PRODUCTIVITY OF GRAIN COWPEA (Vigna unguiculata (L.) Walp.) … EZEORAH... · 2015-09-16 · ii productivity of grain cowpea (vigna unguiculata (l.) walp.)as influenced by season,

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EZEAKU, EZEORAH INNOCENT

PRODUCTIVITY OF GRAIN COWPEA (Vigna unguiculata (L.)

Walp.) AS INFLUENCED BY SEASON, GENOTYPE, INSECT

PEST MANAGEMENT AND CROPPING SYSTEM IN

SOUTHEASTERN NIGERIA

biological sciences

CROP SCIENCE

Madufor,Cynthia c

Digitally Signed by: Content manager‟s Name

DN : CN = Webmaster‟s name

O= University of Nigeria, Nsukka

OU = Innovation Centre

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PRODUCTIVITY OF GRAIN COWPEA (Vigna unguiculata (L.) Walp.) AS

INFLUENCED BY SEASON, GENOTYPE, INSECT PEST MANAGEMENT AND

CROPPING SYSTEM IN SOUTHEASTERN NIGERIA

BY


PG/Ph.D/08/49869

DEPARTMENT OF CROP SCIENCE,

UNIVERSITY OF NIGERIA, NSUKKA

MARCH, 2013

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PRODUCTIVITY OF GRAIN COWPEA (Vigna unguiculata (L.) Walp.) AS

INFLUENCED BY SEASON, GENOTYPE, INSECT PEST MANAGEMENT AND

CROPPING SYSTEM IN SOUTHEASTERN NIGERIA

BY


B.Sc., M.Sc. (Nigeria)

A THESIS SUBMITTED TO THE DEPARTMENT OF CROP SCIENCE,

UNIVERSITY OF NIGERIA, NSUKKA IN PARTIAL FULFILMENT OF THE

REQUIREMENTS FOR THE AWARD OF THE DEGREE OF DOCTOR OF

PHILOSOPHY IN FIELD CROP PRODUCTION.

MARCH, 2013

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CERTIFICATION

Ezeaku, Ezeorah Innocent, a postgraduate student in the Department of Crop Science, with

the Reg. No. PG/Ph.D/08/49869, has satisfactorily completed the requirements for research

work for the degree of Doctor of Philosophy in Crop Science (Field Crop Production).

The work embodied in this thesis is original and has not been submitted in part or in full for

any other diploma or degree of this or any other University.

..………………………………….. …………………………………...

PROFESSOR B.N. MBAH PROFESSOR K.P. BAIYERI

(Supervisor) (Supervisor)

…..…………………………………….

PROFESSOR M.I. UGURU

(Head of Department)

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DEDICATION

To the Glory of God, and all

the members of my family particularly my beloved dad who was anxiously looking forward

to my graduation but never lived to witness it.

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ACKNOWLEDGEMENT

I wish to express my profound gratitude to my supervisors Professors B. N. Mbah and K. P.

Baiyeri for their support and guidance throughout the period of this research work. Professor

Mbah personally visited all the locations of the study and offered useful suggestions. His

contribution towards the success of this work is tremendously recognized. The contributions

of Professor Baiyeri in advicing on the experimental design and data analysis are deeply

appreciated.

I am immensely grateful to Dr. B. B. Singh who encouraged me to undertake this study and

provided the needed planting materials and relevant literature. His strong belief is that

although southeastern Nigeria is a non-traditional cowpea growing region, it has favourable

weather and soil that could support commercial production. It is our earnest expectation that

through this piece of work the dream of this world renowned cowpea breeder toward

promoting grain cowpea production in farmers‟ field conditions in sourtheastern region will

be realised. The contributions of Dr. A. Kamara of the International Institute of Tropical

Agriculture (IITA) and Dr. H. Ajeigbe of International Crops Research Institute for the Semi-

Arid Tropics (ICRISAT) in providing literature for this work and useful suggestions are

sincerely acknowledged and cherished. I wish to acknowledge the encouragement and useful

suggestions received from colleagues I worked with in IITA and ICRISAT particularly Drs.

U. Udensi, B. Bankefa, S. Aladele and Messrs. Abu Musa and Femi Ajiboye. Professor A. M.

Emechebe (Integrated Pest Management (IPM) Specialist formerly with IITA) and Dr. B.

Echezona (Entomologist, Crop Science Department, UNN) contributed significantly in

refining the experiment particularly insect pest parameters. Your efforts are recognized and

appreciated. I equally wish to thank Dr. A. A. Melifonwu (Deputy Provost, Federal College

of Agriculture Ishiagu, Ebonyi state) and Prince Onyeagba Emmanuel (Former Provost of

College of Agriculture Mgbakwu, Anambra state) for providing useful field level crop

management and logistical support services. Let me extend my special thanks to the

Managing Director of Demacco Integrated Farms Ltd Ako, Enugu State, Mr. Don Onyia in

providing facilities in his farm for this study. Dr. G. Tarawali of IITA/Cassava Enterprise

Development Project (CEDP) is remembered for showing interest in this work and providing

financial support at the inception of the research. I am profoundly thankful to the Head of

Department of Crop Science, academic and non-academic staff of the Department for their

contributions and moral support throughout the period of this study. Barrister Dr. G. Okeke is

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remembered for his fatherly counsel and prayers. I thank all the members of my group of

districts for their prayers and cooperation in various ways.

I am indebted to my brothers, Engr. Clement A. Ezeaku and Dr. Israel Ezeaku for their

support and encouragement. I am equally most sincerely appreciative of my beloved wife and

children for their constant prayers, unwavering love and understanding during the period of

my study. I appreciate you mum for your love, kind words and prayers that has sustained my

life thus far.

Mr. Paul Madumelu is remembered for demonstrating high level technical skills and

competence in data collection. Mr. Ezeani Nnanyelugo is greatly recoganized for being

meticulous and careful in data processing.

Above all, I thank God who redeemed me and translated me to the kingdom of his dear Son.

All Glory to His Wonderful Name.

Ezeaku, Ezeorah Innocent

University of Nigeria, Nsukka

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TABLE OF CONTENTS

Page

Title

Title Page …… …… …… i

Certification …… …… …… ii

Dedication …… …… …… iii

Acknowledgement …… …… …… iv

Table of Contents …… …… …… vi

List of Tables …… …… …… xi

List of Figures …… …… …… xiv

Abstract …… …… …… xvii

Introduction …… …… …… 1

Literature Review …… …… …… 5

2.1 Origin and distribution of cowpea …… …… 5

2.2 Soil and nutrient requirement …… …… 6

2.3 Climatic requirement …… …… …… 7

2.4 Cowpea insect pests …… …… …… 8

2.4.1 Aphids …… …… …… 8

2.4.2 Pod bugs …… …… …… 9

2.4.3 Thrips …… …… …… 10

2.4.4 Pod borers …… …… …… 10

2.4.5 Beetles …… …… …… 11

2.4.6 Bruchids …… …… …… 13

2.5 Pest management philosophy …… …… 13

2.6 Host plant resistance …… …… …… 14

2.7 Chemical control …… …… …… 15

2.8 Post harvest storage …… …… …… 16

2.9 Cultural practices and control …… …… 17

2.10 Intercropping …… …… …… 23

2.11 Varieties adapted to intercropping system …… 24

2.12 Cowpea haulms as fodder for livestock …… 25

2.13 Genotype by environment interaction …… …… 26

2.14 Genotype and genotype by environment (GGE) biplot 28

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Materials and Methods …… …… …… 30

3.1 Genotype, soil and weather description and characterization

of the experimental sites … …… …… 30

3.1.1 Genotype description …… …… …… 30

3.1.2 Soil characterization …… …… …… 30

3.1.3 Weather description …… …… …… 32

3.2 Experiment one …… …… …… 35

3.2.1 Experimental sites …… …… …… 35

3.2.2 Sowing dates …… …… …… 35

3.2.3 Experimental design, treatments and treatment allocation.. 35

3.2.4 Cultural operations …… …… …… 36

3.2.5 Data collection …… …… …… 36

3.2.6 Statistical analysis …… …… …… 38

3.3 Experiment two …… …… …… 38

3.3.1 Experimental sites …… …… …… 38

3.3.2 Sowing dates …… …… …… 38

3.3.3 Experimental design, treatments and treatment allocation.. 38

3.3.4 Cultural practices …… …… …… 40

3.3.5 Data collection …… …… …… 40

3.4 Statistical analysis …… …… …… 41

Results …… …… …… …… 42

4.1 Test of significance of growth, reproductive, grain

yield and yield components and insect damage responses …… 42

4.2 Main effect of genotype on growth, reproductive,

grain yield and insect pest damage component

in early and late season combined in Ishiagu, 2007 …… …… 48

4.3 Main effect of genotype on growth, reproductive, grain

yield and insect pest damage component in early and late

season combined in Ishiagu, 2008 …… …… …… …… 54

4.4 Main effect of genotype on growth, reproductive grain

yield and insect damage components in early season,

combined over 2007 and 2008, Ishiagu .…… …… …… …… 56

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yield and insect damage components in late season

combined over 2007 and 2008 in Ishiagu. .…… …… .…… …… 61


yield and insect pest damage component in early and late

season combined in Mgbakwu, 2007. .…… …… …… .…… 66


yield and insect damage components in early and late

season combined in Mgbakwu, 2008 .…… …… …… ……. 73

4.8 Genotype main effect for growth, reproductive, grain

yield and insect damage components early season

combined over 2007 and 2008, Mgbakwu ……. …… …….. 78

4.9 Genotype main effect for growth, reproductive, grain

yield and insect pest damage components late season

combined over 2007 and 2008 in Mgbakwu ……. …… …….. 83

4.10 Interaction effects of year, season and location on

genotype performance for some selected growth,

reproductive and grain yield traits (Performance

of genotype in each environment)-Experiment one …… …….. 89

4.11 Genotype by trait (GXT) relationship combined over

Ishiagu and Mgbakwu for 2007 and 2008 (Experiment one) …….. 99

4.12 Performance of genotypes across environments (GXE)

for insect damaged components (Experiment one) …… …….. 99

4.13 Genotype by insect damaged traits (GXT) across 2007

and 2008 (Experiment one) …… …… ……. …… …….. 111

4.14 Interaction effects of spray regime and season on

performance of genotype for some selected growth,

reproductive and grain yield components (Experiment one) 111

4.15 Main effect of genotypes combined over 2009 and

2010 in Ako location (Experiment two) ……. …….. …….... 122

4.16 Cropping system and genotype effects in early season

combined over 2009 and 2010 …….. …..… ………….. 124

4.17 Cropping system and genotype effects in late season

combined over 2009 and 2010 …….. ……… …………. 127

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4.18 Season by genotype effect combined over 2009 and 2010 …… 134

4.19 Interaction effects of year, season and cropping system

on the performance of genotypes for some selected growth,

reproductive and grain yield components in

Ako location (Experiment two) …… …… …… …… 137

4.20 Genotype by trait (GXT) relationship across 2009

and 2010 for growth, reproductive and grain yield components

(Experiment two)… … …… …… …… …… 143

4.21 Interaction effects of year, season and cropping system

on the performance of genotypes for some selected insect

damaged traits (Experiment two) …… …… …… …… 143

4.22 Genotype by trait (GXT) relationship across 2009 and

2010 for insect damaged components (Experiment two) ……… 151

4.23 Barchart showing the effects of spray regime, genotype,

cropping system, season, year, insect pests on grain

yield and insect pest population in Ako location …… ………. 157

4.24 The main effect of maize/cowpea intercropping

on maize growth, reproductive and grain yield components

combined over 2009 and 2010 in Ako …… ……… ……… 168

4.25 Season and genotype effects on growth, reproductive

and grain yield of maize variety combined over 2009

and 2010 in Ako …… …… …… 168

Discussion …… …… …… 171

5.1 Test of significance for variance component …… 171

5.2 Seasonal effects …… …… …… 172

5.2.1 Plant traits …… …… …… 172

5.2.2 Genotypes …… …… …… 175

5.2.3 Insect pest components …… …… 181

5.2.3.1 Aphids …… …… …… 181

5.2.3.2 Bruchids …… …… …… 182

5.2.3.3 Ootheca …… …… …… 183

5.2.3.4 Pod sucking bugs …… …… …… 184

5.2.3.5 Maruca …… …… …… 185

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5.2.3.6 Thrips …… …… …… 187

5.3 Insecticides spray regime effects …… …… 187

5.3.1 Growth, reproductive and grain yield components …… 187

5.3.2 Insect pest‟s management …… …… …… 190

5.4 Cropping system effects …… …… 191

5.4.1 Cowpea genotypes and plant traits …… …… 191

5.4.2 Insect pest infestation …… …… …… 194

5.5 Cropping system X season X spray regime X

genotype interactions …… …… …… 195

5.6 Cropping system X season interaction

on maize productivity …… …… …… 197

Conclusion and Recommendations …… …… …… 199

References …… …… …… 205

Appendices …… …… …… 238

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LIST OF TABLES

Table Page

1 The origin and description of the cowpea genotypes used in the study …… … 31

2 Soil physical and chemical properties of the experimental sites ….. …… 33

3 Rainfall (mm), temperature (oC) and relative humidity (percent) of the study sites 34

4 The main effect of genotype on growth component of 10 cowpea genotypes during

the early and late seasons in Ishiagu, 2007 …… …… …… 49

5 The main effect of genotype on reproductive and grain yield components

of 10 cowpea genotypes during the early and late seasons in Ishiagu 2007 …… 51

6 The main effect of genotype on insect damage of 10 cowpea genotypes

during the early and late seasons in Ishiagu, 2007 …… …… …… …… 53

7 The main effect of genotype on growth component of 10 cowpea genotypes

evaluated during the early and late seasons in Ishiagu, 2008 …… …… …… 55


of 10 cowpea genotypes during the early and late seasons in Ishiagu 2008 …… 57


during the early and late seasons in Ishiagu, 2008 …… …… …… …… 58


evaluated during the early season in Ishiagu in 2007 and 2008 …… …… …… 60

11 The main effect of genotype on reproductive and grain yield components of

10 cowpea genotypes evaluated during the early season in Ishiagu, 2007 and 2008 …… 62


evaluated during the early season in Ishiagu, 2007 and 2008 …… …… …… 63


evaluated during the late season in Ishiagu in 2007 and 2008 …… …… …… 65


10 cowpea genotypes during the late season in Ishiagu in 2007 and 2008 …… …… 67


evaluated during the late season in Ishiagu, 2007 and 2008 …… …… …… 69


evaluated during the early and late season in Mgbakwu, 2007 …… …… …… 70


of 10 cowpea genotypes during the early and late seasons in Mgbakwu 2007… 72


during the early and late seasons in Mgbakwu, 2007 …… …… …… 74

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Table Page


evaluated during the early and late season in Mgbakwu, 2008 …… …… …… 76


of 10 cowpea genotypes during the early and late seasons in Mgbakwu 2008… 77


during the early and late seasons in Mgbakwu, 2008 …… …… …… 79


evaluated during the early season of 2007 and 2008 in Mgbakwu …… …… 81


10 cowpea genotypes evaluated during the early season of 2007 and 2008 in Mgbakwu…82

