Proceedings of the National Conference on Shambu -2017.pdfproduction and efficiency. There was no motivation and pressure to alter and transform the system. Ethiopia is mainly characterized

Proceedings of the National Conference on

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

Transformation in Ethiopia

Date: 23rd and 24th 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.

Copyright © Wollega University, 2018

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)

1.

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

Fantahun Dereje, Ashenafi Mengistu, Diriba Geleti and Buzunesh Tesfaye ... . 19-38

2.

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

Melkamu Dugassa, Hirpa Legesse, Negash Geleta .. .. .. 39-54

3.

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

Mengesha Lemma Urgaya . 55-72

4.

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

Desalegn Negasa Soresa and Tola Abdisa .. .. 73-82

5.

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 .. 83-87

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

A National Conference on

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

Date: 23-24 February 2017

i

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 23rd 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.

ii

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 self-

sufficiency 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

iii

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,

iv

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 President

Wollega University Nekemte, Ethiopia.

Dr. Hirpa Legesse Research and Technology Transfer Vice-president


Dr. Diriba Diba Research & Innovation Director


Dr. Raghavendra HL Publication and Dissemination Director


v

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

vi

km2 : 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

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

1

Welcome Address

By

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


2

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


3

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 sub-Saharan 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.


4

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


5

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.


6

Opening Speech By

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 energy-efficient projects in less-developed countries (known as “joint


7

implementation”), clean-development 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.


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.


8


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!


9

Keynote Address

By

Dr. Amsalu Ayana

ISSD Ethiopia Project, Addis Ababa, Ethiopia.

Email: [email protected]; Tel: +251 911842210

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

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 Agro-biodiversity

• 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


10

• 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 (agro-industry =food and beverages,

textile, leather, sugar)

– Plays 1st 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 5th 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 knowledge-worker 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.


11

• 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 self-sufficiency 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


12

– e.g. Japan adapted American large farm technologies to its small rice

plots

• Focusing 1st 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 3rd

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 micro-ecologies.

• Public sector education, research and extension systems were

demand-driven 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


13

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 self-sufficiency 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


14

– 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.

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

Keynote Address

Dr. Alem Tsehai

Dambalii Dairy Farm

External Structure of Dambalii Farm

Animals from Dambalii Farm


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

15

Keynote Address

By

Dr. Alem Tsehai Tesfa (PhD)

Dambalii Dairy Farm PLC, Nekemte

Internal Structure of the Farm

Pasture Field around the Farm



Agriculture and Rural Development

The Challenges on National Transformation in Ethiopia

� Knowledge 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

How to Plan and Implement of Development Program


16

The Challenges on National Transformation in Ethiopia

dge is Power, So is Development!!

Help rural community to identify their primary need instead of telling them their need

on few/several options how to meet these

Give them some time to digest these options before taking any action

option and start planning

Rural Development Plan

How to Plan and Implement of Development Program


17

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,

humanWetc )

� 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 out-lets for their products

� Emphasize on reducing soil compaction and erosion (stall feeding/zero grazing)

� Develop efficient utilization of on farm produced by-products

� 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


Role of an Advisor

� Advisor is a CHANGE AGENT, who creates an atmosphere

ways of DOING THINGS

OR

� He or she is AN INTRUDER – forcing people to change their way of living instead

of Motivating them to up-grade their traditional knowhow

Important Points to Consider in 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

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?

የእድገትየእድገትየእድገትየእድገት መሰላልመሰላልመሰላልመሰላል

� 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


18

Advisor is a CHANGE AGENT, who creates an atmosphere for learning better

forcing people to change their way of living instead

grade their traditional knowhow

n Advisory

community and the problem within, in order to be able

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

WHAT ARE THE COMPONENTS OF THE DEVELOPMENT PROGRAM?

Who is the right advisor for this development program? Based on what criteria?

ማያያዝ

ማዘጋጀት

ጥናት ማድረግ


19

The Effect of Variety and Seed Proportions on Yield, Nutritional

Quality and Compatibility of Oats and Vetch Mixtures

Fantahun Dereje1, 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.


