltrations observed are in the areas covered by forest areas and lower river bed, settlement lands. The majority of the southern parts of the catchment have minimum runoff as shows in Fig: 7.

Figure 7: Runoff Volume Depths of RINPSPE Model for Scenario:1

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The summarized depths (mm) of annual rainfall, initial loss, infiltration and runoff based on scenario-2 and their respective percentage values are shown in Table:2. All type of Forest category has got the lowest runoff percentage of 83.81 % of rainfall received whereas the Water Bodies and River bed categories have got maximum runoff percentages (100% and 98.81% of rainfall respectively). The highest infiltrations observed are in the areas covered by forest and low for dry river bed and settlement. Figure 9 shows that majority of the southern parts of the catchment have minimum runoff. Figure 8: A comparison graph for Scenario: 1

Table 1: RINSPE Model results for scenario 1: λ value as 0.2

Table 2: RINSPE Model results for scenario 2 : λ value as 0.3

The results obtained from RINSPE model exercise for Scenarios: 2 are shown in Table : 2 and Figures 9 & 10. The results reveals that volume of annual rainfall lost as initial loss from the catchment is 88.266 ML or 0.0882 Gm3. The total annual volume of surface runoff (direct runoff) is 104021 ML or 0.104021 Gm3. There is no much variation in runoff volume between scenario 1&2. The runoff depths ranges from 106.16-479.24 m3 as the rainfall received in the Northern part is low, the infiltration and runoff observed are also low in that region. The mean initial loss predicted by the model is 2.9296 mm, mean infiltration is 62.93 mm and the mean surface runoff is 860.79 mm.

Figure 9: Runoff Volume Depths of RINPSPE Model for Scenario : 2

The comaprision graph between rainfall and predicted values of infiltration and runoff for Scenario:2 from RINPSPE model as shown in Fig. 10. This graph resembles the graph drawn for Scenario:1. The results of runoff depths for fallow land, riverbed, settlements and crop land are at similar trend when compare to forest and tea gardens

Figure 10: A comparison graph for Scenario: 2

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A comparison graph (Fig:11) has been prepared to show the runoff depths obtained from both scenarios of RINSPE model. Visually there is nothing much variation of runoff depths between scenario 1 & 2 for all types of land classes covered in the entire Ton watershed. The graph clearly demonstrated that tea gardens showing highest rainfall along with highest runoff depths. Similarly, the lowest rainfall and the corresponding runoff occurred at forest areas of the watershed.

Figure 11: A comparison graph of Runoff-Depths for Scenario 1&2

With Scenario: 2 of using „λ‟ value as 0.3 shows that the initial loss from the catchment is 0.6539 mm, the cumulative infiltration is 62.92mm, whereas the surface runoff is 860.51mm. During such a rainfall event, the total volume of direct runoff predicted by the model is 10391.276 ML or 10.391 Mm3, whereas the total volume of cumulative infiltration is 1679.749 ML or 1.679 Mm3 The runoff predicted by the model is just the surface runoff or direct runoff and it does not include the contribution of interflow from the catchment that forms part of surface runoff as return flow or discharge from the groundwater which forms part of the total flow in a river. This study reveals that a slight higher runoff obtained with scenario : 1. The other parameters values are not much sensitive with both the values of „λ‟ used in Initial Abstraction (Ia) calculation used for SCS-CN equation in RINSPE Model for both scenarios. This study reveals that Initial Abstraction parameter is sensitive to get higher runoff depths with general condition of Initial Abstraction values, and sensitive to get lower Runoff depths with Indian conditions of Initial abstraction values.

VI. REFERENCES V. CONCLUSION RINSPE model could be used successfully to estimate the surface runoff, cumulative infiltration and accumulated runoff in the Ton watershed area, using Land Type data and HSG with SCS-CN method. Results reveal that the distribution of surface runoff and infiltration is fully dependent on the rainfall distribution and the nature of the land use / land cover types underlain by different types of hydrologic soil groups. With Scenario:1 considering „λ‟ value 0.2, the initial loss of the catchment is about 0.04% of the annual rainfall while surface runoff and infiltration are 92.98 %, 6.97 % of the annual rainfall received. With an average annual rainfall of 924.09mm the predicted average initial loss, infiltration and surface runoff is 0.366mm, 62.93mm and 860.79mm respectively. The total annual surface runoff volume predicted by the model for the Ton watershed is 104021.77ML or 10.402 Mm3 whereas the total volume of cumulative infiltration is 16800.203 ML or 1.680 Mm3.

[1] Abraham Thaomas, Wisemen Chingombe, 2009, „A Comprehensive investigation of the kils-Erste River catchment Water Pollution and Development of a Catchment Sustainability Plan‟, WRC Project No K5/1692, Department of Earth Sciences, University of the Western Cape, South Africa. [2] Kalpana O. Bhaware,2006, „Soil Erosion Risk Modelling and Current Erosion Damage Assessment Using Remote Sensing and GIS Technique‟ M.Tech Thesis, IIRS, Dehradun, India [3] K.Subramanya text book on “Engineering Hydrology” third edition- TATA McGraw-Hill, New Delhi publication 2011 [4] N.Omani et al, 2007. Modelling of a river basin using SWAT model and GIS. Accepted to be published in 7th International River Management Conference Kuching, Malaysia 4th International SWAT Conference, [5] NRCS Small Watershed Hydrology 2009, Win TR-55 User Guide.

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[6] Pidwirny, M. (2006). "Introduction to Surface Runoff". Fundamentals of Physical Geography, 2nd Edition. Date Viewed.13/11/08 http://www.physicalgeography.net/fundamentals/8 n.html. [7] Thomas, Abraham, 2001. A Geographic Information System Methodology For Modelling Urban Groundwater Recharge And Pollution. Ph. D. Thesis. The School of Earth Sciences, The University of Birmingham, Birmingham, United Kingdom. [8] Thomas, A. and Tellam, J.H. 2004. Development of an ArcView GIS Based Petrol Station BTEX Pollution Model for Assessing Groundwater Pollution from Small Scale Petrol Spills. Proceedings of 32nd International Geological Congress, Florence, Italy (Aug 20 - 28, 2004). Abstract Vol., Part 1, Abstract 98-16, p. 437. [9] Thomas, A. and Tellam, J.H. 2005. Development of A GIS Model For Assessing Groundwater Pollution From Small Scale Petrol Spills. Paper accepted for publishing in the Matthias Eiswirth Memorial Volume- the proceeding of the 32nd International Geological Congress held at Florence, Italy, August 20-28, 2004. [10] Tindall, James A., and Kunkel, James R. 1999. Unsaturated Zone Hydrology for Scientists and Engineers. Prentice-Hall, Inc. [11] US EPA, 1993. Natural Wetlands and Urban Stormwater: Potential Impacts and Management. Office of Wetlands, Oceans and Watersheds Wetlands Division, United States Environmental Protection Agency, Washington, D.C. http://www.epa.gov/OWOW/wetlands/stormwat.p df [12] US EPA, 1998a. Estimation of Infiltration Rate in the Vadose Zone: Compilation of Simple Mathematical Models. Volume I. EPA/600/R87/128a, February 1998. United States Environmental Protection Agency. [13] US EPA, 1998b. Estimation of Infiltration Rate in the Vadose Zone: Application of Selected Mathematical Models. Volume II. EPA/600/R87/128b, February 1998. United States Environmental Protection Agency.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

A Review of on the Spikelet Number in Rice 5

Ali Sattari1, ZA-Jahantigh Haghighi2, HO-Nohtani3, MO-Noorozi4, Ab-Nokhbeh Zaeim K-Moradi6 , Na-Mirzaie amirabad7

,

1

Phd. student of Dept. of Agronomy and Plant Breeding, Faculty of Agriculture, Zabol University 2 M.Sc. Dept. of Agronomy and Plant Breeding, Faculty of Agriculture, Zabol University,Iran 3 M.Sc. Dept. of Agronomy and Plant Breeding, Faculty of Agriculture, Zabol University,Iran 4 Tanin Keshtzar Sabz Agricultural Research, Service and Production Cooperative Company, Iran 5 M.Sc. Dept. of Agronomy and Agroecology, Faculty of Agriculture, Ferdowsi University of Mashhad,Iran 6 Phd. student of Dept. of Agronomy and Plant Physiology, Faculty of Agriculture, Zabol University, Iran 7 M.Sc. Dept. of Agronomy and Horticultural Plant Breeding, Faculty of Agriculture, Zabol University, Iran

ABSTRACT Grain yield of rice (Oryza sativa L.) has four components: panicle number, total spikelet number per panicle (TSN), grain weight and spikelet fertility. There is wide variation in TSN among cultivated rice varieties and it is one of the targets of breeding programs to improve rice yield. Many hypotheses have been proposed to explain ecophysiological process that determines spikelet number per unit area. Nitrogen is one of the most yield-limiting nutrients in crop production, and its proper management is essential for improving grain yield. Grain number is linearly correlated with total plant N content. Nitrogen fertilizer might affect CKs levels to increase rice flower numbers. To identify the loci controlling panicle architecture, QTLs for panicle traits such as number of primary or secondary branches and spikelet number per primary or secondary branch have been mapped and studied. QTLs for TSN have been identified using various segregating populations, including F2 populations, recombinant inbred lines (RILs), and doubled haploid (DH) lines. Keywords: Oryza sativa L., total spikelet number (TSN), QTLs, recombinant inbred lines (RILs)

I. INTRODUCTION Rice (Oryza sativa L.) is one of the most important crops in the world, especially in Asia. To meet the increasing demands of the booming population and urbanization of Asia, it is estimated that a 50% ncrease in rice yield is needed (Murchie et al., 2009). Therefore, finding traits that substantially increase rice yield is an urgent issue. Rice inflorescence architecture is a key agronomic factor that determines grain yield, and thus has been a major target for crop improvement. Rice inflorescence, called the panicle, consists of a rachis, primary branches, secondary branches, and spikelets. The primary branches are arranged in a spiral phyllotaxy, and spikelets are produced on both the primary and secondary branches. Understanding the genetic basis of inflorescence architecture will contribute to improving crop grain yield (Akter et al., 2014).Grain yield of rice (Oryza sativa L.) has four components: panicle number, total

spikelet number per panicle (TSN), grain weight and spikelet fertility. There is wide variation in TSN among cultivated rice varieties and it is one of the targets of breeding programs to improve rice yield. However, genetic analysis of TSN is difficult because it is a complex trait controlled by multiple genes and influenced by environmental conditions. Quantitative trait locus (QTL) analysis using DNA markers has recently made it possible to understand the genetic basis of TSN and other complex traits. QTLs for TSN have been identified using various segregating populations, including F2 populations, recombinant inbred lines (RILs), and doubled haploid (DH) lines (Hittalmani et al., 2003; Kobayashi et al., 2004; Mei et al., 2005; Xing et al., 2002; Yagi et al., 2001; Zhuang et al., 1997; Zou et al., 2005). Many hypotheses have been proposed to explain ecophysiological process that determines spikelet number per unit area. Those hypotheses may be classified into the following three types. The first is that

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the spikelet number is proportional to nitrogen (N) content of plant (product of percentage N and crop biomass per unit area) at around spikelet formation stage (Murayama, 1969; Hasegawa et al., 1994; Kobayashi and Horie, 1994; Horie et al., 1997). The second is that the spikelet number is proportional to biomass production during the period from panicle initiation to heading (Kropff et al., 1994). The third is that the final spikelet number is represented as the difference between the numbers of spikelets differentiated and degenerated; the former is proportional to the crop-N content at the late spikelet differentiation stage and the latter to crop growth rate (CGR) during the period from the late stage of spikelet differentiation to heading (Wada, 1969).