24 The main effect of genotype on insect damage of 10 cowpea genotypes evaluated

during the early season of 2007 and 2008 in Mgbakwu …… …… …… 84


evaluated during the late season of 2007 and 2008 in Mgbakwu …… …… …… 85


10 cowpea genotypes during the late season of 2007 and 2008 in Mgbakwu …… 87

27 The main effect of genotype on insect damage of 10 cowpea genotypes evaluated

during the late season of 2007 and 2008 in Mgbakwu …… …… …… 88

28 The main effect of genotypes on growth component of 5 cowpea

genotypes combined over 2009 and 2010 in Ako …… …… …… …… 123

29 The man effect of genotypes on reproductive and grain yield components

of 5 cowpea genotypes combined over 2009 and 2010 in Ako …… …… 125

30 The man effect of genotypes on the insect damage of 5 cowpea genotypes

combined over 2009 and 2010 in Ako …… …… …… 126

31 Effects of cropping systems and genotypes on growth component of

5 cowpea genotypes in early season of 2009 and 2010 in Ako …… …… 128

32 Effects of cropping systems and genotypes on reproductive and

grain yield components of 5 cowpea genotypes evaluated in early

season of 2009 and 2010 in Ako …… …… …… …… 129

33 Effects of cropping systems and genotypes on insect damage of 5 cowpea

genotypes evaluated in early season of 2009 and 2010 in Ako …… …… 130

34 Effects of cropping systems and genotypes on growth component of

5 cowpea genotypes in late season of 2009 and 2010 in Ako …… …… 132

35 Effects of cropping systems and genotypes on reproductive and

grain yield components of 5 cowpea genotypes evaluated in late season

of 2009 and 2010 in Ako …… …… …… …… 133

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Table Page

36 Effects of cropping systems and genotypes on insect damage of 5 cowpea

genotypes evaluated in late season of 2009 and 2010 in Ako …… …… 135

37 Effects of season and genotypes on growth component of 5 cowpea

genotypes combined over 2009 and 2010 in Ako …… …… …… 136

38 Effects of season genotypes on reproductive and grain yield components

of 5 cowpea genotypes combined over 2009 and 2010 …… …… 138

39 Effects of season and genotypes on insect damage of 5 cowpea

genotypes combined over 2009 and 2010 in Ako. …… …… 140

40 The main effect of maize/cowpea intercropping on maize growth, reproductive

and grain yield components combined over 2009 and 2010 in Ako location … 169

41 Effects of season and genotypes on growth, reproductive and grain yield

of maize variety combined over 2009 and 2010 in Ako …… …… 170

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LIST OF FIGURES

Figure Page

1a Biplot of genotype by environment- year, season and location (GXE)

for grain yield per hectare …… …… …… …… 90

1b Biplot of genotype by environment- year, season and location (GXE)

for grain yield per hectare indicating ideal environments …… …… 91

2 Biplot of genotype by environment- year, season and location (GXE)

for dry fodder yield …… …… …… …… …… 92


for 100 seed weight …… …… …… …… …… 94


for threshing percentage …… …… …… …… 96


for harvest index …… …… …… …… …… 97


for number of plant stand …… …… …… …… 98

7 Biplot on genotype by traits (GXT) for selected growth, reproductive

and grain yield traits …… …… …… …… 100


for aphid damage …… …… …… …… 102


for Maruca damage …… …… …… …… 103


for Ootheca damage …… …… …… …… 104


for Ootheca damage showing an ideal environment …… …… 106


for pod sucking bug damage …… …… …… …… 107


for bruchid damage …… …… …… …… 109


for thrips damage …… …… …… …… 110


for thrips damage showing ideal environment …… …… …… 112

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Figure Page

14 Biplot of genotype by traits (GXT) interaction for selected insect damage traits.. 113

15a Biplot of genotype by environment (spray regime and season) for

grain yield per hectare …… …… …… …… 114

15b Biplot of genotype by environment (spray regime and season) for

grain yield per hectare showing ideal environment …… …… 116

16 Biplot of genotype by environment (spray regime and season)

for dry fodder yield …… …… …… …… 117


for 100 seed weight …… …… …… …… 118


for threshing percentage …… …… …… 120


for harvest index …… …… …… …… 121

20 Biplot of genotype by environment (Year, season and cropping

system) for grain yield per hectare …… …… …… 141


system) for dry fodder weight …… …… …… 142


system) for 100 seed weight …… …… …… 144


system) for threshing percentage …… …… …… 145


system) for harvest index …… …… …… 146

25 Biplot of genotype by traits (GXT) interaction for

selected growth, reproductive and grain yield traits… …… 147


system) for aphid damage …… …… …… …… 149


system) for Maruca damage …… …… …… 150


system) for Ootheca damage …… …… …… 152


system) for pods sucking bugs damage…… …… …… 153


system) for bruchid damage …… …… …… 154


system) for thrips damage …… …… …… 155

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Figure Page

32 Biplot of genotype by traits (GXT) interaction for selected insect

pest damage traits …… …… …… …… 156

33 Interaction effects of spray regime and genotype on grain yield evaluated

in early season in sole cropping (a) and intercropping (b) in Ako …… 158

34 Interaction effects of spray regime and genotype on grain yield evaluated

in late season, sole cropping (a) and intercropping (b) in Ako …… 159

35 Interaction effects of cropping system and genotype on grain yield evaluated

in early season (a) and late season (b) in Ako …… …… …… 161

36 Interaction effects of season and genotype on grain yield averaged over

two years in Ako …… …… …… …… …… 163

37 Interaction effects of year and genotype on grain yield averaged over

season in Ako …… …… …… …… …… 163

38 Interaction effects of spray regime and genotype on grain yield in early

season (a) and late season (b) averaged over cropping system in Ako …… 165

39 Interaction effects of year and insect pest on insect population

averaged over genotypes in Ako …… …… …… …… 166

40 Interaction effects of cropping system and insect pests on insect population

averaged over genotypes, season and years in Ako …… …… …… 166

41 Interaction effects of season and insect pest on insect population

averaged over genotypes and years in Ako …… …… …… 167

42 Interaction effects of spray regime and insect pest on insect population

averaged over genotypes, seasons and years in Ako …… …… …… 167

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ABSTRACT

The first experiment involved nine improved cowpea genotypes and a local variety. The ten

treatments were planted in two locations, namely the Research Farm of the College of

Agriculture, Mgbakwu in Anambra State (060 17ʹN, 07

0 04ʹE; 83m asl) and the Experimental

Farm of the Federal College of Agriculture, Ishiagu in Ebonyi State (050 58ʹN, 07

0 34ʹE; 197

m asl), over a period of two years and two seasons per year in each of the two locations. The

experiment was spilt-plot arranged in randomized complete block design (RCBD) with three

replications. The second experiment was conducted at the DEMACCO Integrated Farms Ltd.,

Ako, Nike in Enugu State (060 34ʹN, 07

0 35ʹE; 154 m asl). The experiment consisted of four

promising genotypes selected from experiment one and a local variety used as check. An

open pollinated maize variety (ACR9931) was intercropped with the five cowpea genotypes.

The maize and cowpea genotypes were sown over a period of two years and two seasons in

each year. The experiment was split-split plot arranged in RCBD with three replications. A

total number of twenty nine parameters were sampled consisting of eleven growth, twelve

grain yield and six insect pest damage components. Data were subjected to analysis of

variance (ANOVA) using the GENSTAT, 2003 edition. Differences among treatment means

were compared using F-LSD, while interaction of genotype by environment, genotype by

traits and environment by traits were computed using GGE biplot analytical model. This

study revealed the presence of genotype X season, genotype X insect protection and genotype

X season X insect protection interaction for experiment one, while experiment two indicated

the presence of genotype X season, genotype X cropping system, genotype X spray regime

and genotype X season X cropping system X spray regime interaction. Growth, reproductive,

grain yield and insect damage components were highly significant in all the environments.

Yield and yield components were significantly higher in early season than in late season.

Similarly, plant population and cowpea biomass were higher in early than late season. Pod

length, number of seed per pod, number of branches and number of internodes were least

influenced by the environments due to their high heritability. In all the environments, seed

size was significantly higher in IT97K-277-2, IT97K-556-4 and IT93K-452-1, than the rest

genotypes, while IT84S-2246-4 and IT90K-82-2 consistently expressed significantly lower

seed size. The local variety produced significantly higher seed size than all the test genotypes

when sprayed with insecticide in late season. The genotypes IT90K-277-2, IT97K-556-4 and

local variety exhibited dual-purpose (grain and fodder) characteristics, while the rest

genotypes were purely grain type. Most of the dual-purpose cowpeas are both indeterminate

xviii

and long duration. The short growth duration and higher mean grain yield made IT93K-452-1

the best grain type cowpea because it combined these qualities with tolerance to most post

flowering pests. The genotype IT93K-452-1 also produced reasonable grain yield in late

season without chemical spray. IT98K-131-2 was an outstanding medium maturing genotype

combining superior grain yield attribute with tolerance to both pre-and-post flowering pests

in all the environments. Furthermore, this variety also produced satisfactory grain yield in

late season without insecticide application. Genotype IT97K-556-4 on the other hand,

harboured the highest population of most pests sampled in all the environments. This study

further showed that thrips, Maruca, pod sucking bugs and bruchids were the most prevalent

insect pests of cowpea in south eastern Nigeria, while aphids and Ootheca were the minor

pests. Application of insecticides once each at flower bud initiation, full bloom and podding

significantly reduced insect pest population and increased grain yield of cowpea significantly.

Improved cowpea genotypes recorded significantly higher grain yield than the local check in

all the environments. Medium to late maturing genotypes were better adapted to late season

while early maturing genotypes performed well in both seasons. Bruchids, Maruca, pod

sucking bugs and thrips were more abundant in late season than early season while aphids

and Ootheca population were more widespread in early season than late season. Brown

seeded cowpea genotype consistently harboured lower infestation by bruchids than white

seeded types. This study also showed that insecticide treatment targeted at the critical growth

stages especially at 50 percent podding and early sowing significantly reduced bruchids

damage on stored cowpea seed. Grain yield loss assessment was negligible in early season for

all the genotypes while in late season it was 100 percent for local variety, 34 percent for best

yielding medium maturing genotype (IT98K-131-2) and 30 percent for best yielding early

maturing genotype (IT93K-452-1). Percentage reduction in insect population when 3 sprays

were applied relative to zero spray for aphids, bruchids, Maruca, Ootheca, pod sucking bugs

and thrips are 121 percent, 240 percent, 174 percent, 45 percent, 38 percent and 270 percent

respectively. Intercropping reduced dry fodder yield in early season by 22 percent and in late

season by 41 percent. On the other hand, intercropping did not significantly reduce number of

branches, internodes number, number of leaves, number of nodules, plant population, and

root length. Meanwhile, peduncle length was significantly reduced by intercropping in both

early and late season but varied widely among the genotypes tested, with local cowpea

variety being most affected. Peduncle length in cowpea was obviously sensitive to stress

imposed by intercropping particularly in late season and could be used as an index for

determining cowpea cultivars adapted to intercropping environment. Intercropping in both

xix

seasons significantly reduced yield and yield components in cowpea but more in late than

early season. Consequently, intercropping reduced grain yield in early season by 14 percent

while in late season it reduced it by 25 percent. Also, intercropping in early season reduced

days to maturity but did not affect 50 percent bloom and pod filling duration. However, in

comparison with early season, all the genotypes in late season flowered and matured earlier,

while on the contrary they took longer days to fill their pods. In both seasons, sole cropping

generally produced higher grain yield than intercropping when sprayed with insecticide.

Conversely, cowpea grain yield in intercropping were generally higher than yields from sole

cropping when no insecticide was applied, suggesting less insect damage under

intercropping. Early maturing genotypes produced significantly higher grain yield in early

and late seasons and in both sole and intercropping, while medium and late maturing

genotypes expressed their highest yield potentials in sole cropping in late season. Also, in late

season, intercropping significantly reduced the population of bruchids, pod sucking bugs and

thrips but did not affect the population of the rest insect pests. Highest grain yield

components were realized in genotypes grown in intercropping with two sprays while in sole

cropping early maturing genotypes required two sprays while medium and late maturing

genotypes required three sprays to produce the highest grain yield. Late season planting

reduced the population of aphids, Maruca and Ootheca by 122 percent, 183 percent, and 47

percent respectively, while early season sowing reduced the population levels of pod sucking

bugs by 47 percent and thrips by 104 percent. Intercropping reduced the population of aphids,

bruchids, pod sucking bugs and thrips by 40 percent, 9 percent, 8 percent, and 100 percent

respectively. Meanwhile, intercropping increased the infestation of Maruca by 9 percent

while Ootheca was unaffected by cropping system. Intercropping combination of

ACR9931/IT98K-131-2 had positive effects on maize through the production of significantly

higher yield and yield components of maize, while ACR9931/Local combination depressed

components of maize yields. We found improved medium maturing, indeterminate cowpea

cultivar with long peduncle length as most suitable for use in intercropping with maize in

South-eastern Nigeria. Maize performed better under intercropping than sole cropping in

early than in late season, in 2009 than 2010. The yield reduction in maize from cropping

system, season and year effects was caused by decline in cob length, cob weight, number of

cobs per plot, seed weight, 100 seed weight and harvest index, and not by number of plant

stands. This revealed that maize productivity is more influenced by these traits.

1

CHAPTER ONE

INTRODUCTION

Cowpea is cultivated on at least 12.5 million hectares, with an annual production of over 3

million tonnes world wide. Cowpea is widely distributed throughout the tropics, but Central

and West Africa accounts for over 64 percent of the area. In West Africa, a substantial part

of the cowpea production comes from the drier regions of northern Nigeria (Singh et al.,

1997). Mortimore (1980) reported that by the 1960s and 1970s there was a long established

cowpea trade network, linking the producing areas in northern Nigeria with the major centers

of demand in the south. In other words, cowpea remains predominantly a crop of drier areas.

Quin (1997) noted that as further advances are made in crop improvement and management,

there will be opportunities for commercial production of cowpea in longer season, wetter

agro-ecologies. Furthermore, Kormawa et al. (2002) observed that if suitably adapted

improved varieties of cowpea along with appropriate integrated management packages are

identified the crop‟s production area will expand rapidly to wetter regions.

Cowpea is consumed by humans in many forms; the young leaves, green pods, and green

seeds are used as vegetables; dry seeds are used in various food preparations; and the haulms

including pod walls are fed to livestock as nutritious supplement to cereal fodder (Barrett

1987). Nigeria is the largest consumer of cowpea in the world (Nnanyelugo et al., 1985;

McWatters et al., 1990). Nnayelugo et al. (1997) stated that cowpea consumption in southeastern

Nigeria has increased in frequency and quantity by 150 percent and has also reduced severe

malnutrition in children by 70 - 100 percent. The image of cowpea has improved and it is being

introduced into children‟s diets at earlier ages in both rural and urban areas, and that almost all the

dry cowpea seeds consumed in southern Nigeria are brought in from the northern part of the

country. Similarly, Uguru (2008) is in support of this observation. Although southeastern Nigeria

has favorable weather and soil that can sustain commercial grain cowpea production, the region

unfortunately accounted for only about 0.57 percent of the total grain cowpea production and

0.38 percent of the total area cultivated in Nigeria in 2007 (APS, 2008).

