last final thesis of umer

MEKELLE UNIVERSITY

CoDANR

Yield and Economic Advantage of Intercropping Maize using

different densities and varieties of cowpea in Jijiga, Eastern

Ethiopia

By

Omar Hassan Elmi

A Thesis

Submitted in Partial Fulfilment of the Requirement for the

Masters of Science Degree in Dryland Agronomy

College of Dryland Agriculture and Natural Resources

Department of Dryland Crop and Horticultural Science

Mekelle University, Ethiopia

Main Advisor: Daniel Gebrekidan (PhD)

Co -Advisor: Alemtsehay Tsegay (PhD)

May, 2019

Mekelle ,Ethiopia

i

DECLARATION

This is to certify that this thesis entitled “Yield and Economic Advantage of Intercropping

Maize using different densities and varieties of cowpea in Jijiga, Eastern Ethiopia” submitted

to the Department of Dryland Crop and Horticulture Science, Mekelle University, in partial

fulfillment of the requirements for the award of the degree of Master of science in Dryland

Agronomy, is my (Omar Hassan) own original research work under the guidance of my

supervisors Daniel Gebrekidan(PhD) and Alemtsahy Tsegay (PhD).

I declare that the matter embodied in this thesis work has not been submitted earlier for award of

any degree or diploma to the best of my knowledge.

Name of student: Omar Hassan Elmi

Name of the main adviser: Daniel Gebrekidan (PhD)

Name of the Co-adviser: Alemtsehay Tsegay (PhD)

Name of Postgraduate coordinator

Name of Department head

Signature and date_______________



Signature and date _______________

Signature and date ______________

i

ABSTRACT

A field experiment was conducted at Jijiga University Eastern Ethiopia, during 2018 cropping

season to investigate the effect of maize-cowpea intercropping systems on the productivity of the

component crops, on soil fertility and investigate the cost effectiveness of intercropping. Maize

variety ‘Malkasa-4’ was intercropped with three varieties of cowpea (Kenketi, Black eye bean and

Bole) in a factorial combination of three population densities of 50%, 75% and 100% of the

recommended population density along with sole crops of the respective varieties of cowpea and

maize in randomized complete block design with three replications. The Highest and lowest of

grain yield(3184 1271and kg ha -1 ) were obtained from maize intercropped with 50% population

of cowpea, kenketi variety and maize intercropped with100% population of cowpea, Bole variety

cowpea respectively. Sole (3189kg ha -1 ) maize record higher yield than intercropped maize

(2210kg ha -1 ). The highest (8537kg ha -1 ) and lowest (4643 kg ha -1 ) biomass of maize was recorded

from maize intercropped with cowpea at 50% and 100% planting density respectively. Moreover

Sole maize (11682kg ha -1 ) was significantly superior (P<0.05) than the intercropped maize (6507

kg ha -1 ) with regard to maize dry biomass. The highest grain yield (2298 kg ha -1 ) of cowpea

varieties was recorded for cowpea variety kenketi at planting density of 100% while the lowest

grain yield (696kg ha -1 ) was recorded for cowpea variety Bole at 50% planting density. The

highest total LER (1.478) and net benefit (69264.81 Birr/hr) were recorded when 100% cowpea,

Kenketi variety was intercropped with maize. Therefore, based on the above agronomic and

economic evaluations, maize intercropped with cowpea variety kenketi at planting density of 100%

of the cowpea can be recommended for intercropping of maize with cowpea in the study area.

However, the experiment has to be repeated across over seasons with consideration of farmer’s

preference of the cowpea varieties to reach at conclusive recommendation.

Keywords: Maize, Intercropping, cowpea density, Land equivalent ratio, cowpea varieties.

ii

DEDICATION

I dedicate this Thesis to my parents and all family members, for nursing me with affection, love

and for their dedicated partnership in the success of my life.

iii

BIOGRAPHICAL SKETCH

The author, Omar Hassan, was born in June 1993 in Aysha District, Sitti Zone of Ethio-Somale

Regional State. He attended his junior and elementary School at Alfalah from 1999 to 2007 and

his secondary and preparatory school at Addisu School from 2008 to 2012 in Dire Dawa. Then, he

joined Adama University College of Agriculture and Environmental science in 2013 and graduated

with BSc degree in Agriculture (Plant science) in June 2015. Soon after graduation he was

employed by Jigjiga University in September 2015 to work in Dryland Crop Science Department

where he served as Graduate Assistance until he joined the post graduate programs at Mekelle

University in October 2018 through financial grant obtained from the Ministry Education to pursue

a Postgraduate Master of Science in the field of Dry land Agronomy.

iv

ACKNOWLEDGMENTS

First of all thanks to Almighty Allah (sw), for helping me in all circumstances to complete the course

work and my thesis research successfully. Next I would like to express my heart-felt gratitude to my

major adviser Dr. Daniel Gebrekidan for his unreserved genuine guidance and constructive

comments, starting from proposal writing to end of the work and I appreciate his readiness to share

his experience and knowledge. I am so grateful to my co-adviser Dr. Alemtsehay Tsegay for her

positive comments, suggestions and criticisms, throughout the research time.

Special thanks also go to Haramay University soil laboratory technicians for their support on

analyzing soil phsio-chemical properties.

Many thanks also go to Jigjija University for providing me land for the field experiment, inputs and

equipment for field work, data collection and measurements.

Grateful thanks is also extended to the staff and the management of Melkasa Agricultural Research

Center for providing me improved maize (melkasa-4) and cowpea varieties (Kenketi, Black eye

bean and bole) seeds.

Finally, I want to express my love and thanks to my companions Hassen,Abdi and Abdikadir for

their help and good friendship during the thesis research.

v

TABLE OF CONTENTS

DECLARATION............................................................................................................................ i

ABSTRACT ................................................................................................................................... ii

DEDICATION.............................................................................................................................. iii

BIOGRAPHICAL SKETCH ...................................................................................................... iv

ACKNOWLEDGMENTS ............................................................................................................ v

LIST OF TABLES ....................................................................................................................... ix

LIST OF ABBREVIATIONS AND ACRONYMS .................................................................. xii

CHAPTER 1: INTRODUCTION ................................................................................................ 1

1.2 Statement of the problem and justification....................................................................... 2

1.3 Objective of the study ......................................................................................................... 3

1.3.1 General objective of the study ..................................................................................... 3

1.3.2 Specific objectives ......................................................................................................... 4

1.4. Research Questions ............................................................................................................ 4

1.5. Hypothesis ........................................................................................................................... 4

CHAPTER 2. LITERATURE REVIEW .................................................................................... 5

2.1. Origin and Distribution of Maize ..................................................................................... 5

2.2. Ecology of Maize................................................................................................................. 6

2.3. Maize Production in Ethiopia ........................................................................................... 8

2.4. Importance of Maize .......................................................................................................... 9

2.5. Yield Gap in Maize ........................................................................................................... 11

2.6. Origin, Distribution and World Production of Cowpea ............................................... 12

2.7. Major Cowpea production constraints .......................................................................... 13

2.8. Importance of Intercropping........................................................................................... 14

2.9. Maize-cowpea intercropping systems ............................................................................. 15

vi

2.10. Relations of maize and cowpea intercropping in terms of nutrient use efficiency

(NUE)........................................................................................................................................ 16

2.11. Relations of maize and cowpea intercropping in terms of water use efficiency

(WUE)....................................................................................................................................... 17

2.12. Relations of maize and cowpea intercropping in terms of radiation Use Efficiency

(RUE)........................................................................................................................................ 17

2.13. Intercropping and Weed Effects ................................................................................... 19

2.14. Pests and diseases in intercropping .............................................................................. 20

2.15 Competition of species in intercropping ....................................................................... 22

Chapter 3: MATERIALS AND METHODS ............................................................................ 23

3.1. Description of the Study Area ......................................................................................... 23

3.2 Experimental materials..................................................................................................... 24

3.3. Treatment and Experimental Design ............................................................................. 25

3.4. Experimental Procedure and Field Management ......................................................... 26

3.5. Soil Sampling and Analysis ............................................................................................. 27

3.6 Data Collection and analysis ............................................................................................ 28

3.6.1. Phenological stages .................................................................................................... 28

3.6.2. Growth parameters ................................................................................................... 28

3.6.3. Yield and yield components ...................................................................................... 29

3.7. Land Equivalent ratio (LER).......................................................................................... 30

3.8 Economic analysis ............................................................................................................. 31

3.9. Statistical Data Analysis .................................................................................................. 32

Chapter 4: RESULT AND DISCUSSION ................................................................................ 33

4.1. Effect of intercropping of maize with different population density and varieties of

cowpea on soil properties ........................................................................................................ 33

4.1.1. Soil Analysis before Planting .................................................................................... 33

vii

4.1.2 Soil analysis after Harvesting .................................................................................... 34

4.2 Effect of intercropping of maize with different population density and varieties of

cowpea on yield and yield components of maize crops ........................................................ 37

4.2.1. Maize phenology ........................................................................................................ 37

4.2.2. Effect on Growth parameters of maize .................................................................... 39

4.2.3. Effect on Yield and Yield Components of maize .................................................... 41

4.3. Effect of intercropping of maize with different population density and varieties of

cowpea on yield and yield components of cowpea crop ....................................................... 46

4.3.1. Cowpea Phenology ..................................................................................................... 46

4.3.2. Effect on Growth parameters of cowpea ................................................................. 49

4.3.3. Effect on yield and yield related parameters of cowpea ........................................ 53

4.4 Land Equivalent Ratio ...................................................................................................... 59

4.5. Economic Analysis............................................................................................................ 61

CHAPTER 5. CONCLUSION AND RECOMMENDATION................................................ 63

5.1 Conclusions ........................................................................................................................ 63

5.2 Recommendations ............................................................................................................. 64

REFERENCES ............................................................................................................................ 65

APPENDIXES ............................................................................................................................. 86

viii

LIST OF TABLES

Table 1.Description of the maize and cowpea varieties. .............................................................. 25

Table 2.Treatment combinations. ................................................................................................. 26

Table 3.Physio-chemical properties of the experimental site before planting. ............................. 34

Table 4.Interaction effect of the intercropped cowpea varieties and plant populations on Total

nitrogen (%) after harvesting. ....................................................................................................... 35

Table 5.Interaction effect of the intercropped cowpea varieties and plant populations on organic

matter content (%) after harvesting............................................................................................... 37

Table 6.Effects of densities and varieties of cowpea on phenology of sole and intercropped

maize. ............................................................................................................................................ 39

Table 7.Growth parameters of maize as affected by varieties, population densities of component

cowpea and cropping system. ....................................................................................................... 41

Table 8.Interaction effect of the intercropped cowpea varieties and plant populations on grain

yield (kg ha -1 ) of maize. ................................................................................................................ 44

Table 9.Effects of cowpea densities, varieties and cropping system on number of ears per plant

(NEPP), Thousand kernel weight (TKW (g)), Dry above ground biomass (B (kgha -1 )), Harvest

index (HI (%) of sole and intercropped maize. ............................................................................. 45


cowpea with maize. ....................................................................................................................... 48

Table 11.Interaction effect of the intercropped cowpea varieties and plant populations on height

of cowpea in maize/cowpea intercropping. .................................................................................. 50

Table 12.Effects of component densities and varieties of cowpea on number of branches per

plant (NBPP) and leaf area (LA) of sole and intercropped cowpea. ............................................ 52

Table 13. Interaction effect of the intercropped cowpea varieties and plant populations on grain

yield of cowpea in maize/cowpea intercropping. ......................................................................... 57

Table 14.Effects of component densities and varieties of cowpea on number of pods per plant

(NPPP), number of seed per pod (NSPP) ,aboveground dry biomass (AGBB) and harvest index

(HI) of sole and intercropped cowpea. ......................................................................................... 59

Table 15.Cowpea varieties, plant density and their interaction effects on total LER of

intercropped maize and cowpea. ................................................................................................... 60

Table 16.Dominance analysis of the treatment combinations ...................................................... 61

Table 17.The marginal rate of return of maize, cowpea varieties and plant density combinations.

....................................................................................................................................................... 62

ix

LIST OF FIGURES

Figure 1.Ethio-maize production .................................................................................................... 9

Figure 2. Map of the study area, Jijiga, Ethiopia. ......................................................................... 23

Figure 3. Rainfall pattern at Jijiga Station. (Devereux, 2006) ...................................................... 24

x

LIST OF TABLES IN THE APPENDIXES

Appendix Table 1.Mean square values of ANOVA for phenological parameters of maize as

affected by cowpea density and cowpea varieties. ....................................................................... 86

Appendix Table 2.Mean square values of ANOVA for growth parameters of maize as affected

by cowpea density and cowpea varieties ...................................................................................... 86

Appendix Table 3.Mean square values of ANOVA for yield and yield related parameters of

maize as affected by cowpea density and cowpea varieties. ........................................................ 87

Appendix Table 4.Mean square values of ANOVA for phenological parameters of cowpea as

affected by cowpea density and cowpea varieties. ....................................................................... 87

Appendix Table 5.Mean square values of ANOVA for growth parameters of cowpea as affected

by cowpea density and cowpea varieties. ..................................................................................... 88


cowpea as affected by cowpea density and cowpea varieties. ...................................................... 88

Appendix Table 7.Mean square values of ANOVA for total nitrogen and organic matter content

as affected by cowpea density and cowpea varieties. ................................................................... 89

xi

LIST OF ABBREVIATIONS AND ACRONYMS

ANOVA

CEC

CSA

DAP

FAO

GM

GMO

HI

IPM

IPS

LER

LSD

MoA

MRR

NUE

PAR

RCBD

RUE

SOC

SRS

TR

TVC

WUE

Analysis of Variance

Cation Exchange Capacity

Central Statistical Agency

Diammonium Phosphate

Food and Agriculture Organization

Gross Margin

Genetically Modified Organisms

Harvest Index

Integrated Pest Management

Industrial Project Service

Land Equivalent Ratio

Least Significant Difference

Ministry of Agriculture

Marginal Rate of Return

Nutrient Use Efficiency

Photosynthetically Active Radiation

Randomized Complete Block Design

Radiation Use Efficiency

Soil Organic Carbon

Somale Regional State

Total Return

Total Variable Cost

Water Use Efficiency

xii

CHAPTER 1: INTRODUCTION

1.1 Background

Maize (Zea mays, L) is one of the major cereals and chief sources of energy in human diet. It is

the most widely distributed cereal crop. Maize has a number of uses as food for man, feed for

livestock and for making many kinds of non-food products (Usha and Pandey, 2007). It is the most

versatile crop with wider adaptability in varied agro-ecologies and has highest genetic yield

potential among the food grain crops. New production technologies offer great promise for

increasing maize productivity to meet the growing demands of world consumers. For decades,

maize growers have worked for continuous improvement and greater efficiency (Singh et al.,

2002).

In Ethiopia maize is the second in area coverage (2,128,948.91 hectares annually) next to Teff

(3,023,283.50 hectares) and first in production (83,958,872.44 quintals) (CSA, 2018).Maize is

grown primarily in the Amhara, Oromia and SNNP regions of Ethiopia (FAO, 2008). From 2001

to 2011, maize production increased by 50%, due to increases in both per hectare yields (+25%)

and area under cultivation (+20%).So maize continues to be a significant contributor to the

economic and social development of Ethiopia (Mogues, et al., 2008).

Cowpea is an important food grain legume for over 200 million people in the dry savanna

of tropical Africa and its grain is a good source of human protein, while the haulms are

valuable source of livestock protein (Fatokun, 2002). The dried seed and green pods are

consumed as human food. It is cultivated between 35 0 N to 30 0 S of the equator .Being a drought

tolerant crop with better growth in warm climates, cowpea is most popular in the semi-arid regions

of the tropics, where other food legumes do not perform well.

1

Cowpea is tolerant to a wide range of soil textures from sands to heavy, well-drained clays. It

adapts to a wide range of pH although it prefers slightly acid to slightly alkaline soils. It has little

tolerance to salinity (Romain and Raemaekers, 2001). Cowpea is also shade-tolerant and,

therefore, compatible an intercrop with a number of cereals like maize and root crops as well as

with cotton, sugarcane, and several plantation crops (Magashi et al., 2012).

In Jijiga (the study area), farmers harvest only twice in a year, from sole cropping systems. Such

traditional farming systems doesn’t ensure the production of adequate food for the family

especially under the increasing population. It is also true that most farmers of the zone use

traditional cropping systems which are based on poor agricultural inputs, subsistence requirements,

and are not necessarily the most efficient ones. Because of this, crop production per unit land area

is usually below world average. Therefore, in diversified crop production systems having

production constraints, diversified options need to be assessed (Fininsa, 2001).

Intercropping is the simultaneous growing of two or more crops in the same field (Takim, 2012)

and is a cropping system that has long been used for a long-time in tropical areas to increase

productivity and sustainability (Hauggaard-Nieson et al., 2001).

In general, agronomic recommendation for intercropping maize with cowpea and other food

crops is scanty in the study area most especially relating to other row arrangement and optimum

population density of the component crop(s).

1.2 Statement of the problem and justification

Poor soil fertility management, poor crop husbandry and effects of climate change are the major

challenges and contribute for low crop productivity. Agro-ecological intensification of land use is

2

a prerequisite for increased agricultural productivity, natural resource conservation and sustainable

development (CCRP, 2009).

Poor agricultural production and productivity is also a problem in Somale Region of Ethiopia due

to low soil fertility and the situation is worsened by cultivating of one crop year after year causing

certain nutrient depletion.The majority of somale region farmers lack financial resources to

purchase sufficient amount of mineral fertilizers to replace soil nutrients removed through

harvested crop products, crop residues, and through loss by runoff, leaching and as gases.

Consequently, poor soil fertility has emerged as one of the greatest biophysical constraint to

increasing agricultural productivity hence threatening food security in this region.

Therefore, it is necessary to adopt improved and sustainable agronomic practices in order to

guarantee improvement in food productivity and there by food security (Landers, 2007). Such

technologies include the use of integrated soil fertility management (ISFM) like intercropping

cereals with legumes (Sanginga and Woomer, 2009). Intercropping legumes with cereals in water

limited areas like the study area can be a principal means of intensifying crop production both

spatially and temporally to improve crop yields for smallholder farmers and for effective labor

utilization per unit of area of available land (Seran and Brintha, 2010).