20

INTRODUCTION

Ethiopia has large livestock population and diverse agro-ecological 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 industry-based

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 grass-legume 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


21

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.


22

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 sub-moist agro-ecology, 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 6m2

(3m*2m). In each plot

there were 7 rows and seeds were uniformly drilled in rows with intra-row spacing 30cm.


23

Table 1: Depiction of the treatment combinations and their sole counterparts.

Trt Treatment combination Amount

sown in (gm) Variety name and their combinations

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



6 75% oats V1+25% vetch V2 36(oats) + 3(vetch) SRCP X 80 Ab 2806 + 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 65oC 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 = sub-sample dry weight (g); HA = harvest area

(m2), and SSFW = sub-sample fresh weight (g).


24

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.


25

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:

RCCGL=DMYGL / (DMYGG - DMYGL)

RCCLG =DMYLG / (DMYLL - DMYLG)

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

RCCGL = DMYGL X ZLG/ (DMYGG - DMYGL) X ZGL

Where: RCC = relative crowding coefficient, ZGL = the sown proportion of grasses in

combination with legumes, ZLG = 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,


26

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=µ +Ti+Bj+ εijk;

Where, Yijk= measurable variable, µ=overall mean of the population, Ti= The ithTreatment

effect, Bj= jthBlock effect, εijk=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 /m2 and stand count at tillering has a range of 15 to 408.


27

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

Treatments

Seedling count at emergence (per m2)

Stand count at tillering (per m2)

Oats Vetch Oats Vetch

100% oats variety 1 143a - 757ab -

100% oats variety 2 133a - 846a -

75% oats V2+25% vetch V1 120ab 7bcde 712ab 37d

75% oats V2+25% vetch V2 91abc 4de 636abc 15d

50% oats V2+50% vetch V2 69bcd 5cde 663abc 23d

50% oats V2+50% vetch V1 62cde 5de 528bcd 45cd

75% oats V1+25% vetch V1 57cde 4de 512bcde 43cd

75% oatsV1+25% vetch V2 48cdef 4de 429cdef 15d

50% oats V1+50% vetch V1 46cdef 8bcd 358def 115bc

50% oats V1+50% vetch V2 39def 6cde 400cdef 37d

25% oats V2+75% vetch V2 35def 6bcde 340def 27d

25% oats V2+75% vetch V1 27def 9abc 288def 154b

25% oats V1+75% vetch V1 20def 10ab 246efg 124b

25% oats V1+75% vetch V2 17ef 7bcde 222fg 30d

100% vetch variety 1 - 12a - 408a

100% vetch variety 2 - 6cde - 164b

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 abcW

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


28

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

Treatment DM (t/ha) Height (cm)

Vigor Plot cover Oats Vetch

75% oats V2+25% vetch V1 17.61a 71bcde 103bcd 8ab 8

100% oats variety 2 16.32ab 87ab - 7ab 8

100% oats variety 1 15.76ab 78abc - 9a 8

75% oats V1+25% vetch V1 15.57ab 51e 96cd 9a 9

75% oats V2+25% vetch V2 15.43ab 77abcd 63e 8ab 8

25% oats V2+75% vetch V1 14.09abc 80abc 116abc 8ab 9

100% vetch variety 1 13.94abc - 117ab 8ab 8

50% oats V2+50% vetch V2 13.72abcd 90ab 68e 9a 9

25% oats V1+75% vetch V1 13.49abcde 72bcd 94d 8ab 8

50% oats V1+50% vetch V1 13.44abcde 73bcd 123ab 8ab 8

75% oats V1+25% vetch V2 13.14bcde 58de 55e 7bc 7

50% oats V2+50% vetch V1 12.82bcde 85ab 126a 8ab 8

25% oats V2+75% vetch V2 11.15cde 95a 51e 8ab 8

50% oats V1+50% vetch V2 9.60def 62cde 53e 7bc 7

25% oats V1+75% vetch V2 9.29ef 65cde 55e 7abc 8

100% vetch variety 2 6.48f - 60e 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

abcW 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


29

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.