II. METHODS AND MATERIAL A. The Effect of Low Planting Density on the Spikelet Number

Whole rice plants, including panicles, leaves and stems, are harvested at the yellow ripening stage and made into whole-crop silage to feed to cattle. A salient problem with whole-crop rice silage is that some of the grain eaten by the animals is excreted in feces without being digested, causing a loss of nutrients (Koga et al., 2003; Matsuyama et al., 2005; Yamamoto et al., 2005; Shinoda et al., 2007; Shinde et al., 2008; Katoet al., 2009; Feng et al., 2011). To solve this problem, ‘Tachisuzuka’ was developed and released as the first rice cultivar with improved feed value and sugar content due to a radical decrease in grain yield (Kouno, 2011; Matsushita et al., 2011, 2012). This promising characteristic results from defective elongation of the primary branches at the basal part of the panicle axis, owing to ashort panicle 1 (sp1) mutant gene (Li et al., 2009). Tachisuzuka’ has been developed for silage use with improved feeding value due to a radical decrease in spikelets. We investigated the effect of planting density on the spikelet number in ‘Tachisuzuka’ to find out how seed yields of this cultivar can be increased by means of cultivation methods. Moreover, the spikelet number increased by 67% under the low planting density. This result implies that the efficiency of seed production of ‘Tachisuzuka’ could be improved by low planting density through an increase in spikelet number per unit area(Kei et al., 2013 ).

B. The Effect of Nitrogen Fertilizer to Increase Spikelet Number Per Panicle Nitrogen is one of the most yield-limiting nutrients in crop production, and its proper management is essential for improving grain yield. Grain number is linearly correlated with total plant N content (Makino, 2011). Nitrogen fertilizer might affect CKs levels to increase rice flower numbers. CKs regulate rice branch and flower numbers (Barazesh and McSteen, 2008). CKs oxidase/dehydrogenase (OsCKX) is an enzyme that degrades CKs and, in many plant species, is responsible for the majority of metabolic CKs inactivation (Werner et al., 2003). Reduced expression ofOsCKX2 causes CKs accumulation in inflorescence meristems and increases the number of reproductive organs and yield (Ashikari et al., 2005). The effects of nitrogen fertilizer on panicle branching may be mediated by CKs, in which accumulation in the inflorescence meristem can regulate panicle development, resulting in increased numbers of flowers and branches. Adenosine phosphateisopentenyltransferase (IPT) catalyzes the rate-limiting step of CKs biosynthesis.The results showed that OsIPTs were markedly increased, and CKs accumulated in panicle when nitrogen fertilizer was applied. CKs biosynthesis in the roots and leaves was not up-regulated by nitrogen. These results suggest that nitrogen fertilizer enhances local CKs synthesis to increase flower numbers in the panicles of rice (Chengqiang et al., 2014 ). C. OsSPS1, a Gene Increases Spikelet Number Per Panicle Analysis of an NIL carrying a chromosome segment containing QTLph1 of Kasalath revealed that OsSPS1, a gene encoding sucrose phosphate synthase (SPS), is the target gene underlying QTLph1 (Ishimaru et al., 2004). SPS catalyzes the conversion of fructose 6-phosphate and UDPglucose into sucrose 6-phosphate, and it is generally considered to be the rate-limiting enzyme in sucrose synthesis (Huber, 1983). OsSPS1 is one of the 5 isogenes encoding SPS in the rice genome. Expression analysis revealed that OsSPS1 is preferentially expressed in the source tissue, particularly in leaf blades, and it plays a dominant role in sucrose synthesis in the source leaf blades among the 5 isogenes for SPS (Okamura et al., 2011). Analysis of the distribution of dry matter revealed that a higher source-leaf SPS

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activity in NIL-SPS1 at the panicle formation stage might promote the distribution of dry matter to panicles and increase the number of secondary rachis branches. (Hashida et al., 2013). D. QTL for Spikelet Number To identify the loci controlling panicle architecture, QTLs for panicle traits such as number of primary or secondary branches and spikelet number per primary or secondary branch have been mapped and studied (Ando et al., 2008; Yamagishi et al., 2002). Several QTLs for TSN in rice have also been identified from wild relatives O. rufipogon, O. nivara and O. glumaepatula ( Brondani et al., 2002; Li et al., 2006; Moncada et al., 2001; Onishi et al., 2007; Septiningsih et al., 2003; Thomson et al., 2003; Xiao et al., 1998; Xiong et al., 1999). The QTLs detected in these studies, which were located throughout all 12 rice chromosomes, have provided useful information with which to survey the genes that govern TSN within different populations. Additionally, five QTLs for TSN—QSpp8 on chromosome 8, qSPP1 on chromosome 1, qSSP2 on chromosome 2, qSPP3 on chromosome 3 and qSPP7on chromosome 7 have been mapped as single Mendelian factors (Zhang et al., 2006, 2009). Fine maps of three QTLs for grain number per panicle and TSN—SPP1 on chromosome 1 (Liu et al., 2009) and two QTLs (gpa7 and qSPP7) on chromosome 7 (Tian et al., 2006; Xing et al., 2008)—have been constructed. Furthermore, three QTLs for increasing grain number (Gn1a on chromosome 1, Ghd7 on chromosome 7 andWFP on chromosome 8) have been cloned (Ashikari et al., 2005; Miura et al., 2010; Xue et al., 2008). E. Importance Of IR64 Variety Since the 1960s, IRRI-bred rice varieties have been distributed worldwide and used by both plant breeders and farmers. IR64, which was released in 1985, had been widely accepted as a high-quality rice variety in many countries (Khush, 1987). Because of the wide adaptability of IR64, breeding materials with an IR64 genetic background, such as DH lines, RILs and thousands of mutant lines, have been developed for research and improvement of rice varieties (Guiderdoni et al., 1992; Wu et al., 2005). In the late

1980s, a breeding program to develop a new plant type (NPT) of rice was launched at IRRI with the goal of increasing yield potential under tropical environments. Unlike IR64, the NPT varieties have several agronomic traits inherited from tropical japonica-type varieties: low tiller number, low number of unproductive tillers, large panicle, thick culm, lodging resistance and large, dark green flag leaves (Khush , 1995). Thus, the NPT varieties were chosen for experiments designed to improve the yield potential of IR64.

III. REFERENCES [1] Akter MB, Piao R, Kim B, Lee Y, Koh E, Koh H-J. 2014. Fine mapping and candidate gene analysis of a new mutant gene for panicle apical abortion in rice. Euphytica 197:387–398. [2] Ando T, Yamamoto T, Shimizu T, Ma XF, Shomura A, Takeuchi Y, Lin SY, Yano M. 2008. Genetic dissection and pyramiding of quantitative traits for panicle architecture by using chromosomal segment substitution lines in rice. Theor. Appl. Genet. 116: 881–890 [3] Ashikari M, Sakakibara H, Lin S, Yamamoto T, Takashi T, Nishimura A, Angeles ER, Qian Q, Kitano H, Matsuoka M. 2005. Cytokinin oxidase regulates rice grain production. Science 309, 741–745 [4] Barazesh S, McSteen P. 2008. Hormonal control of grass inflorescence development. Trends Plant Sci 13:656–662 [5] Brondani C, Rangel PHN, Brondani RPV, Ferreira ME. 2002. QTL mapping and introgression of yield-related traits from Oryza glumaepatula to cultivated rice (Oryza sativa) using microsatellite markers. Theor. Appl. Genet. 104: 1192–1203 [6] Chengqiang D, Juan Y, Lin C,Shaohua W,Yanfeng D. 2014. Nitrogen fertilizer increases spikelet number per panicle by enhancing cytokinin synthesis in rice. Plant Cell Rep.33:363–371 [7] Feng J, Matsuzaki M, Suzuki Het al., 2011. Fermentation quality, digestibility and unhulled rice excretion of forage paddy rice silage prepared by different harvester types.Grassl Sci57:23–27. [8] Guiderdoni E, Galinato E, Luistro J, Vergara G. 1992. Anther culture of tropical japonica × indica hybrids of rice (Oryza sativa L.). Euphytica 62: 219–224

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[9] Hasegawa T, Koroda Y, Seligman NG, Horie T. 1994. Response of spikelet number to plant nitrogen concentration and dry weight in paddy rice. Agron. J. 86, 673–676. [10] Hittalmani S, Huang N, Courtois B, Venuprasad R, Shashidhar HE, Zhuang JY, Zheng KL, Liu GF, Wang GC, Sidhu JS. 2003. Identification of QTL for growth- and grain yield-related traits in rice across nine locations of Asia. Theor. Appl. Genet. 107: 679–690 [11] Horie T, Ohnishi M, Angus JF, Lewin LG, Tsukaguchi T, Matano T. 1997. Physiological characteristics of high-yielding rice inferred from cross-location experiments. Field Crops Res. 52, 55–67. [12] Kato T, Shirota K, Shinde S, Bansho H. 2009. Effect of hullsplitting in rice on the digestibility of grain in whole crop silage. In:Bulletin 24, Faculty of Biology-Oriented Science and Technology, Kinki University, Higashiosaka, Osaka, Japan, 1–5. [13] Kei M, Shuichi I, Osamu I, Takuro I,Hiroshi F,Hajime W,Yoshihiko T. 2013. Effect of low planting density on the spikelet number in ‘Tachisuzuka’, a rice (Oryza sativaL.) cultivar with a short panicle for whole crop silage use. Japanese Society of Grassland Science. [14] Khush GS. 1987. Rice breeding: past, present and future. J. Genet. 66: 195–216 [15] Khush GS. 1995. Breaking the yield frontier of rice. GeoJournal 35: 329–332 [16] Kobayashi K, Horie T. 1994. The effect of plant nitrogen condition during reproductive stage on the differentiation of spikelets and rachisbranches in rice. Jpn. J. Crop Sci. 63 (2), 193–199 (in Japanese, with English Abstract). [17] Kobayashi S, Fukuta Y, Yagi T, Sato T, Osaki M, Khush GS. 2004. Identification and characterization of quantitative trait loci affecting spikelet number per panicle in rice (Oryza sativa L.). Field Crops Res.89: 253–262. [18] Koga T, Okubo Y, Kubota K, Karasawa T, Kishimoto T, Tanaka A. 2003. Digestibility of paddy or ears of a rice plant fed to dry or lactating cows. In: Bulletin 30, Nagano Animal Industry Experiment Station, Shiojiri, Nagano, Japan, 1–5. (In Japanese.). [19] Kouno S. 2011. Feeding value and supply for lactating cattle of the high sugar content forage rice

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Blast Disease in Rice : A Review 1

Farshad Karamian , AM- Heydari Nezhad2, Ab- Nokhbeh Zaeim3,K-Moradi4, AH-Drakhshan5 1

Phd. student of Dept. of Agronomy and Plant Pathology, Faculty of Agriculture, Zabol University, Iran Phd. student of Dept. of Agronomy and Plant Pathology, Faculty of Agriculture, Zabol University,Iran3 M.Sc. Dept. of Agronomy and Agroecology, Faculty of Agriculture, Ferdowsi University of Mashhad,Iran 4 Phd. student of Dept. of Agronomy and Plant Physiology, Faculty of Agriculture, Zabol University, Iran 5 Phd. student of Zabol University and Institute jahad daneshgahi of Kashmar. Iran 2

