Wollega University, Shambu, Ethiopia

Proceedings of the National Conference on

Agriculture, Climate Change and Environmental Safety: The Challenges on National Transformation in Ethiopia

Date: 23 rd and 24 th February 2017 Venue: Shambu Campus, Wollega University, Shambu, Ethiopia.

Editors Dr. Eba Mijena Dr. Hirpa Legesse Dr. Diriba Diba Dr. Raghavendra HL

WOLLEGA UNIVERSITY P.O. Box: 395, Nekemte, Ethiopia. Website: http://www.wollegauniversity.edu.et/

Published by: Wollega University Press, Nekemte, Ethiopia.

No part of these policies and procedures may be reproduced, stored in a retrieval system, or transmitted in any form by any means, including electronic, photocopying, recording, or otherwise, without prior written permission of the Office of the Research and Technology Transfer Vice-president, Wollega University, Nekemte, Ethiopia.

ISBN No: 978-99944-889-7-1

WOLLEGA UNIVERSITY P.O. Box: 395, Nekemte, Ethiopia.

Website: http://www.wollegauniversity.edu.et/

Tel: +251 57 6617981 Fax: +251 57 6605015

Contents

No Title P. No Preface i-iv Abbreviations v-vi Section I: Welcome Address and Opening Speech

1. Welcome Address: Dr. Eba Mijena. 1-5 2. Opening Speech: Ato Abebe Kebede Jalleta 6-8 Section II: Keynote Address

1. Dr. Amsalu Ayana ... 9-14 2. Dr. Alem Tsehai Tesfa 15-18 Section III: Papers Presented at the Conferences (Selected Papers)

The Effect of Variety and Seed Proportions on Yield, Nutritional Quality and 1. Compatibility of Oats and Vetch Mixtures

Fantahun Dereje, Ashenafi Mengistu, Diriba Geleti and Buzunesh Tesfaye .... 19-38 Yield and Yield Components of Maize (Zea mays L.) Groundnut (Arachis 2. hypogaea) Intercropping as Affected by Spacing and Row Arrangements

Melkamu Dugassa, Hirpa Legesse, Negash Geleta...... 39-54 Analyses of Climate Variables and Determination of Chickpea Water 3. Requirement for Rainfed Production in Ada’aa District, Ethiopia

Mengesha Lemma Urgaya. 55-72 Screening of Bread Wheat ( Triticum aestivum L.) Genotypes for Resistance 4. Against Stem Rust ( Black Rust ) Diseases

Desalegn Negasa Soresa and Tola Abdisa .... 73-82 Anthropological inquiry in retrospect of forest biodiversity, forest policy in 5. Horro Guduru Wollega Zone of Oromia regional state, Ethiopia

V. Sree Krishna and Belay Ejigu .. 83-87

A National Conference on Agriculture, Climate Change and Environmental Safety: The Challenges on National Transformation in Ethiopia

Date: 23-24 February 2017

Thematic Areas

THEME 1: AGRICULTURE AND CLIMATE CHANGE Climate Change, Water and Agriculture: Towards Resilient Systems Farmer Practices, Agricultural Management and Climate Change Climate Change and Agriculture: Impacts, Adaptation and Mitigation Disaster Management in Agriculture: Policy Lessons and Approaches Modeling for Climate Change in Agriculture THEME 2: CLIMATE CHANGE AND FOOD SECURITY Food and Nutrition Security in the Pace of Climate Change Food Security through Improved Production Systems Agriculture-related Investments and Policies Climate Smart Agriculture Natural Disasters and Food Security THEME 3: ENVIRONMENTAL SAFETY AND CLIMATE CHANGE Natural Resource Management and Global Warming Development Polices and Environment Indigenous Knowledge in the View of Climate Change Biodiversity, Conservation and Management Green Economy and Environmental Safety Community based Natural Resource Management Land Degradation Disaster and Risk Management THEME 4: AGRICULTURE AND RURAL DEVELOPMENT Improving Access to International and Local Markets Agricultural Productivity and Rural Development Improving Crop Production and Productivity Improving Animal Production and Productivity Agricultural Commercialization and Agro-Industry Development Organic Farming and Soil Fertility Management Access to Agricultural Inputs and Finance Improved Agricultural Technology Dissemination and Adoption

THEME 5: AGRICULTURE PRODUCTION AND MARKETING

Agricultural Production Systems: Husbandry Practices and Genetics

Livestock/Crop Diseases and Control Measures

Livestock/Crop Marketing and Animal Welfare

Feed Quality and Safety

Agricultural Technology and Extension Services in Ethiopia Opportunities and Challenges of Fish Production and Marketing in Ethiopia Bee Production, Product Processing and Marketing Animal Products Processing and Marketing Agro-processing and Biotechnology Recent Technologies in Agricultural Production

Preface

Welcome you to this volume of the proceedings of a National Conference on “Agriculture, Climate Change and Environmental Safety: The Challenges on National Transformation in Ethiopia ”, which was held on 23 rd and 24 th February 2017 at Shambu Campus, Wollega University, Shambu, Ethiopia . In this proceeding, the opening and welcome addresses, the keynote addresses and key technical papers presented on the conference have been compiled. Conferences traditionally take a broad approach to thinking and cognition, in all their various aspects and manifestations, and this is broadly reflected in the content of the various papers submitted for publication in this proceedings. The papers are from researchers working in academia and research institutes. All the papers are compatible with the core thematic areas requested for the conference. The publication of the papers aimed at importance of climate change and environmental safety towards agriculture productivity and national transformation and avail it to the wider audience.

Ethiopia is endowed with abundant agricultural resources and has diverse ecological zones. Ethiopia, the oldest state in sub-Saharan Africa, is located within the tropics and hence it has no significant variation in its local temperature. It has four agro-ecological zones: wurch (alpine), dega (highland of its altitude), woyna-dega (medium of its altitude) and qola (lowland). These different agro-climate zones have been important in the development of self-sufficient agriculture in the region. It is also the agro-climatic conditions, inter alia, that have influenced the pattern of settlement, mode of production, activities and life of the rural population. The systems of agriculture, the pattern of crop production and population distribution are highly dependent upon the climate, soil, land management and tenure system.

Agriculture is the backbone of the Ethiopian economy and therefore this particular sector determines the growth of all the other sectors and, consequently, the whole national economy. On average, crop production makes up 60% of the sector’s outputs whereas livestock accounts for 27% and other areas contribute 13% of the total agricultural value added. Agriculture accounting for half of gross domestic product (GDP), 83.9% of exports, and 80% of total employment. An estimated 85 percent of the population are engaged in agricultural production. Important agricultural exports include coffee, hides and skins (leather products), pulses, oilseeds, beeswax, and, increasingly, tea. Domestically, meat and dairy production play an integral role for subsistence purposes. Ethiopia has about 51.3 million hectares of arable land.

However, just over 20% is currently cultivated, mainly by the smallholders. Over 50% of all smallholder farmers operate on one hectare or less. Smallholder producers, which are about 12 million households, account for about 95% of agricultural GDP. Agricultural production is mainly subsistence, and a large portion of the country’s commodity exports is provided by the small agricultural cash-crop sector.

Although agriculture is one of Ethiopia’s most promising resource, the sector has been slowed down by deforestation (depletion of forests), over-grazing (depletion of pastures), soil erosion (depletion of quality soil), desertification (extensive drying of the land) and poor infrastructure that often make it hard and expensive to get goods to market. Also, overgrazing, deforestation and high population density has led to massive soil degradation leading to low productivity. Since only 12 percent of all Ethiopian land is arable, 1 percent is used for permanent crops, and 40 percent is comprised of permanent pastures, it is essential for Ethiopia to address these environmental problems in order to maintain the land so fundamental for agricultural activities. However, a critical look at the sector shows a high potential for selfsufficiency in grains and also for the development export especially for livestock, vegetables, fruits and grains.

Climate Change constitutes one of the most important environmental, social and economic challenges of our time on both the global and regional level. Agriculture’s role in climate change is three-fold. Firstly, it causes part of the release of greenhouse gas emissions through intensive land use, livestock and land use changes. Agriculture is also directly affected by the consequences of climate change through phenomena such as droughts and water scarcity and is also subject to heavy rain events, which endanger productivity. In addition, agriculture serves to preserve natural resources and established cultural landscapes by increasing soil carbon contents and adapting management practices to preserve carbon sinks.

Since the last two millennia, there have been continuous demographic increments, but limited resources. During the second half of the twentieth century of Ethiopia, in particular, the rural setting and landscape has been radically changed. It became eroded, barren and broken. The process of deforestation and devastation of Ethiopia proceeded unhindered over three millennia. The saying, “ Meder Bewoledech Nededech (the earth has been devastated for giving birth to [man],” well expresses the deforestation and destruction speed and intensity of natural resources in the postwar period. Though the continuity of Ethiopian state and culture have largely depended on

ii agriculture and land used, it is a rare case when the land is used for crops for which it was most suitable and under which it could give maximum yield. Presence of excess land in the hands of some rist holders made most peasants to work less. This was aggravated by civil strife, drought and poor development strategic plans of the imperial period. Absence of cadastral works, unclear ownership and tenancy rights and undefined landlord-tenant relationship had also a cumulative tenure insecurity effect in most areas of the country. In addition, poor market infrastructure hampered agricultural production and efficiency. There was no motivation and pressure to alter and transform the system.

Ethiopia is mainly characterized by low output rain-fed mixed farming with traditional technologies. The country, both the past and the present, has subsistence farming in which food production is the most important activity of the peasants. Agriculture is by and large dependent on the use of oxen-drawn mode of farming. People have made their livelihood by tilling and herding. The sector has remained more or less static for centuries. People have remained poor. There were different but interwoven constraints. The presence of an unproductive class, lack of capital, poor infrastructure, absence of access to markets, a shortage of skilled manpower, land degradation, population pressure, religion, culture, deforestation, tenure regimes and polices, poor land management practices and varied but interrelated natural factors could be mentioned as important factors of rural poverty. In developing solutions, experts in the fields of policy, science, agriculture, environment and nature conservation must work together. Everyone’s common goal must be to transform our consuming, destructive economy to a sustainable economy and way of life, including sustainable agriculture. Another goal must to foster the protection of resources and energy efficiency. Only by pursuing these goals is it possible to fulfill the responsibility owed to the next generation.

The Conference Purpose and Thematic Areas The purpose of this conference is to provide platform for stakeholders from different areas related to agriculture in order to present and discuss on the practical problems of agricultural productivity and prospects based on research outputs, ideas, development and applications in all areas of agriculture in Ethiopia. Researchers, Scholars, Policy Makers and professionals working in the Ministry of Agriculture and Rural Development, Universities, Research Institutes, Non-government Organizations, Investors, TVET's and different offices are invited to exchange ideas and experiences, and to showcase methods and innovations relevant for agricultural development in Ethiopia. The main thematic areas of the conference are as follows,

iii

Theme 1: Agriculture and Climate Change Theme 2: Climate Change and Food Security Theme 3: Environmental Safety and Climate Change Theme 4: Agriculture and Rural Development Theme 5: Agriculture Production and Marketing

Organization of the Proceedings This publication is arranged into three main sections. The first section is comprises the opening addresses given on the formal commencement of the conference. The conference had formal welcome addresses from Dr. Eba Mijena, President of Wollega University, Nekemte, Ethiopia and opening speech from Ato Abebe Kebede Jalleta, Administrator, Horro Guduru Wollega Zone, Oromia National Regional State (ONRS), Shambu. The second section contains keynote addresses made by Dr. Abera Deressa Former State Minister of Ministry of Agriculture, and WU Board Member, Dr. Amsalu Ayana, ISSD Country Director, Addis Ababa and Dr. Alemtsehay Tesfa, Dambalii Dairy Farm PLC, Nekemte. Third section comprises those plenary addresses for which presenters made detailed papers available. It is unfortunate not to include all papers presented in the two days conference because of lack of space.

Papers published in here were submitted as formal research papers by authors, and were subject to a peer review and editing process conducted by a panel of academics from Wollega University, Nekemte, Ethiopia. These papers were also proof-read and edited for English style, grammar and syntax. The editors of these papers trust that the editing of certain English expressions, grammar, and so on, have not changed the central meaning and content of the papers, and that these remain true to the authors’ intent. Therefore, the views expressed therein are entirely those of the authors. We would like to thank all those who sent their papers in time.

Editors

Dr. Eba Mijena Dr. Hirpa Legesse President Research and Technology Transfer Vice-president Wollega University Wollega University Nekemte, Ethiopia. Nekemte, Ethiopia.

Dr. Diriba Diba Dr. Raghavendra HL Research & Innovation Director Publication and Dissemination Director Wollega University Wollega University Nekemte, Ethiopia. Nekemte, Ethiopia.

Abbreviations

ADF : Acid Detergent Fiber ADLI : Agricultural Development Led Industrialization AGLI : Agriculture Growth Lead Industrialization AGRA : Alliance for a Green Revolution in Africa ANOVA : Analysis of Variance ATA : The Agriculture Transformation Agency CIMMYT : The International Maize and Wheat Improvement Center cm : Centimeters CP : Crude Protein CSA : Central Statistical Agency of Ethiopia CV : coefficient of Variation CWR : Chickpea Water Requirement 0C : Degree Celsius EC : Ethiopian Calendar EIA : Environmental Impact Assessment EIAR : The Ethiopian Institute of Agricultural Research EOS : End of Season EPRDF : The Ethiopian People’s Revolutionary Democratic Front FAO : The Food and Agriculture Organization FAOSTAT : Food & Agriculture Organization Corporate Statistical Database FDRE : The Federal Democratic Republic of Ethiopia GC : Gregorian Calendar GTP : Growth and Transformation Plans HEIs : Higher Education Institutions HI : Harvest Index ICT : Information and Communications Technology ISSD : Integrated Seed Sector Development Programme IT : Information Technology ITs : Infection Types

v km 2 : Square kilometer LGP : Length of Growing Period LSD : Least Significant Difference m.a.s.l : Metres above sea level mm : Millimetre MoA : The Ministry of Agriculture MoE : Ministry of Education NARS : National Agricultural Research Systems NDF : Neutral Detergent Fiber NMA : National Meteorological Agency ONRS : The Oromia National Regional State PASDEP : Plan for Accelerated and Sustained. Development to End Poverty RCBD : Randomized Complete Block Design RCBD : Randomized Complete Block Design RCC : Relative Crowding Coefficient RYT : Relative Yield Total SOS : Start of Season SPSS : Statistical Package for Social Sciences t ha -1 : Tonne per Hectare UPLB : University of the Philippines at Los Banos USA : United States of America USAID : The United States Agency for International Development WU : Wollega University

Welcome Address

Dr. Eba Mijena

President, Wollega University, P.O.Box 335, Nekemte, Ethiopia

Your Excellency Mr Abebe Kebede, Horro Guduru Wollega Zone Administrator Your Excellency Dr Abera Deressa Former State Minister of Ministry of Agriculture, and WU Board Member Your Excellency Dr Amsalu Ayana, ISSD Country Director, Addis Ababa Your Excellency Dr Alemtsehay Tesfa, Dambalii Dairy Farm PLC, Nekemte

Distinguished Guests and Dear Participants, It is a pleasure and privilege to welcome you all to this national conference on “Agriculture, Climate Change and Environmental Safety: The Challenges on National Transformation in Ethiopia ” prepared by Shambu Campus, and to express all my thanks to you all for your participation. I would like, first of all, to convey my regards and wishes to all of you who, despite your very hectic schedule and numerous responsibilities, have kindly agreed to come over here and share your thoughts, and participate on the conference.

The main purpose of this conference is to provide a platform for various stakeholders to come together and discuss on issues related to agriculture, climate change and environmental safety as challenges of national transformation in Ethiopia with the major focuses on: Agriculture and Climate Change, Climate Change and Food Security, Environmental Safety and Climate Change, Agriculture and Rural Development, and Agricultural Production and Marketing . It is believed that it gives scientists, scholars and researchers ample opportunity to exchange views on experiences, opportunities and challenges in the thematic areas identified and on the possibilities that are offered for using the innovative ideas and experiences which will come out of it to tackle the pertaining challenges in the country.

Dear Participants, Why agriculture, climate change and environmental safety are areas of focus on this symposium? It is clear that the more traditional system of our agriculture, the climate

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 1 change and the environmental problems are directly or indirectly challenges on national transformation in Ethiopia. They are pillars and determine the development of one country. These issues are at the center of all development agenda all around these days.

Let’s take agriculture which is the backbone of the Ethiopian economy. It employs over 80% of the population, and still dominates GDP contribution. Its growth, like the country’s economic growth, was stagnant and backward for decades. To this end, the Ethiopian Government began taking different policy measures and development interventions since the 1990s. The overarching development policy of the country is Agricultural Development Led Industrialization (ADLI). The country has trained tens of thousands of extension workers and assigned a minimum of three extension agents (crop, livestock, and natural resources management) to each Kebele. The agricultural sector has performed strongly over the last decade, registering an average of 8% growth. However, there is high potential to improve productivity, production and market linkages. The government has made strong commitment to the sector through allocation of more than 15% of the total budget.

Based on the successes of the past years, the Government of Ethiopia has created the Agriculture Transformation Agency to transform the agriculture sector and realize the interconnected goals of food security, poverty reduction, and human and economic development. The ATA is one of the measures taken by the government, in order to achieve the targets set in Ethiopia’s Five Year Growth and Transformation Plan (GTP) I. The targets focus on enhancing the productivity and production of smallholder farmers and pastoralists, strengthening marketing systems, improving participation and engagement of the private sector, expanding the amount of land under irrigation, and reducing the number of chronically food insecure households.

Nevertheless, agriculture still faces many challenges, making it more and more difficult to achieve its primary objective ‐feeding the world –each year. Population growth and changes in diet associated with rising incomes drive greater demand for food and other agricultural products, while food systems are increasingly threatened by land degradation, climate change, and other stressors.

Distinguished Guests, When it comes to climate change, we observe that it is the most serious environmental threat that adversely affects agricultural productivity. Climate changes over time due to natural variability or as a result of human activity. It is mainly caused by greenhouse

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 2 gases accumulation in the atmosphere, which results in increased greenhouse effect. Climate change and agriculture are interrelated processes, both of which take place on a global scale and their relationship is of particular importance as the imbalance between world population and world food production increases. Based on some projections, changes in temperature, rainfall and severe weather events are expected to reduce crop yield in many regions of the developing world, particularly subSaharan Africa and parts of Asia. The impact and consequences of climate change for agriculture tend to be more severe for countries with higher initial temperatures, areas with marginal or already degraded lands and lower levels of development with little adaptation capacity. Climate change affects not only agriculture but also the livestock sector both by affecting the quantity and quality of feed and by affecting the frequency and severity of extreme climate events.

Ladies and Gentlemen, The issue of environment is one of the focus areas on this conference. Every country has policy to deal with the issue of environment, so does Ethiopia. The Environmental Policy of Ethiopia, was approved on April 2, 1997 by the Council of Ministers. It has embraced the concept of sustainable development and as its goal, and it states “to improve and enhance the health and quality of life of all Ethiopians and to promote sustainable social and economic development through the sound management and use of natural, human made and cultural resources and the environment as a whole so as to meet the needs of the present generation without compromising the ability of future generations to meet their own needs.” Over the last decades, the Ethiopian government has put in place a number of policies, strategies and laws that are designed to support sustainable development agenda. With regard to the environmental pillar, Ethiopia has developed and implemented a range of legal, policy and institutional frameworks on environment, water, forests, climate change, and biodiversity. The Environment Protection Authority was created in 1994. The Institute of Biodiversity and the Ethiopian Wildlife Conservation Authority have also been strengthened with more power and mandate in conservation of biodiversity and sustainable use.

Land degradation is the major environmental problem resulting in low and declining agricultural productivity in the country. The average annual soil erosion rate nationwide was estimated at 12 tons per ha, giving a total annual soil loss of 1,493 million tons. Studies show that the soil erosion hazard is much higher for land under annual crops as compared to that under grazing, perennial crops, forest and bush.

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Dear Participants, We all agree that poverty and hunger must be eradicated and our country has to be transformed. The implication is that agriculture must change to meet the rising demand, to contribute more effectively to the reduction of poverty and malnutrition, and to become ecologically more sustainable. The majority of our people live in rural areas, and agriculture growth has proven effective in lifting rural families out of poverty and hunger. Equality important is the issue of climate change and environmental safety, which need attention if practical transformation is required. This is why Ethiopia has planned to become the middle income country by 2025 as part of national transformation plan. Yet, there are lots of challenges in all our systems, in our agriculture, addressing climate change and environmental safety issues. Do the strategies and policies, which we have at hand strong enough to transform our country? How do we solve the pertaining challenges we have today? The answer is direct and simple: we need to focus on major deliverables in agriculture, climate change and environmental safety among others which, I hope, will be the outcome of this particular conference.

As indicated earlier in my talk, at present, the country is formulating strategies and action plans aiming at realizing the vision to become a middle income country by 2025 which is founded upon improving the agricultural productivity. The country's commitment is to build, develop and promote the “quality of life” of its peoples. In this regard, we highly appreciate the initiative of organizing this conference to exchange views and experiences among researchers on introducing and promoting quality of life of people in the country. I believe that it is very important and timely then to organize forums on such critical and meaningful issues for a better understanding of them and timely actions. Thus, this conference won’t be a mere gathering of scholars but as you are aware is a crucial step towards investigating and looking into the critical issues which in one or another way negatively affect the country’s development. It is expected to have a larger impact on the capacity building of our staff and the future intervention policies. We also hope that we would be able to provide for a wider dissemination of the existing knowledge and present experiences in the thematic area indicated.

Excellencies, Ladies and Gentlemen, Different renowned researchers and participants have come from different corners of the country to attend this conference. The 121 abstracts were submitted based on the call for paper. Out these, only 54 papers were provisionally accepted of which 43 papers (15 papers on crop science, 15 papers on natural resources and 13 papers on animal

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 4 sciences) have been selected for today’s presentation based on their relevance and quality. More than 300 participants are expected from different universities, institutes, Horro Guduru Wollega Zone and Woredas. Sharing experiences on existing international trends and views becomes paramount important whereby conferences of this kind give opportunity for better understanding of the issues. I believe that lots of valuable initiatives and policy issues will come out of it. Having said all this, finally, I would like to thank you all for your participation and friends and colleagues of Wollega University who have contributed a lot for conducting this conference.

I wish you all a fruitful discussion and I look forward to welcoming you again to the conference and wish you all have the most pleasant time in Shambu.

Thank you for your attention.

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Opening Speech

His Excellency Mr. Abebe Kebede Jalleta

Administrator, Horro Guduru Wollega Zone, Oromia National Regional State (ONRS), Shambu, Ethiopia

Your Excellency Dr. Aberraa Dheeressaa, Board Member of Wollega University (WU) Your Excellency Dr. Amsalu Ayana, ISSD, Country Director Your Excellency Dr. Alemtsahy Tesfa, Owner and Managing Director of Dairy farm PLC Your Excellency Dr. Eba Mijena President of Wollega University

Invited Guests, Researchers and Participants of this Conference, First of all, It is my pleasure to say Welcome to the ever green and blessed lands of Western Oromia, Horo Guduru Wollega Zone, Shambu Town.

The Oromia National Regional State (ONRS), The Horro Guduru Wollega people and I became very happy when we heard that The Wollega University (WU) hosts “The National Symposium entitled “Agriculture, Climate change and environmental safety; the challenges on National Transformation in Ethiopia” at Shambu Campus. Since then, we have been counting days to have you here as we got chance to harvest a lot from the symposium.

Agriculture plays pivotal role in accelerating our development in general and our journey of rural transformation in particular. It is also the main source for manufacturing and processing sectors to uphold and further their products. The emphasis given to this sector is, indeed, correct and the research findings of this conference will serve as supplementary tool for the success of the Second Growth and Transformation Plan (GTP) of our country.