1.3 Objective of the study

1.3.1 General objective of the study

The purpose of this study is to investigate the effect of maize-cowpea intercropping systems on

the productivity of the component crops, on soil fertility and investigate the cost effectiveness of

intercropping.

3

1.3.2 Specific objectives

1. To evaluate how different population densities of cowpea variety influences the yield and

yield components of maize crop.

2. To study the effects of different cowpea varieties intercropped with maize on yield and yield

related components of maize crop.

3. To demonstrate the crop yield differences between intercropping and sole cropping of maize.

1.4. Research Questions

‣ Does maize and cowpea intercropping have a significant relationship with the yields of the

component crops?

‣ Does different combinations of cowpea varieties with maize affects the productivity of

maize?

‣ How different population densities of cowpea affects the maize yield?

‣ Does intercropping be economically feasible to small holder farmers compare to sole

cropping of the component crops?

1.5. Hypothesis

Intercropping maize with different densities and varieties of cowpea will affect the yield and

yield related components of the component crops.

4

CHAPTER 2. LITERATURE REVIEW

2.1. Origin and Distribution of Maize

Maize (Zea mays L.) is considered to be indigenous to the Americas particularly Southern Mexico.

It has been domesticated about 8000 years ago and does not exist in its wild form (Mandal, 2014).

The crop is a tropical grass that is well adapted to many climates and hence has varieties which

have wide range of maturity from 70 to 210 days (Stephanie and Brown, 2008).

The name ‘maize’ is derived from a South American Indian Arawak – Carib word “Mahiz”. It was

first used for food about 10,000 years ago by Red Indians living in the area now called Mexico.

For hundreds of years, the tribal people in the area, gathered the grains from wild plants before

they learnt to grow maize themselves. Thus, it was also called “Indian corn” although this did not

refer to the Asian country “India” in any way, rather it refers to Red Indians (Usha and Pandey,

2007).

The genus Zea is classified in the tribe Maydeae of the family Poaceae/Gramineae. There is only

one species, Zea mays, which is known only in cultivation. Closely related to this genus are two

other New World genera, Tripsacum (called Gama grass which is used as fodder in North America)

and Euchlaena (called Teosinte, believed to be the closest wild relative of maize). Some

taxonomists do not recognize Euchlaena as a separate genus and have transferred all the species

of this genus to Zea (Usha and Pandey, 2007).

Usually Africa, Ethiopia in particular, grow mainly white dent or semi-flint white grain maize.

White flint maize is growing in Central America and South America, Asia and Southern Europe.

Overall white maize occupies only 10% of the world maize production. The majority of the areas

5

around the world are planted under yellow maize, and a very small fraction to other grain colors,

such as black, red, violet, green-blue and other grain colors (ATA, 2013a).

Yellow dent maize is primarily produced as livestock feed. Lesser amounts are grown and

harvested (the entire aboveground biomass) at physiological maturity to be made into green silage

for animal feed. Recently, some large areas of maize production have been dedicated for the

production of biofuel, such as ethanol. Sweet maize was developed to be harvested immature green

on the cob for human consumption. Popcorn is used primarily for human consumption as a freshly

popped snack food (ATA, 2013a).

2.2. Ecology of Maize

Maize is grown globally from 50° N to 40° S, and from sea level up to 4000 m altitude. It is a

short-day plant with 12.5 hour light per day being suggested as the critical photoperiod.

Photoperiods greater than this may increase the total number of leaves produced prior to initiation

of tasseling, and may increase the time taken from emergence to tassel initiation (Stephanie and

Brown, 2008).

It is a warm weather plant that requires high temperature during the growing period. The crop

requires an average temperature of about 24 °C. Low temperature reduces growth and extremely

high temperature may retard germination of seed, particularly when it’s combined with deficient

moisture (Balasubramaniyan and Palanlappan, 2007). The optimum temperature for maize growth

and development is 18 to 32 °C, with temperatures of 35 °C and above considered inhibitory. The

optimum soil temperatures for germination and early seedling growth are 12 °C or greater, and at

tasseling 21 to 30 °C is ideal (Stephanie and Brown, 2008).

6

Approximately 10 to 16 kg of grain are produced for every millimeter of water used. Yield of 3152

kg/ha requires between 350 and 450 mm of rain per annum. At maturity, each plant will have used

250 liter of water in the absence of moisture stress (Plessis, 2003). According to the Stephanie and

Brown (2008) maize can grow and yield with as little as 300 mm but prefers 500 to 1200 mm as

the optimal range. Depending on soil type and stored soil moisture, crop failure would be expected

if less than 300 mm of rain were received in crop.

The crop grows well under any soil type with pH ranging from slightly acidic to slightly alkaline

(pH range of 5.8 to 7.5). Adequate drainage is needed to allow for the maintenance of sufficient

oxygen in the soil for good root growth and microbial activity, as well as water holding capacity

to provide adequate moisture throughout the growing season (ATA, 2013a). A deep loamy soil,

high in organic matter and plant nutrients is the best soil for maize production. However, with

proper management and fertilizer practices, a variety can be grown successfully on any soil from

loamy sand to clay. The soil should be free from salinity and water logging (Chowdhury and

Hassan, 2013).

Water loggings is very damaging specifically at seeding stage. Continuous water logging for 3

days reduces the yield by 40–45% (Chandrase, 2010). The most suitable soil for maize is one with

a good effective depth, favorable morphological properties, good internal drainage, optimal

moisture regime, sufficient and balanced quantities of plant nutrients and chemical properties that

are favorable specifically for maize production (Plessis, 2003).

7

2.3. Maize Production in Ethiopia

Ethiopia’s agriculture is complex, involving substantial variation in crops grown across the

country’s different regions and ecologies. Five major cereals (barley, maize, sorghum, wheat and

teff) are the core of Ethiopia’s agriculture and food economy (Alemayehu et al., 2011).

In Ethiopia cereals are the major food crops both in terms of area and volume of production. They

are produced in larger volume than with other crops because they are the principal staple crops.

Cereals are grown in all the regions with varying quantity. Out of the total grain crop area, 80.78%

(10,144,252.30 hectares) was under cereals, of the 80.78% maize is 16.80 %( CSA, 2015).

In Ethiopia, maize production is of recent history. Probably it was introduced to this country from

Kenya during the 17th Century. Maize has been introduced to Ethiopia in the 1600s to 1700s.

Since its introduction it has become an important food crop and at present covers the area of over

1.5 million ha; second only to teff in area, but first in total production. In Ethiopia, maize grows

under a wide range of environmental conditions between 500 to 2400 meters above sea level.

Ethiopia is already a significant maize producer in Africa. Currently, Ethiopia is the fourth largest

maize producing country in Africa, and first in the East African region (ATA, 2013a).

The national maize average grain yield is relatively low, standing at around 2300kg/ha, well below

the world average of 4000 kg/ha. However, the crop is planted mainly for self-consumption and

significant proportion of it is harvested as green maize on the cob during the “hungry period”

which brings the dry average grain yield lower (ATA, 2013a).

Maize is the only crop with significant use of commercial inputs. In 2008, about 37 % of the maize

farmers used fertilizer, compared to the national average of 17 % for all cereal farmers. An

8

estimated 26 % of the maize growers used improved seed, which is again about twice the national

average for all cereal farmers (Rashid et al., 2010).

2.4. Importance of Maize

Figure 1.Ethio-maize production

Maize is one of the most important cereal crops in the world’s agricultural economy both as food

for men and feed for animals. Because of its higher yield potential than other cereals, it is called

as “Queen of Cereals”. Maize has low fiber content, more carbohydrate and most palatable. It is

widely used in preparation of cattle feed and poultry feed. It can be used as green fodder and has

no hydrogen cyanide (HCN) content. It can be preserved in silage (Chandrase, 2010).

9

Food products, like corn meal, corn flakes, etc., can be prepared. Green cobs are roasted and eaten

by the people. It is used in making industrial products, like alcohol, corn starch (dextrose), glucose,

corn oil, corn syrup etc., and used in canning industry; production of polymer, making paper, paper

boards, and bread. Its grain contains proteins (10%), carbohydrates (70%), oil (4%), albuminoides

(10.4%), crude fiber (2.3%) and ash (1.4%) (Chandrase, 2010).

In developed countries, maize is consumed mainly as second-cycle produce, in the form of meat,

eggs and dairy products. In developing countries, it is consumed directly and serves as staple diet

for some 200 million people. Most people regard maize as a breakfast cereal. However, in a

processed form it is also found as fuel (ethanol) and starch. Starch in turn involves enzymatic

conversion into products, such as sorbitol, dextrine, sorbic and lactic acid, and appears in

household items, such as beer, ice cream, syrup, shoe polish, glue, fireworks,ink, batteries,

mustard, cosmetics, aspirin and paint ( Plessis, 2003).

In Ethiopia maize is produced mainly for food, especially in major maize producing regions,

particularly for low income groups, it is used as stable food. It is consumed as injera,

porridge,bread and nefro. It is also consumed roasted or boiled as vegetable at green stage. In

addition to the above, it is used to prepare local alcoholic drinks known as tella and arekie. The

leaf and stalk are used for animal feed and also dried stalk and cobs are used for fuel. It also used

as industrial raw material for oil and glucose production, (MoA, 2010).

Moreover, maize plays a central role in Ethiopia’s food security. It is the lowest cost source of

cereal calories. It is the staple cereal crop with the highest current and potential yield from available

inputs, at 2.2 tons per hectare in 2008/09 with a potential for 4.7 tons per hectare according to onfarm

field trials, when cultivated with fertilizer (Rashid et al., 2010).

10

2.5. Yield Gap in Maize

Increasing concern about the future of agriculture in sub-Saharan Africa in light of accelerating

soil degradation and potential of threats of climate change have increased the need for new and

more adapted cropping systems that increase production ,whilst conserving the natural

resources(FAO,2002).

Conservation agriculture is one of the “greener” solutions currently being controversially

discussed (Gilbert,2012) as a potential cropping system that can mitigate the negative effects of

declining soil fertility and climate change under arrange of farming systems.

Conservation agriculture is cropping system based on minimum soil disturbance, the retention of

living or dead plant materials as surface mulch and rotation of crops of different species in full

rotations, as inter or relay crops (FAO, 2002).

Maize yield in conservation agriculture system (mono cropped or intercropped with legume) were

higher than in conventional tillage practices. However, associating maize with legumes reduced

maize grain in some seasons when only conservation agriculture were compared to each other

(Kamanga et al., 2010).

Closing the yield gap, therefore is wide geographic variation in crop and livestock production,

even cross regions that experience similar climates. The difference between realized productivity

and the best that can be achieved using current genetic materials and available technologies is

termed the “yield gap”. The best yield that can be obtained locally depend the capacity of the

farmers to access and use sustainable cropping system, improved seed and proper agronomic

managements (Charles et al., 2016).

11

2.6. Origin, Distribution and World Production of Cowpea

Cowpea is one of the most ancient crops known to man. Its origin and domestication occurred in

Africa near Ethiopia and subsequently was developed mainly in the farms of African savannah.

It’s an indigenous crop that has evolved from the native wild types and its genetic diversity is

greater than that of any other crop in the dry African savannah (IFAD, 2000).

Nowadays it’s a legume widely adapted and grown throughout the world, especially in the tropics

and subtropics and has become a part of the diet of about 110 million people .It is a warm season

crop that can be produced in semi-arid regions and dry savannah. The major cowpea growing

countriesare,Niger,Mali,Senegal,Togo,Benin,Ghana,ChadinwestAfrica;Tanzania,Somalia,Kenya,

Zambia,Zimbabwe,Bostwana and Mozambique in Easter and southern Africa; India, Pakistan, Sri

Lanka, the Philippines, Bangladesh, Indonesia and china in Asia; and Brazil, West India, Cuba and

Southern USA in America(Gianessi,et al.,2007).Burkina Faso, Cameroon, Kenya, Mali, Senegal

are the other prominent producers in Africa (IITA, 1977). Generally area under cowpea has gone

up with many new countries contributing to total production from the last decade onwards.

In Ethiopia, cowpea is now becoming among the most commonly cultivated lowland pulses. It is

grown in rift valley areas of Ethiopia for its fodder and grain value (dual purpose) (Kidane et al.,

2004). Similarly different genotypes of cowpea are adapted well to the semi-arid lowlands of

northern Ethiopia. Different cowpea varieties such as 82D-889, Bole (85D-3517-2), IT (98K-131-

2) Asrat ( IT 92KD-279-3) and Bekur(8386894) which were released by different research center

since 2001 are under production (MoARD,2009).

12

2.7. Major Cowpea production constraints

In Ethiopia, at the farm level, productivity appears to be severely constrained by three major factors

(MoARD, 2008). Those factors include (i) limited or no use of chemical fertilizers (e.g.

Phosphates) ;( ii) very limited availability of improved varieties (mostly grown from unimproved

cultivars with low genetic potential); and use of conventional agronomic practices (e.g., suboptimal

crop rotation, poor seed bed preparation, in appropriate planting density).

Generally biotic (weeds, insect pest) and abiotic (infertile soil, moisture stress etc.) factors are the

main challenges in cowpea production. Weeds are a serious problem in cowpea production and if

not managed well can harbor pest and reduce both the yield and quality of the grain and fodder

yield. Cowpea is not strong competitor with weed especially at the early stage of the growth. The

two types of parasitic weeds that attack cowpea are striga gesnerioides and Alectra (Ditomaso et

al., 2017).Moreover, cowpea may be affected by fungal diseases such as fusarium wilt (fusarium

oxysporum), brown rust (Uromyces appendiculatu); southern stem blight (Sclerotium spp) and

bacterial diseases such as bacterial blight or canker (xanthomonas vignicola) and visrus diseases

such as cowpea mosaic virus (Ditomaso et al., 2017).

Insect pests are also major constraints to cowpea production. Cowpea pest can be classified into

three major groups: pre-flowering (Cowpea aphid), flowering/post flowering (Flower thrips,

Blister beetles, Pod-sucking bugs) and storage (weevil). Damage by insect pest on cowpea can be

as high as 80-100% if not effectively controlled (Alectra (Ditomaso et al., 2017).

13

2.8. Importance of Intercropping

Cereal-legume intercropping plays an important role in subsistence food production in both

developed and developing countries, especially in situations of limited water resources

(Dahmardeh et al., 2010). Intercropping of cereal and legume crops helps maintain and improve

soil fertility (Tsubo M et al., 2005) and plays an important role in subsistence food production in

developing countries (Dahmardeh et al., 2010). Because farmers cannot afford inorganic

fertilizers. Legumes fix atmospheric nitrogen, which may be utilized by the host plant or may be

excreted from the nodules into the soil and be used by other plants growing nearby (Andrews,

1979). Legumes can also transfer fixed N to intercropped cereals during their joint growing period

and this N is an important resource for the cereals (Shen and Chu, 2004).

Legume intercrops have several socioeconomic (Ofori and Stern, 1987), biological and ecological

advantages compared to sole cropping for small-holder farmers (Chemeda, 1997).In addition,

certain legumes crops provide food to humans and livestock (Jeranyama et al., 2000). There are

several intercrop arrangements which may include row intercropping worldwide. Yields of

intercropping are often higher than in sole cropping systems (Lithourgidis et al.,2006) mainly due

to resources such as water, light and nutrients that can be utilized more effectively than in sole

cropping systems (Li et al.,2006).

The principal reasons for small holder farmers to intercrop are flexibility, profit maximization, risk

minimization, soil conservation improvement of soil fertility, weeds, pests and disease minimizing

and balanced nutrition. Intercropping have some disadvantage such as the selection of appropriate

crop species, extra work in planting and preparing the seed mixtures and extra work during crop

management including harvest(Atila et al ,2015).

14

2.9. Maize-cowpea intercropping systems

Maize (Zea mays) and cowpea (Vigna unguiculata) are important components of traditional mixed

cropping system in the tropics because of the associated benefits; notable among which are

suppression of weeds, maintenance of soil fertility, protection of soil against soil erosion and soil

water losses, insurance against crop failure. Intercropping practice helps to increase profit margin

of the farmers, and usually suppress growth of weeds. It also controls pests and diseases occurrence

and guides against crop failure (Agbato, 2000).

Maize and cowpea exhibit complementary use of water and N resources in intercrop systems.

Cowpea in intercrop with maize has been found to supply up to 72% of its N needs through

biological N fixation, though this percentage is depressed under P limited conditions (Vesterager

et al., 2008). Maize cowpea intercrops have also been found to exhibit higher water use efficiency

than either crop in monocrop (Hulugalle and Lal, 1986).

In intercropping systems maize has been found to withdraw the majority of water under wet

conditions, while cowpea is capable of withdrawing soil water under conditions too dry for maize,

resulting in complementary water use (Adiku et al., 2001).

The productivity of maize in intercrop with cowpea relative to maize in monoculture may depend

on the fertility inputs applied to the system. Additive maize cowpea intercrops have been found to

produce maize yields that are equivalent to maize monocrops, while also producing cowpea, when

no N is added to the system (Ofori and Stern, 1987; Rusinamhodzi et al., 2012). However, under

fertilized conditions, maize yields in maize cowpea intercrops can be sharply depressed when

compared with maize monocrops (Ofori and Stern, 1987; Watiki et al., 1993) but see

15

(Rusinamhodzi et al., 2012). Similar trends have been found in other maize legume intercrops,

including maize pigeonpea and maze leucaena (Kamanga et al., 2010; Sileshi et al., 2011).

Fertility inputs can also be a factor determining intercrop advantage when the productivity of the

entire system is considered. The productivity and yield stability of maize in intercrop with cowpea

can also depend on the way that plants are arranged in the system.

2.10. Relations of maize and cowpea intercropping in terms of nutrient use

efficiency (NUE)

A possible advantage of intercropping legumes with non-legumes may be more efficient use of

soil nutrients. If both species have different rooting and uptake patterns, more efficient use of

available nutrients may occur and higher total N-uptake in intercropping systems compared to

monoculture systems have been reported (Dalal,1974). It is unclear, however, if better nutrient

uptake is the cause or the effect of higher yield potential (Willey, 1979). At high levels of nitrogen,

especially under intercropping, grain and legume yield was found to be reduced by the maize

intercrop (Ezumah et al., 1987; Ofori & Stern, 1987). Other researchers have reported a decrease

in maize yield under intercropping (Shumba et al., 1990; Siame et al., 1998).