ABSTRACT Rice blast caused by the fungal pathogen, Magnaporthe grisea (anamorph: Pyricularia grisea) limits rice yield in all major rice-growing regions of the world and the rice blast fungus, Magnaporthe oryzae, is responsible for the most serious disease of rice and is a continuing threat to ensuring global food security. The fungus has also, however, emerged as a model experimental organism for understanding plant infection processes by pathogenic fungi. This hemibiotrophic pathogen penetrates in epidermal cells and causes lesions on leaves, leaf collar, culm, culm nodes and panicle neck causing failure of seed filling. After successful penetration, the invasive hyphae grow rapidly in the host cells and caused blast lesions. in 5 to 7 days, the pathogen produces numerous conidia from the lesions and initiates a new infection cycle. A number of signal transduction pathways are implicated in appressorium-mediated plant infection and have been characterised as a potential means of developing new chemical intervention strategies for disease control. With the advent of new technologies like marker-assisted selection, molecular mapping, mapbased cloning, marker-assisted backcrossing and allele mining, breeders have identified more than 100 Pi loci and 350 QTL in rice genome responsible for blast disease. Keywords: Rice Blast, Magnaporthe Oryzae, Lesions, Marker-Assisted Selection

I. INTRODUCTION Magnoporthe oryzae Heb.(anamorph: Pyricularia oryzae Cav. Or Pyricularia grisea Sacc.) causes the rice blast disease (Wu et al., 2006). M. oryzae is a hemibiotrophic, ascomycetous fungus that has been reported to infect more than 50 grass species (Pennisi 2010). Rice blast disease is one of the most devastating of all cereal diseases worldwide and causes harvest losses of 10–30 % of the global rice yield annually (Talbot 2003) and economic losses over $70 billion of dollar (Scheuermann 2012). M. oryzae is listed as number one of the ten most important fungal pathogens in molecular biology (Dean et al., 2012). In the first phase of infection, the conidia form an injection apparatus (appressorium), which penetrates the leaf cuticle (Wilson and Talbot 2009). Invasive hyphae then rapidly grow in the rice leaf and stem. The fungal

biomass soon reaches over 30% and the rice plant succumbs to necrosis ( Wilson and Talbot 2009). This hemibiotrophic pathogen penetrates in epidermal cells and causes lesions on leaves, leaf collar, culm, culm nodes and panicle neck causing failure of seed filling. Blast-resistant rice cultivars (cvs) have normally a short field life due to the plasticity of the M. oryzae genome, that is able to evolve new race by mutation of the avirulence (Avr) genes, causing a breakdown of the deployed plant resistance conditioned by R genes (Dean et al., 2005; Valent and Khang 2010). Many studies indicated that the genetic control of blast resistance is complex and involves both major and minor resistance genes with complementary or additive effects, as well as environmental interactions (Wang et al., 1994; Wu et al., 2005; Li et al., 2007, 2008a, b; He et al., 1989; Bonman 1992). Thus, the discovery and use of novel R genes and development of broad-spectrum resistant varieties are

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urgent goals in breeding for blast resistance in rice. Since the idea of indirect selection using genetic markers was first reported by Sax (Sax et al., 1923) over 80 years ago, and particularly in the last few decades, new technologies have emerged that allow breeders to more easily select changes at the DNA level. Much of the progress to date has centered on marker-assisted backcrossing or the pyramiding of genes against rice blast (Torres, 2010). Molecular markers are essential for mapping genes of interest, marker-assisted breeding, and cloning genes using mapping-based cloning strategies (Hayashi et al., 2004).

II. METHODS AND MATERIAL A. Plant Penetration The heterothallic ascomycete Magnaporthe oryzae, is the most destructive disease of cultivated rice worldwide and can lead to severe losses of annual rice yield (Valent et al., 1991; Talbot, 2003). Under normal conditions, the fungus uses a highly specialized infection structure appressorium generated from a conidium for plant penetration (Howard et al., 1991; Jong et al., 1997). After successful penetration, the invasive hyphae grow rapidly in the host cells and caused blast lesions. In 5 to 7 days, the pathogen produces numerous conidia from the lesions and initiates a new infection cycle. B. Regulation of gene expression at the level of transcription Regulation of gene expression at the level of transcription controls many crucial biological processes. A number of different factors, including transcription factors, are essential for the process of transcription. Transcription factors can recognize DNA in a sequencespecific manner and modulate the frequency of initiation of transcription upon binding to specific sites in the promoter of target genes. The transcription factors can be activators, repressors, or both usually display a modular structure named the DNA-binding domain (Pabo and Sauer 1992). In M. oryzae, numerous transcription factors were identified and characterized to be important for proper regulation of infection related morphogenesis (Li and Xu, 2012; Kim et al., 2009). Many transcription factors, including MoCrz1, MoAp1, MoAtf1, MoHac1, MoBzip10, MoSwi6 and MoMsn2 were reported to be involved in hyphal growth, asexual

development, stress response, infectious growth and virulence by controlling the expression levels of a series of target genes (Zhang et al., 2009; Tang et al., 2014). C. Effect of azoxystrobin and kresoxim-methyl on rice blast During the 1980s, organophosphorus fungicides such as kitazin (EBP), kitazin P (IBP) and isoprothiolane (FJone) with different chemical structures but similar mode of action were widely used (Katagiri and Uesugi, 1977; Zhang et al., 2009). The strobilurin-based (QoI; Quinone outside inhibitors) fungicides have been reported to be very effective in controlling rice blast in the USA (Groth, 2006). The specific target of QoI fungicides is the quinol-oxidising (Qo) site of the mitochondrial enzyme cytochrome b (Kim et al., 2003), as these chemicals block electron transport at the Qo site, thereby inhibiting fungal respiration (Bartlett et al., 2000). Azoxystrobin and kresoxim-methyl, belonging to QoI fungicides, are relatively new for controlling rice blast in China. The results of field experiments also suggested that both azoxystrobin and kresoxim-methyl at 187.5 g.a.i. ha−1gave over 73% control efficacy in both sites, exhibiting excellent activity against rice blast. Taken together,azoxystrobin and kresoxim-methyl could be a good substitute for Carbendazim (MBC) or IBP for controlling rice blast in China, but should be carefully used as they were both at-risk (Chen et al., 2015). D. Methionine Biosynthesis Some plant amino acids such as cysteine, methionine, tryptophan, histidine and arginine are only present in trace amounts in the leaf apoplast and are likely not available for fungal nutrition ( Fernandes et al., 2014; Solomon et al., 2003). Infectious hyphae are expected to synthesize these amino acids from abundant apoplastic amino-acid such as glutamate or aspartate. Genetic studies in M.oryzae support this hypothesis for different amino-acids including methionine (Marie et al., 2015). E. Allele Mining Strategies for Blast Resistance Allele mining approaches have been intended to identify superior alleles of rice blast resistance genes such as Pita (Yang et al., 2007; Huang et al., 2008; Wang et al., 2008; Ramkumar et al., 2010), Pikh (Ramkumar et al., 2010), Pi54 (Kumari et al., 2013), and Pi-2 (Hittalmani

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et al., 2013) from different cultivated rice varieties and wild species. The blast resistance genes Pi9, Pi2 and Pizttend to be alleles from different rice resources while physically on the same gene locus on rice chromosome 6, but their level of resistance spectra can be quite different (Zhou et al., 2006; Zhu et al., 2012). In general, there are two approaches available for allele mining and/or identification of sequence polymorphisms for a given gene in a naturally developing population: (i) modified TILLING (Targeting Induced Local Lesions in Genomes) (Comai et al., 2004), called Eco-TILLING and (ii): Re-sequencing (Huang et al., 2009) or sequencing based allele mining. F. Current advance methods for the identification of blast resistance genes in rice

After the discovery of molecular markers, the selection of target traits becomes easier and many new cultivars have been developed accordingly. Nowadays, breeders are focusing on marker-assisted selection instead of using conventional breeding because it reduces the time for phenotypic selection, saves input costs, brings more reliability to select a desired trait with no influence of environmental factors (Koide et al., 2010). Many DNA markers are directly linked with Pi genes in rice including simple sequence repeats (SSRs), amplified fragment length polymorphisms (AFLPs), and cleaved amplified polymorphic sequences (CAPS), random amplified polymorphic DNAs (RAPDs), restriction fragment length polymorphisms (RFLPs), singlenucleotide polymorphisms (SNPs) and small insertions/deletions (InDels). SSRs and CAPS are PCRbased markers and require only a small amount of DNA for genotyping. These markers are very precise and cost effective and can be applied for the selection of plants containing blast resistance genes in rice at an early stage. Small In Dels and SNPs markers are found in abundance and dispersed widely in the rice genome (Yu et al., 2002). On the basis of information on these markers, (Hayashi and Yoshida, 2006), developed nine PCRbased markers linked with blast resistance in rice. These markers help in finding a gene within the desired target genome regions. Microsatellite markers, also called SSRs, are widely used for screening the blast-resistant and susceptible varieties. The difference between two varieties is based on polymorphism (Miah and rafii 2013). With the advent of new technologies like marker-

assisted selection, molecular mapping, map-based cloning, marker-assisted backcrossing and allele mining, breeders have identified more than 100 Pi loci nd 350 QTL in rice genome responsible for blast disease. These Pi genes and QTLs can be intro grassed into a blast susceptible cultivar through marker-assisted backcross breeding. These molecular techniques provide timesaving, environment friendly and labour-cost-saving ways to control blast disease.

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[46] Wu SC, Halley JE, Luttig C, Fernekes LM, GutiérrezSanchez G, Darvill AG, Albersheim P. 2006. Identification of an endo-β-1,4-Dxylanase from Magnaporthe grisea by gene knockout analysis, urification, and heterologous expression. Applied and environmental microbiology 72: 986–993. [47] Yang MZ, Cheng ZQ, Chen SN, Qian J, Xu LL and Huang XQ. 2007. A rice blast-resistance genetic resource from wild rice in Yunnan, China. Journal of Plant Physiology and Molecular Biology 33: 589-595. [48] Yang S, Gu T, Pan C, Feng Z, Ding J, Hang Y, Chen JQ and Tian D. 2008. Genetic variation of NBS-LRR class resistance genes in rice lines. Theoretical and Applied Genetics. 116: 165-177. [49] Yu J, Hu S, Wang J,Wong JKS, Li S, Liu B, Zhang B. 2002. A draft sequence of the rice genome (Oryza sativa L. ssp. indica), Science 296: 79–92. [50] Zhang C, Huang X, Wang J, Zhou M. 2009. Resistance development in rice blast disease caused byMagnaporthe griseato tricyclazole.Pesticide Biochemistry and Physiology,94,43–47 [51] Zhang H, Zhao Q, Liu K, Zhang Z, Wang Y, Zheng X. 2009. MgCRZ1, a transcription factor of Magnaporthe grisea, controls growth, development and is involved in full virulence. FEMS Microbiology Letters. 293: 160–9 [52] Zhou B, Qu S, Liu G, Dolan M, Sakai H, Lu G, Bellizzi M and Wang GL. 2006. The eight amino-acid differences within three leucine-rich repeats between Pi2 and Piz-t resistance proteins determine the resistance specificity to Magnaporthe grisea. Molecular plant microbe interactions 19: 1216-1228. [53] Zhu X, Chen S, Yang J, Zhou S, Zeng L, Han J, Su J, Wang L and Pan Q. 2012. The identification of Pi50 (t), a new member of the rice blast resistance Pi2/Pi9 multigene family. Theoretical and Applied Genetics 124: 1295-1304.