Treatments Chemical composition

DM (%) Ash ADF ADL NDF CP Hemi Cell

100% oats variety 1 93.56a

11.68abc

31.67bcde

4.60b

49.87abcd

14.56gh

18.20abc

27.07abcd

100% oats variety 2 93.40a

11.53abc

36.47a

5.20b

53.73abc

13.76h

17.27abcd

31.27a

75% oats V1+25% vetch V1 92.95a

11.62abc

32.50abcd

7.80ab

41.80cde

17.67bcd

9.30cd

24.70bcde

50% oats V1+50% vetch V1 92.85a

11.59abc

27.73ef

10.13a

44.73bcde

17.75bc

17.00abcd

17.60f

25% oats V1+75% vetch V1 91.15b

11.43abc

31.60bcde

7.90ab

60.00a

18.68ab

28.40a

23.70bcde

75% oats V1+25% vetch V2 93.76a

12.21a

28.60def

6.40ab

41.93cde

17.73bc

13.33bcd

22.20bcdef

50% oats V1+50% vetch V2 93.06a

11.17abc

28.73cdef

5.40b

41.60cde

17.12bcde

12.87bcd

23.33bcdef

25% oats V1+75% vetch V2 93.10a

12.30a

26.60def

6.33ab

42.07cde

17.48bcd

15.47bcd

20.27ef

75% oats V2+25% vetch V1 92.90a

12.07ab

32.07abcde

7.00ab

56.67ab

16.55cdef

24.60ab

25.07bcde

50% oats V2+50% vetch V1 93.05a

10.69bcd

32.13abcde

6.80ab

49.73abcd

15.55ef

17.60abcd

25.33bcde

25% oats V2+75% vetch V1 93.36a

11.49abc

33.07abc

5.33b

50.60abcd

18.58ab

17.53abcd

27.73abc

75% oats V2+25% vetch V2 93.06a

11.78ab

28.60def

4.20b

46.00bcde

16.01defg

17.40abcd

24.40bcde

50% oats V2+50% vetch V2 93.23a

11.74abc

33.27ab

5.27b

49.80abcd

15.46fg

16.53abcd

28.00ab

25% oats V2+75% vetch V2 93.22a

10.85abcd

32.53abcd

10.47a

48.73abcde

15.56ef

16.20bcd

22.07cdef

100% vetch variety 1 93.67a

10.24cd

33.27ab

6.40ab

39.47de

19.80a

6.20d

26.87abcd

100% vetch variety 2 92.75a

9.35d

27.73ef

6.20ab

36.73e

18.01bc

9.00cd

21.53def

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 abcW

means with different superscripts within a column are significantly different (P<0.05)


30

0

2

4

6

8

10

12

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

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.

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%


31

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 oats-vetch 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% oats-vetch 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% oats-vetch. 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.

Crop Seed

proportion

Relative Yield RYT

Relative Crowding Coefficient

Aggressivity Index

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


32

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

grass-legume mixtures grasses showed higher herbage DM yield. In the present study,

relatively higher DM yield was obtained from mixtures of 75% oats-25% 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

two-cut 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

oats-vetch 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.


33

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 non-significance 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).


34

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.


35

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 oats-vetch 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% oats-vetch 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


36

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% oats-vetch 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,

tha-1) 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 agro-ecologies and soil type.

Further assessment of the oats-vetch variety mixtures for their performance over years,

across diverse agro-ecologies and on-farm farmer managed plots is also vital to more

fine-tuned recommendation.

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Akililu M. and Alemayehu M. (2007). Measurements in pasture and forage cropping systems. Technical manual 18, EIAR, Addis Ababa, Ethiopia.Pg 41.

Alemu B., Melaku S. and Prasad N.K. (2007). Effects of varying seed proportions and harvesting stages on biological compatibility and forage yield of oats (Avena sativa L.) and vetch mixtures. Livestock Research for Rural Development 19(1): Article #12. Retrieved Jan 9, 2018, from http://www.lrrd.org/lrrd19/1/alem19012.htm

AOAC. (1995). Official methods of analysis. Association of Official Analytical Chemists (A.O.A.C), 15th ed. Washington, DC, 69-88.