The bulk of the diet of rural and urban poor African people consists of starchy food made

from cassava, yam, cocoyam, millet, sorghum, and maize. The addition of even a small

2

amount of cowpea ensures the nutritional balance of the diet and enhances the protein quality

by the synergistic effect of high protein and high lysine from cowpea and high methionine

and high energy from the cereals. The nutritious and balanced diet ensures good health and

enables the body to resist infectious diseases and slow down their development (Nielsen et

al., 1993). It has been found that HIV/AIDs patients placed on daily cowpea diets

experienced significant boost in their immunity level thus prolonging their lifespan (Clark,

2005). Similarly, Carper (1988) pointed out that a cup of cooked, dry beans every day should

lower the low-density lipid cholesterol, regulate blood sugar and insulin, lower blood

pressure, regulate the bowels, and prevent gastrointestinal troubles, even hemorrhoids and

cancer of the gut. Furthermore, individuals with type 1 diabetes can cut their insulin

requirements by 38 percent if they increase their bean intake a cup (about 184 g) a day. It is

estimated that cowpea supplies about 40 percent of the daily protein requirements to most of

the people in Nigeria (Muleba et al., 1997).

Insect pest damage is a major constraint to cowpea production in Nigeria (Raheja, 1976;

Amatobi, 1994). Insect pest attack in cowpea often leads to total yield loss (Singh and Allen,

1980; Jackai et al., 1985). Use of insecticides improves the yield of cowpea ten fold (Singh

and Allen, 1980; Parh, 1993). Jackai (1983) and Adalla (1994) observed that in parts of Asia

the effects of misuse of insecticide is already being felt as more cases of resistance and

damage to ecosystems are being reported yearly. Edwards (1993) warned that unless this

trend is reversed in Nigeria, we can expect the same problems of the insecticide treadmill that

characterizes agricultural systems in the developed world. To increase the efficiency of

insecticides and reduce overuse, chemical application should be carefully managed to

coincide with critical growth stages where pest pressure is high (Alghali, 1992). In order to

reduce insect damage, increase cowpea productivity, and control indiscriminate use of

insecticides, it is important to conduct studies to determine the growth stages at which

minimum use of insecticide is advisable. Moreover, application of insecticides should be

integrated with other cultural practices to increase effectiveness and reduce over use of

insecticides (Kamara et al., 2009). There is therefore the need to develop a robust pest

management package for cowpea production in Nigeria especially in a pest endemic region

like southeastern Nigeria. Afun et al. (1991) stated that cost effectiveness of minimum

insecticide applications in combination with other cultural practices show a 50 percent

reduction in production cost.

3

Planting date has been identified as an important component of integrated pest management

practices ((Hall, 1992). It has been suggested that adjusting planting dates could cause

asynchrony between crops and insect pests (Pedigo, 1989). Karungi et al. (2000) reported that

planting early in the season reduced aphids, thrips and pod-sucking bug‟s infestation but

increased Maruca infestation in Uganda. The reduction in aphids, thrips and pod bugs was

attributed to lower population in the early season, which could build up as the season

progresses and cause more damage to lately planted cowpea. It was suggested that differences

in planting dates could be explored in different agro-ecologies as it may have some potential

in influencing the incidence of various insect pests (Taylor, 1978; Akingbohungbe, 1982).

Intercropping has long been known to be a major component of integrated pest management

(IPM) (Olufajo and Singh, 2002). Singh and Emechebe (1998) found that intercropped

cowpea gave higher grain yields than yields from the sole crop when no insecticide was

applied, indicating less insect damage under intercropping. Blade et al. (1997) noted that the

local cowpea varieties are highly adapted to intercropping systems than improved varieties

but they have a very low harvest index. However, Singh and Emechebe (1998) identified

good performance of a number of IITA improved varieties under both sole and intercropping.

These cultural practices when combined with the use of insecticides and host-plant resistance

are probably the most effective measure against some of the cowpea pests, and could be used

as cost effective components of integrated pest management package (Javaid et al., 2005).

However, there is no properly packaged IPM program for cowpea production in southeastern

Nigeria yet. This is because the individual components have to be developed first before they

can be consolidated into a management package. This is part of what this experiment seeks to

establish.

Despite the high potential benefits of cowpea in Nigeria, the yield levels are very low which

range from 240-300kg/ha (Rachie, 1985). Meanwhile, when the crop is grown in pure stand

with required inputs, improved varieties, and appropriate management practices, yield as high

as 4 tonne per hectare has been reported (Rachie, 1985; Huxley and Summerfield, 1976;

Singh, et al., 2002).

Although different categories of improved cowpea varieties are available on the shelf in the

research stations of IITA, there is limited study on the productivity of these varieties in

Southeastern Nigeria with respect to their performance or responses when exposed to the

4

entire pest complex under natural field infestation (either sprayed or not sprayed with

insecticides) and at different planting dates. The identification of cultivar(s) that produce

reasonable yield without insecticidal protection can be a low input approach to solving the

problem of yield constraints in cowpea occasioned by high population of insect pests in the

region, and also enhance the promotion of sound ecologically and economically viable

cowpea production options. Furthermore, the integration of these selected low input

genotypes with appropriate sowing date and cropping system will even result in more

sustainable cowpea production system through better IPM strategy. Such IPM package would

be compatible with resource poor cowpea farmers and equally promote organically produced

cowpea crop. On the other hand, identification of responsive cowpea cultivars to insecticidal

treatments will certainly catalyze the commercialization of cowpea production enterprise by

medium to large scale farmers. The pest problem in cowpea is complex and requires

diversified efforts. Any single effort will be a slow and frustrating process (B.B. Singh,

personal communication).

The general objective of this research is to assess the productivity of ten cowpea genotypes

under varying spray regimes, locations, seasons, and cropping system in the moist savanna of

southeastern Nigeria agro-ecology.

The specific objectives are to:

1. determine the effects of insecticide treatment on cowpea insect pests infestation and

growth and yield of cowpea genotypes;

2. determine the effects of time of seeding on cowpea insect pests infestation and growth

and yield of cowpea genotypes;

3. determine the effects of cropping system on cowpea insect pests infestation and

growth and yield of cowpea genotypes; and

4. establish appropriate combination of insecticide treatment, time of seeding and

cropping system on insect pests management and growth and yield of cowpea

genotypes.

5

CHAPTER TWO

LITERATURE REVIEW

2.1 Origin and distribution of cowpea

The centre of origin of cowpea has been most controversial. Much of the confusion

surrounding the origin of cowpea resulted from the predominance of different cultivated

types in different regions of the world (Padulosi and Ng, 1997). The suggestion that cowpea

originated in Asia could not be supported because of the absence of progenitors there.

Speculation on the origin and domestication of cowpea has been based on botanical and

cytological evidence, geographical distribution and cultural practices, as well as historical

records (Faris, 1965; Steele and Mehra, 1980; Ng and Merechal, 1985; Ng, 1995). Wide

spread distribution of wild cowpeas is one of the strongest lines of evidence favoring Africa

as the center of origin of the crop (Verdcount, 1970). This agreed with Steele (1972) who

reported that cowpea is a native of Africa where it was domesticated in the millet/sorghum

farming systems of the semi–arid West Africa, where most of the crop is now grown.

Within Africa, the precise location where cowpea was first domesticated is uncertain.

Ethiopia (Vavilov, 1951; Sauer, 1952; Steele, 1976), West Africa (Murdock, 1959; Faris,

1965; Marechal et al., 1978; Steel and Mehra, 1980), Central Africa (Piper, 1913) and

Central and South Africa (Zhukovskii, 1962) have all been considered probable centers of

domestication. However, the existence of wild and weedy species which abound both in the

savanna and forest zones lead to some support to the view of Rawal (1975) and many earlier

authors such as Piper (1913); Rachie and Roberts (1974), who postulated that the primary

center of origin of cowpea is West Africa and very likely Nigeria from where it spread to

other tropical and subtropical zones of the world. Studies of more than 10,000 accessions of

world cowpea collections held at IITA revealed that germplasm accessions from Nigeria,

Niger, Burkina Faso and Ghana showed greater diversity than those from other regions (Ng,

1982). Ng and Marechal (1985), Ng (1995) concluded that the centre of maximum diversity

of cultivated cowpea is found in West Africa in an area encompassing the savanna region of

Nigeria, Southern Niger, part of Burkina Faso, northern Benin, Togo, and the northern part of

Cameroon.

6

Cowpea was introduced from Africa to the new world in 17th

century by the Spanish in the

course of slave trade, and has been grown in Southern USA since the early 18th century

(Padulosi and Ng, 1997), to Europe through Northeastern Africa around 300 BC, to India at

about 200 BC from where it underwent further diversification in India and South east Asia

(Ng and Marechal, 1985). It can be argued that the wide spread of the crop globally in

tropical and subtropical zones of the world can be attributed to its adaptability to a wide range

of soils and climatic conditions cropping systems and to its‟ value as food crop for man and

fodder for livestock.

2.2 Soil and nutrient requirement

Cowpea thrives in a well drained sandy loam soil. Cowpea is a low inputs crop which can

grow and yield in relatively poor soils better than most cereal crops. It has reduced demands

for mineral nitrogen, but has a special demand for Molybdenum, Cobalt, Boron, Copper,

Phosphate and Zinc (Summerfield et al., 1974). Cowpea taproot is stout with laterals near the

soil surface (Duke, 1990). The roots are associated with large nodules, which are smooth and

spherical. They are numerous on the taproot and its main branches, but sparse on the small

roots. Significant cowpea responses to nitrogen applied as Urea have been obtained in

different agro ecological zones of West Africa semi-arid tropics. These significant responses

indicate that the predominantly sandy soils of this region may be deficient in molybdenum

required for efficient symbiotic fixation (Hafner et al., 1992). On the sandy acid soil at

Bengou in the Sudanian zone significant molybdenum response was obtained at different

levels of soil fertility management for cowpea (Bationo et al., 2003). Cowpea generally does

not respond to nitrogenous fertilizer when plant properly nodulate and on soils of moderate to

high fertility levels. Nitrogenous fertilizer application in fertile soils reduces nodulation and

cause excessive vegetative growth with few pods which adversely affect seed yield, on the

other hand it increases seed yield when applied on poor soils and in soils continuously

cropped without fertilizer (Nanju et al., 1975).

Legumes such as cowpea have a high phosphorus requirement. Phosphorus is reported to

stimulate root and plant growth, initiate nodule formation, as well as influence the efficiency

of the rhizobium-legume symbiosis. It is also involved in reactions with energy transfer, more

specifically ATP in nitrogenase activity (Israel, 1987). Research conducted at Ikenne in the

humid zone and Kamboinse in the Sudanian zone of West Africa indicated a strong

differential response to phosphorus by cowpea cultivars (Bationo et al., 2003). The

7

application of phosphorus on cowpea resulted in significant decrease of zinc concentration in

the cowpea grain which can affect the nutritional quality (Buerkert et al., 1998; Dwivedi et

al., 1975; Khan and Zende, 1977; Stukenholtz et al., 1966; Takkar et al., 1976; Youngdhal et

al., 1977).

Phosphorus is the most limiting plant nutrient for cowpea production in West Africa and

there is ample evidence that indicates marked differences between cowpea genotypes for

phosphorus uptake (Bationo et al., 2003). Phosphorus, although not required in large

quantities, is critical to cowpea yield because of its multiple effects on nutrition (Muleba and

Ezumah 1985). It not only increases seed yields but also nodulation (Luse et al., 1975; Kang

and Nangju, 1983) and thus nitrogen fixation. Phosphorus application influences the contents

of other nutrients in cowpea leaves (Kang and Nangju, 1983) and seed (Omueti and Oyenuga,

1970). Application of phosphorus is recommended for cowpea production on soils low in

phosphorus (Sellschop, 1962; Rachie and Roberts, 1974; Casky et al., 2003; Kolawole et al.,

2003). Cowpea nodulation is generally reduced in acid, aluminum-rich soils. Manganese

toxicity reduces cowpea nodulation at low PH

(Keyser et al., 1979). The poor ability of some

genotypes especially most landraces to assimilate carbon and nitrogen during the

reproductive periods and to partition large amount of their daily gains of these two elements

into fruit has been identified as one of the factors limiting cowpea yields (Patel and Hall,

1990). Recommendations for cowpea as starter dose are 20kg N/ha, 40kg P2 O5 and 40kg K2

O/ha (Casky et al., 2003).

Warm-season annual crops such as cowpea exhibits slow and incomplete emergence when

subjected to cool soils. The threshold soil temperature where cowpea exhibits incomplete

emergence is about 19oc

(Ismail et al., 1997). Soil temperatures below 19oc

often occur at the

pick of rainy season. Early sowing can result in high plant population and consequently

higher yield because of high soil temperatures during the early season (Hall, 1992).

2.3 Climatic requirement

Cowpea grows under a wide range of climatic conditions, arid to sub-humid and performs

well on acidic soils (Pandey and Ngarm, 1985). In many areas cowpea is grown in sloping

land as a cover crop for grazing. In Srilanka the crop is grown in both rice land and hilly

areas where slope is 15–20 per cent. In Burma, Philippines and Thailand, it is grown after

rice where soil moisture is limited. In Indonesia it is grown in the highly acidic soils and

8

performs better than other grain legumes (Rajan, 1977). In Jodhpur, an arid region of India,

analysis of the climatic pattern for 1901–1972 showed cowpea was more successful than

mung bean, sun flower and groundnut (Ramakrishna and Singh, 1978). Cowpea was found to

be superior to other crops in tolerance to sandstorm exposure and had normal yield. First

harvest yields decrease with increasing sandstorm velocity, indicating that sandstorm injury

delayed maturity (Downes et al., 1977).

2.4 Cowpea insect pests

At least 85 insect species have been identified which attack cowpea (Booker, 1965), but only

some of them cause wide spread damage (Chalfant, 1985; Daoust et al., 1985; Singh, 1985;

Singh and Jackai, 1985). The most important ones include aphids Aphis craccivora Koch

(Homoptera: Aphididae), pod borers Maruca vitrata (Fabricus) (previously M. testulalis

[Geyer]) (Lepidoptera: Pyralidae), flower thrips Megalurothrips sjostedti, especially

clavigralla tomentosicollis Stal (Hemiptera: Coreidae) and the storage beetles (Jachai et al.,

1985; Singh et al., 1990).

In Africa, insect pests are often responsible for 100 percent yield losses (Singh and Jackai,

1985). Ng and Marechal (1985) pointed out that the reason why cowpea insect pest severity is

higher in African than other regions is probably because many of the pests are considered

indigenous to the continent and/or have had ample time to co-evolve with the crop in its

centre of origin and domestication.

2.4.1 Aphids

There are two Aphids spp.(Homoptera: Aphididae) reported to be associated with cowpea in

Africa, Aphis craccivora Koch, which is the main aphid infesting cowpea through out Africa

and Asia, and A. fabae (Scopoli) which has been reported as a minor pest in East Africa

(Singh and van Emden, 1979). Mostly females are found, and they reproduce

parthenogenetically (Singh and Jackai, 1985). The biology of A. craccivora varies a great

deal with the host plant, soil fertility, soil moisture and temperature. The adults live from 5 to

15 days and have a fecundity of over 100. Daily progeny may vary from 2 to 20. A

generation can be completed within 10 – 20 days (Singh, 1980). Aphids primarily infest

seedlings, although large populations also infest the pods. They cause direct damage on the

plant by removal of its sap. Small population may have little impact on the plant, but large

populations can cause distortion on leaves, stunting of plants and poor nodulation of the root

9

systems. Yield is reduced, and in extreme cases the plant dies (Singh and van Emden, 1979).

Indirect, and often more serious, damage is through transmission of aphid-borne viruses

(Bock and Centi, 1974). Several insecticides such as phosphamidon and dimethoate are

effective against aphids, but pirimicarb is probably the best (Singh and Allen, 1980).