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

A Review for Rice Sheath Blight Disease Abdolreza Nokhbeh Zaeim1, Na-Mirzaie Amirabad2, Ah-Drakhshan3, Mo-Noorozi4, K-Moradi5 1

M.Sc. Dept. of Agronomy and Agroecology, Faculty of Agriculture, Ferdowsi University of Mashhad, Iran M.Sc. Dept. of Agronomy and Horticultural Plant Breeding, Faculty of Agriculture, Zabol University,Iran 3 Phd. student of Zabol University and Institute jahad daneshgahi of Kashmar. Iran 4 Tanin Keshtzar Sabz Agricultural Research, Service and Production Cooperative Company, Iran 5 Phd. student of Dept. of Agronomy and Plant Physiology, Faculty of Agriculture, Zabol University, Iran

2

ABSTRACT Rice is an important food grain and is a staple food for majority of the world’s population. However, biotic stresses such as diseases have impeded rice cultivation both in the tropics and subtropics. Of them, Rice sheath blight (ShB), caused by Rhizoctonia solani, leads to severe yield losses in many rice production areas worldwide. little progress has been made in rice breeding for sheath blight resistance. None of the commercially cultivated rice varieties have sufficient level of field resistance, and the disease is presently being managed by chemical pesticides.Within the strobilurins group, azoxystrobin fungicide is widely used as it works effectively against ShB pathogen infestation. The survival and inoculums potential of the R. solani is directly related with severity and incidence of disease. Wild relatives of cultivated rice are a potential source of novel genes for insect and disease resistance, as well as tolerance to several abiotic stresses and a source of yield and yield enhancing traits. Keywords : Rice, Rhizoctonia Solani, Sheath Blight, Chemical Pesticides.

I. INTRODUCTION R. solanican infect seed to fully mature plant, causing moderate to significant yield losses depending on the plant part affected. Visible plant disease symptoms include formation of lesions, plant lodging, and presence of empty grains. Large lesions formed on infected sheaths of lower rice leaves may lead to softness of the stem thereby initiating stem lodging (Wu et al., 2012). Rhizoctonia solaniis a common soilborne pathogenic fungus that has worldwide implications on an extensive range of agricultural plants (Anderson, 1982). In rice, it is responsible for causing sheath blight disease, rendering significant declines in crop quality and yield (Su’udi et al., 2013).Wild relatives of cultivated rice are a potential source of novel genes for insect and disease resistance, as well as tolerance to several abiotic stresses and a source of yield and yield enhancing traits (Brar and Singh, 2011; Shakiba and Eizenga, 2014). It has been reported that polygalacturonase inhibiting proteins

can inhibit the degradation of the plant cell wall by polygalacturonases from pathogens. Activity assay confirmed the inhibitory activity of OsPGIP1 against the PGase from Rhizoctonia solani. In addition, the location of OsPGIP1 was determined by subcellular localization ( Rui et al., 2015). Damage increased substantially in major rice growing regions following introduction of high-yielding semi-dwarf rice cultivars, and the application of excessive nitrogen fertilizers to rice fields. Sheath blight management is difficult due to the low inherent level of resistance among cultivated or wild rice, and broad host range and high genetic diversity of the pathogen (Taheri et al., 2007). Owing to the limitations of conventional breeding and the use of environmentally hazardous chemical pesticides, alternative strategies are being tried globally to enhance protection of crops against invading pathogens (Maruthasalam et al., 2007). Genetic engineering may be proved as a promising alternative strategy for the management of economically important plant disease like rice sheath blight.

IJSRST151547 | Received: 16 December 2015 | Accepted: 31 December 2015 | November-December 2015 [(1)5: 233-237]

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II. METHODS AND MATERIAL A. Mode of Survival of Pathogen The survival and inoculums potential of the R. solani is directly related with severity and incidence of disease. Sclerotia are the most important source of inoculums (Allison, 1951). Li Shi Dong (2004) reported that 60.9% sclerotia could survive after 265 days of being buried in natural sandy loam under field conditions in Beijing, while colonized rice straw debris (0.5-10 cm long) could not yield the fungus on medium plates after 88 days of being buried under same conditions. Singh and Singh (2008) reported that the infected leaf pieces incubated at 10 and 28°C also showed a steady reduction in fungus survival with an incubation period from an initial 100% to 53.3% and 63.3% respectively after a period of 5 months. B. Host Range Kozaka (1965), Tsai (1974) observed that rice fungus infected 20 species which are from 11 families and observed that the sclerotia from diseased tissue of weed hosts produced typical symptoms of sheath blight on paddy plants. Singh and Saksena (1980) found that aerial strain causing banded blight disease in bajra infected 22 plants species of both crop and wild plants belonging to 6 different families. Kannaiyan and Prasad (1980) have listed 30 monocot weed species as host of Thanatephorus cucumeries (Rhizoctnia solani).Goswami . (2010) reported that isolate SYL-13 possessed narrow host range and low avirulent while DIN-8 and GAZ-18 had wide host range and considered as virulent isolate of Rhizoctonia solani. C. Chemical Control Within the strobilurins group, azoxystrobin fungicide is widely used as it works effectively against ShB pathogen infestation (Groth and Bond, 2006 ). The fungicide is a derivative of β-methoxyacrylate and was the first registered fungicide from this class of chemistry (Anonymous, 1996). It is sold as Quadris 2.08 SC (Syngenta, Raleigh, NC). Azoxystrobin is considered one of the best fungicides in the U.S. for sheath blight control (Grichar et al., 2004). The mode of action of azoxystrobin is to inhibit electron transport and kill the fungal pathogen Use of fungicide rate and composition

is based on intensity of disease and the type of cultivars (susceptible/medium susceptible/ moderately resistant) used. Benefits from fungicide control include lower disease incidence, likely reduction of inoculum, and improved grain and milling yields (Groth, 2008; Groth, 1996). D. Biological Control

Rhizosphere-isolated, free living soil bacteria with proven plant beneficial properties are known as plant growth- promoting rhizobacteria (PGPR) (Kloepper et al., 1978). Besides, PGPR role in increasing plant or root growth, they directly influence increasedN uptake, phosphate solubilization, phytohormone synthesis, and production of iron chelating siderophores (Lalande et al., 1989; Bowen and Rovira, 1999 ). Some PGPR are used commercially to enhance plant growth and health. Seed treatment of rice with PGPR resulted in increased root and shoot length of seedlings (Kumar et al., 2009). Secondary metabolites of rice sheath blight pathogen A series of metabolites from several types of R. solani have been identified. They included fatty acids (i.e., 9(Z)-octadecenoic acid and 9,12-octadecadienoic acid) (Aliferis and Jabaji, 2010a), steroids (i.e., ergosterol) (Ma et al., 2004; Aliferis and Jabaji, 2010a), phenolics (i.e., m-hydroxyphenylacetic aicd, mmethoxyphenylacetic acid, p-hydroxybenzoic acid, methyl p-hydroxybenzoate) (Mandavaetal, 1980; Adachi and Inagaki, 1988), alkaloids (i.e., Nb-acetyltryptamine) (Pedrasetal, 2005), cyclopeptides (i.e., cyclo (S-Pro-SLeu), cyclo (S-Pro-S-Ile), cyclo (S-Pro-S-Val)) (Pedras et al., 2005), saccharides (i.e., RS-toxin) (Vidhyasekaran et al., 1997; Sriram et al., 2000), and glycoprotein (Velazhahan and Vidhyasekaran, 2000). Some metabolites were screened to have phytotoxic activity (i.e., m-hydroxyphenylacetic aicd, mmethoxyphenylacetic acid, p-hydroxybenzoic acid) (Mandava et al., 1980; Adachi and Inagaki, 1988), and elicitation effect on the activities of phenylalanine ammonia-lyase (PAL) and 4-coumarate: CoA ligase (4CL) in suspension-cultured rice cells (i.e., glycoprotein) (Velazhahan and Vidhyasekaran, 2000). The aim of this investigation was to further search for bioactive metabolites from rice sheath blight pathogen R. solaniin order to provide supporting data for reveal their physiological and ecological functions.

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E. Role of OsWRKY Transcription Factors in rice Disease Resistance WRKY transcription factors in plants regulate diverse biological functions including abiotic and biotic stress responses, growth and development, embryogenesis and many other physiological processes.Indica and japonica genotypes of rice were identified to have 111 and 113 WRKY genes respectively in their genomes. Reports on the involvement of some of the WRKY genes in rice disease resistance covering the major diseases like blast and bacterial blight indicate the possibilities of further exploring these genes for the production of disease resistant varieties (John et al., 2015). F. PR Genes Enhance Resistance Against Sheath Blight Several groups have reported that the introduction of single PR genes such as PR-3 chitinase (Datta et al., 2000, 2001; Lin et al.1995), PR-5(thaumatin-like protein) (Datta et al., 1999) provides resistance against rice sheath blight pathogen. The expression of differentPRgenes in combination such as rice chitinase (CHI11) and tobaccob-1,3-glucanase(gluc) (Sridevi et al., 2008), CHI11and thaumatin-like protein (Kalpana et al., 2006), maize ribosomeinactivating gene MOD1and rice basic chitinase gene RCH10(Kim et al., 2003a) and barleychitinase, and barley b-1,3-glucanasegenes (Jach et al., 1995) that are driven by different constitutive promoters, conferred a higher level of sheath blight resistance than any single PRgene. Moreover, constitutive expression of these genes may provide a metabolic burden and increased energy cost to the plants. Therefore, combined tissue-specific overexpression of PR genes in rice may deliver a novel strategy to control yield losses caused by sheath blight pathogen. G. OsPGIP1 in rice Sheath Blight Resistance Cell wall is the first shield for the defense of plant cells against the attack of pathogens (De Lorenzo et al., 2001). During the early stage of pathogen invasion, phytopathogenic fungi produce a series of hydrolytic enzymes to degrade the plant cell wall, such as polygalacturonases (PGases), xylanases and galucanases (Alghisi and Favaron, 1995). In order to resist the invasion of pathogens, the plant also secretes some

enzymes such as chitinases and polygalacturonase inhibiting proteins (PGIPs) to prevent the degradation of the plant cell wall by pathogens (Shanmugam, 2005; Vorwerk et al., 2004). PGIP can also maintain the elicitation activity of oligosaccharides for a longer time, prolonging the defense response of the plant (Mishra et al., 2012). H. Predicting Potential Epidemics of Rice Sheath Blight Using a Rice Disease Epidemiology Model, EPIRICE EPIRICE is a generic epidemiological model that can be parameterized to address any specific rice disease (Savary et al., 2012). It was recently developed as a general model framework for fungal, viral, and bacterial diseases at different levels of hierarchy in a crop canopy (leaves, sheaths, entire plants) depending on the nature of the disease. Thus, its structure was designed to be as simple as possible, involving a few state variables and a limited number of core parameters and weather variables. Savary et al. (2012) developed EPIRICE to evaluate the potential importance of plant diseases in rice and their intensity and distribution at a global scale, at which very limited actual field data on disease epidemics exist across different locations and years.