Assefa G. and Ledin I. (2001). Effect of variety, soil type and fertiliser on the establishment, growth, forage yield, quality and voluntary intake by cattle of oats and vetches cultivated in pure stands and mixtures. Animal Feed Science and Technology 92: 95-111.

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39

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


40

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 bio-fuel. 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 agro-ecological 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).


41

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. Non-availability 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 13th 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 rain-fed 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 socio-economic 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.


42

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.



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

Nekemte-Bure-Bahir Dar Main road. The area is located at altitude between 1500-


43

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. BH-540 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, (12m2) with spacing of 2m

between blocks and 1m between plots.

Experimental Procedure

The total area used for the experiment was 1392 m2 (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 4th 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


44

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


45

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 inter-specific

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 1.44-3.84%. The highest grain yield of maize in monoculture compared to their yield

in the intercropping situation might be due to absence of inter-specific 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.


46

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 non-significant

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 variation

Df EL ED NEPP NRPE NSPR NSPE HI HUSW BYt/ha GYt/ha

Replication 2 22.316* 0.018* 0.006* 0.026Ns 0.788* 1079.437* 0.00006* 2.150Ns 0.147Ns 0.016*

Arrangement(A) 3 8.55Ns 0.251** 0.001* 0.390* 4.243** 4856.558* 0.0021** 0.638Ns 23.903** 0.006*

Spacing (B) 4 58.625* 0.108* 0.003* 1.353* 6.381** 11302.057** 0.00026* 1.275Ns 3.073** 0.002Ns

AXB 12 2.98Ns 0.007Ns 0.0003Ns 0.032Ns 0.158Ns 231.487Ns 0.7Ns 0.763Ns 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) 100.20a 3.47

a 1.01

a 13.06

ba 42

a 559.10

a 30.7

c 39.93

a

2(1:2) 100.80a 3.31

b 1.00

a 12.95

ba 41.12

b 537.91

b 32.3

b 40.06

a

3(2:1) 101.20a 3.54

a 1.02

a 13.17

a 42.01

a 566.68

a 30.5

c 39.66

a

4(2:2) 99.46a 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


47

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 98.08c 3.28

b 1.00

b 12.97

c 40.70

d 508.58

d 32.3

a 40.25

a

2 15cm 98.58bc

3.30b 1.00

b 12.81

bc 41.06

dc 529.39

dc 31.8

ba 40.25

a

3 20cm 100.08bac

3.45a 1.00

b 13.17

ba 41.42

c 549.01

bc 31.5

bc 39.75

a

4 25cm 102.16ba

3.45a 1.01

ba 13.21

a 42.00

b 565.02

ba 31.2

c 39.50

a

5 30cm 103.16a 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 98.93b 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 100.93b 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 100.06b 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 101.06b 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 101.06b 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 104.00a 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


48

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


49

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


50

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 67.48-93.83 % 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.


51

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

Sources of Variation

Degrees of

freedom

Mean square values

NPPP NPPPP NSPP HPW HSW HI PYPP

Replication 2 0.882* 0.365* 0.043* 0.35Ns 10.85* 0.00006NS

0.468*

Row arrangement(A)

3 171.859** 149.731** 0.16** 28.416** 14.71* 0.0004* 184.368**

Spacing (B) 4 8.589** 6.567** 0.088* 16.166* 9.566* 0.00006Ns

7.961**

AXB 12 0.477* 0.478* 0.004Ns

1.166Ns

0.377Ns

0.00005Ns

0.941*

Error 38 0.608 0.451 0.012 2.385 2.604 0.0001 0.284

Coefficient of Variation

6.823 7.195 5.954 1.105 2.553 2.714 5.007

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

Sources of Variation Degrees of Mean square Values

freedom PYt/ha SP

BYt/ha GYt/ha

Replication 2 0.0003Ns

0.0001*

0.011Ns

0.0003Ns

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

SP NPPP NPPPP NSPP HPW HSW

PYPP (g)

BYPP (g)

HI (%)

PY t/ha

BY t/ha

GY t/ha

SP

10cm 15.22b 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 9.26d 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 13.26c 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 7.97d 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 7.97d 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) 45.66a 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


52

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 (67.48-93.83%) due

to the different row arrangements and spacing of the intercropping situation but maize can

be intercropped with groundnut by less yield sacrifice of (1.44-3.84%) only.

