international conference on sustainable agriculture ...

3rd INTERNATIONAL CONFERENCE ON SUSTAINABLE AGRICULTURE AND ENVIRONMENT

PROCEEDINGS BOOK

Editor Mithat DIREK

ISBN: 978-605-9831-95-6

Konya, TURKEY – December 2016

3rd INTERNATIONAL CONFERENCE ON SUSTAINABLE AGRICULTURE AND ENVIRONMENT © COPYRIGHT All right for the papers in this book are reserved to the individual authors. Papers are published here unedited, as submitted by their authors. The conference does not necessarily endorse their contents. No part of this publication may be reproduced in any form or by any means, electronically, mechanically, by photocopying, recording or other wish without the prior permission of the copying owners.

PROCEEDINGS BOOK Copyright Reserved by Organizing Committee of 3rd International Conference on Sustainable Agriculture and Environment (3rd ICSAE) Editor

Mithat DIREK

ISBN: 978-605-9831-95-6

Rampalı İş Merkezi Kat:1 No: 121 Tel.&Fax: (0.332) 351 92 85 • Meram / KONYA e-mail: [email protected] Baskı ve Cilt: DİZGİ OFSET Matbaacılar Sit. 10451. Sk. No:4 Tel: 0332 342 00 05 - 342 07 42 T.C. Kültür ve Turizm Bakanlığı Yayıncı Sertifika No: 14824

Konya, TURKEY – December 2016 www.3rdicsae.org

PREFACE Sustainable agriculture is "a way of practicing agriculture which seeks to optimize skills and technology to achieve long-term stability of the agricultural enterprise, environmental protection, and consumer safety. It is achieved through management strategies which help the producer select hybrids and varieties, soil conserving cultural practices, soil fertility programs, crop rotations, weed, pest and disease biological management programs, and strategic use of animal and green manures and use of natural or synthetic inputs in a way that poses no significant hazard to man, animals, or the environment. The system is envisioned in its broadest sense, from the individual farm, to the local ecosystem, and to communities affected by this farming system both locally and globally. The goal of sustainable agriculture is to minimize adverse impacts to the immediate and off-farm environments while providing a sustained level of production and profit. Sound resource conservation is an integral part of the means to achieve sustainable agriculture. Sustainable agriculture integrates three main goals--environmental health, economic profitability, and social and economic equity. A variety of philosophies, policies and practices have contributed to these goals. People in many different capacities, from farmers to consumers, have shared this vision and contributed to it. Despite the diversity of people and perspectives, the following themes commonly weave through definitions of sustainable agriculture. Sustainable agriculture presents an opportunity to rethink the importance of family farms and rural communities. Economic development policies are needed that encourage more diversified agricultural production on family farms as a foundation for healthy economies in rural communities. In combination with other strategies, sustainable agriculture practices and policies can help foster community institutions that meet employment, educational, health, cultural and spiritual needs. By helping farmers to adopt practices that reduce chemical use and conserve scarce resources, sustainable agriculture research and education can play a key role in building public support for agricultural land preservation. Educating land use planners and decision-makers about sustainable agriculture is an important priority. Consumers can play a critical role in creating a sustainable food system. Through their purchases, they send strong messages to producers, retailers and others in the system about what they think is important. Food cost and nutritional quality have always influenced consumer choices. The challenge now is to find strategies that broaden consumer perspectives, so that environmental quality, resource use, and social equity issues are also considered in shopping decisions. At the same time, new policies and institution must be created to enable producers using sustainable practices to market their goods to a wider public. We are yet a long way from knowing just what methods and systems in diverse locations will really lead to sustainability. In many regions of the country, however, and for many crops, the particular mix of methods that will allow curtailing use of harmful farm chemicals or building crop diversity, while also providing economic success, are not yet clear. The stage is set for challenging not only farm practitioners, but also researchers, educators, and farm industry. New policies are needed to simultaneously promote environmental health, economic profitability, and social and economic equity. For example, commodity and price support programs could be restructured to allow farmers to realize the full benefits of the productivity gains made possible through alternative practices. Government and land grant university research policies could be modified to emphasize the development of sustainable alternatives. Marketing orders and cosmetic standards could be amended to encourage reduced pesticide use. Coalitions must be created to address

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these policy concerns at the local, regional, and national level. In addition to strategies for preserving natural resources and changing production practices, sustainable agriculture requires a commitment to changing public policies, economic institutions, and social values. Strategies for change must take into account the complex, reciprocal and ever-changing relationship between agricultural production and the broader society. Critical discussion of the sustainable agriculture concept will and should continue. Understanding will deepen; answers will continue to come. On-going dialog is important for another reason: with more parties, each with its own agenda, jumping into the sustainable agriculture "tent," only a continued focus on the real issues and goals will keep sustainable agriculture from becoming so allencompassing as to become meaningless. Finally, it is important to point out that reaching toward the goal of sustainable agriculture is the responsibility of all participants in the system, including farmers, laborers, policymakers, researchers, retailers, and consumers. Each group has its own part to play, its own unique contribution to make to strengthen the sustainable agriculture community.

Dr. Mithat Direk Chair, Editor in Chief On behalf the Organizing Committee

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Topics Agriculture Biodiversity Plant and animal genetic resources Biotechnology Horticulture, plants, animal production Animal nutrition Environment Local ecological knowledge Water and wastewater treatment Soil, water, and climate Climate change Surface and groundwater resources Structures and environment Nanotechnology and agriculture Precision farming and variable rate technology Power and machinery in agriculture GPS and GIS technology Agricultural waste management Mathematical modeling in agriculture Renewable Energy & Energy Management Agriculture social economics Plant protection IPM (Integrated pest management) Integrated agriculture management Maintenance and operation Food sovereignty Food security Economy Rural areas Supply and Demand Economy management Other related agricultural and environmental issues

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Honorary Committee Prof. Dr Mustafa Sahin, President, Selcuk University, Konya, Turkey Prof. Dr Hab. Wieslaw Bielawski, The Rector of Warsaw University of Life Science, Poland Prof. Andrzej Kowalski, Director of Institute of Agricultural and Food Economics, Poland Prof. Ir. Ahmad Yunus, Director, Graduate Program, Sebelas Maret University, Indonesia Prof. Dr. H.Avni Öktem, President, Konya Food & Agriculture University, Konya, Turkey Conference Chairs Prof. Dr. Lilianna Jabłońska, Warsaw University of Life Sciences, Section of Horticultural Economic, Poland Dr Mithat Direk, Agricultural Economy, Selcuk University, Turkey Conference Co-Chair Dr. Bożena Nosecka, Head of Horticultural Economics Department in Institute of Agricultural and Food Economics, Poland Dr. Kubilay K. Baştaş, Plant Protection, Selcuk University, Turkey Organizing Committee (in alphabetical order) Dr. Aisha Anjum, Ministry of Agriculture, Directorate of Animal Health Livestock & Dairy Development Department Punjab Lahore, Pakistan MSc. Anna Bugała, Horticultural Economics Department in Institute of Agricultural and Food Economics, Poland Dr. Halis Simsek, Agricultural & Biosystems Engineering, North Dakota State University, Fargo, ND, USA Dr. Komariah Kokom, Soil Science, Sebelas Maret University, Solo City, Indonesia MSc., Eng. Lidia Gunerka, Warsaw University of Life Sciences, Section of Horticultural Economic, Poland Eng. Łukasz Gajkowski, Warsaw University of Life Sciences, Section of Horticultural Economic, Poland Eng. Magda Marzec, Warsaw University of Life Sciences, Section of Horticultural Economic, Poland MSc. Michał Wielechowski, Warsaw University of Life Sciences, Poland MSc. Paweł Kraciński, Horticultural Economics Department in Institute of Agricultural and Food Economics, Poland MSc., Eng. Wioleta Sobczak, Warsaw University of Life Sciences, Section of Horticultural Economic, Poland Conference Secretary MSc., Eng. Łukasz Zaremba, Horticultural Economics Department in Institute of Agricultural and Food Economics, Poland

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Scientific Committee (in alphabetical order)  Dr. Ahmad Muhammed Ahmed, Agribusiness & Applied Economic, Tanta University, Egypt

 Dr. Nuray Ates, Environmental Engineering, Erciyes University, Kayseri, Turkey

 Dr. Bahri Ozsisli, Food Science, Kahramanmaraş Sütçü İmam University, Turkey

 Dr. Probang Setyono, Environmental-Expert, Sebelas Maret University, Indonesia

 Dr. Bilal Cemek, Agricultural & Biosystems Engineering, Ondokuz Mayis University, Turkey

 Dr. Rabha Bennama, Biology, University of Mostaganem, Algeria

 Dr. Darlina Md. Naim, Biological Sciences, University Sains Malaysia, Penang, Malaysia

 Dr. Rai Niaz Ahmad, Pir Mehr Ali Shah Arid Agriculture University, Rawalpindi, Pakistan

 Dr. Dawid Olewnicki, Warsaw University of Life Sciences, Section of Horticultural Economic, Poland

 Dr. Renata Grochowska Food Industry Economics Department in Institute of Agricultural and Food Economics, Poland

 Dr. Eakalak Khan, Program Director, Civil & Environmental Engineering, North Dakota State University, USA

 Dr. Richard Horsley, Department Head, Plant Science, North Dakota State University, USA

 Dr. Felix Arion, University of Agricultural Sciences and Veterinary Medicine, Romania

 Dr. Rudi Hari Murti, Vice Dean of Academic and Student Affairs, Gadjah Mada University, Indonesia

 Dr. Ganesh Bora, Agricultural &Biosystems Engineering, North Dakota State University, USA

 Dr. Senar Aydin, Environmental Engineering, Necmettin Erbakan University, Konya, Turkey

 Dr. Grzegorz Dybowski, Market Research Department in Institute of Agricultural and Food Economics, Poland

 Dr. Şenay Aydın, Soil Science, Celal Bayar University, Department of Agricultural Sciences, Alaşehir, Manisa

 Dr. Hatice Ozaktan, Plant Protection, Ege University, Bornova-İzmir, Turkey

 Dr. Şenay Şimşek, Plant Science, North Dakota State University, USA

 Dr. Igathinathane Cannayen, Agricultural & Biosystems Engineering, North Dakota State University, USA

 Dr. Shazia Shafique, Plant Pathology, University of the Punjab, Pakistan

 Dr. Krishna Pagilla, Program Director, Civil, & Environmental Engineering, University of Nevada, Reno, USA  Dr. Latif Kalin, Forestry and Wildlife Sciences, Auburn University, USA

 Dr. Sobiya Shafique, Mycology &Plant Pathology, University of the Punjab, Lahore, Pakistan  Dr. Sreekala Bajwa, Agricultural & Biosystems Engineering, North Dakota State University, USA  Dr. Şükrü Dursun, Environmental Engineering, Selcuk University, Turkey

 Dr. M. Musa Ozcan, Food Engineering Department, Agriculture Faculty, Selcuk University, Konya, Turkey

 Dr. Sutrisno Hadi Purnomo, Agribusiness, Sebelas Maret University Solo, Indonesia

 Dr. Mehmet Serhat Odabas, Bafra Vocation School, Ondokuz Mayis University, Samsun, Turkey

 Dr. Tawan Limpiyakorn, Department of Environmental Engineering, Chulalongkorn University, Thailand

 Dr. Muhammad Ashfag, Director, Institute of Agriculture & Resource Economics, University of Agriculture, Faisalabad, Pakistan

 Dr. Widyatmani Sih Dewi, Agricultural Technology, Sebelas Maret University, Indonesia

 Dr. Muhammad Subhan Qureshi, Dean, Animal Husbandry and Veterinary Science, Agricultural University, Peshawar, Pakistan

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 Haroun Chenchouni, Ecology, University of Tebessa, Algeria  Zafar Hussain, CEO, Dairy Science Park, Peshawar, Pakistan

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CONTENTS An Econometric Model for the Effect of Demand and Supply Determinants of Meat in Egypt Abdullah Mahmoud Abdel Maqsoud Ahmed, ...................................................................................... 1 Lignin Degradation by Two Isolated Bacillus Sp. Strains and Their Co-Culture Potential in the Production of Platform Chemicals Abeer Ahmed Qaed Ahmed, Olubukola Oluranti Babalola, Tracey McKay, ................................... 10 Distribution of Optimal Transport to Tomato Crop Between the Governorates of Egypt Ahmed Mohammed Ahmed, Hanan Mohamed Bahgat, .................................................................... 20 An Economic Study of the Most Important Factors Affecting the Demand for Agricultural Labor in Egypt Ahmed Mohamed Ahmed, Mofida El-Sayed Kabeel, .......................................................................... 25 Determination of the Yield Response to Water for Two Different Globe Artichokes Cultivars (Cynara Scolymus L. Cv. Bayrampaşa and Starline F1) in Greenhouse Conditions Ahmet Yılmaz, Yeşim Ahi, ...................................................................................................................... 34 Antimicrobial Resistance Patterns of Escherichia Coli Isolates From Broiler Flocks In Ardabil Province to Six Antibacterial Agents Commonly Used in the Iranian Poultry Industry Aidin Azizpour, Zahra Amirajam, ......................................................................................................... 42 Effects of Low and High Frequency Ultrasounds on Hatchability and Embryonic Mortality in Broiler Hatching Eggs Ali Aygun, İskender Yıldırım, ................................................................................................................. 46 Effects of Different Types of Cakes in Rations on the Performance of Culled Cyprus Shami Does in Half Elgadeda, Kassala State, Sudan Amani A. B. Osman, Mohammed E. Elimam, ..................................................................................... 49 Suppression Threat of Red Palm Weevil, Rhynchophorus Ferrugineus (Coleoptera: Curculionidae) in Date Palm by Using Novel of Insecticides and Technology Atef M. M. Sayed, Sayed, A. Ahmed, Abdalla, M.M. EL-Adawy, Mohesn M. M. Ali, ................... 54 Modeling Sustainable Sheep and Goats Production System Azizollah Kamalzadeh, ............................................................................................................................ 64 Slaughter and Carcass Characterıctıcs of Some Native Sheep Ali Karabacak, Saim Boztepe, ................................................................................................................. 72 Enzyme Activities of Bean Genotypes to Bacterial Common Blight Infections Within Sustainable Management Approaches Badel Uysal, Kubilay Kurtulus Bastas, .................................................................................................... 79 Impact of Salycilic Acid, Cyanocobalamin and Glutamic Acid on Fruiting of Barhy Date Palms Grown Under Upper Egypt Conditions Ahmed , M. K. Abdel Aal, Faissal F. Ahmed, Hussein H. Saied, ........................................................ 84

Interaction of Methanol Foliar Application and Water-Deficit Stress on Physiological Performance of Sugar Beet (Beta Vulgaris L.) Ebrahim Khalilvand Behrouzyar, Mehrdad Yarnia, ............................................................................ 90 Impact of Applying Agricultural Policies on the Production Costs of Wheat and Cotton in Egypt Eman R. El-Fahl, Mohamed Othman Abd El-Fattah, ......................................................................... 95 Priming of Seeds With Nitric Oxide Donor Sodium Nitroprusside Enhances the Germination Performance of Common Bean (Phaseolus Vulgaris L.) Seeds Under Salinity Stress Erdal Elkoca, Mostafakemal Shams, Ertan Yildirim, Melek Ekinci, Kamil Haliloğlu, ………................................................................................................. 100 Toxicity of Synthesized Copper Nanoparticles to Soybean: Deferential Effects of Nano and Bulk-Size Particles on Root Elongation Rate Ezzat. R. Marzouk, Sally A. Ismai, Ahmed F Hamza, ......................................................................... 111 The Effects of Different Tillage Methods on the Nutrient Contents of Organically Grown Sultani Çekirdeksiz Grape Fadime Ateş, Bülent Yağmur, Engin Çakır, ......................................................................................... 119 Economic Analysis of the Green Beans Growing on Farm in Derbent District Of Konya Province Fadime Üçpinar, Mithat Direk, ............................................................................................................ 126 Effect of Plant Growth-Promoting Bacteria (Pgpr) and Arbuscular Mycorrhizal Fungi (Amf) Inoculation on Some Physiological Traits and P-Uptake in Ex Vitro Potato Plantlets Farshid Hassani, Abbas areian, ............................................................................................................. 135 Effectiveness of Phosphate Solubilizing Bacteria Inoculation for Improving Phosphorus Absorption and Root Growth Indices Farshid Hassani, Ahmad Asgharzade, ................................................................................................. 146 Irrigation for Salinity Soils and High Evaporation Funda Dökmen, Meryem Kuzucu, ...................................................................................................... 154 Comparison of Virulence Genes (Eae, Stx1, Cnf2) of Escherichia Coli Isolates From Ows With Coliform Mastitis and Healthy Cows Gholam Ali Moradli, .............................................................................................................................. 157 Investigation of Environmental Effects and Water Quality of Aksaray Melendiz Stream and Mamasin Dam Site in Aksaray City, Middle Anatolian Part of Turkey Hatim Elhatip, Hasan Koçyiğit, ............................................................................................................ 163 Economic Efficiency of Orange Crop in West Nubaria Region in Egypt Elhussein. A. Elseify, .............................................................................................................................. 176 Mycotoxins in Lithuanian Buckwheat Grain Grown Under Sustainable And Organic Production Systems Ilona Keriene, Audrone Mankeviciene, Ruta Cesnuleviciene, Sigita Janaviciene, ....................... 181 New Data for Invasive Pilengas Mullet Species Liza Haematocheila, (Temminck And Schlegel, 1845) Along Bulgarian Black Sea Coast Ivanova, P., Nikolov, V., Dzhembekova, N., ..................................................................................... 186 A New Quarantine Criterion for Fire Blight Disease Management: Diversity of Erwinia Amylovora Plasmids Kubilay Kurtuluş Baştaş........................................................................................................................ 192

Reducing of Enteric Bacterial Contamination on Chicken Eggs by Ultrasonic Applications in Organic Production Kubilay Kurtuluş Baştaş, Ali Aygün, İskender Yıldırım.................................................................... 196 Reduction of Unwanted Products in Incineration Processes Şükrü Dursun, Zeynep Cansu Ayturan, .............................................................................................. 201 The Determinants of Multidimensional Poverty Using Logistic Model in Egypt Kamal Sultan Mohamed Salem, ........................................................................................................... 206 Impact of Using Irrigation System Developer on the Productivity of Resources In Gharbia Governorate, Egypt Kamal S. Salem, Ahmed M. Ahmed, Khalid Sh. Alsehsah, .............................................................. 213 Investigations on Various Methods for Cryopreservation of Callus of the Medicinal Plant Satureja Spicigera L. Ghaffarzadeh-Namazi, E.R.J. Keller, A. Senula, N. Babaeian, ..................................................... 219 Price Risk in Horticultural Sector in Poland Lukasz Zaremba, ..................................................................................................................................... 229 Classification of Plant Leafs by Using Color and Texture Properties of Leafs with Knn and Mlp Algorithms M.Fahri Ünlerşen, Kadir Sabanci, Cevat Aydin, ................................................................................ 236 The Effects of Adding Oxygen in Incubator at High Altitude (1700 M) and Different Genotypes on Hatching Results M. Fatih Çelen, Burcu Babacan, İskender Yıldırım, .......................................................................... 243 Dietary Intake of Micronutrient and Basal Metabolic Index (Bmi) of Women in Rural Pakistan Muhammad Israr, Saleem Khan, Aurangzeb, ..................................................................................... 247 Productivity and Water Use Efficiency of Onion Plants as Affected by Irrigation Water Levels and Sulphur Rates At El-Arish Region Mahmoud I.M. Ibrahim, M.S.A. El-Kassas, ........................................................................................ 259 Recovery of Waste Tire Chips and Sawdust for Thermal Insulation: Determination of Optimum Waste Mixture Mehmet Emin Argun, ............................................................................................................................ 273 Rural Origins of Poverty and the Efficiency of Rural Development Policies: A Cross-Country Comparison Mehmet Okan Taşar, Savaş Çevik, Perihan Hazel Kaya, .................................................................. 280 Antioxidant Enzymes Activities, Osmotic Adjustment Substances and Some Physiological Traits of Amaranth Cv. Koniz ‘As A New Crop’ in Saline Condition Mehrdad Yarnia, Ebrahim Khalilvand Behrouzyar, .......................................................................... 290 Using Rice Husks Powder to Upgrade the Rheological Properties of Bitumen Binder Mohammed Hadi Nahi, Ibrahim Kamaruddin, Madzlan Napiah, .................................................. 299 Impact of Gibberellic Acid, Cytofex and Calcium Chloride as Preharvest Applications on Yield and Fruit Quality of ‘Thompson Seedless’ Grapevine El-Abbasy U. K, Mohammed S. M, Fatma E. Ibrahim, Maha H.Abd El-Aziez, ............................ 305