2.4.2 Pod bugs

Numerous species of pod bugs infest cowpea at the podding stage and do considerable

damage. Normally their populations are high because the adults constantly migrate from wild

host plants to cultivated fields. They breed through out the year if food is available and the

climate favorable (Singh and Jackai, 1985). Adults and nymphs suck the sap from the

developing pods and can cause serious yield losses through premature drying of pods and

lack of normal seed formation (Tamo et al., 1997).

Among the major pod bugs, four species in the family coreidae cause economic losses in

Africa; clavigralla tomentosicollis (Stal.) synonym: Acanthomia tomentosicollis (Stal.) found

in East and West Africa, C. Shadabi Dolling synonym: A. horrida (Germar) found in West

Africa; and C. elongata signoret in East Africa. Anoplocne mis curvipes (Fabricius) is found

in East, West and Central Africa (Jackai and Daoust, 1986; Singh et al., 1990). Clavigralla

tomentosicollis is medium sized, hairy, and grey. Nymphs form large colonies on cowpea

pods and peduncle and are not easily disturbed. Adults are not strong fliers and have

longevity of 100 – 150 days. Eggs are laid in batches of 10 -70, and, on average, abut 200

eggs are laid by each female. Each instar lasts about 2 days, but the last instar is about 6 days.

The total nymphal period is about 14 days (Singh and Taylor, 1978). Clavigralla Shadabi and

C. elongata are similar than C. tomentosicolis and are grey. The former has a spiny dorsal

thorax, and the latter is distinguishable by its long cylindrical body. The two pests feed on

pods and they have similar biology. Adult longevity is from 40 to 80 days. Eggs are laid

singly, about 250 eggs per single female and they hatch in about 6 days. There are five

nymphal instars, and the total nymphal period is about 20 days (Singh and Taylor, 1978). At

present, insecticides such as edosulphan and dimethoate offer the only effective control

method, although manipulating the planting date also holds some promise (Singh and Jackai,

1985).

Anoplocnemis curvipes (Fabricius) is a major pest of cowpea found throughout Africa; it has

a large host range, including leguminous trees and several other wild host plants. The adults

10

are strong fliers, dark black and fairly large, they live from 24 to 84 days, but unmated males

and females survive up to 150 days. Eggs are laid in batches, normally in chains, and are dark

grey. They are laid on leguminous trees and wild host plants rather than on cowpea. Each

batch contains 10 – 40 eggs, and a single female normally lays 6 – 12 batches. The eggs hatch

in about 7 – 11 days. There are five nymphal instars, and the early instars resemble ants. The

total nymphal period is about 30 – 60 days, depending on the host plant and climatic

conditions (Singh et al., 1990). Endosulfan, fenitrothion and dimethoate are effective in

controlling this species.

2.4.3 Thrips

Several species of thrips damage cowpea in Africa, but only a few are important (Singh and Jackai,

1985). Legume bud thrips, megalurothrips sjostedti (Trybom) synonym: Taeniothrips sjostedti

(Trybom) (Thysanoptera: Thripidae), are a major pest of cowpea and often cause up to 60 percent

damage to the crop (Singh and Taylor, 1978). The biology of this pest is not completely known,

although the entire life cycle takes about 18 days. Eggs are laid in flower buds, and nymphs

and adults develop. Adults are shiny black and are easily noticed on the flowers where they

feed on pollen. The nymphs and adults feed on flower buds and can cause complete loss of

flower production. The racemes of severely infested plants do not have any flower buds and

existing flowers appear diseased (Singh, 1985). Methomyl, monocrotophos and cypermethrin

are effective against this pest.

Foliar thrips, Sericothrips occipitalis Hood (Thysanoptera: Thripidae), have been noticed as

a minor pest of cowpea seedlings during draught stress. The infestation declines with the

onset of the rains, and the plants appear to recover fully. Foliar thrips are often found on

seedlings in greenhouse or on irrigated crops in the dry season (Singh and Jackai, 1985).

2.4.4 Pod borers

Legume pod borer Maruca vitrata Fabricius is found throughout the continent of Africa and

can cause serious losses in cowpea yield (Singh and Van Emden, 1979). The adult moth is

dull white, with light-brown markings on the forewings and at the edges of the hind wings.

The female moth lays up to 200 eggs on flower buds, flowers and tender leaves (Jackai,

1982). The late larval instars can be easily identified by the characteristic black dots on their

body (Usua and Singh, 1978). A two days pre-pupal period follows the larval period, during

which feeding ceases. The pupal stage takes 6 – 9 days, and the pupae are initially green or

11

pale yellow but later darken to grayish-brown. Pupation occurs on the soil in a double walled

pupal cell, and adults emerge after about 5 – 10 days and have a life span of 5 – 15 days

(Taylor, 1967). In the absence of flower buds and flowers, the early larvae, feed on young

tender shoots and peduncles. Later, when the flower buds and flowers are formed, they prefer

to feed on floral parts and the green pods. They hide during the day in the flowers or pods

and are active during the night, wandering around the host plant and invading uninfested

flowers and pods. The larval usually web together leaves, flowers and pods (Taylor, 1967).

IITA has developed cowpea varieties that are resistant to many insect pests; however, despite

the extensive germplasm screening, effective sources of resistance to Maruca vitrata and

pod-sucking bugs have not been identified among cultivated varieties of cowpea. Controlling

these pests necessitates chemical spray during the flowering and pod development stages

(Singh et al., 1990; Singh et al., 1997). Several insecticides such as methromyl, endosulfan

and cypermethrin are effective against M.vitrata (Singh and Allen, 1980). Detailed studies on

the importance of alternative host plants for the population dynamics of M.vitrata have

revealed that the insect is oligophagous, feeding and reproducing on a number of cultivated

and wild host plants, all of which belong to the Fabaceae (Leumann, 1994; Arodokoun,

1996). The alternation of the flowering pattern of these plants on a South-north gradient has

been found to influence the migration of M.vitrata from the coast to the dry savannas of West

Africa (Bottenberg et al., 1997). During this migration population of M.vitrata finds

favourable conditions for multiplying on the different host plants, thereby increasing the size

of each new generation. When this huge population reaches the main cowpea growing areas

in the northern regions, it is too late to intervene unless highly resistant varieties are available

or intensive pesticide use is envisaged (Alghali, 1991). To prevent the build up of such large

populations, a suitable bio-control agent should be able to arrest their migration from the

south to the north. Any efficient bio-control candidate should be able to recognize the most

important host plants for M.vitrata, in order to follow the pest migration through host

switching (Tamo et al., 1997).

2.4.5 Beetles

A large number of coleopterous beetles feed on cowpea foliage and flowers and some are

effective vectors for viruses (Singh and Taylor, 1978). In general they are sporadic pests, and

unless their populations are high the damage by direct feeding is insignificant (Chalfant,

1985). Cowpea leaf beetle, Ootheca mutabilis (Shalberg) (Coleoptera: Chrysomelidae), is

12

probably the most damaging of the foliage-feeding beetles that attack cowpea in East and

West Africa (Booker, 1965; Halteren, 1971). A related species, O.bennigseni Weise, has been

reported from East Africa (Le Pelley, 1959) Ootheca Mutabilis adults are normally shiny,

light brown or orange; however, light- black or brown adults are also found. Adults are about

6mm long, oval and can live up to 3 months. Eggs are laid in the soil (about 60 eggs/egg

mass) and the total number of eggs laid by a single female varies from 200 to 500. The eggs,

which are elliptical, light yellow and translucent, are held together in a mass by a sticky

substance secreted by the female; they hatch in about 13 days. The larvae develop in the soils.

And they are three larval instars (Singh and Jackai, 1985). The first and second instars last

about 6 days each, and the third lasts about 18 days followed by a prepupal stage, which lasts

about 15 days. The pupal stage is about 16 days. The life cycle of this pest is greatly affected

by the season and ranges from 60 to 250 days (Jackai et al., 1985; Chalfant, 1985, Singh and

Jackai, 1985)

In Southern Nigeria, where the rainfall is bimodal, during the second season, adults undergo

obligatory diapause (Ochieng, 1977). After emergence they remain inactive in the soil for

almost 60 days while reproductive parts are not fully developed and they are incapable of

flight (Jackai et al., 1985). Singh and Taylor (1978) observed that the damage is done by the

adults, feeding between veins on the leaves. Dense populations can totally defoliate cowpea

seedlings, resulting in the death of the plant. The larval feed on the cowpea roots but seldom

cause serious damage. Bock (1971) noted that the adult cause indirect damage by transmitting

cowpea yellow mosaic virus.

Blister beetles, Mylabris spp. (Coleoptera: Meloidae), are pests of cowpea flowers. Those

that are commonly found are M. farquharsoni Blair and M. amplectens Gerstaecker). A few

beetles of the genus Coryna, especially C. apicicornis (Guerin) are also important cowpea

flower feeders (Singh and Jackai, 1985). They are often found in cowpea planted with or near

maize. The life history of blister beetles is rather complex; the larva undergo

hypermetamorphosis, and each larval instars is different. Eggs are laid in the soil where

larvae and pupae are usually found. The adults are strong fliers and feed on flowers‟ and

pollen grains. These beetles are often difficult to control because the adults are found only on

flowers, whereas the larvae are scattered in the soil (Chalfant, 1985). Insecticide such as

endosulfan, methomy and Chlorpyrifos are effective against these Pests, and the number of

applications required to control the insect depends on the location, season and the insect

13

population.

2.4.6 Bruchids

Several storage weevils species such as Callosobruchus (Coleoptera: Bruchidae) cause

damage but the two most important are C. maculatus (Fabricius) and C. chinensis (Linnaeus)

(Murdock et al., 1997). Infestation occurs in the field when the pods are nearly matured.

Eggs are laid on the pods, but weevils prefer to slip inside the pods through holes made by

the other pests and lay eggs directly on the seed. After the crop is harvested the bruchids

multiply and do considerable damage to stored cowpea (Kitch et al., 1997). The adult life

span is from 5 – 7 days and each female lays 50 – 80 eggs. The eggs are glued on the top of

the seed in storage; they are glossy and oval when fresh and hatch in about 3 – 5 days. After

moulting three times and reaching the fourth instar, the larvae construct a cell inside the seed

and pupate in it. The life cycle is completed in about 30 days (Messina, 1984). The damage is

done by larvae feeding inside the seed. Often farm storage for 6 months is accompanied by

about 30 percent loss in weight with up to 70 percent of the seeds being infested and virtually

unfit for consumption (Singh and Allen, 1980). For large-scale storage, efficient methods to

control bruchids have been developed, and these involve the use of proper storage facilities

and various fumigants. On subsistence farms, treatments with pirimiphos-methyl are suitable.

Wherever the produce can be fumigated under air tight conditions, phostoxin has been found

effective (Litsinger et al., 1983). Phostoxin treatment is effective against the eggs and larvae

inside the seed and does not have any residual effect. Therefore, produce has to be protected

from re-infestation in storage (Murdock et al., 1997). For subsistence farmers who produce

less than 10kg seeds for their own consumption, mixing the seed with groundnut oil (about 5

ml/kg of seed) were found practical and effective (Singh et al., 1979).

2.5 Pest management philosophy

Insects are considered pests because of the socioeconomic and medical threat they pose to

man and his property. Biologically, an insect is a pest because its population density and/or

damage level exceeds a pre-established or conceptualized threshold (the economic injury

level) below which the insect does not constitute an economic threat (Horn, 1986). The

economic injury level is defined as the lowest population or damage level capable of causing

economic impact (Poston et al., 1983). If the population of an organism exceeds the

economic injury level, the organism becomes a pest. When an insect is introduced into a

favorable environment, its population density tends to increase to the carrying capacity of the

14

resources. This is not usually exceeded because of the balance in environmental stress factors

(example predation, competition, and other natural mortality factors), constituting the

environmental resistance (Jackai and Adalla, 1997). The economic injury level is usually

below the carrying capacity of the resources. Maintaining a pest population below this level

may require some manipulation of planting dates, use of resistant cultivars, beneficial

organisms, insecticides, and cropping system arrangement. Usually, we do not let the damage

or population density of the pest reach levels that would result in economic loss before action

is taken. This resource damage level, or pest population density prior to the economic injury

level, is the economic or action threshold (Stern et al., 1959), or damage boundary (Pedigo,

1989). This is when control measures must be introduced, augmented, or applied to the

system (Horn, 1986; Metcalf and Luckmann, 1994).

Cowpea pest incidence and diversity dictate that no single control measure is likely to

produce satisfactory results. The “best mix” approach which involves the most logical

combination of different compatible tactics is advocated. This is what is simply termed,

intelligent pest management (Kitch et al., 1997). When several control methods are included

in a control programme, the amount of insecticide needed is reduced. However, to date no

integrated pest management programme have been properly packaged for cowpea pests in

Southeastern Nigeria. This is because the individual components have to be developed first

before they can be consolidated into a management package.

2.6 Host plant resistance

The use of cowpea cultivars that are resistant to attack by insects pest is one of the most

promising alternative control measures since it is economically and environmentally safe, and

can easily be integrated with other control measures (Alabi et al., 2003). Host Plant resistance

has been used as the principal tool for pest control in certain instances (Jackai and Singh,

1983). The control of aphids and leafhoppers can be achieved solely by the use of resistant

cowpea varieties. According to Singh et al. (1984), the most realistic approach to insect pest

management in cowpea is to combine insecticide spray and cultural practices with the

utilization of insect resistant varieties. Oghiakhe et al. (1995) found eight cultivars of

improved cowpea to be resistant to legume pod borer but exposure of the cultivars to the

entire pest complex without protection from insecticides gave zero yields.

15

2.7 Chemical control

Insect pests attack in cowpea if not controlled often leads to total yield loss (Singh and Allen,

1980). Insecticide use on cowpea has a long history (Booker, 1965; Jackai, 1983; Jackai et

al., 1985; Singh et al., 1990). It is the most widely known form of pest control on cowpea.

Traditional cowpea growers in Nigeria do not habitually use insecticides, as reflected in the

poor yields they obtain. In many countries in Asia, pest control is mainly insecticide based

and for many commercial growers it is the only way. It is not surprising that insecticide

resistance is already evident in certain areas (Jackai and Adalla, 1997). Singh and Allen

(1980) pointed out that if farmers use insecticides, they can improve the yield of their crop

tenfold. Yield losses due to insects could be reduced and seed yield increased by the use of

insecticides (Parh, 1993).

To optimize production without damaging the environment or endangering consumers, those

who use insecticides or are in a position to advise on their use, must consider, the feeding

behavior of the target pest, the activity cycle of the pest, especially the damaging stage, the

part of the plant affected, the mode of action of the chemical, the residual activity of the

compound, the phytotoxicity of the chemical at effective dosage, and the efficacy of the

compound (Jackai et al., 1985). Choosing a wrong chemical can lead to unexpected and

costly results, for example, applying monocrotophos to control Maruca borer would be

ineffective in controlling the pest (Jackai, 1983). The combined formulation of insecticides is

more effective against all the pests currently affecting cowpea in Africa than single,

conventional insecticide. The combined formulations are safer because it uses smaller

amounts of each active ingredient than are normally recommended (Singh et al., 1990). The

combined formulations have eliminated the need for farmers to purchase more than one

chemical and the need for them to decide whether, and when, to change from one single

chemical to another. Even though the dosages used in combined formulations are still some

what high, they are substantially lower than earlier recommended dosages with reduced risks

of man and the environment (Raheja, 1978; Ezueh, 1980: Litsinger et al., 1983).