Dear Honorable Guests, Researchers, Ladies and Gentlemen, Beginning from 1681 when William Penn, Quaker leader of the English colony of Pennsylvania, ordered “the one acre of forest be preserved for every five acres cleared for settlement, the issue of environmental safety has not been uncommon to any individual country till the adoption of the Kyoto Protocol on Climate Change in 1997. Although other international agreements and conventions remained in vein, the later one featured binding emission targets for developed countries, they are debited toward their emission targets by financing energyefficient projects in lessdeveloped countries (known as “joint

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 6 implementation”), cleandevelopment mechanisms, and emissions trading. The climate change caused by El Nino and La Nina has been attacking the world, however.

Ethiopia, the signatory state of global protocol mentioned afore, has become a victim of this challenge and suffering from famine caused by it without contributing any emission to the environment. To tackle this problem, the EPRDF lead Ethiopian government devised Climate Resilience Green Economy policy, which is a complementing document to Agriculture Growth Lead Industrialization (AGLI). Accordingly, the research findings of this symposium those are going to be presented here by many of our scholars from various corners are believed to enable the agricultural lead policy of FDRE be more practicable in due course of implementing the Strategies designed for the policy.

In addition, the research outputs are presumed to indicate clues for more bargaining power to our country to maintain our interests on global forums.

On top of that, each research will indicate the effective ways to manage the nation’s variety of plant and animal species and its dominant resources for livestock and agricultural production properly. It is also believed that the upcoming potential findings will contribute a lot in transforming the existing traditional practice on our nation’s livestock and arable land management system to commercial system through trained human power, further use of research output and meteorological data.

Dear Honorable Guests, Researchers, Ladies and Gentlemen, The Ethiopian policy on environment protection and rehabilitation is also effective as it has been involving the public at large, who have done recognized natural resources management in different parts of the country since the period of PASDEP. The enactment of the law of Environmental impact assessment (EIA) obliged any one to observe the Policy on environmental protection as the objective of this law is to prevent our environment from different pollutants that have hazardous effect for the health of human and the environment itself. In addition it obliges that the establishment of any project for the public service or business organization should be in line with the requirements of the law. Above all, safe environment is required for the betterment of the health and survival of our community including our resources. Hence, all of these reasons justify that inclusion of environmental issues in this conference is very critical and recent demand of all concerned stakeholders and the public at large.

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Dear Honorable Guests, Researchers, Ladies and Gentlemen, One can learn from the success of a developed country’s development strategy and track record that research outputs have upper hand in materializing their dream. In this second GTP plan of our state, the FDRE government strives to transform the resources of the country through scientific methods for the wise use same.

Hopefully, this National Symposium will address the challenges and success of the current Ethiopian endeavor in Agricultural transformation, resilience of climate change and environmental safety. The researchers result may also contribute for policy makers and new concept for future research.

Finally, wishing you the best for your stay in Shambu town, I declare that the National symposium entitled “Agriculture, Climate change and environmental safety: the challenges on National Transformation in Ethiopia” is officially opened.

I thank you very Much!

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Keynote Address

Dr. Amsalu Ayana

ISSD Ethiopia Project, Addis Ababa, Ethiopia. Email: [email protected] ; Tel: +251 911842210

Objectives of my talk • To draw insights from national and global experience on the role of agricultural education, research and extension in increasing agricultural productivity; • To identify some key choices and good practices for strengthening agricultural education, research and extension institutions in Ethiopia; • To suggest operational recommendations appropriate for Ethiopian universities, particularly for Wollega University

What I observed in my age • Increasing number of Education and research Institutions • Increased urbanization and human population • Improved social services (Telecommunication, bank, electricity, road, administrative settings) • Severe Environmental Degradation – Significant climate change which resulted in shortened crop growing season; erratic rainfall, rise in temperature. • Loss of Biodiversity, including Agrobiodiversity • Increasing concern of food security

Base my talk is on Agriculture • Why? – About 40% of GDP • About 2/3 of agricultural GDP is from crop production

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• The remaining 1/3 comes from livestock, forestry and fishery – About 80% employment (directly & indirectly) – Major source of earning foreign currency (export) – Source of raw material for industry (agroindustry =food and beverages, textile, leather, sugar) – Plays 1 st role in poverty reduction

Why we need Universities? • Develop human capital – are the principal means for replenishing the stock of human capital in research, extension and agribusiness organizations • Support research and extension programs by using existing staff & facility at little extra cost. • Able to access global research findings and share this information with academic staff and students, as well as researchers in NARs and instructors in extension training programs. • Agriculture is highly location specific. • Hence, appropriate training in agriculture requires a detailed and intimate knowledge of local farming systems. Relevance of # of universities and research centers in Ethiopia

The world is in 5 th phase of Civilization • Phase I: The Hunter and Gatherer Era = Arrow and bow • Phase II: The Agrarian Era = Farm Machinery • Phase III: The Industrial Era = Factory • Phase IV: The ICT Era = Computer • Phase V: The Knowledge Era (The knowledgeworker Era = wisdom – In this last generation well developed human capital is more important than physical capital and money – That is why we need to invest more and more in education at all levels

What the knowledge era demands from Universities? • To contribute to a nation’s economic development and overall competitiveness in the era of globalization • To produce new technology and improved farm practices/innovations. • To invest in generating new knowledge and research, particularly applied research like agricultural research for increasing agricultural productivity.

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• To build an interactive system of three core institutions—education and training, research, and extension – The concept of equilateral triangle USA, Netherlands/the golden triangle, JATS, ICAMA) • Building this required 40 to 60 years for USA, Japan and Brazil • Many recent studies of human capital, including training, education and health, have shown that human capital can contribute to worker productivity and agricultural growth.

Lessons from Global experiences: The Evolution of Agricultural Education and Training, Research and Extension: Global Insights of Relevance for Africa – THE WORLD BANK GROUP (2006) – USA – Japan – Denmark – Netherlands – Brazil – India – Philippines – Malaysia – Nigeria

Global Lessons • Building the knowledge triangle (education, research and extension requires 40 50 years) – Initial investment and technical support from USAID, foundations in USA and American universities • Similar to Haramaya and Jimma • Attaining food selfsufficiency requires only about 10 years • Mobilizing and sustainable political leadership for public investment in the knowledge triangle – E.g. exceptionally Brazil • Breakthroughs in technology development and adoption. E.g. USA hybrid maize, rice and wheat for Green revolution in Asia • Bench marking/experience exchange and adapting to own context is useful

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– e.g. Japan adapted American large farm technologies to its small rice plots • Focusing 1 st on key food, and export commodities – E.g. maize in USA; wheat and rice in India, Philippines; rice, silk and industry in Japan; rubber and oil palm in Malaysia; coffee, oranges and sugarcane in Brazil – Agribusiness e.g. Denmark dairy industry – Netherlands is 3 rd agricultural exporter in the world (adopted the Golden Triangle) • Fostering the concurrent growth of agriculture and industry. – E.g. Japan’s economic transformation from a feudal to an industrial power in one generation (1868 – 1912) • Establishing decentralized education, research and extension systems – E.g. State universities of USA and Indian State agricultural universities • Typical Land Grant University model • Both set up about 350 –branch research stations to address the problems of microecologies. • Public sector education, research and extension systems were demanddriven in both countries • Failure occurs but bouncing back is common – E.g. Japan adoption of big farm technologies – University of the Philippines at Los Banos (UPLB). – Crisis due to shortage of academic staff – Destroyed during second World War – Rebuilt in 1958 (same period as of Imperial College of Agriculture and Mechanical Arts at Haramaya and Jimma Agricultural Technical schools • Increasing/sustainable national, regional and international partnership and linkage for – Funding – Technical support/Staff exchange/scholarship – Germplasm acquisition e.g. University of the Philippines at Los Banos (UPLB) from IRRI. • Incentive to retain academic staff – e.g. Malaysia

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The Variable Performance of the Land Grant Model in Nigeria • USAID through Michigan State, Colorado State, the University of Wisconsin and Kansas State University –assisted Nigeria in building new Land Grant Universities in four different regions in early 1960 • That the Land Grant model was successful in building teaching capacity, but unsuccessful in establishing research and extension at the University of Nigeria. – Lack of political decision to unify education, research and extension in the same institution • That the Land Grant model was successful at Ahmadu Bello University (ABU) at Zaria – decision to unify education, research and extension in the same institution successful The disruption of Land Grant colleges model in Ethiopia • JATS established 1952; initial plan was for 6 • ICAMA established in 1953 • Used equilateral triangle as logo (education, research and extension) • Oklahoma support ended 1968 • The extension wing of ICAMA moved to MoA in 1953 • EIAR established in 1966

The case of Mexico • Mexico's food crisis in 1930 • High degree of environmental degradation • Frustrating visit by one of high level American officials • Ford and Rockefeller Foundations • Four capable scientists • No trained Mexican • Mexico attained food selfsufficiency in the 1940s • CIMMYT established early 1960s followed by IRRI

AGRA’s efforts akin to USA’s effort to support Mexico in late 1930s • AGRA – Trains new generations of African plant breeders • University of Ghana • University of Nulu Natal • University of Nariobi

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– Support seed sector development (Program for African seed system development) – Promotes research on key African food crops

Ethiopia's recent efforts to build agricultural knowledge institutions • Establishment of ATEVET • Decentralized research and extension system • Expansion of research centers and universities • Trainings and development projects – ARTP – Rural capacity building – AGP – ATA

Can Ethiopian universities and research institutes/centers form real and sustainable partnership? • Partnership for what? – Ensure coordination and integration – Effective use of resources – Reduce duplication of efforts – Ensure decentralized knowledge institution building (education and training, research and extension) – Raise the productivity and improve the overall livelihood in their domain

Priority for Wollega University • Have three types of staff (Academic, Research and extension) and budget for the three core areas • Generate and promote technology to mitigate: – Environmental degradation, including termite – Postharvest loss, esp. of maize – Soil acidity • Introduce and adapt fruits and vegetables for acidic soils – E.g. blue berry Seek strong partnership with nearby research centers and international universities and research institutes.

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Keynote Address

Dr. Alem Tsehai Tesfa (PhD)

Dambalii Dairy Farm PLC, Nekemte

External Structure of Dambalii Farm Internal Structure of the Farm

Animals from Dambalii Farm Pasture Field around the Farm

Animals from Dambalii Farm

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Agriculture and Rural Development The Challenges on National Transformation in Ethiopia Knowle dge is Power, So is Development !! Help rural community to identify their primary need instead of telling them their need Based on the identified need, discuss on few/several options how to meet these needs Do not impose on them any option Give them some time to digest these options before taking any action Select the ‘appropriate’ option and start planning

Factors Determining Agriculture and Rural Development Plan

How to Plan and Implement of Development Program

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Foundation Footings of a Successful Plan STRONG DETERMINATION WITHCAREFULL PLANNING (Organize our thinking about the feasibility of the program to Guide & direct the operation and minimize the risk) ENVOLVEMENT OF LOCAL EXPERTS (do not depend on others to do it for us) BE CAREFUL ON FINANCIAL EXPENDITURE/ Resource allocation (capital, land, humanetc ) SOLVE THE ON COMING PROBLEMS IMMEDIATELY (develop new approach in reshaping the program)

Our system of Development plan seems based on “SHOOTING FIRST AND AIMING LATER” A) Far-sighted planning There should be harmony between national objectives and needs of local community B) Involvements and Understanding Participation of community in planning, implementing and maintaining of development program (Environment, Animal, crop, Community, Health, Education) is crucial

Rural Agricultural Developments should aim to Provide rural employment through integrated farming /through diversified products Improve Family Nutritional State with the increased consumption of animal products Increase awareness (education, hygiene, health, gender equality, legal rights) Encourage them to develop their traditional way of livings Develop linkage with input providers Develop market outlets for their products Emphasize on reducing soil compaction and erosion (stall feeding/zero grazing) Develop efficient utilization of on farm produced byproducts

Agro-forestry Related Efficient use of high biomass crops (Perennial food & feed crops and tree plants) Recycle agricultural byproduct (leaves, tops, roots, straw) Protect soil fertility & cover soil all year round Integrated system (Animal+Crop/Vegitable+Forestry) Less waste & pollution (manure Biogas Compost organic Fertilizer) More efficient use of products & byproducts produced on farm Lower transportation cost and energy used

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Role of an Advisor Advisor is a CHANGE AGENT, who creates an atmosphere for learning better ways of DOING THINGS OR He or she is AN INTRUDER – forcing people to change their way of living instead of Motivating them to upgrade their traditional knowhow

Important Points to Consider i n Advisory Thorough knowledge of the community and the problem within, in order to be able to give proper advice Solving problems should begin with the definition of the problems at hand/an overview of the context of apparent problems Problems should be dealt in a broad sense MORE CLOSLY TO THE REALITY OF RURAL LIFE STRUCTURE WHAT ARE THE COMPONENTS OF THE DEVELOPMENT PROGRAM? Who is the right advisor for this development program? Based on what criteria?

የእድገት መሰላል

ካለፈዉ መማር

ደካማ ጎኑን / ጠንካራ ጎኑን ማመዛዘን

የታቀደዉን ወደ ተግባር መለወጥ

በእቅዱ ላይ መወያየት፤ ማከል / ማስተካከል

ማቀድ / ቢቻል ተጓዳኝ የልማት ፕሮግራሞችን ማያያዝ

የአካባቢዉን ህዝብ ማወያየት / ቅድመ ዝግጅት ማዘጋጀት

የአካባቢዉን የተፈጥሮ ሀብት /ሁኔታ ማጥናት

በአካባቢዉ ያለዉ ችግር ምን እንደሆነ ለመረዳት ጥናት ማድረግ

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The Effect of Variety and Seed Proportions on Yield, Nutritional Quality and Compatibility of Oats and Vetch Mixtures

Fantahun Dereje 1, Ashenafi Mengistu 2, Diriba Geleti 3 and Buzunesh Tesfaye 4

1Department of Animal Science, Wollega University, Shambu campus, Ethiopia Email: [email protected] ; phone: +251936206790 2Department of Animal Production Studies, College of Veterinary Medicine and Agriculture, Addis Ababa University, Ethiopia. Email: [email protected] 3Department of Forage and Pasture Research, Ethiopian Institute of Agricultural Research, Ethiopia. Email: [email protected] 4School of Animal and Range Sciences, Haramaya University, Ethiopia Email: [email protected]

Abstract The study was conducted to assess the varietal and seed proportion effects on yield, quality and compatibility of oats and vetch mixtures under varying seed proportion (100%, 75%, 50%, 25%) using two varieties for each of the component species. The experiment was conducted in Randomized Complete Block Design (RCBD) with three replications. Seedling count, biomass yield, plant height, vigor and plot cover were collected. Forage quality traits considered for the experiments were DM content, ash, crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), lignin, cellulose and hemicelluloses. Relative yield, Relative yield total, Relative crowding coefficient and Aggressivity index were indices calculated for biological compatibility and yield advantages of oats and vetch. Significant (P<0.05) differences were observed for all measured agronomic traits except for plot cover. The highest DMY (17.61) was obtained from the mixture of 75% SRCP × 80 Ab 2291 + 25% Vicia dasycarpa lana. Mean values of Ash, CP, NDF, ADF and cellulose had significant (P<0.05) difference whereas mean values of DM content, ADL and hemicelluloses had non-significant (P>0.05) difference. The highest DMY, CPY and NDFY was showed by the mixture of 75% SRCP × 80 Ab 2291 + 25% Vicia dasycarpa Lana. Relative yield (RY) of oats and vetch varieties were less than one indicating that the yield obtained in the pure stands were higher than those from the mixed stands of the component species for both varieties. The relative yield total (RYT) of most mixed stands were greater than one indicating mixed stands to have superior yield advantage compared to the pure stand plots. The highest RYT value of 1.48, from the mixture of 50% SRCP × 80 Ab 2291 + 50% Vicia sativa ICARDA 61509, suggested a biological yield advantage of 48% in mixed cropping compared to the pure stand plots. The vetch varieties are the dominant except at the seed proportion of 75% +25% oats-vetch mixtures respectively. Generally, the result indicated that vetch species had higher CP and lower NDF than their respective mixtures and pure oats. The DMY, CPY and NDFY of mixtures of 75% oats + 25% vetch and 50% oats + 50% vetch seed proportions were better than pure stands. The RYT values of these mixtures were also greater than one. Therefore, it is concluded mixtures at seed proportions of 75% oats + 25% vetch and 50% oats + 50% vetch had relatively higher yield, quality and better compatible. Keywords: Biological compatibility; Herbage; DM yields; Nutritional quality; Oats and Vetch varieties and Seed proportions.

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INTRODUCTION Ethiopia has large livestock population and diverse agroecological zones suitable for livestock production. However, livestock production has mostly been subsistence oriented and characterized by low reproductive and production performance. This is mainly attributed to shortage of feed in quality and quantity (Malede, 2013). Livestock production in the tropics can be increased through increasing the productivity per animal and per unit land area. In view of that, increasing livestock productivity does necessitate improvement of animal feed availability besides improvements in health management and genetic improvement (Whiteman et al ., 1980).

In Ethiopia, livestock are mainly dependent on naturally available feed resources (Abebe et al., 2014). Most of the areas in the highlands of the country are put under cultivation of cash and food crops. This resulted in keeping large number of livestock on limited grazing areas, leading to overgrazing and decreased productivity. Cereal crop residues are also important feed resources but they are characterized by low quality and consequently could not support reasonable animal performance.

Farmers of low income countries like Ethiopia could not afford to use industrybased concentrates and chemicals as supplements to improve utilization of roughages. Leguminous forage crops can improve the utilization of low quality roughages and they are being used more extensively throughout the world. In various production systems legumes are capable of enhancing both crop production through sustained soil fertility and livestock production through increased availability of high quality feed.

The potential of improved forages such as oats and vetches in enhancing livestock feed availability is highly recognized mainly in intensively cultivated highlands and in areas where market oriented livestock production is practiced. The present high demand and price of livestock and livestock products is also expected to encourage farmers and large scale investors to cultivate improved forage crops.

One of the potential approaches to improve livestock feed availability in terms of quality and quantity is the use of grasslegume mixtures (Alemu et al., 2007). In this regard, the dry matter yield of grass and legume mixed stands has been reported to be superior compared with sole legume plots (Assefa and lendin, 2001). The role of such integrated forage production system in ensuring quality fodder availability is also much recognized by others (Geleti, 2000). Matt et al . (2013) also reported that growing mixtures of grasses and legumes improves biomass production as compared to grass monocultures. Mixed

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 20 planting of grasses and legumes was also indicated to be more productive than monocultures and the approach was thus reported to help control weeds, diseases and pests (Erla, 2011).

Productivity of oats and vetch mixtures are also known to be superior to pure stands in yield and quality (Assefa and Ledin, 2001; Erol et al ., 2009). Earlier studies, however, didn’t indicate the appropriate seed proportion that would result in balanced stands and the effect of varietal differences on forage yield and quality attributes. In this regard, Alemu et al. (2007) reported that planting of oats and vetch mixtures at 25% oats and 75% vetch proportion to result in better relative yield, but only one variety of each species was tested.

In a Panicum coloratum and Stylosanthes giuanensis mixed stands, it was also reported that grasses are aggressive compared to legumes leading to inferior performance of the legume component in the binary mixture (Diba and Geleti, 2013). To enhance the contribution of the legume component, optional agronomic strategies that help manipulate interspecies interactions and ensure balanced contribution of the component species to the total herbage mass and quality must be designed. In this regard, indices such as relative yield total, relative crowding coefficient and aggressivity index, among others are used to assess yield advantages in intercropping (Ghosh, 2004). But, these indices have not been used in intercropping systems of oat and vetch varieties to understand the nature of competition among species and also assess the yield advantage in mixed stands.

Furthermore, there is no adequate information on comparative productivity and compatibility performance of newly released varieties of oats and vetches when different varieties of each component species are mixed under Ethiopian situation. Therefore, in the present study it was hypothesized that varietal and seed proportion differences of oat and vetch mixed stands would influence productivity and compatibility of the mixed stands. The study further envisaged to see the differences in forage quality as influenced by varietal and seed rate proportion of the component species.

The objectives of the study were: (1) To assess the varietal and seed proportion effects of oats and vetch mixtures on yield and quality; (2) To assess the compatibility of oats and vetch mixtures under varying seed proportions of the component species.

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MATERIALS AND METHODS Description of the Study Area The experiment was conducted at Debre Zeit Agricultural Research Centre (Latitude: 08044’ N; Longitude: 38038’ E) located in East Shewa Zone of Oromia Regional State, Ethiopia. The Center is located at 47 km away from Addis Ababa to the East at an altitude of 1900 m above sea level. The average maximum and minimum temperatures of the center are 28.3 and 8.9 °C, respectively, with a mean annual rainfall of 1100 mm, having a bimodal pattern. The site is characterized by tepid to cool submoist agroecology, with dominant soil types consisting of light (alfisols/holisols) and heavy black soil (vertisols) (EIAR, http://www.eiar.gov.et ). The experimental plots were laid out on light soil.

Land Preparation and Planting A fine seed bed plots were prepared using tractor drawn implements before the experimental plots are laid out. Then, the plots were uniformly fertilized with diammonium phosphate (DAP) at a rate of 100 kg/ha at planting by broadcasting and then mixing with the upper soil layer using hand rake (Alemu et al., 2007). At early stages of seedling development, weeds were controlled through a manual and additional plot management practices were undertaken as deemed necessary.

Experimental Treatments The two recently released oats varieties by HARC (SRCP X 80 Ab 2806 and SRCP X 80 Ab 2291) and vetch ( Vicia dayscarpa lana and Vicia sativa ICARDA 61509) were used for sowing during main rainy season of 2015. The varieties were mixed at three seed rate proportions (25%+75%, 50%+50% and 75%+25%) of the component species and 100% of sole. The base seed rate used were 80kg and 20 kg for oats and Vetch, respectively (Alemu et al., 2007). The sown seed for each plot were given in Table 1 below.

The experimental treatments were laid out using Randomized Complete Block Design (RCBD) with three replications. The experiment consisted of three blocks; each block contained 16 experimental units (plots), which were fully randomly assigned to treatments. The spacing between blocks and plots was 1.5m and 1m, respectively (Akililu and Alemayehu, 2007). The plot size of each experimental unit was 6m 2 (3m*2m). In each plot there were 7 rows and seeds were uniformly drilled in rows with intrarow spacing 30cm.

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Table 1: Depiction of the treatment combinations and their sole counterparts. Amount Trt Treatment combination Variety name and their combinations sown in (gm) 1 100% oats variety 1 48 SRCP X 80 Ab 2806 2 100% oats variety2 48 SRCP X 80 Ab 2291 3 75% oats V1+25% vetch V1 36(oats) + 3(vetch) SRCP X 80 Ab 2806 + Vicia dasycarpa lana 4 50% oats V1+50% vetch V1 24(oats) + 6(vetch) SRCP X 80 Ab 2806 + Vicia dasycarpa lana 5 25% oats V1+75% vetch V1 12(oats) + 9(vetch) SRCP X 80 Ab 2806 + Vicia dasycarpa lana 6 75% oats V1+25% vetch V2 36(oats) + 3(vetch) SRCP X 80 Ab 2806 + Vicia sativa ICARDA 61509 7 50% oats V1+50% vetch V2 24(oats) + 6(vetch) SRCP X 80 Ab 2806 + Vicia sativa ICARDA 61509 8 25% oats V1+75% vetch V2 12(oats) + 9(vetch) SRCP X 80 Ab 2806 + Vicia sativa ICARDA 61509 9 75% oats V2+25% vetch V1 36(oats) + 3(vetch) SRCP X 80 Ab 2291 + Vicia dasycarpa lana 10 50% oats V2+50% vetch V1 24(oats) + 6(vetch) SRCP X 80 Ab 2291 + Vicia dasycarpa lana 11 25% oats V2+75% vetch V1 12(oats) + 9(vetch) SRCP X 80 Ab 2291 + Vicia dasycarpa lana 12 75% oats V2+25% vetch V2 36(oats) + 3(vetch) SRCP X 80 Ab 2291 + Vicia sativa ICARDA 61509 13 50% oats V2+50% vetch V2 24(oats) + 6(vetch) SRCP X 80 Ab 2291 + Vicia sativa ICARDA 61509 14 25% oats V2+75% vetch V2 12(oats) + 9(vetch) SRCP X 80 Ab 2291 + Vicia sativa ICARDA 61509 15 100% vetch variety 1 12 Vicia dasycarpa lana 16 100% vetch variety 2 12 Vicia sativa ICARDA 61509

Data Collection Seedling Data: Seedling count data were taken two weeks after emergence using a 1m x 1m quadrant in each plot. Stand count at tillering for oats and vetches are counted at 45 days of age (Akililu and Alemayehu, 2007).