The Response of Myrobolan 29c Plum Rootstock to Salinity in Vitro Culture Condition Muzaffer İpek, Şeyma Arıkan, Lütfi Pırlak Ahmet Eşitken, .............................................................. 311 Effect of Farmyard Manure and Elemental Sulfur on the Growth and Chemical Characteristics of Jatropha Curcas L.Tree Grown in Calcareous Soil Nermeen T. Shanan, Mohamed A. EL- Hady, .................................................................................... 316 Wheat Logistic in Egypt Nashwa El-Tatatwy, ................................................................................................................................ 324 Ecological Tourism Activities in The Rural Life in Turkey Mithat Direk, Arzu Kan, ........................................................................................................................ 330 Use of Artificial Intelligence to Obtain Data on Virulence of Erwinia Amylovora Causing Fire Blight Disease in Orchards Ömür Baysal, Kubilay Kurtulus Bastas, ............................................................................................... 336 The Effect of Bacterial Based Bio-Formulations on Tea (Camellia Sinensis L.) Growth, Yield, and Enzyme Activities Ramazan Çakmakçı, Yaşar Ertürk, Atefeh Varmazyari, Ali Atasever, Recep Kotan, Kamil Haliloğlu, Mustafa Erat, Kubilay Türkyılmaz, Remzi Sekban, Ayhan Haznedar, ............. 339 The Some Grasses forage Crops Grown in Arid Rangeland of the Central Anatolian and Properties of These Plants Ramazan Acar, Nur Koç, Sadiye Ayşe Çelik, Mithat Direk, ............................................................. 347 Determinants of Trade Flows Between Egypt and Eu Countries: Gravity Model Approach Rania Ahmed Mohamed Ahmed, ........................................................................................................ 351 Role of Nutrients for Fire Blight Disease Management Within Sustainable and Organic Agriculture Approaches Kubilay Kurtulus Bastas, ........................................................................................................................ 358 The Role of Non-Indigenous Insects in Agricultural Crop Pest Complex of Bulgaria – A Review Rumen Tomov, ........................................................................................................................................ 363 Diffusion and Adoption of Some New Fertilizer Technology Between Growers of Three Villages in Qalubia Governorate Saied Abbas Mohammed Rashad, ........................................................................................................ 372 Risk Assessment of Heavy Metals in Wheat and Barley Mohamad Sakizadeh, Fatemeh Mehrabi Sharafabadi, Eshagh Shayegan, Hadi Ghorbani, ......... 378 Groundwater Quality With Respect to the Levels of Nitrate and Fluoride in Urban Area of Malayer City and the Associated Health Risk Mohamad Sakizadeh, Fatemeh Mehrabi Sharafabadi, Eshagh Shayegan, ...................................... 392 Effectof Proquinazid 20% Ec Against Powdery Mildew of Pea Vis-À-Vis Impact of Weather Facors on Disease Progression in Field. Partha Sarathi Nath, ............................................................................................................................... 399

Urban-Rural Differences in Subjective Well-Being: Turkish Case Savas Cevik, M. Okan Tasar, ................................................................................................................. 402 Incineration Methods for Solid Waste From Waste Water Treatment Plants Sukru Dursun, Mosstfa Maaroof, ......................................................................................................... 414 Usability of Fly Ash From Solid Waste Incineration as a Concrete Production as a Supplement Material Mosstfa Maaroof, Sukru Dursun, ......................................................................................................... 421 Change of Soil Properties in an Ameliorated Pasture in a Long-Term Period Serkan İç, Ayşe Erel, Coşkun Gülser, .................................................................................................. 428 Sources of Agricultural Growth in Aegean Region: 1980-2015 Sevim Artık, ............................................................................................................................................. 433 The Future and Expectations of Agriculture in the Mediterranean Region Sevim Artık, ............................................................................................................................................. 444 The Effect of Different Levels of Chemical Fertilizer on Thymus Vulgaris Performance and Its Different Parts in Qom Region Sharrif Moghaddassi Mohammad, Arabiyan, ..................................................................................... 453 Insecticidal Efficiency Essential Oil of Punica Granatum Flower Against Callosobruchus Chinensis (F.) and Rhyzopertha Dominica (F.) Shayesteh Nouraddin, Hamed Hasankhani, Alireza Askari Kochi, Mehdi Badri Anarjan, ......... 463 The Effect of Different Treatments Before Sowing the Seeds of Old and Worn Morphological Characteristics of Chickpea in Vitro and Greenhouse Shayesteh Nouraddin, ............................................................................................................................ 468 Effect of Fungicidal Mixture on Severity of Brown Spot and Blast of Rice Vis-AVis Meteorological Factors on Disease Progression in Field Srikanta Das, Ayana Chakraborty, Sunita Mahapatra, ..................................................................... 475 Support of Knowledge Base Economy in Polish Agriculture Bozena Nosecka, ..................................................................................................................................... 484 Butterfly Diversity Along Urban- Rural Gradient in Kolkata, India Sushmita Chaudhuri, Parthiba Basu, ................................................................................................... 489 Assessment of Alternative Tillage Practices Used in Middle Anatolia Tamer Marakoğlu, Kazım Çarman, ..................................................................................................... 498 Correlation Between Resistance Markers and Enterotoxins Horizontal Transfer In Staphylococcus Aureus Isolates Tarek El-Saeed El-Banna, Ahmed Ahmed Abd El-Aziz, Fatma Ibrahem Sonbol, Lamiaa Abdullah Al-Madboly, …......................................................................................................... 504 The Competitive Position of Polish Apples Pawel Kracinski, ...................................................................................................................................... 514

Sustainable Organic Hazelnut Production in Turkey Tuğba Er, Özlem Boztepe, ..................................................................................................................... 520 Response of Pasture-Fed Lambs to Supplemental Feeding of forage Legumes or Concentrated Feed Ugur Demirci, Sukru Dogan, Gurhan Keles, Saban Isik, Serkan Ates, ........................................... 523 Simulation of Agronomic Practices for Southern Highlands of Tanzania Using Dssat Ceres-Maize Model Vijaya Kumar Gude, ………………………………………………………………......................... 527 Economic Analysis of the Current and Future Situation and Self-Sufficiency Of Wheat in Egypt Yasser HamediAbdlah Ali, .................................................................................................................... 532 Research on Evapotranspiration Components and Irrigation Scheduling Under Pepper (Capsicum Annuum L.) Cultivation Yeşim Ahi, Levent Tuna, ....................................................................................................................... 539 Assessing the Impacts of Interpersonal and Communication Skills of Agricultural Professionals on the Farming Community in Khyber Pakhtunkhwa- Pakistan Muhammad Zafarullah Khan, Rehmatullah and Asif Nawaz, ......................................................... 550 Polish International Trade of Horticulture Products After the Accession to the EU Anna Bugała............................................................................................................................................. 558 Iron (Fe) and Iron Chlorosis in Plant Nutrition Yavuz Talas, Senay Aydin, E. Dilsat Yegenoglu, H. Simsek ............................................................. 563 Sources of Agricultural Growth Between 1980-2015 Years in Turkey and Sustainability of Growth Sevim Artık ...........................................................................................................................................568

3rd International Conference on Sustainable Agriculture and Environment (3rd ICSAE) September 26-28, 2016, Warsaw, POLAND

AN ECONOMETRIC MODEL FOR THE EFFECT OF DEMAND AND SUPPLY DETERMINANTS OF MEAT IN EGYPT ABDULLAH MAHMOUD ABDEL-MAQSOUD AHMED Agricultural Economics - Faculty of Agriculture - Ain Shams University, Egypt

SUMMARY The study aims to limit the most important determinants of the food gap of meat, as well as the import of them and to this end is through the following: • A study of some of the current economic aspects of meat production sector in Egypt during the period (1995-2013). • appreciation record of the impact of the most important determinants of the demand and supply of meat in Egypt. • predict the behavior of economic variables components of the model the demand and supply of meat in Egypt. INTRODUCTION The agricultural sector is the mainstay of the Egyptian economic architecture because it is the main and basic food, clothing and in addition to that source, it contributes a portion of the national income and Egypt faces a deficit in agricultural Alantjh in general and meat production in particular. State and was trying its best to increase self-sufficiency and reduce the food gap and achieve food security and agricultural commodities in general and of livestock products in particular, and also the reduction of import rates and as a result of the widening gap size and low rate of self-sufficiency will lead to problems in the malnutrition the long term, and the state is working to provide meat for low-income people on an ongoing basis and in general we can say that the study of the market, especially in the open market system requires the provision of goods and services was high quality and improve the marketing system. The Problem of Study: Still the Egyptian individual suffers from malnutrition and lack of equilibrium in essential nutrients such as protein, fat and calories in terms of what most of the food sources of private low nutritious plant sources are still of the protein compared to animal food sources of high nutritional value, and then lay the features of the basic problem in the presence of food gap of meat, in addition to the presence of import gap of them. Objective of the Study:In light of the above study it aims to limit the most important determinants of the food gap of meat, as well as the import of them and to this end is through the following: • A study of some of the current economic aspects of meat production sector in Egypt during the period (1995-2013). • Appreciation record of the impact of the most important determinants of the demand and supply of meat in Egypt. • predict the behavior of economic variables components of the model the demand and supply of meat in Egypt. RESEARCH METHOD AND DATA SOURCES The study relied on the use of the style of appropriate quantitative analysis of the nature of the objective of the study as methods simplex different manner to estimate the general time trends for the variables of the study Downhill and also use the transition variables (Dummy Variables) and test (T) of the -1-


difference between the two groups to learn about the impact of GATT on the demand and supply of meat in Egypt and build and real-time estimation equations model and predict the sources of demand and supply of meat. The study relied on published and unpublished secondary data from various sources such as the Economic Affairs Sector data of the Ministry of Agriculture, and bulletins Central Agency for Public Mobilization and Statistics, and bulletins of the Arab Organization for Agricultural Development, as well as studies and research other relevant field of study. RESULTS AND DISCUSSION First, the study of some of the current economic aspects of meat production sector in Egypt during the period (1995-2013). (1): Evolution of the consumption of meat: Table refers (1) to the development of the consumption of meat in thousand tons during the period (1995-2013), where he took the consumption of meat trend with increasing starting from (683.42) thousand tons in 1995 fluctuated between increases and decreases until it reached the maximum at about the end (2002.44) thousand tons in 2013. Results estimate the statistical relationship directional consumption of meat also made it clear during the period (1995-2013) that the linear image is more suitable for the nature of the data images, where the results of the statistical analysis showed that the consumption of meat is growing at about 69.71 thousand tons per year during the study period, where proven moral at the level 0:05 spirits as proven moral model as a whole. The results showed that about 98% of the changes in the consumption of meat is due to a combination of factors, which reflects the impact of time. Table 1: Evolution of meat consumption in thousand tons during the period (1995-2013) Y=772.6+69.71X (7.7) (7.5) 0.99 0.98 575.13 linear Meat Sig=(.000) (.000) consumption Source: calculated using SPSS software (2) the impact of GATT on the consumption of meat: Study the impact of GATT on the consumption of Egyptian meat during the period (1980-2013) of the table (2) show that the average consumption of the Egyptian meat is increasing by about 552.8 thousand tons after the application of GATT compared penultimate applied, where proven moral at the 0.05 level, as proven moral model as a whole, as the results of the statistical estimate showed that about 40% of the changes in the consumption of Egyptian meat due to the impact of the application of GATT or not. Y=882+552.8D(9.9) (4.6) 0.64 Sig=(.000) (.000) Source: calculated using SPSS software

0.40

20.98

linear

Meat consumption

(3) the development of exports of meat: Table indicates (3) to the development of exports of meat in thousand tons during the period (19952013), where exports of meat taken an increasing trend year starting from (0.82) in 2000 fluctuated between increases and decreases until it reached the maximum at about the end (10.63) in 2010 . Studying directional relationship to meat exports during the period (1995 to 2013) was found from the equation following table No. (3) where the results of the statistical analysis showed that the Exponentialform are more suitable for the nature of the data nature, where the results of the statistical analysis showed that -2-


exports of meat is growing at a rate of about 8% per year during the study period as set at the level of significant 50.0 also set a significantly model as a whole. The results showed that about 36% of the changes in the exports of meat due to a combination of factors, which reflects the impact of time.

Y = e 0.73+0.08X (3.55) (2.98) 0.60 0.36 Sig=(.003)(.009) Source: calculated using SPSS software

8.92

Exponentialform Meat exports

(4) the impact of GATT on exports of meat: Study the impact of GATT on the Egyptian sugar exports during the period (1980-2013) of the table (4) show that the average Egyptian exports of meat decreased by about 3.2 thousand tons after the application of GATT compared penultimate application, where no proven moral at the 0.05 level, as not proven significantly model as a whole Y=5.25 -3.18D(3.3) (-1.4) 0.26 0.06 Sig=(.003) (.151) Source: calculated using SPSS software

2.2

linear

Meat exports

(5) The development of the production of meat: Table indicates (5) to the development of meat production in thousand tons during the period (19952013), where he took the production of meat-year-old rising trend starting from (560.9) in 1995 fluctuated between increases and decreases until it reached the maximum at about the end (1696.41) ( ) year 2013. Studying directional relationship to the production of meat during the period (1995-2013) turned out of the equation the following table No. 5, where the results of the statistical analysis showed that the Exponential form are more suitable for the nature of the data images, where the results of the statistical analysis showed that the production of meat is growing at a rate of about 6% per year during the study period as set at the level of significant 50.0 also set a significantly model as a whole. The results showed that about 70% of the changes in the production of meat due to a combination of factors, which reflects the impact of time. Y = e 676.58+0.06X(9.5) (6.1) 0.84 0.70 37 Exponential Meat Sig=(.000)(.000) form production Source: calculated using SPSS software (6) The impact of GATT for meat: Statistical results showed appreciation for the test (T) of the difference between two independent samples during the study periods prior to the application of the Convention (1980-1994), and after the application of the Convention (1995-2013) of the (6), where the production of Egyptian meat decreases after the application of GATT estimated 542.8 thousand tons compared to the period before GATT, has proved to be a significant difference in favor of the application of GATT period at the 0.05 level. Table (6): Test (T) of the difference between two independent samples of meat production during the period (1980-2013) according to the GATT: Sig T difference 1000 tons group .000 -4.80 -542.8 meat Source: calculated using SPSS software

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(7): Evolution of imports of meat: Table indicates (7) to the evolution of imports of meat per thousand tons during the period (19952013), where imports of meat taken an increasing trend year starting from (96.21) in 2003 fluctuated between increases and decreases until he reached the end of the maximum estimated (265.79) in 2008. Study the directional relationship of imports of meat during the period (1995 to 2013) was found from the following equation in Table (7), where the results of the statistical analysis showed that linear image is more suitable for the nature of the data images, where the results of the statistical analysis showed that imports of meat is increasing by about 7.99 thousand tons per year during the study period as set at the level of moral moral 0.05 also set a moral model as a whole. The results showed that about 52% of the changes in imports of meat due to a combination of factors, which reflects the impact of time. Y=103.51+7.99X(4.99) (4.18) 0.72 0.52 17.45 linear Meat imports Sig=(.000) (.001) Source: calculated using SPSS software (8): the impact of GATT for meat: Results of the statistical estimate showed the test (T) of the difference between two independent samples during periods of study before the application of the Convention (1980-1994), and after the application of the Convention (1995-2013) of the (8), where imports of Egyptian meat decreases after the application of GATT about 6. 81 thousand tons compared to the penultimate Ttabaagaha. Table (8) test (T) of the difference between two independent samples of imports of food groups during the period (1980-2012) according to the GATT in 1995. difference Sig T group .716 -.36 -6.81 meat Source: calculated using SPSS software (9): the evolution of the food gap of meat group: Statistics indicate the presence of meat food gap estimated at 177.42 thousand tons on average for the period (1995-2013) and indicates table (9) to the food gap of meat in thousand tons during the period (19952013), where he took the food gap of meat-year-old growing trend starting from (7383.53) thousand tons in 1997 fluctuated between increases and decreases until it reached the maximum at about the end (16,779.14) in 2011. Study the directional relationship of food from the meat of the gap during the period (1995-2013) turned out of the equation the following table No. 9, where the results of the statistical analysis showed that linear image is more suitable for the nature of the data images, where the results of the statistical analysis showed that the food gap of meat decreased by about 7.7 thousand tons per year during the study period as set at the level of moral moral 0.05 also set a moral model as a whole. The results showed that about 50% of the changes in the food gap of meat due to a combination of factors, which reflects the impact of time. Table (9): The results of the statistical analysis of the equations of the general trend of the evolution of the gap in thousand tons of meat during the period (1995-2013). F Math. form variable No. Estimated model R R2 Y=-103.6-7.7X (-4.95) (-4.02) 0.71 Sig=(.000)(.001) Source: calculated using SPSS software

0.50

-4-

16.2

linear

Meat gap

9


SECOND, ESTIMATE THE STATISTICAL ECONOMETRICMODEL OF DEMAND AND SUPPLY OF MEAT IN EGYPT: This section includes a statistical model to estimate the economic record total of variables demand and supply of meat during the period (1990-2013) using multiple equations models. Because economic phenomena are often not simple so that it can be described and analyzed through a single equation, there has always been a need to describe economic phenomena being complex and contain many overlapping economic relations, on the other hand, the multi-model equations reflect the reciprocal influence between the dependent and independent variables model, and not, as is the case in a single equation models as interested in influencing the direction of a single independent to the child just does not explain the reverse arrangement to that effect has appreciated the statistical study of the components of the Egyptian demand for meat by using multi-model equations. it is a econometric model estimating multi equations relatively more difficult compared to those of single models equation () and that what is needed from many stages and the main steps starting from the characterization of economic relations (according to economic logic) and then determine the most important variables that will be used in accordance with the matrix of simple correlation coefficients, then determine the best sports images that will be used in the statistical analysis, and after the completion of the coefficients of the model, is determining the degree of form definition and then select the most suitable for estimating the roads and in this regard, the study used the overall picture sometimes medium and image at other times as well as images logarithmic each of them. As It used the national production value and the value of national consumption overall its image once and medium again were all these permutations and combinations between the user model variables under certain criteria are economic logic, statistical moral dimension as possible from econometric problems in order to ensure the achievement of precision in the estimates obtained as much as possible and even it can be relied upon to predict later. The econometric model for meat simultaneous specification of meat in Egypt First, Demand Function Besides the demand for meat is composed in the form of the consumption function and exports of meat, these functions can be illustrated in the following: 1. where he describes the following equation consumption function: Y4t = f (Y3 (t-1), x2, x4, x11, x 12) where: Y4t the amount of consumption of meat in thousand tons Y3 (t-1) the amount of meat production in thousand tons in the previous year X2 national income in dollars to Egypt X4 population per thousand inhabitants X11 retail price of red meat in dollars per ton X12 retail price of white meat in dollars per ton 2. where the following equation describes a function of exports: Y1t = f (Y3 (t-1), x1, x2, x3, x4) where: Y1t export quantity of meat per thousand tonnes Y3 (t-1) the amount of meat production in thousand tons in the previous year X1 export price in dollars per ton X2 national income in dollars to Egypt X3 exchange rate X4 population per thousand inhabitants

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Second, the display function Supply Function: Includes the supply side in the Egyptian demand for meat two relationships first major model includes factors affecting the production of meat, while the second is in the factors affecting the quantity of imports to Egypt, where the Egyptian demand for meat is facing a deficit of continuing and growing every year, which has led to increased imports. 1. Production Function: could be clarified in the following equation: Y3t = f (x6, x7, x8, x9, x10) where: Y3t production in thousand tons size X7 total amount of dry Hays thousand tons X8 total amount of concentrated feed per thousand tonnes X9 total amount of green forage crops in thousand tons X10's total green fodder crop area per thousand acres 2. where the following equation describes the function of imports: Y2t = f (Y4 (t-1), x2, x3, x4, x5) where: Y2t quantity of imports of meat in thousand tons Y4 (t-1) the amount of consumption of meat in thousand tons in the previous year X2 national income in dollars to Egypt X3 exchange rate X4 population per thousand inhabitants X5 import price in dollars per ton - Results of the statistical estimation: Is evident from the above results that the model plus definition Over identified so was the way minimum of three squares stages (3SLS) Three stages least Squares most suitable methods used to estimate the standard model using the following Eviews program where it came from results of the statistical analysis are as follows: 1. Exports equation 1.27 lnX2 – 6.77X4+1.62 lnY3(t-1)+ lnY1t = 36.33 + 0.45 lnX1 (0.98) (2.01) (3.02) (3.37) (2.78) (0.33) (0.04) (0.00) (0.00) (0.01) R2 = 0.28 R-2 = 0.24 D.W=1.18 2.imports equation 1.17 lnX3 + 5.27 X4+2.70 lnY4(t-1)- lnY2t = -50.27 - 0.26 lnX5 (-2.74) (-1.21) (-2.71) (2.94) (2.21) (0.00) (0.23) (0.00) (0.00) (0.01) 2 -2 R = 0.50 R = 0.40 D.W=1.22 3.production equation lnY3t = -15.62 + 1.87 lnX7+ 1.53 lnX9 (-2.99) (5.67) (4.92) (0.00) (0.00) (0.00) 2 -2 R = 0.61 R = 0.58 D.W=1.91 4.consumption equation LnY4t = -6.17 + 0.60 X2 – 0.53X11+ 0.39 lnY3(t-1) (-3.46) (4.44) (-2.93) (4.79) (0.27) (0.01) (0.00) (0.00) 2 -2 R = 0.87 R = 0.85 D.W=1.67 Source: calculated using EViews program. -6-