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[18] Jach G, Go ¨rnhardt B, Mundy J, Logemann J, Pinsdorf E, Leah R,Schell J, Maas C. 1995. Enhanced quantitative resistance against fungal disease by combinatorial expression of different barley antifungal proteins in transgenic tobacco. Plant J 8:97–109 [19] John J. Subramanian B. 2015. Role ofOsWRKY transcription factors in rice disease resistance. Trop. plant pathol.40:355–361. [20] Kalpana K, Maruthasalam S, Rajesh T, Poovannan K, Kumar KK,Kokiladevi E, Raja JA, Sudhakar D, Velazhahan R, Samiyappan R. 2006. Engineering sheath blight resistance in elite indica rice cultivars using genes encoding defense proteins. Plant Sci 170:203–215. [21] Kannaiyan S and Prasad NN. 1980. Dicot weed hosts of Rhizoctonia solani Kuhn. Agri. Res. J. Kerala. 18:125-127 [22] Kloepper JW, Schroth MN. 1978. Plant growth promoting rhizobacteria on radish.: Proceedings of the Fourth Conference Plant Pathogenic Bacteria. INRA, Angers, France. [23] Kozaka T. 1961. Ecological studies on sheath blight of rice of rice caused Pellicularia sasakii (Shirai) and its chemical control. Chugoko agric. Res. 20:1-133 [24] Kumar KVK, Reddy MS, Kloepper JW, Lawrence KS, Groth DE. 2009. Sheath blight disease of rice (Oryza sativa L.) -An overview. Biosciences, Biotechnology Research Asia 6: 465-480. [25] Lalande R, Bissonnette N, Coutlee D, Autoun H. 1989. Identification of rhizobacteria from maize and determination of their plant-growth promoting potential. Plant and Soil 115: 7-11. [26] Li D. 2004. Population dynamics and survival of Rhizoctonia solani AG-1 in the field soil under ricewheat rotation. Agricultural sciences of China. 3:448-455 [27] Lin W, Anuratha C, Datta K, Potrykus I, Muthukrishnan S, Datta SK. 1995. Genetic engineering of rice for resistance to sheath blight.Nat Biotechnol 13:686–691. [28] Ma Y, Li Y, Liu JY, Song YC, Tan RX. 2004. AntiHelicobacter pylori metabolites from Rhizoctonia sp. Cy064, an endophytic fungus in Cynodon dactylon. Fitoterapia, 75, 451–456. [29] Mandava NB, Orellana RG, Warthen JD, Worley JF, Dutky SR, Finegold H, Weathington BC.

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1980. Phytotoxins in Rhizoctonia solani: isolation and biological activity of m-hydroxy and mmethoxyphenylacetic acids. Journal of Agricultural and Food Chemistry, 28, 71–75. Maruthasalam S, Kalpana K, Kumar KK, Loganathan M, Poovannan K, Raja JAJ (2007) Pyramiding transgenic resistance in elite indica rice cultivars against the sheath blight and bacterial blight. Plant Cell Rep 26:791–804. Mishra AK, Sharma K, Misra RS. 2012. Elicitor recognition, signal transduction and induced resistance in plants. J Plant Interact 7:95–120 Pedras M S, Yu Y, Liu J, Tandron-Moya Y A. 2005. Metabolites produced by the phytopathogenic fungus Rhizoctonia solani: isolation, chemical structure determination, syntheses and bioactivity. Zeitschrift für Naturforschung C (Journal of Biosciences), 60, 717–722. Rui Wang Liaoxun Lu Xuebiao Pan Zongliang Hu•Fei Ling Yan Yan Yemao Liu Yongjun Lin.2015. Functional analysis of OsPGIP1in rice sheath blight resistance. Plant Mol Biol ,87:181– 191 Savary S, Nelson A, Willocquet L, Pangga I, Aunario J. 2012. Modeling and mapping potential epidemics of rice diseases globally. Crop Prot. 34, 6–17. Shakiba E, Eizenga GC. 2014. Unraveling the secrets of rice wild species. In: Yan WG, Bao J (eds.) Rice—germplasm,genetics and improvement, doi:10.5772/58393 Shanmugam V. 2005. Role of extracytoplasmic leucine rich repeat proteins in plant defence mechanisms. Microbiol Res 160:83–94 Singh PK and Singh AK. 2008. Effect of temperature and soil texture on the survival ability of rice sheath blight pathogen (Rhizoctonia solani). Flora and Fauna (Jhansi). 14:55-56. Singh SB and Saksena HK. 1980. A new sheath and leaf blight of bajra.Indian Phytopath.33:127129 Sridevi G, Parameswari C, Sabapathi N, Raghupathy V, Veluthambi K. 2008. Combined expression of chitinase andb-1, 3-glucanase genes in indica rice (Oryza sativaL.) enhances resistance against Rhizoctonia solani. Plant Sci 175:283–290

[40] Sriram S, Raguchander T, Babu S, Nandakumar R, Shanmugam V, Vidhyasekaran P, Balasubramanian P, Samiyappan R. 2000. Inactivation of phytotoxin produced by the rice sheath blight pathogen Rhizoctonia solani. Canadian Journal of Microbiology, 46, 520–524. [41] Su’udi M, Park J-M, Kang W-R, Hwang D-J, Kim S, Ahn I-P. 2013. Quantification of rice sheath blight progression caused by Rhizoctonia solani. J Microbiol 51:380–388 [42] Taheri P, Gnanamanickam S, Ho¨fte M. 2007. Characterization, genetic structure, and pathogenicity ofRhizoctoniaspp. associated with rice sheath diseases in India. Phytopathology 97:373–383 [43] Tsai WH. 1974. Assessment of yield losses due to rice sheath blight at different inoculation stages. Journal of Taiwan Agricultural Research. 23: 188194 [44] Velazhahan R, Vidhyasekaran P. 2000. Isolation of an elicitor from Rhizoctonia solani, the rice sheath blight pathogen which activates phenylpropanoid metabolism in suspensioncultured rice cells. Zeitschrift fur Pflanzenkrankheiten und Pflanzenschutz, 107, 135–144. [45] Vidhyasekaran P, Ponmalar T R, Samiyappan R, Velazhahan R, Vimala R, Ramanthan A, Paranidharan V, Muthukrishnan S. 1997. Hostspecific toxin production by Rhizoctonia solani, the rice sheath blight pathogen. Phytopathology, 87, 1258–1263. [46] Vorwerk S, Somerville S, Somerville C. 2004. The role of plant cell wall polysaccharide composition in disease resistance. Trends Plant Sci 9:203–209 [47] Wu W, Huang J, Cui K, Nie L, Wang Q. 2012. Sheath blight reduces stem breaking resistance and increases lodging susceptibility of rice plants. Field Crops Research 128: 101-108

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Temperature Dependence of Polarizability in Sodium Potassium Tantalate Mixed Ceramic System Manish Uniyal, H.K.Semwal, S.C.Bhatt Department of Physics, H. N. B. Garhwal University, Srinagar, Garhwal, Uttarakhand, India

ABSTRACT Using a quadratic anharmonic model Hamiltonian and using double time temperature dependent Green’s function method and Dyson’s equation treatment, expression for polarizability in the frequency response for mixed perovskite type ferroelectrics have been obtained. Using the experimentally observed temperature dependent dielectic constant, loss tangent, soft mode frequency, width for Na 1-xKxTaO3 (x=0,0.2,0.4,0.5 and 0.6) the polarizability has been calculated for these samples at 10kHz Keywords : Polarizability, ferroelectrics, Model Hamiltonian

I. INTRODUCTION The study of polarizability factor for Na1-xKxTaO3 ceramics is important because it was realized that the large nonlinear polarizability of ferroelectrics makes them one of the most promising classes of materials for electro-optical and optical parametric devices. A self-consistent of the soft mode frequencies was first given by Boccara and Sarma[1] by employing at the onset a renormalized phonon basis. Their formal treatment represented (the lowest order of) what is now called the self-consistent phonon approximation (SPA)[2]. This approximation has been very successful in describing the anharmonic rare-gas solids, including the quantum crystals of solid helium. Numerical calculations have shown that the SPA gives a first – order transition for a model ferroelectric containing only fourth order anharmonic interactions [3]. This result is surprising because the phenomenological Landau (Devonshire) theory predicts the transition to be second order when only terms up to fourth order in the polarization are included [4-6].

II. METHODS AND MATERIAL To illustrate the essential features of the selfconsistent phonon approximation (SPA)[2] and to understand why a first-order transition is obtained, it is instructive to consider a simple model with a single degree of freedom, H=1/2Pl2(l)+½o2lQl2(l)1/2llV(ll`)Ql(l)Ql`(l`)+1/2Г1Q4l(l) ….. (1) Here Ql is a localized normal mode coordinate describing the ion displacements in cell l, and P(l)is the canonical conjugate momentum [Ql, Pl’] = iδll’

………(2)

We set Ql = Q0 + Ul, where the thermal average Q0 = ‹ Ql› measures the distortion from the high temperature structure, while Ul describes the fluctuations about the average value. In the SPA the free energy F= ‹ H›-TS is obtained by using a harmonic trial density matrix2. The distortion Q0 and the effective harmonic force constants are determined

IJSRST151550 | Received: 29 December 2015 | Accepted: 04 January2016 | November-December 2015 [(1)5: 238-241]

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by minimizing the free energy. For the Hamiltonian given by Eq. (7) the extremum condition, ∂F/∂Q0 = 0 takes the form

Δ = 3kT/ωd2 - Δ0(Ω /ωd)tan-1(ωd/ Ω) = 3kT/ωd2 - 3kT/ωd2 (Ω/ωd)tan-1(ωd/Ω) = 3kT/ωd2 [1- (Ω /ωd)tan-1(ωd/ Ω)] ,…(10)

Q0[Ω02 – v (0) + г1Q02 +3 г1Δ]=0 , ……..(3) Where v (0) =ll V(ll`), and Δ is defined below. The effective force constants determine the self-consistent normal mode frequency. For this model it is given by

where ωd=α qD, qD being the Debye wave vector. ΔT denotes the contribution to Δ due to long wavelength fluctuations. For Q0 ≠ 0, Eq. (9 ) may be written

ωq2 = Ω 2 + v (0)- v(q) ~ Ω 2 + α2q2 , ……..(4) where Ω2= Ω02 - v (0) + 3 г1 Q02+3 г1Δ ,………..(5) Or, in the distorted phase, using equation (9) Ω2 = 2 г1 Q02 ………….(6)

a(T-Tc)+ г1Q02 -3 г1ΔT =0 ,……. (11) where a= 9г1KB/ωd2 , Tc= a-1[v(0) - Ω02] …. (12) and v(0)= Tca+ Ω02 ….(13)

The correlation function Δ = ‹ UiUj › is determined with the help of the fluctuation dissipation theorem6 Δ= N-1 q ½ ωq-1 coth 1/2β ωq. ,……….(7) for simplicity we consider the limit ωq/kT «1, Δ may be approximated by the Ornstein- Zernike form Δ=kTN-1q (Ω2 + α2q2 )-1

…………..(8)

On substituting Eq.6, 7 and 13 in Eq.5,we get the expression as Q02 = 9 KB/ωd2 [Tc - {1- Ω /ωd tan-1ωd/ Ω }T] ….(14)

Evaluating the summation in the Debyeapproximation, we obtain Δ = Δ0 – Δt

Because ΔT is linear in Ω as Ω →0, it follows from Eqs. (6) and (11) that the transition is first order. However it is important that the linear term giving rise to the first order transition is entirely due to the long wavelength fluctuations.