The inconsistency of cereal and legume intercropping performance requires critical investigation

in areas where farmers are to benefit from intercropping in that specific locality (Mpangane et al.,

2004). Recent efforts to improve soil fertility have been through the introduction of legumes as an

intercrop and in rotation to minimize external inputs.

16

2.11. Relations of maize and cowpea intercropping in terms of water use

efficiency (WUE)

Availability of water is one of the most important factors determining productivity in

legume/cereal cropping systems. Farmers in the semi-tropical regions under rainfed conditions

usually practice mixed cropping. According to Ofori & Stern (1987), cereals and legumes use

water equally and competition for water may not be important in determining intercrop efficiency,

except under unfavorable conditions.

Water use by intercrops has mostly been studied in terms of water use efficiency (WUE). An

intercrop of two crop species such as legumes and cereals may use water more efficiently than a

monoculture of either species through exploring a larger total soil volume for water, especially if

the component crops have different rooting patterns (Willey, 1979). Hulugalle & Lal (1986)

reported that WUE in a maize/cowpea intercrop was higher than in the sole crops when soil water

was not limiting. However, under water limiting conditions, WUE in the intercrop compared to

sole maize can be higher resulting in retarded growth and reduced yield.

2.12. Relations of maize and cowpea intercropping in terms of radiation Use

Efficiency (RUE)

Solar radiation provides energy for photosynthesis, which ultimately sets the potential for crop

productivity and also determines water use by the process involved in evaporation and

transpiration (Goudriaan, 1982; Keating & Carberry, 1993).

17

Photo synthetically active radiation (PAR), which is utilized by green leaves, conservatively makes up

about 50% of global short wave radiation (Szeicz, 1974). Compared to high variability that occurs in

the supply of water and nutrients to the plant, solar radiation is more reliable and used sufficiently by

intercrops as they form a complete cover to allow full interception. Solar radiation cannot be stored for

later use, it must be intercepted and utilized instantaneously to energize the photosynthesis process.

Therefore, neighboring plants compete for solar radiation by direct interception (Keating & Carberry,

1993).

Studies on crop mixtures e.g. intercropping and crop/weed interactions, have concentrated on the

competition for resources between species and the emphasis in the case of competition for light

has been placed on the ability of one species to compete with and shade another (Caldwell,

1987).Differences between species, plant density, developmental pattern, plant height, canopy

architecture, foliage overlap, photosynthetic rate and in the assimilate reserves, result in great

structural complexity in mixed-species canopies.

Leaf area index (LAI), is the amount of green leaf area per unit of ground area, which is a parameter

commonly used to describe the probability of light interception in relation to crop canopies

(Keating & Carberry, 1993). Great diversity in intercrop canopies is possible, resulting from the

various combinations in space and time of planting date and spatial distribution, leaf size, shape

and orientation and plant height.

The canopy characteristics of component crops are not constant, but may change due to the

presence of other crop species (Caldwell, 1987). Crop yield is closely related to assimilate

production during the yield development period of crop growth, although it is difficult to relate

18

yield directly to solar radiation because of factors that influence the relative contributions of

assimilates produced at pre-anthesis and post-anthesis.

According to Evans & Wardlaw (1976), shading and reduced assimilate production will have the

least effect on yield if competition occurs during the vegetative growth phase. Reddy & Willey

(1981) stated that, where the components of an intercrop are in direct competition for light,

increased total biomass production by the crop could result in improved yields.

The capturing of radiant energy drives crop evapotranspiration, and the pattern of its interception

determines the ratio of water use through crop transpiration to that lost in soil evaporation.

Probably the single most disadvantage is that cowpea plants are shaded by the cereal throughout

the growing season, which results in severe reduction in shoot and root growth and ultimately in

low grain and fodder yields. Although cowpeas occupy 50% of the land area under intercropping,

its grain and fodder yields are 10- 20% less than those in sole cropping (Singh et al., 1997; Terao

et al., 1997).

2.13. Intercropping and Weed Effects

It is commonly known that intercropping reduces weed infestation and is one of the integrated

weed management strategies with less effect on the environment than the use of chemical

herbicides. The success of intercropping on weed control is much more diverse when different

legumes are inter-planted and both the cereal and the legume are considered as main crops. The

legume crop under intercropping suppresses weeds through competition for resources (Fortin et

al., 1996).

Weed infestation causes severe yield reductions in field crops, and losses of 40-60% have been

reported under sole maize cropping (Ayeni et al., 1984) although growing crops in a mixture

19

usually reduces weed occurrence (Zuofa, Tariah & Isirimah, 1992). According to Olasantan, Lucas

& Ezumah (1994), the practice of growing early maturing crops between widely spaced rows of

long duration crops and the use of nitrogen fertilizer to enhance early ground cover, improves the

suppression of weeds. In maize/cowpea intercropping, shading suppresses weed growth that

suggests the superiority of cereal and legume crops over weed growth.

Maize intercropping with soybean was also found to reduce weeds by 39% as compared to sole

maize. In a study of Ayeni et al. (1984), weed growth was not suppressed by intercropping maize

and cowpea. It was concluded that weed growth must be controlled initially in order for a canopy

to develop sufficiently enough for weed suppression in intercropped maize/cowpea systems.

2.14. Pests and diseases in intercropping

Maize is susceptible to many insects such as weevils, beetles, bollworms, stalk borers and chilo

borers and the ones that suck plant sap such as leafhoppers and maize aphids (Drinkwater et al.,

2002). Diseases such as bacterial (stalk rot and leaf streak), viral (dwarf mosaic and streak

diseases) and fungal (cob and tassel smut) are common infectious diseases including maize root

knot nematodes (Flett et al., 1996).

Cowpea is normally affected by insects such as aphids, foliage beetles, thrips and legume pod

borers (Adipala et al., 1999). Diseases such as rusts, viral diseases (e.g. athracnose) and scab are

also important including bacterial disease such as blight (Edema, 1995).

When species are grown as sole crops it attracts many pests and diseases, which visually might

show less damage when intercropped compared to monoculture (Trenbath, 1993). This may be

related to microenvironment effects of associated crops in intercropping compared to sole cropping

20

(Vandermeer, 1989; Letourneau, 1990). Thus, depending on the crop, the attack may affect

resource capture, resource conversion efficiency or harvest index (HI) through attacking of leaves,

flowers, flower buds and fruits hence upsetting the source-sink relationship and phenology (Baker

& Yusaf, 1976; Crawley, 1989). Various integrated pest management (IPM) control strategies such

as the use of cultural, biological and chemical methods are also being used for insect pest control.

Root (1973) stated that pests find it very difficult to find their hosts because of visual disturbance

for their search pattern and tend to stay for shorter times because of disruptive effect of landing on

non-host plants resulting in slow survival. Even the presence of weeds can similarly affect pest

search for their hosts (Altieri, Glaser & Schmidt, 1990).

Breeding of cereal cultivars resistant to diseases has also been used in intercropping to control

airborne diseases of rapidly evolving specialized fungal diseases such as rusts and mildews (Wolfe,

1985). Maize leafhopper (Dalbus maindis) was significantly reduced from different maize

cultivars under intercropping (Power, 1990). This was the same with fungal spores on leaves, root

parasitic nematodes (eelworms) intercepted by roots of hosts and non-hosts (Trudgill, 1991).

Intercropping the cowpea cultivar PAN 311 also reduced stalk borer Chilo partellus (Swinhoe)

infestation significantly in sorghum compared to sole crop (Ayisi & Mposi, 2001). Bean yield was

found to be reduced by intercropping as well as aphid attack (Florentine et al.,2003). Thus, when

yield is reduced due to diseases and pests attack LER is also reduced (Kass, 1978).

The variability of insect pest control and yield improvement in intercropping systems relative to

sole cropping have been inconsistent over habits, component species, varieties, density, row

arrangement, soil fertility and moisture (Ayisi & Mposi, 2001) and individual crops may not

respond the same (Nwanze & Mueller, 1989). Maize stem borer was found to be more severe under

sole cropping than intercropping with lablab [Lablab purpureus (L)] (Maluleke, Addo-Bediako &

21

Ayisi, 2005). Higher plant densities were also reported to reduce aphid infestation under

intercropping and there was a possibility that low viral disease(s) under these conditions were due

to unfavorable microclimate for the aphids in intercrops (Ogenga-Latigo et al., 1992a,b).

2.15 Competition of species in intercropping

Intercropping different crop species results inter-specific competition between the Crops. This

competition usually decreases survival, growth or reproduction of at least one species (Zhang and

Li, 2003). According to Corre-Hellou and Crozat (2007), reported that the intercropped plant

species compute the resources such as light, water and soil nutrients.

Sobkowic (2006) showed that crop competition in intercropping depends on choice of the

appropriate ratio of component species, proper choice of total density of plants per unit area for

the intercrops and planting time of the Intercrops.

22

Chapter 3: MATERIALS AND METHODS

3.1. Description of the Study Area

The study was conducted in Somali Regional State (SRS) of Ethiopia, Jijiga Zone (Figure 2), at

Jijiga University (JJU) campus experimental site. It is 630 km from Addis Ababa and lies between

9°35’N latitude and 42°8’ E longitude. The elevation is 1609 meters above sea level. Jijiga zone

is bordered in the east with the Republic of Somalia, in the west with the Oromia Regional State

and Fique Zone of the SRS, and in the South with Degahbour. It covers 40,861km 2 , of which the

rangeland extends over 36,629 km 2 (World Bank, 2001).

Figure 2. Map of the study area, Jijiga, Ethiopia.

23

The Somali Regional State has a bimodal pattern of rainfall regime. Hence, there are two cropping

seasons: The relatively long rainy season (March to April) locally called Gu and the short rainy

season (October to November) locally called Deyr. The later characterize the lowland parts of the

Ogaden basin while the highland parts of the region, mainly Jijiga and its surrounding have Gu

and Kiremt (July to September) as their cropping seasons (IPS, 2002).

According to the National Meteorological Service Agency (NMSA, 2000), the mean annual

rainfall which is 660 mm is bimodal (Figure 3). In the zone, there is generally low, unreliable and

uneven distribution of rainfall. The mean monthly minimum temperature varies from 5.8 0 C in

November to 14 0 C from July to September and the mean monthly maximum temperature varies

from 25 0 C in July to 29 0 C from March to April. In addition high runoff rates coupled with high

evaporation rates make the available rainfall insufficient especially for crop production.

Figure 3. Rainfall pattern at Jijiga Station. (Devereux, 2006)

3.2 Experimental materials

The experimental materials used were seeds of improved maize variety melkassa-4 (ECA-EE-36)

and cowpea varieties that were released by Melkasa Research Center (Kenketi, Black eye bean

and Bole). These materials were obtained from Melkasa Agricultural Research Center.

24

Table 1.Description of the maize and cowpea varieties.

Maize and

Cowpea varieties

Cowpea

1.Kenketi

2.Black eye bean

Main description Best adaptation area Date of

released

Early maturing 72-81days, erect

type, red seed color, yield ranges

2.2–3.2. T/ha.in research.

Drought resistant, early maturing

80–85

Days, white with black eye color

seed. Determinate, erect type, yield

ranges 1.6–2.0 t/ha.

3. Bole Early maturing 86-98 days, erect

type, yield 1.9 t/ha. In research. ,

white with red eye color seed

Well adapted to areas

with altitude 1000 –1850

m,and rainfall 350–

1100 mm.

Well adapted to the

drylands

with short growing

period,altitude1000–

1600 m,and rainfall

300–600 mm

Well adapted to areas

with altitude 350–1850

m,and rainfall 350–

1100 mm

2012

1970-80

2006

Maize

Melkassa-4

Maturity within 105 days; plant

height 40–165 cm; flowering 53

days; resistance

to rust-less tolerant; cooks faster;

seed color white; seed shape -semi

dent; yield

3.5–4.5 t/ha in research center; 3–

3.5 in farmers’ fields; 1000 seed

weight

350–400g.

Released for drought

stressed mid

Altitude areas of

Ethiopia,

Melkassa,Mieiso,

Ziway, Wolenchiti.

Source: Ethiopian Institute of Agricultural Research, unpublished data, 2010

2006

3.3. Treatment and Experimental Design

Three cowpea varieties and three cow pea population densities were intercropped with a maize

variety Melkasa 4. The cowpea varieties were Kenketi, Black eye bean and Bole. Cowpea

population densities were 100% (recommended seed rate), 75% and 50% in additive series for

25

maize. The treatments combinations are listed below in Table 2. The experimental plot size was

be 5 m x 4 m (20 m 2 ).The experiment was laid out in factorial randomized complete block design

(RCBD) with three replications.

Table 2.Treatment combinations.

Treatments Treatment combinations Cowpea population densities

T1 Maize +Kenketi 50%



T4 Maize+ Black eye bean 50%



T7 Maize+ Bole 50%

T8 Maize+ Bole 75%

T9 Maize+ Bole 100%

T10

Sole Maize

T11

Sole Kenketi

T12

Sole Black eye bean

T13

Sole Bole

Maize was planted at a spacing of 80 x 25 cm while cowpea varieties, which had been planted

three weeks later after maize at 1:2 maize-cowpea spatial arrangement, was planted with intra-row

spacing of 20 cm, 30 cm and 40 cm based on the treatments which represented 100%, 75% and

50% of the recommended cowpea planting density, respectively. Moreover, the three varieties of

cowpea

were planted at a spacing of 40 x 20 cm.

3.4. Experimental Procedure and Field Management

The experimental land was mechanically prepared by ploughing and harrowing. The plots were

laid out and treatments were randomly assigned onto the plots.

26

The maize seeds were planted three weeks before the planting of cowpea varieties at a spacing of

80 cm and 25 cm between and within rows, respectively for both sole and intercropping maize and

the rows for cowpea varieties were separated 40 cm from each other. The blocks and plots were

separated by 1m and 0.5 m, respectively.

3.5. Soil Sampling and Analysis

Before planting, soil samples were taken in zigzag manner randomly from the experimental site

from ten locations at a depth of 20 cm using an auger based on procedures described by Munson

and Nelson (1993) and the samples were mixed thoroughly to produce one representative

composite sample. About 1.0 kg of composite sample was taken (using polyethylene bag) to

Haramaya University soil laboratory for testing total nitrogen, available phosphorous, cation

exchange capacity (CEC), organic matter, pH and to determine soil textural class.

Soil organic carbon (SOC) was estimated for organic matter determination by wet digestion

method and organic matter was calculated by multiplying the SOC% by factor 1.724 as described

by (source). The soil pH was measured potentiometrically in 1:2.5 soil-water suspensions with

standard glass electrode pH meter.

The cation exchange capacity (CEC) was measured using 1 M ammonium acetate washed with

ethanol and the adsorbed ammonium was replaced by sodium (Na). Then, the CEC was determined

titrimetrically by distillation of ammonia that was displaced by Na. The proportion of the soil

particles was analyzed by Bouyoucos Hydrometer Method and the soil textural class was

determined using the textural triangle of USDA system. Total N in the soil was determined by the

Kjeldahl method (Dewis and Freitas, 1975). Available P was determined by the Olsen's method

27

using a spectrophotometer (Olsen et al., 1954). After harvesting, soil sampling was taken from all

treatments at a depth of 20 cm and the above mentioned parameters were analyzed.

3.6 Data Collection and analysis

3.6.1. Phenological stages

For maize

Days to 50% tasseling: The number of days taken from planting to when 50% of the plants in a

plot start emerge tassel.

Days to 90% maturity: The number of days taken from planting to when 90% the plants in a

plot formed black layer at the base of the seed.

For cowpea

Days to 50% flowering: The number of days taken from planting to when 50% of the plants in a

plot start emerges flower.

Days to 90% maturity: The number of days taken from planting to when 90% of the pods of the

plants in the plots get dried.

3.6.2. Growth parameters

For maize

Plant height (cm): The height of five randomly select plants from each row was measured after

tasseling from ground level to the point where the tassel starts branching and the mean value will

record as plant height.

For cowpea

Plant height (cm): five plants were taken as a sample to measure the height of the plants taken

from each row.

28

Leaf Area: (LA = maximum leaf width (cm) x Leaf length (cm)), so five leaves from the middle

part of five sample plants were measured in each rows.

Number of branches per plant: Number of branches per plants were counted taking five

sample plants randomly.

3.6.3. Yield and yield components

For maize

Number of ears per plant: The number of ears were taken from five random plants per plot at

harvest and the mean value was calculated.

Ear length (cm): This was recorded from the measure of five randomly sample plants ear length

at harvest.

Thousand kernel weight (g): weight of 1000 kernels taken randomly from samples used for

grain yield analysis.

Grain yield (kg ha -1 ): This refers to the weight of grain harvested from the central three rows of

the net plot. Grain yield was then converted in to adjust yield for the analysis by using this

formula. Adjusted yield=AGY-(AGY*0.1)

Aboveground biomass (kg ha -1 ): This was measured based on central three rows of the net plot

plants at harvest time after sun drying, and was changed to per hectare using respective plant

weight for each treatment.

Harvest index (HI): This was the ratio of grain yield to aboveground biomass multiplied by

100.

HI =

Grain yield

Aboveground biomass

x 100

29

For cowpea

Number of pods per plant: The number of pods per plant were counted from the five taken

sample plants.

Number of seeds per pods: The number of seeds per pod were determined from 20 pods taken

from the five sampled plants.

Grain yield: was determined from the net harvestable area and converted into adjusted yield by

using this formula Adjusted yield=AGY-(AGY*0.1)

100 seeds weight (g): weight of 100 seeds were randomly obtained from samples used for grain

yield analysis.

Harvest index (HI): This was the ratio of grain yield to aboveground biomass multiplied by

100.

HI =

Grain yield

Aboveground biomass

x 100

3.7. Land Equivalent ratio (LER)

Land Equivalent Ratio (LER): the ratio of the area under sole cropping to the area under

intercropping needed to give equal amounts of yield at the same management level. It is the sum

of the fractions of the intercropped yields divided by the sole-crop yields (FAO, 1976).