Where:Y1t export quantity in thousand tons Y2t quantity of imports in thousand tons Y3t production in thousand tons Y4t consumption in thousand tons Y3 (t-1) production in thousand tons in the previous year Y4 (t-1) consumption in thousand tons in the previous year X1 export price in dollars per ton X2 national income in dollars to Egypt X3 exchange rate X4 population per thousand inhabitants X5 import price in dollars per ton X6 agricultural investment dollars in millions X7 Total Hays dry thousand tons X9 total amount of green crops in thousand tons X11 retail price of red meat in dollars per ton As shown above, the exports of meat equation, to increased exports in thousand tons by about 1.62% and 1.27% and 0.45% for every 1% increase in both of the previous year of production and national income and export price in dollars per ton for both of them, respectively, while decreasing the volume of exports at a rate of about 6.77% for each increase in the population by 1%. That is the most influential variables in the volume of exports of meat in a given year is a production in the previous year, and the national income and export price, in dollars per tonne and then the population. Statistical morale has been proven at the level of 0.05, also set a moral model as a whole also show that about 24% of the changes in the exports of meat due to the change in the independent variables under study. Also it shows imports equivalent to meat, to the increase in the imports in thousand tons by about 5.27% and 2.70% for every 1% increase in the per thousand inhabitants of the population the previous year and consumption, while the volume of imports is decreasing at a rate of approximately 1.17% and 0.26% at each increase in the exchange rate and the import price by 1%. Any more influential variables in the volume of imports of meat in a given year per thousand people was public consumption former population, then the exchange rate and import price. Statistical morale has been proven at the level of 0.05, set a moral model as a whole also show that about 40% of the changes in imports of meat due to the change in the independent variables under study. It also is clear from the output of meat is equivalent to increasing production in thousand tons by about 1.87% and 1.53% for every 1% increase in both the amount of dry Hays thousand tons and the amount of green crops in thousand tons each of them on Altertab.oa that the most influential variables in size production of meat in a given year is the amount of Hays dry thousand tons and the amount of green crops in thousands of tons for both of them, respectively, have proven statistical morale at the 0.05 level, as proven moral model as a whole also show that about 58% of the changes in the production of meat due to the change in the independent variables under study. As shown above, the equation of meat consumption, to an increase in consumption in thousand tons by about 0.60% and 0.395 for each 1% increase in national income and output the previous year. While the volume of consumption is declining at a rate of about 0.53% for each increase in the retail price of red meat by 1% or more variables that influence in the volume of meat consumption in a given year the population was the retail price of oil. Statistical morale has been proven at the level of 0.05, also set a moral model as a whole also show that about 85% of the changes in the consumption of meat due to the change in the independent variables under study. Third, the use of real-time models to predict the behavior of the variables of the study: -7-


Evident from the table (10) that the average of exports and imports, production and meat consumption during the period (2014-2020) amounted to about 7.62, 269.84, 1841.35,2175.03 thousand tons respectively. Table (10) to predict the request and offer a range of meat per thousand tons during the period (2014-2020) ‫اﻻﺳﺘﮭﻼك ﺑﺎﻻﻟﻒ طﻦ‬

‫اﻻﻧﺘﺎج ﺑﺎﻻﻟﻒ طﻦ‬

‫ﻛﻤﯿﺔ اﻟﻮاردات ﺑﺎﻻﻟﻒ طﻦ‬

‫ﻛﻤﯿﺔ اﻟﺼﺎدرات اﻟﻒ طﻦ‬

Model: Random walk

Model: Random walk

Model: Linear trend

Model: Quadratic trend

model

Upper Limit

Lower Limit

Forecast

Upper Limit

Lower Limit

Forecast

Upper Limit

Lower Limit

Forecast

Upper Limit

Lower Limit

Forecast

Period

2382.73

1708.45

2045.59

2076.16

1389.13

1732.64

351.69

152.79

252.24

10.14

0.94

5.54

2014

2565.52

1611.95

2088.74

2254.68

1283.08

1768.88

358.51

157.71

258.11

11.02

1.30

6.16

2015

2715.83

1547.95

2131.89

2400.09

1210.13

1805.11

365.39

162.56

263.97

12.00

1.65

6.82

2016

2849.31

1500.76

2175.03

2528.37

1154.32

1841.35

372.33

167.35

269.84

13.07

1.99

7.53

2017

2972.05

1464.32

2218.18

2645.70

1109.46

1877.58

379.33

172.09

275.71

14.25

2.32

8.28

2018

3087.15

1435.52

2261.33

2755.24

1072.38

1913.81

386.39

176.76

281.58

15.52

2.64

9.08

2019

3196.46

1412.50

2304.48

2858.90

1041.20

1950.05

393.50

181.38

287.44

16.88

2.94

9.91

2020

2824.15

1525.92

2175.03

2502.73

1179.96

1841.35

372.45

167.23

269.84

13.27

1.97

7.62

‫اﻟﻤﺘﻮﺳﻂ‬

The obtained results: Statistical results of the assessment of the standard model for real-time demand and supply of meat in Egypt showed that the most important determinants of the demand and supply of meat in Egypt are as follows: The amount of consumption of meat in thousand tons, the amount of production of meat in thousand tons in the previous year, the national income of Egypt dollars, in thousands Population, Price Retail red meat in dollars per ton price retail for white meat in dollars per ton, the amount of exports of meat per thousand tons, Production quantity of meat per thousand tons in the previous year Export dollars per ton price Egypt's national income in dollars exchange rate Production volume in thousand tons The total amount of dry Hays thousand tons The total amount of concentrated feed per thousand tonnes The total amount of green forage crops in thousand tons The total area of green forage crops in thousands of acres The quantity of imports of meat in thousand tons The amount of consumption of meat in thousand tons in the previous year Egypt's national income in dollars Import price in dollars per ton REFERENCES 1. Mohammed al-Husseini, Essayed Hashem Mohammed (doctors): the main determinants for the production and consumption of poultry meat in the Arab Republic of Egypt, the Fifth Conference of the economy and development in Egypt and the Arab nation, College of Agriculture, Mansoura University, the second volume 0.1996. 2. Nashwa Abdul Hamid Tatawi, (Dr.): economics of production and consumption of red meat in Egypt, Mansoura Journal of Agricultural Science, Vol. 23, No. 10.1997. 3. Abdullah Mahmoud Ahmed Abdel-Maksoud (Dr.) demand for food in the Arab world, Mansoura Journal of Agricultural Sciences, Vol. 21, No. 7.2007. -8-


4.El Kholi, O., Others, The Economics of Agricultural Intensification Strategies for the Attainment of National Goals, The Summary Paper Resulting from The Agricultural Development Systems, Egypt, California Economics Sub – Project Policy Workshop Held in Cairo, Egypt, March 28 – April 21, 1981.

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LIGNIN DEGRADATION BY TWO ISOLATED BACILLUS SP. STRAINS AND THEIRCO-CULTURE POTENTIAL IN THE PRODUCTION OF PLATFORM CHEMICALS ABEER AHMED QAED AHMED1,2*, OLUBUKOLA OLURANTI BABALOLA3 AND TRACEY MCKAY1 1

Department of Environmental Sciences, School of Agriculture and Environmental Sciences, University of South Africa, P.O. Box 392, Florida 1710, South Africa 2 Pharmacy Department, Medical Sciences collage, Al-Saeed University, Osaifrah, Taiz 4999, Yemen 3 Food Security and Safety Niche Area, Faculty of Agriculture, Science and Technology, North-West University, Mmabatho, Mafikeng 2735, South Africa

ABSTRACT Lignin degradation produces multiple aromatic monomers which can act as platform chemicals for the production of high value products. Ligninolytic bacteria produce different lignin-degradation enzymes which are well known as having more favourable characteristics compared to fungal enzymes. In this study, two lignin-degrading bacterial strains identified as Bacillus sp. L1 and Bacillus sp. L11 were isolated from soil, screened for their ligninolytic ability, and tested for their synergism effect in lignin degradation in axenic and co-culture conditions. Solid screening assay using a modified agar well diffusion method showed the efficiency of co-culture in decolorizing the indicator dyes and creating decolourization zones was better when compared to axenic cultures. Decolourization zones for the co-culture of Bacillus sp. L1 and Bacillus sp. L11 was found to be the largest (CR: 16 mm, MG: 20 mm, TB mm: 18 mm, and MB:17 mm) compared to the axenic culture of Bacillus sp. L1 (CR: 13 mm, MG: 12 mm, TB mm: 14 mm, and MB:13 mm) and Bacillus sp. L11 (CR: 10 mm, MG: 14 mm, TB mm: 12 mm, and MB:11 mm). Colony forming unit (CFU) counts showed that the co-culture had the highest ability to grow on lignin compared to both axenic cultures. These findings indicate that the co-culture of Bacillus sp. L1 and Bacillus sp. L11 have a synergism activity in the process of lignin degradation. This study revealed that bacterial co-culture is more effective than axenic cultures in lignin degradation. Thus, ligninolytic bacterial co-cultures have a huge potential for the production of platform chemicals from lignin. Keywords: Bacillus sp., co-culture, ligninolytic bacteria, platform chemicals 1. INTRODUCTION Biomass has attracted a lot of attention as a sustainable alternative source of raw materials compared to fossil resources in order to produce a variety of platform chemicals, and as the only other available resource for the production of chemicals (Cherubini & Strømman, 2011; Park et al., 2013; Ragauskas et al., 2006). Lignin is the second most abundant compound in plant biomass, consisting of up 20-30% of the dry weight of woody tissues (Abd-Elsalam & El-Hanafy, 2009). It is a highly complex heteropolymer synthesized by the polymerization of three different phenolic components (sinapyl alcohol, coniferyl alcohol, and p-coumaryl alcohol) (Menon & Rao, 2012). The degradation of lignin provides multiple aromatic monomers which act as building blocks for the production of high value products (Abd-Elsalam & ElHanafy, 2009; Agrawal et al., 2014). These aromatic compounds, considered renewable resources, can produce chemicals that are traditionally obtained from fossil resources (Abd-Elsalam & El-Hanafy, 2009). The breakdown of lignin provides various chemicals such as phenols, ferulic acid, vanilic acid, Benzene, Toluene, and p-Xylene. These compounds can be used in different applications such as in the food and pharmaceutical industries (Agrawal et al., 2014; Wong, 2012).

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Although there are many physical and chemical methods for breaking down lignin, the biological methods remain the most effective and favoured (Kurakake et al., 2007; Menon & Rao, 2012; Salvachúa et al., 2011). This could be attributed to the high cost of physical and chemical methods and their hazardous impact on the environment when compared to the more efficient, low-cost and the eco-friendly biological methods. There are a wide variety of microorganisms including actinomycetes, fungi and bacteria which have the ability to degrade lignin (Buraimoh et al., 2015; Huang et al., 2013; Shi et al., 2014). The recalcitrant structure of lignin is a major challenge however, hindering the efficient break down of lignin by many microorganisms (Wang et al., 2011). There is a wide variety of microorganisms including actinomycetes, fungi and bacteria which have the ability to degrade lignin (Buraimoh et al., 2015; Huang et al., 2013; Shi et al., 2014). Lignin-degrading bacteria however have attracted attention in respect of lignin degradation applications due to their wider tolerance of high pH, temperature, extractive and lignin concentration, and oxygen limitation compared to other lignin-degrading microorganisms (Abd-Elsalam & El-Hanafy, 2009; Martins et al., 2002; Ruijssenaars & Hartmans, 2004). As lignin degradation is a key step in converting biomass into platform chemicals for the production of high value products, ligninolytic bacteria deserve to be investigated intensively in order to maximize their full potential to be used in variety of industrial processes. Previous reports illustrated that some bacterial strains have the ability to degrade lignin (Bugg et al., 2011; Huang et al., 2013; Vicuña, 1988; Zimmermann, 1990). However, bacterial consortiums were found to be more effective in the degradation process compared to individual isolates (Wang et al., 2011; Wang et al., 2013). The efficient degradation of lignin could be achieved by the synergism between several ligninolytic enzymes obtained from different bacteria. Bacterial consortiums could provide the needed enzymes for the degradation process. Individual strains might have different roles to play in lignin degradation, and each individual strain could contribute differently in the process. Bacterial consortia with the ability to degrade lignin can be found naturally, such as in wood-feeding insects (Geib et al., 2008). Mixed cultures are known to have the potential to enhance the degradation processes (Chandra et al., 2009; Singh et al., 2008; Wang et al., 2011; Wang et al., 2013). Moreover, bacterial co-culture was found to be more effective in lignin degradation compared to axenic cultures (Yadav & Chandra, 2015). This indicates that different bacteria could contribute cumulatively to lignin degradation. Thus, ligninolytic bacterial co-culture might be a solution for the production of platform chemicals from lignin. This study aimed to find ligninolytic bacterial co-culture with high potential to be used in the production of platform chemicals from lignin. 2. MATERIALS AND METHODS Isolation of ligninolytic bacteria Soil samples were collected from an agro-field located at 25°47'26.5"S 25°37'07.7"E in Mafikeng, North West Province, South Africa. The collected soil samples were kept in sterilized polythene bags and further preserved at 4oC. Ligninolytic bacteria were enriched using minimal salts medium (MSML) which contains the following: kraft lignin (10 g), NH4Cl (1.0 g), NaCl (0.5g), Na2HPO4 (12.8 g), KH2PO4 (3.0 g), and deionized water (1 L). Minimal salts media was divided into 95 ml in 250 ml Erlenmeyer flasks. After sterilization and cooling, an amount of 5 g soil sample was added individually into the 95 ml MSML media. Then, all sampled MSML media were subjected to incubation at 30oC and 120 rpm for 7 days. One ml from the enriched cultures was serially diluted with deionized water up to 10-7. From each serial dilution, 100 µl spread onto LB agar plates, then plates were incubated at 37oC for 24 hours. Bacterial colonies were purified by streaking onto LB agar plates repeatedly until pure colonies were obtained. Twenty phenotypically different bacterial colonies were chosen and kept at 4oC for further analysis.

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Screening for ligninolytic bacteria 2.2.1. Solid screening assay Preliminary qualitative test was used to screen bacteria with ligninolytic activity by using indicator dyes which were Congo red (CR), Malachite Green (MG), Toluidine Blue O (TB) and Methylene Blue (MB). The preliminary screening test was performed by growing the isolated bacteria on LB agar plates containing one of the indicator dyes (0.25 g/l) previously mentioned. Then, plates were incubated at 37oC for 1-3 days with daily monitoring for colonies growth and decolourization zones development. The ratio of the colony diameter to the decolourization zone diameter was measured. Colonies with the largest clear zone ratio were selected for further analysis. 2.2.2. Liquid screening assay Liquid screening assay for lignin-degrading bacteria was performed using LB broth media containing each one of the indicator dyes (0.25 g/l). The test was carried out by inoculating overnight-culture of each isolated bacteria individually in a test tube containing 10 ml of dye containing LB broth media, then incubated at 30oC and 120 rpm for 1-3 days. The change in colour was monitored every 6 hours by comparing it to the negative control of the same dye containing LB broth media which was incubated under the same conditions. Bacterial isolates that showed complete dye-decolourization ability for the entire tested indicator dyes in the first 24 hours of incubation were selected for further experiments. Total DNA extraction, 16S rRNA amplification and gene sequencing, and phylogenetic analysis From the previous results, two bacterial isolates (L1 and L11) were found to have the largest clear zone ratios in the solid screening media, and were able to decolourize the entire indicator dyes completely during the first 24 hours of incubation in the liquid screening assay. These two isolates were selected for further experiments and molecular identification. Total genomic DNA was isolated from the pure cultures of L1 and L11 isolates using ZR Fungal/Bacterial DNA MiniPrepTM kit (Inqaba Biotechnical Industries (Pty) Ltd., South Africa). Partial 16S rRNA gene sequences were amplified by polymerase chain reaction (PCR) using primers 27F (5”-AGAGTTTGATCCTGGCTCAG-3”); and 1492R (5”GGTTACCTTGTTACGACTT-3”). PCR reaction mixture composed from 25 µl PCR master mix, 22 µl nuclease free water, 0.5 µl primer (each) and 2 µl DNA template. PCR was performed using the following conditions: 1 initial cycle of denaturation at 94oC for 1 min, then followed by 35 cycles of denaturation for 1 min at 94oC, annealing for 1 min at 55oC, and extension for 2 min at 72oC. PCR products were sent to Inqaba Biotechnical Industries (Pty) Ltd., Pretoria, South Africa for sequencing. The resulting partial sequences were subjected to the nucleotide Basic Local Alignment Search Tool (BLAST) analysis of the National Center for Biotechnology Information database (NCBI) to identify the approximate species based on the closest sequence data reported (http:// www.ncbi.nlm.nih.gov/blast/). The two isolates found to belong to Bacillus genus with similarity of 98% with their other closest Bacillus species counterparts (Table 1). L1 and L11 isolates were identified and named as Bacillus sp. L1 and Bacillus sp. L11, respectively. A distance-based neighbour-joining tree was constructed using four related sequences (Bacillus cereus SMR3 [KX355797.1], Bacillus thuringiensis RB90 [KJ534465.1], Bacillus pumilus mv49b [KU230016.1] and Bacillus safensis 35cp [KU921072.1]) with one unrelated sequences [Staphylococcus aureus ATCC 31890 (AY688034.1)] which was included in the phylogenetic tree as a control. All included sequences for phylogenetic tree construction were downloaded from the GenBank database. Multiple alignments for the partial 16S rRNA gene sequences of the two isolated strains and all other reference sequences which were included in the phylogenetic tree were done using ClustalX2. MEGA 6.0 software program was used to construct the phylogenetic tree based on a neighbour-joining algorithm.