Plant Height: At herbage harvest for dry matter yield determination, the plant height for each species were determined by measuring the height of five (average) randomly selected plants from ground level to the tip of the main stem were taken .

Dry Matter Yield: Three adjacent rows from the center of each plot were taken when oats were at dough stage to estimate fresh biomass yield (Akililu and Alemayehu, 2007). The harvested biomass was manually chopped into small pieces using sickle and a subsample of 300gm fresh weight were taken and dried at 65 oC for 72 hrs in an oven for herbage dry matter yield (DMY) determination.

DM yield (t/ha) = (10 x TFW x SSDW) / (HA x SSFW) (James, 2008).

Where: 10 = constant for conversion of yields in kg/m2 to tone/ ha; TFW = total fresh weight from harvesting area (kg); SSDW = subsample dry weight (g); HA = harvest area (m 2), and SSFW = subsample fresh weight (g).

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Besides, a chopped and sun dried forage sample material for each plot was prepared and saved for chemical analyses. Crude protein yield (CPY) and neutral detergent fiber (NDFY) of the treatments were further determined as the product of CP and NDF content and herbage DM yield (Starks et al ., 2006).

Laboratory Techniques and Chemical Analysis Sample Preparation The saved samples of forages maintained during herbage harvest were used for chemical analysis. These samples were dried overnight at 60 0C in an oven to ease for grinding and ground to pass through 1 mm screen using Wiley mill. Then, during analysis samples of feed were taken and weighed (hot weighing procedure) according to the chemical parameters analyzed.

Chemical Analysis The chemical analysis of feed was done using standard analytical methods. The DM and ash contents were determined by oven drying at 105°C overnight and combusting in a muffle furnace at 500°C for 6 hours, respectively. The nitrogen (N) content was determined by Kjeldahl method and CP content was calculated as N x 6.25 (AOAC, 1995). The neutral detergent fiber (NDF), acid detergent fiber (ADF) and acid detergent lignin (ADL) were determined according to the procedures of Van Soest and Robertson (1985). Hemicellulose was determined by subtracting ADF from NDF and cellulose subtracting lignin from ADF. The analysis of feed samples was done at Debre Zeit Agricultural Research Center (DZARC).

Biological Compatibility DM yield of oats varieties and vetch species in mixtures with in replacement series (75%+25%, 50%+50, 25%+75%) were compared with their respective monocultures, (De wit 1960).

Relative Yield The relative yields (RY) of the components in the mixtures were calculated using the equations of De Wit (1960) as: RYG = DMYGL/DMYGG and RYL = DMYLG/DMYLL Where; DMYGG is the dry matter yield of oats as monoculture; DMYLL is the dry matter yield of vetch as monoculture; DMYGL is the dry matter yield of oats grown in mixture with vetch and DMYLG is the dry matter yield of vetch grown in mixture with oats.

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Relative Yield Total (RYT) Relative total yield (RTY) was calculated according to the formula of De Wit (1960):

RTYGL = (DMYGL/DMYGG + DMYLG/DMYLL)

Where; DMYGG is the dry matter yield of oats as monoculture; DMYLL is the dry matter yield of vetch as monoculture; DMYGL is the dry matter yield of oats grown in mixture with vetch and DMYLG is the dry matter yield of vetch grown in mixture with oats.

It shows that if RTYGL > 1, there is yield advantage of mixtures compared to the pure stand.

Relative Crowding Coefficient (RCC) This parameter was calculated to determine the competitive ability of the annual grass and legume in the mixture by measuring the component that has produced more or less DM than expected in a 50:50 grass legume mixture (De Wit 1960):

The formula for the 50:50 grass legume mixture is:

RCC GL =DMY GL / (DMY GG DMY GL )

RCC LG =DMY LG / (DMY LL DMY LG )

The formula for mixtures differing from 50:50 proportions was:

RCC GL = DMY GL X Z LG / (DMY GG DMY GL ) X Z GL

Where: RCC = relative crowding coefficient, ZGL = the sown proportion of grasses in combination with legumes, Z LG = the sown proportion of legumes in combination with grasses.

Aggressivity index The aggressivity index (AI) of annual grass against the annual legume mixture was calculated as described by McGilchrist (1965) and Trenbath (1986):

AIGL = (DMYGL /DMYGG) (DMYLG/DMYLL)

AILG = (DMYLG/DMYLL) (DMYGL/DMYGL)

Where, AIGL = Aggressivity index of annual grass component grown in mixture with annual legume, AILG = Aggressivity index of annual legume component grown in mixture with annual grass,

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Statistical Analysis The data on seedling count at emergence and tillering, herbage DM yield, plant height (oat and vetch) and chemical analysis were subjected to analysis of variance. Statistical Analysis system (Version 9.0) was used to compute the data. The statistical model used to fit the data was:

Yijk = +T i+B j+ ε ijk; th Where, Yijk = measurable variable, =overall mean of the population, T i= The i Treatment th effect, B j= j Block effect, ε ijk =random error term.

Significant differences between means were separated at p≤0.05 using LSD (Least Significant Difference).

RESULTS Seedling Count at Emergence and Tillering of Pure and Mixed Stand of Oats and Vetch Varieties The seedling counts at emergence and number of tillers for oats and vetch varieties at different seed proportions was significantly different (P<0.01) for both varieties (Table 2). The highest seedling count at emergence for oats was obtained at both pure oats varieties and the lowest seedling count at emergence for oats was obtained from 25% oats (Ab 2806) +75% vetch (ICARDA 61509). The highest and lowest count had differences of 126 seedlings.

The result also revealed that the highest stand count at tillering was obtained at both pure oats varieties, followed by 75% oats (Ab 2291) +25% vetch (lana) mixture which has highest DM yield.

The lowest stand count at tillering was the same as that of at emergence which was 25% oats (Ab 2806) + 75% vetch (ICARDA 61509). The differences between highest and lowest were 624.

The seedling counts at emergence and tillering for vetch varieties, given in Table 2, was also found to be significantly different ( P<0.01) among the different treatments. The highest seedling counts at emergence and tillering was obtained from pure Vicia dasycarpa lana. The seedling counts at emergence for vetch varieties ranged 4 to 12 which was 8 seedlings /m 2 and stand count at tillering has a range of 15 to 408.

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Table 2: The effect of variety and seed proportions on seedling count at emergence and stand count at tillering.

Seedling count at Stand count at Treatments emergence (per m 2) tillering (per m 2) Oats Vetch Oats Vetch 100% oats variety 1 143 a 757 ab 100% oats variety 2 133 a 846 a 75% oats V2+25% vetch V1 120 ab 7bcde 712 ab 37 d 75% oats V2+25% vetch V2 91 abc 4de 636 abc 15 d 50% oats V2+50% vetch V2 69 bcd 5cde 663 abc 23 d 50% oats V2+50% vetch V1 62 cde 5de 528 bcd 45 cd 75% oats V1+25% vetch V1 57 cde 4de 512 bcde 43 cd 75% oatsV1+25% vetch V2 48 cdef 4de 429 cdef 15 d 50% oats V1+50% vetch V1 46 cdef 8bcd 358 def 115 bc 50% oats V1+50% vetch V2 39 def 6cde 400 cdef 37 d 25% oats V2+75% vetch V2 35 def 6bcde 340 def 27 d 25% oats V2+75% vetch V1 27 def 9abc 288 def 154 b 25% oats V1+75% vetch V1 20 def 10 ab 246 efg 124 b 25% oats V1+75% vetch V2 17 ef 7bcde 222 fg 30 d 100% vetch variety 1 12 a 408 a 100% vetch variety 2 6cde 164 b P value 0.0001 0.0001 0.0001 0.0001 SE 17.992 1.344 93.340 26.719 LSD (5%) 51.964 3.880 269.580 77.170 abc means with different superscripts within a column are significantly different (P<0.05)

Herbage Dry Matter Yield and Related Stand Traits of Mixed and Pure Stands of Oats and Vetch varieties The results from analysis of variance for herbage DM yield, plant height, vigor and plot cover of sole oats and vetch varieties and their mixtures was given in Table 3. The effect of treatment was significantly different for herbage DMY, oats height, vetch height and vigor while for plot cover not significantly different was observed.

The highest mean value of herbage DM yield was recorded for 75% oats variety (Ab 2291) + 25% vetch variety ( Vicia dasycarpa lana) mixed stand and the least herbage yield was recorded for the vetch variety (ICARDA 61509). The DM yield obtained in a mixtures were increased by 25% and >100% for Vicia dasycarpa lana and Vicia sativa ICARDA 61509 vetch varieties respectively. The herbage DM yield also showed an increased with an increasing of oats varieties in a seed proportions. Generally, the DM yields of pure oats varieties and mixture treatments exceeded that of their respective of pure stand vetch varieties.

The result also revealed that from oats variety (Ab 2291) and from vetch variety ( Vicia dasycarpa lana) had better height than their respective varieties (Table 3). The mean of

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 27 these two varieties was 84 and 111 respectively. Vetch variety (ICARDA 61509) showed the lowest height. It was also indicated that this vetch variety had the lowest vigor and plot cover.

Table 3: The effect of variety and seed proportions on herbage DM yield, plant height, vigor and plot cover of oats and vetch mixtures

Height (cm) Plot Treatment DM (t/ha) Vigor Oats Vetch cover 75% oats V2+25% vetch V1 17.61 a 71 bcde 103 bcd 8ab 8 100% oats variety 2 16.32 ab 87 ab 7ab 8 100% oats variety 1 15.76 ab 78 abc 9a 8 75% oats V1+25% vetch V1 15.57 ab 51 e 96 cd 9a 9 75% oats V2+25% vetch V2 15.43 ab 77 abcd 63 e 8ab 8 25% oats V2+75% vetch V1 14.09 abc 80 abc 116 abc 8ab 9 100% vetch variety 1 13.94 abc 117 ab 8ab 8 50% oats V2+50% vetch V2 13.72 abcd 90 ab 68 e 9a 9 25% oats V1+75% vetch V1 13.49 abcde 72 bcd 94 d 8ab 8 50% oats V1+50% vetch V1 13.44 abcde 73 bcd 123 ab 8ab 8 75% oats V1+25% vetch V2 13.14 bcde 58 de 55 e 7bc 7 50% oats V2+50% vetch V1 12.82 bcde 85 ab 126 a 8ab 8 25% oats V2+75% vetch V2 11.15 cde 95 a 51 e 8ab 8 50% oats V1+50% vetch V2 9.60 def 62 cde 53 e 7bc 7 25% oats V1+75% vetch V2 9.29 ef 65 cde 55 e 7abc 8 100% vetch variety 2 6.48 f 60 e 5c 6 P value 0.0009 0.0001 0.0001 0.034 0.1116 SE 1.47 6.738 7.017 0.604 0.546 LSD (5%) 4.247 19.461 0.8 1.743 1.577 abc means with different superscripts within a column are significantly different (P<0.05)

Herbage Nutritive Value of Mixed and Pure Stands of Oats and Vetch varieties Analysis of variance and level of significance for pure stand of oats and vetch varieties and their mixtures at different seed proportions on chemical composition were given in Table 4. The result showed that Ash, ADF, NDF, CP and cellulose significantly different among treatments. But the ADL & hemicelluloses values showed no significant variation.

Ash content was significantly affected by variety and seeding proportions (Table 4). The highest ash content was recorded for 25% oats variety (Ab 2806) + 75% vetch variety (ICARDA 61509) followed by 75% oats varieties +25% vetch varieties. The ash content of both varieties of vetch was low compared to the mixtures and sole oats varieties. The lowest ash content was obtained from Vicia sativa ICARDA 61509.

The present study also revealed that the CP content varied among the treatments (Table 4). Both varieties of vetch showed better CP content and from the two vetch variety Vicia dasycarpa lana had better CP content. Though the CP content of mixtures were below the

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 28

CP content of their respective pure vetch varieties, mixtures showed greater than CP content of their respective pure oats varieties. Generally, the CP content was relatively increased with increasing rate of vetch ( Vicia dasycarpa lana) seed proportion in the forage which is not for Vicia sativa ICARDA 61509.

The NDF content of the sole varieties of oats and vetch and their mixtures varied significantly (Table 4). The two vetch varieties exhibited the lower mean values of NDF content than the two varieties of oats and mixtures.

The result from the present study also indicated that the mean value of ADF was significantly affected (P<0.001) by treatments. The decline in ADF levels with increasing vetch seed proportion observed and Vicia sativa ICARDA 61509 showed relatively lower ADF level.

The acid detergent lignin (ADL) contents of the sole varieties and mixed crops are not significantly affected (P>0.05) by varieties and seed proportions.

The result also revealed that cellulose content significantly varied among the treatments (Table 4). The cellulose content of the treatment also showed the highest value when compared with hemicelluloses and lignin. It was also revealed that hemicelluloses content didn’t show the variation ( P>0.05) among treatments.

Table 4: The effect of varieties and seed proportions on qualities of oats and vetch mixtures.

Chemical composition Treatments DM (%) Ash ADF ADL NDF CP Hemi Cell 100% oats variety 1 93.56 a 11.68 abc 31.67 bcde 4.60 b 49.87 abcd 14.56 gh 18.20 abc 27.07 abcd 100% oats variety 2 93.40 a 11.53 abc 36.47 a 5.20 b 53.73 abc 13.76 h 17.27 abcd 31.27 a 75% oats V1+25% vetch V1 92.95 a 11.62 abc 32.50 abcd 7.80 ab 41.80 cde 17.67 bcd 9.30 cd 24.70 bcde 50% oats V1+50% vetch V1 92.85 a 11.59 abc 27.73 ef 10.13 a 44.73 bcde 17.75 bc 17.00 abcd 17.60 f 25% oats V1+75% vetch V1 91.15 b 11.43 abc 31.60 bcde 7.90 ab 60.00 a 18.68 ab 28.40 a 23.70 bcde 75% oats V1+25% vetch V2 93.76 a 12.21 a 28.60 def 6.40 ab 41.93 cde 17.73 bc 13.33 bcd 22.20 bcdef 50% oats V1+50% vetch V2 93.06 a 11.17 abc 28.73 cdef 5.40 b 41.60 cde 17.12 bcde 12.87 bcd 23.33 bcdef 25% oats V1+75% vetch V2 93.10 a 12.30 a 26.60 def 6.33 ab 42.07 cde 17.48 bcd 15.47 bcd 20.27 ef 75% oats V2+25% vetch V1 92.90 a 12.07 ab 32.07 abcde 7.00 ab 56.67 ab 16.55 cdef 24.60 ab 25.07 bcde 50% oats V2+50% vetch V1 93.05 a 10.69 bcd 32.13 abcde 6.80 ab 49.73 abcd 15.55 ef 17.60 abcd 25.33 bcde 25% oats V2+75% vetch V1 93.36 a 11.49 abc 33.07 abc 5.33 b 50.60 abcd 18.58 ab 17.53 abcd 27.73 abc 75% oats V2+25% vetch V2 93.06 a 11.78 ab 28.60 def 4.20 b 46.00 bcde 16.01 defg 17.40 abcd 24.40 bcde 50% oats V2+50% vetch V2 93.23 a 11.74 abc 33.27 ab 5.27 b 49.80 abcd 15.46 fg 16.53 abcd 28.00 ab 25% oats V2+75% vetch V2 93.22 a 10.85 abcd 32.53 abcd 10.47 a 48.73 abcde 15.56 ef 16.20 bcd 22.07 cdef 100% vetch variety 1 93.67 a 10.24 cd 33.27 ab 6.40 ab 39.47 de 19.80 a 6.20 d 26.87 abcd 100% vetch variety 2 92.75 a 9.35 d 27.73 ef 6.20 ab 36.73 e 18.01 bc 9.00 cd 21.53 def P level 0.2019 0.0395 0.0044 0.2939 0.0301 0.0001 0.0934 0.0101 SE 0.494 0.525 1.544 1.596 4.312 0.565 4.137 2.045 LSD (5%) 1.428 1.516 4.459 4.610 12.455 1.633 11.947 5.907 abc means with different superscripts within a column are significantly different (P<0.05)

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 29

Crude Protein Yield (CPY) and Neutral Detergent Fiber Yield (NDFY) Figure 1 shows the calculated CPY and NDFY from the DMY of the pure oats and vetch and their mixtures. The highest CPY and NDFY was obtained from the mixture of 75% SRCP × 80 Ab 2291 + 25% Vicia dasycarpa lana and the lowest was obtained from Vicia sativa ICARDA 61509. The oats varieties showed better result and mixtures with the Vicia sativa ICARDA 61509 were relatively showed low CPY and NDFY.

CPY (t/ha) NDFY (t/ha) Tot(t/ha) 14

Figure1: Nutrient yield indices CPY (tha 1) and NDFY (tha 1)

Biological Compatibility and Yield Advantages of Oats and Vetch Mixtures Indices comparing plants in pure stands and mixtures are presented in Table 5. The RY of both varieties of oats and vetch are increased as seed proportions of oats and vetch are increased. The result also showed, RY of oat varieties was below a unity which indicates the DM yield of oats varieties in a mixture is below sole varieties of oats. The RY of vetch variety indicated that when 75% of vetch variety ( Vicia sativa ICARDA 61509) mixed at the proportion of 25% of both varieties of oats; the value of RY of vetch showed greater than one. The highest RY of vetch was obtained at the seed proportion of 25%:75% oats (Ab 2291) and vetch (ICARDA 61509). The RY of both varieties also showed that the RY increased with increasing seed proportions and vice versa.

The result from the Table 5, revealed that the RYT of mixtures were greater than 1 except when vetch variety ( Vicia dasycarpa Lana.) mixed at the seed proportion of 25% and 50%

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 30 of both varieties of oats. Moreover, the greatest RYT (1.48) was calculated in the oats vetch variety (Ab 2291 and ICARDA 61509) mixed at the seed proportion of 50:50. In addition, the RYT of all mixtures of vetch variety (ICARDA 61509) with both varieties of oats were greater than one.

Competition function of the mixtures of two oatsvetch component species in relation to RCC was also given in (Table 5). The result showed that at the seed proportion of 75% oats varieties with 25% vetch varieties; the oats varieties were found greater than vetch varieties. It was also shown that when vetch variety ( Vicia dasycarpa lana) mixed with the two varieties of oats except at seed proportion of 75%:25% oatsvetch mixtures respectively; the RCC of vetch was greater than that of oats. In mixing of vetch variety (ICARDA 61509) with both varieties of oats the RCC of oat varieties was higher except at the proportion of 50%:50% with oats variety (Ab 2806).

The results of aggressivity index conformed to those of RY. The aggressivity indexes of oats varieties are higher only at the mixture of 75%:25% oatsvetch. The vetch varieties had positive value of aggressivity index except when mixed at proportions of 75% oats varieties + 25% vetch varieties. The result also showed the aggressivity index of both varieties increases with the increasing seed proportions of both varieties as that of RY.

Table 5: Relative Yield, Relative Yield Total, Relative Crowding Coefficient and Aggressivity Index of Oats and vetch mixtures.

Relative Crowding Aggressivity Seed Relative Yield Crop RYT Coefficient Index proportion Oats Vetch Oats Vetch A oats A vetch Oats V1:Vetch V1 25:75 0.214 0.726 0.940 0.051 0.497 0.512 0.512 Oats V1:Vetch V1 50:50 0.426 0.482 0.909 0.743 0.931 0.056 0.056 Oats V1:Vetch V1 75:25 0.741 0.279 1.020 0.536 0.073 0.462 0.462 Oats V1:Vetch V2 25:75 0.147 1.074 1.222 0.032 2.707 0.927 0.927 Oats V1:Vetch V2 50:50 0.305 0.741 1.045 0.438 2.855 0.436 0.436 Oats V1:Vetch V2 75:25 0.625 0.507 1.132 0.313 0.193 0.118 0.118 Oats V2:Vetch V1 25:75 0.216 0.758 0.974 0.052 0.587 0.542 0.542 Oats V2:Vetch V1 50:50 0.393 0.460 0.853 0.647 0.851 0.067 0.067 Oats V2:Vetch V1 75:25 0.809 0.316 1.125 0.795 0.087 0.493 0.493 Oats V2:Vetch V2 25:75 0.171 1.290 1.460 0.039 0.835 1.119 1.119 Oats V2:Vetch V2 50:50 0.420 1.058 1.479 0.725 18.14 0.638 0.638 Oats V2:Vetch V2 75:25 0.709 0.595 1.304 0.457 0.276 0.114 0.114

DISCUSSION Seedling Count at Emergence and Tillering The higher Seedling count at emergence and tillering for oats varieties had related to seed rate base of sowing which were 80kg for oats varieties and 20kg for vetch varieties. The

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 31 variation of seedling count was due to seed proportion that it is increased with increasing seed proportions of both oats and vetch varieties and the present report agreed with (Assefa and lendin, 2001). Treatments that had highest seedling count also showed relatively higher DM yield and vice versa which concurs with the results of others (Geleti, 2000; Alemu et al ., 2007).

Herbage Yield and Related Stands The significance of treatments observed for herbage DM yield were similar to reports of others (Assefa and Ledin, 2001; Alemu et al ., 2007). Geleti, 2000 also reported that in the grasslegume mixtures grasses showed higher herbage DM yield. In the present study, relatively higher DM yield was obtained from mixtures of 75% oats25% vetch varieties and pure oats. It seems that the relative DM yield increased in mixture was one of the advantages obtained due to intercropping of the component species.

In current study the DM yield of pure oats and mixtures higher concurred with Lithourgidis et al . (2006) which yields of mixtures were similar to that of pure oats and greater than that of pure common vetch. Ross et al . (2004) also reported that forage yield of oats berseem clover intercrops was 50–100% higher than yields of pure berseem clover under twocut harvesting in Montana. These implies that the yield advantage of mixing vetch varieties with that of oats varieties. Similarly, Caballero et al . (1995) showed yields of oatsvetch mixtures to be higher by 34% higher than pure vetch.

In comparison of vetch species Vicia sativa ICRDA 61509 vetch species showed lower DM yield than Vicia dasycarpa lana which agreed with (Gezahegn et al ., 2014).

Plant height was one of the contributors for green fodder and dry matter yield; because varieties that had highest plant height varieties showed better DM yield within their varieties and this rport agreed with (Dhumale and Mishra, 1979).

Nutritional Quality of Pure and Mixed Oats and Vetch Varieties The ash content is the concentration of minerals in the forages. The lower ash content that vetch varieties showed agreed with (Negash, 2014). This variation in concentration of minerals in forages induced by factors like varieties (Gezahegn et al., 2014), plant developmental stage, morphological fractions, climatic conditions, soil characteristics and fertilization regime (Jukenvicius and Sabiene, 2007). McDonald et al . (2002) also reported that mineral concentration declines with age and is also influenced by soil type, soil nutrient levels and seasonal conditions.