Relative yield was first determined by dividing intercrop yield of each crop by yield of sole crop.

From the sum of relative yields the land equivalent ratio (LER) were calculated mathematically as

follows as described by (FAO, 1976)

30

Relative yield =

Intercrop yield of crop A intercrop yield of Crop B intercrop yiled of crop C

+ +

Sole crop yiled of A sole crop yield of Crop B sole crop yield of crop C

Total LER = Relative yield of maize + Relative yield of cowpea

3.8 Economic analysis

Economic analysis was done using the CIMMYT partial budget analysis methodology (CIMMYT,

1988). The variables that varied the treatments were the costs of seeds, perdium (day labour) for

seeding, weeding and harvesting. During the time of purchasing we bought 2kg of maize each 17

ETB and 5kg of cowpea each 27 ETB. During the time of selling the average grain yield price of

ETB 11 per kg for maize and cowpea grain yield for Kenketi and Bole varieties of ETB 23 per kg

whereas Black eye bean ETB 26 per kg

was considered for the computation. Following the

CIMMYT partial budget analysis method, total variable costs (TVC), gross benefits (GB) and net

benefits (NB) was computed. Then treatments were arranged in an increasing TVC order with

respected benefits and dominance analysis was performed to exclude dominated treatments from

the marginal rate of return (MRR) analysis. A treatment is said to be dominated if it has a higher

TVC than the treatment, which has lower TVC next to it but having a lower net benefit. A treatment

which is non-dominated and having a MRR of greater or equal to 100% and the highest net benefit

is said to be economically profitable (CIMMYT, 1988).

Total cost that varies (TVC): This was the cost of seeds, day labour for planting, weeding and

harvesting. The cost that varied was construction of ridge and furrow, tied ridge, mulching material

and mulch application.

Gross benefit (GB): is determined by multiplying field price of soybean grain by adjusted grain

yield. GB= field price kg-1 x ADJGY

31

Net benefit (NB): was calculated by subtracting the total costs from gross field benefits for each

treatment. NB= GB-TVC

Marginal rate of return (MRR): was change in net benefit divided by change in total variable

cost. MRR (%) =

Change in net benefit

Change in total variable costs ∗ 100

3.9. Statistical Data Analysis

Analysis of variance (ANOVA) for RCBD with factorial arrangement was made using the Genstat

software (Genstat 18th Edition,) (Gomez and Gomez (1984). All treatment means were compared

using the least significant difference (LSD) at 5% level of significance.

32

Chapter 4: RESULT AND DISCUSSION

4.1. Effect of intercropping of maize with different population density and

varieties of cowpea on soil properties

4.1.1. Soil Analysis before Planting

Analysis of soil samples before planting was done for the major soil physical and chemical

properties at soil laboratory of Haramaya University and the results are indicated in Table 3.

Accordingly, the soil had total N of 0.12%, characterizing moderate according to Tekaligne et al.

(1991) where the authors classified soil total N availability of <0.05% as very low, 0.05-0.12% as

poor, 0.12-0.25% as moderate and >0.25% as high. The possible reason could be that the area was

used to cultivate cereal crops without using any organic or in organic fertilizers. The organic

carbon content of the experimental site was 1.33% and this was rated as low according to Landon

(1991) while the organic matter content of the soil computed as a function of organic carbon was

2.29% and was also rated as low according to the classification of Berhanu (1980). This author

rated soils with organic matter content of >5.20%, 2.6-5.2%, 0.8-2.6% and <0.8% as high,

medium, low and very low, respectively. Please also explain the possible reasons for low content

of the OM content in the experimental site. The soil analysis result also showed that the available

P content was rated under low (4.21ppm) according to Tekalign et al. (1991) who described soils

with available P<10, 11-31, 32-56, >56 ppm as low, medium, high and very high, respectively.

The cation exchange capacity (CEC) of the soil was medium (16.99 Cmol (+)/kg) according to

Landon (1991) who described top soils having CEC greater than 40 Cmol (+)/kg of soil are rated

as very high and 25-40 Cmol (+)/kg as high, 15-25, 5-15 and < 5 Cmol (+)/kg of soil are classified

as medium, low and very low, respectively.

33

Moreover, the pH value was 7.71, which is considered as alkaline soils according to Tekalign

(1991). The soil of the experimental site had a proportion of 64% sand, 16% silt, and 20% clay

that lead the soil to be texturally classified as sandy loam (Table 3).

Table 3.Physio-chemical properties of the experimental site before planting.

Soil parameter Unit Value

Total nitrogen % 0.12

Organic carbon % 1.33

Organic matter % 2.29

Available phosphorous ppm 4.21

Cation exchange capacity Cmol (+)/kg 16.99

Soil PH - 7.71

Particle size distribution

Sand % 64

Silt % 16

Clay % 20

4.1.2 Soil analysis after Harvesting

The soil samples from the top soil (20 cm) taken after harvest showed a pH ranges between 7.71

to 7.73 indicating alkaline. The total nitrogen of the soil after harvesting was highly significantly

(p<0.01) affected by population density and cowpea varieties as well as their interaction and

cropping system(Appendix Table 7) .The highest(0.133%) and lowest(0.129%) total nitrogen were

recorded maize intercropped with 100% kenketi variety of cowpea and maize intercropped with

50% bole variety respectively (Table 4).The differences in population densities of cowpea varieties

cause variation in the total nitrogen content among the treatments (Table 4). The higher nitrogen

content was obtained at higher population density of cowpea. This is in agreement with the finding

34

of Jossias (2011) who reported that soybean population increases the total nitrogen in

maize/soybean intercropping.

Table 4.Interaction effect of the intercropped cowpea varieties and plant populations on Total

nitrogen (%) after harvesting.

Population of cowpea

Cowpea varieties

50% 75% 100%

Kenketi 0.130 b 0.131 c 0.133 e

Black eye bean 0.131 c 0.132 d 0.131 c

Bole 0.129 a 0.132 d 0.132 d

Intercrop

Sole crop

0.131 a

0.135 b

Variety x Density

Cropping system

LSD0.05 0.00049 0.00086

CV (%) 0.22 0.83

NS = non-significant, CV (%) = coefficient of variation in %, LSD = least significant difference

at 5% level of significance , Means in column and followed by the same letters are not significantly

different at 5% level of significance according to LSD test.

Moreover, the soil analysis after harvesting showed that the intercropping of maize and cowpea

increased total soil nitrogen than sole maize planting. Unlike the sole maize, all combinations of

maize and different varieties of cowpea increased total nitrogen compared to total nitrogen content

of the site before planting (Table 4). The possible reason might be the N fixation by cowpea

varieties. Cowpea fix atmospheric nitrogen because in cowpea the bacteria (Bradyrhizobium spp)

capable of fixing atmospheric N to usable forms live in symbiotic association with the roots.

Estimate of the amount of N fixed by cowpea varies from 30 to 240kgN/ha (Jayshanker et al.,

35

2002). In addition to that, the differences in population densities of cowpea varieties also cause

variation in the total nitrogen content among the treatments (Table 4).

Similar to that of total nitrogen, organic matter content was also highly significantly (p<0.01)

affected by population density and cowpea varieties as well as their interaction but not cropping

system(Appendix Table 7).The highest(2.57%) and lowest(2.36%) organic matter were recorded

from intercropping of maize with 100% Bole variety and 50% kenketi variety respectively(Table

5). Among the varieties, bole variety results higher organic matter than cowpea varieties because

it stays long period on the field than other varieties. This shows that the building up of OM in the

soil is determined by the length of green manure growing period and maturity of the phytomass

incorporated. In addition to this, higher population densities of the cowpea also significantly

increases the organic matter of the site. In agreement with this result, Sainju (2005) found that the

amount and length of green manures stays on the field determines the level of soil organic C.

generally the organic matter content of the soil was higher after harvesting comparing before

planting due to green legumes(cowpea) which leads the increment of the organic carbon.

Available phosphorous and Cation exchange capacity (CEC) was significantly affected by none

of the factors and the ANOVA revealed no significance difference before planting and after

harvesting.

36

Table 5.Interaction effect of the intercropped cowpea varieties and plant populations on organic

matter content (%) after harvesting.


Cowpea varieties

50% 75% 100%

Kenketi 2.36 a 2.46 bc 2.51 cde

Black eye bean 2.40 ab 2.47 cd 2.55 ef

Bole 2.55 ef 2.55 ef 2.57 f

Intercrop

Sole crop

Variety x Density

Cropping system

2.497 a

2.483 a

LSD0.05 0.03 0.018

CV (%) 0.74 3.01




4.2 Effect of intercropping of maize with different population density and

varieties of cowpea on yield and yield components of maize crops

4.2.1. Maize phenology

Days to 50% Tasseling

Analysis of variance revealed that days to tasseling was significantly (P<0.05) and highly

significantly (p<0.01) affected by cropping system and population densities of cowpea,

respectively while cowpea varieties and interactions (variety and density) were not significant

(Appendix Table1). Sole cropped maize took longer days to tasseling than intercropped. This

might be because of less number of plants per plot in the case sole crop than intercropped which

37

allows sole crops to extend its vegetative growth as described by Morris and Garrity (1993). With

regard to density, days to tasseling range from 68.67 days for 50 % population density to 70.44

days for 100% population density (Table 6).This result indicated when plant population increase,

the number of days to tasseling was increased due to inadequacy of light, nutrient and water

resulted due to competition. This result agrees with the findings of Sangoi et al. (2002) who

concluded that high plant density lengthen the gap between pollen shedding and silking. This result

is also in line with the report of Tokatlidis and Koutroubas (2004) who found that high plant

density affects the required interval for pollen shedding and silk emergence. Similarly, Verdelli et

al. (2012) and Yusuf et al.(2012) reported that high plant density of soybean extends the days of

maize to tasseling and silking in maize/soybean intercropping. Mitiku & Getachew (2017) reported

that common bean varieties were not significantly affected on days to 50% heading and days to

90% maturity of rice crop.

Days to 90% to physiological maturity

The analysis of variance revealed that days to 90% physiological maturity was not significantly

affected by population density, cowpea varieties and their interaction as well as cropping system

(Appendix Table1). Similar to this finding, Lulie et al. (2016) reported that the effect of common

bean spatial arrangement and population density had no significant effect on days to tasseling,

silking and maturity on maize. Moreover, Demessew (2002) and Yesuf (2003) reported that days

to 50% emergence and maturity of maize/common bean and sorghum/common bean are not

affected by component planting density and varieties of common beans. In addition to these

findings, Sisay (2004) reported that non-significant sorghum-green gram intercrop on days 50%

maturity of sorghum which harmonized to the current findings.

38


maize.

Treatments Days to 50% tasseling Days to 90% maturity

Cowpea plant density

50% 68.67 a 104.6 a

75% 69.44 ab 104.3 a

100% 70.44 b 104.1 a

LSD(P<0.05) 2.016 NS

Cowpea verities

Kenketi 69.11 a 104.0 a

Black eye bean 69.22 a 104.3 a

Bole 70.22 a 104.7 a

LSD(P<0.05) NS NS

CV% 1.67 1.41

Cropping system

Sole maize 71.67 a 105.0 a

Intercropped maize 69.52 b 104.3 a

LSD(P<0.05) 1.70 NS

CV% 1.96 1.22




4.2.2. Effect on Growth parameters of maize

Plant height (cm)

The result of study indicated that planting density had highly significant (P<0.01) effect on plant

height of maize unlike to cowpea varieties, interactions (variety and density) as well as cropping

system that showed non-significant effect (Appendix Table 2). The tallest (120.5 cm) plants were

recorded at planting density of 100% which was at par with 75% and shortest (111.0 cm) plants

were recorded from 50% maize-cow pea intercrop (Table 7). In general, as the planting density of

39

cowpea increased, the height of the associated maize increased indicating increased competition

from the associated cowpea for the limited resources. This result is in agreement with previous

studies conducted by Sarma (1994) on Sesamum indicum which indicated that in narrow spacing

plants that resulted high population per unit area compete more for available resources especially

for light and this resulted in more height than widely spaced plants. As sesame plants compete for

light, high populations grow taller and faster than low populations (Langham, 2007). However,

the current study with regard to the varieties and cropping system contradicted with Abebe et al,

(2013) who reported that there was significant variation in plant height of intercropped maize due

to soybean varieties integrated with N fertilizer application on maize-soybean intercropping

although it is in line with Biruk (2007 who reported that main effect of component planting

densities, interaction effect and cropping system had no effect on plant height of sorghum

intercropped with common bean varieties .

Ear height (cm)

Similar to plant height, ear height was highly significantly (P<0.01) affected by population

densities while cowpea varieties, interaction (variety and density) as well as cropping system

showed non-significant (Appendix Table 2). The longest (49.27 cm) and shortest (44.00 cm) ear

heights were recorded at planting density of 100% and 50%, respectively (Table 7). This might be

due to high competition for growth resources at high density. This current finding agree with

Hassan (2000) report who found that ear heights increased with the increase of the plant number

and Kariaga (2004) who reported that cropping system did not significantly affect maize ear height

in miaze/bean intercropping. Similarly, Gözübenli (2010) who concluded that the ear heights

increased as the plant density increased. However, this result disagree with the result reported by

40

Alemayehu et al, (2018) where common bean varieties significantly influenced the ear height of

maize in maize-common bean intercropping.

Table 7.Growth parameters of maize as affected by varieties, population densities of component

cowpea and cropping system.

Treatments Plant height (cm) Ear height(cm)


50% 111.0 a 44.00 a

75% 118.0 b 46.44 b

100% 120.5 b 49.27 c

LSD(P<0.05) 2.074 2.38

Cowpea verities

Kenketi 117.2 a 47.21 a

Black eye bean 116.7 a 47.07a

Bole 115.6 a 45.43 a

LSD(P<0.05) NS NS

CV% 1.78 3.20

Cropping system


Intercropped maize 116.5 a 46.57 a

LSD(P<0.05) NS NS

CV% 4.04 6.43




4.2.3. Effect on Yield and Yield Components of maize

Number of ears per plant

Number of ears per plant showed significant (P<0.05) difference due to cropping systems, and

cowpea density but non-significantly affected by cowpea variety and interaction (variety and

density) effect (Appendix Table 3). Significantly higher number of ears per plant (1.733) was

recorded from sole maize than the intercropped maize (1.474) (Table 9). The reduction in number

41

of ears per plant in intercropped maize might be due to the reduction in the ear leaf photosynthesis

due to competition for growth resources with cowpea. With regards to cowpea density, the highest

number of ears per plant (1.667) was obtained from maize intercropped with 50% of cowpea

population while the lowest number of ears per plant (1.343) was obtained from maize

intercropped with 100% of cowpea population which is statically no different from 75%population

density of cowpea (Table 9). This might be due to increased inter competition for growth resources

from the associated cowpea as its density increased. This result is inconformity with Teshome et

al, (2015) who reported that cropping system and soybean densities cause difference on number

of ear per maize plant in maize/soybean intercropping.

Thousand kernel weight (g)

1000 kernel weight was significantly (P<0.05) affected by cowpea population density while

cowpea varieties, interaction (variety and density) and cropping system showed non-significance

difference (Appendix Table 3). The highest thousand kernel weight (207.5 g) was obtained from

maize intercropped with 50% of cowpea population while intercropping with 100% cowpea

population gave the lowest thousand kernel weight (162.2 g) (Table 9). This might be due to

increased competition for growth resources from the associated cowpea as its density increased.

In conformity with this result, Biruk (2007) reported that 25% common bean planted with 100%

sorghum planting density gave the highest mean 1000 kernel weight of the sorghum component.

In contrast, Tilahuun (2002) reported that planting density and planting patterns of beans had no

significant effect on 1000 kernel weight of the associated maize. In agreement with this finding,

Wogayehu (2005) reported non-significant effect of the associated bean varieties on thousandkernel

weight of maize.

42

Aboveground biomass (kg ha -1 )

Dry aboveground biomass was significantly (p<0.05) affected by the planting density of the

associated cowpea and cropping system but non-significantly affected by variety and the

interaction of variety with planting density (Appendix Table 3). The highest (8537 kg ha -1 ) and

lowest (4643 kg ha -1 ) biomass of maize was recorded from maize intercropped with cowpea at

50% and 100% planting density, respectively (Table 9). The higher biomass at 50% might be due

to less planting density that might have resulted in less competition between maize and cowpea

for the resources. This is in line with the findings of Mitiku & Getachew (2017) who reported that

rice dry biomass significantly decreased as common bean density increased from 25% to 75% in

rice/common bean intercropping. With regard to cropping system, sole maize (11682 kg ha -1 ) was

significantly superior (P<0.05) than the intercropped maize (6507 kg ha -1 ) (Table 9). This could

be due to less competition between the component crops. This result is in line with Siddig et al.

(2013), who reported that dry matter weight of sorghum was negatively influenced due to

sorghum-ground nut intercropping.

Grain Yield (kg ha -1 )

Grain yield of maize was highly significantly (p<0.01) affected by planting density and cowpea

varieties as well as their interaction while cropping system was significant (p<0.05) (Appendix

Table 3).The highest maize yield (3184 kg ha -1 ) was obtained from the combinations of maize x

50% plant population of cowpea variety kenketi while the lowest grain yield (1271 kg ha -1 ) was

obtained from combination of maize x 100% plant population of cowpea variety Bole (Table 8).

The highest grain yield of maize from 50% population of cowpea variety Kenketi might be due to

reduction in competition for growth resources and early maturity of the intercropped cowpea

43

variety. This result was in conformity with that of Rao (1980) who reported that early maturing

legume varieties could lead to increased productivity of the cereal component. The yield reduction

due to 100% population of variety Bole might be due to its late maturity. In line with this result,

Davis and Garcia (1983) reported that maize yield was reduced by 17% when intercropped with

the most competitive common bean cultivars. With regard to cropping system , sole maize gave

higher yield (3189 kg/ha) than intercropped maize (2210 kg/ha) (Table8).This result in line with

the findings of Tamado and Eshetu (2000), Yesuf (2003) and Dechasa (2005) who reported that

yield of sole cropped sorghum was significantly higher than intercropped sorghum.