Chemical control is the most readily available technology for the suppression of cowpea

pests, but it has disturbing consequences (Luck et al., 1977; Vanden Bosch, 1978).

Entomologists in several countries have stressed the need for developing integrated pest

management strategies to optimize agricultural production without adverse effect on the

environment (Singh et al., 1990).

16

Study conducted by IITA involving three varieties of thrips resistant varieties and susceptible

check under two levels of protection in two environments showed that there was no

significant yield differences found between the two levels of protection, (two sprays and four

sprays) for the resistant varieties. Many insecticides used on cowpea are foliar sprays, either

of emulsifiable concentrates (EC) or wettable powers (WP). Several of these chemicals are

effective against most cowpea pests, although there is greater specificity in some cases

against specific groups, a distinction related to the feeding behavior of the different pests

(Afun et al., 1991). The most commonly used insecticides include endosulfan, Lambda

cyhalothrin, cypermethrin, permethrin, and dimethoate (Jackai and Adalla, 1997). Despite

their differential efficacy, most of these chemicals will increase cowpea yields by at least

tenfold with 2-4 applications (Franks et al., 1987; Afun et al., 1991). The more versatile and

less expensive low volume knapsack sprayer has remained the dominant sprayer although it

is clearly less suitable because of the water needed for use especially in the drier savannas

where most cowpea is grown (Jackai and Adalla, 1997).

2.8 Post harvest storage

The principal storage pest of cowpea grain in sub-Saharan Africa is the cowpea beetle

Callosobruchus maculatus Walp. also known erroneously as the “cowpea weevil” (Taylor,

1981). In low resource farms, C. maculatus infestations start in the field and continue in

storage. In the field, gravid females deposit eggs on the surface of pods still hanging on the

plant. The females prefer mature green pods but will oviposit on dry, mature pods as well

(Messina, 1984). Females oviposit more readily on exposed grain as in cowpea lines whose

pods dehisce easily (Murdock et al., 1997). Larvae hatching from eggs on either seeds or

pods use their mouthparts to bore through the bottom of the chorion. They tunnel onwards

penetrating the pod wall or the seed testa. Larvae hatching from eggs laid on pod walls must

not only pass through the pod wall itself but must also gain entry into one of the seeds

enclosed by the pod wall. Difficulty in surmounting these physical barriers partly accounts

for the higher mortality of cowpea bruchids whose eggs are laid on pod walls compared to

those laid on cowpea grain (kitch et al., 1991). Within the seed, the larvae undergo four

instars, the longest of which is the fourth (Shade et al., 1990). The development from egg to

adult at 26OC and 55 percent relative humidity takes about 35 days in susceptible seeds.

Emerging females mate and lay viable eggs on the same day they emerge. Since each female

can produce about 21 female offspring that survive to adulthood in susceptible grain, the

population of bruchids in a cowpea store can grow exponentially in a few months (Taylor,

17

1981; Messina, 1984). Little is known about the applied ecology of C. maculatus.

Alternative host plants are known and include numerous wild species. The range of host

species anywhere is also poorly understood. Little is known about the distances adult cowpea

beetles actually cover, although it is established that there are two phases, a sedentary and an

active dispersing morph (Messina, 1987); the dispersing morph accumulates high levels of

lipid reserves, which supply it energy for dispersal (Nwanze et al., 1976). Besides C.

maculatus, there are numerous insect pests of cowpea in storage (Singh et al., 1990).

Infestations of an important one, Bruchidius atrolineatus Pic., begin in the field, like those of

C. maculatus. Unlike C. maculatus, the B. atrolineatus populations do not increase in storage;

instead, adults who emerge in grain stores enter a reproductive diapause until cowpea begins

to flower during the subsequent rainy season (Huignard et al., 1984). Another bruchid pest of

cowpea, ranked as nest in importance to C. maculatus, is Callusobruchus chinensis L.

(Taylor, 1981). Cowpea on sale in markets in sub-Saharan Africa often has bruchid

emergence holes. In most cases, such holes could be due to either C. maculatus or B.

atrolineatus.

The financial and nutritional losses of cowpea to storage pests in sub-Saharan Africa are not

well documented, but are clearly high. Low-resource farmers often sell their cowpea at

harvest, when prices are lowest in the year, partly because they anticipate storage losses.

Being aware of the storage problem, they are interested in better techniques for preserving

their grain after harvest (Taylor, 1981). Caswell (1984) has documented the loss of cowpea

grain during traditional post harvest storage in Nigeria. Pods stored for eight months had 50

percent of the grain damaged by bruchids, but when stored as grain, 82 percent of the grain

had one or more holes. Emergence holes represent insects that have developed and left the

seed, mated, and laid additional eggs, counting emergence holes is one way of assessing

bruchid damage. The next generation of larvae, more numerous yet, will generally still be

developing within the grain. Visits to virtually any village market in sub-Saharan Africa

reveal that the cowpeas for sale are typically damaged by bruchids. When the damage

exceeds one emergence hole per seed, the prize is usually discounted (Schulz, 1993).

2.9 Cultural practices and control

Pest problems on cowpea can be reduced through the use of methods that alter the

microenvironment of the pest, for example, species diversification, manipulation of planting

date and pest diversion (or trap cropping) (Wilken, 1972; Olufajo and Singh, 2002).

18

Companion cropping increases crop diversity, changes or modifies the insects habitat and

interferes with the insects identification of, and responses to, its host plant (Tahvanainen and

Root, 1972; Southwood and Way, 1970). Modifications that lead to the reduction of

populations of a pest have been referred to as cultural control or association resistance (Root,

1973). Many farmers in the tropics practice companion cropping involving a few to several

crops. The choice of crops has been governed primarily by the crops‟ contribution to diets

and subsistence rather than their effects on insect control. In other words cultural control of

insects has not been consciously practiced by most tropical farmers, and has not received the

attention it deserved from crops scientists (Kayumbo, 1976; Okigbo and Green land, 1976;

Richards, 1985; Litsinger and Ruhendi, 1984).

Cowpeas are mostly intercropped with maize, sorghum, millet and cassava, but occasionally

with cotton and groundnuts. Studies on the effects of companion cropping on insects pests

have been conducted in systems involving cowpea – maize, cowpea – sorghum, cowpea-

millet and cowpea – cassava (Olufajo and Singh, 2002). When cowpea is grown as a

monocrop, it is subjected to heavy depredation by insect pests and yields levels are low.

However, when intercropped, the populations of several pests are reduced and yields

increased (Singh and Emechebe, 1998; Mensah, 1997). Work conducted in Nigeria (Perfect

et al., 1978) and in Tanzania (Karel et al., 1982) showed that the populations of leaf hoopers,

Empoasca dolichi, Sericothrips occipitalis and Callosobruchus maculatus were reduced in

cowpea–maize intercrops. Similar trends were reported for flower thrips by Matteson (1982),

Ezueh and Taylor (1983). Damage by pod borer and Maruca testulalis, are not reduced by the

cropping system (Taylor, 1977; Perfect et al., 1978; IITA, 1982). Notable exception to this

assertion were reported by Seshu Reddy and Masyanga (1987) who claimed to have got a 46

percent reduction of M.vitrata in a 1:3 sorghum–cowpea intercrop. Karel et al. (1982)

working in Tanzania also reported less damage by flower thrips and the Maruca pod borer on

cowpea intercropped with maize. For pod sucking bugs (PSB) the reports have been mixed.

Perfect et al. (1978) and Matteson (1982) indicated a decrease in numbers of PSB in cowpea-

maize intercrop in South West Nigeria, whereas at other locations in same region increased

numbers had been associated with cowpea–maize and cowpea–sorghum intercrops

(Kayumbo, 1976; Ochieng, 1977; Perfect et al., 1978; Matteson, 1982). According to Ezueh

and Taylor (1983) simultaneous sowing of cowpea and maize appeared to increase infestation

by the borer. This is perhaps because higher humidity and relatively lower temperature

typical of intercropped cowpea are generally favorable to the borer (Oghiakhe et al., 1995).

19

There are other documented cases of pest population increase with intercropping, a classical

example being that of the foliage beetle, Ootheca mutabilis which feeds on cowpea foliage,

and its incidence is dependent on the onset and distribution of rainfall during the cropping

season (Kayumbo, 1976). This means that the populations of O.mutabilis can be quite

variable. In intercrops involving either cowpea and maize or cowpea and sorghum in

Tanzania the population of this insect has been found to increase (Kayumbo, 1976; Karel et

al., 1982). Increased shading is thought to be partly responsible for this observation

(Kayumbo, 1976). In northern Nigeria, Matteson (1982) also recorded higher population of

meloid beetles (Mylabris sp. and coryna sp.) on cowpea–maize intercrops than on monocrop

cowpea and suggested that the insects normally fed on maize pollen and then infested and

damage cowpea flowers as the maize was dying. Jackai (1983) found that intercropping of

two rows of cowpea with one of cassava reduced the populations of thrips and pod-sucking

bags. It did not affect Maruca borers. Similarly, results from Brazil showed an increase in

Maruca populations but reductions in flower thrips, foliage beetles (Diabrotica speciosa) and

leafhoppers (Empoasca Kraemeri) (Aidarand Kluthcouski, 1983). Cassava may be acting as a

physical barrier to movement of thrips or an alternative food sources for the pod bugs. It is

possible that the cassava is emanating chemicals or that the cowpea host becomes less

apparent to the insects (Trenbath, 1993). The shading from the associated crops adversely

affects cowpea performance and may also be responsible for the observed population

changes. In this system the humidity is known to increase and insolation is reduced inside the

crop canopy (IITA, 1982).

Decreases in pest populations have been attributed to a disruption of the insect‟s perception

of its host plant. Plant species diversity alters the host-selection repertoire involving vision,

Olfaction contacts (Southwood and Way, 1970; Tahvanainen and Root, 1972; Altieri et al.,

1978). In cowpea– maize or cowpea–sorghum intercrops, the factors that are suspected of

playing a vital and combined role in reducing pest population are, restriction of movement of

thips, leafhoppers, aphids; increase in canopy closure leading to increased humidity,

reduction in temperature and provision of greater shading for shelter; and increase in the

natural enemy populations leading to a net reduction in pest population (Jackai et al., 1985).

On the other hand the population increase in pests in intercrops have been attributed to the

reduction of the overall effort required for movement of insects that prefer different hosts,

example for ovipositor for feeding. For instance, the meloid beetles and some pod bugs

oviposit on maize but feed mostly on cowpea (Matteson, 1982; Ochieng, 1977).

20

Intercropping effectively reduces the time and energy required by the insect to move from

one host to another. Moreover, increased shading and humidity and reduced temperature

brought about by some crop mixtures favor high populations of some foliage beetles (Karel et

al., 1982). Mixed cropping was found to reduce cowpea aphids (Bottenberg et al., 1997),

thrips (Ezueh and Taylor, 1983; Kyamanywa and Ampofo, 1988; Alghali, 1993a;

Kyamanywa et al., 1993), and pod-sucking bugs (Alghali, 1993a). Maruca vitrata

populations move from South to north over a period of several months or generations,

following the northward progression of rainfall, cowpea planting, and possibly the flowering

pattern of leguminous trees. The farther north, the later the moths arrive; also, the fewer the

generations that can be completed, the lower the population buildup. M.vitrata does not

survive the dry season in the north, even if cowpea is available in the fadamas, probably

because of some unfavorable climate conditions other than the absence of rain, such as

temperature or relative humidity (Bottenberg et al., 1997). M. vitrata is a migratory pest,

which survives the dry season on alternative hosts in the more humid south and migrates to the

north following the pattern of rainfall and cowpea cultivation. Several studies have shown that

the population density of flower thips is consistently lower in cowpea intercropped with maize,

or sorghum (Matteson, 1982), cassava (Lawson and Jackai, 1987), and beans (Kyamanywa and

Ampofo, 1988), for exactly the same reasons that foster increase in the borer populations.

Kyamanywa and Ampofo (1988) have shown convincingly that shade, high humidity, and

lower temperatures keep the population of thrips down in intercropped cowpea and field beans.

Even though plant species diversity (crop-crop and weed–crop diversity) results in a reduction

of pest populations (Ballidawa, 1985), not all intercropping with cowpea confers entomological

advantage. For example, blister beetles (Meloidae) and pod and seed sucking bugs (Coreidae)

increased in population when cereals and cowpea were intercropped in Nigeria (Ochieng, 1977;

Matteson, 1982).

The lower and upper temperature thresholds for M. vitrata are 15.6 and 34OC, respectively

(Jackai and Inang, 1992). Flower thrips are known to survive the dry season in the southern

Benin Republic on a wide range of alternative hosts (Tamo et al., 1993). However,

unfavorable temperature extremes in northern Nigeria may suppress populations of flower

thrips during the dry season. Temperatures less than 15OC and greater than 35

OC severely

reduce survival of all developmental stages of flower thrips (Tamo, 1991). Alghali (1991b)

attributed crashes in thrips populations to mean daily temperatures greater than 30OC and

scotophases of less than 18h. Populations of clavigralla tomentosicollis were also very low on

21

cowpea during the dry season, but they increased rapidly during the wet season. Their pest

status may also be related to migratory movement from southern refugia and sensitivity to

unfavorable climatic conditions during the dry season (Bottenberg et al., 1997). Jackai and

Inang (1992) reported temperature thresholds of 18.5 and 37OC for C.tomentosicollis.

The value of manipulating the planting date as a package for optimizing cowpea productivity

have been confirmed, thus giving scientific credence to the traditional practice of planting

early in the season than late planting (Jackai et al., 1985). Summerfield et al. (1974) and Mc

Donald (1970) suggested that date of panting cowpea should be such that does not conflict

with the period when staple foods make high labour demands and that allows pods to mature

during dry, bright sunny weather. Experiment conducted in monomodal climates had shown

early planting, as soon as rains become well established in mid to late June, to be associated

with high grain yield (IITA – SAFGRAD, 1981, 1982, 1983). Such early planting would,

however, conflict with critical periods for planting and weeding cereals. It also would mean

that, in the northern guinea and sudan savannas, photoperiod–insensitive cultivars would

mature in August and early September under humid, cloudy weather that favours pod rots.

IITA–SAFGRAD program recommend planting cowpea in mid – July of every year. In

humid zones, Rachie and Robert (1974) recommended planting photo-period insensitive

cowpeas in late May and late August. They also recommended that photoperiod–sensitive

cowpeas should not be planted in the first season in bimodal rainfall regions. When cowpea is

planted in July they are likely to mature before the peak of infestation of Clavigralla

tomentosicollis (IITA, 1982). If an early maturing cowpea variety were planted early, it

should be able to avoid damage. In a study conducted in the Delmarva region of United

States using four different sowing dates, Javaid et al. (2005) reported increased grain yield

from the second sowing date treatment in both sprayed and unsprayed treatments.

A number of pests such as thrips and Maruca borer can not be effectively controlled or

avoided by planting early or using early maturing varieties, but the prevalence of pod-sucking

bugs seems to be more dependent on environmental triggers than on the phonological stage of

the plant. Host evasion is probably the most promising approach in controlling of pod

sucking bugs (Jackai, 1983). Variation in planting time could be explored as it may have

some scope in avoiding M. vitata attack (Taylor, 1967; Akingbohungbe, 1982; Alghali,

1993b). Planting early maturing cowpea in September at the end of rainy season after harvest

of cereal crop could be a feasible option (Blade and Singh, 1994). However, risk of late-

22

season drought may limit the adoption of this practice.