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 32

Crude protein content is one of the very important criteria in forage quality evaluation (Geleti, 2000; Lithourgidis et al ., 2006). Legumes in general and vetch in specific had better CP content compared with grasses and cereals. The inclusion of vetch in oats significantly improves the biomass quality of forages. Assefa and Ledin (2001) reported that vetch was the highest in nutritional parameters analyzed than oats but lower in dry matter (DM) forage yield per hectare.

The CP content of vetch varieties and mixtures showed greater than the threshold level (15%) reported to be optimal for production or growth (Norton, 1982). In comparison of the two vetch varieties Vicia dasycarpa lana showing higher CP content concurred with reports of Gezahegn et al . (2014). Generally, legumes have higher feeding values due to their higher protein content.

The neutral detergent fiber (NDF) concentration in forage is a dominant factor in determining forage quality. An increasing trend for NDF and ADF was observed with increasing seed proportion of oats in the mixture and this agreed with reports of others (Gezahegn et al ., 2014; Negash, 2014). This is due to the fact that grasses contain higher concentrations of NDF and ADF than do legumes.

Geleti (2000) indicated that the NDF contents above the critical value of 60% results in decreased voluntary feed intake, feed conversion efficiency and longer rumination time. According to Van soest (1965) the critical level of NDF which limits intake was reported to be 55%. However, the NDF content of all the treatments were observed to be below this threshold level except for 25% oats (Ab 2806) +75% vetch ( Vicia dasycarpa lana) and 75% oats (Ab 2291) +25% vetch ( Vicia dasycarpa lana).

Acid detergent fiber (ADF) is the percentage of indigestible and slowly digestible material in a feed or forage (McDonald et al ., 2002). This fraction includes cellulose, lignin and pectin. Acid detergent fiber has a positive relationship with the ages of the plant (NRC, 1981). The lower ADF observed indicates it is more digestible and more desirable which agreed with the report of Negash (2014).

The nonsignificance of acid detergent lignin (ADL) contents and lower values of the treatments concurred with observations of Geleti (2000) in Panicum coloratum and Stylosanthes giuanenis mixtures. The higher the ADL content and the lower will be the digestibility of the feed. The presence of insoluble fiber, particularly lignin, lowers the overall digestibility of the feed by limiting nutrient availability (Mustafa et al., 2000).

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 33

Crude Protein Yield and Neutral Detergent Fiber Yield Crude protein and neutral detergent fiber were the most important nutrients that determine the quality of forages. Crude protein yield (CPY) and neutral detergent fiber yield (NDFY) were the total important nutrients yield. Mixtures at seed proportion of 75% oats + 25% and 50% oats + 50% vetch had relatively higher total nutrients. The result also concurred with report of Geleti (2014) that higher CPY indicates higher importance of the forages.

Biological Compatibility of Oats and Vetch Mixtures The RY which compare yield of the component variety in the mixtures with the respective to pure stand varieties; as indicated it was less than one. The RY values less than one means that the yields obtained in mixed stand is less than those obtained in pure stands. In the present study, the RY of vetch (1.29) indicated that the DM yield obtained from mixture of 25% oats (Ab 2291) + 75% vetch (ICARDA 61509) was higher than 29% in pure stand of Vicia sativa ICARDA 61509 and this report agreed with Diriba (2000).

In addition, the RY showed relationship with the seed proportion which shows an increasing trend with an increased seed proportion and vice versa and report is similar to others (Lithourgidis et al ., 2006). It seems that yield of forages was influenced by seed proportions.

The intercropping system resulted in higher cumulative total biomass yield than either of the sole crops, resulted in RYT values greater than one. This RYT does not only give a better indication of the relative competitive ability of the component species, but also it showed the actual advantage due to intercropping (De wit and Van der Bergh, 1965). In the present study, vetch variety ( Vicia sativa ICARDA 61509) mixed with both varieties of oats indicated that the yield obtained from mixtures of this variety was better than yield obtained in the pure stand.

This report was agreed with Erol et al . (2009) in intercropping maize with faba bean RYT higher than unity is observed. The higher cumulative total biomass yield was probably due to increased light use efficiency of the intercrops, which has resulted in higher cumulative leaf area of the intercrops.

It was also showed that he highest RYT (1.48) indicates that 48% more area would be required for a sole cropping system to achieve the yield obtained from an intercropping system. Geleti (2000) also reported a similar result from intercrops of Panicum coloratum and Stylosanthes giuanenis .

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 34

Jaballa (1995) also reported that intercropped treatments had higher combined leaf area than monocultures and the intercrops gave higher biomass yield per unit area than sole crops.

Relative crowding coefficient of the present study indicated that vetch variety ( Vicia dasycapa lana) mixed with oats varieties, vetch varieties were more competent except at the seed proportion of 75%:25% of oatsvetch mixtures and this report was similar with the result of others (Rakeih et al ., 2010; Javanmard et al ., 2014).

Aggressivity index matches the RY which reflects the dominance of vetch varieties except at the seed proportion of 75%:25% oatsvetch mixtures and this observation are similar with that of Javanmard et al . (2014). Others (Oseni, 2010; Zhang and Yang, 2011) also reported that in mixtures of cereal and legumes; cereals may not always be the dominant crops in the intercropping with legumes which had an agreement with the present study.

CONCLUSIONS AND RECOMMENDATIONS Conclusions The varietal and seed proportion effects of oats and vetch on yield and quality of their mixed stand and the compatibility and effects of intercropping of oats and vetch mixtures under varying seed proportion and varieties of the component species were evaluated. The result revealed that herbage DMY was significantly ( P<0.001) affected by treatment with 75% SRCP × 80 Ab 2291 oats + 25% Vicia dasycarpa lana vetch high and Vicia sativa ICARDA 61509 low and the rest treatments being intermediate.

The analysis of variance also showed most chemical composition of the pure stand and mixtures of oats and vetch varieties were significantly different. The crude protein of the vetch varieties and mixtures were above the critical point. The fiber content was not above the reported threshold level which does affect the digestibility. The NDF content most mixtures were found below threshold except 25% oats (Ab 2806) + 75% vetch ( Vicia dasycarpa lana) and 75% oats (Ab 2291) + 25% vetch ( Vicia dasycarpa lana). CP (Concentration and Yield) of 75% oats both varieties + 25% Vetch both varieties and 50 % oats both varieties + 50% Vetch both varieties and NDF (Concentration and Yield) of 75% oats both varieties + 25% Vetch both varieties and 50 % oats both varieties + 50% Vetch both varieties relatively higher.

Relative yield total of 75% oats both varieties + 25% Vetch both varieties and 50 % oats both varieties + 50% Vetch both varieties the mixtures were greater than 1 which indicates

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 35 the yield advantages of mixtures. The calculated RY, RCC and AI values revealed the dominance of vetch varieties at compared to that of oats except at the seed proportion of 75% + 25% oatsvetch respectively. These Indices increased with the increasing of seed proportions of both varieties. In general, When the CP, NDF and DMY are combined in to nutrient yield indices NDFY(tha 1) and CPY (tha 1) and calculation of competition indices (RYT, RCC and AI) 75% (oats; both varieties) + 25% (Vetch; both varieties) 50 % (oats; both varieties) + 50% (Vetch; both varieties) showed yield advantage.

Recommendations Based on yield, quality, indices of compatibility and nutrient yield indices (CPY; NDFY, tha1) generated in this study, 75% (oats; both varieties) + 25% (Vetch; both varieties) and 50 % (oats; both varieties) + 50% (Vetch; both varieties) Can be recommended for use by farmers in Bishoftu area and other areas having similar agroecologies and soil type.

Further assessment of the oatsvetch variety mixtures for their performance over years, across diverse agroecologies and onfarm farmer managed plots is also vital to more finetuned recommendation.

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McGilchrist, C.A. and Trenbath B.R. (1971). A revised analysis of plant competition experiments. Biometrics 27: 659677. Mustafa A.F., McKinnon J.J. and Christensen D.A. (2000). The nutritive value of thins tillage and wet distillers' grains for ruminants. Asian Australian Journal of Animal Science 13: 16091618. Negash D. (2014). Evaluation of yield and nutritive value of oats ( Avena sativa ) grown in mixture with vetch ( Vicia villosa ) with or without phosphorus fertilization. M.Sc. Thesis. Haramaya University, Ethiopia. Norton B.W. (1982). Differences between species in forage quality. P. 89110. In: J.B. (ed). Nutritional limits to animal production from pastures. Proceedings of an international symposium held at St. Luica Queensland, Australia, August 2428, 1981. Common wealth agricultural bureau. U.K. NRC (National Research Council). (1981). Nutrient Requirements of Domestic Animals. No. 15.Nutrient Requirements of Goats. National Academy of Sciences, Washington, D.C. Oseni T.O. (2010). Evaluation of sorghumcowpea intercrops productivity in savanna agro ecology using competition indices. Journal of Agriculture Science 2: 229234. Rakeih N., Kayya H., Larbi A. and Habib N. (2010). Forage yield and competition indices of Triticale and Barley mixed intercropping with common Vetch and Grasspea in the Mediterranean Region. Jordan Journal of Agricultural Sciences 6(2). Ross S.M., King J.R., O’donovan J.T. and Spaner D. (2004): Inter cropping Berseem Clover with Barley and Oat Cultivars for Forage. Agronomy Journal 96: 17191729. Starks P.J, Zhao D., Philips W.A, Coleman S.W. (2006). Herbage mass, nutritive value and canopy spectral reflectance of Bermuda grass. Grass and Forage Science 61: 101111. Statistical Analysis System (SAS) (2002). SAS/STAT guide for personal computers, version 9.0 editions.SAS Institute Inc., Cary, NC, USA. Trenbath B.R. (1986). Resource Use by Intercrops. In: Francis C A (editor) 1986. Multiple Cropping. Macmillan Publishing Company, New York. pp. 5781. Van Soest P.J. (1965). Symposium on factors influencing the voluntary intake in relation to chemical composition and digestibility. Journal of Animal Science 24: 834. Van Soest P.J. and Robertson J.B. (1985). Analysis of Forages and Fibrous Foods. A Laboratory Manual for Animal Science 613.Cornel University, Ithaca. New York, USA, 202p. Whiteman P.C., Awarding S.S., Wallis E.C. and Brucc R. (1980). Tropical Pasture Science. Oxford University, London, pp: 425. Zhang G., Yang Z. and Dong S. (2011). Inter specific competitiveness affects the total biomass yield in an alfalfa and corn intercropping system. Field Crops Research 124: 6673.

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Yield and Yield Components of Maize (Zea mays L.) Groundnut (Arachis hypogaea) Intercropping as Affected by Spacing and Row Arrangements

Melkamu Dugassa 1*, Hirpa Legesse 2, Negash Geleta 2

1Center for studies of Environment and Society, Wollega University, Nekemte Ethiopia 2Department of plant Sciences, Wollega University, Nekemte, P.O. Box: 395, Ethiopia

Corresponding Author; Emil [email protected], mobile: +251923443575

Abstract A study was conducted during the main cropping season of 2015 /2016 at Wollega University Uke Research and Demonstration station with the objectives of determining the effect of row arrangements and spacing in maize groundnut intercropping on yield and yield components of the crops. Maize BH 540 and groundnut local were used as a planting material. The treatments consisted of four row arrangements with five intra row spacing for groundnut combined factorially and arranged in randomized complete block design. Groundnut sole was planted at row and plant spacing of (60*10) cm. Row spacing for the intercropped groundnut was 37.5cm when 1:1and 2:1row arrangement and 25cm was used in 1:2 and 2:2 row arrangements. Intercropped and maize sole was planted at a spacing of 75 x 25 cm. Data were collected on yield and yield components of both crops. The analysis of variance has shown that there were no significant differences at probability <0.05 in all yield and yield components of maize except biomass and grain yield in tone hectare -1. Treatment 2:1*30cm produced the highest biomass and grain yield of maize. All Groundnut yield and yield components except number of seed per pod, hundred pod weight and hundred seed weight were significantly affected at p<0.05 due to the interaction effects. The highest number pod yield per plant, productive pod per plant, pod yield per plant, and biomass yield plant –1 were observed in treatment 1:1*30cm. The highest biomass and grain yield in tone hectare -1 were produced from treatment 1:2*10cm.The sole cropping was significantly different and attained the highest values for all yield and yield components of maize except number of ear plant -1 and harvest index while groundnut sole cropping was significantly different and attained the highest values for all yield and yield components studied.

Keywords : Number of pods per plant; Pod yield per plant; Pod Yield per hectare; Grain yield per hectare

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INTRODUCTION Maize is an annual crop of great importance; it was first domesticated in America. It is the most important cereal crop in the world after wheat and rice (Onwueme and Sinha, 1991). Maize has the highest average yield per hectare and it is grown in most parts of the world over a wide range of environmental conditions. The crop belongs to the Family Poaceae that is used as a source of carbohydrate to both human (in the developing countries) and animal feed worldwide due to its high feeding value (Undie et al., 2012 ). It is recently used in production of biofuel. It is equally well accepted for feed ingredient and can contribute up to 30% protein, 60% energy, and 90% starch in animal diet. It is a major item in the diet of many tropical countries whereas in the temperate regions, maize is the main grain used for animal feed (Dado, 1999).

Global production exceeds 600 metric tons (McDonald and Nicol, 2015). Out of this 60% produced in the developed countries, particularly by the United States of America, China produces 27% of the world’s maize. The rest is produced in countries of Africa, Latin America and southern Asia. The major producers in Africa are South Africa, Nigeria, Egypt and Ethiopia (USDA, 2007). Maize is one of the most important cereals cultivated in Ethiopia. It ranks second after teff in area coverage and first in total production. Maize is cultivated in a wide range of altitudes, moisture regimes, soil types and terrains, mainly by smallholder crop producers, which comprise 80 percent of the total population, in all regional states. Maize is currently grown across 13 agroecological zones, which together cover about 90 percent of the country (Dawit et al ., 2008). According to CSA (2014), in Ethiopia maize is produced on an area of 2 million hectares and occupies more than 21% of the area allocated to cereals and 30% of the total cereal production which accounted for 6.5 million tones. The crop is grown by the vast majority of the rural households and food staple especially in major growing regions. Current national average grain yield is 3.5 tones ha 1 which is very low as compared to developed countries. FAOSTAT, (2010) report showed the yield per hectare of different countries as 10.3 tones ha 1 for USA, 9.7 tones ha 1 for Germany, 8.4 tones ha 1 for Canada 4.96 tones ha 1 for South Africa and 5.1 tones ha 1 the world average.

In Ethiopia, the crop is an important because of its high productivity per unit area, suitability to major agro ecologies, compatibility with many cropping systems, ease of traditional dish preparation. It is also a food security crop in the country where recurrent drought is a common phenomenon (Tesfaye et al ., 2001).

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Despite the large area under maize, the national average yield of maize is about 3.5 t/ha which is by far below the world’s average yield which is about 5.1t/ha (FAOSTAT, 2010). The low productivity of maize is attributed to many factors like frequent occurrence of drought, declining of soil fertility, poor agronomic practice, limited use of input, insufficient technology generation, lack of credit facilities, poor seed quality, disease, insect and weeds (CIMMYT, 2004).The availability of quality seed with necessary inputs at the right time and place with a reasonable price is crucial. The maize productivity gap between stressed and high potential areas is not only an issue of technology but also differences in climatic factors. Nonavailability of suitable maize varieties is also responsible for such a significant yield reduction. Unavailability of improved infrastructure and maize grain marketing represents major limiting factors for maize production. Wise utilization and conservation of natural resources will also have a significant impact on maize grain production (Mosisa et al ., 2001).

Groundnut ( Arachis hypogaea L.) is an annual legume which is also known as peanut, earthnut, monkey nut and goobers. Cultivated groundnut originated from South America (Wiess, 2000). It is one of the most popular and universal crops cultivated in more than 100 countries in six continents (Nwokoto 1996). Groundnut is the 13 th most important food crop and the sixth most important oilseed crop in the world. It is grown on 26.4 million ha worldwide with a total production of 38.2 million metric tons (FAOSTAT, 2010). Developing countries account for 97% of the world’s groundnut area and 94% of the total production. Groundnut is an unpredictable crop due to the development of pods underground (Zaman et al ., 2011).Groundnut is one the five widely cultivated oilseed crops in Ethiopia (Wijnands et al., 2009 ). The crop is grown under rainfed and used for oil extraction, and for confectionary in Ethiopia. Moreover, it generates considerable cash income for several small scale producers and foreign exchange earnings through export for the country (Geleta et al ., 2007).

As indicated by FAOSTAT (2011), groundnut yield in Africa is lower (0.98 t/ ha) than the average world groundnut yields 1.77 tons per hectare. Researchers associate these lower yields to abiotic, biotic and socioeconomic factors (Pandey et al ., 2003; Upadhyaya et al ., 2006; Caliskan et al ., 2008). In Ethiopia the national average yield of groundnut is 1.123 t/ ha. Berhanu, et al. (2011). The survey report by Berhanu, et al . ( 2011) indicated the significant yield gap between the farmers’ fields and the research centers, which is due to lack of improved groundnut varieties and as a result of various biotic and abiotic stresses like drought, insect pests, diseases etc.

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Andrews and Kassam, (1976) defined intercropping as the agricultural practice of cultivating two or more crops in the same farm and at the same cropping season. In intercropping farming system, usually one main crop and one or more can be used as added crops (Saka, 2007). The two or more crops used in an intercrop may be from different species or different plant families, they can simply be different varieties or cultivars of the same crop species, such as mixing two kinds of barley seed in the same farm. Main purpose of intercropping is to produce a greater yield on a given piece of land by making use of resources in the way of maximum efficiency. According to Tsigbey et al . (2003) and Naab et al . (2005),to enable the farm family meet its household food needs and cash requirements, many subsistence farmers practice intercropping in which groundnut frequently forms an important part of the system.

Groundnut maize intercropping, as a common practice among farmers in dry land areas is well documented in Ghana (Reddy et al ., 1987 Amankwah et al ., 1990; Tsigbey et al ., 2003; Naab et al ., 2005) and elsewhere (Molatudi and Mariga, 2012; Siddig et al ., 2013; Mehdi, 2013). The yields obtained from the intercrops were found to relate directly to their population densities (Langat et al ., 2006), giving an indication that the overall plant population can be skewed to favor one crop over the other in the intercrop depending on the farmer’s priority or individual crop profitability.

Differences in the canopies of crops appear to provide more efficient light use by spatial arrangements than by sole cropping (Dwomon and Quainoo, 2012). In spite of the multi advantages of intercropping, the farmers in the study area plant maize and groundnut crops separately. Moreover, no research has been done in western region of Ethiopia regarding the effects of spacing and row arrangement in maize groundnut intercropping system. This study was supposed to fill the information gap regarding the effects of spacing and different row arrangement of maize and Groundnut crops on yield and yield components of the crops in the intercropping system. Thus, this trail was conducted to analyze the effects of maize/groundnut intercropping on yield and yield components of the crop.

MATERIALS AND METHODS Description of the Study Area The research was conducted in East Wollega zone, Guto Gida district at Uke Research and Demonstration center of Wollega University during the main rainy season of 2015/2016. Uke is located at about 365km far away from Addis Ababa to the west on NekemteBureBahir Dar Main road. The area is located at altitude between 1500

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1700masl; and it is an area with high temperature, and rain fall conditions. Major crops produced in the area include maize, sorghum, soybean, sesame, groundnut etc.

Planting Material A maize variety BH 540 and groundnut seed locally available were used for the experiment. BH540 a maize variety released by Bako agricultural research center and ground nut seed used was a local variety produced by farmers locally.

Experimental Design The treatments consisted of different row arrangements of maize/groundnut alternately (1:1, 1:2, 2:1, 2:2) one row maize and one row groundnut, one row maize and two rows of groundnut, two rows maize and one row groundnut, two rows maize and two rows groundnut with five different intra row spacing (10, 15, 20, 25, and 30 cm) for groundnut. The treatments are combined factorially and laid out in Randomized Complete Block Design (RCBD).There were 20 treatment combinations and 2 controls (sole Maize and sole Groundnut.) with three replications. Plot size was 3x4m, (12m 2) with spacing of 2m between blocks and 1m between plots.

Experimental Procedure The total area used for the experiment was 1392 m 2 (87*16m). The area was cleared of grasses and crop debris and then ploughed with mounted tractor and be harrowed. Planting of seeds was carried out by putting seeds of maize with in ridges by (75*25) cm. using 25 kg 1 seed of maize and 100 kg of DAP were used at planting and 200kg of urea was used (100 kg during planting and the remining100 kg at knee stage for maize at 40 days after planting). Groundnut sole was planted at row and plant spacing of (60*10), and seed rate is 100kg 1.

The intercropped groundnut was planted in between the normal rows of maize. Spacing for the intercropped groundnut crop was 37.5x 10cm, 37.5x15cm, 37.5x20cm, and 37.5x25cm and 37.5x30cm inter and intra row respectively when 1:1 and 2:1row arrangements were used. In 1:2 and 2:2row arrangements, 25x10cm, 25x15cm, 25x20cm, 25x25cm and 25 x30cm inter row and intra row spacing were used respectively. Weeding was carried out manually at 4 th and 6 th weeks after planting. Harvesting of maize was done by cutting the whole plant after fully matured and dried from the middle three rows and the cobs were collected together while the Stover was collected separately. The grain of maize was shelled from the cob by hand. Groundnut was harvested by digging out the whole plant including the pods with a hoe and turned over with the roots facing up to dry

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 43 the pods in the sun to maintain a constant weight before weighing to separate the pods and then shelled by hand to get grain.

Data Collected and Analysis Maize: Ear height, Ear diameter, number of ears per plant, number of rows per ear, number of kernel rows per ear, number of seed per ear, hundred seed weight, biomass Yield, grain yield and harvest index were collected.

Groundnut: Yield and yield components of groundnut like number of pods per plant, number of seeds per pod, hundred pod weights, hundred seed weight shelling percentage, grain yield harvest index and above ground biomass were collected.

RESULT AND DISCUSSION Maize The analysis of variance (ANOVA) of this study showed that there was no significant difference at ( P<0.05) in ear length of maize due to the effects of row arrangements while there was a significant difference due to the effect of spacing. The interaction effect of row arrangement and spacing was not significant for this parameter (Table 1).The ear diameter, number of ear per plant and number of row per ear were significantly affected (P<0.05) due to row arrangement and spacing but not significantly affected by the interaction effects (Table 1).The sole cropping was significantly different from the intercropping treatments in these parameters except number of ear per plant (Table 4).

Number of seeds per row was significantly affected ( P<0.01) due to the effects of row arrangement and spacing but not significantly affected by their interaction effects (Table 1). Arrangement three (2:1) produced the highest (42.01) number of seed per row though it was not statistically different from arrangement one (1:1) while row arrangement four (2:2) and (1*2) produced the lowest (41.05) number of seed per row (Table 2). Spacing of 30cm was significantly different among the spacing and produced the highest (42.53) while spacing of 10cm showed the lowest (40.70) number of seeds per row (Table 3).

The number of seed per ear was significantly affected ( P <0.05) due to the effects of row arrangement and spacing but not by the interaction effects (Table 1).Row arrangement three (2:1) showed the highest (566.68) number of seed per ear though it was not statistically different from arrangement one (1:1). Arrangement four (2:2) attained the lowest (528.07) NSPE but not statistically different from arrangement three (2:1) (Table 2). Spacing of 30cm attained the highest (587.70) number of seed per ear however not

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 44 statistically different from spacing of 25cm while spacing of 10cm attained the lowest (508.58) number of seed per ear (Table 3).This might be due to more interspecific competition for resources in the closer spacing that increases the plant population. The sole cropping was significantly different from the intercropping treatments in number of seed per ear and attained the highest mean value (Table 4)

Biomass yield in tone hectare 1 was significantly affected ( P <0.01) due to the effects of row arrangement and spacing while significantly affected ( P<0.05) due to their interactions (Table 1). The treatment composed of two rows of maize, one row of groundnut by 30cm (2:1*30cm) produced the highest biomass yield in tone per hectare among the intercropping treatments (Table 5).The sole cropping produced the highest (34.49) BYt/ha though it was not statistically different from arrangement one (1:1) (Table 4).