Table 8.Interaction effect of the intercropped cowpea varieties and plant populations on grain

yield (kg ha -1 ) of maize.


50% 75% 100%

Cowpea varieties Kenketi 3184 d 3070 d 2262 c

Black eye bean 2338 c 2272 c 1940 bc

Bole 1957 bc 1597 ab 1271 a

Intercrop

Sole crop

Variety x Density

2210 a

3189 b

Cropping system

LSD0.05 225.5 760

CV (%) 5.75 17.62




44

Harvest Index (HI %)

The harvest index (HI) is the ratio of grain yield to total aboveground biomass and it indicates the

ability of the crop to allocate biomass (assimilates) into the formed reproductive parts. Harvest

index (HI) was highly significantly (p<0.01) affected by planting density but not by cowpea

varieties, cropping system as well as their interaction (Appendix Table 3).

Table 9.Effects of cowpea densities, varieties and cropping system on number of ears per plant

(NEPP), Thousand kernel weight (TKW (g)), Dry above ground biomass (B (kgha -1 )), Harvest

index (HI (%) of sole and intercropped maize.

Treatments NEPP TKW (g) BM (kg/ha) HI (%)

Cowpea plant

density

50% 1.667 b 207.5 b 8537 b 38.47 a

75% 1.422 a 175.4 a 6341 ab 40.33 ab

100% 1.343 a 162.2 a 4643 a 47.86 b

LSD(P<0.05) 0.1609 23.37 3050 19.18

Cowpea verities

Kenketi 1.533 a 185.1 a 6446 a 41.90 a

Black eye bean 1.444 a 176.3 a 5375 a 46.69 a

Bole 1.444 a 183.8 a 7700 a 44.08 a

LSD(P<0.05) NS NS NS NS

CV% 10.73 12.68 13.68 14.92

Cropping system

Sole maize 1.73 a 209.8 a 11682 a 46.68 a

Intercropped

1.47 b 181.7 a 6507 b 44.22 a

maize

LSD(P<0.05) 0.25 NS 4654 NS

CV% 13.53 16.85 15.2 2.80




45

The highest HI (47.86%) was recorded from maize intercropped with 100% cowpea density where

the lowest HI (38.47%) was recorded from maize intercropped with 50% cowpea density (Table

9). The reduction of HI% at 50% population density might be due to less grain yield and high dry

biomass of maize at 50% population density of cowpea. This result agrees with the finding of

Saleem et al. (2015) on maize-mung bean intercropping. High harvest index indicates the presence

of good partitioning of dry matter to grain yield.

4.3. Effect of intercropping of maize with different population density and

varieties of cowpea on yield and yield components of cowpea crop

4.3.1. Cowpea Phenology

Days 50% to Flowering

Days to flowering was highly significantly (p<0.01) affected by cowpea varieties while cropping

system, planting density as well as interaction effect was not significant (Appendix Table 4). This

result contradicted with Smith et al. (2001) who reported that days to flowering of pigeon pea

decreases with increasing pigeon pea population when intercropped with maize.

Although days to flowering was not significantly affected due to cropping system, there was a

delay in one day in intercropped treatments compared to sole cowpea. This could probably be due

to shading effect of maize which reduces effective heat unit accumulation, resulting in longer

required growth period. Similarly, Muoneke et al. (2007) and Mpangane et al. (2004) did not find

any significant differences in terms of days to 50% flowering of soybean intercropped with maize

and maize-cowpea intercropping, respectively. Hardley et al. (1983) stated that flowering is

dependent on both genotype and environment.

46

On the other hand cowpea varieties had highly significant (P<0.01) on both days to flowering and

days to physiological maturity duet to verities (Appendix Table 4). The variety Kenketi took

shortest time 54.30 and 78.44 days to reach flowering and maturity respectively while Bole took

longest time, 61.83 and 83.33 days to reach flowering and maturity respectively (Table 10). This

might be due to the difference of their genetic inheritance between this varieties of cowpea. In

agreement with this result, Alemayehu et al. (2018) who reported that highly significance effect

of common bean varieties intercropped with maize on days to flowering and maturity of common

bean. Similarly, Biruk (2007) reported similar result on common bean intercropped with sorghum.

Days to 90% Physiological Maturity

Cowpea physiological maturity was significantly (P<0.05) affected by cropping system (Appendix

Table 4). There was delay of physiological maturity in the case of intercropped (80.74 days) than

sole cropped (78.44 days) of all cowpea varieties which might be due to inter specific competition

for water and other growth factors (Table 10). This finding is in line with the report of Thobatsi

(2009) who reported that significance effect of cropping system on maturity of cowpea varieties

on maize/cowpea intercropping.

Unlike cropping system, cowpea planting density and interaction (density and variety) effect did

not significantly (P>0.05) affected the days to cowpea physiological maturity (Appendix Table 4).

The crops reached their physiological maturity with in mean days of 80.89 days for 50% and 81.00

days for 100% population of cowpea (Table 10).

47


cowpea with maize.

Treatments Days to 50% flowering Days to 90% maturity


50% 58.56 a 80.89 a

75% 57.67 a 80.33 a

100% 56.78 a 81.00 a

LSD(P<0.05) NS NS

Cowpea verities

Kenketi 54.30 a 78.44 a

Black eye bean 56.57 b 80.44 b

Bole 61.83 c 83.33 c

LSD(P<0.05) 1.404 1.417

CV% 2.73 1.77

Cropping system


Intercropped maize 57.67 a 80.74 b

LSD(P<0.05) NS 1.83

CV% 6.35 2.91




Similar to this current finding, Eyob (2007) reported non significance effect of faba-bean planting

densities on 90% physiological maturity of faba bean in sorgum/faba bean intercropping. This

result contradicts with the finding of Alemayehu et al. (2018) who reported significance effect on

physiological maturity of common bean due to planting density of common bean varieties in

maize/common bean intercropping.

48

4.3.2. Effect on Growth parameters of cowpea

Plant height (cm)

The result of this study indicated that Cowpea variety, planting density and their interaction had a

highly significant (P<0.01) effect on plant height of cowpea (Appendix Table 5). The longest

plants t (40.50 cm) were recorded from cowpea variety Bole at 100% planting density whereas the

shortest (36.13cm) were recorded from Kenketi at 50% population density therefore the height

was significantly increased as planting density of cowpea was increased( Table 11). The raise in

plant height of cowpea with increase in planting density of cowpea might be due to increased

competition for growth resources such as radiation, soil moisture and nutrients with increased

population of the intercropping system which makes the stem of the plant weak. Similar result was

reported by Mitiku and Getachew (2017) who found that the height of common bean was highly

significantly affected by planting density and varieties of common bean intercropped with rice.

However, Biruk (2007) found that planting density of common bean was not significantly affected

the height of common bean intercropped with sorghum.

Plant height of cowpea was also significantly affected (P<0.05) by the cropping system (Appendix

Table 5). The intercropping of cowpea with maize resulted in an increase of cowpea plant height

by about 2.16 cm compared to its pure stand. Competition for light under intercropping could have

induced taller plants at the different cropping pattern compared to sole cropping of cowpea.

Muoneke et al. (2007) and Ennin et al. (2002) were also reported that increased soybean plant

height under intercrop with maize in maize/soybean intercropping.

49

Table 11.Interaction effect of the intercropped cowpea varieties and plant populations on height

of cowpea in maize/cowpea intercropping.


Cowpea varieties

50% 75% 100%

Kenketi 36.13 ab 36.67 abc 36.80 abc

Black eye bean 36.80 abc 36.80 abc 38.07 bc

Bole 35.23 a 38.70 cd 40.50 d

Intercrop

Sole crop

Variety x Density

Cropping system

37.30 a

35.14 b

LSD0.05 1.205 1.735

CV (%) 1.89 6.02



different at 5% level of significance according to LSD test

According to Keating and Carberry (1993) increased plant height of the lower component is typical

responses in the intercrop due to increase far: red ratio what is this intercepted at the lower levels

of the intercrop canopy. Similarly, Carr et al. (1995) found intercropping wheat and lentil increased

lentil plant height in intercrop compared to its monocrop.

Number of branches per plant

The ANOVA result showed that the number of branches per plant was not significantly (p>0.05)

affected by neither population density of cowpea nor the interaction of population density and

varieties of cowpea as well as cropping system (Appendix Table 5). In spite of this finding, Daniel

50

(2006) reported lower number of branches per plant of soybean at the higher plant density. Though

this parameter was not statically significant due to cropping system, the number of branches in

sole was greater (5) than that of intercropping (4.737) of all cowpea varieties. This result is in line

with finding of Agete (2008) on sorghum/forage legume intercropping who reported that the

number of branch per plant was not significantly (p>0.05) affected due to cropping system.

Unlike density and cropping system, number of branches per plant was significantly (p<0.05)

affected by cowpea varieties (Appendix Table 5). The highest number of branches per plant (5.433)

was recorded from Kenketi variety while and the lowest (4.333) was recorded from Bole variety,

however the number of branches per plant from Bole (4.333) and Black eye bean (4.444) varieties

was statically similar (Table 11) . This difference observed on number of branches per plant could

be due to the inherent characteristics or genetic makeup of the varieties. Similar result was reported

by Zerihun (2011) on maize/soybean intercropping who found that number of primary branches

per plant showed significant variation due to effect of soybean varieties and integrated N fertilizer

application.

Leaf Area (cm 2 )

Leaf area was highly significantly (p<0.01) affected by cowpea varieties while the effects of plant

densities and cropping system as well as their interaction did not significantly (p>0.05) affect the

trait (Appendix Table 5). The highest leaf area (60.28 cm 2 ) was recorded from Kenketi variety

while the lowest (35.72 cm 2 ) was recorded from Bole (Table 12). The variation in leaf area

observed due to varieties might be due to the difference in inherent characters of the varieties.

Correspondingly, Mitiku & Getachew (2017) reported significant variation on leaf area of common

been in rice/common bean intercropping due to common bean varieties.

51

Table 12.Effects of component densities and varieties of cowpea on number of branches per

plant (NBPP) and leaf area (LA) of sole and intercropped cowpea.

Treatments NBPP LA (cm 2 )


50% 4.711 a 49.44 a

75% 4.800 a 49.01 a

100% 4.700 a 48.80 a

LSD(P<0.05) NS NS

Cowpea verities

Kenketi 5.433 b 60.28 b

Black eye bean 4.444 a 51.24 b

Bole 4.333 a 35.72 a

LSD(P<0.05) 0.30 16.60

CV% 6.41 19.47

Cropping system


Intercropped maize 4.737 a 49.08 a

LSD(P<0.05) NS NS

CV% 12.78 18.92




Moreover, Biruk (2007) reported that leaf area of common bean on sorghum-common bean

intercropping had been differently affected by neither of the common bean planting density nor

cropping system and the interaction effect. Generally higher leaf area is very important

determinant of biomass productivity.

52

4.3.3. Effect on yield and yield related parameters of cowpea

Number of pods per plant

The analysis of variance showed that number of pods per plant were highly significantly (P˂0.01)

affected by cowpea densities and varieties but not their interaction (Appendix Table 6). It was also

significantly (P˂0.05) affected by cropping system. The highest number of pods per plant (13.67)

was recorded from 50% cowpea population while the lowest number of pods per plant (10.78) was

obtained from 100% cowpea population though it was not statically different from 75% cowpea

population (Table 14). The decrease in number of pods per plant at higher plant density might be

due to increased inter and intraspecific competition for growth resources, which might have led to

reduced number of effective branches. The higher pods per plant at 50% cowpea population might

also be due to the lower cowpea population and the lower maize competition due to the greater

distance between cowpea plants that might have provided a better soil resource condition with

higher light availability for cowpea plants. This result was in agreement with Biruk (2007) who

reported decreased number of pods per plant in sorghum/common bean intercropping as an

increase in planting density. Similarly, Luiz and Robert (2003) reported that increasing bean

population in maize/bean intercropping, significantly decreased the number of pods per bean plant.

With regards to variety, the highest number of pods per plant (14.89) was obtained for variety

Kenketi while variety Black eye bean had the lowest (10.67) though it was not significantly

different from Bole (Table 14). Alemayehu et al. (2018) reported significant difference among the

intercropped common bean varieties on number of pod per plant in maize/common bean

intercropping. This could be probably the genetic difference among the different varieties of

cowpea.

53

Significantly higher number of pods per cowpea plant (14.33) was obtained from sole than

intercropped cowpea (12.37) (Table 14). The decrease in number of pods per plant might be due

to the competition effect of maize component. Carruthers et al. (2000) related this situation to the

reduction of photosynthesis due to shading of associated crops to a level that the legume plants

compensated by decreasing the amount of assimilate allocation to reproductive growth or grain

production. In line with this result, Teshome et al. (2015) reported significantly high number pod

per plant for sole crop compared with intercropped soybean in maize/soybean intercropping.

Number of seeds per pod

Number of seeds per pod was significantly (p<0.05) affected by cowpea variety while plant

density, cropping system and interaction effects did not significantly (p>0.05) affect the trait

(Appendix Table 6).The highest number of seeds per pod (16.50) was recorded from Kenketi

variety while the lowest (11.89) was recorded from Bole variety(Table 14). The variation in

number of seed per pod observed due to varieties might be due to the difference in inherent

characters of the varieties. The same result was reported by Mitiku and Getachew (2017) who

found highly significant effect of common bean varieties on number of seed per pod of common

bean varieties in rice/common bean intercropping. However, Teshome et al. (2015) on

maize/soybean found non-significant effect of soybean varieties on number of seeds per pod of

soybean varieties. Moreover Sisay (2004) on sorghum/green gram intercropping and Dechasa

(2005) on sorghum/bean intercropping reported non-significant effect on number of seeds per pod

of the legume components due to planting density of the legume crop. Biruk (2007) also found on

sorghum-common bean that seed pod -1 of common bean did not vary significantly in terms of

cropping system.

54

Hundred Seed Weight (g)

Hundred seed weight of the associated cowpea was highly significantly (P<0.01) affected by

cowpea variety while plant density, interaction (density and variety) and cropping systems, showed

non-significant (Appendix Table 6) effect on this trait. The highest hundred seed weight (24.79 g)

was recorded from variety Black eye bean while the lowest seed weight was recorded from variety

Kenketi (15.24 g) (Table 14). With regard to planting density, though it showed non significance

effect on the parameter but 50% plant density recorded highest (18.73 g) seed weight due to less

computation.

The variation in seed weight for varieties could be due to the genetic differences among the

varieties. This result was in agreement with the result reported by Biruk (2007) where the hundred

seed weight was significantly (P<0.05) different between common bean varieties under

sorghum/common bean and maize/ common bean intercropping respectively. Similarly, Zerihun

(2011) reported that thousand seed weight of soybean was significantly different under

maize/soybean intercropping due to soybean variety.

Above Ground Biomass (kg ha -1 )

Aboveground dry biomass (kg/ha) was highly significantly (P<0.01) affected by the varieties and

planting densities of cowpea but their interaction and cropping system were non-significant

(Appendix Table 6). The highest aboveground dry biomass (4925 kg ha -1 ) was recorded from

variety Kenketi while the lowest (4116 kg ha -1 ) was recorded from variety Bole (Table 14). With

regard to the planting density, the highest aboveground dry biomass (4940 kg ha -1 ) was recorded

at cowpea planting density of 100% and it was decreased significantly with the decrease in planting

55

density of cowpea to 50%. This decrease might be decrease in population of cowpea in the

intercropping system. In agreement with this result, Sisay (2004) recorded the highest above

ground dry biomass from 100% green gram intercropped with sorghum. Similarly, intercropping

of full density of barley with five planting densities of faba bean (100:12.5%, 100:25%,

100:37.5%, 100:50% and 100:62.5%) showed significant increment on dry biomass yield of

intercropped faba bean from 653 kg/ha to 2494 kg/ha as plant density of faba bean increased from

12.5% to 62.5% (Getachew et al., 2006). Moreover though the difference was not statistically

significant (p>0.05) due to cropping system, sole cowpea gave higher aboveground dry biomass

(4779 kg ha -1 ) than the intercrop (4442 kg ha -1 ). The increment in dry biomass production of sole

cropped cowpea was attributed to absence of competition and thus, more dry matter accumulation

in stem, branches and leaves matter as a result of its good vegetative cover to harvest ample solar

radiation important for its photosynthesis.

Grain Yield of Cowpea (kg ha -1 )

Cowpea varieties and planting density highly significant (P<0.01) affect the grain yield of the

intercropped cowpea where their interaction revealed significant (p<0.05) effect (Appendix Table

6). The highest grain yield (2298 kg ha -1 ) was recorded for cowpea variety Kenketi at planting

density of 100% while the lowest grain yield (696 kg ha -1 ) was recorded for cowpea variety Bole

at 50% planting density (Table 13). In general variety Kenketi gave higher grain yield than the

other varieties as it had the highest number of branches and number of pods per plant. Moreover,

the grain yield of cowpea was increased as the planting density increased which might be due to

the increased population. In agreement with this result, Sisay (2004) reported the highest seed yield

of green gram when it was intercropped with sorghum with full rate and the lowest seed yields of

green gram from intercrop combinations containing 20% and 40% populations of green gram.

56

There was also significant difference (P<0.05) on grain yield due to the cropping system. Sole

cropped cowpea had significantly higher grain yield (1940 kg ha -1 ) than the intercropped system

(1459 kg ha -1 ) (Table 13). The grain yield reduction of the intercropped cowpea could be due to

shading effect of the maize crop on cowpea during the different growth stage and inter-specific

competition. In consistence with this result, Muoneke et al. (2007) reported similar yield reduction

in soybean inter cropped with maize and sorghum and attributed the yield depression to inter

specific competition.

Table 13. Interaction effect of the intercropped cowpea varieties and plant populations on grain

yield of cowpea in maize/cowpea intercropping.