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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):78-85.

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):45-62.

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: 313-320.

Fukai S. and Trenbath B.R.C (1993). Processed determining intercrop productivity and yield of Component crops. Field Crop Research 34: 247-257.

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: 53-57.

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: 202-207

Ghosh P.K. (2002) Agronomic and economic evaluation of groundnut (Arachis hypogaea)-Cereal fodder intercropping during the post-rainy season. Indian Journal of Agronomy 47(4): 509-513.

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): 479-486.

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): 99-102.

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):87-90

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): 7-11.

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): 3139-3146.


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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): 15-18.

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): 37-43.

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, 10-14 Feb. 1986, Harare, Zimbabwe. Patancheru, A. P. 502:324 India: ICRISAT. pp. 57-64.

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 2:1-8

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): 147-150.

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):92-94, 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 Rain-Fed Conditions. ARPN Journal of Science and Technology 3(1): 69-74.

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): 16-19.

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: 280-290.

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55

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 agro-based

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


56

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 rain-fed 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.


MATERIAL AND METHODS


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

50' 0" to 390 10' 0" E longitudes with al

boundary area of 894.37 km2 (Figure1).

Figure 1: Map of the study area

The study area is characterized by unimodal ra

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

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 and length of growing period (LGP) are critical

information on historical rainfall changeability over an area.

Characterization of Rainfall Features of the

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


57

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 altitude ranges from 1097to 2513 m.a.s.l and

Map of the study area

The study area is characterized by unimodal rainfall 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

nd length of growing period (LGP) are critical

information on historical rainfall changeability over an area.

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 data’s


58

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 rainfall-reference 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 30th 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.


59

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


60

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

Descriptive statistics

Annual Rainfall (mm)

Total Seasonal Rainfall (mm)

ONDJ (Dry)

FMAM (Belg)

JJAS (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

25th

percentile 723.65 11.475 96.35 544.6

50th

percentile 833.55 25.4 167.1 601.95

75th

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: Mann-Kendall trend analysis of rainfall (mm)

Time series Rainfall trend

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 = mann-kandall 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).


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

The mean annual rainfall increased at Ada’aa District in

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

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).

common, understanding, the rainfall amount, distribution, onset and

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

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


61

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

Annual total rainfall anomalies at Ada’aa District


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

DOY), 2001 (72 DOY) and 2005 (66 DOY) to the latest around July 11

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

with a standard deviation of 39 DOY (Figure 4).

SOS is on March 27th (87 DOY) (once in every four years) with the upper percentile on

June 10th (157 DOY) (three times out of four years). Therefore planting e

(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

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

3).

Figure 4: Start of the season (SOS) of rainfall at

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

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

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.


62

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)), 1987 (66 DOY), 1996 (70

DOY), 2001 (72 DOY) and 2005 (66 DOY) to the latest around July 11th

(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 of May

with a standard deviation of 39 DOY (Figure 4). As showed in Table 3, the 25 percentile of

(87 DOY) (once in every four years) with the upper percentile on

(157 DOY) (three times out of four years). Therefore planting earlier 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

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 is 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.


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 hence, LGP becomes dependent on the onset of rainfall (Table


63

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

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

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

nce, LGP becomes dependent on the onset of rainfall (Table


64

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 (1980-2010)

Descriptive statistics Rainfall features (Start, End and Length of growing period)

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

21stuntil 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).


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

probability of 10 and 15 days dry spells occurrence become less than 10% from mid

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

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

September, which is a time that most people in the study area

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

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

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


65

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 spells. 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

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 well 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 of drought immediately after the cessation of

Therefore, farmers who have access to supplementary irrigation could cope up with risks

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


66

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.