Grain yield in tone hectare 1 of maize was significantly affected ( P<0.05) due to the effects of row arrangement but not due to spacing. The interaction effects of row arrangement and spacing significantly affected the grain yield of maize (Table 1). The highest grain yield among the intercropping treatments was produced by the treatment composed of two rows of maize and one row of groundnut by 30cm (2:1*30cm) (Table 6).The sole cropping was significantly different from the row arrangements and spacing of the intercropping situation and produced the highest (10.40) grain yield in tone hectare 1 (Table 4). The maize yield under intercropping treatments was lower than that of respective monoculture, though its population was constant regardless of the treatments.

The yield reduction in maize in the intercropping situation compared to the sole cropping was 1.443.84%. The highest grain yield of maize in monoculture compared to their yield in the intercropping situation might be due to absence of interspecific competition between maize and groundnut. Huxley and Maingu (1978) reported 11 % yield reduction in cereal in the intercropping of cereal legume. The result of this intercropping study was in agreement with the findings of Quayyum and Maniruzzaman (1995), Nag et al. (1996) and Uddin et al. (2003) who reported yield reduction in maize under intercropping situation. The result was also in agreement with the works of Francis et al. (1982) who reported drastic yield reduction of 31% in yield of maize intercropped with climbing bean. However, the result was in disagreement with the works of Kimani et al. (1999) who indicated that intercropping maize with bean tended to lower maize grain yield but the effects were not significant.

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Hundred seed weight was not significantly affected ( P<0.05) due to the effects row arrangement, spacing and their interaction effect (Table 1). The result was in agreement with the work of Agegnehu et al. (2006) who reported that there were nonsignificant differences between the weights of 1000 barley seeds in different combinations of barley and fababean cumulative intercropping. The result also agrees with the works of and Tilahun (2002) Tolera (2003) who reported that planting density of beans had no significant effect on 1000 kernel weight of maize. The sole cropping was significantly different from the spatial arrangements of the intercropping in HUSW (Table 4).

Harvest Index was significantly affected ( P<0.05) due to the effect of row arrangement and spacing but the interaction effect was not significant (Table 1). The highest (32.9) and the lowest (30.5) harvest index were obtained from row arrangement four (2:2) and three (2:1) respectively (Table 2) This might be due the differences in competition among the row arrangements that may favors or disfavors the yield and yield components. The highest (32.3) and the lowest (31.1) harvest index were obtained from spacing of 10cm and spacing of 30cm respectively (Table 3).The sole cropping was not significantly affected in HI at ( P<0.05) from the intercropping treatments (Table 4).

Table 1: ANOVA for Yield and yield components of maize in groundnut Intercropping.

Sources of Df EL ED NEPP NRPE NSPR NSPE HI HUSW BYt/ha GYt/ha variation Replication 2 22.316* 0.018* 0.006* 0.026 Ns 0.788* 1079.437* 0.00006* 2.150 Ns 0.147 Ns 0.016* Arrangement(A) 3 8.55 Ns 0.251** 0.001* 0.390* 4.243** 4856.558* 0.0021** 0.638 Ns 23.903** 0.006* Spacing (B) 4 58.625* 0.108* 0.003* 1.353* 6.381** 11302.057** 0.00026* 1.275 Ns 3.073** 0.002 Ns AXB 12 2.98 Ns 0.007 Ns 0.0003 Ns 0.032 Ns 0.158 Ns 231.487 Ns 0.7 Ns 0.763 Ns 0.333* 0.004* Error 38 20.421 0.877 0.039 8.498 13.557 820.898 0.00004 4.957 0.375 0.0039 CV 4.5 4.47 3.199 3.638 1.437 5.228 2.221 5.573 1.901 0.613

*= significantly different at probability of 0.05 significance level; **=highly significantly different at probability of 0.01 significance level; CV= coefficient of variation; EL= ear length; ED= ear diameter; NEPP= number of ear per plant; NSPR= number of seed per row; NSPE= number of seed per ear; HI= harvest index; HUSW=hundred seed weight; BYt/ha=biomass yield in tone per hectare; GYt/ha=grain yield in tone per hectare

Table 2: Yield and yield components of maize as affected by the main effects of Row Arrangement.

RA EL ED NEP NRPE NSPR NSPE HI HUSW 1(1:1) 100.20 a 3.47 a 1.01 a 13.06 ba 42 a 559.10 a 30.7 c 39.93 a 2(1:2) 100.80 a 3.31 b 1.00 a 12.95 ba 41.12 b 537.91 b 32.3 b 40.06 a 3(2:1) 101.20 a 3.54 a 1.02 a 13.17 a 42.01 a 566.68 a 30.5 c 39.66 a 4(2:2) 99.46 a 3.26 b 1.00 a 12.79 b 41.05 b 528.07 b 32.9 a 40.13 a Mean 100.415 3.395 1.007 12.99 41.54 547.94 31.6 39.94 CV (%) 4.50 4.47 3.19 3.63 1.43 5.22 2.22 5.57 Means in the same column indicated with the same letter are not significantly different RA=row arrangement; EL= ear length; ED= ear diameter; NEPP= number of ear per plant; NSPR= number of seed per row; NSPE= number of seed per ear; HI= harvest index and HUSW=hundred seed weight

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Table 3: Yield and yield components of maize as affected by the main effect of Spacing.

SP EL ED NEPP NRPE NSPR NSPE HI HSW 1 10cm 98.08 c 3.28 b 1.00 b 12.97 c 40.70 d 508.58 d 32.3 a 40.25 a 2 15cm 98.58 bc 3.30 b 1.00 b 12.81 bc 41.06 dc 529.39 dc 31.8 ba 40.25 a 3 20cm 100.08 bac 3.45 a 1.00 b 13.17 ba 41.42 c 549.01 bc 31.5 bc 39.75 a 4 25cm 102.16 ba 3.45 a 1.01 ba 13.21 a 42.00 b 565.02 ba 31.2 c 39.50 a 5 30cm 103.16 a 3.49 a 1.04 a 13.28 a 42.53 a 587.70 a 31.1 c 40.00 a Mean 100.41 3.39 1.01 13.08 41.54 547.94 31.58 39.95 CV (%) 4.50 4.47 3.19 3.63 1.43 5.22 2.22 5.57 Means in the same column indicated with the same letter are not significantly different SP= intra row pacing for groundnut; RA=row arrangement, EL= ear length; ED= ear diameter, NEPP= number of ear per plant, NSPR= number of seed per row; NSPE= number of seed per ear, HI= harvest index; HUSW=hundred seed weight

Table 4: Yield and yield components of Maize in sole and in intercropping

SP EL ED NEPP NRPE NSPR NSPE HUSW HI (%) BY t/ha GY t/ha 10cm 98.93 b 3.44b a 1.00 a 13.14 b 41.94 ba 554.34 b 39.53 bc 0.31 a 32.67 ba 10.17 b 15cm 100.93 b 3.32 b 1.02 a 12.76 c 41.24 b 539.26 b 40.73 ba 0.32 a 31.75 b 10.15 b 20cm 100.06 b 3.44 ba 1.02 a 13.05 cb 41.74 ba 558.17 b 40.06 bac 0.31 a 32.42 b 10.21 b 25cm 101.06 b 3.38 ba 1.00 a 13.04 cb 41.08 b 538.88 b 39.20 c 0.32 a 32.07 b 10.20 b 30cm 101.06 b 3.38 ba 1.00 a 13.04 cb 41.08 b 538.88 b 39.20 c 0.32 a 32.07 b 10.20 b MS 104.00 a 3.70 a 1.09 a 13.46 a 42.60 a 625.53 a 41.33 a 0.31 a 34.49 a 10.40 a Mean 100.408 3.392 1.008 13.006 41.416 545.906 39.744 0.316 32.196 10.186 CV(%) 0.27 5.08 4.74 1.21 1.32 6.26 1.93 3.12 3.33 0.36 Means in the same column indicated with the same letter are not significantly different Sp= intra row spacing for groundnut, MS=maize sole, EL= ear length, ED= ear diameter, NEPP= number of ear per plant; NSPR= number of seed per row, NSPE= number of seed per ear, HI= harvest index, HUSW=hundred seed weight ;BYt/ha=biomass yield in tone per hectare, GYt/ha=grain yield in tone per hectare.

Table 5: Two way interaction table for biomass yield in tone per hectare of Maize intercropped with Groundnut due to Spacing and Row arrangements

Factors Spacing 1(10cm) 2(15cm) 3(20cm) 4(25cm) 5(30cm)

Row arrangement

1(1:1) 32.71 33.06 33.42 33.6 33.6 2(1:2) 30.58 31.47 32 31.82 31.64 3(2:1) 32 33.06 33.6 33.6 34.31 4(2:2) 30.4 30.58 30.76 30.93 31.47 Mean=32.23; CV=1.9 and LSD=1.02

Table 6: Two way interaction table for grain yield in tone per hectare of maize intercropped with groundnut due to spacing and row arrangements

Factors Spacing 1(10 cm) 2(15cm) 3(20cm) 4(25cm) 5(30cm) Row arrangement 1(1:1) 10.2 10.2 10.23 10.22 10.18 2(1:2) 10.21 10.15 10.12 10.18 10.18 3(2:1) 10.15 10.2 10.19 10.2 10.25 4(2:2) 10.13 10.15 10.13 10.2 10.23 Mean=10.18; CV 0.61; LSD=0.11

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 47

Groundnut This study has shown that there was a significant difference in number of pod per plant (P<0.01) due to the effects of row arrangement and spacing but their interaction is significant ( P<0.05) (Table 7). The sole cropping was significantly different from the spatial arrangements of the intercropping and produced the highest (45.66) average number of pods per plant (Table 9). The result agrees with works of Godwin and Mosses (2013) who reported the number of pods per plant was significantly affected under intercropping.

The number of productive pod per plant was significantly affected (P<0.01) due to the effects of row arrangement and spacing and the interaction effect was significant ( P<0.05) (Table 7). The sole cropping was also significantly different from the intercropping treatments and also produced the highest (40.72) average number of productive pods per plant (Table 9).

Number of seeds per pod was significantly affected (P<0.01) due to the effects of row arrangement ( P<0.05) due to spacing and the interaction effect was not significant (Table 7). The sole cropping was significantly different from the spatial arrangements of the intercropping in number of seed per pod and recorded the highest (2.23) average number of seeds per pod (Table 9).This might be resulted from the absence of inter specific competition from the dominant crop maize.

There was a significant difference in pod yield plant 1 in gm (P<0.01) due to the effects of row arrangement and spacing and their interaction was also significant ( P<0.05) (Table 7). The sole cropping was significantly different from the spatial arrangements of the intercropping and attained the highest (26.26) average pod yield per plant which was greater than any of the spatial arrangements of the intercropping treatments (Table 9).This might also be resulted from the absence over shading and inter specific competition by the dominant crop maize.

Hundred pod weights was significantly affected ( P<0.01) due to the effects of row arrangement (p<0.05) due to spacing but not significantly affected due to their interactions (Table 7). The sole cropping was significantly different from the spatial arrangements of the intercropping in hundred pod weight and produced the highest (145.33) gm that was greater than any of the spatial arrangements of the intercropping (Table 9). The sole cropping attained the highest hundred pod weight that might be attributed to the absence of inter specific competition and over shading from the dominant crop maize. The result

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 48 agrees with the works of Nweke et al (2013) who reported a significant difference in pod weight in Maize groundnut OKra intercropping.

Hundred seed weight was significantly affected at (P<0.05) due to the effects of row arrangement and spacing but not due to the interaction effects (Table 7).The sole cropping was significantly different from the spatial arrangements of the intercropping and attained the highest (69.00) gm hundred seed weight ( Table 9).

Harvest index (HI) was significantly affected ( P<0.05) due to the effects of row arrangement but not significantly affected due to spacing and the interaction effects (Table 7). The sole cropping was significantly different from the spatial arrangements of the intercropping in HI and attained the highest (48%) percent which was greater than any of the intercropping treatments (Table 9).

Biomass yield in tone hectare 1 was also significantly affected at (P<0.01) due to the effects of row arrangement, spacing and their interactions (Table 8). The highest biomass yield in tone hectare 1 in closer spacing might be attributed to the plant population obtained per hectare. The treatment composed of one row maize, one row groundnut by 10cm (1:1x30cm) produced the highest biomass yield in tone per hectare (Table 10).The sole cropping was significantly different from the spatial arrangements of the intercropping and produced the highest (12.6) tones biomass yield hectare 1 which was greater than any of the spatial arrangements of the intercropping (Table 9). The result was in agreement with the findings of Sutharsan and Srikrishnah (2015) who reported intercropping significantly affected biomass yield. The result also agrees with the works of Getachew et al. (2006) who reported that the biologic yield of fababean in intercropping decreased compared to the sole culture treatment as a result of increasing inter specific competition. Again the result was in agreement with the work of Thorsted et al., 2006 who indicated a decrease in the biomass yield of white clover when compared with the sole crop in the intercropping of white clover and wheat.

The ANOVA of this study has also shown that pod yield in tone hectare 1 was significantly affected ( P<0.01) due to the effect of row arrangement and spacing but their interaction was significantly affected ( P<0.05) (Table 8). The treatment of one row maize, two row groundnuts by 10cm (1:2x10cm) produced the highest pod yield in tone per hectare among the intercropping treatments (Table 11). The pod yield in tone hectare 1 was differed mainly due to the differences in number of plants per hectare and number of pods per plant. The sole cropping was significantly different from the intercropped one and

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 49 produced the highest (3.31) pod yield in tone hectare 1 (Table 9). The reduction of pod yield might be due to competition and shading effect of maize on the groundnut crop in the intercropping situation. The result agrees with the findings of Ghosh (2002), Sarkar and Pal (2004) and Razzaque et al. (2007) who reported higher pod yield of groundnut in monoculture. The result was also in agreement with the findings of Karim et al. (1990) and Patra et al. (1990) who reported more pod yield for the sole cropping.

The grain yield in tone hectare 1 was significantly affected ( P <0.01) due to the effects of row arrangement and spacing. Their interaction is significant at ( P<0.05) (Table 8). The treatment composed of one row maize, two rows of groundnut by 10cm (1:2*10cm) produced the highest grain yield in tone per hectare among the intercropping treatments (Table 12). The sole cropping was significantly different from the spatial arrangements of the intercropping and produced the highest (2.42) grain yield in tone hectare 1 which was by far greater than any of the spatial arrangements in the intercropping situation (Table 9).

The grain yield of groundnut was reduced by 67.4893.83 % under the intercropping situation in relative to its sole cropping. The poor grain yield of the groundnut in the intercropping situation might attributed by the shading effect of the maize plants on the groundnut and low plant population. The result of this study agrees with the findings of Egbe et al (2009) who reported that low plant population results in low yields. Godwin and Mosses (2013) also reported that the grain yield of Bambara groundnut landraces significantly declined with declined planting density. Similar observation was also made in the findings of Fukai and Trenbath (1993), who reported low grain yield due to competition during the grain production stage. The result was also in line with the findings of Chui and Shible (1984), who reported poor performance of groundnut in intercropping by the taller component crop maize. Huxley and Maingu, 1978 reported 52 % yield reduction in legume in cereal legume intercropping. The result of this study however disagrees with the findings of Atilola (2007) who reported no significant effect of groundnut intercropped with maize on yield parameters of groundnut.

Shelling percentage (SP) was significantly affected ( P<0.05) due to the effects of row arrangement, spacing and their interactions (Table 8). The sole cropping was significantly different from the intercropping treatments and attained the highest (73.33) shelling percentage (Table 9). The SP followed the same trend for the sole cropping with other yield components.

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Table 7: ANOVA for yield and yield components of Groundnut in intercropping with maize

Degrees Sources of Mean square values of Variation freedom NPPP NPPPP NSPP HPW HSW HI PYPP Replication 2 0.882* 0.365* 0.043* 0.35Ns 10.85* 0.00006 NS 0.468* Row 3 171.859** 149.731** 0.16** 28.416** 14.71* 0.0004* 184.368** arrangement(A) Spacing (B) 4 8.589** 6.567** 0.088* 16.166* 9.566* 0.00006 Ns 7.961** AXB 12 0.477* 0.478* 0.004 Ns 1.166 Ns 0.377 Ns 0.00005 Ns 0.941* Error 38 0.608 0.451 0.012 2.385 2.604 0.0001 0.284 Co efficient 6.823 7.195 5.954 1.105 2.553 2.714 5.007 of Variation AXB = Arrangement spacing interaction; Ns = non significant; * =Significantly different at probability of 0.05; **= highly significantly different at p of 0.05; NPPPP=number of productive pods per plant; NSPP=number of seed per pod; HPW=hundred pod weight; HI=harvest index and PYPP=pod yield per plant

Table 8: ANOVA for yield and yield components of Groundnut in intercropping with Maize

Degrees of Mean square Values Sources of Variation freedom PYt/ha SP BYt/ha GYt/ha

Replication 2 0.0003 Ns 0.0001* 0.011 Ns 0.0003 Ns

Row arrangement(A) 3 0.811** 0.0012* 148.609** 0.441**

Spacing(B) 4 0.333** 0.0005* 35.657** 0.169**

AxB 12 0.003* 0.0002* 10.661** 0.001*

Error 38 0.002 0.0001 0.079 0.001

Co efficient of Variation 7.66 1.744 7.525 8.518

Ns = non significant; * =Significant at probability of 0.05; **= highly significant at p of 0.01; BYPP=biomass yield per plant; SP=shelling percentage; BY t/ha=biomass yield in tone per hectare; NPPP= number of pods per plant; NPPPP=number of productive pods per plant; GY t/ha= grain yield in tone per hectare

Table 9: Yield and yield components of Groundnut in sole and in intercropping

HSW PYPP BYPP HI PY BY GY SP NPPP NPPPP NSPP HPW SP (g) (g) (%) t/ha t/ha t/ha 10cm 15.22 b 12.93 b 1.98 b 141.20 b 63.86 b 14.53 b 45.42 b 44.33 b 0.75 b 6.83 b 0.54 b 72.00 ba 15cm 9.26 d 7.46 d 1.81 c 139.26 c 63.93 b 8.02 d 24.34 d 45.33 b 0.82 b 6.09 c 0.59 b 72.66 ba 20cm 13.26 c 10.94 c 1.86 cb 140.46 b 63.20 cb 12.69 c 39.97 c 44.33 b 0.36 c 1.22 d 0.25 c 71.33 bc 25cm 7.97 d 6.03 d 1.73 c 138.06 d 61.80 b 7.37 d 22.92 d 45.66 b 0.41 c 0.86 e 0.29 c 70.33 c 30cm 7.97 d 6.03 d 1.73 c 138.06 d 61.80 b 7.37 d 22.92 d 45.66 b 0.41 c 0.86 e 0.29 c 70.33 c 5(GS) 45.66 a 40.72 a 2.23 a 145.33 a 69.00 a 26.26 a 75.60 a 48.00 a 3.31 a 12.60 a 2.42 a 73.00 a Mean 10.736 8.678 1.822 139.408 62.918 9.996 31.114 45.062 0.55 3.172 0.392 71.33 CV(%) 5.45 5.65 4.52 1.25 1.57 4.52 2.06 1.57 8.78 2.19 7.95 0.99 Means in the same column indicated with the same letter are not significantly different Sp= intra row spacing for groundnut; NPPP= number of pods per plant; NPPPP=number of productive pods per plant ; P=number of seed per pod; HPW=hundred pod weight; HSW=hundred seed weight; PYPP=pod yield per plant; BYPP=biomass yield per plant; HI=harvest index; PY t/ha=pod yield in tone per hectare ; BY t/ha=biomass yield in tone per hectare; GY t/ha= grain yield in tone per hectare and SP=shelling percentage

Table 10: Two way interactions for biomass yield in tone per hectare of Groundnut due to Spacing and Row Arrangement

Factors Spacing

1(10cm) 2(15cm) 3(20cm) 4(25cm) 5(30cm)

Row arrangement

1(1:1) 11.11 7.62 5.97 4.78 4.7

2(1:2) 11.13 8.01 6.62 5.61 5.06

3(2:1) 1.33 1 0.8 0.63 0.55

4(2:2) 2.05 1.4 1.06 0.87 0.73

Mean=3.75, CV=7.52, LSD=0.31

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 51

Table 11: Two way interactions for pod yield in tone per hectare due spacing and row arrangement

Factors Spacing 1(10 cm) 2(15cm) 3(20cm) 4(25cm) 5(30cm)

Row arrangement

1(1:1) 0.99 0.92 0.72 0.58 0.56

2(1:2) 1.02 0.99 0.77 0.7 0.63

3(2:1) 0.6 0.43 0.32 0.26 0.22

4(2:2) 0.63 0.5 0.38 0.3 0.25

Mean=0.59, CV=7.66, LSD=0.11

Table 12: Two way interaction for grain yield in tone per hectare of groundnut due to row arrangement and spacing

Factors Spacing

1(10cm) 2(15cm) 3(20cm) 4(25cm) 5(30cm)

Row arrangement

1(1:1) 0.71 0.66 0.52 0.42 0.41

2(1:2) 0.74 0.71 0.55 0.5 0.46

3(2:1) 0.42 0.31 0.23 0.19 0.15

4(2:2) 0.43 0.36 0.26 0.22 0.18

Mean=0.42, CV=8.51, LSD=0.05

CONCLUSIONS From this study, it can be concluded that maize and groundnut can be intercropped under different spacing and row arrangements with varying yield and yield components. The sole cropping of both component crops has shown superiority in all yield and yield components in this study except number of ear per plant and harvest index for maize.

All Yield and yield components of maize assessed in this study were not significantly affected by the interaction effects of spacing and row arrangement except biomass and grain yield. Yield and yield components of groundnut assessed in this study were significantly affected due to the interaction effects of spacing and row arrangement except number of seed per pod, hundred pod weight, hundred seed weight and harvest index. As observed from the results of this study, to produce more yields of groundnut, sole cropping is advantageous since the yield was drastically decreased (67.4893.83%) due to the different row arrangements and spacing of the intercropping situation but maize can be intercropped with groundnut by less yield sacrifice of (1.443.84%) only.

REFERENCES Andrews D.J. and A. H. Kassam (1976).The importance of multiple cropping in increasing World food supplies, pp. 110 In : R.I. Papendick, A. Sanchez, G.B. Triplett (Eds.), Multiple Cropping. ASA Special Publication 27 American Society of Agronomy, Madison, WI Atilola N.C.P (2007). Effect of interplant Groundnut with Maize on soil organic carbon and Yield of Groundnut and Soil Fertility. Soil Fertility Research 16: 8186.