Isenmilla et al. (1981) reported that yield losses of cowpea intercropped with maize could be

reduced from 68 to 48 percent by proper choice of cultivar. IITA (1986) reported that cowpea

yields were reduced by only 41 percent in spreading cowpea intercropped with maize,

whereas the determinate, early cowpea sustained 54 percent yield loses. The detrimental

effect of shading on cowpea in association with cereals was demonstrated by Wahua (1983)

who showed that the more light is transmitted to cowpea the greater were its growth and

yield. Similar yield results were obtained from maize varieties intercropped with semi-

determinate and indeterminate cowpea (IITA, 1986). Adetiloye (1980) showed that yield of

semi erect and semi prostrate cowpea cultivars were reduced by an associated maize

intercrop. Adetiloye (1980) also reported that a cowpea cultivar with a climbing growth habit

performed satisfactorily in association with maize. Wien and Nangju (1976) reported that the

climbing cultivars caused increased lodging in maize and lowered maize yields much more

than do erect or spreading cowpea cultivars. Cowpea intercropped with maize having wide

range of growth habits consisting of short, intermediate height, and sturdy, spreading, tall

cultivars with leaf area index at 8 weeks after sowing as 4.2 for short, 5.4 for intermediate

and 5.7 for tall cultivars. Higher cowpea yields were realized in intercrops with the short

maize variety, but higher gross returns were obtained from the high-yielding, tall maize

variety. The portion of gross returns attributed to maize ranged from 70 to 82 percent (IITA,

1993). Cowpea significantly reduced weed dry weight and hence weed infestation in cowpea-

maize plot (IRRI, 1978). Maize cultivars that mature in 100 – 105 days were found less

suitable than early maturing varieties; they had a yield advantage over early varieties, but it

never exceeded 15 percent in good years, and they depressed cowpea yield by 30 percentage

more than early cultivars because of shading effects by tall cultivars (Muleba and Ezumah,

1985). Photo period–sensitive cowpea cultivars were more adapted to intercropping with

maize than were photoperiod – insensitive ones. The former flower after maize harvest at the

end of September or early October and thus form pods and mature when there is no

competition from maize. Good yields for both maize (>3tonne per hectares) and cowpea

(500-1500 kg/ha) had been repeatedly obtained in this system. In contrast, photoperiod –

insensitive cultivars flower and form pods while under maize cover (IITA – SAFGRAD,

1983).

23

2.10 Intercropping

Intercropping is the growing of two or more crops simultaneously on the same field in a year

irrespective of the spatial arrangement. The crops are not necessarily sown at exactly the

same time and their harvest time may be quite different, but they are simultaneous for a

significant part of their growing period (Andrews and Kassam, 1976; Willey, 1979).

Intercropping is characteristic of the small scale farming system in the tropics, and is

regarded by many researchers as a primitive system which would eventually be replaced by

sole cropping in the course of agricultural development (Willey, 1979). However, according

to Norman et al. (1982), the system is likely to remain a widespread practice in the coming

future because substantial evidence has been provided to suggest that yield advantages can be

achieved by intercropping to explain its continued persistence in the tropical Africa.

Numerous advantages have been highlighted for the continued practice of intercropping

which include profit maximization (Abalu, 1976), more efficient resource utilization, yield

stability and risk minimization (Okigbo and Greenland, 1976; Wien and Smithson, 1979). It

also suppresses weeds, thus reducing cost of weed control and improves the quality of the

products (Okigbo and Greenland, 1976). Willey and Osiru (1972) reported considerable

higher (38 percent) yield advantage from mixtures of maize and beans than could be achieved

by growing the two crops separately. Willey and Osiru (1972) attributed yield increase

however, to efficient environmental resources utilization and that the different heights of the

two crops produced a better light utilization.

The growth habit of the component crops is essential in practicing intercrop. Beefs (1975)

stated that an ideal intercropping combination is a deep rooted legume which can fix nitrogen

and a cereal with superficial root system requiring a large amount of nitrogen, so that the

nutrient and moisture requirements of the two crops are not the same and they do not occur at

the same time. Barker and Norman (1975) suggested that better use of resources such as

water by intercrops was probably a common cause of yield advantage in semi-Arid tropics

where moisture is usually a major limiting resource. Another consideration is leaf canopy

and light interception. Trenbath (1993) showed that photosynthetic-light use efficiency of the

canopy is the product of the proportion of the incident light that is intercepted and the

efficiency of the canopy. Trenbath (1993) suggested that intercropping should consist of an

upper canopy of small inclined leaves with maximum rate of leaf photosynthesis and lower

canopy of more horizontal leaves. Wien and Nangju (1976) reported that shading of cowpea

24

resulted in the reduction of number of nodes per plant and time to 50 percent flowering.

Shading during the vegetative period caused erect cowpea to lodge, thereby reducing the

grain yield by 46 percent and that climbing cultivar resulted in increased maize lodging and

lower maize yield than erect or spreading cultivars. Terao et al. (1997) advocated

simultaneous planting of cowpea and millet if there is no severe competition for water. Blade

et al. (1997) found that delayed planting of cowpea for two or three weeks resulted in a

reduction of cowpea grain yield of over 50 percent in comparison to simultaneous millet and

cowpea planting. Most of the reported work on maize-cowpea mixtures indicated a reduction

in cowpea yield while maize yields were unaffected (Haizel, 1974; Isenmilla et al., 1981;

Olufajo, 1988; Cardoso et al., 1993). However, the competitive effects from the maize

component could be reduced by sowing cowpea early. Myaka (1995) showed that when sown

four weeks after maize, cowpea yields were 67 percent less than cowpea planted two weeks

after maize.

2.11 Varieties adapted to intercropping system

Variety selection is a key to modifications that is required for profitability and productivity of

cropping system (Singh et al., 2002). This is especially relevant, as different plant traits are

required for cultivars intended for use under intercropping compared to those for use under

sole cropping (Nelson and Robichaux, 1997). Terao et al. (1997) pointed out that the type of

cowpea adapted to intercropping is the improved spreading type, improved to retain a

substantial root system and high translocation efficiency. The number of branches and nodes

and increased internodes length are plant traits that are important under intercropping (Nelson

and Robichaux, 1997). The cultivar with a busy-type habit has been reported to be higher

yielding under sole cropping, whereas the cultivar with a spreading habit was higher yielding

under intercropping (Nelson and Robichaux, 1997). Singh and Emechebe (1998) found some

good levels of performance of a number of improved varieties under both sole and

intercropping.

Short-duration, determinate cultivars fit well as an intercrop with maize, sorghum, pearl

millet, cassava, cotton, pigeon pea sugarcane, coconut and rubber. The cowpea crop should

mature in 60 days so that its yield will not be reduced by shading. It should also not compete

with the major staple food crop for moisture in the latter part of the rainy season so that full

field potential of the main crop is realized (Singh et al., 1983; Pandey and Ngarm, 1985).

25

2.12 Cowpea haulms as fodder for livestock

The use of cowpea as fodder is most advanced in Asia, especially India, where green

materials is used for grazing or, more commonly, cut and mixed with dry cereals for stall

feeding (Tarawali et al., 1997). Relwani (1970) recommended the use of cowpea in

combination with cereals for lactating cows, to maintain milk yields of 5 l/cow/day. Cowpea

fodder provides nutrition for farm animals during the dry season, which in turn provide milk

and meat for human consumption (Norman et al., 1982). Fodder production is not reduced by

flower thrips and M. vitrata damage (Suh and Simbi, 1983); it rather simulates higher fodder

production because photosynthates that would have been invested in flowers and pods are

used for foliage. Alghali (1991a) found that fodder production was enhanced by non

application of insecticides.

Insect pests significantly reduced the quality of cowpea fodder (Ram et al., 1990). Trials of

fodder varieties of cowpea in India gave dry matter yields of 4 t/ha, with crude protein

contents of up to 26 percent (Relwani et al., 1970). Bhatti et al. (1983) recommended forage

cowpea for use in Pakistan, recording dry-matter yields of 5.7 t/ha for the best variety. Dry

matter yields can be positively associated with days to flower. The longer vegetative period,

the more forage was produced (Tyagi et al., 1978). The number of leaves and branches were

positively correlated with green fodder yield (Ram et al., 1990). In Australia cowpea is

regarded primarily as a fodder crop with grain harvest being an exception (Tarawali et al.,

1997). Imrie and Butler (1983) found that seed yield is positively correlated with forage yield

in determinate cowpea accessions. In eastern and southern Africa cowpea is grown for human

consumption of its leaves and beans, whereas in West Africa cowpea fodder plays a major

role in the drier areas. In sudan and sahelian areas farmers plant cowpea varieties or use

intercropping arrangements which favor forage production (Steiner, 1982). At the first sign of

drought at the end of the rainy season the fodder is cut and rolled, with any grain produced

considered as bonus. Typical yields from farmers‟ fields are 400 – 500 kg/ha dry cowpea

fodder. Bundles of harvested fodder are stored on rooftops or on trees fork for use, and for

sale as “harawa” (feed supplement) in dry season (Singh, 1983; Tarawali et al., 1997). Singh

et al. (1994) reported that early and medium maturing varieties yielded higher grain but lower

fodder than late maturing and fodder-type cowpea varieties which yielded 5 t/ha of fodder

and less grain. This informed the farmer‟s practice of growing different cowpea varieties for

grain and for fodder production. If fodder is harvested late, when the dry season is already

underway, quality is poor (Tarawali et al., 1997). NIMET (2011) advocated an innovative

26

livestock feed production practices using appropriate crop options, harvesting, processing and

preservation of fodder to reduce communial clashes between farmers and cattle rearers.

2.13 Genotype by environment interaction

Annicchiarico (1997) stated that with regard to the comparison of plant material in a set of

multi-environment yield trials, the term genotype refers to a cultivar with material genetically

homogeneous, such as pure lines or clones, or heterogeneous, such as open-pollinated

populations, rather than to an individual‟s genetic make-up. The term environment relates to

the set of climatic, soil, biotic (pests and diseases) and management conditions in an

individual trial carried out at a given location in one year (in the case of annual crops) or over

several years (in the case of perennials). Cooper et al., (1996) reported that purely

environmental effects, reflecting the different ecological potential of sites and management

conditions, are not of direct concern for the breeding or recommendation of plant varieties.

Genotypic main effects (i.e. differences in mean yield between genotypes) provide the only

relevant information when genotype X environment interaction effects are absent or ignored.

The termed genotype-by-environment interaction (GXE) means that distinct genotypes may

vary in the degree to which their phenotypes are affected by environmental conditions. In

order word differences between genotypes may vary widely among environments in the

presence of GXE interaction effects (DeLacy et al., 1990). Furthermore, Baker (1988) stated

that GXE interactions are the failure of genotypes to achieve the same relative performance in

different environments. In general, GXE interactions are considered a hindrance to crop

improvement in a target region. Kang (1998) revealed that GXE interactions may offer

opportunities, especially in the selection and adoption of genotypes showing positive

interaction with the location and its prevailing environmental conditions (exploitation of

specific adaptation) or of genotypes with low frequency of poor yield or crop failure

(exploitation of yield stability). Growing awareness of the importance of GXE interactions

has led crop genotypes to be assessed in multi-environment and regional trials for cultivar

recommendation or for the final stages of elite breeding material selection. Simmonds (1991)

noted that GXE effects should not be ignored but rather analyzed using appropriate

techniques, in order to explore the potential opportunities and disadvantages. The information

from these trials can help breeding programmes to better understand the type and size of the

GXE interactions expected in a given region, and the reasons for their occurrence; and to

define, if necessary, a strategy to successfully cope with the effects of interactions.

27

The presence of the GXE interaction indicates that the phenotypic expression of one

genotype might be superior to another genotype in one environment but inferior in a different

environment (Falconer and Mackay, 1996). Crop yield fluctuates due to suitability of

varieties to different growing seasons or conditions. A specific genotype does not always

exhibit the same phenotypic characteristics under all environments and different genotypes

respond differently to a specific environment. Gene expression is subject to modification by

the environment; therefore, genotypic expression of the phenotype is environmentally

dependent (Kang, 1998). Inconsistent genotypic responses to environmental factors such as

temperature, soil moisture, soil type or fertility level from location to location and year to

year are a function of GXE interactions. Identification of yield-contributing traits and

knowledge of GXE interactions and yield stability are important for breeding new cultivars

with improved adaptation to the environmental constraints prevailing in the target

environments (Ceccarelli, 1996). Phenotypic traits are determined by a combination of

genetic and environmental influences. Even traits that have strong genetic determination can

be profoundly influenced by environmental conditions, such that the same genotype may

yield quantitatively or qualitatively different phenotypes in different environments (Stroup et

al., 1993). In a heterogeneous environment, GXE reduces the population-level

correspondence between genotype and phenotype. Since natural selection acts on phenotypes

but evolution occurs only through genetic change in populations, GXE reduces the global

efficiency of natural selection and can even result in the maintenance of polymorphism

(Lazzaro et al., 2008).

Genotype by environment (GXE) interactions is almost unanimously considered to be among

the major factors limiting response to selection and, in general, the efficiency of breeding

programs. GXE interactions become important when the rank of breeding lines changes in

different environments. This change in rank has been defined as crossover GXE interaction

(Baker, 1988). GXE interactions in general, and GXE interactions of crossover type in

particular, are considered to have a negative impact on the success of breeding programs,

because breeders search for a few widely adapted cultivars. Ceccarelli (1989) pointed out that

experimental evidence from a number of crops in different geographical areas suggests that

when different cultivars or breeding lines are tested in a sufficiently large environmental

range, GXE interactions of the crossover type are of common occurrence. However, many

breeders still believe that selection should be conducted under optimum conditions for plant

28

growth because these conditions maximize heritability (Ceccarelli, 1996). Consequently,

most selection work in developing countries, particularly in the early stages, is done in

favorable conditions or in high-input experiment stations. If there are GXE interactions of

crossover type, and the selection and the target environments lie at opposite sides of the

crossover point, breeding materials developed in favorable conditions or in high-input

experiment stations are not likely to perform well in difficult environments (Baker, 1988).

Farmers' participation in selection under their own environmental and agronomic conditions

is eventually envisaged as a way to maximize specific adaptation, and to speed up the transfer

of new cultivars and their adoption (Hildebrand, 1990). One important consequence of

breeding for specific adaptation is that the number of cultivars of a given crop grown at any

moment in time will be large and this will maintain more genetic diversity within a crop than

with breeding for broad adaptation. Breeding for sustainability has been defined as a process

of fitting cultivars to an environment instead of altering the environment (by adding fertilizer,

water, pesticides, etc.) to fit cultivars (Coffman and Smith, 1991). Also, it has been

recognized that the key to increased production with fewer external inputs, a condition which

is more self-sustaining, less harmful to the environment, and yet productive enough to meet

the increasing demand for food, will be through a reevaluation of the identification and use of

selection and testing environments (Bramel-Cox, et al., 1991).

Large GXE interactions have frequently been reported between pairs of environments with

contrasting levels of one major stress, defined as “favourable” when characterized by low

stress and high mean yield and “unfavourable” with high stress and low yield (Ceccarelli,

1989; Bramel-Cox, 1996). However, large interactions may also occur between pairs of

unfavourable environments and even between pairs of moderately favourable environments

possessing similar mean yield but with differing combinations of stresses or patterns of one

major stress (Annicchiarico, 1997).