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Synergistic effect of Bacillus sp. L1 and Bacillus sp. L11 for lignin-degradation 3.3.1. Lignin-degradation by co- and axenic cultures Pure MSML broth cultures of Bacillus sp. L1 and Bacillus sp. L11 with an inoculum size (cfu/ml) of 2.0 x 105 and 3.0 x 105 cells, respectively, were used to inoculate co- and axenic cultures in 99 ml MSML medium (250 ml flask). For preparing the axenic culture of Bacillus sp. L1, 1 ml of the Bacillus sp. L1 inoculum (2.0 x 105) was transferred into 99 ml MSML medium (250 ml flask). Meanwhile for the axenic culture of Bacillus sp. L11, the same amount (1 ml) from of the Bacillus sp. L11 inoculum (3.0 x 105) was transferred into 99 ml MSML medium (250 ml flask). Co-culture was prepared by transferring 0.5 ml from Bacillus sp. L1 inoculum (2.0 x 105) with 0.5 ml from Bacillus sp. L11 inoculum (3.0 x 105) into 99 ml MSML medium. The two axenic cultures with the co-culture of both strains were incubated in a rotary shaker at 30°C and 120 rpm for 6 days. Bacterial cell growth in both co- and axenic cultures was monitored by CFU counts from zero time and daily up to 6 days. CFU counts were performed by withdraw 1 ml of cultures at various time of intervals and serially diluted up to 10-8. Then, an amount of 100 µl of each serial dilution was streaked onto LB agar plates. All plates were incubated at 37°C and bacterial growth was monitored until no further increase of CFU was observed. 3.3.2. Agar well diffusion assay A modified agar well diffusion assay was conducted to evaluate the synergistic effect in lignin degradation for Bacillus sp. L1 and Bacillus sp. L11. This experiment was done first by inoculating 99 ml MSML medium (250 ml flask) with one single colony from overnight grown bacteria (Bacillus sp. L1 or Bacillus sp. L11). Both cultures were incubated in a rotary shaker at 30°C and 120 rpm for 4 days. After incubation, two inoculums of Bacillus sp. L1 and Bacillus sp. L11 were prepared with inoculum size (cfu/ml) of 5.0 x 102 and 7.0 x 102 cells, respectively. Both inoculums were used to prepare co- and axenic cultures of Bacillus sp. L1 and Bacillus sp. L11 in 99 ml MSML medium (as it previously described in 3.3.1). Further incubation was done at 30°C and 120 rpm. This step was done to induce lignin-degrading enzymes. After 4 days of incubation, 1 ml from each culture was withdrawn and centrifuged at 15000 x g for 5 min. Supernatants were kept for further steps. In this assay, LB agar plates were prepared by pouring LB agar media that contains one of the indicator dyes into sterilized petri plates. After solidification, each agar plate was punched with an eight millimetre diameter cork borer to create 3 wells. For better synergistic comparison, the first well was filled with 100 µl supernatant from Bacillus sp. L1 axenic culture, the second well was filled with 100 µl supernatant from Bacillus sp. L11 axenic culture, and lastly the third well was filled with 100 µl supernatant from the co-culture of both strains. Plates were left for 60 min at room temperature to allow cultures supernatants containing lignin-degrading enzymes to diffuse through the agar, and then they were incubated at 37°C for 24 h. Plates were monitored for the development of decolourization zones around wells every 6 h. Decolourization zones diameters were measured in millimetres. 3. RESULTS AND DISCUSSION Isolation and screening of ligninolytic bacteria in solid- and liquid assays Twenty phenotypically different bacterial colonies were obtained from the enrichment technique using MSML. These twenty isolates were subjected to solid and liquid assays screening in order to obtain lignindegrading bacteria with the highest ligninolytic ability. Two bacterial isolates (L1 and L11) were found to have the largest clear zone ratios in the solid screening media, and were they able to decolourize the entire indicator dyes completely during the first 24 hours of incubation in the liquid screening assay. These findings vindicate the selection of these two isolates for further analysis. The ability of bacteria to decolourize indicator dyes (lignin-mimicking dyes) is a clear indication that these bacteria have ligninolytic ability -13-


(Husain, 2006). The ability of L1 and L11 isolates to completely decolourize the entire indicator dyes during the first 24 h in the liquid assay show the high ligninolytic potential of these two isolates. In addition to these findings, the largest clear zones of these two isolates on the solid assay screening showed that these two isolates deserve to be investigated intensively. Molecular identification, 16S rRNA gene sequencing and phylogenetic analysis The investigation of 16S rRNA partial sequence alignment and phylogenetic analysis identified L1 and L11 as Bacillus sp.. The phylogenetic tree, which was constructed using 4 different related Bacillus members of Bacillus genus, demonstrates the linkage distance of L1 and L11 isolates with other Bacillus species (Fig. 1). The phylogenetic tree was generated by MEGA version 6 using four related sequences (Table 1) and one unrelated sequence (Staphylococcus aureus ATCC 31890 [AY688034.1]) as a control to demonstrate the linkage distance of the selected samples. ClustalX2 was used to do the multiple alignments. L1 showed 98% similarity with Bacillus cereus SMR3 [KX355797.1] and Bacillus thuringiensis RB90 [KJ534465.1] (Table 1). On the other hand, L11 also showed 98% similarity with Bacillus pumilus mv49b [KU230016.1] and Bacillus safensis 35cp [KU921072.1] (Table 1). These findings demonstrate that the two isolated strains are related to Bacillus genus and further named as Bacillus sp. L1 and Bacillus sp. L11. Synergistic effect of Bacillus sp. L1 and Bacillus sp. L11 for lignin-degradation: evaluating the growth on lignin and the development of decolourization zones in a modified agar well diffusion assay Results showed that the co-culture of Bacillus sp. L1 and Bacillus sp. L11 in MSML medium exhibited a high growth rate on lignin and a clear increase in CFU count compared to axenic cultures (Fig. 2). These findings indicate that both bacterial strains grow well in MSML medium, and there was a synergistic effect which enhanced bacterial growth in co-culture compared to the axenic cultures. These findings are in agreement with a study done by Yadav and Chandra (2015) which found that co-culture of Bacillus subtilis and Klebsiella pneumoniae was more effective in lignin degradation compared to axenic cultures. The synergistic effect between Bacillus sp. L1 and Bacillus sp. L11 in lignin degradation also was evaluated using a modified agar well diffusion assay. Results showed that co-culture had the largest zone of decolourization (CR: 16 mm, MG: 20 mm, TB mm: 18 mm, and MB: 17 mm) compared to the two axenic cultures of Bacillus sp. L1 (CR: 13 mm, MG: 12 mm, TB mm: 14 mm, and MB: 13 mm) and Bacillus sp. L11 (CR: 10 mm, MG: 14 mm, TB mm: 12 mm, and MB:11 mm)]. This was observed for the entire indicator dyes under the study (Fig. 3 & Table 2). The larger the ratio of the decolourization zones the highest the ligninolytic activity. Therefore, results showed a clear indication that a synergistic effect occurred between Bacillus sp. L1 and Bacillus sp. L11 which led to enhance the efficiency of the degradation of lignin as well as the efficiency of the decolourization of indicator dyes by the co-culture compared to axenic cultures. Mixed cultures reported previously to have potential in enhancing the degradation processes (Chandra et al., 2009; Singh et al., 2008; Wang et al., 2011; Wang et al., 2013). The synergism between different ligninolytic enzymes from different bacteria can provide an efficient degradation process for lignin. Moreover, different bacteria might have different roles to play in lignin degradation, and can contribute cumulatively to enhancing the process of lignin degradation. Results from the current study indicate that coculture found to have a higher potential to be used in the production of platform chemicals from lignin compared to the axenic cultures.

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4. CONCLUSION Two bacterial isolates identified as Bacillus sp. L1 and Bacillus sp. L11 were elected to be evaluated with respect to the efficiency of using co-cultures in the production of platform chemicals from lignin due to their superior ligninolytic potential that was found in solid and liquid screening assays. The co-culture was found to have a higher growth rate on lignin as well as better decolourization efficiency of indicator dyes compared to axenic cultures. The present study describes the potential of co-culturing ligninolytic bacteria for efficient lignin degradation to produce platform chemicals. ACKNOWLEDGMENTS AAQA and OOB are grateful for the research support provided by North-West University. AAQA and TM are thankful to University of South Africa (UNISA) for the valuable support for their research. OOB would like to thank the National Research Foundation, South Africa for grant (Ref: UID91990) that has supported research in her laboratory. REFERENCES Abd-Elsalam, H.E., El-Hanafy, A.A., 2009. Lignin biodegradation with ligninolytic bacterial strain and comparison of Bacillus subtilis and Bacillus sp. isolated from Egyptian soil. Am. Eurasian J. Agric. Environ. Sci., 5, 39-44. Agrawal, A., Kaushik, N., Biswas, S., 2014. Derivatives and Applications of Lignin–An Insight. SciTech J., 1, 30-36. Bugg, T.D., Ahmad, M., Hardiman, E.M., Singh, R., 2011. The emerging role for bacteria in lignin degradation and bio-product formation. Curr. Opin. Biotechnol., 22(3), 394-400. Buraimoh, O.M., Amund, O.O., Ilori, M.O., 2015. Kraft lignin degradation by autochtonous streptomyces strains isolated from a tropical lagoon ecosystem. J. Microbiol. Biotechnol. Food Sci., 5(3), 248. Chandra, R., Raj, A., Yadav, S., Patel, D.K., 2009. Reduction of pollutants in pulp paper mill effluent treated by PCP-degrading bacterial strains. Environ Monit Assess, 155(1-4), 1-11. Cherubini, F., Strømman, A.H., 2011. Chemicals from lignocellulosic biomass: opportunities, perspectives, and potential of biorefinery systems. Biofuels Bioprod. Biorefin, 5(5), 548-561. Geib, S.M., Filley, T.R., Hatcher, P.G., Hoover, K., Carlson, J.E., Jimenez-Gasco Mdel, M., Nakagawa-Izumi, A., Sleighter, R.L., Tien, M., 2008. Lignin degradation in wood-feeding insects. Proc Natl Acad Sci U S A, 105(35), 12932-7. Huang, X.F., Santhanam, N., Badri, D.V., Hunter, W.J., Manter, D.K., Decker, S.R., Vivanco, J.M., Reardon, K.F., 2013. Isolation and characterization of lignin‐degrading bacteria from rainforest soils. Biotechnol. bioeng., 110(6), 1616-1626. Husain, Q., 2006. Potential applications of the oxidoreductive enzymes in the decolorization and detoxification of textile and other synthetic dyes from polluted water: a review. Crit Rev Biotechnol, 26(4), 201-21. Kurakake, M., Ide, N., Komaki, T., 2007. Biological pretreatment with two bacterial strains for enzymatic hydrolysis of office paper. Curr. Microbiol., 54(6), 424-428. Martins, L.g.O., Soares, C.M., Pereira, M.M., Teixeira, M., Costa, T., Jones, G.H., Henriques, A.O., 2002. Molecular and Biochemical Characterization of a Highly Stable Bacterial Laccase That Occurs as a Structural Component of theBacillus subtilis Endospore Coat. J. Biol. Chem., 277(21), 18849-18859. Menon, V., Rao, M., 2012. Trends in bioconversion of lignocellulose: biofuels, platform chemicals & biorefinery concept. Prog. Energy Combust. Sci., 38(4), 522-550. Park, J.-M., Kondo, A., Chang, J.-S., Perry Chou, C., Monsan, P., 2013. Biorefineries. Bioresour. Technol., 135, 1.

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Ragauskas, A.J., Williams, C.K., Davison, B.H., Britovsek, G., Cairney, J., Eckert, C.A., Frederick, W.J., Hallett, J.P., Leak, D.J., Liotta, C.L., 2006. The path forward for biofuels and biomaterials. Science, 311(5760), 484-489. Ruijssenaars, H.J., Hartmans, S., 2004. A cloned Bacillus halodurans multicopper oxidase exhibiting alkaline laccase activity. Appl. Microbiol. Biotechnol., 65(2), 177-82. Salvachúa, D., Prieto, A., López-Abelairas, M., Lu-Chau, T., Martínez, Á.T., Martínez, M.J., 2011. Fungal pretreatment: an alternative in second-generation ethanol from wheat straw. Bioresour. Technol., 102(16), 7500-7506. Shi, L., Yu, H., Dong, T., Kong, W., Ke, M., Ma, F., Zhang, X., 2014. Biochemical and molecular characterization of a novel laccase from selective lignin-degrading white-rot fungus Echinodontium taxodii 2538. Process Biochem., 49(7), 1097-1106. Singh, S., Chandra, R., Patel, D.K., Reddy, M.M., Rai, V., 2008. Investigation of the biotransformation of pentachlorophenol and pulp paper mill effluent decolorisation by the bacterial strains in a mixed culture. Bioresour. Technol., 99(13), 5703-9. Vicuña, R., 1988. Bacterial degradation of lignin. Enzyme Microb. Technol., 10(11), 646-655. Wang, W., Yan, L., Cui, Z., Gao, Y., Wang, Y., Jing, R., 2011. Characterization of a microbial consortium capable of degrading lignocellulose. Bioresour. Technol., 102(19), 9321-9324. Wang, Y., Liu, Q., Yan, L., Gao, Y., Wang, Y., Wang, W., 2013. A novel lignin degradation bacterial consortium for efficient pulping. Bioresour. Technol., 139, 113-119. Wong, J.T. 2012. Technological, commercial, organizational, and social uncertainties of a novel process for vanillin production from lignin, Simon Fraser University. Canada. Yadav, S., Chandra, R., 2015. Syntrophic co-culture of Bacillus subtilis and Klebsiella pneumonia for degradation of kraft lignin discharged from rayon grade pulp industry. J. Environ. Sci. (China), 33, 229-38. Zimmermann, W., 1990. Degradation of lignin by bacteria. J. Biotechnol., 13(2-3), 119-130. Figures legends Fig. 1. Phylogenetic tree showing the relationship between Bacillus sp. L1 and Bacillus sp. L11 and the related selected sequences linked based on 16S rRNA sequence comparisons. Fig. 2. The growth on lignin in co- and axenic cultures of Bacillus sp. L1 and Bacillus sp. L11 monitored daily by CFU counts. Fig. 3. Synergistic effect of Bacillus sp. L1 and Bacillus sp. L11 in co- and axenic cultures for lignindegradation using modified agar well diffusion assay and different indicator dyes: Congo red (a), Malachite Green (b), Toluidine Blue O (c) and Methylene Blue (d), after 12 h.

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Fig. 1

Fig. 2 1,40E+06 CFU/ML Bacillus sp. L1

1,20E+06 1,00E+06 8,00E+05

CFU/ML Bacillus sp. L11

6,00E+05 4,00E+05

CFU/ML Bacillus sp. L1 & Bacillus sp. L11

2,00E+05 0,00E+00

0

1

2

3

4

5

Incubation time (d)

-17-

6


Fig. 3

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Table 1. BLAST results of the partial 16S rRNA gene sequence identity between the bacterial isolates under the study and the most probable hits of GenBank sequences

Isolated strain

Bacillus sp. L1 Bacillus sp. L11

Similar species

GenBank accession No.

Identity sequence (%)

Bacillus cereus SMR3 Bacillus thuringiensis RB90 Bacillus pumilus mv49b Bacillus safensis 35cp

KX355797.1 KJ534465.1 KU230016.1 KU921072.1

98% 98% 98% 98%

Table 2. Decolourization zones diameter (mm) for co- and axenic cultures of Bacillus sp. L1 and Bacillus sp. L11 using modified agar well diffusion assay and different indicator dyes after 12 h incubation.

Indicator dyes

Decolourization zones diameter (mm) Axenic culture of Bacillus sp. L1

Axenic culture of Bacillus sp. L11

CR

13

10

16

MG

12

14

20

TB

14

12

18

MB

13

11

17

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Co-culture of Bacillus sp. L1 &Bacillus sp. L11


DISTRIBUTION OF OPTIMAL TRANSPORT TO TOMATO CROP BETWEEN THE GOVERNORATES OF EGYPT AHMED MOHAMMED AHMED, HANAN MOHAMED BAHGAT Department of Agricultural Economics, Agriculture Faculty, Tanta University, Tanta Egypt Agricultural Economics Research Institute, Cairo Egypt

SUMMARY Distribution of optimal transport to tomato crop between the governorates of Egypt. The research aimed to minimize transport distances to tomato cropfrom the consumption surplus Governorates to deficit by using linear programming model. The results showed that surplus Governorate are: Alexandria, El Beheria, El Sharkia, Ismailia, Beni Suef, Fayoum, Luxer, Qena, North Sinai, Matrouh. deficit Governorates are Kafr el-Sheikh,Qalubia, Gharbia, Dakahlia, Menoufiy, Cairo, Damietta, Port Said, Giza, Minya, Assiut, Allwady El Gadid, Aswan, Sohag, Red Sea, Suez and South Sinai respectively. INTRODUCTION The function of the transport and distribution of great importance to the most productive processes and marketing .where different transport costs by distance between the farm and the market in particular and the degree of the validity of the roads in general .transport servicing adds the benefit of potential agricultural output, which increases the benefit of the consumer in view of the transfer of the crop regions of surplus areas to deficit areas Research the problem:Determined search problem in the presence of the unbalanced distribution of tomato between the governorates of Egypt and wholesale markets and are in the process of the transfer of the crop from areas of production to consumption areas the imbalance as a resultfarmers to sell the crop in the areas close to the areas of production and to avoid increasing the cost of transport., While linked to the transport service wholesale markets and the conventions and contracts with the previous farmers where commodity open cars heading to the central market to shop and then downloaded and stored and offered for retail sale. Aim of the research: Minimize transport distances to harvest tomatoes, between them producing provinces, which increases the need for production and consumption, which called surplus provinces and to the provinces, which the production does not meet the consumption needs or do not produce this crop. It is worth mentioning that minimize transport distances necessarily mean to minimize transport costs where the latter are associated significantly with spaces that are transferred Wales Where the latter are associated significantly spaces, which are transported through which crops. Research method and data sources : Search adopted in achieving its objectives on secondary data obtained from the Ministry of Agriculture and Land Reclamation , and then next to the data obtained from the Central Agency for Public Mobilization and Statistics, as was the use of appropriate descriptive statistical methods, and the use of transport model as one of the basic applications of linear programming, where linear programming of three components R. model consists of three major components, namely: 1. target function Opjective function. 2- Constraints restrictions. 3-limitations or restrictions is negative Non-Negativity constraints The targets of the application of linear programming in the style of this problem minimize distances to transport tomatoes from production areas to consumption areas under certain restrictions, or own energies -20-


production and consumption for each province, determinants, Where the movement amounts of tomato production areas is characterized by a surplus to the needs of consumption to production zones least about the need for tomato consumption or other areas not producing tomatoes, to illustrate the nature of the model used in this problem is supposed number (i) of the production areas producing volumes : K1, k2, .................ki of homogeneous commodity, a tomato as the total output of the production areas G = k1 + k2 + k3 + ......................ki and the movement of the total amount of the commodity to the number (j) of the consumer areas, in amounts Since the total consumption of consumer areas : G = r1 + r2 + r3 .......................... + rj The main problem for transport in determining the distributional pattern optimization, which achieves lower end of the distances, assuming the amount transferred from the production area (i) to the consumer area (j) Xij is achieved the goal of the model in determining Nukaly pattern (ie, determining X11, X12, ............ Xij Which achieves the lower end of the target function (1) where T= Σ4i= 1Σ5j= 1Cij Xij 1............. And within the limits of the restrictions or limitations illustrated equations numbers (2, 3,4) : Indicate where the equation (2) that the total amounts transferred from a certain area of productivity to all consumer areas must be less than or equa or at least equal to the production of this region Σ5j= 1Cij Xij ≤ ki ( i = 1,2, .....2... (4 According to the equation number (3,4) that the total amounts transferred from a certain area of productivity to all consumer areas must be equal to or greater than the energy Or more than a consumer of energy for this region Σ4i=1 Xij ≥ rj (j = 1,2,….. 5) 3........... Xij ≥ ) 0 i = 1, ..............., (4…… 4 J = 1, ............. 5 To ensure a consistency in the mathematical model must be achieved following condition : Σ4i= 1Σ5j= 1Xij = Σ5j= 1Σ4i=1 Xij The development of tomato production on the level of Republic: Review the data contained in Table No.1 shows that the tomato crop is produced from the majority of the provinces of the Republic, and comes in Lake County ranked first among Producing provinces him a quantity of about (2363)thousand tons, equivalent to about(27 %) of the total production of the republic as an average for the period ( (2013 -2009, followed by the provinces of Alexandria, Eastern, Fayoum, Ismailia , Qena, Beni Suef, producing abanteg is about (375 ,421 ,499 ,506 ,537 ,643 ,742 ,748)thousand tons, respectively, as an average for the period of the study , equivalent to about (8,6%, 8,5%, 7,4%, 6%, 5,8%, 5,7%) from the total production of the republic in the same order . While it is representing the production of the remaining governorates other by 5 % of the average production of the Republic of tomatoes during the study period. Estimate the actual consumption of tomato crop: Estimated actual consumption of tomato crop at the level of governorates of the republic on the basis of each of the average annual per capita availability of tomatoes multiplied by the average number of provincial residents different and described in Table (1) during the period ( (2013 -2009. A review of the Table Table No.1 it is clear that El Beheria governorate tops the governorates of the republic in terms of excess consumption of tomato yield by( 51 %) of the total surplus tomato crop on the republic level , followed by each of the governorates of Ismailia , Fayoum , Alexandria, Beni Suef , Qena , respectively, at rates of(12%, 9%, 7,6%, 6,3%, 5,6%) respectively.