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Atuahene Amankwah G., Hossain M.A., Assibi M.A. (1990). Groundnut Production and Improvement in Ghana First ICRISAT Regional Groundnut Meeting for West Africa, 1316 Sept. 1988. Niamey, Niger, pp. 4547. Berhanu Gebremedhin S., FernandezRivera Mohammed., Hassena W. Mwangi and Seid Ahmed (2011). Maize and livestock: Their inter-linked rolesin meeting human needs in Ethiopia. Research Report 6 ILRI. De Wit (1960). On competition. Verslagen van Landbouwkundige Onderzoekingen 66(8): 1 Dwomon I.B. and Quainoo A.K. (2012). Effect of spatial arrangement on the yield of Maize and Groundnut intercrop in the northern Guinea Savanna agro ecological zone of Ghana. International Journal of Life Science and Pharma Research 1(2):7885. Egbe O.M., Kalu B.A., Idoga S. (2009). Contribution of common food legumes to fertility status of Sandy soils of the moist savanna woodland of Nigeria. Report and Opinion Journal 1(1):4562. Francis C.A. Prager M. and Tejada G. (1982). Effect of relative planting dates in bean (Phaseolu Vulgaris L.) and Maize ( Zea mays L.) intercropping patterns. Field crops Research 4: 313320. Fukai S. and Trenbath B.R.C (1993). Processed determining intercrop productivity and yield of Component crops. Field Crop Research 34: 247257. Geleta T., Purshotum K.S., Wijnand S., Tana T. (2007). Integrated management of groundnut Root Rot using seed quality and fungicide seed treatment. International Journal of Pest Management 53: 5357. Getachew A., Ghizaw A. and Sinebo W. (2006) Yield performance and land use efficiency of barley and faba bean mixed cropping in Ethiopian high lands. European Journal of Agronomy 25: 202207 Ghosh P.K. (2002) Agronomic and economic evaluation of groundnut (Arachis hypogaea)- Cereal fodder intercropping during the postrainy season. Indian Journal of Agronomy 47(4): 509513. Godwin Adu Alhassan and Mosses Onyilo Egbe (2013). Bambara groundnut intercropping: Effects of planting densities in southern guinea savanna of Nigeria. African Journal of Agricultural Research 9(4): 479486. Karim, M.A. Zaman S.S. and Quayyum M.A. (1990). Study on groundnut rows grown in Association with normal and paired row of maize. Bangladesh Journal of Agricultural Research 17(1): 99102. Langat M.C., Okiror M.A., Ouma J.P., Gesimba R.M. (2006). The effect of intercropping groundnut (Arachis hypogea L) With sorghum ( Sorghum bicolor L. Moench) on yield and cash income. Agricultura Tropica Et Subtropica 39(2):8790 Mehdi D. (2013). Intercropping Two Varieties of Maize ( Zea mays L.) and Peanut ( Arachis hypogaea L.): Biomass Yield and Intercropping Advantages. International Journal of Agriculture and Forestry 3(1): 711. Molatudi R.L., Mariga I.K. (2012). Grain yield and biomass response of a maize/dry bean intercrop to maize density and dry bean variety. African Journal of Agricultural Research 7(20): 31393146.

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Naab J.B., Tsigbey F.K., Prasad P.V.V., Boote K.J., Bailey J.E., Bradenberg R.L. (2005). Effects of Sowing date and fungicide application on yield of early and late maturing peanut cultivars grown under rainfed conditions in Ghana. Crop Protection 24(1):107110 Nweke I.A., Ijearu S.I. and Igili D.N. (2013). The growth and yield performances of groundnut and in Sole cropping and intercropped with Okra and Maze in Enugu, South Eastern Nageria. OSR Journal of Agriculture and Veterinary Science 2(3): 1518. Patel B.P. and Gangavani S.B. (1990). Effects of water stress imposed at various stages on yield of groundnut and sunflower. Journal of Maharashtra Agricultural University 15: 322 324 Razzaque M.A., Rafiquzzaman, S., Bazzaz M.M., Ali M.A. and Talukdar M.M.R. (2007). Study on the Intercropping groundnut with chilli at different plant populations Bangladesh Journal of Agricultural Research 32(1): 3743. Reddy M.S., Kelly G., Musanya J.C. (1987). Recent Agronomic developments in groundnut investigations in Zambia in proceedings of the second regional Groundnut Workshop for Southern Africa, 1014 Feb. 1986, Harare, Zimbabwe. Patancheru, A. P. 502:324 India: ICRISAT. pp. 5764. Saka J.O., Adeniyan, O.N., Akande S.R. and Balogun M.O. (2007). An economic evaluation of Intercropping African yam bean, Kenaf and maze in the rain forest zone of Nigeria. Middle East Journal of Scientific Research 2:18 Sarker R.K. and Pal P.K. (2004). Effect of intercropping rice (Oryza sativa) with groundnut (Arachis hypogaea) and pigeonpea (Cajanuscajan) under different row orientations on rainfed uplands. Indian Journal of Agronomy 49(3): 147150. Shalim Uddin M., Rahaman M.J., Shamin Ara Bagum., Uddin M.J. and Rahaman M.M. (2003). Performance of Intercropping of Maize with Groundnut in saline area under rain fed condition. Pakistan Journal of Biological Sciences 6(2):9294, 2003 Siddig A., Mohamed A., Adam A, Mohamed A., Bahar H., Abdulmohsin R.K. (2013). Effects of Sorghum (Sorghum Bicolor (l) Moench) and Groundnut ( Arachis Hypogaea L) Intercropping on Some Soil Chemical Properties and Crop Yield under RainFed Conditions. ARPN Journal of Science and Technology 3(1): 6974. Sutharsan S. and Srikrishnah S. (2015). Effect of different spatial arrangements on the growth and yield of Maize ( Zea mays L.) and Groundnut ( Arachis hypogaea L.) intercrop in the Sandy Regosol of Eastern region of Sri Lanka. Research Journal of Agriculture and Forestry Sciences. 3(2): 1619. Tesfaye Zegeye., BedassaTadese and Shiferaw Tesfaye (2001). Adoption of high yielding maize technologies in major maize growing regions of Ethiopia EARO (Ethiopian Agricultural Research Organization) Research Report 41 EARO, Addis Ababa, Ethiopia Comparative Study and History. Thorsted M.D., Olesen J.E. and Weiner S. (2006). Width of clover strips and wheat rows Influence grain yield in winter wheat/white clover intercropping. Field Crops Research 95: 280290. Tsigbey F.K., Brandenburg R.L., Clottey V.A. (2003). Peanut production methods in northern Ghana And some disease perspectives. Online Journal of Agronomy 34(2): 3647. Wijnands J.H.M., Biersteker J., Van Loo E.N. (2009). Oil seed business opportunity in Ethiopia Oil seed Research report, Addis Ababa, Ethiopia

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 54

Analyses of Climate Variables and Determination of Chickpea Water Requirement for Rainfed Production in Ada’aa District, Ethiopia

Mengesha Lemma Urgaya

East Shoaw Zone Agriculture and Natural Resources Department, Oromia Bureau of Agriculture and Natural Resources, P.O. Box: 316, Adama, Ethiopia

Email: [email protected] ; Tel +251 911988727 and +251 922686831

Abstract Agriculture is essential for Ethiopian economy while the concerns of climate change impact on agriculture in developing countries have been increasing and this impact could influence agriculture production in a variety of ways. Increasing in temperature and rainfall fluctuation patterns, including the amount of rainfall could adversely affect the productivity of crops. Among the various crops cultivated in the area chickpea productivity is paramount importance. Hence, the study is aimed to characterizing climate variability of the study area and crop water requirement of chickpea under rainfed production. Accordingly, for the purpose of the study, climate data were collected from Debrezeit Agricultural Research Center. Whereas Mann-Kendall test and sen’s slope estimator, INISTAT+v.3.37 were used for analyzing rainfall variability including trends. While, Cropwat 8.0 was used to compute chickpea water requirement. The analysis results showed that the mean annual total rainfall was about 830mm with the growing period ranging from 99 to 215 days. The variability in start of the season for the stations was relatively high as compared to the end of the season. Crop water requirement of chickpea doesn’t vary by planting date in the study area and the total water requirement indicated on ranged between 340.6mm and 346.7mm during the growing season. Whereas, the effective rainfall which is the most determinant factor for yield is very variable by planting dates.

Keywords: Chickpea, Rainfall variability, CROPWAT, CWR

INTRODUCTION In Ethiopia agriculture is the largest source of economy of the country with the majority of the population engaged in the sector (Kidane et al ., 2011). It affords direct livelihood for about 83% of the population, 87% of its export earnings, 73% raw material for agrobased industries and contributing 45% of the country’s gross domestic product (GDP). Ethiopian economy is dominated by subsistence farming where more than 95% is a rainfed (Araya, 2011).The main season crops (cereals, pulses, and oil crops) are grown in Ethiopia (CSA, 2013). Of the pulse crops, chickpea is the major crop with greater production potential (5 t/ha) (Mzezewa and Gwata, 2012). Despite its best production potential, the crop has not

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 55 been widely utilized in the country due to impact of rainfall features and other constraining factors.

Rising in temperature and fluctuating rainfall patterns, including amount of rainfall could adversely affect the productivity of chickpea (Berger and Turner, 2007). For instance, temperature is one of the most important determinants of crop growth over a range of environments (Summerfield et al., 1990).Thus increase or decrease in temperature may have significant effect on the growth and yield of chickpea (Basu and Ali , 2009). At the same time, higher temperatures increases evaporation and transpiration which could have impact soil water availability and crop yield (Clinen and William, 2007).The analysis of rainfall records for long periods provides information about, cropping system, rainfall patterns and variability and used for cultivar choice, that can be grown (NAP, 2007). Furthermore, the amount and temporal distribution of rainfall and other climatic factors during the growing season are critical to crop yields. Poor or excessive rainfall could induce food shortages and famine, as result Ethiopia has suffered from periodical extreme climate events manifested in the form of frequent droughts and flooding that occurred in various years (NAP, 2007). This affects agriculture production and lowers the GDP in Ethiopia (CEEP, 2006).

Ethiopian agriculture is the most susceptible and vulnerable to climate change (Marius, 2009). This is due to its dependency on rainfed agriculture where irrigated agriculture accounting for less than 1% of the country’s total cultivated land (Di Falco et al ., 2011). Therefore, analysis of impact of rainfall variability on crop is essential, especially in Ada’aa District, East Showa Zone of Ethiopia. The area is vulnerable to drought and the people have poor adaptive capacity compared to other parts of Ethiopia. The analysis of rainfall variability is particularly important for pulse crops mainly for chickpea, which is very sensitive to risks associated with high rainfall variability and drought stress, especially at flowering and grain filling stages (Devasirvatham, 2012). This paper sets out to characterizing the impact of rainfall features of the study area and assesses the adverse effect of rainfall variability on chickpea production in Ada’aa District, East Showa Zone, to advance advices on adaptation mechanisms that could help the farmers to move forward direction and improve farmer’s adaptation capacity.

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MATERIAL AND METHODS Description of the Study Area The study was conducted in Ada’aa District around Debrezeit Agricultural Research Centre in Ethiopia. It is located 50 km south from Addis Ababa, in Oromia National Regional State. Its geographical location is from80 36' 0" N to 80 53' 0" N latitude and 380 50' 0" to 390 10' 0" E longitudes with al titude ranges from 1097to 2513 m.a.s.l and boundary area of 894.37 km 2 (Figure1).

Figure 1: Map of the study area

The study area is characterized by unimodal ra infall type which can be seen separately in terms of crop production. The first is the short rainy season, which extends between March to May and locally known as “Belg”. The second is the long rainy season, which extends from June to September (JJAS) and locally known as kiremt. The rainfall distribution during this period annually varies between 587 to 1122.7 mm with a peak rainfall in August in the study area. The amount and distribution of annual and seasonal total rainfall, timing of onset, end dates a nd length of growing period (LGP) are critical information on historical rainfall changeability over an area.

Characterization of Rainfall Features of the Study Area The historical daily climate data of rainfall and temperature (minimum and maximum)were collected starting from 1980 to 2010 from National Meteorological Agency (NMA) of Ethiopia. In order to make the series acquiescent to further analyses, the missing dat a’s

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 57 were checked using Markov chain simulation model in INSTAT+v3.37 version (Stern et al., 2006). Then, the analyses of rainfall feature for the study area were carried out. The INSTAT+ v3.37 software was used to characterize the start and end of rainfall, length of growing period and a range of dry spell length. The onset and end of main season was determined from the rainfallreference crop evapotranspiration (ETO) relationship, this approach was presented in (Ati et al ., 2002). Start of the season was the first occasion when cumulative 3 day rainfall is greater than or equal to 50% of the cumulative 5 day reference crop evapotranspiration and with no consecutive dry spells of longer than 9 days within the following 21 days. The choice of 50% ETo as the threshold for water availability is based on experimental evidence that crop water stress becomes severe when the available water is below half the crop water demand (0.5 ETo) (Dorenboos and Kassam, 1979) and hence the minimum required rainfall amount of a particular date of onset should be at least half of the amount of ETo of that particular date. For end of rainy season (EOS), was determined from rainfall reference evapotranspiration relationship. End of growing season was the cessation of rainy season plus the time required to evapotranspire 100 mm of stored soil water (Kassam et al ., 1978). There was humid period, when rainfall exceeds ETO, at Ada’aa District. So, surplus stored soil water was available to continue through the growing season beyond the cessation of the rainy season. The rainy season was assumed to close down after 30 th September or 274 DOY (day of the year) when 3day cumulative rainfall was less than 50% of the 5day cumulative ETO when soil water balance become 0.5 (Girma Mamo et al ., 2011). The length of growing period (LGP) was determined through subtraction of the SOS from the EOS total seasonal rainfall (mm). Therefore, this inducts the possible plant production time.

On the other hand, the dry spells were analyzed to determine distribution of rainfall and the probability of availability of rains during the critical water requirement periods of crop growth in the rains season which is said to be more reliable for chickpea production in the areas. Dry spells were described as periods with 0.85 mm of rainfall or less. Then dry spell length analysis were used the Markov Chain process, 0.85 mm rainfall as critical water requirement periods of crop growth dry spells (Meinke and Stone, 2005). Most farmers of the study area practiced chickpea planting in the second decade of August to September first week. Therefore, analysis was carried out for the probability of dry spell longer than at least five, seven, ten and fifteen consecutive days after the last rains days.

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Analyzing Rainfall Trends Statistical analyses and simple linear regression analysis were performed with excel sheet and INSTAT v3.37 statistical software for estimating an unknown trend. Trends were assessed at 0.01, 0.1 and 0.05 level of significance using the Mann–Kendall trend test and Sen’s slope estimator (Timo salmi et al ., 2002). A total of monthly, seasonal and annual rainfalls were computed from daily data and trends were determined by using graphs and trend lines. The positive value indicates an upward trend and a negative value indicates a downward trend per given value or calculated time step.

Estimation of Crop Water Requirement and Effective Rainfall In Ethiopia this crop is planted on conserved soil moisture starting from the second dekade of August to first week of September, at which time the water logging problem has recede and drought stress is about to set in. On the other hand chickpea requires 100 day (length of growing period) starting from initial too late development stage (Tesfaye and Walker, 2004). Cropwat 8.0 software was used to analyze the evapotranspiration, crop water requirement, effective rainfall and chickpea supplementary irrigation requirement. The evapotranspiration using the Cropwat software method (ETO Penman calculated from temperature data).The effective rain was obtained from annual mean monthly rainfall data of the station (Dependable rainfall (FAO/AGLW formula). In addition to this, chickpea crop water requirement was analyzed based on Kc (crop coefficient value) and chickpea growth stage data (Tesfaye and Walker, 2004). Besides, for chickpea crop water requirement calculation the critical depletion factor, yield response factor, plant root and planting height were computed (Andreas and Keren, 2002). Chickpea is mostly grown on residual or stored soil water, its planting date was chosen according to the practice of farmers in Ada’aa District and the chickpea supplementary irrigation was analyzed for early, normal (farmers planting date) and late planting date.

RESULTS AND DISCUSSION Seasonal Rainfall Variability at Ada’aa District The seasonal total rainfall ranged from 0 to 138.6 mm in ONDJ, whereas for FMAM ranges from 46.6 to 443.7 mm and 385.1 to 804 mm in JJAS, respectively (Table 1). The CV is much higher for ONDJ (Bega season), then followed by FMAM (Belg season) and least for JJAS (kiremt season). On the other hand, the CV is much higher for Belg total seasonal rainfall than kiremt indicating higher chronological variability of the Belg total season rainfall (Table 1). The annual total rainfalls also showed high inter annual variability that ranged from 587.2 to 1122.7mm. The kiremt season rainfall contributes

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73.1%, Belg (21.9%) and Bega (5 %) of the annual rainfall. Therefore, the annual rainfall amount could not be a problem to chickpea production in the study area and hence, what could be the challenge is the occurrence of different dry spell lengths and water logging as result of rainfall variability of the Ada’aa District.

Table 5: Descriptive statistics of annual and seasonal rainfall at Ada’aa District

Total Seasonal Rainfall (mm) Descriptive Annual ONDJ FMAM JJAS statistics Rainfall (mm) (Dry) (Belg) (Kiremt/Mehare) Minimum 587.2 0 46.6 385.1 Maximum 1122.7 138.6 443.7 804 Range 535.5 138.6 397.1 418.9 Mean 830.38 42.363 181.09 606.92 Std.deviation 144.64 38.955 103.31 102.5 Coeff.of variation 17.4 92 57 16.9 25 th percentile 723.65 11.475 96.35 544.6 50 th percentile 833.55 25.4 167.1 601.95 75 th percentile 916.68 65.075 256.38 676.95

The trend line for long term rainfall anomaly analysis shows shortage of Belg (FMAM) rainfall with decline trends for the period from 1980 to 2010 (Figure 2). While the annual and Kermit (JJAS) seasonal total rainfall trends increased for the period from 1980 to 2010 at Ada’aa District. Regarding the annual rainfall anomaly, 17 years (57%) showed above average rainfall mean record for a long period, while the remaining 13 years (43%) showed below average rainfall amount. Most of the negative anomalies of the annual rainfall (7 years) occur between 1986 and 1996 (Figure 2, and 3) in the study area.

Table 2: MannKendall trend analysis of rainfall (mm)

Rainfall trend Time series Test Z Significant Q June 1.65 + 0.784 July 0.99 1.543 August 0.34 0.331 September 0.26 0.153 Notes: Q = sen’s slope estimator, z = mannkandall trend test

Trends of seasonal monthly rainfall and Mann–Kendall test result for trends at the study area, positive values of normalized test statistics (Z) indicate an increasing trend and negative Z values indicate decreasing trends. The rainfall trend was not significant in all months of the growing season (JJAS) except in June (p=0.1) which demonstrated an increasing trend with a magnitude of 0.78mm per year. Even though it was not significant, the August rainfall trend has shown a decreasing trend with a magnitude of 0.33mm per year (Table 2).

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Figure 2: Season (Bega, Belg and Kermit) rainfall anomaly at Ada’aa District

The mean annual rainfall increased at Ada’aa District in the years 1981, 1983, 1985, 1990, 1993 1996 1997 1998 1999 2001 2003 2005 2006 and 2007. In the rest of years, the annual rainfall showed below normal rainfall (Figure 3). For instance in 1986, 1995 and 2002 seasons there has been a clear confirmation of water stress and droughts in the study area. Mean seasonal rainfall showed a decreasing trend at Ada’aa District for Belg and Kiremt seasons in most of years between 1997 and 2009 (Figure 2 and 3). In common, understanding, the rainfall amount, distribution, onset and cessation date of the season is essential for altering the crop production system, depending on the length of growing period of the crop and its water requirement. Therefore, for the crop planted at the end of the season and short rainfall to satisfy the crop water demand under changing climate depending on the crop type and growth stage, supplementary irrigation is very crucial for getting better yield.

Figure 3: Annual total rainfall anomalies at Ada’aa District

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Analyzing Rainfall Features at Ada’aa District The variability in start of the season over the past 31 years was very high with the early on March 6 observed in years 1983 (72 Day of the year (DOY)), 198 7 (66 DOY), 1996 (70 DOY), 2001 (72 DOY) and 2005 (66 DOY) to the latest around July 11 th (187 DOY) observed in years 1981 (187 DOY) 1995 (175 DOY), 2000 (176 DOY) and 2009 (171 DOY). The mean start of season was 126 DOY which is nearly in the first week o f May with a standard deviation of 39 DOY (Figure 4). As showed in Table 3, the 25 percentile of SOS is on March 27 th (87 DOY) (once in every four years) with the upper percentile on June 10 th (157 DOY) (three times out of four years). Therefore planting e arlier than April 9 (97 DOY) was possible once every four years. Then, the maximum (longest) end of season was 298 days of year (DOY) while the minimum (earliest) was 274 DOY which occurred around the end of September (Figure 5). The average end of season was 281 days of year indicating the variability was very low compared to SOS across the past 31 years in the study area, indicated by small standard deviation 7 days with CV 2.5% (Table 3).

Figure 4: Start of the season (SOS) of rainfall at Ada’aa district

Length of growing period is the time between the SOS and EOS (Table 3). The average growing length period of the study area is 154 days of year which is the difference between the average SOS (127 DOY) and EOS (281 DOY) (Figure 6). There i s a strong relationship between length of the growing period and start of the rain season because the longest growing period not necessarily depends on EOS rather it depends on the SOS. This shows that the study area is characterized by long growing period . Therefore, length of growing period could not be a problem to any crop in Ada’aa District and hence, what could be the challenge is the occurrence of different dry spell lengths.

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Figure 5: End of the season (EOS) of rainfall at Ada’aa woreda

Figure 6: Inter annual length of growing period (LGP)

The length of the growing season was 122 days occurring once in four year where as 187 DOY occurring only in three out of four years at Ada’aa District (Table 3). Most of the variability in length of growing period (LGP) was explained by the start of the season (R2= 0.97) while it was less dependent on the end of the season (R2= 0.065). This can be best explained by reason that the end of season in the study area has been more or less constant (CV=2.5%) and he nce, LGP becomes dependent on the onset of rainfall (Table

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3). That means if the onset date is early the LGP becomes long while the reverse holds, if it starts late. The LGP was strongly correlated with SOS (r = 0.98) whereas weakly correlated with EOS (r = 0.25). A similar result has been pointed by (Kassie et.al, 2012)in Zeway, Ethiopia. On the other hand, according to Figure 6, there is a great variation in the length of growing period in the study area. Therefore, early onset date of the season suggested that planting long cycle crops whereas if the length of growing period is short it is possible to plan for short cycle crop. In addition to this, understanding the variability of length of growing period (LGP) is very important for analysing the risk level of the season and for considering different adaption option in the study area.

The season starts from March 6 (66 DOY) and ends ahead of September 30th. However, using the onset and cessation of rainfall criteria’s, it was difficult to capture the length of growing period for chickpea, as it is mainly sown at the end of the growing season. Hence, as an alternative, crop water requirement of the chickpea was determined for each growth stage and then estimated the likely impact of soil moisture stress.

Table 3: Descriptive statistics for start, end and length of growing season at Ada’aa District for the last 31 years (19802010)

Rainfall features (Start, End and Length of growing period) Descriptive statistics SOS (DOY) EOS (DOY) LGP (days) Minimum 66 274 99 Maximum 187 298 215 Range 121 24 116 Mean 126.67 280.73 154.1 Std.deviation 39.63 7.11 37.1 Coeff.of variation 31.3 2.5 24.1 25thpercentile 87.25 274 122 50th percentile 144.5 279.5 134.5 75th percentile 157.5 285 187

Probability of Dry Spell in Ada’aa District The overall risk of dry spells from the beginning of March (DOY 66) to end of September (DOY 274) in Ada’aa District over the last 30 years period considering chance of occurrence exceeding 5, 7, 10 or 15 days are showed in (Figure 7).The maximum unconditional risk of dry spells with length of more than 5, 7, 10, and 15 days at the beginning of March were 99%, 94%, 70% and 30%, respectively whereas the corresponding dry spell length for mid of April were 99%,91%,65% and 26% respectively. The probability of dry spells of 5, 7 and 10 days decreases gradually starting from June 21 st until the peak rainy period during July and August. The probability of occurrence of short dry spell days is higher than the prolonged dry spells (Figure 7).