Cowpea varieties

Cowpea density

Kenketi Black eye

bean

Bole

50% 931 b 784 a 696 a

75% 2086 cd 1404 b 1408 b

100% 2298 d 1778 bc 1745 bc

Intercrop

Sole crop

Variety x Density

Cropping system

1459 b

1940 a

LSD0.05 213.0 404.3

CV (%) 7.79 3.26




57

Harvest Index (%)

Harvest index of cowpea was highly significantly (P<0.01) affected by plant population density of

cowpea but not their interaction while cropping system and cowpea varieties shows significant

(p<0.05) effect (Appendix Table 6). The highest HI percentage (41.30%) was recorded on sole

cropped while the lowest (32.16%) was from intercropped cowpea (Table 14). The reason for high

percentage of HI in sole cowpea could be due to partitioning of more dry matter to seed yield.

Correspondingly, Saleem et al. (2015) on maize-mungbean intercropping reported that HI of

mungbean significantly varied due to cropping system where sole mungbean comprised higher HI

than the intercrop. Generally, improved HI represents increased physiological capacity to mobilize

photosynthates and translocate them into organs having economic yield. This is, therefore, a fact

that the economic yield of a cropping system is determined by the harvest index (HI) (ratio of grain

yield to above ground biomass). The higher the HI is, the higher the dry matter conversion

efficiency (Karanja et al., 2014).

With regard to cowpea varieties, the highest cowpea harvest index (35.34%) was obtained from

cowpea variety Kenketi and the lowest cowpea harvest index (30.52%) was obtained from cowpea

variety Black eye bean (Table 14). The highest Harvest index recorded for variety Kenketi, might

be due to the high grain yield to biomass obtained by the variety as a result of high partitioning of

dry matter to the grain. With regards to the planting density, the highest harvest index (39.27%)

was recorded at cowpea planting density of 100% and the lowest (20.41%) was recorded at cowpea

planting density of 50% (Table 14). The increment of harvest index with cowpea population

density is attributed to the higher grain yield at higher population. This result is in conformity with

Teshome et al. (2015) who reported highest harvest index at highest soybean population density

in maize/soybean intercropping.

58

Table 14.Effects of component densities and varieties of cowpea on number of pods per plant

(NPPP), number of seed per pod (NSPP) ,aboveground dry biomass (AGBB) and harvest index

(HI) of sole and intercropped cowpea.

Treatments NPPP NSPP HSW (g) ABGM (kg

ha -1 )

Cowpea plant

density

HI (%)

50% 13.67 b 14.49 a 18.73 a 3974 a 20.41 a

75% 12.67 b 14.24 a 19.12 a 4413 b 36.80 b

100% 10.78 a 14.02 a 18.32 a 4940 c 39.27 b

LSD(P<0.05) 8866 NS NS 235.0 6.3

Cowpea verities

Kenketi 14.89 b 16.50 c 15.24 a 4925 b 35.34 b

Black eye bean 10.67 a 14.37 b 24.79 c 4286 a 30.52 a

Bole 11.56 a 11.89 a 17.63 b 4116 a 33.62 a

LSD(P<0.05) 1.54 0.94 0.95 407.1 3.61

CV% 6.90 6.63 11.39 5.20 10.50

Cropping system

Sole maize 14.33 a 13.94 a 19.93 a 4779 a 41.30 a

Intercropped 12.37 b 14.25 a 18.87 a 4442 a 32.16 b

maize

LSD(P<0.05) 1.799 NS NS NS 7.16

CV% 17.85 16.70 17.2 14.26 17.16




4.4 Land Equivalent Ratio

The cowpea plant density and varieties as well as their interaction had highly significant (p<0.01)

effect on total land equivalent ratio (Table 15). The highest total LER (1.478) was recorded when

100% cowpea, variety Kenketi was intercropped with maize whereas the lowest LER (1.027) was

recorded when 50% cowpea Bole variety intercropped with maize.

59

Tauro et al. (2013) showed that when the LER > 1, intercropping is advantageous because

environmental resources are used more efficiently for plants growth and LER < 1, there is

disadvantage as environmental resources utilized less efficiently. Moreover, yield advantages have

been recorded in many legume-cereal intercropping systems, including soybean-sorghum (Hayder

et al., 2003), maize-mungbean (Saleem et al., 2015) and cowpea-maize (Eskandari and Ghanbari,

2010). The reason of yield advantages of intercropping are mainly that environmental resources

such as water, light and nutrients can be utilized more efficiently in intercropping than in the

respective sole cropping systems (Liu et al., 2006). Intercropping also gives higher yield advantage

when total population in the system is higher than that of sole crops (Willey, 1979b).

Table 15.Cowpea varieties, plant density and their interaction effects on total LER of

intercropped maize and cowpea.

Cowpea varieties

Cowpea density

Kenketi Black eye

bean

Bole

50% 1.347 b 1.075 a 1.027 a

75% 1.419 bc 1.310 b 1.327 b

Intercrop mean

100% 1.478 c 1.361 bc 1.378 bc

1.302

LSD0.05 0.06596

CV (%) 2.93

Variety x Density




60

The data for LER (1.302) in Table 14 showed that intercropping gave 30% advantage in efficiently

utilizing land than planting the crops sole. The sole cropping of either maize or cowpea would

require 0.30 more unit of land to get the same yield obtained from the intercropping system. This

result agreed with the report of Chemeda (2003) who found up to 28% higher total productivity

increase of maize-bean intercropping compared with pure stand. Likewise, Getachew et al. (2013)

also reported that intercropping gave a 45%, 29%, and 21% yield advantages than planting sole

crops on maize-forage legumes (vetch and lablab) intercropping system. These values were

achieved when vetch was row-sown at 50% seed rate of its sole followed by vetch broadcast at the

same rate and lablab broadcast at 75% seed rate of its sole.

4.5. Economic Analysis

In economic analysis the 13 treatments were tested, 10 treatments were dominated and excluded

from the marginal analysis (Table 16).

Table 16.Dominance analysis of the treatment combinations

Treatment

TVC Net benefit Dominance analysis

combinations

SOLE-kenketi 2300 44226.7 Dominated

SOLE-Black 2300 34325.2 Dominated

SOLE-Bole 2300 38761.9 Dominated

SLOE-M 4500 64425.16 Dominated

M+Kenketi-50% 5500 45296.67 Dominated

M+Bole-50% 5500 28693.32 Dominated

M+Black-50% 5500 35986.97 Dominated

M+Kenketi-75% 5800 67779.31 Non-dominated

M+Bole 75% 5800 39153.69 Dominated

M+Black-75% 5800 49550.47 Dominated

M+Kenketi-100% 6100 69264.81 Non-dominated

M+Bole-100% 6100 31172.7 Dominated

M+Black-100% 6100 69264.81 Non-dominated

61

The highest net benefit (69,264.81 Birr/ha) were obtained from combination of maize with 100%

population density of cowpea, variety Kenketi followed by maize intercropped with 75%

population density of the same variety (67779.31 Birr/ha) and combination of maize with 100% of

cowpea black eye bean variety (66823.49 Birr/ha)(Table 17).

The highest net benefit (69264.81) was obtained from combination of maize with 100% population

density of cowpea, kenketi variety and suggests that for each ETB invested in maize production

by intercropping with cowpea, Kenketi variety at 100% plant density, the producer will get ETB

4.95 after recovering the investment.

Table 17.The marginal rate of return of maize, cowpea varieties and plant density combinations.

Non dominated

Treatments Incremental cost (Birr/ha) incremental benefits (Birr/ha) (MRR %)

Maize+ Kenketi100% 6100 69264.81 4.95

Maize + Kenketi 75% 5800 67779.31 3.18

Maize + Black 100% 6100 66823.49

62

5.1 Conclusions

CHAPTER 5. CONCLUSION AND

RECOMMENDATION

Intercropping is an important option for efficient utilization of resource especially under gradually

decreasing cultivated land. Even though there is practice of intercropping cereals and legumes in

some of the eastern part of Ethiopia, the practice of intercropping maize with cowpea is not

common in the study area.

Analysis of variance revealed that days to tasseling was significantly affected by cropping system

and population densities of cowpea. Only planting density of cowpea significantly affected the

plant and ear height of maize. The plant density of cowpea also showed significantly affected on

number of ears per plant and thousand kernel weight. The plant density of cowpea and cropping

system also causes significantly effect on above ground dry biomass of maize. Harvest index (HI)

was highly significantly affected by planting density. The plant density of cowpea and varieties as

well as their interaction showed significant effects on grain yield of the maize component.

Days to flowering of cowpea was significantly affected by planting density and cowpea varieties

as well as their interaction. Cowpea physiological maturity was significantly affected by cropping

system. On the other hand cowpea varieties had highly significant on both days to flowering and

days to physiological maturity duet to verities. Number of branch per plant and leaf area was

significantly affected by cowpea varieties. The highest number of branch per plant and leaf area

were recorded from kenketi variety while the lowest number of branch per plant and leaf area was

obtained from Bole variety. Number of pods per plant was significantly affected by cowpea

63

varieties and planting density of cowpea. Number of seeds per pod and hundred seed weight were

significantly affected by cowpea variety. Above ground dry biomass (kg ha -1 ) and Harvest index

were highly significantly affected by the varieties and planting densities of cowpea. Grain yield of

cowpea was significantly affected by associated varieties, plant population and cropping system

as well as their interaction.

According to the result of this study intercropping of cowpea varieties with maize results higher

economic advantage per unit land of area over sole cropping due to the efficient use of growth

resources such as light, water, nutrients etc. Hence, it could be concluded that intercropping maize

with cowpea variety is economically important for the local farmers and it would improve their

livelihood by increasing their income from a given land of area.

5.2 Recommendations

Though the grain yield of sole crops in both component crops recorded higher yield than their

representative intercropping but LER and marginal rate of return showed that intercropping is

advantageous over sole cropping. Therefore, considering the experimental findings intercropping

of maize with 100% cowpea population and Kenketi Variety was recommended for the study area.

However, as this is one field experiment, the experiment has to be repeated over seasons with

consideration of farmer’s preference of the cowpea varieties to reach at conclusive

recommendation.

64

REFERENCES

Abebe Zerehun, Sharma jj.,Dechasa Nigussie and Fred K.(2013).The effect of integrated organic

and in organic fertilitizer rates on the performances of soybean and maize component crops

of a soybean/maize mixture at Bako, Western Ethiopia .African journal of agriculture

research ,8(29),3921-3929.DOI:10.5897/AJAR12.1044.

Adiku, S.G.K., Ozier-Lafontaine, H., Bajazet, T., 2001. Patterns of root growth and water uptake

of a maize-cowpea mixture grown under greenhouse conditions. Plant and Soil 235, 85-94.

Adipala, E., Omongo, C.A., Sabiti, A., Obuo, J.E., Edema, R, Bua, B., Atyang, A., Nsubuga, E.N.

& Ogenga-Latigo, M. W., 1999. Pests and diseases on cowpea in Uganda: Experiences

from a diagnostic survey. African Crop Sci .J. 7(4), 465- 478.

Agbato, S.O. 2000: Principle and practice of Arable crop production,. Odumatt Press, Oyo. Page

1 – 30.

Agete, G., 2008.Intercropping of Forage Legumes with Sorghum in the Central Rift Valley,

Ethiopia. MSc Thesis, Haramaya University, Haramaya, Ethiopia.

Alemayehu D, Shumi D, Afeta T .2018. Effect of Variety and Time of Intercropping of Common

Bean (Phaseolus vulgaris L.) With Maize (Zea mays L.) on Yield Components and Yields

of Associated Crops and Productivity of the System at Mid-Land of Guji, Southern

Ethiopia. Adv Crop Sci Tech 6: 324.

Alemayehu Seyoum Taffesse, Dodos, P. and Sinafikeh Asrat. 2011. Crop Production in Ethiopia:

Regional Patterns and Trends. Development Strategy and Governance Division,

International Food Policy Research Institute, Ethiopia Strategy Support Program II (ESSP

II), Ethiopia. ESSP II Working Paper No. 0016.

65

Altieri, M.A., Glaser, D.L. & Schmidt, L.L., 1990. Diversification of agroecolosystems for insect

pest regulation: experiments with collards. In: S.R. Gliesma (Editor),Agroecology:

Researching the Ecological Basis for Sustainable Agriculture. Springer-Verlag, New York,

pp 70- 82.

Andrews R.W.1979, Intercropping, Its importance and research need I. Competition and yield

advantages. Field Crops Abstr. 32: 1−10.

ATA (Agricultural Transformation Agency). 2013a. Maize Production Manual for Extension Staff

of Ministry of Agriculture, Ethiopia. ATA. Addis Ababa, Ethiopia.

Atilla L, Mahmut Yildiztekin, Said Nadeem And Fatma Yildiztekin,.2015. Effects Of Mono- And

Intercropping On Growth And Boron Uptake Of Wheat Plant (Triticum Aestivum L.)

Cultivated On Boron-Contaminated Media, Pak. J. Bot., 47(4): 1259-1264, 2015.

Ayeni, A.O., Duke, W.B. & Akobundu, I.O., 1984. Weed interference in maize, cowpea and

maize/cowpea intercrop in a sub-humid tropical environment. I. Influence of cropping

season. Weed Res. 24. 269-279.

Ayisi, K.K. & Mposi, M.S., 2001. Grain yield responses and Chilo partellus infestation in diverse

sorghum-cowpea intercrop arrangements. S. Afr. J. Plant Soil.18 (1), 39- 42.

Balasubramaniyan, P. and Plalaniappan, S.P. 2007. Principle and practice of agronomy. 2 nd

Edition. Agrobios ISBN 10. Jodhpur, India.

Barker, E.F.I. & Yusuf, Y., 1976. Research with mixed crops at the Institute for Agricultural

Research, Samaru, Nigeria. Samaru conference paper 10, Institute for Agricultural

Research, Samaru, Ahmadu Bello University, Nigeria.

66

Berhanu Debele.1980. The physical criteria and their rating proposed for land evaluation in the

highland region of Ethiopia. Land use planning and regulatory department,Ministry of

Agriculture. Addis Ababa, Ethiopia.

Biruk Tesfaye.2007.Effcet of planting density and common bean(phaseolus vulgaris

L.)Intercropped with sorghum (sorghum bicolor) on the performance of the component

crops and productivity of the system in south Gondar Ethiopia.MSC Thesis, Haramaya

University,Haramaya,Ethiopia.

Caldwell, M.M., 1987. Plant architecture and resource competition. Ecol. Studies. 61, 164- 179.

Carberry, P.S., Adiku, S.G.K., McCown, R.L., Keating, B.A.,1996. Application of the APSIM

cropping systems model to intercropping systems. In: Ito, O., Johansen, C., Adu-Gyamfi,

J.J., Katayama, K., Kumar Rao, J.V.D.K., Rego, T.J. (Eds.), Roots and nitrogen in cropping

systems of the semi-arid tropics. International Crops Research Institute for the Semi-Arid

Tropics.

Carr, P. M., Gardner, J. C., Schatz, B. J., Zullnger, S. W., Guldan, J.1995. Grain Yield and Biomass

of a Wheat – Lentil Intercrop. Agron. J. 87: 547 – 579.

Carruthers K, Prithiviraj B, Cloutier D, Fe Q, Martin RC, et al.2000. Intercropping of corn with

Soybean, Lupine and forages: Silage yield and quality. European Journal of Agronomy 12:

103-115.

Chandrase, K.B., Annadurai, K. and Somasun, D.E. 2010. Text book of agronomy. New Age

International (p) Ltd, New Delhi, India.

Charles H.,Godfray,John R.,Ian R.,Haddad,L.,Lawrence,D.,James F.,Pretty ,J.,Robinson,Sh.,

Sand M.Thomas and Toulmin,C( January 28,2016) Science 327pp,812-818.

67

Chemeda F, 1996, Effect of bean and maize intercropping on bean common bacteria blight and

rust diseases. Int. J. Pest Manag. 42(1):51−54.

Chemeda F, 1997, Effects of planting pattern, relative planting date and intra-row spacing on a

haricot bean/maize intercrop. Afr. Crop Sci. J. 5(1):15−22.

Chemeda Fininsa. 2003. Relationship between bacterial blight severity and bean yield loss in pure

stand and bean-maize intercropping systems. International Journal of pest management,

49(3): 177-185.

Chowdhury, M.A.H. and Hassan, M.S. 2013. Handbook of Agricultural Technology.Bangladesh

Agricultural Research Council, Farmgate, Dhaka, Bangladesh.

CIMMYT.1988: Annual Report. Mexico City: CIMMYT.

Climate Change Research Programme (CCRP).2009.Report Series No. 7

CORRE-HELLOU, G., and Y. CROZAT. 2007. Competition for soil N between species in cereal-legume

intercropping systems and the role of below ground characteristics on competition. In

SUSVAR Workshop Sustainable lowinput cereal production: required varietal

characteristics and crop diversity, 29 May-1 June, Velence, Hungary. (Com. Orale).

Craufard P.Q, 2000, Effect of plant density on the yield of sorghum-cowpea and pearl milletcowpea

intercrops in northern Nigeria. Exp. Agric. 36(3):379−395.

CRAWLEY, M.J., 1989. Insect herbivores and plant population dynamics. Ann. Rev. Entomol.

34, 531- 564.Agric Bull. 32. Cornell University, Ithaca, NY.

CSA (Central Statistical Agency). 2015. Agricultural Sample Survey 2014/2015 (2007 E.C.). Vol-

I. Report on Area and Production of Major Crops. Statistical Bulletin-278. Addis Ababa,

Ethiopia.

68

CSA (Central Statistical Agency).2018. Agricultural Sample Survey 2017/2018: Report on area

and production of major crops (private, peasant holdings, 'Meher' season).Statistical

Bulletin. Vol.1, Addis Ababa: CSA.

CSA (Central Statistical Authority), 2002. Reports on socioeconomic characteristics of the

population in agricultural households, land use area and production of crops farm

management practices, livestock and farm implements. Addis Abeba, Ethiopia. 615p.

Dahmardeh M, Ghanbari A., Syahsar B.A and Ramrodi M., 2010, The role of intercropping maize

(Zea mays L.) and Cowpea (Vigna unguiculata L.) on yield and soil chemical properties.

African J. Agric. Res. 5(8):631−636.

DALAL, R.C., 1974. Effects of intercropping maize with pigeon peas on grain yield and nutrient

uptake. Exp. Agric. 10, 219- 224.

Daniel Markos, (2006). Effect of Planting Pattern and Plant Density on Agronomic Performance

of Soybean (Glycine max L.)Varieties on Andosols of Rift Valley in Southern

Ethiopia M.sc Thesis.Haramaya University, Haramaya, Ethiopia.