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.)

Depth (mm) Early planting (20-Jul)

Etc 340.6

Eff.Rain 257.5

Gross Irr.Req. 158.4

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

determinant 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

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

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


67

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

Growing period chickpea crop water requirement (ETc), effective rainfall (Eff.

Rain) of the season and supplemented irrigation requirement (Irr.Req.)

Planting date

Normal Planting (20-Aug) Late planting

(10-Sep)

346.4 343.8

108.2 38

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

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. The

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

upplementary 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 irrigation

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


68

0

50

100

150

Initial Phase Development Phase Flowering Phase Maturity Phase

Depth (mm)

Normal plant (August 20)

ETc (mm/decade) Eff.rainfall (mm/decade) Irr.req (mm/decade)

(b)

0

50

100

150

Initial Phase Development phase Flowering Phase Maturity Phase

Depth (mm)

Early planting (July-20)


(a)

0

50

100

150

Initial Phase Development Phase Flowering Phase Maturity phase

Depth (mm)

Late planting (September 10)


(c)

but the distribution of the rainfall throughout the critical growth stages of chickpea

production of the study area.

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


69

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 9a-c). 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 (July-20) and hence, provides better yield with less

supplementary irrigation ((Figure 9a-c). In all planting date development followed by

flowering (mid) growth stage is sensitive to water stress. Therefore, Water harvesting (in

situ and ex-situ) 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 mid-August 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


70

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 in-situ and ex-situ 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.


71

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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73

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

E-mail: [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 m2 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


74

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 wheat-based diet is higher in fiber than a meat-based 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


75

wheat gene (Yr27) that was previously resistant to the disease (Winning the Battle Against

Deadly Wheat Fungus: http://www.cgiar.org/consortium-news/winning-the-battle-against-

deadly-wheat-fungus/: 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.


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. 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 1800-2000mm and the annual minimum and maximum

temperature is 17-210C. 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


76

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

Entry Genotype Pedigree Seed Source

1 ETBW 7178 DVERD-2/AE.SQUARROSA(214)//2*ESDA/ IESRRL# 53

2 ETBW 7252 SAMAR-8/KAUZ’S’//CHAM-4/SHUHA’S’ IESRRL # 214

3 ETBW 7238 CROW ‘S’/BOW’S’ 3-1994/95//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’ 3-1994/95//TEVEE’S’/T IESRRL # 176