On substituting the experimental results of soft mode frequency (Ω), natural frequency of the system (ω d) for Na1-xKxTaO3 (x=0,0.2,0.4,0.5 and 0.6) system , we get the variation of polarizability factor (Q02) with temperature is given in table 1 and fig.1 at 10Khz. Experimental results for Na1-xKxTaO3 system has been obtained by S.Glinsek et.al.[7]. The result has been obtained by using our previously experimental results[8-13] and the theoretical data by earlier workers[4,6,14-16].

……………(9)

where Δ0 = 3kT/ωd2 and ΔT = Δ0(Ω/ωd)tan-1(ωd/Ω), On substituting in equation (9), we get

Table-1: Variation of Polarizability factor with temperature for Na 1-xKxTaO3 system at 10 kHz Temp(k)

-47

NaTaO3(x10 )

Na0.8K0.2TaO3 -47 (x10 )

423 443 463 483 503 523

8.293 8.245 8.191 8.142 8.093 8.038

8.69 8.645 8.601 8.522 8.501 8.498

Na0.6K0.4TaO3 -47 (x10 ) 8.866 8.766 8.697 8.655 8.635 8.581

543

7.99

8.47

8.542

Na0.5K0.5TaO3 -47 (x10 ) 9.668 9.588 9.561 9.443 9.357 9.297

Na0.4K0.6TaO3 -47 (x10 ) 10.558 10.508 10.466 10.333 10.245 10.198

9.262

10.101

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563 583 603 623

7.941 7.885 7.781 7.606

8.402 8.35 8.258 8.105

8.467 8.388 8.301 8.214

9.196 9.16 9.048 8.997

10.057 9.945 9.807 9.721

643 663 683 703 723 743

7.626 7.541 7.457 7.197 7.402 7.331

7.821 7.705 7.601 8.018 7.721 7.688

8.143 7.939 8.226 8.17 7.964 7.907

8.662 9.09 8.95 8.86 8.667 8.589

9.535 9.82 9.675 9.502 9.485 9.207

763

7.244

7.587

7.815

8.488

9.106

Variation of polarizability factor w ith tem perature for Na 1-xKxTaO3 system at 10 kHz NaTaO3 Na0.8K0.2TaO3 Na0.6K0.4TaO3 Na0.5K0.5TaO3 Na0.4K0.6TaO3

12

Qo2 x 10-47 J sec2

11.5 11 10.5 10 9.5 9 8.5 8 7.5 7 420

470

520

570

620

670

720

770

820

o

Tem perature ( C)

Figure 1

III. RESULT AND DISCUSSION Polarizability factor (Q02) is calculated by using the formula obtained by Pytte [14]. The temperature dependence of polarizability factor at 10 kHz frequency for Na1-xKxTaO3 has been shown in figure 1. For Na1-xKxTaO3 [x=0, 0.2, 0.4, 0.5 and 0.6] transition temperature are found at 703oC, 683 oC, 663 o C, 643 oC and 640 oC respectively. From these figures it is observed that polarizability factor tends to minimum up to the transition temperature thereafter increases with the increasing temperature and hence showing anomaly at transition temperature. The

nature of polarizability factor is found to be in good agreement with the results obtained theoretically by Pytte [15].

IV.

ACKNOWLEDGEMENT

The authors are thankful to Material Science Research Centre (MSRC), IIT Madras for laboratory facilities for preparation and characterization of the samples. Special thanks to Prof. B.S.Semwal- Ex.Head Department of Physics, HNB Garhwal University for valuable suggestions and encouragement.

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V. REFERENCES [1] Boccara N and Sarma G., Physics (Long Is. City,N.Y.) 1(1980) 219. [2] Werthamer N B, Phys.Rev.B 1(1980)572. [3] Gillis N S and Koehler T R, Phys.Rev. B4 (1980) 3971. [4] Landau L D and Lifshitz E M, Statistical Physics I Addison- Wesley, Reading mass,(1958) Sect.135. [5] Devonshire A F, Advan.Phys.3 (1980) 85. [6] Brout R, Phase Transition (Benjamin, New York, 1965). [7] Glinsek S, Malic B et.al., Applied Physics Letters, vol.94, issue 17 (2009) id.172905. [8] Pytte E ,Physical Review Letters, Vol. 28, No.4 (1980) 895 [9] Kuldeep Singh, Manish Uniyal, S.C.Bhatt and B.S.Semwal, Srilankan Journal of Physics 1(2001)13 [10] S. C. Bhatt, H. K. Semwal, Manish Uniyal and B. S. Semwal, J. Acoustic Soc. Of India 33(2005)264 [11] Manish Uniyal, K. Singh, Sunil Bhatt ,S. C. Bhatt, S. C. Bhatt, R. P. Pant, D. K. Suri and B. S. Semwal, Indian Journal of Pure & Applied Physics Vol.41(2003)305 [12] Manish Uniyal, S. C. Bhatt, R. Bhandari, M.S. Ramchandra Rao, R. P. Pant and B. S. Semwal Indian Journal of Pure & Applied Physics Vol.42(2004)341 [13] S. C. Bhatt, K. Singh, Manish Uniyal & B. S. Semwal, Indian Journal of Pure & Applied Physics Vol.45(2007)613 [14] Manish Uniyal & S.C.Bhatt, , Indian Journal of Pure & Applied Physics Vol.49(2011)350 [15] Pytte E., Physical Review B, Vol.5(1971) no.9. [16] Manish Uniyal & S.C.Bhatt, Indian Journal of Pure & Applied Physics Vol.52(2014)391-394

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© 2015 IJSRST | Volume 1 | Issue 5 | Print ISSN: 2395-6011 | Online ISSN: 2395-602X Themed Section: Science and Technology

Farmer’s perception of sustainable alternatives to the use of chemical fertilizers to enhance crop yield in Bauchi state Nigeria Gizaki, L. J.1, Alege, A. A.1 and Iwuchukwu, J. C.2 1

School of Undergraduate studies, College of Education Azare, Bauchi state, Nigeria

2

Department of Agricultural Extension, University of Nigeria, Nsukka, Nigeria

ABSTRACT The study was undertaken to examine the perception of farmers on the sustainable alternatives to the use of chemical fertilizers to enhance crop yield in Bauchi state. Data were collected from 900 crop farmers spread across the three agricultural zones through the use of structured interview schedule. Multistage random sampling technique was used in selecting respondents. Data were analyzed using descriptive statistical techniques and correlation analysis. The findings showed that majority of the respondents were male (92%), aged less than 50 years (76%) and earn less that N500, 000 per annum (68%). Also, majority (84%) of the respondents were not aware of the detrimental effects of chemical fertilizers. The correlation between awareness and practice of sustainable alternatives such as planting of nitrogen fixing legumes (0.474**), use of crop rotation (-0.309**) and conservation tillage -0.149**) were positive. While leaving of crop residues (-0.011), fallowing (-0.131) and permaculture (0.005) had negative values. It is therefore recommended that Bauchi State Agricultural Development Programme should within the limited resources available to it step up sensitization and enlightenment of farmers in the state on the harmful effects of chemical fertilizers and the need to replace them with sustainable alternatives. It can achieve this through local radio and television programs, demonstration and village enlightenment campaigns. Keywords: Farmers, Perception, Chemical Fertilizer, Bauchi State

I. INTRODUCTION Inorganic fertilizers and other chemicals used to enhance crop production have been instrumental to increasing crop yield and performance worldwide beyond any iota of doubt. However, it has become evident that they have many negative consequences and have become beyond the reach of ordinary farmers. For instance, Usman and Dosumu (2007) report that, fertilizers and pesticides contribute greatly to enhancing soil fertility they are also major sources of farmland pollution and contamination by heavy metals. Usman and Dosumu contend that these metals pose a dual threat, directly through their toxic effect on crops and soil organisms and indirectly posing an adverse health risk to human beings and animals who consume the contaminated products.

Environmental pollution is another significant problem posed by using chemical fertilizers. But while most of the focus is placed on polluting industries as the culprits, use of chemical fertilizers and other chemicals used in modern food production are also to blame. Meldora (2013) reports that, far from being life sustaining, our modern chemical-dependent farming methods strips soil of nutrients, destroys critical soil microbes, contributes to desertification and climate change and saturates farmlands with toxic pesticides, herbicides and fertilizers that then migrates into ground water, rivers, lakes and oceans. Repeated applications may result in a toxic buildup of chemicals such as arsenic, cadmium, and uranium in the soil. These toxic chemicals can eventually make their way into your fruits and vegetables. Long-term use of chemical fertilizer can change the soil pH, upset beneficial microbial

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ecosystems, increase pests, and even contribute to the release of greenhouse gases (Day, 2008). Deepali and Gangwar (2000) reported that, increasing use of chemical fertilizers in agriculture makes a country self-dependent in food production but it deteriorates the environment and causes harmful impacts on living beings. Due to insufficient uptake of these fertilizers by plants results, fertilizers reaches into water bodies through rain water, causes eutrophication in water bodies and affect living beings including growth inhabiting microorganism. Groundwater contamination has been linked to gastric cancer, goiter, birth malformations, and hypertension; testicular cancer and stomach cancer. Excessive air and water-borne nitrogen from fertilizers may cause respiratory ailments, cardiac disease, and several cancers, as well as can inhibit crop growth, increase allergenic pollen production, and potentially affect the dynamics of several vector-borne diseases, including West Nile virus, malaria, and cholera. One popular fertilizer, urea, produces ammonia emanation, contributes to acid rain, groundwater contamination and ozone depletion due to release of nitrous oxide by denitrification process. With its increased use and projections of future use, this problem may increase several fold in the coming decades. The excess uses of chemical fertilizers in agriculture are costly and also have various adverse effects on soils i.e. depletes water holding capacity, soil fertility and disparity in soil nutrients. According to Food Programme, (2014), alternatives to synthetic fertilizer use include compost (decomposed organic matter), animal manure, seaweed, and worm castings. Each of these products can help boost soil health through the introduction and maintenance of healthy soil organisms and micronutrients. Organic fertilizers increase soil biodiversity and have been shown to increase the uptake of nutrients by plants. There is also evidence that use of organic fertilizers improves the nutrient value of the plants themselves. Sustainable crop production is a way of growing or raising food in an ecologically and ethically responsible manner. This includes adhering to agricultural and food production practices that do not harm the environment, that provide fair treatment to workers, and that support and sustain local communities. Sustainable crop production is in contrast to industrial crop production,

which generally relies upon mono-cropping (growing only one crop in a large area of land), intensive application of chemical fertilizers, heavy use of pesticides, and other inputs that are damaging to the environment, to communities, and to farm workers. In addition, sustainable crop production practices can lead to higher yields over time, with less need for expensive and environmentally damaging inputs.

II. METHODS AND MATERIAL A. Problem Statement Despite the harmful effects of chemical fertilizers, farmers in Bauchi state (as in other parts of Nigeria) rely heavily on the use of chemical fertilizers to increase crop yield because soil nutrients have been depleted due to incessant continuous tillage. This overdependence is still in vogue despite the availability of many better options such as use of bio-fertilizers, fallowing, crop rotation, zero tillage, organic farming and permaculture. The increased use of chemical fertilizers in agricultural production will make the state independent in food production but it is however detrimental to the environment and has harmful effects on living things. It is in view of these problems that this study seeks to investigate whether farmers in the state are aware of viable and sustainable alternatives to the use of chemical fertilizers to increase crop yield? If yes, what are the challenges inhibiting their adoption and how can the identified constraints be overcome? B. Purpose of the Study The main purpose of this study is to identify sustainable alternatives to the use of chemical fertilizers to enhance crop yield in Bauchi state. The study will specifically seek to: i. Determine whether farmers in Bauchi state are aware of these alternatives ii. Identify the constraints of using each identified alternative and iii. Suggest how these constraints can be ameliorated.