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Table No. 1 governorates surplus & deficit from tomato average period (2009- 2013)

governorates

The averageproduction

1 2 3

Alexandria

Ton 748723

% 8.6

El Beheria

2363219

Gharbia

4 5 6 7 8 9 10 11 12

No

13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

The average number ofpopulation (people)

the actual consumption (*)

surplus

4480387

Ton 484666

% 5.6

Ton 264057

% 7.6

27

5287196

571942

6.6

1791277

51.4

37668

0.4

4399817

475950

Kafrel-Sheikh

206985

2.4

2911386

Dakahlia

62345

0.7

Damietta

23341

El Sharkia

deficit Ton

%

5.5

438283

12.7

314939

3.6

107954

3.1

5501933

595172

6.8

532827

15.4

0.3

1225008

132515

1.5

109174

3.2

742800

8.5

5948885

643521

7.4

99279

2.9

Ismailia

536954

6.1

1069669

115711

1.3

421243

12.1

Port Said

3066

0

622397

67328

0.8

64262

1.9

Suez

50547

0.6

570402

61703

0.7

11156

0.3

Menoufiy

125876

1.4

3622249

391837

4.5

265961

7.7

Qalubia Cairo ,Helwan Giza

57636

0.7

4705025

508966

5.8

451330

13

309335

3.5

8655085

936264

10.7

626929

18.1

374970

4.3

6939156

750643

8.6

375673

10.8

Beni Suef

499414

5.7

2576630

278727

3.2

220687

6.3

Fayoum

643176

7.4

2847657

308045

3.5

335131

9.6

Minya

420881

4.8

4668972

505066

5.8

84185

2.4

Assiut

288594

3.3

3852919

416790

4.8

128196

3.7

Sohag

342846

3.9

4179212

452086

5.2

109240

3.2

Qena

506761

5.8

2880283

311575

3.6

195186

5.6

Luxer

172320

2

950541

102825

1.2

69495

2

Aswan Allwady ElGadid Matrouh

26336

0.3

1310892

141806

1.6

115470

3.3

10943

0.1

206828

22374

0.3

11431

0.3

69249

0.8

383579

41494

0.5

Red Sea

2861

0

317528

34349

0.4

31487

0.9

NorthSinai

100083

1.1

391467

42347

0.5

0.2

158486

17144

0.2

100

80663589

8725785

100.2

SouthSinai Total

8726929

27755

0.8 0

57736

1.7 566

3481846

100

3464124

100

Source:1- Ministry of Agriculture and Land Reclamation, Annual Bulletin of Agricultural Economics, Economic Affairs Sector, the central management of agricultural Aqsad, various issues. 2. Central Authority of the Central Agency for Public Mobilization and Statistics, annual publication of the balance of food, various issues. Distribution optimized to tomato crop : A review of the results of resolving transport model schedule No. 2 of the tomato crop between the governorates of the republic is evident from Table No. 3 that the distributional optimized to harvest tomatoes pattern involves the following: 1- Transfers surplus Alexandria Governorate to each of the governorates of Kafr el-Sheikh, Qalubia by 41%, 59%. -22-


2-El Beheria distributes its surplus to the governorates of Gharbia, Dakahlia, Menoufiy and Qalubia and Cairo 24%, 9%,14,8%, 16,5% and 35% respectively. 3-Surplus El Sharkia governorate of tomato crop distribut to the entire governorate of Dakahlia. 4-Ismailia governorate distributes Surplus of tomatoes on El Dakahlia, Damietta, Port Said and Giza by 63,7%, 25%, 4,3% and 6% respectively. 5-Governorate of Beni Suef distributes the surplus to El Giza, Minya ,Assiut and Allwady El Gadid by about 2,4%, 38%, 58%and 1,3% respectively . 6- conveys all the surplus tomatoes from the Fayoum to Giza governorate. 7- conveys all the surplus tomatoes from the Luxer to Aswan governorate. 8-Governorate of Qena distributes surplus tomatoes to the Governorates of Sohag, Aswan, Allwady El Gadid and Red Sea by 56%, 23,5%, 4,3% and 16% respectively. 9- transferred the surplus tomatoes from North Sinai governorate by 79,7%, 19% and 1% on the Port Said, Suez and South Sinai respectively. 10-Tomatoe crop surplus distribute from Matrouh to Giza Governorate by 36% of the total surplus of it. REFERENCES 1. Ministry of Agriculture and Land Reclamation, Annual Bulletin of Agricultural Economics , Economic Affairs Sector , the central management of agricultural Aqsad , various issues 2. Central Authority of the Central Agency for Public Mobilization and Statistics , annual publication of the balance of food , various issues. 3. Mr. Hassan Mahdi , a Farghaly Faraj , a study of the impact of different Mqanh A method of estimating the cost of transport to the distributional pattern Nukaly optimal agricultural products , Egyptian Journal of Agricultural Economics , Vol. IV , First Issue Mars 4. Farghaly Faraj , an economic study of the methods of transportation of agricultural crops in ARE , Master Thesis Agricultural Economics Department , Faculty of Agriculture, Zagazig University, 1983 . 5. On Farghaly Faraj , distribution Nukaly optimum harvest oranges between the governorates of Egypt in the future , Egyptian Journal of Agricultural Economics , Vol. III , No. II in September 1993 .

-23-


Table No.2 Solving model transport model tomato crop between the governorates of the Rrepublic total deficit&surplus

164876 99279 268671

109174

18248

25150 5379 335131

84185

128196

2946 109240

45975 69495

8485

31487

109240

115470

11431

31487

10032 438283

107954

532826

109174

46014 64262

11156 11156

265961

451330

626929

Source: computer program

-24-

40896

84185

128196

566 566

Total surplus

NorthSinai

Red Sea

Allwady ElGadid

Aswan

Sohag

626929

Assiut

156103 295227

Minya

Cairo, Helwan

265961

107954 438283

Giza

Qalubia

Suez

Port Said

Damietta

Menoufiy

Alexandria El Beheria El Sharkia Ismailia Beni Suef Fayoum Qena Luxer Matrouh SouthSinai

Dakahlia

Gharbia

surplus

Kafrel-Sheikh

deficit

264057 1791276 99279 421243 220687 335131 195186 69495 27755 57736


AN ECONOMIC STUDY OF THE MOST IMPORTANT FACTORS AFFECTING THE DEMAND FOR AGRICULTURAL LABOR IN EGYPT

AHMED MOHAMED AHMED, MOFIDA EL-SAYED KABEEL Department of Agricultural Economics, Agriculture Faculty, Tanta University, Tanta Egypt Agricultural Economics Research Institute, Cairo Egypt

ABSTRACT Targeted research mainly a function of the estimate of the total demand for agricultural labor in Egypt and stand on the most important factors affecting, was based on the search for a method of multiple regression in the image of the dual logarithmic to determine the most important independent variables likely to affect agricultural employment (variable continued) has been confined to those independent variables in six variables, as follows: Agricultural Machinery (x1), Agricultural Investment (x2), the proportion of agricultural wages to non-agricultural (x3), the value of agricultural output (x4), the value of production requirements (x5), crop area (x6). She pointed out the search results to the moral statistically model at the level of the moral 0.01, which shows a parameter value specifically ratios (R2 ), which was estimated at about 0.92 any that about 92 % of changes in demand for agricultural labor due to the change in the independent variables: agricultural investments (x2), the proportion of agricultural wages to non-agricultural (x3), the value of production requirements (x5). The research laboratories moral decline for the third and fifth at the level of the moral0.01, while moral proved coefficient of steep variable when a moral level 0.05. In order to obtain the strongest variables on the impact of the changing where it was based on the method of the gradient of the interim or gradual (step-wise) showed the most important results that the Model statistically moral at the level of the moral 0.01 The strongest independent variables impact on the demand for labor is the value of production requirements (x5) , the interpretation of about 80% of changes in labor demand and an increase of 1% in the value it would increase the proportion of demand for business stay total unacceptable majesty about 0.28%. Keywords: non-farm agricultural, farm agricultural,value of agricultural production. INTRODUCTION The demand for agricultural labor of are important to identify the needs are met Egyptian agriculture of human labor indicators estimate, and then how to maximize the efficient use of this element and to identify the deficit or surplus of human labor, especial offer on agricultural work, so it must be proportional to the width of the agricultural labor with the actual demand which is expected of them. Research Problem: Decreasing productivity of the agricultural working group and the extent of the reflection of the level of income, in addition to the economic variables that play an important and effective in the efficiency of the element of human action as one of the elements of production, which directly affects the balance of the structure of the labor market and the deviation of the current operating agricultural employment for the optimal level to achieve economic efficiency, in addition to the problems facing the human employment at the present time, perhaps the most important of which is the nature of the competitive relationship between the element of human labor and the rest of the elements of the other production and employment of Egyptian agricultural an essential component of the labor force at the national level, and therefore become studied a vital requirement to clarify the most important factors that directly affect the nature of relations Productivity. Aim of the Research: Estimating function of The total the demand for agricultural labor in Egypt and study the economic relationship between the number of agricultural workers in the sector and the factors determining the demand function. -25-


RESEARCH METHOD OF DATA SOURCES Search adoptedthe stylistic descriptive analysis and quantitative; to express the economic relations of the variables relevant to the subject of research, where the use of the technique of linear simple to identify the extent of moral statistical models user, and moral regression equations, wasalso based on the method of multiple regression in written form the Logarithmic functions to determine the most important independent variables likely to affect agricultural employment (variable continued) was limited to those independent variables in six variables, as follows: Agricultural Machinery (x1), Agricultural Investment (x2), the proportion of agricultural wages to non-agricultural (x3), the value of agricultural output (x4), the value of production requirements (x5), crop area (x6), as was the use of the regression analysis of the interim or gradual (step-wise) in identifying the most variables The impact of the variable. And search adopted in achieving its objectives on the secondary data obtained from the Ministry of Agriculture and the Ministry of economic development, as well as the Central Agency for Public Mobilization and Statistics, data in some scientific studies and research relevant to the subject of the study. The analysis considers in this research themost important determinants of therequest on agricultural employment has been the following steps: 1. Identification of independent variables likelyto affect agricultural employment (Yi) variable continued has been confined to those independent variables in six variables where it was found that the most important variables affecting the function of the total demand for agricultural labor are: X1 = ratio of agricultural wagesto the non-farm. X2=agricultural investment. X3= number of agricultural machinery. X4= agricultural output. X5= value of production requirements. X6= crop area. Hasbeena function of thetotal demand for agricultural laborthrough thelinear modelin the following format:

Y

^ i

= a + b1x1 + b 2 x 2 + b3 x3 + b 4 x 4 + b5 x5 + b6 x 6

2 -an estimate ofa matrix transactions simple link in the written image between the independent variables each other and changing and independent of the other hand. 3- The exclusion of the variables that indications transactions simple link to illogical and has been for written image. According to the economic logic , it is expected that there is an inverse relationship between the demand for agricultural labor variable continued all agricultural wages and the number of agricultural machinery, while the direct correlation between agricultural labor and between each of the crop area agricultural output and investment value of agricultural production requirements. 4- Several attempts to assess the relationship of multiple regression in the written form of the variables that are consistent with the signs of suspicious transactions linked to the age variable with economic logic, taking into account the not include any attempt to independent variables over the link them on the + 0.75 to overcome the problem of duplication pace. 5- On the basis in determining the best relations of multiple regression that reflect the relationship between the changing realities of the independent variables to the following: A-Moral relationship as a whole between independent variables and changing of the basis of the value of the (F). B-Moral transactions independent variables contained in the relationship on the basis of the value of the (T) of the transactions. C – a parameter value. D-Stroll the transactions signals the gradient of these variables with the economic logic. 6- On the basis of the best attempts have been the use of multiple regression progress report to stand the strongest variables on the impact of changing the subject of study. -26-


- A function of the demand for agricultural labor: Estimate was a function of the demand for agricultural labor in Egypt during the period (2000-2013) on the basis of the relationship between the number of agricultural workers variable continued in million workers, and a number of independent variables which are believed to have an impact on the agricultural labor, these variables are: X1=number of agricultural machinery, X2=agricultural investment, X3=proportion of agricultural wages to the non-farm, x4= agricultural output, x5= value of production requirements and x6=crop area. On the basis of the matrix of transactions simple link between independent variables and changing of the Table (1) indicate that the reference laboratories special link of the crop area (x4) was not in conformity with the economic logic therefore have been excluded from the study. Relational Database relations between independent variables and some other changing of: Given the difficulty of relational database relations between independent variables and some are some of the many variables used these relations table (1) indicate transactions matrix link between the model variables to the rise of link transactions between independent variables studied except for agricultural investment where results indicated that there is a correlation between the agricultural investments x2 and the rest of the variables in the study, which indicates that the volume of agricultural investment is still hinder the agriculture sector to achieve the goals of the desired development, where agricultural investment basic pillar to increase agricultural production and thus increasing agricultural exports and reduce imports, and thus to increase agricultural output and employment in this sector, the results also indicated that there is a correlation between the Agricultural Wages X3and the rest of the variables of the study. Table No. (1) a matrix of the link between the demand for labor and the variables affecting the in the written picture.

Farming

Agricultural machinery

Agricultural investments

Agricultural Wages

Agricultural output

Production requirements

Farming

1


-0.70

1

0.57

-0.66

1

Agricultural Wages

-0.64

0.27

-0.21

1

Agricultural output

0.88

-0.74

0.49

0.50

1


0.86

0.77

0.44

-0.39

0.94

1

The crop area

-0.86

-0.45

-0.26

-0.54

-0.86

0.89


The crop area

1

source: collector and calculated from table NO . (1) The regression relations between the number of workers and the specific factors: i. The relationship between the number of workers in the agriculture sector and gross domestic agricultural. Examining the relationship between the number of workers in the agriculture sector and gross domestic agricultural show an increase in the number of workers by 0.47 work unit by increasing gross domestic agricultural one unit, the increase represents about 0.0003% of the annual average of about 118402 million pounds. The following are the regression equation simple No.(1) to clarify the relationship between the number of workers in the agriculture sector and gross domestic agricultural. -27-


Y

^ i

= 17.7 + 0.47

X .........................................(1) i

(10.3)** (3.5)*

R 2 = 0.51 R −2 = 0.47 F = 12.3* Where: ^

Y i = The estimated value of the number of people working in agriculture during the year i.

Xi = The value of agricultural output during the year i, I =(1,2,3,......,14) ii.

The relationship between the number of workers in agriculture and agricultural investment. To study the relationship between the number of workers in agriculture and agricultural investment and reflect an increase of the number of people employed by 0.709 unity of action by increasing the agricultural investment one unit, the increase represents about 0.0086% of the annual average of around 8172.2 million pounds. The following are the regression equation simple No.(2) to clarify the relationship between the number of workers in the agriculture sector and agricultural investment. ^

Y

i

= 33.04 + 0.709 X i ………………………………..(2) (0.04) (2.4)*

R 2 = 0.32

R ‫ ـ‬2 = 0.27

F = 5.7 *

Where: ^

Y i = The estimated value of the number of people working in agriculture during the year i. Xi = The value of the agricultural investment during the year I ,i =.(1,2,3,......,14) iii. The relationship between the number of workers in the agriculture sector harvest area. Examining the relationship between the number of workers in the agriculture sector harvest area indicate an increase in the number of workers by 1293.88 work unit to increase the crop area the increase represents about 86.72% of the annual average of around 14.91 million feddans. The following are the regression equation simple No.(3) to clarify the relationship between the number of workers in the agriculture sector harvest area. ^ Y i = −13466.2 + 1293.88 X i …………………………………….(3) (−4.03) ** (5.84)**

R 2 = 0.74 R ‫ ـ‬2 = 0.71

F = 33.35**

Where: ^

Y i = The estimated value of the number of people working in agriculture during the year i.

The crop area during the year i, i = (1,2,3,......,14) iv. The relationship between the number of workers in the agriculture sector and the number of agricultural machinery. Examining the relationship between the number of workers in the agriculture sector and the number of agricultural machinery shows the lack of the number of people employed by 0.14 a work unit to increase the number ofagricultural machinery one unit, the increase represents about 0.018% of the annual average of about 783 thousand vending machine. The following are the regression equation simple No.(4) to clarify the relationship between the number of workers in the agriculture sector and the number of agricultural machinery Xi =

Y

^ i

= 16593.37 − 0.14 X i ………………………………(4) (5.25)**

(−3.4)**

-28-


R 2 = 0.49 R ‫ ـ‬2 = 0.45 F = 11.63** Where: ^

Yi =

The estimated value of the number of people working in agriculture during the year (i).

The number of agricultural machinery during the year i, i = (1,2,3,......,14) v. The relationship between the number of workers in the agriculture sector and the value of production requirements. Examining the relationship between the number of workers in the agriculture sector and the value of production requirements reflect an increase of the number of people employed by 0.04 a work unit to increase the value of production requirements and one unit, the increase represents about 0.0009% of the annual average of about 44050 million pounds. The following are the regression equation simple No. (5) to clarify the relationship between the number of workers in the agriculture sector and the value of production requirements. Xi =

Y

^ i

= 4259.9 + 0.04 X i ………………………………….(5) (14.48) **

(5.84)**

R 2 = 0.74 R ‫ ـ‬2 = 0.72 F = 34.12** Where: ^

Y i = The estimated value of the number of people working in agriculture during the year (i). Xi =

The value of production requirements during the year i, i =(1,2,3,......,14)

vi. The relationship between the number of workers in the agriculture sector, the proportion of agricultural wages to the non- farm. To study the relationship between the number of workers in the agriculture sector and the proportion of agricultural wages to the non- farm show a lack of the number of people employed by 76.79 work unit to increase the proportion of agricultural wages to the non-farm the increase represents about 115% of the annual average of about 66.3 Sew Institute. The following are the regression equation simple No. (6) to clarify the relationship between the number of workers in the agriculture sector and the proportion of agricultural wages to the non- farm. ^ Y i = 10921.48 + 76.79 X i ……………………………..(6) (6.08) **

(2.85) **

R 2 = 0.40 R ‫ ـ‬2 = 0.35

F = 8.12

Where: ^

Yi =

The estimated value of the number of people working in agriculture during the year (i).

Xi = The proportion of agricultural wages to the non- farm during the year i, i =(1,2,3,......,14) (2) Relations of multiple regression between the demand for agricultural labor and the factors affecting them: A-Attempts in the written picture : On the basis of a matrix Klein transactions simple link between explanatory variables on the one hand and the explanatory variables and changing the other hand shown in table (1) was excluded variable crop area (X4) the lack of compatibility of reference coefficient of his association with the economic logic, as demonstrated the existence of the problem of duplication between the pace of variables (x5 and x6) so saw not to enter these two variables in the equation of one, have accordingly been many attempts to get rid of the problem of duplication pace, and limited attempts in the written picture in four attempts as shown in table (2).

-29-


Reviewing the results of the different measurement for both the written image outlined the schedule (3), it is clear that humans attempts to multiple regression is try No. (4) The agenda No. (3) which came its image as follows: Y = 1073.06 − 0.008 x1 − 27.67 x3 + 841.7 x6 ……………..(4) ^

i

(1.89.) * (-4.26) ** (-3.40.) ** (0.24)

R 2 = 0.90 R ‫ ـ‬2 = 0.87

F = 28.82**

According to the results of the analysis to moral former model statistically at the level of 0.01 The parameter value specifically ratios ( R ‫ ـ‬2 ), which amounted to about 0.87 that about 87%of changes in demand for Agricultural employment to a change in the independent variables containing the combined model, which is the number of agricultural machinery (x1), the proportion of agricultural wages to the wages non-farm (x3), harvest area (x6), it was clear moral decline for the first and the second at the level of the moral 0.01, whereas moral proved coefficient of steep variable at 0.05 In order to obtain the strongest variables impact on the variable of the number of people working in agriculture in the Arab Republic of Egypt was invoked the regression method of the interim or gradual (stepwise former model where the results came as shown the recertification No. (7) which was its image as follows:

Y

^ i

= 4.26 + 3.56 X 5 ……………………(7)

(5.84) **

(14.48) ** R 2 = 0.74 R ‫ ـ‬2 = 0.72

F = 34.12**

According to the results of the analysis, the equation is unacceptable in terms of economic and statistical recalling the value (F) calculated to statistically moral at the level of the moral 0.01 The strongest independent variables impact on the demand for labor is the value of production requirements (x5), which the interpretation of about 74% of the changes in the demand for labor and an increase of 1% in the value it would increase the proportion of demand for employment of about 3.56%. B - Attempts in the picture logarithmic: Relational Database relations between independent variables and some are some of the variable in the picture logarithmic : The table No. (2) results of the attempts to measure the regressions in written picture of the demand for agricultural labor and the most important factors in Egypt during the period (2000-2013)

source: collector and calculated from table NO . Given the difficulty of relational database relations between independent variables and some are some of the many variables used these relations table (3) indicate transactions matrix link between the model variables to the rise of link transactions between independent variables studied except for agricultural investment where results indicated that there is a correlation between the agricultural investments x2 and the rest of the variables in the study, which indicates that the volume of agricultural investment is still hinder the agriculture sector to achieve the goals of the desired development, where agricultural investment basic pillar to increase agricultural production and thus increasing agricultural exports and reduce imports, and -30-


thus to increase agricultural output and employment in this sector, the results also indicated that there is a correlation between the Agricultural Wages x3 The rest of the variables of the study. Accordingly the results shown a matrix Klein transactions simple link between the different variables of the subject of the study in the picture double logarithmic table (3) was excluded variable agricultural output (X4) the lack of compatibility of reference coefficient of his association with the economic logic, as demonstrated the existence of the problem of duplication between the pace of variables (x5 and x6) so saw not to enter these two variables in the equation of one, have accordingly been many attempts to get rid of the problem of duplication pace, and limited attempts in the picture double logarithmic in four attempts as shown in table (4). The table No. (3):a matrix of the link between the demand for labor and the variables affecting them in the picture logarithmic. Agricultural machinery

Farming


Agricultural Wages

Agricultural output

The crop area


Farming

1


-0.69**

1


0.55*

-0.66*

1

Agricultural Wages

-0.60*

0.18

-0.16

1

Agricultural output

0.92**

-0.69**

0.44

-0.55

1


0.90**

-0.69

0.37

-0.39

0.97**

1

The crop area

0.87 **

-0.45

0.25

-0.49

-0.92**

-0.95**

1

source: collector and calculated from table NO (1). According to the results of the analysis to moral former model statistically at the level of 0.01 The parameter value specifically ratios ( R −2 ), which amounted to about 0.92 that about 92%of changes in demand for agricultural labor to a change in the independent variables containing the combined model, which is the number of agricultural machinery (x1), the proportion of agricultural wages to the wages nonfarm (x3), harvest area (x6), and reviewing the results of the different measurement for both the image logarithmicoutlined the schedule (4), it is clear that humans attempts to multiple regression is try No. (4) The agenda No. (4) that came to its image as follows:

Y

^ i

= 1.45 + 0.24 Logx 2 − 0.19 Logx3 + 0.22 Logx5 ……………….(4)

(7.66) ** (3.33.) **

(-2.90) *

(2.58) * R 2 = 0.94 R ‫ ـ‬2 = 0.92

F = 50.14**

According to the results of the analysis to moral former model statistically at the level of 0.01 The parameter value specifically ratios ( R −2 ), which amounted to about 0.87 that about 87%of changes in demand for agricultural labor to a change in the independent variables containing the combined model, which is the number of agricultural machinery (x1), the proportion of agricultural wages to the wages non-

-31-


farm (x3), harvest area (x6), it was clear moral decline for the first and the second at the level of the moral 0.01, whereas moral proved coefficient of steep variable at 0.05 In order to obtain the strongest variables impact on the variable of the number of people working in agriculture in the Arab Republic of Egypt was invoked the regression method of the interim or gradual (stepwise) former model where the results came as shown the recertification No. 6 (which was its image as follows: According to the results of the analysis, the equation is unacceptable in terms of economic and statistical recalling the value (F) calculated to statistically moral at the level of the moral 0.01 The strongest independent variables impact on the demand for labor is the value of production requirements (x5), which the interpretation of about 80% of changes in labor demand and an increase of 1% in the value it would increase the proportion of demand for employment of about 0.28%. The table No. (4) results of the attempts to measure the regressions in the picture logarithmicdemand for agricultural labor and the most important factors in Egypt during the period (20002013)

Source: collector and calculated from table NO(1) .