7 ETBW 7171 FOW'S'//NS732/HER/3/CHAM-6//GHURA IESRRL# 43

8 ETBW 7208 CHAM-4/SHUHA'S'/6/2*SAKER/5/RBS/AN IESRRL# 110

9 ETBW 7236 CROW ‘S’/BOW’S’ 3-1994/95//KATILA-11 IESRRL # 174

10 ETBW 7248 SAKER/5/RBS/ANZA/3/KVZ/HYS//YMH/TUL/ IESRRL # 209

11 ETBW 7173 FOW'S'//NS732/HER/3/CHAM-6//GHURA IESRRL# 45

12 ETBW 7235 CROW ‘S’/BOW’S’-1994/95//ASFOOR-5 IESRRL # 173

13 ETBW 7268 SOMAMA-9//SERI 82/SHUHA’S’ IESRRL # 272

14 ETBW 7174 CHAM-6/GHURAB'S'//JADIDA-2 IESRRL# 46


16 ETBW 7221 DUCULA/KAUZ/3/KAUZ'S'//GLEN/PRL'S'/4 IESRRL# 142

17 ETBW 7227 IZAZ-2//TEVEE'S'/SHUHA'S' IESRRL# 164

18 ETBW 7239 WEEBILL – 1/BOCRO-3 IESRRL # 178

19 ETBW 7160 CHAM-6/WW 1402 IESRRL# 29

20 ETBW 7161 CHAM-6/WW 1403 IESRRL# 30

21 ETBW 7191 BOCRO-4/3/MAYO'S'//CROW'S'/VEE'S' IESRRL# 72


23 ETBW 7182 CHIL-1//VEE'S'/SAKER'S' IESRRL# 58


25 ETBW 7204 SHA3/SERI//YANG87-142/3/2*TOWPE IESRRL# 103

26 ETBW 7234 IRQIPAW 35 S5B-98/ABUZIG-4 IESRRL# 172

27 ETBW 7164 SHUHA-4//NS732/HER IESRRL# 33


29 ETBW 7244 ANDALIEB-5// TEVEE-1/SHUHA-6 IESRRL # 198

30 ETBW 7258 SABA/FLAG-1 IESRRL # 234

31 ETBW 7264 SERI 82/SHUHA’S’// SOMAMA-9 IESRRL # 268


33 ETBW 7156 TAM200/TUI//MILAN/KAUZ/3/CROC-AB 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/FOW-2 IESRRL# 47


77

Design and Data Management

At Debre-Zeyit, 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 m2

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 Metro-Mix 200 vermiculite peat-perlite 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

06YEM34-1 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 air-tight container at 80 % humidity maintained by

a KOH solution for 2–4 h. Urediniospores were then suspended in a light-weight 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±20 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.