Davis, J.H.C., Garcia, S. (1983). Competitive ability and growth habit of indeterminate beans and

maize for intercropping. Field Crops Research 6: 59-75.

Dechasa Hirpha (2005). Effect of moisture conservation methods and plant density of component

crops on performance of sorghum/bean intercropping in Meiso district, west Hararghe.

M.Sc. Thesis, Haramaya University, Ethiopia.

Demeke, M. 2012. Analysis of incentives and disincentives for maize in Ethiopia. Technical notes

series, MAFAP, FAO, Rome.

69

Demessew Mengesha,2002. Effect of planting density of common bean and nitrogen fertilizer on

productivity of maize haricot bean additive intercropping system. Msc. Thesis, Alemaya

University.

Devereux, S. 2006. Vulnerable livelihoods in Somali Region, Ethiopia. IDS Research Report 57.

Brighton: Institute of Development Studies.

Dewis, J and P. Freitas. 1975. Physical and chemical methods of soil and water analysis.FAO bul.

No. 10, Rome. P 275.

DiTomaso, J. M., Van Steenwyk, R. A., Nowierski, R. M., Vollmer, J. L., Lane, E., Chilton,

E.,Dionigi, C. P.2017. Enhancing the effectiveness of biological control programs of

invasive species through a morecomprehensive pest management approach. Pest

Management Science, 73(1), 9-13. https://doi.org/10.1002/ps.4347.

Drinkwater, T.W., Bate, R., Du Toit, H.A. & Van Den Berg, J., 2002. A field guide for

identification of maize pests in South Africa. Agricultural Research Council.

Potchefstroom.

Edema, R., 1995. Investigations into factors affecting disease occurrence and farmer control

strategies on cowpea in Uganda. MSc. Thesis, Makerere University, Kampala. pp 100.

Ennin, S. A., Clegg, M. D., and Francis, C. A. (2002). Resource Utilization in Soybean/Maize

Intercrops. African Crop Science Journal, Vol. 10. No. 3, 2002, pp. 251-261.

Eskandari, H., A. Ghanbari.2010. Environmental resource consumption in wheat and bean

intercropping: Comparison of nutrient uptake and light interception. Notulae Scientia

Biologicae, 2(3):100-103.

Evans, L.T. & Wardlaw, I.F., 1976. Aspects of the comparative physiology of grain yield in

cereals. Adv. Agron. 28, 301- 359.

70

Eyob Kahsay. (2007). Effect of sorghum plant density and nitrogen rates on productivity of faba

bean(vicia faba L.)/sorghum(sorghum bicolor L.moench) intercropping system at wukro

maray,Central zone of tigray Ethiopia.MSC Thesis ,Hramaya University ,Haramaya,

Ethiopia.

Ezumah, H.C., Nguyen K.Y.N. & Walker, P., 1987. Maize-cowpea intercropping as affected by

nitrogen fertilization. Agron. J. 79, 275- 280.

FAO .1976. A Framework for Land Evaluation. FAO Soils Bulletin 52, FAO, Rome, 79p.

[Outlines the basic principles of the FAO approach to land evaluation and land use

planning].

FAO. 2002: Conservation agriculture:case studies in Latin America and Africa/ Agricultura de

Conservación: estudiosde caso en América Latina y África. SoilsBulletin No. 78. Rome.

FAO.2008: World Bank Country Memorandum for Ethiopia; Central Statistical Agency.

Fatokun, A.C., 2002. Breeding Cowpea for Resistance to Insects Pests, Attempted Crosses

between Cowpea and Vigna vexillata. In: Challenges and Opportunities for

Enhancing Sustainable Cowpea Production, Fatokun, C.A., S.A. Tarawali, B.B.

Singh, P.M. Kormawa and M. Tamo (Eds.). International Institute for Tropical

Agriculture (IITA) Ibadan, Nigeria, pp: 52-61.

Fininsa, C. and J. Yuen, 2001. Association of bean rust and common bacterial blight epidemics

with cropping systems in Hararghe highlands, eastern Ethiopia. Intl. J. Pest mgt. , 47 (3):

211-219.

Flett, B.C., Bensch, M.J., Smit, E., Fourie, H., 1996. A field guide for identification of maize

diseases in South Africa. Agricultural Research Council. Potchefstroom.

71

Florentine, S.K. & Fox, J.E.D., 2003. Allelopathic effects of Eucalyptus species and grasses.

Allelopathy J. 11. 77-78.

Fortin, M.C. & Pierce, F.J., 1996. Leaf azimuth in strip-intercropped corn. Agron. J.88, 6-9.

Gabatshele, M. L., Teko, K. M., and Witness, M. Effects of intercropping on the performance of

maize and cowpeas in Botswana. International Journal of Agriculture and Forestry 2 [6]:

307-310.

Gebremedhin, B, Fernandez-Rivera, S., Hassena, M., Mwangi, W., Ahmed, S. 2007. Maize and

Livestock: Their inter-linked roles in meeting human needs in Ethiopia.

Getachew Agegnehu, Amare Ghizaw and Woldeyesus Sinebo.2006. Yield performance and landuse

efficiency of barley and faba bean mixed cropping in Ethiopian highlands. European

Journal of Agronomy, 25: 202–207.

Getachew Bekele, Ketema Belete and Sharma, J.J. 2013. System Productivity of Forage Legumes

Intercropped with Maize and Performance of the Component Crops in Kombolcha, Eastern

Ethiopia. East African Journal of Sciences, 7 (2): 99-108.

Gianessi, L. P., & Reigner, N. P. 2007. The value of herbicides in US crop production. Weed

Technology, 21(2),559-566. https://doi.org/10.1614/WT-06-130.1.

Gilbert, N., 2012. Dirt poor: the key to tackling hunger in Africa is enriching its soil. The big

debate is about how to do it. Nature 483, 525–527.

Gomez, K.A. and A.A. Gomez, 1984. Statistical procedures for agricultural research (2 ed.). John

wiley and sons, NewYork, 680p.

Goudriaan, J., 1982. Potential production process. In: F.W.T. Penningde Vries and H.H. van Laar

(Eds), Simulation of Plant Growth and Crop Production. Pudoc,Wageningen, pp. 98- 113.

72

Gözübenli, H. 2010. Influence of planting patterns and plant density on the performance of maize

hybrids in the Eastern Mediterranean conditions. International Journal of Agriculture and

Biology, 12: 556-560.

Hadley, P., Roberts, E. H., Summerfield, R. J., and Minchin, F. R. 1983. A quantitative Model of

Reproductive Development in Cowpea (Vigna unguiculata (L) Walp) in Relation to

Photoperiod and Temperature, and Implications for Screening Germoplasm. Annals of

Botany 51, 531-543.

Hassan, A.A. 2000. Effect of population density on yield and yield components of eight Egyptian

maize hybrids, Bulletin of Faculty of Agriculture, 51 (1): 1-16.

Hauggaard-Nieson H., Ambus P and Jensen E. S. 2001. Temporal and spatial distribution of roots

and competition for nitrogen in pea-barley intercrops. A field studies employing 23P

techniques. Plant Soil 236:63−74.

Hayder Ghulam, S., Suhail Mumtaz, Aslam Khan, Sherin Khan.2003. Maize and Soybean

Intercropping under Various Levels of Soybean Seed Rates. Asian Journal of Plant

Science, 2(3): 339-341.

Hulugalle, N.R. & Lal, R., 1986. Soil water balance in intercropped maize and cowpea grown in a

typical hydromophic soil in Western Nigeria. Agron. J. 77, 86-90.

IFAD(Food and Agricultural organization of the United Nations),2000.IITA:Applied and adaptive

research on cowpea in semi-arid zones of West Africa .Executive Board-sixty ninth

sessions,Rome,3-4 May,2000.Pp:18-20.

IITA. 1977. Grain Legume Improvement Program Annual Report (p. 78). Ibadan, Nigeria, IITA.

73

IPS (Industrial Project Service), 2002. Resource potential assessments and project identification

study of Somali Region. Vol.3. Agricultural Resources. Industrial Projects Service. No. 09

(137)-91. Addis Ababa. 401p.

Ismail, A. M., & Hall, A. E. 2001. Semi-dwarf and standard-height cowpea responses to row

spacing in different environments. Crop Science, 40(6), 1618-1623.

https://doi.org/10.2135/ cropsci2000.4061618x.

Jayashanker, M., Subramannian, K., Arumugasamy, S.,Saraswathy, H and Vijayalakshmi,

K.2002. Soil conservation in organic farming.CIKS. Chennai. India.

Jeranyama P, Hesterman O.B, Waddington S.R and Harwood R.R, 2000, Relay-Intercropping of

Sunnhemp and Cowpeas into a smallholder maize system in Zimbabwe. Agron. J.

92:239−244.

Jones, R.J., Simmons, S.R. 1986. Effect of altered sourcesink ratio on growth of maize kernels.

Crop Science 23:-134.

Jossias Mateus Materusse Matusso.2011. Effects of Maize (Zea Mays L.) – Soybean (Glycine Max

(L.) Merrill) Intercropping Patterns on Yields And Soil Properties In Two Contrasting Sites

Of Embu And Meru Counties,MSC.Thesis. Kenyatta University.

Kamanga, B.C.G., Waddington, S.R., Robertson, M.J., Giller, K.E., 2010. Risk Analysis of Maize-

Legume Crop Combinations with Smallholder Farmers Varying In Resource Endowment

in Central Malawi. Experimental Agriculture 46, 1-21.

Karanja, S.M., Kibe, A.M., Karogo, P.N. and Mwangi, M. 2014. Effects of Intercrop Population

Density and Row Orientation on Growth and Yields of Sorghum - Cowpea Cropping

Systems in Semi-Arid. Rongai, Kenya, Journal of Agricultural Science; Vol. 6, No. 5.

74

Kariaga,B.M.(2004). Intercropping maize with cowpeas and beans for soil and water management

in western Kenya.proceedings of the 13 th international soil conservation organization

conference,july 2004.conserving water and soil for the society,Brisbane,pp:1-5.

Karikari, S.K.,O.Choba and B.Molosiwa.1999.Effect of intercropping Bambara groundnut on

pearmillet,sorghum and maizein Bostwana .African crop science journal ,7(2):143-152.

Kass, D.C., 1978. Polyculture Cropping Systems: A review and Analysis. Cornell Int.

Keating, B.A. & Carberry, P.S., 1993. Resource capture and use in intercropping: solar radiation.

Field Crops Res. 34, 273- 301.

Kidane Georgis, John H Sanders, Della Macmillan and ELuid O. Omolo. Technologies

2004.Technologies, Policy changes and market Development to increase crop production

in the Semiarid Ethiopia. Igad/IntSOMIL/USAYD-REDSO.

Landon J.R. 1991. Booker tropical soil manual: A hand book for soil survey and agricultural land

evaluation in the tropics and sub tropics. (ed). John W. and Sons I., New York,

USA.

Langham, D.R., 2007. Issues in new crops and new uses. J. Janick and A. Whipkey (eds.) ASHS

Press, Alexandria, VA.

Lavlu Mozumdar.2012.Agricultural productivity and food security in the developing world.

Bangladesh J. Agric. Econs. XXXV, 1&2(2012) 53-69.

Letourneau, D.K., 1990. Two examples of natural enemy augmentation: consequence of crop

diversification. In: S.R. Gliessman (Editor), Agroecology : Researching the ecological

Basis for sustainable Agriculture. Springer-Verlag, NewYork, pp 11- 29.

75

Li L, Sun JH, Zhang FS, Li XL, Yang SC, Rengel Z .2006. Wheat/maize or wheat/soybean strip

intercropping I. Yield advantage and interspecific interactions on nutrients. Field Crop Res. 71:

123-137.

Liebman, M., and E. Dick, 1993. Crop Rotation and Intercropping strategies for weed

management. Journal of the Ecological Society of America, 3(1):92-122.

Lithourgidis A.S., Vasilakoglou I.B., Dhima K.V., Dordas C.A and Yiakoulaki M.D., 2006,

Forage yield and quality of common vetch mixtures with oat and triticale in two seeding

ratios. Field Crop Res. 99: 106−113.

Liu, J.H., Z.H. Zeng, L.X. Jiao, Y.G. Hu, Y. Wang, H. Li. (2006). Intercropping of different silage

maize cultivars and alfalfa. Acta. Agron. Sci. 32:125- 130.

Luiz, B.M., Robert W.W. 2003. Effects of plant population and nitrogen fertilizer on yield and

efficiencyof maizebean intercropping. Pesq agropec bras Brasília 38(11): 1257-1264.

Lulie B, worku W Beyene S.2016. Determinations of Haricot Bean (Phaseolus vulgaris L.) plant

density and spatial arrangement for staggered intercropping with mize(Zea

Mays L) at Wondo Genete, Sourhern Ethiopia. Acad. Res. J. Agri. Sci. Res.

4(6):297-320.

Magashi .Auwal Ibrahim, Musa, Sarkin Fulani, and Muhammad Ibrahim. 2012. Evaluation of

Cowpea Genotypes (Vigna Unguiculata (L.) Walp) for some Yield and Root Parameters

and their Usage in Breeding Programme for Drought Tolerance. MSC Thesis,Kano

University.Nigeria.

Maluleke, M. H., Addo-Bediako, A. & Ayisi, K.K., 2005. Influence of Maize/Lablab Intercropping

on Lepidopterous Stem Borer Infestation in Maize. J. Econ. Entomol. 98(2), 384- 388.

76

Mandal, B,C. 2014. Maize Breeding and Seed Production Manual. Food and Agriculture

Organization of the United Nations. Office of the Food and Agriculture Organization in

DPR Korea.

Marshal B and Willy R.W., 1983, Radiation interception and growth in an intercrop of Pearl

millet/groundnut. Field crops Res., 7:141−160.

Mitiku woldesenbet & Getachew mekonnen 2017. Effects of Common Bean Varieties and

Densities Intercropped with Rice on the Performance of Associated Components in Kaffa

and Benchi Maji Zones, Southwestern Ethiopia.MSC Thesis, Mizan-Tepi University,

Mizan-Tepi, Ethiopia.

MoA (Ministry of Agriculture). 2010. Animal and Plant Health regulatory directorate. Crop variety

register, Issue NO 13. Addis Ababa, Ethiopia.

MoARD (Ministry of Agriculture and Rural Development), 2008. Investment opportunity in

SNNP’s South Omo zone. Addis Ababa

MoARD (Ministry of Agriculture and Rural Development). 2009. Crop Development Department

of Crop Variety Register. Issue No. 10. Addis Ababa, Ethiopia.

Mogues, T., Ayele, G., and Paulos, Z. 2008. The bang for the Birr: public expenditures and rural

welfare in Ethiopia. IFPRI Research Report 160. International Food Policy Research

Institute.Washington, D.C., USA.

Mohr, P., 1971. The Geology of Ethiopia. 2nd ed. Addis Ababa University Press, Addis Ababa,

Ethiopia.

Mpangane, P. N. Z., Ayisi, K. K., Mishiyi, M. G., and Whitebread, A. M. 2004. Grain Yield of

Maize Grown in Sole and Binary Cultures with Cowpea and Lablab in the Limpopo

Province of South Africa. Tropical Legumes for Sustainable Farming Systems in Southern

77

Africa and Australia. Eds: Whitebread, A. M. and Pengelly, B. C. ACIAR Proceeding No.

115.

Munson, R. D. and Nelson, W. L. 1993. Principles and practices in plant analysis; Soil Testing and

Plant Analysis. Soli Science Society of America, 40:223-248.

Muoneke, C.O.,Ogwuche, M.O., Kalu, B.A. 2007. Effect of maize planting Density on the

performance of maize/soybean intercropping system in a guinea savanna agroecosystem.

Afrcan Journal of Agricultural Research 2: 667-677.

NMSA (National Meteorological Service Agency), 2000. National Meteorological Service Addis

Ababa, Ethiopia. 152p.

Nnadi, L.A., and I. Haque, 1986. Forage legume-cereal systems: Improvement of soil fertility and

Agricultural production with special reference to sub-saharan Africa. In Haque L.S. Jutzi

and P.J.H Neate (eds.). Potentials of forage legmes in farming systems of sub-saharan

Africa. Proceedings of a work shop held at ILCA, Addis Ababa, Ethiopia.16-19

September1985.ILCA Addis Ababa.

Nwanze, K.F. & Mueller, R.A.E., 1989. Management options for sorghum stem borers for farmers

in the semi-arid tropics. In international workshop on sorghum stem borers, 17- 20

November 1987. ICRISAT. Patancheru. India. pp 105- 113.

Ofori F and Stern W.R, 1987, Cereal and legume intercropping systems. Advances in Agron.

41:41−90.

Ofori, F., Stern, W.R., 1987. The Combined Effects of Nitrogen-Fertilizer and Density of the

Legume Component on Production Efficiency in a Maize Cowpea Intercrop System. Field

Crops Research 16, 43-52.

78

Ogenga-Latigo, M.W., Ampofo, J.K.O. & Baliddawa, C.W., 1992a. Influence of maize row

spacing on infestation and damage of intercropped beans by the bean aphid (Aphis fabae

Scop.). I. Incidence of aphids. Field Crops Res. 30, 111-122.

Ogenga-Latigo, M.W., Ampofo, J.K.O. & Baliddawa, C.W., 1992b.Influence of maize row

spacing on infestation and damage of intercropped beans by the bean aphid (Aphis fabae

Scop.). II. Reduction in bean yields. Field Crops Res.30, 123- 130.

Olasantan, F.O.E., Lucas, E.O. & Ezumah, H.C., 1994. Effects of intercropping and fertilizer

application on weed control and performance of cassava and maize. Field Crops Res. 39,

63- 69.

Olsen SR, Cole CW, Watanabe FS, and Dean LA. 1954. Estimation of available phosphorus in

soils by extraction with sodium bicarbonate circular. US Department of

Agriculture,Washington.

Padulosi, S., Ng, N., 1997. Origin, taxonomy, and morphology of Vigna unguiculata (L.) Walp.