-32-


The Supplements Supplement No. (1) the development of agricultural machinery and investment and of output and the requirements of agricultural production harvest area, the proportion of agricultural wages to the non-farm agricultural employment. The Supplements

Years

agricultural machinery


agricultur al output

production requirements

The crop area

The proportion of agricultural wages to non-agricultural

Agricultur al Labor.

2000

0.76

8133.5

52840

20969

13.92

72.2

4.92

2001

0.8

8497.3

55,065

21119

14.03

70.7

4.97

2002

0.81

8693.5

58369

23772

14.35

75.6

5.02

2003

0.81

7104.0

63822

28306

14.47

70.3

5.08

2004

0.83

7359.0

69252

29293

14.55

65.1

5.16

2005

0.81

7220.0

75291.2

34083

14.9

64.5

5.24

2006

0.84

7981.8

81766.2

35053

14.92

71.8

5.33

2007

0.82

7791.2

99953.1

39638

15.18

65.4

5.43

2008

0.77

8972.5

113103.8

48911

15.24

63.6

6. 97

2009

0.79

8362.3

205464.6

51384

15.49

52.2

6.88

2010

0.75

8143.1

160969.6

58641

15.33

61.9

6.73

2011

0.71

9233.7

190159.3

70313

15.35

53.2

6.82

2012

0.75

7870.7

188216.2

76608

15.57

71.1

6.39

2013 Mediter ranean

0.71

9048.0

243355.5

78610

15.49

70.6

6.7

8172.2

118401.9 6

44050.00

14.91

66.30

5.83

0.78

Source: (1) The Central Agency for Public Mobilization and Statistics - Bulletin Search sample employment - Separate preparation. (2) The Ministry of Agriculture and Land Reclamation. Bulletin of agricultural machinery preparation of separate areas. (3) The Ministry of Planning. (4) The Ministry of Local Development. REFERENCES 1- Central agency for public mobilization and statistics labor force sample survey bulletin preparation sporadic 2- Ministry of Agriculture and land Reclamation - Agricultural machinery bulletin 3- The Ministry of planning. 4- The Ministry of local development .

-33-


DETERMINATION of THE YIELD RESPONSE to WATER for TWO DIFFERENT GLOBE ARTICHOKES CULTIVARS (Cynara Scolymus L. cv. Bayrampaşa and Starline F1) in GREENHOUSE CONDITIONS AHMET YILMAZ1, YEŞİM AHİ1,∗ 1Department of Biosystem Engineering, Faculty of Agriculture, Namık Kemal University, 59030 Tekirdağ, TURKEY * Corresponding author. Tel.: +90 282 2502263. E-mail address: [email protected](Y. Ahi)

ABSTRACT The research was conducted during the 2013/2014 cultivation season in Tekirdag Faculty of Agriculture. In the research, the response of artichoke plant, irrigated by drip irrigation method, to various amounts of irrigation water was determined and efforts were made towards developing the optimum irrigation schedule and water-yield-production factors under regional conditions. The trial was conducted in randomized complete block design, with regard to three different levels of irrigation and two different artichoke cultivars (Cynara scolymus L. cv. Bayrampasa and Starline F1), with 3 replications. Levels of irrigation were organized, based on the principal of monitoring the soil, so that irrigation would start when 40% of the available water holding capacity was exhausted and 100%, 70% and 40% of the moisture deficit would beapplied. Seasonal evapotranspiration values reached the highest in the fully irrigated (100%) subject, calculated as 797 mm and 811 mm for the cultivars Bayrampaşa and Starline F1 respectively. As a result of -1 the research, the highest artichoke yield was obtained from 100% irrigation level as 20.33 t ha for the -1 Bayrampaşa cultivar and as 33.69 t ha for the Starline F1 cultivar. In general, it was seen that various irrigation applications have statistically significant effects on yield. The highest values of irrigation water use efficiency (IWUE) were obtained from the irrigation level in which 70% of the irrigation need was met. Water -3 -3 use efficiency (WUE) rates ranged between 1.84 kg m and 2.55 kg m for the Bayrampaşa cultivar and -3 -3 between 2.62 kg m and 4.15 kg m for the Starline F1 cultivar. The water-yield relation factor was determined to be 1.37 for the total growing season. Keywords: Globe Artichoke (Cynara scolymus L.), drip irrigation system, water - yield production, crop water stress index (CWSI) INTRODUCTION Irrigation programming involves studies about determining when and how much irrigation to apply to a plant during its growing period. Within this scope; it is first needed to choose an irrigation method which is consistent with the climatic, soil, topographical and botanical conditions of the area, which allows efficient use of available water and will not cause yield decrease. Among irrigation methods, drip irrigation method comes forward in terms of uniform use of water, high efficiency, irrigation water saving and ease of operating, especially in the irrigation of vegetable and fruit trees. Today, all of Israel’s irrigated farming lands, 95% of those in France, 62% of those in Egypt and 50% of those in the U.S.A. are irrigated with pressured irrigation methods, including the drip irrigation method (www.icid.org). Although it is assumed to be roughly around 10% in our country, it is increasingly becoming more widely used. Both domestically and worldwide, a great deal of research has been conducted which will shed light on irrigation programming for various climatic and plant conditions. In some of these researches, irrigation pro.gramming of plants are carried out in a manner which monitors the moisture content of the soil and studies these assessments in conjunction with evapotranspiration and athmospheric relations. A lot of research has been completed on vegetable and fruits groups, which were irrigated with drip irrigation -34-


method and evaluated by taking plant-soil-atmosphere relations into consideration, such as broccoli, carrot, zucchini, radish (Imtiyaz et al., 2000); zucchini (Eliades, 1988; Randall and Locascio, 1988); tomato (Locascio and Smajstrla, 1996); potato (Panigrahi et al., 2001; Ferreria and Carr, 2002; Ünlü et al., 2006); strawberry (Yuan et al., 2004) and artichoke (Boari et al., 2012) and it has been clarified that this method yields quick and practical results. As artichoke, cultivated in large areas in Mediterranean countries and consumed in considerable amounts, is a very good diet vegetable which is rich in protein, vitamins and nutrients, the demand for this vegetable type is rapidly growing. Since it is beneficial for human health, artichoke is commonly used in pharmaceutical industry as well. It is declared that artichoke has positive effects against heart diseases, cancer and liver diseases (Krauss et al.,1996). In artichoke cultivation, water-production functions must be known very well in order for the yield to be highly efficient and of high quality. As it is necessary to develop a favorable irrigation program in order to be able to generate alternative production under irrigated conditions and also in greenhouse conditions, in regions where water sources are scarce and the aim is to achieve high quality and high efficiency with the available water the applicability of current artichoke production under specific region conditions has been inquired, through the detailed study of soil, plant and water relations and with resulting data that can be used as a base for new research. MATERIALS AND METHODS The research was conducted during the years 2013-2014 in the city of Tekirdağ, in Namık Kemal University Faculty of Agriculture Research Greenhouse. Each trial parcel, sized 4.0 m x 3.0 m, covers a 2

total of 12.0 m -space and consists of 4 plant rows. The inter-row and above-row is 1.00 m. The soil type is deep, heavy textured, well-drained and the available water holding capacity within 0.90 m of the soil profile is approximately 0.17 m. The electrical conductivity (EC) of irrigation water was classified as C1S1 according to U.S. Salinity Lab. (US Salinity Laboratory Staff, 1954). In the research greenhouse, climatic elements were monitored throughout the cultivating period from the meteorology station that was placed into the greenhouse. Irrigation system was composed of water source, fertilizer tank, screen filter, pipelines and drippers, respectively. The irrigation water needed for the irrigation of research parcels was taken from a nearby city feeder into the system. In the research, soil moisture change was monitored via tensiometers. For this purpose, tensiometers of SR model, manufactured by Irrometer company were used. For moisture assessments, in conformity with the principles stated in Güngör and Yıldırım (1989), 2 tensiometers were fixed into the the trial parcels so as to go 30 cm and 60 cm deep into the soil. Prior to the initiation of the study, tensiometer calibration was done under field conditions and equations were formulated for each 30-cm-layer. The artichoke cultivars that were used in the research were the so-called Bayrampasa and Starline F1. The cuttings of cv. Bayrampaşa were obtain from underground stem of dormant plants. The seedlings of cv. Bayrampaşa and cv. Starline F1 were transplanted into the plots in early September. The Starline F1 is an early season cultivar with high yield and strong root and stem structures. The Bayrampaşa cultivar has quite large and flattened heads with brownish-red bracts. The fact that it is a late season cultivar decreases its level of freshconsumption. The experimental design was a split plot replicated three times. The experiments consisted of two cultivars (main plots) and three irrigation levels (sub-plots). These are; Main plot: V1 : Bayrampaşa cultivar V2 : Hibrit Starline F1 cultivar Sub plot: I100 : The subject which was irrigated so much as to increase the level of moisture to match the field capacity when 40% of the available water holding capacity is consumed, -35-


I70 : The subject to which 70% of the amount of irrigation water applied to subject I1 was applied, I40 : The subject to which 40% of the amount of irrigation water applied to subject I1 was applied. Irrigation water was applied to plots with drip irrigation. The percentage of wetted area was realized as 50%. Effective root depth was 60-90 cm and evapotranspiration rates were calculated with respect to 90 cm soil depth, according to water budget approach (Walker and Skogerboe, 1987). Starline F1 seedlings and Bayrampasa underground buds were planted by hand into the parcels of which the field preparation was completed on September 20th, 2013 (DOY 263). Yield harvest was done when the crown diameter generally reached approximately 13 cm in the year 2014, between March 20th25th (DOY 79-84). Produce samples taken from each parcel were taken to the laboratory and physical measurements werecompleted Water-yield functions were determined (Howell et al., 1990) with reference to the relations between applied irrigation water and measured evapotranspiration, and harvest efficiency. Irrigation water use and water use efficiency rates were calculated based on the irrigation water applied to trial subjects, measured evapotranspiration and harvest efficiency values (Zhang et al., 1999). In addition, water-yield relation method which is known as the Stewart model (Doorenbos and Kassam 1979, Korukçu and Kanber 1981) was used in order to determine the effect of water deficit on harvest yield. The variance analysis of the data obtained from the research, the significance control of the variations between the averages, the correlations between the characters studied were determined according to the principals stated in Yurtsever (1984) and Düzgüneş et al. (1987) using SPSS8.0. RESULTS AND DISCUSSION Throughout the cultivation period, the climatic elements taken from the meteorology station located within the greenhouse are graphed in Figure 1. As it can be seen on the figures, in parallel with the increase in the interior temperature of the greenhouse, soil temperature and leaf surface temperatures in the greenhouse showed an increase whereas relative moisture values showed a decrease. Interior temperature values showed the same tendency as the changes in outer temperature. The maximum interior temperature value was measured as 35°C in the month March while the minimum interior temperature value was measured as 1.7 °C in the monthDecember. The growth periods and growing season lengths for the year 2013/2014 is shown in Figure 2. As can be followed on the figure, it took the crop approximately 116 days to reach the first harvest maturity in 2014 within the fruit growth period The whole growing season was completed in 281 day. In the research, the growth periods of the artichoke plant were defined as early vegetative growth period (1a, leaf growth), late vegetative growth period (1b, leaf growth, sub-branch formation, flower bud formation), generative growth period (flowering, fruit formation, maturity) and the period of loss in vegetative parts. When researches conducted under different regional conditions and with different artichoke types, the growing period is completed about 270 days and subsequently left to rest for 3 months (Vural ve ark. 2000, Prohens ve Nuez 2008). Evapotranspiration Results Seasonal total evapotranspiration values, calculated according to water budget approach and with respect to the amounts of applied irrigation water and rates of changes in soil moisture for all treatments during the cultivation periods, are summarized in Table 1. As can be seen on the table, the highest amount of irrigation water and the highest evapotranspiration belong to subject I100 in both varieties. The evapotranspiration values measured in the trial subjects throughout the whole growing season ranged between 435.8 mm and 796.5 mm for the Bayrampasa -36-


cultivar, and between 431.4 mm and 811.4 mm for the Starline F1 cultivar. The seasonal evapotranspiration of the artichoke cultivar grown by Cantore et al. (2013) in Bari-Italy under lysimeter conditions was 967 mm for the first year and 911 mm for the second year. Results concerning yield and yield components Artichoke yield and some physical yield parameters and results of variance analyses onthe parameters are presented in Table 2 for each treatment andvarieties. The highest average yields for the cultivars Bayrampasa and Starline F1 were obtained as -1 -1 respectively 20.33 t ha and 33.69 t ha in subject I100. Whereas the lowest average yields for both -1 cultivars were seen to take place in subject I40 to which 40% irrigation was applied, as 8.00 t ha and 11.32 t ha-1 respectively. According to variance analysis results; variance among difference irrigation application levels and cultivars statistically showed a significance of 0.05 and cultivar * irrigation level interaction was found to be insignificant. According to the Duncan test results, which is performed in order to determine the level of variance, each cultivar and irrigation level constituted a different group where the fully irrigated subject I100 formed the first group and subject I40 formed the last one with the lowest yield. Also, some yield parameters such as total head number and head weight showed a significance of 5% among the irrigation levels while the differences were not significant among the cultivars. When the world average yield value of artichoke is assessed on the basis of countries; it is seen that Argentina and Egypt have the highest yield with 23 t ha-1, followed by Uzbekistan, Cyprus and Peru with approximately 20 t ha-1. The yield values obtained in the artichoke study conducted by Munich Technical University (Saleh 2003) in Germany ranged between 14.64 – 21.07 t ha-1, while they ranged between 11.9 – 19.9 t ha-1 in the study conducted by Garnica et al. (2004) in Spain and between 10 – 11.4 t ha-1 in the study conducted in Italy by Boari et al. (2012). The yield average in Turkey is around 12 t ha-1 (Anonymous 2013; Bektaş and Saner, 2013). Seasonal water-yield relation is graphed in Figure 3. The water-yield relation factor (ky) of the artichoke plant was found to be 1.37 for the cultivars Bayrampasa and Starline F1. According to these results, it is clear that, as explained in theory in Doorenbos and Kassam (1979), water limitation to be implemented throughout the whole growing season, or in other words, artichoke cultivation under dry conditions, will face yield loss. According to the above mentioned graph, it can be said that when a 25% of proportional water consumption deficit is generated throughout the total growing season a 34% yield decrease will be seen, while this would increase to 69% when the proportional water consumption deficit is50%. As it can be seen on Table 1, IWUE and WUE values decrease as the irrigation water level decreases. Statistically, the variance between the cultivars in terms of IWUE and WUE values showed 5% significance, whereas the variance among irrigation subjects was found to be insignificant. The highest irrigation water use efficiency (IWUE) values for the -3 cultivarsBayrampasaandStarlineF1wereobtainedfromsubjectI70 as2.63kgm and -3, 4.47 kg m respectively, while the lowest IWUE values were obtained from subject I 40 as -3 -3 2.58 kg m and 3.54 kg m , respectively. In the optimum subject, the IWUE values for the cultivars -3 -3 Bayrampasa and Starline F1 were calculated as 2.62 kg m and 4.21 kg m , respectively; whereas the -3 -3 WUE values were found to be 2.55 kg m and 4.15 kg m , respectively.

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CONCLUSIONS The fact that yield values obtained from the fully irrigated subject I100 were considerably greater than those obtained from subject I 40, which was subjected to maximum limitation, clearly exhibits the importance of irrigation for artichoke cultivation. Irrigation water use efficiency and water use efficiency values varied depending on irrigation levels. Generally, as the amounts of applied irrigation water decrease, irrigation water use efficiency and water use efficiency showed a decrease in both varieties. When yield and efficiency results are taken into consideration together, while statistically variance is seen between the cultivars, no significant variance is found among the subjects. Therefore, in terms of obtaining maximum yield in artichoke cultivation, the fully irrigated subject (I100) can be recommended. And in cases where water source capacity is limited, it can be said that the option of limiting irrigation water can be taken for saving purposes, provided that level of this limitation should not exceed 30%. Consequently, scientific data which will support the water-yield functions and irrigation programming of artichoke was obtained in the study. It is expected that the findings will be useful for the researchers and investors who will work in this subject. REFERENCES Anonymous (2013). Türkiye İstatistik Kurumu Veritabanı. Ankara. (http://www.tuik.gov.tr) Bektaş ZK ve Saner G (2013). Türkiye’de Enginar Üretimi ve Pazarlaması. U. Ü. Ziraat Fakültesi Dergisi (Journal of Agricultural Faculty of Uludag University), 2013, Cilt 27, Sayı 1, 115-128 Boari F, Bernardo P, Todorovic M, De Palma E ve Cantore V (2012). Effect of water regime and salinity on artichoke yield. Italian J. of Agron., 7 (e9): 58-63. Cantore V, Todorovic M, Schiattone MI ve Boari F (2013). Modelling evapotranspiration of seed propagated Globe Artichoke in a Mediterranean environment. 1st CIGR Inter-regional conference on land and water challenge. Mediterranean Agronomic Institute of Bari Doorenbos J, Kassam AH (1979). Yield Response to Water. FAO Irrigation and Drainage Paper No: 33, Rome,Italy. Düzgüneş O, Kesici T, Kavuncu O, Gürbüz F (1987). Araştırma ve Deneme Metotları (İstatistiksel Metotları-II). Ankara Üniversitesi Ziraat Fakültesi Yayınları No. 1021. Ankara. Eliades G (1988). Irrigation of greenhouse-grown cucumbers. J. Hortic. Sci. 63 (2), 235–239. Ferreria TC, Carr MKV (2002). Response of Potatoes (Solanum tuberosum L.) to Irrigation and Nitrogen in a Hot, Dry Climate. I. Water use. Field Drops Research, 78, 51-64. Garnica J, Macua JI, Lahoz I ve Malumbres A (2004). Influence of irrigation in the production and industrıal quality of artichokes in Navarra. Acta Horticulturae 660: V International Congress on Artichoke. Güngör Y, Yıldırım O (1989). Tarla Sulama Sistemleri. Ankara Üniversitesi Ziraat Fakültesi Yayınları No. 1155. 371s.Ankara. Howell TA, Cuenca RH, Solomon KH (1990). Crop Yield Response. in Management of Farm Irrigation System, Eds. Gj, Hoffman, Ta, Howell, Kh, Solomon. St. Joseph, Mich.: Asae. Imtiyaz M, Mgadla NP, Chepete B, Manase SK (2000). Response of six vegetable crops to irrigation schedules. Agric. Water Manage. 45, 331-342. Korukçu A ve Kanber R (1981). Water-yield relationship. Soil-Water Main Project 435-1, Tarsus Krauss RM, Deckelbaum RJ ve Ernst N (1996). Dietary guidelines for Healty American Adults. A Statement for Health Professionals from The Nutrition Committees American Heart Association, 94; 1795-1800. Locascio SJ ve Smajstrla AG (1996). Water Application Scheduling by Pan Evaporation for DripIrrigated Tomato. J. Am. Soc. Hortic. Sci. 121(1), 63–68. Panigrahi B, Panda SN ve Raghuwanshi NS (2001). Potato water use and yield under furrow irrigation. Irrigation Sci. 20(4), 155–163.