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Figure 7: Estimated probability of dry spell and length in Ada’aa District

The probability of occurrence of five days dry spell is the highest, followed by seven and ten dry spells in the growing season. Despite the highest probability of occurrence, its consequence on crop yield may be negligible compared to the longer dry spell s. The probability of 10 and 15 days dry spells occurrence become less than 10% from mid June to end of August. The occurrence dry spell probability of 5, 7, 10 and 15 were rose from first week September to end of September and during this period chickpea is the dominant crop left in the field based on the local practice in the study area. The probability of 5 and 7 days dry spells were greater than 50% starting from mid August to the begging of September, which is a time that most people in the study area usually sow chickpea. Similarly, the probability of 10 and 15 days dry spells were greater than 50% starting from the first week of September as shown in Figure 7. The occurrences of dry spell length and its consequence increase in evapotranspiration as we ll as loss of soil moisture. As a result the chickpea crop water requirement increased and supplementary irrigation will require. Moreover, starting from September 29 the probability of longer dry spells increased rapidly, which indicates the seriousness o f drought immediately after the cessation of rainfall at Ada’aa District.

Therefore, farmers who have access to supplementary irrigation could cope up with risks of longer dry spells (Girma Mamo, 2005). If a farmer cannot cope up with risks of 10 to 15 longer dry spells after a potential planting date, he/she has to wait until all dry spells probabilities attains minimum values. There is also the probability of evapotranspiration

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 65 which become increasing and the probability of moisture stress to crop could be very high. As indicated by, dry spell analyses are important for farm level agricultural decisions like choice of crop or variety and crop management practices. Hence, it is a key indicator for choosing adaptation option depending on the length of growing period and probability of dry spell length. It is important for chickpea cultivator farmers to know the dry spell length from start of the season to end of the season to decide an appropriate cultivar and planting date. During chickpea flowering and pod setting usually chickpea growers face shortage of moisture in the study area. So getting advisory services on dry spell length and end of the rain season is very crucial, especially for the farmers, who have no access to supplementary irrigation. Deep black soils could support a crop through longer dry spells of 15 and 20 days, whereas sand soils could support only through breaks of 7 to 10 days (Feyera Merga, 2013). These demand farmers and/or planners at Ada’aa District to design water conservation practices and/or adoption of early maturing or drought tolerant crops/varieties.

Rainfall, Evapotranspiration and Effective Rainfall of Chickpea Mean monthly evapotranspiration rate of Ada’aa woreda ranges between 116.4 to 154.2mm/month. The lower monthly evapotranspiration was occurred in the months of June (122.1mm), July (116.4mm) and August (127.5mm). During this time, the annual mean monthly rainfall varies between 95mm to 206.3mm, whereas during lower evapotranspiration the total rainfall of (JJA) was 504.2mm for the reason that ETO was very low in Ada’aa woreda. The monthly evapotranspiration of September, October and January was similar. On the other hand, the reference evapotranspiration was higher in April (154.2mm) than the rest month of the year (Figure 8).The assessment shows that evapotranspiration is higher in the dry months, indicating that, the high temperature in these months. Even though there is high moisture in the wet months, the evapotranspiration was very low due to the effect of cloud on the incoming solar radiation. Chickpea is commonly sown at the end of growing season of many crops and hence, this makes chickpea vulnerable to drought stress.

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Figure 8: Comparison between monthly total rainfall, evapotranspiration and eff. rainfall

Crop Water Requirement, Effective Rainfall and Irrigation Requirement The comparison of crop water requirement, effective rainfall and Irrigation requirement of chickpea are presented in (Figure 9).

Table 4: Growing period chickpea crop water requirement (ETc), effective rainfall (Eff. Rain) of the season and supplemented irrigation requirement (Irr.Req.) Planting date Depth (mm) Late planting Early planting (20-Jul) Normal Planting (20-Aug) (10-Sep) Etc 340.6 346.4 343.8 Eff.Rain 257.5 108.2 38 Gross Irr.Req. 158.4 258.9 292.7

The crop water requirement of chickpea doesn’t vary by plantation date (almost the same). In the study area, the total water requirement provided in Table 4 ranges between 340.6mm and 346.7mm during the growing season. Effective rain, which is the most det erminant factor for yield was very variable by planting dates. Considering July planting date, the effective rainfall was 257.5 mm; however, if the planting date is shifted to August, the effective rainfall was decreased by 42% compared to July planting. T he effective rain was very low (38 mm) in September planting date which even hinders the growth of chickpea in the area, unless supported by irrigation. The difference between the crop water requirement and effective rain demonstrates that chickpea needs supplementary irrigation with existing cultural practices. However, the amount of irrigation that needs to be supplemented depends on the planting dates. Planting in September, July and August needs about 292.7mm, 258.9mm and 158.4mm supplementary irrigatio n respectively (Table 4). The water requirement of crops varies by their growth stages. Hence, what matters for yield may not be the total amount of rainfall in the growing period

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 67 but the distribution of the rainfall throughout the critical growth stages of chickpea production of the study area.

Early planting (July-20) 150 (a)

100

50 Depth (mm) Depth

0 Initial Phase Development phase Flowering Phase Maturity Phase ETc (mm/decade) Eff.rainfall (mm/decade) Irr.req (mm/decade)

Normal plant (August 20) (b) 150

100

50 Depth (mm) Depth

0 Initial Phase Development Phase Flowering Phase Maturity Phase ETc (mm/decade) Eff.rainfall (mm/decade) Irr.req (mm/decade)

Late planting (September 10) 150 (c)

100

50 Depth (mm) Depth

0 Initial Phase Development Phase Flowering Phase Maturity phase ETc (mm/decade) Eff.rainfall (mm/decade) Irr.req (mm/decade)

Figure9a-c: Crop water requirement, effective rainfall and irrigation requirement of each chickpea growth stages

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The most critical growth stages of most crops including chickpea are the development and mid growth stages (flowering and filling seeds stages) (Devasirvatham, 2012). About 40% of the total crop water requirement was used in the mid growth stage which reveals sensitivity of the crop to water stress during this phase. Therefore, if the crop water requirement is not fulfilled in the mid growth stage there will be more likely to decrease yield. The development stage holds about 22.5% of the water required during the growing period of chickpea and hence, it is the second water stress sensitive growth stage of the crop. The remaining initial and late growth stages are less sensitive to moisture stress. In August and September planting dates, the effective rain was very small (almost none) in the mid growth stage (Figure 9ac). However, in the development stage the effective rain of August planting (57.5 mm) was higher than September planting (17.3 mm) and therefore, this could be the reason why planting in August gives better yield than planting on September. To the contrary, the effective rain was better in all growth stages of the crop in the early planting (July20) and hence, provides better yield with less supplementary irrigation ((Figure 9ac). In all planting date development followed by flowering (mid) growth stage is sensitive to water stress. Therefore, Water harvesting (in situ and exsitu) could have very useful for reducing yield gaps under water deficit climate.

Generally, this analysis indicates that planting date was very important in fulfillment of the crop water requirements of the critical crop growth stages. As both the normal and late planting dates extend the length of growing period (particularly the mid (flowering and filling seeds) and development stages to more dry periods, early planting was found preferable in providing a reasonable yield of chickpeas. However, as chickpea is sensitive to water logging (depends on soil type), increasing the soil water percolation capacity, practicing proper drainage (like raised bed) could reduce the negative impact. Therefore, released water depending on the slop of the land through drainage can be collected in a pond so that it will be used later in the moisture stressed growth stages of chickpea.

CONCLUSIONS As a final point, the historical long term rainfall data analyzed from 1980 to 2010 indicates that there was variability in rainfall features like start of season (SOS), end of season (EOS) and Length of growing period (LGP) for the study area. The average growing length of the study area is 154 days of year. There is a strong relationship between length of the growing period and start of the rain season. The 5, 7, 10 and 15 days dry spell probability occurrence rise from midAugust to end of September when chickpea is dominantly cover the field based on the local practice in the study area. The mean annual rainfall varied

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 69 between 587.2 to 1122.7 mm but the rainfall trend was not significant in all months of the growing season (JJAS) except in June. Even if the water requirement of crops varied by the growth stages. The most critical growth stages of chickpea are the mid and development growth stage, which 62.5% of the total crop water requirement was used in the mid growth stage, while the remaining initial and late growth stages are less sensitive to moisture stress. Moreover, this analysis indicated that selecting planting date was very vital in fulfillment of the chickpea crop water requirements during its critical crop growth stages. The concluding point, risk taker farmers should sow their crops considering the prevailing variability of SOS and EOS to adapt the rainfall features impact on chickpea production. In addition, the available management practice like early planting, moisture conservation during less availability of water and drainage during water logging conditions should be improved.

RECOMMENDATIONS Risk taker farmers should sow their crops considering the prevailing variability of SOS and EOS to adapt the impacts of climate risk and to reduce the impacts of early cessation of rainfall/variability, early planting is one of the adaptation options to consider for successful chickpea production. Besides, appropriate adaptation options like as plant population, planting time, Mulching/ farm land soil and water conservation structures, fertilizer application with rate/amount and time of application need to be set in focus and other management practice such as plant population, planting time, Mulching and moisture conservation during less availability of water and drainage during water logging conditions need to be improved.

More research should be done taking other production limiting factors, such as disease and pest incidence as of climate variability and drought/water logging. Final, it is learned that soil water balances analysis in the phase of reducing the un productive water losses such as through ran off, Evaporation, and deep percolation research should receives greater attention then depending on rainfall information alone and Full flagged irrigation water harvesting both insitu and exsitu need to be adopted

Acknowledgements I am grateful to Dr. Araya Alemie, for his professional support starting from the very beginning and to the final stage of this paper with devotion of his full time and for his unlimited support. I would like to appreciate Dr. Kiros Meles for connecting me with Mekelle University, my genuine gratitude will also goes to Drs. Atkilt Girma, and Dr.

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Solomon Habtu for their helpful technical and criticism provision for the accomplishment of my paper work. My heart full thanks, enthusiasms to Rockefeller foundation project of Mekelle University, for my success full paper work and other expenses was financially supported. I would like to thank also, Dr. Girma Mamo who supported me from the very beginning of my selecting as candidate for this education chance and starting of my class up to end of my paper work for his consistent encouragement and for his the entire support without any preciseness. I would like to extend my thanks to staff of National Meteorological Agency, Debrezeit Agricultural Research and Ada’aa Agricultural office that helped me to obtain the necessary data and information to complete the work. I would like to extend my special appreciation to Melkassa Agricultural Research Center and Adama Agricultural Office for their genuine support to learn my MSc degree in Mekelle University.

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Girma Mamo., Fikadu Getachew and Gizachew Legesse. (2011). The Potential Impacts of Climate Change Maize Farming System Complex in Ethiopia:Towards Retrofitting Adaptation and Mitigation options. Proceedings of the 3 rd national maize workshop of Ethiopia, April 1820, 2011, Addiss Ababa, Ethiopia. Kassam A.H., Kowal J.M. and Sarrof, S. (1978). Report on the agro ecology Zones project methodology and Results for Afrma, world soll Resources report 40 Food and Agricultural organzation of the Umted natlons . Rome, Italy Vol 1. Kidane Giorgis., Abebe Tadege and Degefie Tibebe. (2011). Estimating crop water use and simulating yield reduction for maize and sorghum in Adama and Misesso districts using the cropwat model. Respectively , Ethiopian Agricultural Research Institute National Meteorological Agency (NMA), Ethiopian Agricultural research Institute, P 114. Tesfaye K. and Walker S. (2004). Matching of crop and Environment for optimal water use : The case of Ethiopia. Alemaya, Alemaya University, Dire Dawa, Ethiopia. Meinke H. and Stone R.C. (2005). Seasonal and InterAnnual Climate Forecasting: The New Tool for Increasing Preparedness to Climate Variability and Change in Agricultural Planning and Operations. In: Salinger J., Sivakumar M., Motha R.P. (eds) Increasing Climate Variability and Change. Springer, Dordrecht. Springer, Dordrecht. ISBN: 9781402033544. Marius, K. (2009). Climate risks and development projects assessment report for a community level project in Guduru, Oromia Ethiopia. Climate Risks and Development Projects. https://www.iisd.org/cristaltool/documents/BFAEthiopiaAssessmentReportEng.pdf Mzezewa J. and Gwata E.T. (2012). The natural of rainfall at a typical semiarid tropical ecotope in southern Africa and options for sustainable crop production technologies . In"The nature of rainfall at a typical semiarid tropical ecotope in southern africa and option crop production technologies" Southern Africa, pp 307787. Nahu Senaye Araya. (2011). Weather Insurance for farmers experience from Ethiopia . Conference on New Directions for Smallholder Agriculture 2425 January (pp. Pp14). Rome, IFAD HQ: IFAD enabling poor rural people to overcome poverty. NAP. (2007). Climate change National adaptation programme of action of Ethiopia. Adis Ababa: The Federal Democratic Republic of Ethiopia ministry of water resources' national Meteorological Agency. Roger Stern, Derk Rijks,Lan Dale and Joan knock. (2006, January 03). Instat Climatic Guide. statistica service center .University of reading, UK. Salvatore DI Falco., Mahmud Yesuf., Gunnar Kohlin and Claudia Ringler. (2011). Estimating the impact of climate change on Agriculture in Low Income Countries: Household Level Evidence from the Nile Basin, Ethiopia. Springer Science +Business Media B.V Environ Resource Econ DOI 10.1007/s106400119338y, PP122. Summerfield and ER, E.R. (1990). Adaption of chickpea to agroclimatic constraints. In: proceeding of the second International Workshop on chickpea improvement, 48 december 1989 (pp. PP 5061). Hyderbada, India: ICRISAT Publishing. Timo salmi., Anu maatt., Pia Anttila.,Tuijia RuohoAirola and Toni Amnell. (2002). Detecting trends of annual values of atmospheric pollutants by the MannKendall test and Sen's slope estimates the excel template application" MAKESENS+''. Helsiniki,Finland: Finnish Meteorological Institute. Viola Devasirvatham. (2012). The basis of chickpea heat tolerance under Semi Arid environments. A thesis submitted for the degree of Doctor of Philosophy Faculty of Agriculture and Environment the university of Sydney. Sydney, Australia.

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Screening of Bread Wheat ( Triticum aestivum L.) Genotypes for Resistance Against Stem Rust ( Black Rust ) Diseases

Desalegn Negasa Soresa* and Tola Abdisa

Department of Plant sciences, Wollega University, Shambu Campus, P.O. Box: 38 Shambu, Ethiopia

Email: [email protected]

Abstract Thirty six advanced bread wheat genotypes were grown at Kulumsa Agricultural Research Debrezeyit sub-center for testing against Stem Rust on open field at adult stage and Ambo Agricultural Research Center, for the same disease detection under controlled environment at seedling stage. At Debrezeyit, treatments were arranged in randomized complete block design with three replication on plot size of 5 rows x 1.2meter length x 20 cm between row spacing = 1 m 2 or on a 1.2x0.8m area of land. At least six seedlings of each genotypes were grown in 10 by 10 cm square pots in Metro-Mix 200 vermiculite peat-perlite medium in a greenhouse with supplementary lighting to provide a 16 h photoperiod under controlled environment ( green house) at Ambo Agricultural Research Center for seedling test against the reaction of the inoculated stem rust race. Stem rust evaluations for Pgt races TTKSK, TKTTF, TRTTF and JRCQC were replicated so that a total of at least 20 seedlings from each cultivar were evaluated. At seedling stage, most of the genotypes show low IT < 2 on four of stem rust races indicating that are resistance to the four stem rust races used. Out of these, nine of the genotypes namely genotype ETBW7178, ETBW7198, ETBW7236, ETBW7220, ETBW7161, ETBW7191 and one standard chick Dand’a has potential (IT < 1) to overcome stem rust races at seedling stage. On the experiment for adult stage, the only genotype showing strong resistance was genotype ETBW7178 (5R). The rest genotypes show moderately resistance, moderately susceptible and totally susceptible to stem rust disease

Keywords : Stem Rust; Genotypes; Resistance; Susceptible

INTRODUCTION Ethiopia, with its range of altitudes, soils and climatic conditions provide ecological settings suitable for the cultivation of diverse species of wheat (Harlan, 1971). Durum wheat (Triticum turgidum Desf.) and bread wheat ( Triticum aestivum L.) are, however, the two most important wheat species grown in the country although other species are also cultivated to a lesser extent (Amsal, 2001). Though bread wheat is believed to be a

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 73 relatively recent introduction to Ethiopia (Hailu, 1991); it exhibits wider adaptation and higher yield potential than durum wheat (Amsal, 2001).

Wheat is special in several ways. Wheat is grown on more than 240 million ha, larger than for any other crop, and world trade is greater than for all other crops combined. The raised bread loaf is possible because the wheat kernel contains gluten, an elastic form of protein that traps minute bubbles of carbon dioxide when fermentation occurs in leavened dough, causing the dough to rise (Hanson et al ., 1982). It is the best of the cereal foods and provides more nourishment for humans than any other food source. Wheat is a major diet component because of the wheat plant’s agronomic adaptability, ease of grain storage and ease of converting grain into flour for making edible, palatable, interesting and satisfying foods. Dough’s produced from bread wheat flour differ from those made from other cereals in their unique viscoelastic properties (Orth and Shellenberger, 1988). Wheat is the most important source of carbohydrate in a majority of countries. Wheat starch is easily digested, as is most wheat protein. Wheat contains minerals, vitamins and fats (lipids), and with a small amount of animal or legume, protein added is highly nutritious. A predominately wheatbased diet is higher in fiber than a meatbased diet (Johnson et al ., 1978).

The major diseases in the highlands are stripe rust and Septoria blotches, particularly Septoria tritici blotch. Stem rust can be very damaging to common wheat in Kenya and durum wheat in Ethiopia. Other diseases important in some years are common bunt, loose smut, BYDV and bacterial. When stripe rust disease strikes a susceptible wheat crop, the results are usually devastating leaf streak. The fungus can spread like wildfire, quickly transforming fields of healthy wheat into yellow swathes of stunted grain. The disease results in fewer spikes, fewer grains per spike, and shriveled grains with reduced weight.

Ethiopia’s wheat crops became one of the casualties in the race against the disease in 2010, when a severe stripe rust epidemic struck the country, hitting many dominant wheat varieties. This threat was further compounded by climate change, with persistent gentle rains throughout the year, and prolonged dews and cool temperatures – perfect weather for stripe rust. There was little Ethiopia could do to prevent the epidemic. Imported fungicides controlled the disease when they were applied on time, but supplies were limited and expensive. But Ethiopia was not alone. Many countries in Africa, the Middle East, and Asia, struggled to control the epidemic in 2009 and 2010. But even more alarming was the evolution of new races of stripe rust that are able to overcome a major

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 74 wheat gene (Yr27) that was previously resistant to the disease (Winning the Battle Against Deadly Wheat Fungus: http://www.cgiar.org/consortiumnews/winningthebattleagainst deadlywheatfungus/ : Accessed date December 2012).

Stem rust (also called black rust), is caused by Puccinia graminis . It is also referred to as summer rust due to the abundant production of shiny black spores, which form at the end of the crop growing season. Stem rust is favored by humid conditions and warm temperatures of 15°C to 35°C. The fear of black rust through history – and today – is understandable. Apparently, healthy crop three or four weeks before harvest can be reduced to a black tangle of broken stems and shriveled grain. Harvest losses of 100 percent can occur in susceptible crop varieties.

In Ethiopian highlands, bread wheat has been produced by small scale farmers since the introduction of the crop approximately about 5000 years ago but in recent years because of the emerging new races of stem rust and yellow rust, the production and productivity is highly reduced and in some case there is 100 percent yield losses. The highlands of western Ethiopia suitable for wheat production are in great problems due to lack of resistant varieties with good yield and quality, since most of the adapted varieties became susceptible to the new emerging races and reduced in productivity. Hence, there is a need for screening of genotypes against major disease and yield performance in order to come up with promising varieties which could resist/tolerate the new races of stem rust pathogens with high grain yield. Therefore, the objective of the project was to screen bread wheat genotypes for resistance/tolerance to wheat stem rust diseases.

MATERIALS AND METHODS Thirty six advanced bread wheat genotypes were grown at Kulumsa Agricultural Research Debrezeyit subcenter for testing against stem rust on open field at adult stage and Ambo Agricultural Research Center, for the same disease detection under controlled environment at seedling stage. The sites ranged from mid to high altitude areas which favor the opportunity for different pests and diseases to occur and interact with genotypes. The annual rain fall distribution is 18002000mm and the annual minimum and maximum temperature is 1721 0C. And have clay loam to loam soil types. The population of the area is engaged with mixed farming.

Experimental Materials Thirty six bread wheat genotypes including one standard checks selected from 121 first trial, preliminary yield trials at Shambu during the 2012, Gitilo and Guduru 2013 second

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 75 trial materials grown and Gitilo, Diga, Amuru and Haro Aga in 2014 cropping season respectively. The first 36 materials were originally obtained from Kulumsa Agricultural Research Centre National wheat Research Coordination Centre. The 36 bread wheat genotypes were promoted based on the yield and other agronomic performances in the season.

Table 2: List of bread wheat genotypes used in the study, and their pedigree and origion.

05/06Y /2 nd Genotype Pedigree Seed Source Entry 1 ETBW 7178 DVERD2/AE.SQUARROSA(214)//2*ESDA/ IESRRL# 53 2 ETBW 7252 SAMAR8/KAUZ’S’//CHAM4/SHUHA’S’ IESRRL # 214 3 ETBW 7238 CROW ‘S’/BOW’S’ 31994/95//TEVEE’S’/T IESRRL # 177 4 ETBW 7198 VAN'S/3/CNDR'S'/ANA//CNDR'S'/MUS'S'/ IESRRL# 84 5 Kubsa Check Breeder seed,2011 6 ETBW 7237 CROW ‘S’/BOW’S’ 31994/95//TEVEE’S’/T IESRRL # 176 7 ETBW 7171 FOW'S'//NS732/HER/3/CHAM6//GHURA IESRRL# 43 8 ETBW 7208 CHAM4/SHUHA'S'/6/2*SAKER/5/RBS/AN IESRRL# 110 9 ETBW 7236 CROW ‘S’/BOW’S’ 31994/95//KATILA11 IESRRL # 174 10 ETBW 7248 SAKER/5/RBS/ANZA/3/KVZ/HYS//YMH/TUL/ IESRRL # 209 11 ETBW 7173 FOW'S'//NS732/HER/3/CHAM6//GHURA IESRRL# 45 12 ETBW 7235 CROW ‘S’/BOW’S’1994/95//ASFOOR5 IESRRL # 173 13 ETBW 7268 SOMAMA9//SERI 82/SHUHA’S’ IESRRL # 272 14 ETBW 7174 CHAM6/GHURAB'S'//JADIDA2 IESRRL# 46 15 ETBW 7220 CHAM4/SHUHA'S'/6/2*SAKER/5/RBS/AN IESRRL# 135 16 ETBW 7221 DUCULA/KAUZ/3/KAUZ'S'//GLEN/PRL'S'/4 IESRRL# 142 17 ETBW 7227 IZAZ2//TEVEE'S'/SHUHA'S' IESRRL# 164 18 ETBW 7239 WEEBILL – 1/BOCRO3 IESRRL # 178 19 ETBW 7160 CHAM6/WW 1402 IESRRL# 29 20 ETBW 7161 CHAM6/WW 1403 IESRRL# 30 21 ETBW 7191 BOCRO4/3/MAYO'S'//CROW'S'/VEE'S' IESRRL# 72 22 ETBW 7199 VAN'S/3/CNDR'S'/ANA//CNDR'S'/MUS'S'/ IESRRL# 85 23 ETBW 7182 CHIL1//VEE'S'/SAKER'S' IESRRL# 58 24 ETBW 7194 VAN'S/3/CNDR'S'/ANA//CNDR'S'/MUS'S'/ IESRRL# 76 25 ETBW 7204 SHA3/SERI//YANG87142/3/2*TOWPE IESRRL# 103 26 ETBW 7234 IRQIPAW 35 S5B98/ABUZIG4 IESRRL# 172 27 ETBW 7164 SHUHA4//NS732/HER IESRRL# 33 28 ETBW 7195 VAN'S/3/CNDR'S'/ANA//CNDR'S'/MUS'S'/ IESRRL# 78 29 ETBW 7244 ANDALIEB5// TEVEE1/SHUHA6 IESRRL # 198 30 ETBW 7258 SABA/FLAG1 IESRRL # 234 31 ETBW 7264 SERI 82/SHUHA’S’// SOMAMA9 IESRRL # 268 32 ETBW 7215 CHAM4/SHUHA'S'/6/2*SAKER/5/RBS/AN IESRRL# 117 33 ETBW 7156 TAM200/TUI//MILAN/KAUZ/3/CROCAB IESRRL# 17 34 ETBW 7247 HD2206/HORK’S’/3/2*NS732/HER//KAUZ IESRRL # 208 35 Danda'a Check Breeder seed,2011 36 ETBW 7175 CBME4SA#4/FOW2 IESRRL# 47

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 76

Design and Data Management At DebreZeyit, treatments were arranged in randomized complete block design with three replication on plot size of 5 rows x 1.2meter length x 20 cm between row spacing = 1 m 2 or on a 1.2x0.8m area of land. The seed rate was 150 kg/ha. Treatments were subjected to grow on open field as the environment and the time of sowing used favors the infestation of stem rust in the area. At least six seedlings of each genotype were grown in 10 by 10 cm square pots in MetroMix 200 vermiculite peatperlite medium in a greenhouse with supplementary lighting to provide a 16 h photoperiod under controlled environment at Ambo Agricultural Research Center for seedling test against the reaction of the inoculated stem rust race.