In: Singh, R., Mohan Raj, D., Dashiell, K., Jackai, L. (Eds.), Advances in Cowpea

Research. International Institute for Tropical Agriculture, Ibadan, Nigeria, pp. 1-12.

Plessis, J. 2003. Maize production hand book. Department of Agriculture Resource Centre

Directorate Agricultural Information Services. Private Bag X144, Pretoria, 0001 South

Africa.

Power, A.G., 1990. Leafhopper response to genetically diverse maize stands. Entomol. Exp. Appl.

49: 213- 219.

Quayyum M.A.,Ahmed A and Chowdhury A.K. 1999, Crop weed competition in maize + black

gram in sole and intercropping system. Bangladesh J. Agril. Res. 24(2): 249−254.

79

Raji, J.A. (2007). Intercropping soybean and maize in a derived savanna ecology. African Journal

of Biotechnology 6(16): 1885-1887.

Rao, M.R., Willey, R.W. 1980. Evaluation of Yield Stability in Intercropping Studies on Sorghum/

Pigeon pea.Experimental Agriculture 16(2):105-116.

Rashid, S.K., Kindie Getnet. and Solomon Lemma. 2010. Maize value chain potential in Ethiopia:

Constraints and opportunities for enhancing the system, IFPRI, Working Paper, Ethiopia.

Reddy, M.S. & Willey, R.W., 1981. Growth and resource use studies in an intercrop of pearl millet/

groundnut. Field Crops Res. 4. 13- 24.

Romain, H. and Raemakers .2001. Crop production in tropical Africa. Directorated

General

for International Co-operation (IDGIC), Ministry of Foreign Affairs, External Trade and

International Co-operation. Brussels, Belgium.

Root, R.B., 1973. Organisation of plant-athropod association in simple and diverse habitats: the

fauna of collards (Brassica oleracea). Ecol. Monogr. 43, 94- 125.

Rusinamhodzi, L., Corbeels, M., Nyamangara, J., Giller, K., 2012. Maize-grain legume

intercropping is an attractive option for ecological intensification that reduces climate risk

for smallholder farmers in central Mozambique. Field Crops Research 136, 12-22.

Sainju, U.M., 2005. Cover crops for sustaining vegetable production, improving soil and water

qualities and controlling weeds and pests. pp. 281-296. In: R. Dris (ed.). Vegetables: Growing

Environment and Mineral Nutrition. WFL Publisher, Helsinki, Finland.

Saleem, R, Z. I. Ahmad, M. A. Anees, A. Razzaq and A. Saleem. 2015. Productivity and land use

efficiency of maize-mungbean intercropping under different fertility treatments. Sarhad

Journal of Agriculture, 31(1): 37-44.

80

Salvador, R.J., Pearce, R.B. 1995. Proposed standard system of nomenclature for maize grain

filling events. Maydica 40: 141-146.

Sangoi, L., Gracietti, M.A, Rampazzo, C. and Bianchetti, P. 2002. Response of Brazillian maize

hybrids from different eras to changes in plant density. Field Crop Research, 79:39-51.

Sharma, N.N., 1994. Response of sesame (Sesamum indicum L.) varieties to levels of nitrogen and

spacing. Annual Agricultural Research, 15: 107-109.

Shen Q.R and Chu G.X., 2004, Bi-directional nitrogen transfer in an intercropping system of

peanut with rice cultivated in aerobic soil. Biol. Fertil. Soils. 40(2):81−87.

Shumba, E.M., Dhilwayo, H.H.

& Mukoko, O.Z., 1990. The potential of maizecowpea

intercropping in low rainfall areas of Zimbabwe. Zim J. Agric. Res. 28, 33-38.

Siame, J., Willey, R.W. & Morse, S., 1998. The response of maize/Phaseolus intercropping to

applied nitrogen on Oxisol in northern Zambia. Field Crops Res. 55, 73-81.

Siddig. A., Mohamed, Ali, Adam. A. Mohamed, Ali. H. Bahar and Abdulmohsin. R. Khairelseed.

(2013). Effects of Sorghum (Sorghum bicolor L.) Moench) and Groundnut (Arachis

hypogaea L.) İntercropping on some soil chemical properties and crop yield under rain-fed

conditions. ARPN Journal of Science and Technology, 3:1.

Sileshi, G.W., Akinnifesi, F.K., Ajayi, O.C., Muys, B., 2011. Integration of legume trees in maizebased

cropping systems improves rain use efficiency and yield stability under rain-fed

agriculture. Agricultural Water Management 98.

Singh, B.B., Chambliss, O.L. & Sharma, B., 1997. Recent advances in cowpea breeding. Pages

39- 40 in Advances in cowpea research, edited by B. B. Singh, D. R. Mohan Raj.

Singh, R.P., Kumar, Ranjit and Singh, N.P. 2002. Transitioning maize seed industry in

India:Sectoral dimensions. Indian Journal of Agricultural Economics, 57 (3): 430-442.

81

Sisay, T., (2004).Effect of planting pattern and proportion of green gram (Vigna radiate (L)

wilczec) on productivity of sorghum/ green gram intercropping system in

Kewet wereda. Amhara Region. MSc Thesis, Haramaya University, Haramaya,

Ethiopia.

Smith, C.J.P., baudoin. And G., Mergeani.2001. Potential of short and medium duration of pigeon

pea as component of cereal intercrop. In: Silim, S.N; Mergeai, G. and P.M.

Kimani (ed). Status and potential of pigeon pea in Estern and Souther

Africa.proceeding of a reginal work shop. Nairobi, Kenya. Pp.98-107.

Sobkowicz, P., 2006. Competition between triticale (Triticosecale Witt.) and field Beans (Vicia

faba var. minor L.) in additive intercrops.Plant Soil Environment 52:47-54.

Stephanie, B. and Brown C. 2008. Field Crop Manual of Maize, First edition. Cambodian

Agricultural Research and Development Institute of Department of Primary Industries,the

State of New South Wales.

Szeicz, G., 1974. Solar radiation for plant growth. J. Appl. Ecol. 11, 617- 636.

Takim F. O. 2012, Advantages of Maize-Cowpea intercropping over sole cropping through

competition indices. J. Agric. Biod. Res., 1(4): 53−59.

Tamado Tana and Eshetu Mulatu 2000. Evaluation of sorghum, maize and common bean

intercropping systems in Eastern Hararghe. Ethiopian Journal of Agricultural Science

17(2):33-46.

Tauro. T.P, J. Adu-Gyamfi, Dhliwayo, D.K..C and Heng, L.K. 2013. Nitrogen and phosphorus

budgets for sorghum and cowpea production under simulated sole- and intercropping

systems in low- and medium-P soils. African Journal of Agricultural Research. Vol. 8(9):

82

727-735, DOI: 10.5897/AJAR11.494. Accessed on Decembre 10, 2014. Research, 8(9):

727-735.

Terao, T.I., Watanabe, R., Matsunagas,Hakoyama. & Singh, B.B.,1997. Agrophysiological

constraints in intercrop cowpea: an analysis. Pages 129-140 in Advances in cowpea

research, edited by B. B. Singh, D. R. Mohan Raj, K. Dashiell and L. E. N. Jackai.

Copublication of International institute of Tropical Agriculture (IITA) and Japan

International Research Center for Agricultural Sciences(JIRCAS). IITA, Ibadan, Nigeria.

Teshome G., Tamado T., Negash G.2015. Effect of Varieties and Population of Intercropped

Soybean with Maize on Yield and Yield components at Haro Sabu, Western Ethiopia. MSC

thesis,Wallega University Nekemte, Ethiopia.

Thobatsi Thobatsi.(2009).Growth and yield responses of maize (Zea mays L.) and cowpea

(Vignaunguiculata L.) an intercropping system.MSC thesis ,university of Pretoria,……..

Tilahun Tadesse .2002. Effects of Planting Arrangement of Component Crops on Productivity of

Maize/Faba Bean Intercropping Systems. MSc. Thesis, Haramaya,University, Ethiopia.

Tokatlis, I.S. and Koutroubas, S.D. 2004. A review of maize hybrids dependence on high plant

populations and its implications for crop yield stability. Field Crop Research, 49: 119-126.

Trenbath, B.R., 1993. Intercropping for the management of pests and diseases. Field Crops Res.

34, 381- 405.

Trudgill, D.L., 1991. Resistance to and tolerance of plant parasitic nematodes in plants. Annu.

Rev. Phytopathol. 29, 167- 192.

Tsubo M, Walker S, Ogindo HO.2005. A simulation model of cereal-legume intercropping

systems for semi-arid regions. Department of Soil, Crop and Climate Sciences, University

of the Free State. Field Crops Res. 93(1).

83

USDA, 2016. United States Department of Agriculture. Foreign Agricultural Service. Circular

series WAP 13-05. www.fas.usda.gov/wap/current/.

Usha, R. and Pandey, B.K. 2007. Origin and introduction of crop plants, cereals, and

pulses.Department of Botany, University of Delhi, India.

Vandermeer, J., 1989. "The Ecology of intercropping". University of Cambridge,Cambridge.

Verdelli, D., Acciaresi, H. A., and Leguizamón, E. S. 2012. Corn and Soybean in a Strip

Intercropping System: Crop Growth Rates, Radiation Interception, and Grain Yield

Components. International Journal of Agronomy. Vol. 2012: 1 – 17.

Vesterager, J., Nielsen, N., Hogh-Jensen, H., 2008. Effects of cropping history and phosphorus

source on yield and nitrogen fixation in sole and intercropped cowpea-maize systems.

Nutrient Cycling in Agroecosystems 80, 61-73.

Watiki, J.M., Fukai, S., Banda, J.A., Keating, B.A., 1993. Radiation Interception and Growth of

Maize/Cowpea Intercrop As Affected By Maize Plant-Density and Cowpea Cultivar. Field

Crops Research 35, 123-133.

Willey, R.W., 1979. Intercropping- its importance and research needs. Part 1: Competition and

yield advantages. Field crop abstract. 32, 1- 10.

Wogayehu Woku.2005. Evaluation of common bean (Phaseolus vulgaris L.) varieties

intercropped with maize (Zea mays L.) for double cropping at Alemaya and Hirna areas,

Eastern Ethiopia. M.Sc.Thesis Presented to Haramaya University. Haramaya, Ethiopia.

Wolfe, M.S., 1985. The current status and prospects of multilane cultivars and variety mixtures

for disease resistance. Annu. Rev. Phytopathol. 23, 251- 273.

www.csun.edu/%7Ehcbio027/biotechnology/lec10/lindemann.html.

84

World Bank, 2001. Pastoral Area Development in Ethiopia. Issues Paper and Project proposal.

Discussion draft, April 10, 2001. Addis Ababa, Ethiopia. pp. 27-49.

Yesuf Mohammed .2003. Effects of Planting Arrangement and Population Densities of Haricot

Bean on Productivity of Sorghum/Haricot Bean Additive Mixture. M.Sc. Thesis.

Haramaya University, Ethiopia.

Yusuf, I. A. Bissallah, G., Aiyelari, E. A., and Audu, P.2012. Evaluation of The Planting Schedule

of Soyabean (Glycine max L. Merril) /Maize (Zea mays) Intercrop Systems for Optimum

Yields in the Guinea Savanna of Nigeria. Continental J. Agricultural Science 6 (3): 50–55.

Zerihun Abebe.2011. System Productivity as Influenced by Integrated Organic and Inorganic

FertilizerApplication in Maize (zea mays l.) Intercropped with Soybean (glycine max l.

merrill) Varieties at Bako, Western Ethiopia. M.Sc.Thesis. Haramaya University, Ethiopia.

ZHANG, F., and LI, L., 2003. Using competitive and facilitative interactions in intercropping

systems enhance crop productivity and nutrient-use efficiency. Plant and Soil 248:305-

312.

Zoufa, K., Tariah, N.M. & Isirimah, M.O., 1992. Effects of groundnut, cowpea and melon on weed

control and yields of intercropped cassava and maize. Field Crops Res. 28, 309- 314.

85

APPENDIXES

Appendix Table 1.Mean square values of ANOVA for phonological parameters of maize as

affected by cowpea density and cowpea varieties.

Mean square

Source of

variation

DF

Days to

tasseling

Days to

maturity

Replication 2 0.481 2.111

Cowpea density 2 7.148* 1.000ns

Cowpea varieties 2 3.370ns 0.444ns

Varietyxdensity 4 1.259ns 0.611ns

Error 16 1.356 2.153

CV% 1.67 1.41

Intercopxsolecrop 1 12.459* 1.200ns

CV% 1.96 1.22

Df =degree of freedom *=significant at 5% probability level (p<0.05) **= highly significant at 1%

probability level (p<0.01) ns=non-significant at p>0.05 level of significance

Appendix Table 2.Mean square values of ANOVA for growth parameters of maize as affected

by cowpea density and cowpea varieties

Mean square

Source of

variation

DF

Plant height

(cm)

Ear height

(cm)


Cowpea density 2 219.693** 62.517**

Cowpea varieties 2 5.747ns 8.774ns

Varietyxdensity 4 2.890ns 4.357ns

Error 16 4.309 2.224

CV% 1.78 3.20

Intercopxsolecrop 1 0.84ns 0.856ns

CV% 4.04 6.43

Df =degree of freedom *=significant at 5% probability level (p<0.05) **= highly significant at 1%

probability level (p<0.01) ns=non-significant at p>0.05 level of significance

86


maize as affected by cowpea density and cowpea varieties.

Mean square

Source of

variation

DF NEPP TKW(g) AGBM(kgha -

1 )

GY(kgha -

1 )

HI%

Replication 2 0.00593 22.92 5274871 34795 82.5

Cowpea density 2 0.02370* 4875.5* 34303195* 1076293** 634.7*

Cowpea varieties 2 0.26815ns 204.1ns 12179173ns 3409058** 51.7ns

Varietyxdensity 4 0.01037ns 1463.1ns 29430568ns 85164** 121.9ns

Error 16 0.02593 547.1 9313478 16969 122.8

CV% 10.73 12.68 13.68 5.75 14.92

Intercopxsolecrop 1 0.18148* 2123.8ns 72299528* 2584791* 16.3

CV% 13.53 16.85 15.2 17.62 2.80

Df =degree of freedom *=significant at 5% probability level(p<0.05) **= highly significant

at 1% probability level(p<0.01) ns=non-significant at p>0.05 level of significance

NEPP=number of ear per plant TKW=thousand kernel weight AGBM=Above ground

biomass GY=Grain yield HI=harvest index

Appendix Table 4.Mean square values of ANOVA for phonological parameters of cowpea as

affected by cowpea density and cowpea varieties.

Mean square

Source of

variation

DF DE50% DF50% DPM90%

Replication 2 0.5833 3.00 0.593

Cowpea density 2 0.0370ns 7.111ns 1.148ns

Cowpea varieties 2 0.2500 ns 170.333** 54.370**

Varietyxdensity 6 0.1389ns 2.852ns 0.704 ns

Error 22 0.2197 2.455 2.009

CV% 10.82 2.73 1.77

Intercopxsolecrop 1 0.5926ns 6.75ns 35.593*

CV% 10.19 6.35 2.91

Df =degree of freedom

DE=days to emergence DF=days to flowering DPM=days to

physiological maturity *=significant at 5% probability level(p<0.05) **= highly significant at 1%

probability level(p<0.01) ns=non-significant at p>0.05 level of significance

87

Appendix Table 5.Mean square values of ANOVA for growth parameters of cowpea as affected

by cowpea density and cowpea varieties.

Mean square

Source of

variation

DF

Plant height

(cm)

NBPP

leaf area

(cm 2 )

Replication 2 0.1378 0.32259 4.06

Cowpea density 2 13.0133** 0.02704ns 0.96ns

Cowpea varieties 2 .8811** 3.30037** 1388.95**

Varietyxdensity 4 5.2311** 0.12704ns 132.45ns

Error 16 0.4844 0.09468 91.99

CV% 1.89 6.41 19.47

Intercopxsolecrop 1 31.363* 0.4668ns 38.2ns

CV% 6.02 12.78 18.92

Df =degree of freedom *=significant at 5% probability level(p<0.05) **= highly significant at 1%

probability level(p<0.01) ns=non-significant at p>0.05 level of significance

NBPP=number of branch per plant


cowpea as affected by cowpea density and cowpea varieties.

Mean

square

Source of

variation

DF NPPP NSPP HSW(g) AGBM(kgh

a -1

GY(kgha -1 )

HI%

Replication 2 1.3704 0.3559 3.987 538716 7373 48.28

Cowpea density 2 19.3704** 0.4904ns 2.588ns 2106994** 3111522** 945.42**

Cowpea 2 44.5926** 47.9293** 179.879** 1637505** 663911** 68.40*

varieties

Varietyxdensity 4 0.2593ns 0.5470ns 3.808 ns 78441ns 64673* 10.53ns

Error 16 0.7870 0.8830 4.735 55308 15137 13.07

CV% 6.90 6.63 11.39 5.20 7.79 10.50

Intercopxsolecrp 1 26.009* 0.638ns 8.18ns 764681ns 1561927* 563.96*

CV% 17.85 16.70 17.2 14.26 3.26 17.16

Df =degree of freedom *=significant at 5% probability level (p<0.05) **= highly significant

at 1% probability level (p<0.01) ns=non-significant at p>0.05 level of significance

NPPP=number of pods per plant NSPP=number of seeds per pod HSW=thousand hundred

seed weight AGBM=Above ground biomass GY=Grain yield HI=harvest index

88

Appendix Table 7.Mean square values of ANOVA for total nitrogen and organic matter content

as affected by cowpea density and cowpea varieties.

Mean square

Source of

variation

DF TN OM


Cowpea density 2 1.033** 0.010681*

Cowpea varieties 2 7.500** 0.026133**

Varietyxdensity 6 2.417** 0.002607*

Error 22 6.333 0.002125

CV% 0.22 0.74

Intercopxsolecrop 1 1.141** 0.026759ns

CV% 0.83 3.01

TN=Total Nitrogen OM=Organic Matter *=significant at 5% probability level (p<0.05) **=

highly significant at 1% probability level (p<0.01) ns=non-significant at p>0.05 level of

significance

89

Experimental Photos

90

91

92

last final thesis of umer

Create successful ePaper yourself

Delete template?

Save as template?