78

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


79

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

No Code TTKSK TKTTF TRTTF JRCQC

1ST 5sc 2

nd 3

rd 1

st 2

nd 3

rd 1

st 2

nd 3

rd 1

st 2

nd 3

rd

1 G-1 2 0 - 0 2 - 0 ; - 0 0 -

2 G-2 2 2+ - ; 0 - ; ; - ; 0 -

3 G-3 3- 3- - 2+ 3- - 2 ;2- - ;1 2+ -

4 G-4 ;1 1 - ;1(c) ;1 - ; ; - ; ;1 -

5 G-5 3- 3- - 3- 2+,3- - ;2- ;2- - 0 3- -

6 G-6(1) 2+ 3- - 2+ 0 - 2 ;1 - ;1 ;1 -

7 G-6(2) 2+ 2+,3- - 2 3- - ;2- ;2 - 0,2 2+ -

8 G-8 3- 3 - 2,2+ 3- - 2+ ;2 - ;1 3- -

9 G-9 ;1 ;1 - ;1(c) ;1 - 2- ;1+ - ; ; -

10 G-10 2 1 - ;1 ;1 - 2 ;1 - ;1 1+ -

11 G-11 2+ ;1 - ;1 3- - ;1+ 3- - ;1 ;1 -

12 G-12 3- 3- - 2- 3- - 2- ;1 - ; 3- -

13 G-13 ;1+ 3- - ;2+ ;1 - ;1+ ;2 - ;1 ;1 -

14 G-14 2+,3- 3- - ;1 ;1 - ;1 ;1 - ;1 ;1 -

15 G-15 ;1 ;1 - ;1 0 - ;1 ; - ;1 1 -

16 G-16 2+,3- 2+ - ;2 2

2 3- - 2- 2- -

17 G-17 ;1 2+ - ; ;1 - ; ;1+ - ; ;1 -

18 G-18 ; 2 - ; ;1 - ; ;1+ - ;1 ;1+ -

19 G-19 2- 2+ - ;1 ;1 - ; 2- - ; ;1+ -

20 G-20 ;1 ;1 - ;1 ;1 - ; ;1+ - ; ;1 -

21 G-21 ;1 ; - ;1 ;1 - ; ;1 - 0 ; -

22 G-22 ;1+ 2 - ;1 2 - ;1 ;1 - ;1 ;1 -

23 G-23 ;1,2+ 3- - ;1 1+ - ;1 ;1+ - ;1 2- -

24 G-24 2(c) 3- - ;1 1+ - ;1 ;1+ - ; 2 -

25 G-25 ;1+ 2-

0 1 - ;1 ;1+ - ;1 ;1 -

26 G26 3- 3- - ;2 2 - 3- 3- - ; 3- -

27 G-27 2+ 2+,3- - ;1 ;1 - ;1 ;1+ - ; ;1 -

28 G-28 3- 3- - ;2 3 - 2- 3- - ;1 2+ -

29 G-29 2+ 3- - ;1 1+ - ;1 ;2- - ;1 ;1 -

30 G-30 2+(c) 1 - ;1 1+ - ;1+ 3- - 0,1 0 -

31 G-31 ;1+ ;1 - ;1 ;1 - ;1 ;1 - ;1 ;1 -

32 G-32 2- 2- - ;1+ 2 - ;1 ;1 - ;1 ;1 -

33 G-33 2- 2 - ;1+ 2+ - ;1+ ;1 - ;1 ;1+ -

34 G-34 2,2+ 3- - ;1+ 2- - ;1 2,3- - ; ;1+ -

35 G-35 ;1 ;1 - 0 0 - 0 0 - 0 ; -

36 G-36 ;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 01MN84A-1-2, TTKSK 04KEN156/04, TTKST 06KEN19V3, TTKSF UVPgt55, TTKSP UVPgt59, PTKST UVPgt60


80

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

No. Cultivar/ Accession Number

Terminal 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.


81

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 marker-assisted selection or marker-assisted 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


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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: 762-766

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 Gebre-mariam (1991). Bread wheat breeding and genetics research in Ethiopia. In Hailu Gebre-Mariam, 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 Non-centers. Science 174: 468-473.

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 91:1096-1099.

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: 476-480.

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. 239-255. 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 E-617, p 53

Yu L.X., Liu S., Anderson J.A., Singh R.P., Jin Y., Dubcovsky J., Brown-Guidera G., Bhavani S., Morgounov A., He Z., Huerta-Espino J., and Sorrells M.E. (2010). Haplotype diversity of stem rust resistance loci in uncharacterized wheat lines. Molecular Breeding 26: 667-680.


83

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

E-mail: [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


84

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 Shoreman-Onimet, 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.


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


85

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 agro-forestry 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


86

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 two-thirds 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.


87

REFERENCES

Barbour R. (2008). Introducing Qualitative Research: A Student Guide to the Craft of Doing Qualitative Research. London, UK: Sage Publications Ltd.

Bebarta K.C. (2004). Forest resources and sustainable development. Principles, perspectives, prospective and practices. New Delhi: Concept Publishing Company.

Chivian E. and A. Berustein eds. (2008). Sustaining the life: How human health depends on biodiversity. Oxford: University Press.

Dove M.R. and Carpenter C., eds. (2008). Environmental anthropology: A historical reader. Malden: Blackwell Publishing.

Ellen Roy, ed. (2011). Environmental anthropology: studies in environmental anthropology andethnobiology. Kent: University of Kent.

Flick U. (2006). Introduction to qualitative research.2nd

Edition. London: SWAGE Publication.

Henn N. (2006). The power of environmental knowledge: ethnoecology and environmental conflicts in Mexican conservation. In the environment in anthropology: A reader in ecology, culture, and susta8inable-Nora Haem and Richard Wilk, Eds.P.p226-236 New York: New York University press.

Haenn N. and Wilk R., eds. (2006). The environment in Anthropology. A reader in ecology, culture, and sustainable living. New York: New York University Press.

Kala M and Aruna S. (2010). Traditional Indian beliefs. A key towards sustainable living. Environmentalist 30: 85-89.

Kopnina H., Eshoreman-onimet eds. (2011). Environmental Anthropology today. New York Routledge.

Miller T.G. (1990). Living in the environment. An introduction to environmental Sciences. 6

thedition. Belmont. Wadsworth Publishing Company.

Milton Kay (1996). Environmentalism and cultural theory. Exploring the role of anthropology in environmental discourse. London and New York. Rontledge.

Rabinow P. (1984). Reflections of field work in Morocco. Berkely University of California Press.

Sutton M.Q. and Anderson E.N. (2004). Introduction to cultural ecology. Oxford. BERG

Townsend P.K. (2008).Environmental anthropology. From pigs to policies 2nd

edition. Mayfield, IL. Waveland Press.

Documents

Proceedings of the National Conference on Shambu -2017.pdfproduction and efficiency. There was no motivation and pressure to alter and transform the system. Ethiopia is mainly characterized