2.14 Genotype and genotype by environment (GGE) biplot

Yan and Kang (2003) pointed out that the evaluation of crop varieties is conducted to

compare multiple genotypes in multiple environments for multiple traits, resulting in

genotype by environment by trait three-way data. Variety trials provide essential information

for selecting and recommending crop cultivars. However, variety trial data are rarely utilized

to their full capacity. Although data may be collected for many traits, analysis may be limited

to a single trait usually yield, and information on other traits is often left unexplored.

29

Analysis of genotype by environment data is often limited to genotype evaluation based on

genotype main effect (G) while genotype-by-environment interaction (GE) are treated as

noise or a confounding factor. Although research on GE has contributed considerably to the

understanding of this issue, there remains a gap in how GE is measured among different

practitioners (Yan, 2001).

Yan et al. (2000) said that this gap may be partially bridged by the advent of biplot analysis

methodology. A biplot is a scatter plot that approximates and graphically displays a two-way

table by both its row and column factors such that relationships among the row factors,

relationship among the column factors, and the underlying interactions between the row and

column factors can be visualized simultaneously. Since its first report by Gabriel (1971),

biplots have been used in visual data analysis by scientists of all disciplines, from economic,

sociology, business, medicine, to ecology, genetics, and agronomy. A common

misconception is that biplot analysis equivalent to principal component analysis (PCA).

While both biplot and PCA use Singular Value Decomposition (SVD) (Pearson 1901) as a

key mathematical technique, biplot analysis is a fuller use of SVD to allow two interacting

factors to be visualized simultanaousely. Yan and Nicholas (2006) noted that the term GGE

emphasizes the understanding that G and GE are the two sources of variation that are relevant

to genotype evaluation and must be considered simultaneously for appropriate genotype and

test environment evaluation. Yan and Kang (2003) stated that a user-friendly software

package for biplot analysis that is dedicated to simplifying the selection and construction of

accurate biplot diagrams has been developed. This software performs biplot analysis of

genotype by environment tables and other types of two-way tables, genotype by environment

by trait three-way tables, and year by location by genotype by trait four-way tables. It creates

an interactive analysis environment that is intended to be simple and informative, particularly

for researchers with limited training in statistics and computer application (Yan, 2001).

30

CHAPTER THREE

MATERIALS AND METHODS

3.1 Genotype, soil and weather description and characterization of the experimental

sites

3.1.1 Genotype description

The materials used in this study (Table 1) consisted of 10 genotypes made up of nine elite

genotypes and one local variety used as check. All the improved genotypes were collected

from IITA while the local variety was collected from the location where the experiment was

conducted. The nine genotypes were the best performers out of the 14 cowpea genotypes

evaluated in four states in Southeastern Nigeria in 2006. One out of the ten genotypes was

photo-sensitive while the remaining nine where photo-insensitive. Maturity attributes ranged

from early to late with five genotypes in early and three in medium categories while two

genotypes fell under late maturing category. Different growth habits were expressed by all

the genotypes including prostrate indeterminate, erect determinate, semi-prostrate

determinate, erect semi-determinate, and prostrate determinate. The 100 seed weight ranged

from 12-20 g. Five genotypes were brown seeded while the other five were white seeded.

Seed texture ranged from smooth to rough. Based on these features therefore, there is obvious

evidence that the genotypes used for this study varied considerably from each other with

respect to key cowpea plant traits.

3.1.2 Soil characterization

The status of the soils was evaluated using soil test (Table 2). Both physical and chemical

parameters were used in the assessement of the fertility of the soils of the various study sites.

The soil test was conducted at the Department of Soil Science Laboratory, University of

Nigeria, Nsukka. The chemical parameters included pH, exchangeable bases, cation exchange

capacity, organic carbon (as an index of organic matter), base saturation, total nitrogen and

available phosphorus. Soil texture varied in all the sites used for the study, and ranged from

sandy loam in Ishiagu to sandy in Mgbakwu and loamy in Ako location.

31

Table 1: The origin and description of the genotypes used in this study

NPS - Non- Photosensitive

PS - Photosensitive

Genotype Origin Photo-

Sensitivity

Maturity Growth habit 100Seed

weight(g)

Seed

coat colour

Seed

texture

IT 98K - 131 - 2 IITA NPS Medium Prostrate, indeterminate 16 Brown Rough

IT 84S - 2246 - 4 IITA NPS Early Erect, determinate 12 Brown Rough

IT 90K - 82 - 2 IITA NPS Early Erect, determinate 12 Brown Rough

IT 97K - 568 - 18 IITA NPS Medium Prostrate, indeterminate 16 Brown Rough

IT 98K - 205 - 8 IITA NPS Early Semi-Prostrate, determinate 16 White Rough


IT 97K - 556 - 4 IITA NPS Late Erect, semi-determinate 18 Brown Smooth

IT 90K - 277 - 2 IITA NPS Medium Prostrate, indeterminate 20 White Rough


Local Check Landrace PS Late Prostrate, indeterminate 17 White Rough

32

Ishiagu and Mgbakwu soils had the highest percentage of sand making it inherently porous

and consequently low in moisture retention compared to Ako with low percentage of sand (23

percent), higher organic matter content (2.57 percent), higher silt content (39 percent), and

consequently higher moisture retention and cation exchange capacity (20). Ishiagu and

Mgbakwu possessed lower organic carbon percent of 0.19 and 0.65, organic matter percent of

0.33 and 1.12 respectively compared to Ako with organic carbon percent of 2.57 and organic

matter percent of 4.42. Similarly, Ako location had higher total nitrogen, phosphorus, base

saturation and exchangeable calcium, and consequently had higher nutrient concentration and

its medium pH value was most ideal for cowpea production. Mgbakwu soil was acidic (4.6)

and consequently nutritionally poorer with the tendency to tie up some useful micro-

nutrients, while releasing in excess heavy metals such as aluminium.

3.1.3 Weather description

The weather variables of the experimental sites which included rainfall, air temperature and

relative humidity were collected from near by weather station and presented in Table 3. The

rainfall pattern at the three sites are bi-modal with mean monthly rainfall at Mgbakwu being

(130.9 mm) for 2007 and (136.5 mm) for 2008; Ishiagu (139.8 mm) for 2007 and (162.8 mm)

for 2008 and Ako (153.9 mm) for 2009 and (136.3 mm) for 2010. Annual rainfall pattern and

monthly distribution differed across the study sites with highest monthly rainfall occurring

between the month of June and September. The rainfall is well distributed over the length of

the growing season of about 180 – 215 days, between May and October, and therefore

adequate for two cycles of cowpea crop growth.

Temperatures in Mgbakwu, Ishiagu and Ako ranged between 28 oC – 35

oC; 29

oC – 36

oC

and 28 oC – 34

oC respectively. The lowest temperature was expressed from the month of

July to September and rises steadily from the month of October and reaches the peak in

March. On the other hand, relative humidity followed a reversed order with temperature, with

the highest relative humidity occurring from the month of July to September and decreases

gradually from the month of October to May with the lowest occurring between the month of

January and March. Precipitation, air temperature and relative humidity have significant

impact on insect pest dynamics, and consequently crop performance and quality attributes.

Rainfall, temperature and relative humidity differed among the three locations during the

crop growth periods.

33

Table 2: Soil physical and chemical properties of the experimental sites

Soil properties Ishiagu Mgbakwu Ako

Physical properties

Clay (%)

12

12

18

Silt (%) 13 9 39

Fine Sand (%) 47 26 20

Coarse Sand (%) 28 53 23

Textural Class Sandy loam Sandy Loamy

Chemical properties

pH in Water 6.0 4.6 5.6

pH in Kcl 5.1 4.1 4.9

Organic Carbon (%) 0.19 0.65 2.57

Organic Matter (%) 0.33 1.12 4.42

Total nitrogen (%) 0.042 0.028 0.154

Total phosphorous (ppm) 10.26 10.26 13.06

Base saturation (%) 23.58 29.27 33.35

Exchangeable bases in

Meq/100g Soil

Sodium 0.38 0.38 0.51

Potassium 0.05 0.03 0.16

Calcium 1.8 1.4 4.2

Magnesium 0.6 1.0 1.8

CEC 12.0 9.6 20.0

34

Table 3: Rainfall (mm), Temperature (oC) and Relative humidity (percent) of the study sites

Location

Year

Variable

Months

______________________________________________________________________________________

Total

Mean

Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec.

Ishiagu 2007 Rainfall 0.0 0.0 62.6 31.5 357.1 134.2 179.2 321.8 295.3 197.7 98.1 0.0 1677.5 139.8

Temperature 33 34 36 32 32 34 30 29 29 31 32 32 - 32

Rel.

Humidity

56 65 68 84 89 88 90 96 94 80 77 69 - 80

2008 Rainfall 0.0 0.0 56.6 189.9 403.1 228.2 302 368.9 317.1 79.4 7.9 1.0 1954.1 162.8

Temperature 32 33 34 31 31 30 29 29 29 31 32 33 - 31 Rel.

Humidity

58 56 67 86 88 90 92 96 97 91 888 79 - 82

Mgbakwu 2007 Rainfall 0.0 9.9 39.1 121.7 193.6 327.7 63.0 323.6 169.7 267.2 55.1 0.0 1571 130.9

Temperature 33 35 35 33 31 29 29 28 28 30 30 32 - 31

Rel.

Humidity

55 71 70 75 76 78 79 79 78 77 76 69 - 74

2008 Rainfall 0.0 0.0 61.2 143.3 254.0 186.4 246 203.2 326 198.6 8.4 11.0 1638.1 136.5

Temperature 31 34 34 32 31 30 29 28 28 30 31 32 - 31

Rel. Humidity

56 57 74 75 75 77 78 80 79 76 75 73 - 73

Ako 2009 Rainfall 53.6 2.2 0.0 180.6 283.7 152.4 248.2 260.3 175.8 387.1 103.2 0.0 1847.1 153.9

Temperature 32 33 34 32 30 29 29 28 28 28 30 33 - 31

Rel.

Humidity

71 73 73 76 74 75 75 75 75 75 64 65 - 73

2010 Rainfall 0.0 0.0 43.9 161.8 212.3 247.4 158.5 404.2 204.0 183.6 19.3 0.0 1635 136.3

Temperature 33 34 34 33 30 29 28 28 28 29 30 32 - 31

Rel.

Humidity

67 72 71 73 74 76 77 77 77 76 74 61 - 73

35

3.2 Experiment One: The effects of chemical spray regime and genotype on cowpea

productivity

3.2.1 Experimental Sites

The first location was the research farm of the College of Agriculture, Mgbakwu in Anambra

State (060 17ʹN, 07

0 04ʹE; 83m asl) whereas, the second location was the experimental farm

of the Federal College of Agriculture, Ishiagu in Ebonyi State (050 58ʹN, 07

0 34ʹE; 197 m

asl).

3.2.2 Sowing Dates

Early and late season sowing dates were observed for the two years and in the two locations.

In 2007, the experiments were established on July 23 for early season sowing and September

4 for late season sowing in Mgbakwu while in Ishiagu location, sowing was done on July 31

and September 12 for early and late season sowing respectively. In 2008, the experiment was

established in Mgbakwu on July 21 and September 15 while sowing in Ishiagu was carried

out on July 24 and September 12 for early and late season sowing respectively.

3.2.3 Experimental design, treatments and treatment allocation

The experiment was a split-plot arranged in a randomized complete block design (RCBD)

with insect control treatment as the main treatment plot while genotype constituted the sub-

plot treatment. The experiment was replicated three times on a four row plots of 2 meter long

per plot. In each location, year and season, the experimental fields were divided into six

blocks consisting of two blocks per replicate. Each replicate consisted of two treatment levels

of either insecticide spray treatment or zero spray treatment which constituted the main plot.

Each treatment level (insecticide spray treatment or zero spray treatment) was further sub-

divided into ten plots with the ten cowpea genotypes assigned randomly to the plots as sub-

plot treatment. Each of the treatment blocks was separated by 1-meter alley to control drift of

insecticides to uncontrolled plots in the neighboring block. Also, spray operation was done

early in the morning when wind action was minimal. The treatments were established across

two locations, over a period of two years and two seasons per year. Insecticide applications

were made during the crop growth period. A full dose of 100 ml of insecticide, cypermethrin

and dimethoate mixture containing 30 g and 250 g active ingredients respectively, were

applied using 15 litres knapsack sprayer.

36

3.2.4 Cultural Operations

The experimental plot was ploughed, harrowed and manually ridged. Prior to ridging, a basal

dose of 100 kg NPK 15-15-15 per hectare plus 1000 kg per hectare of well cured cow dung

was broadcast uniformly and later incorporated into the soil and ridges made thereafter. Seed

was dressed with fungicide (seed-plus) at the rate of one sachet (10 g) to two kg of seed.

Inter-row spacing was 75 cm while intra row spacing was 25 cm, 2-3 whole-seeds per hill

were sown at 3-5 cm depth. Each plot consisted of four rows of two meter long while net plot

was the inner two rows (1.5 x 2 m) made up of about 32 plants per plot. Each plots and block

were carefully labeled to avoid confusion during spray and data collection exercise. Plants

were thinned to two stands per hill two weeks after crop emergence. Weeds were manually

controlled as regularly as they appeared while other agronomic practices were carried out as

recommended.

3.2.5 Data Collection

The data were collected from the inner two rows in each replicate. Destructive sampling was

carried out on the plants within the outer two rows. Observation were recorded on 22

different agronomic and six entomological variables. The agronomic parameters collected

included, number of hills, number of plant per stand, 50 percent days to flowering, number of

leaves at full bloom, peduncle length, number of internodes, days to maturity, duration of

grain filling period, pod weight, seed weight, fresh fodder weight, dry fodder weight, 100

seed weight, number of nodules at full bloom, pod length, number of seeds per pod, vine

length, taproot length at full bloom, number of branches, grain yield per hectare, threshing

percentage and harvest index. The insect pest data sampled included, Ootheca score, aphid

score, thrips count, Maruca count, pod sucking bug count and bruchids count.

The two inner rows were used for sampling insects in each plot. Five flowers were randomly

picked from each plot during the morning hours and placed in vials containing 30 percent

alcohol. The samples were thereafter dissected and the number of flower thrips (M. sjostedti)

and Maruca borer (M. vitrata) determined. Pod-sucking bugs (Clavigralla shadabi) were

counted in the two middle rows when the insects were observed on the field. Ootheca

mutabilis and cowpea aphids (Aphis craccivora) were scored on a scale of 1-5, where 1= no

sign of damage, 2 = 25 percent damaged, 3 = 50 percent damaged, 4 = 75 percent damaged

and 5= 100 percent damaged (Amatobi, 1994). A total of 100 seeds from each plot were

37

randomly selected and enclosed in a paper envelop and kept under room temperature in order

to determine bruchids (Callosobruchus maculatus) damage. The damage by bruchids was

determined by counting the number of seeds with bruchids holes out of the 100 randomly

selected seeds. The sampling was carried out after three months storage period from the time

of crop harvest.

The detailed procedures employed in the overall data collection are provided below:

Number of hills: This was determined by counting the number of hills with at least one

seedling.

Number of plant stand: This was determined by counting all the seedlings per net plot at

thinning. It is an index of plant establishment and determines the degree of plant population.