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Prohens J ve Nuez F (2008). Globe Artichoke and Cardoon. Vegetables I, Asteraceae, Brassicaceae, Chenopodicaceae and Cucurbitaceae. Springer. California, U.S.A. Randall HC ve Locascio SJ (1988). Root Growth and Water Status of Trickle-İrrigated Cucumber and Tomato, J. Am.Soc. Hortic. Sci. 113(6), 830–835. Saleh SAHAA (2003). Physiological Responses of Artichoke Plants to İrrigation and Fertilization under Spesial Recognition of Salinity. Technische Universitat München, Ph.D. Thesis, pp:158. US Salinity Laboratory Staff (1954). Diagnosis and improvement of saline and alkali soils. US Dep. Agric., Handbook 60. Ünlü M, Kanber R, Şenyiğit U, Onaran H ve Diker K (2006). Trickle and Sprinkler Irrigation of Potato (Solanum Tuberosum L.) in The Middle Anatolian Region in Turkey. Agric.Wat. Manage. 79,4371. Vural H, Eşiyok D ve İ.Duman, (2000). Kültür Sebzeleri (Sebze Yetiştirme), Ege Üniversitesi Ziraat Fakültesi Bahçe Bitkileri Bölümü, İzmir, 394-408. Walker WR ve Skogerboe GV (1987). Surface Irrigation. Theory and Practice. Prentice- Hall, Englewood Cliffs, 375pp, New Jersey. Yuan G, Luo Y, Sun X ve Tang D (2004). Evaluation of a crop water stres index for detecting water stres in winter wheat in the North China plain. Agric. Wat. Manage. 64: 29-40. Yurtsever N (1984). Deneysel İstatistik Metotları. Köy Hizmetleri Genel Müd. Yayınları No:56, Ankara. Zhang Y, Kendy E, Qiang Y, Changming L, Yanjun S ve Hongyong S (1999). Effect of soil water deficit on evapotranspiration, crop yield, and water use efficiency in the north China plain. Agric. Water Manage. 64: 107-122.

(a)

(b) (c) Figure 1. Climatic factors inside the greenhouse (a, b, c)

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Figure 2. Growth periods of artichoke

Figure 3. Yield response factor, ky, for total growing period (V1:Bayrampaşa; V2: Starline F1)

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Table 1. Effect of irrigation treatment and years on irrigation characteristics Main effect

Soil water depletion

Irrigation water Seasonal applied evapotranspiration (mm)

(mm)

Bayrampaşa

I100 I70 I40

-1 (mm90cm ) 22 87 126

775 542 310

Starline F1

I100 I70 I40

12 85 112

Variety

IWUE

WUE

797 629 436

2,62ns 2,63 2,58

2,55ns 2,26 1,83

799

811

4,21ns

4,15ns

560 320

645 431

4,47 3,54

3,88 2,62

: Significant at the P < 0.05, **: Significant at the P < 0.01 and ns: notsignificant Table 2. Yield and yield parameters of artichoke Variety

Bayrampaş

Starline F1

Main effect I100 I70

Marketable yield -1 (t ha ) 20,33 14,25

Total head number

Head weight (g)

Head Receptacle diameter diameter (cm) (cm)

Receptacle weight (g)

Stem thickness (cm)

4,0 2,8

466,71 446,88

12,69 12,09

8,51 7,27

78,57 54,64

2,01 2,21

I40

8,00

1,9

389,08

12,29

7,31

56,02

2,60

I100 I70

33,69 24,99

6,0 4,5

490,26 487,71

12,46 12,61

7,68 7,14

61,88 52,99

2,58 2,53

I40

11,32

1,3

440,69

12,22

7,89

71,12

2,05

ns

ns

ns

ns

ns

*

2,9a 4,3b

434,23a 472,88b

12,36 12,43

7,69 7,57

63,07 61,90

2,27 2,38

*

*

ns

ns

ns

ns

ns Bayrampaş Starline F1

14,19a 23,33b * I100 I70

27,01a 19,62b

5,0a 3,7b

478,48a 467,29b

12,57 12,35

8,09 7,21

70,22 53,81

2,29 2,37

I40

10,19c

2,1c

414,88c

12,26

7,60

63,56

2,33

*

*

ns

ns

ns

ns

*

: Significant at the P < 0.05, **: Significant at the P < 0.01 and ns: notsignificant

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ANTIMICROBIAL RESISTANCE PATTERNS OF ESCHERICHIA COLI ISOLATES FROM BROILER FLOCKS IN ARDABIL PROVINCE TO SIX ANTIBACTERIAL AGENTS COMMONLY USED IN THE IRANIAN POULTRY INDUSTRY

AIDIN AZIZPOUR1, ZAHRA AMIRAJAM2 1. Poulry Diseases, Meshginshahr Faculty of Agriculture, University of Mohaghegh Ardabili, Ardabil, Iran. 2.Imam Khomeini Hospital of Ardabil, Ardabil University of Medical Sciences, Ardabil, Iran. Corresponding author's Email: [email protected]

ABSTRACT Colibacillosis is one of the most prevalent bacterial diseases in poultry with huge economic losses that is caused by Escherichia coli. Antimicrobial therapy is an important tool in reducing both the incidence and mortality associated with colibacillosis. But, enormous use of antibiotics in poultry medicine has been increased the number of resistant bacterial strains in recent years. The purpose of this study was to investigated the antimicrobial resistance pattern of 178 E.coli isolates from 40 broiler flocks with colibacillosis clinical signs in ardabil province, northwest of Iran. The antimicrobial susceptibility of total isolates to six antibacterial agents commonly used in the Iranian poultry industrywas tested from March 2014 to February 2015. These antibacterial agents include Colisten, Doxycycline, Sulfamethoxazole + Trimethoprime, Enrofloxacin, Florfenicol and Lincospectine. According to disk diffusion method, the maximum resistance was to Doxycycline (81.47%), Enrofloxacin (77.53%), Sulfadiazine + Trimethoprime (71.91%), Colistin (68.54%), Florfenicol (58.99%), Lincospectine (36.52%), respectively. The results of this study showed the high frequency of resistance to antimicrobial agents commonly used in the Iranian poultry industry. It can attributed to the incorrect use of antibiotics in poultry industry. So, National monitoring programs is strongly needed for antimicrobial resistance and for a rational use of antibiotics. Keywords: E.coli, Broiler Flocks, Antibiotic Resistance, Ardabil Province INTRODUCTION Escherichia coli is the most important agent causing secondary bacterial infection in poultry and may also be a primary pathogen (Saif, 2003). Colibacillosis that is caused by avian pathogenic Escherichia coli (APEC) is the most frequently reported disease in surveys of poultry diseases or condemnations at processing (Saif, 2003). It is responsible for large economic losses in poultry industry worldwide (Hammoudi and Aggad, 2008). Antimicrobial therapy is an important tool in reducing both the incidence and mortality associated with avian Colibacillosis (Watts, et al., 1993; Guerra, et al, 2003; Miles, et al, 2006). But, enormous use of antibiotics in poultry medicine has been increased the number of resistant bacterial strains and loss of the efficacy of treatments in recent years. (Hammoudi and Aggad, 2008; Madadi et al., 2014). The purpose of this study was to determined the antimicrobial resistancepattern among a collection of avian pathogenic E. coli recovered from broiler flocks diagnosed with colibacillosis in ardabil province, northwest of Iran during 2014-2015. MATERIALS AND METHODS Bacterial isolates Isolation and identification of E. coli were performed by conventional bacteriological methods (Hammoudi and Aggad, 2008). 178 E.coli isolates were collected from 40 broiler flocks with colibacillosis clinical signs in ardabil province, northern of Iran from March 2014 to February 2015.The antimicrobial susceptibility of these isolates to six antibacterial agents commonly used in the Iranian poultry industry were testedby disk diffusion method (Bozorgmehri Fard et al., 2008). -42-


Antibacterial agents Antibacterial agents that are commonly used in the Iranian poultry industry include Colistin, Doxycycline, Enrofloxacin, Florfenicol, Lincospectine and Sulfadiazine + Trimethoprime. RESULTS Antimicrobial resistance patterns observed for isolates are shown in Table 1. Among E. coli isolates, the maximum resistance was to Doxycycline, Enrofloxacin, Sulfadiazine + Trimethoprime (Sultrim), Colistin, Florfenicol and Lincospectine, respectively. The highest and lowest resistance frequencies were observed to Doxycycline (81.47%) and to Lincospectine (36.52%), respectively. Table1. Antibiotic resistance patterns of 178 E.coli isolates to six antimicrobial agents Antimicrobial agents

Doxycycline

81.47

% of isolate Intrmedate Susceptible 16.85

Enrofluxacine

77.53

13.48

8.99

Trimethoperim /Sulfamethoxazol Colsitin

71.91

11.80

16.29

68.54

24.16

7.30

Florfenicol

58.99

12.92

28.09

Lincospectine

36.52

22.47

41.01

Resistant

Susceptible 1.68

DISCUSSION E. coli may be sensitive to many antibiotics (Bozorgmehri Fard et al., 2008; Khoshkhoo and Peighambari,2005). However, isolates of E. coli from poultry are frequently resistant to one or more antibiotics, especially if they have been widely used in poultry industry over a long period (e.g., tetracyclines) (Watts et al., 1993; Blanco et al., 1997; Madadi et al., 2014). Khoshkhoo and Peighambari (2005) reported that 96.7%, 94%, 72.6%, 66%, 64.7% and 46.7% of 150 E. coli isolates were resistant to colistin, tetracycline, sulfamethoxazole + trimethoprime, enrofloxacin, Lincospectine and florfenicol, respectively (6). Zahraei and Farashi (2006) observed that among 50 E.coli isolates from broiler flocks the antimicrobial resistance patterns include doxycycline (88%), sulfamethoxazole + trimethoprime (80%), enrofloxacin (76%), florfenicol (27%), Lincospectine (15%), and colistin (6%), respectively (13). In the period of 2005-2006, the frequencies of resistance od 103 E.coli isolates to Antibacterial agents were as follows‫׃‬colistin 100%, tetracycline 96%, lincospectine 79%, enrofloxacin 76% and florfenicol 39%. (Saberfar et al., 2008). Resistance frequencies of 54%, 43%, 33% and 1.2% to enrofloxacin, tetracycline, Sultrim and lincospectine were observed among 72 E.coli isolates sampled in 2005, respectively (Bozorgmehri Fard et al., 2008). In more comprehensive study in eight provinces, the maximum resistance was to sulfamethoxazole + trimethoprime (67%), doxycycline (60%), enrofloxacin (42%), colistin (35%) and florfenicol (34%), respectively (Ghaniei and Peighambari, 2011). A recent study from northwest of Iran in 2014, the lowest resistant antibiotics were florfenicol (2006-2008) and lincospectine (2009-2011), While tylosin (2006-2008) and erythromycin and tetracycline (2009-2011) were the most resistant (Madadi et al., 2014). A report from Northern Georgia indicated that the majority of 95 APEC isolates displayed resistance to sulfamethoxazole (93%), tetracycline (87%), and enrofloxacin (52%) (Zhao et al., 2005). In this study, all the E. coli isolates showed high frequency of resistance to the six antibacterial agents commonly used in the Iranian poultry industry. Similar to the findings of previous studies had done in Iran and other countries, multiple antibiotic resistances was observed in all of the examined strains (Blanco, -43-


et al., 1997; Guerra et al., 2003; Miles, et al, 2006; Zahraei and Farashi, 2006; Hammoudi and Aggad, 2008; Madadi et al., 2014). This is most probably due to increased use of antibiotics (Madadi et al., 2014). Antimicrobial-resistant pathogens pose a severe and costly animal health problem in that they may prolong illness and decrease productivity through higher morbidity and mortality (Xu, 2001). In addition, there is also concern that antimicrobial use in food animals can lead to the selection of antimicrobial resistant zoonotic enteric pathogens which may then be transferred to people by the consumption of contaminated food (especially poultry) or by direct animal contact(Saberfar et al., 2008; Madadi et al., 2014). Therefore, National monitoring programs is strongly needed for antimicrobial resistance and for a rational use of antibiotics. Also antibiotics sensitivity test is suggested in order to find out an overview of antimicrobial susceptibility pattern in all provinces

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REFERENCES 1.Blanco, J. E., Blanco, M., Mora, A., Blanco, J. 1997. Prevalence of bacterial resistance to quinolones and other antimicrobials among avian Escherichia coli strains isolated from septicemic and healthy chickens in Spain. J. Clin. Microbiol. 35: 2184–2185. 2.Bozorgmehri Fard, M.H., Karimi, V., Fathi, E., Behmanesh, R. 2007. Bacteriologic survey on infectious cellulitis in broiler chickens in Masjid Soleiman slaughterhouse, Iran. Arch. Razi. Inst. 62: 91-95 3.Ghaniei, A. Peighambari SM, 2011. Antimicrobial susceptibility of one thousand bacterial isolates to five antibacterial agents commonly used in the Iranian poultry industry. Iranian. J. Vet. Med. 6: 1-5. 4.Guerra, B., Junker, E., Schroeter, A., Malorny, B., Lehmann, S., Helmuth, R. 2003. Phenotypic and genotypic characterization of antimicrobial resistance in German Escherichia coli isolates from cattle, swine and poultry. J. Antimicrob. Chemother. 52: 489–492. 5.Hammoudi, A., Aggad, H. 2008. Antibioresistance of Escherichia coli Strains Isolated from Chicken Colibacillosis in Western Algeria, Turk. J. Vet. Anim. Sci. 32(2): 123-126. 6.Khoshkhoo, P.H., Peighambari, S.M. 2005. Drug resistance patterns and plasmid profiles of Escherichia coli isolated from cases of avian Collibacilosis. Iranian. J. Vet. Med. 60: 97-105. 7.Madadi,M.S.,Ghaniei,A.,Zare, P.,Isakakroudi N. 2014. Antimicrobial Susceptibility Pattern of Escherichia Coli Isolates to Antibacterial Agents in Urmia, Iran. Inter. J. Bas. Sci. Appl. Res. 3 (10): 695697. 8.Miles, T. D., McLaughlin, W. M., Brown, P.D. 2006. Antimicrobial resistance of Escherichia coli isolates from broiler chickens and humans. BMC Veterinary Research, 2, 7. 9.Saberfar, E., Pourakbari, B., Chabokdavan, K., Taj Dolatshahi, F. 2008. Antimicrobial Susceptibility of Escherichia coli Isolated from Iranian BroilerChicken Flocks, 2005–2006. J. Appl. Poult. Res. 17: 302– 304. 10. Saif, YM. 2003. Disease of poultry. 11th edition. Lowa State press, A Black well publishing company. PP, 631-652. 11.Watts, J. L., Salmon, S. A., Yancey, R. J., Nersessian, B., and Kounev, Z. V. 1993. Minimum inhibitory concentrations of bacteria isolated from septicemia and airsacculitis in ducks. J. Vet. Diagn. Invest. 5: 625–628. 12.Xu, S. 2001. Actions China needs to take in response to the emergence of antimicrobial resistance. Chinese. J. Vet. Drugs. 35: 39–41. 13.Zahraei, S.T., Farashi, B.S. 2006. Antibiotics Susceptibility Pattern of Escherichia coli Strains Isolated from Chickens with Colisepticemia in Tabriz Province, Iran. Inter. J. Poul. Sci. 5 (7): 677-684. 14.Zhao, S., Maurer, J.J., Hubert, S., De villena, J.F., McDermott, P.F., Meng, J., et al. (2005) Antimicrobial susceptibility and molecular characterization of avian pathogenic Escherichia coli isolates. Vet. Microbiol. 107: 215-224.

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EFFECTS OF LOW AND HIGH FREQUENCY ULTRASOUNDS ON HATCHABILITY AND EMBRYONIC MORTALITY IN BROILER HATCHING EGGS ALI AYGUN, ISKENDER YILDIRIM Selcuk University, Agricultural faculty, Department of Animal Science, Konya, Turkey.

ABSTRACT Ultrasound device are used for efficient cleaning purposes in laboratories, for dissolving, dispersing and in many other areas by creating sound waves in water. The purpose of this study was to establish the effects of low and high frequency ultrasound on hatchability and embryonic mortality in broiler hatching eggs.A total of 416 eggs were randomly divided into four groups. Treatments were no ultrasound but the eggs were incubated for 15 min in water (Control), the eggs were not applied with ultrasound but sprayed with benzalkonium chloride solution (B), ultrasound was applied to eggs with 35 kHz for 15 min (U35) and ultrasound was applied to eggs with 130 kHz for 15 min (U130).There were no significant differences among treatments for hatchability and embryonic mortality (P>0.05). Keywords: Ultrasonic application, hatchability, embryonic mortality, broiler hatching eggs, INTRODUCTION Ultrasound device are used for efficient cleaning purposes in laboratories, for dissolving, dispersing and in many other areas by creating sound waves in water.Recently, ultrasonic devices have also been used in the food industry as a quality measurement of foods (Mizrach et al., 2000; Mizrach, 2007), food preservation (Knorr, 2004; Ordonez et al., 2009; Sertet al., 2011; Caner and Yuceer, 2015), inactivation of microorganisms (Joyce et al., 2003; Yuan et al., 2009; Sert et al., 2011; Sertet al., 2013), and hatching eggs (Aygun and Sert, 2012; Shafey et al.,2013;Yildirimet al., 2015).The structure and function of biological molecules can be changed by the ultrasound irradiation. Most common interaction mechanisms involved in this case are either heat or chemical effects and acoustically induced cavitational activity (Yaldagardet al., 2007). Ultrasonic treatment can make a positive impact on embryo development good hatchability, and therefore enhance the possibility to obtain high-quality and healthy chicks. The aim of this study was to examine the effects of ultrasonic of 35 kHz and 130 kHz frequency on hatchability and embryonic mortality in broiler hatchingeggs. MATERIALS AND METHODS Sampling and Storage In total, 416 fresh eggs (unwashed, feces-free) were obtained from broiler breeders (40 wk of age Ross-308) that were raised on a local commercial farm (Bolu, Turkey). The broiler breeders were fed a breeder diet (2,757 kcal of ME/kg and 18.60% CP). Food and water were provided ad libitum. All eggs were collected over a 24-h period and stored at room temperature (20 ± 2°C) overnight before the ultrasonic treatments. Ultrasonic Equipment and Treatments Treatments were applied in an ultrasonic bath (Transsonic TI-H-15; power, 200 W; Elma, Singen, Germany). Eggs were sunk into an ultrasonic bath with pure water. Eggs were treated with ultrasonic wave for 15 min at a temperature of approximately 22°C. Treatments were no ultrasound but the eggs were incubated for 15 min in water (Control), the eggs were not applied with ultrasound but sprayed with benzalkonium chloride solution (B), ultrasound was applied to eggs with 35 kHz for 15 min (U35) and ultrasound was applied to eggs with 130 kHz for 15 min (U130).