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C. Hypotheses 1. Ho: Farmers in Bauchi state are not aware of sustainable alternatives to the use of chemical fertilizers to enhance crop yield. 2. Ho: Farmers in Bauchi state are not aware of the harmful effects of using chemical fertilizers to enhance crop yield. D. Significance of the Study This research work will be very useful to farmers who have become handicapped in procuring chemical fertilizers for crop production and create awareness on the avalanche of sustainable alternatives that can be successfully adopted. It will also assist extension practitioners especially the Bauchi State Agricultural Development Programme (BSADP) to understand and disseminate technologies that will ease the constant demand by farmers for viable and sustainable alternatives to the use of chemical fertilizers to enhance crop yield in Bauchi state. Similarly, results of this study can be applied or replicated in other states of the Nigerian federation where similar problems exist. Administrators and policy makers will also benefit from the research work by guiding them to formulate policies aimed at encouraging sustainable alternatives to the use of chemical fertilizers for crop production and reducing the huge amounts expended on buying it which does not even reach the ordinary farmers. Finally, future researches into the issue will find the study a useful reference.

F. Research Design Descriptive survey research design was adopted for the purpose of this study. Descriptive survey describes what is going on or what exists (Maduekwe and Akinnagbe, 2014). A descriptive study is one in which information is collected without changing the environment (nothing is manipulated). Sometimes these are referred to as “correlational” or “observational” studies. Kumar and Ranjit (2005), define a descriptive study as “Any study that is not truly experimental.” In human research, a descriptive study can provide information about the naturally occurring behaviors, attitudes or other characteristics of a particular group of people. Descriptive studies are also conducted to demonstrate associations or relationships between things in the world around us. Descriptive studies can involve a one-time interaction with groups of people (Cross-sectional study) or a study might follow individuals over time (Longitudinal study). Descriptive studies, in which the researcher interacts with the participant, may involve surveys or interviews to collect the necessary information. Descriptive studies in which the researcher does not interact with the participant include observational studies of people in an environment and studies involving data collection using existing records. This research design was suitable for the research topic which is aimed at describing alternatives to the use of chemical fertilizers for crop production among farmers in Bauchi state. The study also ascertained whether the farmers are aware of and use these better and sustainable alternatives.

E. Methodology - Study Area

G. Sample and sampling procedure

This study investigated whether farmers are aware of and use sustainable alternatives to chemical fertilizers in order to enhance crop yield in Bauchi state Nigeria. The state is located between latitudes 90 3” and 120 3” North and longitudes 80 50” and 110 East. According to the National Population Commission Census (2006), the area has a population of 4,653,066 people and a land area of 49,119 Km2 representing about 5.3% of Nigeria’s total mass. The population of the state is however, predominantly rural and agrarian. About eighty percent of the people in most of the Local Government Areas are still dependent on farming comprising of 1,500,000 farm families (BSADP, 2012).

Multi-stage sampling method was employed. Three LGAs were purposively selected from the three agricultural zones of the state to give a total of nine LGAs used. Out of this, five villages were randomly selected from each LGA. Similarly, simple random sampling technique was used to select 20 crop farmers from each of the five villages selected. This gave a sample size of 900 crop farmers’ for the study as shown in Table 1 below.

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Table 1: Sampling procedure S/No 1.

Agricultural zones Western zone

2.

Central zone

3.

Northern zone

Total

3

Sampled LGAS Toro Dass Bogoro Ningi Ganjuwa Darazo Jama’are Itas/Gadau Katagum 9

Sampled Villages 5 5 5 5 5 5 5 5 5 45

Sampled Farmers 20 20 20 20 20 20 20 20 20 900

H. Data Collection Data for the study were collected using structured interview schedule. The variables measured include information on the socio-economic characteristics of the respondents, awareness and level of adoption of the sustainable alternatives to the use of chemical fertilizers and their perceived knowledge on the effects of using chemical fertilizers. Respondents level of awareness and adoption was determined by “yes” or “no” options. While their perception on the effects of the identified alternatives was determined by response options of major effects, minor effects, and no effect, respectively. The researchers employed the services of trained research assistants to collect the primary data from the crop farmers through the use of structured interview schedule. I. Validation of the Instrument Validation is the amount of systematic or built-errors in measurement (Nor land, 1990). Validity is established using a panel of experts and a field test. Validity test of the research instrument is necessary to ascertain if the research instrument will be able to measure what it is designed to measure. To ensure that the research instrument was valid, the developed instrument was given to experts in agricultural extension and rural sociology and senior lecturers in the department of agricultural education for proper scrutiny and comments. Based on their comments, the research instrument was modified before being used for the data collection. J. Reliability of the Instrument Reliability indicates the accuracy or precision of the measuring instrument (Nor land-Tilburg, 1990). Test-

retest method of reliability was used to determine the instrument before final application. Three copies of the research instruments were used to collect information from the respondents. After an interval of two weeks the same respondents originally served with the instruments were interviewed again. The first and second test scores for all the variables considered in the study were then subjected to correlation analysis at 5%. A correlation coefficient will be obtained and considered if satisfactory enough to conclude that the instrument is reliable. The reliability coefficient (alpha) can range from 0 to 1, with 0 representing an instrument with full error and 1 representing total absence of error. A reliability coefficient (alpha) of 70 or higher will then be considered acceptable reliability and can be used for the study. A reliability coefficient of 85 was obtained which was enough to accept reliability of the instrument used in collecting information from the respondents. K. Data Analysis Descriptive statistical technique of frequency count and percentage was used to analyze objectives 1 and 2. Furthermore, Pearson product moment correlation coefficient was used to test the hypotheses. The sample correlation coefficient, denoted r, ranges between -1 and +1 and quantifies the direction and strength of the linear association between the two variables. For example, a correlation of r = 0.9 suggests a strong, positive association between two variables, whereas a correlation of r = -0.2 suggest a weak, negative association. A correlation close to zero suggests no linear association between two continuous variables.

III. RESULT AND DISCUSSION A. Sex of Respondents Table 1: Distribution of Respondents according to Sex Sex Male Female Total

Frequency 825 75 900

Percentage 92 8 100

Table 1 show that 92% of the respondents are male, while 8% are female. This confirms that majority of crop farmers in Bauchi state are male. This is not

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unconnected with the predominant cultural and religious beliefs in the area; men dominant the spheres of vocations that require a high amount of energy located outside the home. Usman and Dosunmu (2007) and other related studies carried out in Bauchi state also agree that majority of the crop producers in the area are male. Oluwasola (2015); Alam et al, (2013) and Fabiyi et al, (2007) all confirm that men dominate farming activities in Northeastern Nigeria of which Bauchi is a part. B. Age of Respondents Table 2: Distribution of Respondents according to Age Age 25 – 34 years 35 – 44 years 45 – 54 years 55 – 64 years 65 years and above Total

Frequency 176 302 210 192 20

Percentage 19.5 33.5 23 21 3

900

100

Table 2 shows that 53% of the respondents fall between the ages of 25 to 44 years old, 44% range between 45 to 64 years old, while 3% are above 65 years of age. It can be deducted that the number of active farmers in Bauchi state decline with increase in age; which is a normal trend. It can also be deducted from this result that the most active age group regarding crop production in the study area range between 25 to 44 year olds. This finding is also corroborated by Oluwasola (2015); Alam et al, (2013) and Fabiyi et al, (2007). C. Marital Status of Respondents Table 3: Distribution of Respondents according to Marital Status Marital Status Married Single Total

Frequency

Percentage

893 07 900

99.2 0.8 100

as soon as they can maintain a family. None of the respondents is below 25 years old and as such this result is also normal and in accordance with social structure of the area. D. Annual Income of Respondents Table 4: Distribution of Respondents according to Annual Income Annual Frequency Percentage Income (N) 100,000 – 362 40 250,000 251,000 – 256 28 500,000 501,000 – 172 19 750,000 751,000 – 91 10 1,000,000 Above 19 3 1,000,000 Total 900 100 Table 4 indicates that 68% of the respondents earn less than Five Hundred Thousand Naira (N500, 000) annually, 29% of the respondents earn between N500, 000 and N750, 000 annually, while 3% earn above One Million Naira (N1,000,000) annually. From this result majority of the respondents and by extension crop farmers in Bauchi state can be classified as poor. An earning of N250, 000 per annum which translates to an average of N685 per day which is just a little above $3. Okuneye et al (2004) report that poverty in Nigeria is concentrated among the agrarian populace living in rural areas; they contend that low resource or resource poor farmers characterized by a preponderance of small farm units, rain dependent minimum inputs usage and poor yield dominate the Nigerian agricultural sector. The authors concluded that the incidence of poverty is highest among households in which the head is engaged in agriculture as the main source income and recommend that accelerated agricultural growth as the panacea to alleviating poverty in the country.

E. Farming Experience of Respondents Table 3 shows that 99.2% of the respondents are married, while 0.8% are single. The cultural norms and values of Table 5: Distribution of Respondents according to the study area require that their inhabitants get married Farming Experience

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Experienc e Less than 10 years 11 – 20 years 21 – 30 years 30 years and above Total

Frequenc y 45

Percentag e 5

425

47

307

34

123

16

900

100

G. Awareness of Respondents on the Detriments of Chemical Fertilizers Table 7: Distribution according to Awareness of the Detriments of Chemical Fertilizers Awarenes s Aware Not Aware Total

Frequenc y 144 756 900

Percentag e 16 84 100

Table 5 shows that 52% of the respondents have been farming for less than 20 years, 345 of the respondents have been farming for between 21 to 30 years, while 16% Table 7 shows that 84% of the respondents are not of the farmers have been farming for more than 30 years. aware that chemical or inorganic fertilizers are harmful This result indicates that a major cross-section of the or detrimental to their crop production practices. 16% of respondents have the prerequisite experience in farming the respondents are aware of the harmful effects of to enable them give informed responses to the questions inorganic fertilizers such as the fact that it contaminates ground water, poisonous to human beings, crops, soil posed to them regarding this research work. and pollutes the environment. 98% of the respondents are not aware that inorganic fertilizers are made from F. Type of Crops Produced by Respondents nonrenewable raw materials and therefore unsustainable. Table 6: Distribution of Respondents according to the This leads us to accept the null hypothesis that farmers Type of Crops they produce in Bauchi state are not aware of the harmful effects of using chemical fertilizers to enhance crop yield. Type of Frequency Percentage Crop H. Awareness of Respondents on Sustainable Cereals 410 45.5 Alternatives to Chemical Fertilizers Legumes 258 29.0 Roots and 176 19.5 Table 8: Distribution according to Awareness on Tubers Sustainable Alternatives to Chemical Fertilizers Vegetables 56 6.0 Total 900 100 Awarenes Frequenc Percentag s y e Table 6 shows that 45.5 percent of the respondents Aware 782 87 mostly cultivate cereals such as maize, millet and guinea Not Aware 118 13 corn, 29% of the respondents mostly cultivate legumes Total 900 100 such as cowpea, groundnuts, soybeans, bambara nuts and sesame. 19.5% of the respondents cultivate mostly root and tuber crops such as cassava, sweet potatoes and cocoyam, while 6% of the respondents mostly cultivate vegetable crops such as tomatoes, pepper, onions and lettuce especially during the dry season. It was also discovered that all the farmers practice mixed cropping and the wealthy one also have fruit orchards. The fruit crops that thrive in the study area include mango, cashew, guava and watermelon.