Inoculums and Inoculation All isolates were derived from single pustule, increased in isolation, and stored at 80 C. Inoculation of P. graminis isolates was performed in an inoculation booth at Ambo Agricultural Research Center. Inoculum of four different races was used for stem rust inoculation. Isolates of Pgt races are described in Rouse et al . (2011). In addition, isolate 06YEM341 was used for race TRTTF. Inoculation and incubation were performed as described previously (Jin et al . 2007). P. graminis and P. triticina urediniospores were retrieved from storage at 80 C and heat shocked at 45 C for 15 min. Spores were rehydrated by placing the capsules in an airtight container at 80 % humidity maintained by a KOH solution for 2–4 h. Urediniospores were then suspended in a lightweight mineral oil (Soltrol 70) and sprayed onto seedlings. Seedlings were inoculated when the ﬁrst leaf was fully expanded with a suspension of urediniospores of single P. triticina and P. graminis races. The inoculation booth was washed with water between inoculations of plants with different P. graminis and P. triticina isolates in order to prevent contamination. For approximately 30 min plants were under a fume hood for oil evaporating. Plants were kept in a 100 % humidity chamber overnight and maintained in the greenhouse at 15–25 C with supplemental lighting after inoculation.

Disease Assessment and Data Analysis After dew chamber incubation, plants were kept in a greenhouse at the Ambo Agricultural Research Center, Cereal Disease Laboratory maintained at 18±2 0 C for 14 days. Infection types (ITs) were classified on a 0–4 scale 12–14 days after inoculation on seedlings as described by Stakman et al . (1962): IT 0 = immune response, with no uredinia or necrosis; IT fleck (;) =necrotic flecks; IT1 =small uredinia surrounded by necrosis; IT2 =small uredinia surrounded by chlorosis; IT3 =moderate uredinia; IT 4 =large uredinia.

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 77

Designations of + and were added to indicate larger and smaller size of uredinia; X = a mesothetic response of ﬂecks, small and large uredinia. Stem rust evaluations for Pgt races TTKSK, TKTTF, TRTTF and JRCQC were replicated so that a total of at least 20 seedlings from each cultivar were evaluated.

Treatments use and Experimental Design for Adult Plant Test The experiment was arranged in RCBD with three replications. Plots having the size of 2 X 1 m was prepared. There are 10 rows per plot and the space between rows, plots and replications was 0.2, 0.5 and 1m respectively. To initiate sufficient disease development, known very susceptible bread wheat varieties (604) to rust was sown on the bordered of all plots. Seed of each variety was planted in each plot by hand drilling at the rate 150 kg/ha, which was recommended for the area was used. Fertilizers at a rate of 46 kg/ha N and 46 kg/ha P2O5 was applied during planting. Weeds were controlled by hand weeding was carried out according to the farmers’ practices of the areas. Natural infection was used to initiate the epidemics of the disease.

Data Collection Diseases data Disease incidence : Rust incidence was recorded on each experimental plot by counting number of diseased plants from 16 randomly taken and tagged plant/plot from eight central rows and calculated as the proportion of the diseased plants over the total stand count (16 plants) at 10days interval.

Disease severity : Proportion of the stem and leaf of the plant affected by the disease, recorded using the modified Cobb’s scale (Peterson et al ., 1948). Starting from the appearance of the sign or symptoms, each plant with in each plot was visually evaluated for percent foliar infection (severity) at 10 days interval.

RESULT AND DISCUSSION The result of experimental analysis for seedling stage and adult stage was conducted separately. Following emergence of Ug99, the new virulent race of Puccinia graminisf . sp. triticiin Africa, a global effort for identification and utilization of new sources of Ug99 resistant germplasm has been undertaken.

To combat the threat posed by Ug99, breeders require knowledge about existing sources of resistance to this race. Such information would enable wheat breeders to carefully design crosses to combine individual resistance sources into one breeding line and

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 78 enhance germplasm for Ug99 resistance. Yu et al . (2010) characterized resistance genotypes of a diverse and widely distributed collection of germplasm originating from the International Maize and Wheat Improvement Center (CIMMYT).

Table 2: Wheat germplasm screened against four major stem rust races during seedling stage

TTKSK TKTTF TRTTF JRCQC No Code 1ST 5sc 2nd 3rd 1st 2nd 3rd 1st 2nd 3rd 1st 2nd 3rd 1 G1 2 0 0 2 0 ; 0 0 2 G2 2 2+ ; 0 ; ; ; 0 3 G3 3 3 2+ 3 2 ;2 ;1 2+ 4 G4 ;1 1 ;1(c) ;1 ; ; ; ;1 5 G5 3 3 3 2+,3 ;2 ;2 0 3 6 G6(1) 2+ 3 2+ 0 2 ;1 ;1 ;1 7 G6(2) 2+ 2+,3 2 3 ;2 ;2 0,2 2+ 8 G8 3 3 2,2+ 3 2+ ;2 ;1 3 9 G9 ;1 ;1 ;1(c) ;1 2 ;1+ ; ; 10 G10 2 1 ;1 ;1 2 ;1 ;1 1+ 11 G11 2+ ;1 ;1 3 ;1+ 3 ;1 ;1 12 G12 3 3 2 3 2 ;1 ; 3 13 G13 ;1+ 3 ;2+ ;1 ;1+ ;2 ;1 ;1 14 G14 2+,3 3 ;1 ;1 ;1 ;1 ;1 ;1 15 G15 ;1 ;1 ;1 0 ;1 ; ;1 1 16 G16 2+,3 2+ ;2 2 2 3 2 2

17 G17 ;1 2+ ; ;1 ; ;1+ ; ;1 18 G18 ; 2 ; ;1 ; ;1+ ;1 ;1+ 19 G19 2 2+ ;1 ;1 ; 2 ; ;1+ 20 G20 ;1 ;1 ;1 ;1 ; ;1+ ; ;1 21 G21 ;1 ; ;1 ;1 ; ;1 0 ; 22 G22 ;1+ 2 ;1 2 ;1 ;1 ;1 ;1 23 G23 ;1,2+ 3 ;1 1+ ;1 ;1+ ;1 2 24 G24 2(c) 3 ;1 1+ ;1 ;1+ ; 2 25 G25 ;1+ 2 0 1 ;1 ;1+ ;1 ;1

26 G26 3 3 ;2 2 3 3 ; 3 27 G27 2+ 2+,3 ;1 ;1 ;1 ;1+ ; ;1 28 G28 3 3 ;2 3 2 3 ;1 2+ 29 G29 2+ 3 ;1 1+ ;1 ;2 ;1 ;1 30 G30 2+(c) 1 ;1 1+ ;1+ 3 0,1 0 31 G31 ;1+ ;1 ;1 ;1 ;1 ;1 ;1 ;1 32 G32 2 2 ;1+ 2 ;1 ;1 ;1 ;1 33 G33 2 2 ;1+ 2+ ;1+ ;1 ;1 ;1+ 34 G34 2,2+ 3 ;1+ 2 ;1 2,3 ; ;1+ 35 G35 ;1 ;1 0 0 0 0 0 ; 36 G36 ;1 ;1 ;1 ;1 ; 0 0 ; aInfection types according to a 0 to 4 scale. Within line variation is indicated by ‘/’

b Races were represented by the following isolates: TTTTF 01MN84A12, TTKSK 04KEN156/04, TTKST 06KEN19V3, TTKSF UVPgt55, TTKSP UVPgt59, PTKST UVPgt60

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 79

Infection types (ITs), described by Stakman et al . (1962), were assessed 14 days post inoculation. From a practical point of view, seedling resistance genes can be useful in future selection processes. The information presented can be useful for wheat breeders contributing to a more efficient exchange of information and use of germplasm, but this research needs to be complemented with additional studies on adult plant resistance because some leaf rust resistance genes express resistance optimally in adult plants.

Table 3: Severity of the tested wheat genotypes against stem rust at DebreZeit at adult stage

Cultivar/ Terminal No. Accession Number Severity 1 ETBW 7178 5R 2 ETBW 7252 30MSMR 3 ETBW 7238 40MSS 4 ETBW 7198 30MRMS 5 Kubsa 40MRMS 6 ETBW 7237 40MSS 7 ETBW 7171 30MRMS 8 ETBW 7208 40MS 9 ETBW 7236 40MS 10 ETBW 7248 40SMS 11 ETBW 7173 40MRMS 12 ETBW 7235 50MSS 13 ETBW 7268 40MSS 14 ETBW 7174 30MRMS 15 ETBW 7220 30MS 16 ETBW 7221 30MRMS 17 ETBW 7227 30MRMS 18 ETBW 7239 40MSS 19 ETBW 7160 40MS 20 ETBW 7161 30MRMS 21 ETBW 7191 40MRMS 22 ETBW 7199 40MSS 23 ETBW 7182 50SMS 24 ETBW 7194 40MSS 25 ETBW 7204 50MSS 26 ETBW 7234 50MSS 27 ETBW 7164 30MRMS 28 ETBW 7195 40MSS 29 ETBW 7244 30MSMR 30 ETBW 7258 50MSS 31 ETBW 7264 30MSMR 32 ETBW 7215 40MSS 33 ETBW 7156 30MRMS 34 ETBW 7247 50MSS 35 Danda’a 40MSS 36 ETBW 7175 30MSS IRs at the adult plant stage following the descriptions of Roelfs et al . (1992), where R = resistant, MR = moderately resistant, MS = moderately susceptible, and S = susceptible.

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 80

For seedling stage and, most of the genotypes show low IT < 2 on four of stem rust races indicating that are resistance to the four stem rust races used. Out of these, nine of the genotypes namely genotype ETBW7178, ETBW7198, ETBW7236, ETBW7220, ETBW7161, ETBW7191 and one standard chick Dand’a has potential (IT<1) to overcome stem rust races at seedling stage. Contrarily, half of the materials used as ETBW7238, kubsa, ETBW7237, ETBW7171, ETBW7208, ETBW7182 and ETBW7804 show high infection type (IT) or are susceptibility to stem rust races at seedling stage (table 3).

On the experiment for adult stage, the only genotype showing strong resistance was genotype ETBW7178 (5R). The rest genotypes show moderately resistance, moderately susceptible and totally susceptible to stem rust disease (table 4). Genotype ETBW7161, ETBW7227, ETBW7221, ETBW7174, ETBW7171, ETBW7198, ETBW7164 and ETBW7156 show MRMS. In contrast, genotype ETBW7235, ETBW7204, 7234, ETBW7256 and ETBW7247 showed MSS and ETBW7182 was the one only showed SMS indicating highly susceptible to stem rust at adult stage, which can be used as border variety for infesting stem rust at field condition.

This will require extensive crossing of adapted germplasm with international cultivars and breeding materials that possess the effective resistance genes. Once crossed, procedures such as markerassisted selection or markerassisted backcross selection would be the methods of choice.

CONCLUSIONS Stem rust (also called black rust), is caused by Puccinia graminis . It is also referred to as summer rust due to the abundant production of shiny black spores, which form at the end of the crop growing season. Stem rust is favored by humid conditions and warm temperatures of 15°C to 35°C. The fear of black rust through history – and today – is understandable. Apparently, healthy crop three or four weeks before harvest can be reduced to a black tangle of broken stems and shriveled grain. Harvest losses of 100 percent can occur in susceptible crop varieties.

At seedling stage, most of the genotypes show low IT<2 on four of stem rust races indicating that are resistance to the four stem rust races used. Out of these, nine of the genotypes namely genotype ETBW7178, ETBW7198, ETBW7236, ETBW7220, ETBW7161, ETBW7191 and one standard chick Dand’aa has potential (IT<1) to overcome stem rust races at seedling stage. On the experiment for addult stage, the only genotype showing strong resistance was genotype ETBW7178 (5R). The rest genotypes show

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 81 moderately resistance, moderately susceptible and totally susceptible to stem rust disease. Genotype ETBW7161, ETBW7227, ETBW7221, ETBW7174, ETBW7171, ETBW7198, ETBW7164 and ETBW7156 show MRMS. In countrast, genotype ETBW7235, ETBW7204, 7234, ETBW7256 and ETBW7247 showed MSS and ETBW7182 was the one only showed SMS indicating highly susceptable to stem rust at adult stage which can be used as border variety for infesting stem rust at field condition. These results can assist wheat breeders in Ethiopia for choosing parents for crossing in programs aimed at developing cultivars with desirable levels of stem rust resistance in Croatia and will also facilitate stacking of resistance genes into advanced breeding lines.

REFERENCES Rouse M.N., Wanyera R, Njau P., Jin Y. (2011). Sources of resistance to stem rust race Ug99 in spring wheat germplasm. Plant Diseases 95: 762766 Amsal T. (2001). Studies on Genotypic Variability and Inheritance of Waterlogging Tolerance in Wheat. Ph.D. Dissertation. University of the Free State, Bloemfontein, South Africa. Hailu Gebremariam (1991). Bread wheat breeding and genetics research in Ethiopia. In Hailu GebreMariam, D.G. Tanner and Mengistu Huluka (ed.) Wheat Research in Ethiopia: A Historical Perspective. IAR/CIMMYT. Addis Ababa. Hanson H., Borlaug N.E. and Anderson R.G. (1982). Wheat in the third world. Boulder, CO, USA, Westview Press. Harlan J.R. (1971). Agricultural origions: Centers and Noncenters. Science 174: 468473. Jin Y., Singh R.P., Ward R.W., Wanyera R., Kinyua M.G., Njau P., Fetch T. Jr, Pretorius Z.A., Yahyaoui A. (2007). Characterization of seedling infection types and adult plant infection responses of monogenic Sr gene lines to race TTKS of Puccinia graminis f. sp. tritici. Plant Disease 91:10961099. Jin Y. and Singh R. (2006). Resistance to recent eastern African stem rust isolates with virulence to Sr31 in U.S. Wheat U.S. 90: 476480. Johnson V.A., Briggle L.W., Axtel J.D., Bauman L.F., Leng E.R., Johnston T.H. (1978). Grain crops. In M. Milner, N.S. Scrimshaw & D.I.C. Wang, eds. Protein Resources and Technology , p. 239255. Westport, CT, USA, AVI Publishing. Orth R.A. and Shellenberger J.A. (1988). Origin, production, and utilization of wheat. In Y. Pomeranz, ed. Wheat chemistry and technology , vol. 3. St Paul, MN, USA, American Association of Cereal Chemists. Roelfs A.P., Singh R.P., Saari E.E. (1992). Rust diseases of wheat: concepts and methods of disease management (Translated molecular by G.P. Hettel). CIMMYT, Mexico, DF Stakman E.C., Stewart D.M., Loegering W.Q. (1962). Identiﬁcation of physiologic races of Puccinia graminis var. tritici. US Department of Agric., ARS E617, p 53 Yu L.X., Liu S., Anderson J.A., Singh R.P., Jin Y., Dubcovsky J., BrownGuidera G., Bhavani S., Morgounov A., He Z., HuertaEspino J., and Sorrells M.E. (2010). Haplotype diversity of stem rust resistance loci in uncharacterized wheat lines. Molecular Breeding 26: 667680.

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 82

Anthropological Inquiry in Retrospect of Forest Biodiversity, Forest Policy in Horro Guduru Wollega Zone of Oromia regional state, Ethiopia

V. Sree Krishna* and Belay Ejigu

Department of Animal Sciences, Shambu campus, Wollega univesity, P.O. Box: 38, Shambu, Ethiopia

Email: [email protected]

Abstract The present study was envisaged to examine the forest biodiversity in Horro Guduru. It deals with forest resources, their deforestation, and pertinent state and local peoples’ customary interactions with these resources. This work sets out from practical observations made across the cultural ecology of the Oromo of Horro Guduru, apart from employing series of interviews, case studies and archival investigations. The actions that people exert and the behavior they exhibit in their geographic environments, chiefly their interaction with the forest environments are largely influenced by their customary knowledge systems. This may be what the Ethiopian society in general and that of the Oromo nation in particular share in common with all other human communities on earth. The problems that this yields, however, appear multifaceted to the Ethiopians. In an attempt to identify the root cause of the interwoven environmental problems the country faces now days and to sort out possible solutions, attention has to be focused much on the prevailing socio economic activities of the people. Lack of momentous attention to local customs and the wider natural environment in Ethiopia is an old aged story. As such, local customs and associated natural forest environments had ever been encroached due to overlying of external forces during three distinct state administrative systems in the country. These entail the imperial state’s entwined politico-religious institutional set up (1880’s to 1974), socialist ideology of the military regime (1974 to 1991), and the current Federal and decentralized system of government (1991 to present). These studies demonstrate that forest resources are essential to underneath local lively hoods other than their ecological roles.

Keywords: Archival investigations; Biodiversity; Environments; Multifaceted problems

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 83

INTRODUCTION Today we are facing some of the greatest environmental challenges in global history. Understanding the damage being done and the varied efforts contributing to its repair is of vital importance (Kopnina and ShoremanOnimet, 2011).Urge to understand these issues have been leading anthropologists to fuel rigorous interest in environmental anthropology. Consequently, interest in environmental anthropology has grown steadily in recent years. The rising interest indeed has been reflecting national and international concerns about the environment and developing research priorities, which focus on the interrelationship among the society, culture, and, the environment. While the underlying ethos of environmental anthropology is anthropological, the approach is interdisciplinary (Ellen, 2011).

Dove and Carpenter (2008) also anthropology and anthropologists as essential requirements in environmental concerns. A nearly similar contention was further provided by Hoenu and Wilk (2006).

The present study was inspired by an interest to examine the realm of one entity of the environment in Horro Guduru. It deals with forest resources, their deforestation, and pertinent state and local peoples’ customary interactions with these resources. The research work sets out from practical observations made across the cultural ecology of the Oromo of Horro Guduru, apart from employing series of interviews, case studies, and archival investigations.

MATERIALS AND METHODS This study was conducted in Horro Guduru Wollega Zone. Three sample districts, namely Abee Dongoroo, Horro and Jaardagaa were selected for this study out of the total of nine districts of the site, on the basis of purposive and cluster sampling methods. Purposive sampling was found relevant because almost all the entire forest remains of Horro Guduru are found in these districts. The purposive sampling decision was made in line with the nature of the research, which is essentially qualitative. Qualitative or ethnographic research suggests purposeful decision for a specific case rather than random sampling (Rainbow, 1984; Flick, 2006 and Barbour, 2008). This is important for reliable understanding of specific case so that valid data would be procured.

Relevant Government officers and key informants as well as their net works were selected by snowball method. However, to generate data from extraordinarily scattered peasant

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 84 households, the three representative forest districts were divided into nine vicinities. Therefore, in this research we got three categories to determine the sample size through purposive sampling; the final sample sites or gandas (vicinities) inhabiting representative forest areas, relevant local experts and authorities, and key informants along with their networks. By means of this purposive sampling,77 informants ( local experts & authorities were selected from relevant local government institutions and 8 key informants were selected from Horro and Abee Dongoro districts. Besides nine representative gandas were selected from three districts purposively. Since each ganda has an average of 144 peasant households, we have used a strategy to select informants from a crude total of 1304 peasant households of the nine purposively sampled gandas.

RESULTS AND DISCUSSION The results of this study have been categorized into two parts .The first major part mainly deals with forests as resources in Horro Guduru Wollega Zone over years. The second major part concerns deforestation, its causes, processes and consequences.

Forest Resources This part of results explains the retrospective and perspective situations of forest resources emphasing the indigenous knowledge systems of Oromo. Significant evidences were drawn from the customary knowledge systems being experienced in the area.

On the basis of interviews, case studies and observations, it is confirmed that the Oromo of Horro Guduru Wollega Zone clearly differentiate the ecological worth of forest resources. They recognise this by comparing the prevalence of relatively stable ecology in caatoo sacred forest with the absence of stable ecological phenomenon in other deforested and degraded areas, the problem which in fact they have caused instead mainly because of agriculture. In caatoo sacred forest, relatively undisturbed ecological relationships are abounding between large and small wild animals and dense as well as diverse equatorial rain forest trees and other plant species along with fertile abiotic substances such as soils, which are formed from decomposed plant fossils. The local people have been practicing agroforestry largely because they clearly notice that most forests that have protected the soil have been cleared and large slopes, hills and mountains were cultivated. But the environment was not the same and the land responded differently, soil quickly eroded under seasonal summer rains.

Most of the time the ecological worth of forest resources comprises of complex web of interactions between biotic and abiotic systems. In this respect, ecologist and ecological

Proceedings of the National Conference on “ Agriculture, Climate Change & Environmental Safety: The Challenges on National Transformation in Ethiopia ” 85 anthropologists have contributed a great deal of scientific knowledge (Townsend, 2008; Dove and Carpenter, 2008; Haenn, 2006; Kala and Aruna, 2010). The ongoing global attention being given to forests also appear more off natural ecology oriented than other systems such as cultural ecological significance of forest resources.

Deforestation and Changes in Forest Landscape This major thing attempts to answer the research questions framed at the outset of this research and the once reformulated during the field work just to deal with situations of deforestation in Horro Guduru Wollega Zone. The research questions inquired about the sites, causes, processes, and consequences of deforestation on one hand and changes in forest landscape in the area on the other.

Close examination of the interactions between local people and forests, however, shows forests have been essential resources in various ways particularly in ecological, economical, political, social, cultural and religious ways.

Ecologically forests contain at least twothirds of the earths terrestrials species (Miler, 1990; Bebarta, 2004; Chivian and Berustein, 2008). This enormous wealth of species is heavily dependent on forests, especially in the tropics, making forests to be essential in biodiversity conservation. The biodiversity of forests used as building blocks of selection and breeding of plants and animals to sustain environmental and human use (Bebarta, 2004). Forests also play important role in ameliorating climate, other than serving the purpose of genetic bank or biodiversity.

CONCLUSIONS Forest resources have been harshly degraded because of resettlement patterns and are more severely being destroyed mainly because of agricultural stands validated. Local customs have been relatively environment friendly but, were being outshined by environmentally hostile external forces.

Forest resources could have been maintained, regenerated and sustainably utilized provided there has been state policies having being mutually retained with local realities or coexisted with pertinent indigenous customs stands validated.

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