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Incubation Management Eggs were incubated in a commercial incubator with a dry-bulb temperature of 37.5°C and 60 % relative humidity until d 18 of incubation when incubator condition were changed to 37.2°C and 75% relative humidity. Eggs were turned once every 2 h. At 14 day of incubation, the eggs transferred to hatch baskets. The total 416 eggs were used in 4 treatments with 104 eggs examined in each. There were a total of 26 eggs for each replication. Statistical Analysis An analysis of variance was carried out in order to compare means of the studied traits for treatments. All statistical analyses were carried out using Minitab version 14. RESULTS AND DISCUSSION The effects of treatments on incubation results are shown in Table 1.There were no foundno significant differences among groups for hatchability of set (C, 86.82; B, 91.33%;U35, 85.14 %; U130, 81.14 %; P >0.05), or hatchability of fertile eggs (C, 90.83;B, 91.97%; U35, 86.89%; U130, 84.49 %; P >0.05). There was no significant increase in embryonic mortality at any stage of incubation in any treatment group (see Table 1). These results are in agreement with Aygun and Sert (2012) and Yildirimet al., (2015) who found that ultrasonic treatments did not significantly affect quail hatching eggs’ hatchability and embryonic mortality. Similarly, Fasenkoet al. (2009) found no significant differences in hatchability and embryonic mortality between an electrolyzed oxidizing water treatment and control group. In contrast, Shafeyet al. (2013) found that ultrasonic waves of 117 V at 40 kHz for 15 min reduced the hatchability of layer-type breeder eggs. Table1. Effects of pre-incubation application of low and high frequency ultrasound on Hatchability and embryonicmortality. Embryonic mortality Hatchability Hatchability (% of fertile eggs) Treatment of set eggs, % of fertile eggs, % 1 to 9 d 10 to 21 d 3.45 5.73 86.82 90.83 C 4.31 3.73 91.33 91.97 B 5.63 7.48 85.14 86.89 U35 7.44 8.07 81.14 84.49 U130 SEM 3.30 2.33 4.55 4.55 P-value 0.840 0.569 0.488 0.640 C= No ultrasound, but treated with water; B= Benzalkonium Chloride; U35= Ultrasonic treatment for 15 min at 35 kHz; U130= Ultrasonic treatment for 15 min at 130 kHz. CONCLUSIONS The current results show that using ultrasound to treat eggs did not negatively affecthatchability, embryonic mortality, chick performance, or chick survival. Though we did not collect specific data on this point, we saw no evidence that ultrasound negatively affected the environment. Ultrasound technology can be used as a safe and effective alternative todisinfecting hatching eggs with chemicals. The new studies should be focused on microbial effectiveness of the Ultrasound as well as incubation results. REFERENCES Aygun, A., and D. Sert. 2012. Effects of ultrasonic treatment on eggshell microbial activity, hatchability, tibia mineral content, and chick performance in Japanese quail (Coturnixcoturnix japonica) eggs. Poult. Sci. 91:732-738. -47-


Caner, C., M, Yuceer. 2015. .Maintaining functional properties of shell eggs by ultrasound treatment. J. Sci. Food Agric., 95: 2880-2891. Fasenko, G.M., E.E. O’Dea Christopher, and L.M. McMullen. 2009. Spraying hatching eggs with electrolyzed oxidizing water reduces eggshellmicrobial load without compromising broiler production parameters. Poult. Sci. 88 :1121-1127. Joyce, E., S. S. Phull, J. P. Lorimer, and T. J. Mason. 2003. The development and evaluation of ultrasound for the treatment of bacterial suspensions. A study of frequency, power, and sonication time on cultured Bacillusspecies. Ultrason. Sonochem. 10:315–318. Knorr, D., M. Zenker, V. Heinz, and D. U. Lee. 2004. Applications and potential of ultrasonics in food processing. Trends Food Sci. Technol. 15:261–266. Mizrach, A. 2007. Nondestructive ultrasonic monitoring of tomato quality during shelf-life storage. Postharvest Biol. Technol. 46:271–274. Mizrach, A., U. Flitsanov, M. Akerman, and G. Zauberman. 2000. Measurements of avocado shelf life at various storage temperatures using ultrasound. Postharvest Biol. Technol. 20:279–286. Ordonez, G., V. M. M. Galvis, F. Delgado, and J. Orlando. 2009. The effect of ultrasonic treatment on some functional properties of egg white. Rev. Cient. 19:71–76. Shafey, T.M., Hussein, E.O.S., and AL-Batshan.H. A. 2013. Effects of ultrasonic waves on eggshell strength and hatchability of layer-type breeder eggs.S. Afr. J. Anim. Sci. 43:56-63. Sert, D., A. Aygun, and M. K. Demir. 2011. Effects of ultrasonic treatment and storage temperature on egg quality. Poult. Sci. 90:869–875. Sert, D., A. Aygun, E. Torlak, and E. Mercan. 2013. Effect of ultrasonic treatment on reduction of Esherichia coli ATCC 25922 and egg quality parameters in experimentally contaminated hens’ shell eggs. J. Sci. Food Agric. 93:2973-2978. Yaldagard, M., S. A. Mortazavi, and F. Tabatabaie. 2007. The effectiveness of ultrasound treatment on the germination stimulation of barley seed and its alpha-amylase activity. World Acad. Sci. Eng. Technol. 34:154–157. Yildirim, I., A., Aygun, and D. Sert. 2015. Effects of preincubation application of low and high frequency ultrasound on eggshell microbial activity, hatchability, supply organ weights at hatch, and chick performance in Japanese quail (Coturnix coturnix japonica) hatching eggs. Poult. Sci., 94: 1678-1684. Yuan, Y., Y. Hu, T. Yue, T. Chen, and Y. M. Lo. 2009. Effect of ultrasonic treatments on thermoacidophilicAlıcyclobacıllus acıdoterrestrısin apple juice. J. Food Process. Preserv. 33:370–383.

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EFFECTS OF DIFFERENT TYPES OF CAKES IN RATIONS ON THE PERFORMANCE OF CULLED CYPRUS SHAMI DOES IN HALF ELGADEDA, KASSALA STATE, SUDAN AMANI A. B. OSMAN1, MOHMMED E. ELIMAM2 1

Department of Animal Production, Faculty of Agriculture and Natural Resources, Kassala University, Halfa Elgadeda, Sudan. 2 Goat Research Centre, Faculty of Agricultural Sciences, University of Gezira, P. O. Box 20, Wad Medani, Sudan. [email protected]

ABSTRACT Fifteen culled Cyprus Shami does were used to study effects of some cakes in rations on their performance in Halfa Elgadeda, Kassala State, Sudan. The goats were divided into three groups and allocated at random to three iso-nitrogenous and iso-caloric rations containing groundnut cakes, sesame cakes or sunflower cakes. They were fed the rations for 4 weeks ad lib. in two equal meals at 8am and 4pm and water was offered ad lib. They were fastened for 12 hrs and weighed weekly before the morning meal. The data was statistically analyzed using the completely randomized design. Final BW, total weight gains and daily weight gain varied among rations, but not significantly (P>0.05). Final BW and total weight gain (kg) were 55.9 and 5.9, respectively for the groundnut cakes ration, 56.2 and 6.7, respectively for the sesame cakes ration and 54 and 5.1, respectively for the sunflower cakes ration. Daily weight gain (g) was 306, 318 and 279, respectively for rations containing groundnut cakes, sesame cakes and sunflower cakes, respectively. Daily feed intake varied significantly (P0.05). It was 5.33, 4.65 and 1.34, respectively. Feed intake and FCR were highest in animals fed the groundnut cakes ration and least in animals fed the sunflower cakes ration. Final BW and total and daily weight gains were highest in animals fed the sesame ration, all parameters, except FCR were least in animals fed sunflower. INTRODUCTION Meat demand and prices increased substantially in the Sudan due to increased local and foreign demands (Ahmed, 2014). Per capita meat consumption was 41kg (AOAD, 2011). It is important to produce cheap and high quality meat and exploit less utilized types of meat to meet demands and reduce prices. Sheep meat is the most preferred and expensive in the Sudan and Arab countries and goat meat is the least preferred in the Sudan (MAWF, 2011) and mainly consumed in rural areas as kids’ meat. Goat meat is preferred in Arabia, Gulph countries, Asia, Africa and south Europe (Devendra and Mc Leroy, 1982). The demand for goat meat is increasing in developed countriesmainly due to immigrants and the disputed correlation between cholesterol and saturated fatty acids and cardiovascular diseases. Goat meat has high nutritive value and muscles and low fat and cholesterol (Elimam and Ombabi, 2007; Elimam et al., 2010). Goat production is important in the Sudan due to high goat population, wide distribution and production of high quantities of high quality milk, meat and skin (MAWF, 2011). Sudan ranked 6th in world goat population and 5th in world goat meat production, but is not among the main world goat meat exporters (FAOSTAT, 2011). Goat meat production is mainly traditional in the Sudan based on rangeland and are generally neglected with low inputs and outputs (Devendra and Mc Leroy, 1982). Improving goat meat production will make it competitive locally and abroad and increase demands, exports and national income. There are many goat breeds and Nubian is the main dairy breed and other breeds are considered meat producers (Devendra and Mc Leroy, 1982). Many exotic breeds are imported to improve goat milk production including Saanen and Shami (Damascus). Cyprus Shami goats were recently imported to improve animal production in Kassala State and culled males and females are used for meat production due to the large size. Carcass characteristics are improved by improving the nutrition of culled animals before slaughter. -49-


Nutrition is one of the main constraints for goat production in Halfa Elgadeda area due to rangeland deterioration for many reasons (Yagoub, 1998; Abusuwar and Darrag, 2002) and seasonal variations in feeds quantity and quality associated with seasonal rainfall leading to serious shortages and effects on animal’s health and performance, especially in the dry season (Elhag, 1992). Crop residues are important in filling the nutritional gap, but generally have low nutritive value due to low CP and high CF limiting feeds dry matter intake and animal’s performance (Hamed, 2007). Concentrates are not commonly used and improved animal’s performance (Anyanwu, 2008; Sahu, 2013). Different cakes are used in concentrates with variations in feeds nutritive value. Groundnut cakes DM and CP degradation were higher than cottonseed cakes and sunflower cakes and the latter had the least values (Turki and Atcham, 2011). Sunflower cakes had higher molecular weight amino acids concentration followed by cotton seed cakes and then groundnut cakes and it was postulated that is why groundnut cakes was unstable protein and the other two cakes were stable. There is no available information on effects of different cakes in rations on the performance of culled Shami goats in Halfa Elgadeda area. Consequently, an experiment was conducted to study effects of groundnut, sesame and sunflower cakes in rations on the performance of culled Cyprus Shami goat in Halfa Elgadeda area. MATERIALS AND METHODS Study area The study described below was conducted in the goat pens in the animal production farm in the Faculty of Agriculture and Environmental Sciences, Kassala University in Halfa Elgadeda, Kassala State, Sudan in February and March 2013. Animals Fifteen culled Cyprus Shami does at 4 years old were used in this experiment. They were housed in individual pens and treated against external and internal parasites. They were divided into three groups according to body weight and then allocated at random to three experimental rations. Feeds and feeding Three isonitrogenous and isocaloric rations containing groundnut cakes, sesame cakes or sunflower cakes were used in this experiment. Table 1 shows the ingredients and calculated CP and ME of the rations fed to culled Shami does. The animals were fed the rations ad lib. for a 10 days preliminary period and then the experimental rations for 4 weeks. The rations were fed in two equal meals at 8am and 4pm.Fifty grams Clitoria hay were fed daily before the morning meal to maintain normal gut functions and for vitamins. Clean drinking water was available all time. Daily feed intake was determined by offering preweighed rations and collecting and weighing the refusals before the morning meal in the following day. Weight gain was determined by weighing the animals before the morning meal after fasting for 12 hrs to avoid variations in gut contents, at the beginning of the experiment and then weekly to the experiment end. Calculations and statistical analysis Feed intake was calculated as the difference between offered rations and the refusals. Total weight gain was calculated as the difference between initial and final BW. Daily weight gain was calculated as the difference between successive BW divided by the days between them. Feed conversion ratio was calculated by dividing the total feed intake by total weight gain. The data was statistically analyzed according to Snedecor and Cochran (1980) using the completely randomized design and Duncans Test was used to split means differences. RESULTS AND DISCUSSION Table 2 shows effects of different types of cakes in rations on the performance of culled Shami does.

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Final BW, total weight gain and daily weight gain varied among animals fed different rations, but not significantly (P>0.05). They were highest in animals fed the sesame ration and least in animals fed the sunflower ration. Feed intake varied significantly (P0.05). It was highest in animals fed the groundnut ration and least in animals fed the sesame ration. The increased final body weight was due to weight gain. Similar results were found in Tagger goats (Elimam et al., 2010) and Nubian kids (Yagoub and Babikir, 2008). Culled Shami goats BW was within the breed range in Cyprus (Keskin, 2002) and lighter than the breed males and females above 3 years old in Kassala State (Musa, 2013). They were generally heavier than endogenous Sudanese breeds including Nubian (Elnaim, 1979; Gall, 1986), Desert (Ombabi, 2006), Nilotic (Gall, 1996), Ingessana (Abdalla, 2004) and Tagger (Elbukhary, 1998; Ombabi and Elimam, 2011). The variations among rations in weight gain and daily weight gain in culled Shami goats were also found in young West African goats (Anyanwu, 2008) and Nubian kids (Yagoub and Babikir, 2008). This was mainly due to variations in elements and vitamins in different cakes and hence associated effects and feeds nutritive value. Turki and Atcham (2011) found variations among cakes in composition, rumen degradation and molecular weight amino acids concentrations. Culled Shami goats daily weight gain was higher than Nubian goats (Khalifa, 2002). The significant variations in feeds intake among rations were mainly due to the variations in cakes composition and effects on rations nutritive value. The highest feed intake in animals fed the groundnut cakes ration was due to the high CP and improved feeds nutritive value, digestibility and rates of outflow through the alimentary tract. it also had higher degradation than sunflower cakes (Turki and Atcham, 2011). The least feed intake in animals fed the sunflower cakes ration was mainly due to the least CP among cakes in this study and hence the least nutritive value and performance. The variations in feed intake among rations were reported in young West African goats (Anyanwu, 2008) and Nubian kids in Sudan (Yagoub and Babikir, 2008). The variations in FCR among rations with different cakes were mainly due to variations in feeds nutritive value, feed intake and weight gain. The highest FCR in animals fed the groundnut cakes ration reflected that it was poorly utilized for weight gain although it had the highest feed intake and ranked second in weight gain. The least FCR in animals fed the sesame cakes ration was mainly due to elements and vitamins enhancing feeds nutritive value. The sesame cakes ration had the highest final BW and the highest weight gain and ranked second in feed intake and had beneficial effects. The highest performance in animals fed the sesame cakes ration was similar to that for wheat offal ration in West African goat (Anyanwu, 2008). The least parameters, except FCR, in animals fed the sunflower cakes ration indicated that sunflower cakes were inferior to groundnut and sesame cakes in composition and degradation as found by Turki and Atcham (2011). Similar effects were reported in West African goats fed grasses (Anyanwu, 2008). Shami goats feed conversion ratio was better than Nubian female kids fed different energy rations (Yagoub and Babikir, 2008). REFERENCES Abdalla, A. A. (2004). Body Measurements and Carcass Characteristics of the Ingessana Goats, Sudan. M.Sc. Thesis, Department of Animal Science, Faculty of Agricultural Sciences, University of Gezira, Wad Medani, Sudan. Abusuwar, A. O. and Darrag, A. (2002). Pan Arab integration in forage production and processing. Case study: Sudan. Arab Organization for Agricultural Development (AOAD), Khartoum, Sudan. Ahmed, G. S. A, M. (2014). Performance of Tagger Goats Fed Sorghum Stover and Lukh [Dichanthium annulatum (Frosk)] Supplemented with Seyal [Acacia tortilis (Frosk). Hayn] and Haraz (Faidherbia albida. Del) Pods. Ph. D Thesis, Department of Animal Science, Faculty of Agricultural Sciences, University of Gezira, Wad Medani, Sudan. -51-


Anyanwu, D. C. (2008). Effect of supplemental feeding combinations on the performance of west african dwarf (wad) goats. Animal Production Research Advances 4 (3-4), http://www.ajol.info/index.php/apra/article/view/49772. AOAD (2011). Arab Agricultural Statistics Year Book 31. Arab Organization for Agricultural Development (AOAD), Khartoum, Sudan. Devendra, C. and Mc Leroy, G.B. (1982). Goat and sheep production in the tropics. Commonwealth Agricultural Bureau, UK. Elbukhary, H. A. A. (1998). Production Characteristics of Tagger Goats.M.Sc .Thesis, University of Khartoum ,Shambat, Khartoum North, Sudan. Elhag, F . M. (1992). Effect of chopping and wilting on tropical grass land silage quality in South Kordofan, Sudan. African Livestock Research 2: 11-14. Elimam, M. E., Ombabi, Y. A., Ahmed, S. and Ageeb, H. A. M. (2010). Effect of fattening and age at slaughter on Tagger goat performance and carcass characteristics in the Gezira State, Sudan. Gezira Journal of Agricultural Science 8 (2), 87- 100. Elimam, M. E. and Ombabi, Y. A. (2007). Carcasscharacteristics of male Desert goats in Elobeid area in North Kordofan State, Sudan. Gezira Journal of Agricultural Sciences 5, 190 – 202. Elnaim, Y.A.(1979). Some productive traits of Sudan Nubian goats. M. V. Sc. Thesis . University of Khartoum, Shambat, Khartoum North, Sudan. FAOSTAT (2011). Food and Agriculture organization, United Nations,. Gttp://fostst,fao.org/site/339/default.aspx> Gall, C. (1996). Goat Breeds of the World, CTA, Akersheim, Margraf. Institute for Animal Production, Germany. Hamed, A. H. M. (2007). Utilization of Upgrading straws of Sorghum Pearl, Millet and Sesame by Nubian Goat in the Sudan. Ph.D. Thesis. Department of Animal Science, Faculty of Agricultural Sciences, University of Gezira, Wad Medani, Sudan. keskin.M., (2002) Effect of rearing system on kid performance, lactation traits and profitability of Shami goats. Journal of Applied Animal Research 22, 267-271. Khalifa, N. B. H.(2002).Characteristics and performance of Garaj sheep and Nubian goats in Kenana Sugar Company aream White Nile, Sudan. M. Sc.Thesis, Department of Animal Science, Faculty of Agricultural Sciences, University of Gezira, Wad Medani, Sudan. MAWF (2011). Statistics and Information Department Annual Report, Ministry of Animal Wealth and Fisheries Khartoum, Sudan. Musa O. M. O. (2013). The Performance of Shami Cyprus Goat in Eastern Part of the Sudan in Kassala State. Ph. D. Thesis, Thesis, Faculty of Animal Production, Sudan University of Science and Technology, Helat Kuku, Khartoum North, Sudan. Ombabi, Y. A. (2006). Characteristics of the Desert Goat as a Meat Producer in Elobeid area, Sudan. M. Sc Thesis, Faculty of Agricultural Sciences, University of Gezira, Wad Medani, Sudan. Ombabi, Y. A. and Elimam, M. E. (2011). The phenotypic characteristics of Tagger goat in the Gezira, Sudan. Sudan Journal of Agricultural Research 18, 153-162. Sahu, s., Babu,L. K., Karna, D. K., Behera, k., Kanungo, S., Kaswan, S., Biswas,P. and Patra, J. K. (2013 ). Effect of different level of concentrate supplementation on the periparturient growth performance of Ganjam goat in extensive system Veterinary World 6 (7), 428-432. Snedecor, G. W. and. Corchran, W. G. (1980). Statistical Methods, Iowa State University Press, Ames, Iowa, USA. Turki, I.Y. and Atcham, A .A. (2011). Study on chemical composition, degradation and protein characterization of oilseeds cakes available in Sudanese market. Research Opinions in Animal & Veterinary Sciences 1(9), 587-593. Yagoub, A. M. (1998). Environmental Consideration for Sustainable Development in Greater Darfur State,MSc. Thesis, Institute of Environmental Studies, University of Khartoum, Khartoum, Sudan. -52-


Yagoub, Y. M. and Babikir, S. A. (2008). Effect of dietary energy level on growth and carcass characteristics of female goats in Sudan. Livestock Research for Rural Development 20 (12),

Table 1. The ingredients of rations with different cakes fed to culled Cyprus Shami does in Halfa Elgadeda, Kassala State, Sudan. Ingredients(%)/ A B Rations Sorghum grains 52.0 52.0 Sesame cakes 17.0 00.0 Groundnut cakes 00.0 16.0 Sunflower cakes 00.0 00.0 Groundnut hulls 19.0 15.00 Wheat bran 10.0 15.0 Dicalcium phosphate 01.0 01.0 Salt 00.4 00.4 Lime stones 00.5 00.5 Vitamins 00.1 00.1 Calculated CP 17.56 17.49 Calculated ME (Mj/ kg DM) 11.30 11..0 A= Groundnut cakes ration; B= Sesame cakes ration; C= Sunflower cakes ration.

C 39.0 00.0 00.0 49.0 05.0 05.0 01.0 00.4 00.5 00.1 17.57 11.30

Table 2. Effects of different types of cakes on the performance of culled Shami does in Halfa Elgadeda, Kassala State, Sudan. Parameters Initial BW (kg) Final BW (kg) Total weight gain (kg) Daily weight gain (kg) Daily feed intake (kg)

Rations A 50.00 55.90 05.90 306 1.63a

SE B 49.50 56.20 06.70 318 1.48ab

C 48.90 54.00 05.10 279 1.34b

0.85 0.44 0.89 0.046 0.053

Significa nce NS NS NS NS *

FCR 5.33 4.65 4.80 0.00 NS A= Groundnut cakes ration; B= Sesame cakes ration; C= Sunflower cakes ration. BW= Body weight; FCR (kg feed|kg weight gain) NS= Non significant differences at P