Table 8 indicates that 87% of the respondents are aware of sustainable alternatives to the use of chemical fertilizers such as planting of leguminous cover crops, mulching, leaving of crop residues on the farm, use of bio fertilizers such as animal manure and ash, fallowing, composting, crop rotation, conservation tillage and permaculture. 13% of the respondents are not aware of such alternatives and rely completely on inorganic fertilizers to enhance their crop yield. This leads us to

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reject the null hypothesis that farmers in Bauchi state are not aware of sustainable alternatives to the use of chemical fertilizers to enhance crop yield. I. Practice of Sustainable Alternatives to Chemical Fertilizers by Respondents Table 9: Distribution according to Practice of Sustainable Alternatives to Chemical Fertilizers Practice Practice Do Not Practice Total

Frequency 352 548

Percentage 39 61

900

100

Table 9 shows that 61% of the respondents do not practice the sustainable alternatives to use of inorganic fertilizers to enhance crop yield enumerated in 4.8. 39% of the respondents do practice some of these sustainable alternatives, especially the use of animal manure, ash and garbage. They identified the following constraints as the major reasons why they cannot effectively utilize these alternatives to enhance crop yield – inadequate knowledge of how to use these alternatives as a consequence of inadequate agricultural extension coverage, lack of capital, land tenure system, unavailability of and expensive inputs. They particularly identified permaculture as totally new to them. J. Perception of Farmers on Use of Sustainable Alternatives to Chemical Fertilizers Table 10: Distribution according to Perception on Use of Sustainable Alternatives to Chemical Fertilizers Perceptio n Positive Negative Total

Frequenc y 882 18 900

Percentag e 98 2 100

Table 10 indicates that 98% of the respondents perceive that using sustainable alternatives to chemical fertilizers is a good development while 2% believe the opposite is true. According to Kiratu et al (2014) perception relates to the interpretation of data that is from one’s environs. Thus the perception that farmers have towards a technology is determined to a great deal by the data they

have gathered about it through experience, learning or training. The exposure that a farmer has on a technology therefore determines his/her perception towards it and consequently the adoption or use of that technology. In a similar study carried out by Nnamonu and Ali (2013) on the perception of farmers on agrochemical use and organic farming in Benue State of Nigeria; 56% of the respondents had a positive perception towards organic farming while 38% of the respondents had a negative perception. 6% of the respondents were undecided. Idku et al (2015) also reported that extension agents in Cross River State of Nigeria had an overwhelming positive perception towards the use of bio-fertilizers, crop rotation and planting of leguminous cover crops as viable to the use of inorganic fertilizers that have become expensive, unavailable and insufficient. K. Correlation Analysis between Awareness of Sustainable Alternatives and their Practice by Respondents Table 11: Correlation between Awareness of Sustainable Alternatives and their Practice Variable Coefficient of correlation Planting of Nitrogen fixing 0.474** legumes Leaving of crop residues -0.011 Using bio-fertilizers 0.234** Crop rotation -0.309** Conservation tillage -0.149** Fallowing -0.131 Permaculture -0.005 ** Correlation is significant at the 0.01 Level (2-tailed) Table 11 indicates that the correlation between awareness and practice of sustainable alternatives such as planting of nitrogen fixing legumes, use of biofertilizers, crop rotation and conservation tillage are positive, while the correlation between awareness and practice of sustainable alternatives such as leaving of crop residues, fallowing and permaculture are negative. This result implies that if constraints preventing the practice of sustainable alternatives to the use of chemical fertilizers to enhance crop yield such as inadequate knowledge of how to use these alternatives as a consequence of inadequate agricultural extension coverage, lack of capital, land tenure system,

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unavailability of and expensive inputs are removed; farmers in Bauchi state are willing to put them into practice.

IV.

SUMMARY, CONCLUSION AND RECOMMENDATIONS

Summary This research work investigated the perception of farmers towards the use of sustainable alternatives to replace chemical fertilizers used to enhance crop yield in Bauchi state. It also investigated whether farmers are aware of and use these sustainable alternatives to enhance crop yield in Bauchi state Nigeria. Descriptive survey research design was adopted for the purpose of this study while multi-stage sampling method was employed in selecting the sample. Questionnaires and interviews were used to collect data from the three LGAs purposively selected from the three agricultural zones in the state to give a total of nine LGAs used. Out of this, five villages were randomly selected from each LGA. Similarly, simple random sampling technique was used to select 20 crop farmers from each of five villages selected. This gave a sample size of 900 crop farmers. It was discovered that 98% of the respondents perceive that using sustainable alternatives to chemical fertilizers is a good development while 2% believe the opposite is true. 84% of the respondents are not aware that chemical or inorganic fertilizers are harmful or detrimental to their crop production practices. 16% of the respondents are aware of the harmful effects of inorganic fertilizers such as the fact that it contaminates ground water, poisonous to human beings, their crops, and soil and pollutes the environment. 98% of the respondents are not aware that inorganic fertilizers are made from nonrenewable raw materials and therefore unsustainable. This led to the acceptance of the null hypothesis that farmers in Bauchi state are not aware of the harmful effects of using chemical fertilizers to enhance crop yield. Similarly, the results show that 87% of the respondents are aware of sustainable alternatives to the use of chemical fertilizers such as planting of leguminous cover crops, mulching, leaving of crop residues on the farm, use of bio fertilizers such as animal manure and ash, fallowing, composting, crop rotation, conservation tillage and permaculture. 13% of the respondents are not aware of such alternatives and rely completely on inorganic

fertilizers to enhance their crop yield. This leads us to reject the null hypothesis that farmers in Bauchi state are not aware of sustainable alternatives to the use of chemical fertilizers to enhance crop yield. Finally, the correlation between awareness and practice of sustainable alternatives such as planting of nitrogen fixing legumes, use of bio-fertilizers, crop rotation and conservation tillage are positive, while the correlation between awareness and practice of sustainable alternatives such as leaving of crop residues, fallowing and permaculture are negative. This result implies that if constraints preventing the practice of sustainable alternatives to the use of chemical fertilizers to enhance crop yield such as inadequate knowledge of how to use these alternatives as a consequence of inadequate agricultural extension coverage, lack of capital, land tenure system, unavailability of and expensive inputs are removed; farmers in Bauchi state are willing to put them into practice. Conclusion It can be concluded from the findings of this research that although crop farmers in Bauchi state are aware of sustainable alternatives to the use of chemical fertilizers to enhance crop production, they are constrained to using them because of inadequate land, funds and knowledge. Inadequate extension coverage and unavailability of essential inputs also contribute to low adoption of these alternatives. The study also proved useful in sensitizing farmers on the need to start adopting these sustainable alternatives since the raw materials for manufacturing chemical fertilizers are fast dwindling and thereby unsustainable. This is coupled with the fact that inorganic fertilizers are detrimental to human and environmental health. Recommendations In view of the findings of this research work, it is hereby recommended that: 1. The Bauchi State Government should as a matter of urgency look into the issue of revamping the activities of the Bauchi State Agricultural Development Project (BSADP) which is the apex extension agency in the state. It should place special focus on adequate funding and staffing of extension

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agents to cover all the nooks and crannies of the state. 2. The BSADP should within the limited resources available to it step up sensitization and enlightenment of farmers in the state on the harmful effects of chemical fertilizers and the need to replace them with sustainable alternatives. It can achieve this through local radio and television programs, demonstration and village enlightenment campaigns. 3. Researchers are enjoined to look further into cost effective means of empowering farmers to adopt these sustainable alternatives and increasing their output in an environmentally friendly and sustainable manner.

[7]

V. REFERENCES

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Alam, M.K. Aboki, E. Gidado, E.H. and Buba, D.D. (2013). Economic analysis of cotton production in selected local government areas of Taraba State, Nigeria. Journal of Agricultural Science 4(1) pp. 27-31 Bauchi state Agricultural Development Programme (BSADP) (2012): 2000 Bauchi farmers get free sesame seeds. Blueprint (2012). Available at http://printing.com/new/2012/07/2000-bau. 17/06/2013 Day, J. (2008). The debate over organic vs chemical fertilizers. Retrieved 7th July 2015 from http://www.todayshomeowner.com/debate-overorganic-chemical-fertilizers/ Deepali, A. and Gangwar, K. (2000). Biofertilizers: An eco-friendly way to replace chemical fertilizers. Retrieved 8th July 2015 from www.krishisewa.com/images/biofert.html Deepanjan, M. and Navindu, J. (2000). Nitrate pollution of groundwater and associated human health disorders. Retrieved 7th July 2015 Sustainable Baby Steps http://www.sustainablebabysteps.com/effects-ofchemical-fertilizers.html Fabiyi, E.F. Danladi, B.B. Akande, K.E. and Mahmood, Y. (2007). Role of women in agricultural development and their constraints: A case study of Billiri local government area, Gombe State, Nigeria. Pakistan Journal of Nutrition 6(6) pp. 676-680

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Food Program (2014). Sustainable Crop Production. Retrieved 19th October 2015 from http://www.sustainabletable.org/249/sustainablecrop-production Idku, O.F. Aboh, C.L. Ijogu, B.J. and Wonah, C.O. (2015). Extension Agent’s perception of constraints to fertilizer use by rural farmers in Cross Rivers State Nigeria. International Journal of Research in Agriculture and Food Sciences 2(10) pp. 11-24 Kiratu, N.M. Ngigi, M. and Mshenga, P.M. (2014). Perception of smallholder farmers towards the Kilimo Plus Subsidy Program in Kenya. Journal of Agriculture and Veterinary Science 6(6) pp. 28-32 Maduekwe, M.C. and Akinnagbe, O.M. (2014). Identifying and defining research problems in agricultural extension. A guide to research in agricultural extension. AESON Meldora, D. (2013). How Organic Farming could release us from the curse of fertilizer. Retrieved 7th July 2015 from http://articles.mercola.com/sites/articles/archive/ 2013/07/02/fertilizer.aspx Nnamonu, L.A. and Ali, A.E. (2013). Perception of agrochemical use and organic farming in Makurdi, Benue State. International Journal of Environmental Protection 3(8) pp. 48-52 Norland-Tilburg, E.V. (1990). Controlling errors in evaluation instruments. Journal of Extension 28(2). pp. 11-23 available at www.joe.org/joe/1990summer/tt2/html Okuneye, P.A. Fabusoro, E. Adebayo, K. and Ayinde, I.A. (2004). The Nigerian agriculture and poverty incidence: The need for private sector empowerment. Being a paper presented at the Farm Management Association of Nigeria Conference, held in Abuja, Nigeria. Oluwasola, O. (2015). Vegetable production, livelihood diversification and employment generation in Oyo State, Nigeria. Journal of Agricultural Science 7(8) pp. 165-174 Usman, O.A.S. and Dosumu, O.O. (2007). Cadmium analysis in fertilizers and groundwater samples in Dass Local Government Area of Bauchi State, Nigeria. Centerpoint (Science Edition)14(1&2) pgs. 208-213

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