Days to 50 percent bloom: Measured as days from planting to when 50 percent of the plants

have attained 50 percent flowering within the net plot.

Number of leaves at full bloom: Determined as total number of leaves at full bloom

averaged over five randomly selected plants.

Peduncle length: This was measured from the base of the peduncle to its tip using meter

ruler averaged over five randomly selected plants and recorded in centimeter.

Number of internodes: This is the number of internodes from the plant base to the tip of the main

stem.

Days to maturity: Measured as days from planting to the day when 90 percent of the pods

have dried.

Duration of grain filling period: Measured as days from 50 percent bloom to when the pods

have reached physiological maturity (when the pod starts showing sign of drying).

Pod weight: All the pods harvested from the net plot were dried and the weight determined

using a digital weighing scale (mettler balance) and expressed in grammes.

Seed weight: After threshing the dried pods from the net plot and winnowed, the seeds were

weighed using digital weighing scale and expressed in grammes.

Fresh fodder weight: Immediately after harvesting the pods, the plants were cut at ground

level using sharp cutlass, bundled and weighed using top loading scale and weight expressed

in grammes.

Dry fodder weight: The fresh fodder was sun dried and weighed using top loading scale to

determine dry fodder weight in grammes.

100 seed weight: 100 randomly selected seeds were weighed in grammes using digital meter

scale.

38

Number of nodules: This was determined by counting the number of nodules at full bloom.

Each plant was carefully dug out from the ground making sure that the roots are not damaged

and the number of nodules counted and averaged over five selected plants.

Number of pod per plant: All the matured pods per plant were harvested and physically

counted and averaged over five plants.

Pod length: The length of five randomly selected pods per plot was measured using a meter

rule and average length per pod expressed in centimeters.

Number of seeds per pod: The total number of seeds in each pod was physically counted

and averaged over five pods.

Vine length: The lengths of individual plants were measured in centimeter from the ground

level to the growing tip at the time of harvest.

Taproot length at full bloom: Each of the plant used for determining tap root length were

carefully excavated to ensure that the tap root does not get damaged. The tap root was

measured from the base of the root to the tip of the tap root using meter rule and expressed in

centimeter.

Number of branches: Number of branches was counted from each of the five randomly

selected plants and average determined.

Grain yield (Kg/ha) = (plot yield (Kg) X 10,000)/plot size in square meters

Threshing percentage: This was calculated from each plot using the following formula:

Grain weight X 100

Pod weight

Harvest Index (HI): This was estimated using the method below:

Economic Yield (grain weight) X 100

Biological Yield (fodder weight)

3.2.6 Statistical analysis

Data collected were subjected to analysis of variance (ANOVA) using GENSTAT Discovery

Edition 2 (GENSTAT, 2005) procedures as outlined for RCBD. Insect counts and scores

were square root transformed (Steel and Torrie, 1980) before analysis. Difference among

39

treatment means were compared using F-LSD (P = 0.05) as described by Obi (1986).

Interaction of genotype by environment, genotype by traits and environment by traits were

computed using GGE biplot analytical model (Yan et al., 2000).

3.3 Experiment Two: The effects of cropping systems and number of insecticide

application on productivity of five cowpea genotypes

3.3.1 Experimental Site

The second experiment was conducted at the DEMACCO Integrated Farms Ltd., Ako, Nike

in Enugu State (060 34ʹN, 07

0 35ʹE; 154 m asl).

3.3.2 Sowing dates

This experiment was conducted in 2009 and 2010. In each year early and late season sowing

dates were observed. Similar sowing dates were observed for the two years with early season

sowing on June 18 while late season sowing date was done in August 30.

3.3.3 Experimental design, treatments and treatment allocation.

In each of the two planting seasons, the experiment was split-split plot arranged in a

randomized complete block design (RCBD). Cropping system constituted the main-plot,

number of insect control as the sub-plot while genotypes constituted the sub-sub-plot

treatment. Four promising genotypes selected from experiment one were used for this

experiment. They included IT97K-499-35, IT97K-568-18, IT98K-131-2, and IT93K-452-1.

A local variety was used as control making a total of five test entries. An IITA released open

pollinated maize variety (ACR 9931) was used for the intercrop along with the selected

cowpea genotypes. The five-cowpea genotypes in addition to the maize variety were sown in

one location over a period of two years and two seasons in each year. Each treatment was

replicated three times on four rows plot of 2 m long with 1m alley. In each season, for the

three replications, and for both sole and intercrop the experimental field was divided into six

blocks. Each replicate is made up of two blocks consisting of either intercrop or sole crop

systems as main plot, also each level of system was sub-divided into four plots with the four

levels of insecticide treatment (i.e. zero spray, one spray at flower bud initiation, two sprays

one at flower bud initiation and full bloom, and three sprays one at flower bud initiation, full

40

bloom and 50 percent podding stages) randomized and assigned to each of the plots as sub-

plot treatment. Also each of the levels of insecticide treatment were further split into five

plots and the five genotypes assigned to each plot randomly as sub-sub-plot treatment.

Cowpea and maize intercrop row arrangement consisted of two rows of maize to two rows of

cowpea per plot while cowpea and maize sole crop were established on a four row plot each.

Similar inter and intra row spacing were observed for both crops in the two systems as

applied in experiment one. Cowpea and maize were sown simultaneously. Insecticide was

applied during crop growth stages when insect pest pressure was usually high (flower bud

initiation, full bloom and 50 percent podding) which are the critical periods for insect control

(Taylor, 1978).

3.3.4 Cultural practices

The maize seed was treated with seed plus at the rate of one sachet (10 g) to 1 kg of maize

seed. Two seeds of maize were planted per hill and later thinned down to one seedling per

hill. Basal application of fertilizer and manure (as in experiment one) was same for cowpea

and maize. However, 100 kg of urea per hectare was top dressed to only maize three weeks

after planting. Type of insecticide, dosage, techniques used in application, and spray

equipment used were the same with that of experiment one.

3.3.5 Data collection

Methods of data collection on cowpea were the same as in experiment one.

The following data were collected on maize:

Ear Length: The length of five ears was measured using meter rule from the ear tip to the

base and mean value determined for each plot.

Ear number: Number of ears per net plot.

Plant stand establishment: This was measured by counting all the seedlings per net plot at

thinning.

Days to 50 percent bloom: Measured by the number of days from planting to when 50

percent of the plants had flowered.

Days to maturity: Measured by the number of days to physiological maturity when the black

layer has formed at the helium of the seed.

Plant height: Measured from the ground level to the plant apex using meter rule at maturity.

Ear Weight: Determined by weighing the total number of ears harvested per net plot after

41

drying.

Seed weight: Measured after threshing using digital weighing scale.

100 Seed weight: 100 seeds randomly selected from each plot were counted and weighed

using digital weighing scale.

Seed yield: Yield from each plot was determined and then expressed into kg ha-1

as in

experiment one.

Stover Yield: Stover from net plot was weighed after drying using top loading scale.

Threshing percentage: Grain weight X 100

Ear weight

Harvest Index (HI): This was estimated using the method described below:

HI = Grain weight X 100

Stover weight.

3.4 Statistical analysis

The statistical analysis was the same with experiment one.

42

CHAPTER FOUR

RESULTS

4.1 Test of significance of growth, reproductive, grain yield and yield components

and insect damage responses

Analysis of variance (ANOVA) for test of significant effects of sources of variation, were

investigated. The ANOVA test of significance were carried out for early and late season

combined in Ishiagu in 2007, early and late season combined in Ishiagu in 2008, early season

combined over 2007 and 2008 in Ishiagu, late season combined over 2007 and 2008 in

Ishiagu, early and late season combined in Mgbakwu in 2007, early and late season combined

in Mgbakwu in 2008, early season combined over 2007 and 2008 in Mgbakwu, late season

combined over 2007 and 2008 in Mgbakwu (Appendices 1-24). Variances were partitioned

into main and interaction effects. Interaction effect was sub-divided into first and second

order interactions.

Early and late season combined analysis in Ishiagu in 2007

Variances due to insect protection (IP), genotype (G) and season (S) main effects for growth

components were highly (P<0.001) significant for all the traits studied except dry fodder

weight (DFWT), fresh fodder weight (FFWT), number of branches (NBRANCH); number of

hills (NHILL), number of internodes (INTERNODE), number of leaves (NLEAF), number of

nodule (NNODULE), peduncle length (PEDLT), root length (RTLENGTH) and vine length

(VINELTH) for insect protection main effect; root length (RTLENGTH) for genotype main

effect and number of branches (NBRANCH), number of hill (NHILL), root length

(RTLENGTH) and days to pod filling (PODFILL) for season main effects.

Variance due to first order interaction (insect protection X genotype), (insect protection X

season) and (genotype X season) varied widely for growth components. Insect protection X

genotype (IP X G) variance was non significant for most growth parameters except number

of nodules, root length and vine length that were highly (P<0.001) significant. Variance due

to insect protection X season (IP X S) was highly (P<0.001) significant for dry fodder weight,

fresh fodder weight, maturity, number of hills, root length, vine length and days to pod filling

while the genotype X season (G X S) variance was highly significant (P<0.001) for most of

43

the traits studied but not for the number of hills, number of leaves, number of nodules and

root length. Second order interaction – insect protection X genotype X season (IP X G X S)

variance was highly significant for most of the traits studies except days to bloom, dry fodder

weight, maturity, number of branches, number of nodules, number of stand, root length, vine

length and days to pod filling.

Variances due to insect protection, genotype and season main effects for reproductive and

grain yield components were highly (P<0.001 percent) significant for most of the traits

sampled except days to pod filling which was affected by seasonal component. First order

interaction were non-significant for most of the traits studies except pod length for IP X G.

Interaction IP X S and G X S were highly significant (P<0.001) for most of the traits studied

except number of pod per plant for G X S interaction. Second order interaction (IP X G X S)

was non-significant for all traits except threshing percentage that was highly significant

(P<0.001). Insect protection, genotype and season main effects for insect damage were highly

significant (P<0.001) for most of the traits except aphid score, Maruca count, pod sucking

bug score and thrips count for genotype and bruchids count for season. Insect protection X

genotype was non-significant for all the traits. Variance due to insect protection X season was

highly significant (P<0.001) for most of the traits except thrips while variance due to

genotype X season were non significant for all the traits except Ootheca score which was

highly significant (P<0.001). Second order interaction (insect protection X genotype by

season) variance was non-significant for most of the traits except bruchids count which was

highly significant (P<0.001).

Early and late season combined analysis in Ishiagu in 2008

Variances due to insect protection, genotype and season main effects for growth components

were highly significant (P<0.001) for most of the traits except number of branches, internode

length, number of leaves, number of plant stand, peduncle length, root length and vine length

for insect protection, number of hill for genotype and number of branches, internode length,

number of leaves and root length for season main effect. Variance due to insect protection X

genotype are highly significant (P<0.001) for most of traits except number of nodules,

number of stand and peduncle length, insect protection X season are highly significant

(P<0.001) for most of the traits except dry fodder weight, fresh fodder weight, number of hill,

internode length, number of stand and peduncle length while genotype X season first order

interaction variance are highly significant (P<0.001) except number of hills, internode length,

44

number of leaves, number of nodules, number of plant stand, root length and vine length.

Variance due to second order interaction (insect protection X genotype by season) were

highly significant (P<0.001) for most of traits except fresh fodder weight, number of

branches, number of hill, internode length, number of plant stand, and vine length.

Variances due to main and interaction effects for reproductive and grain yield component are

presented. The main effects of insect protection, genotype and season variances are highly

significant (P<0.001) for most of the traits except days to 50 percent bloom, number of pod

per plant and pod length for insect protection main effect, days to 50 percent bloom, days to

maturity, number of seed per pod, days to pod filling and harvest index for season main

effect. Interaction due to first order effect are highly significant (P<0.001) for most of the

traits except days to 50 percent bloom and number of seed per pod for insect protection X

genotype, number of seeds per pod and pod length for insect protection X season and number

of pod per plant and harvest index for genotype X season efforts. Variance due to second

order interaction was highly significant (P<0.001) for most of the traits except harvest index.

Variances due to insect protection, genotype and season main effect for insect damage is

presented on Appendix 6. Effects due to the three main effects were highly

significant(P<0.001) for most of the traits except Ootheca score for insect protection,

Maruca count and Ootheca score for genotype and aphids for season main effect. First order

interaction variance are non significant for most of the traits except aphids and Maruca that

are highly significant for insect protection X genotype, bruchid count for insect protection X

season while variance due to genotype X season were non significant except pod sucking buy

score and thrip count that were higher significant (P<0.001). Variance due to second order

interaction is highly significant (P<0.001) except aphid score, bruchid count, and Ootheca

score.

Early season combined analysis over 2007 and 2008 in Ishiagu

ANOVA due to insect protection, genotype and year main effects for growth component in

early season were non significant for insect protection X most of the traits except number of

plant stand that was significant. Genotypic main effect was highly significant (P<0.001) for

all the traits while variance due to year effects was highly significant (P<0.001) for most of

the traits except number of branches and number of nodules. Second order interaction were

non significant for all the traits in insect protection X genotype, highly significant (P<0.001)

for most of the traits except dry fodder weight, number of hills, number of internodes,

45

number of leaves, peduncle length and vine length for insect protection X year effects while

genotype X year effects was highly significant (P<0.001) for most of the traits except number

of branches, number of leaves, peduncle length and root length. Insect protection X genotype

X year third order effects was highly significant (P<0.001) for most of the traits except inter

node length, number of leaves, number of stand, peduncle length and vine length.

Variance due to main and interaction effects in early season for reproductive and grain yield

component is presented. Main effects variance were highly significant (P<0.001) for most of

the traits except days to 50 percent bloom, days to maturity, 100 seed weight, number of pod

per plant, number of seed per pod, pod length, threshing percentage and harvest index;

genotypic effect was highly significant (P<0.001) for all the traits, while variance due to year

effects was highly significant (P<0.001) for most of the traits except number of seeds per

pod. First and second order interactions were mainly non significant for all the traits except

days to maturity, days to pod fill, pod length and harvest index that were significant for IP X

G, highly significant (P<0.001) for most of the traits except number of pods per plant,

number of seeds per pod, pod length, threshingpercentage and harvest index for IP X Y while

variance due to G X Y was highly significant (P<0.001) for most of the traits except days to

maturity, number of pods per plant, number of seeds per pod, pod length and harvest index.

IP X G X Y effects was highly significant (P<0.001) for most of the traits except days to 50

percent bloom, days to pod filling, number of pods plant, number of seeds per pod, pod

length harvest index

Variance due to insect protection, genotype and year main effects due to insect damage is

presented. Variance due to insect protection is highly significant (P<0.001) for most of the

traits except pod sucking bugs, highly significant (P<0.001) for most of the traits except

aphid score, Maruca count and pod sucking bug for genotype effects and for year effects,

variance is highly significant (P<0.001) for all the traits. Second order interaction is non

significant for most of the traits except thrip count that was highly significant (P<0.001).

Late season combined over 2007 and 2008 in Ishiagu.

Variance due to main effects (insect protection, genotype and year) effects in late season for

growth component is presented. Insect protection variance is non significant for most of the

traits except fresh fodder weight, number of leaves, and number of stand, variance due to

genotype is highly significant (P<0.001) for all the traits while year effect is highly

46

significant (P<0.001) for most of the traits except dry folder weight. Interaction due to first

order effects were highly significant (P<0.001) for most of the traits except number of

branch, number of hills, number of nodules and number of plant stand for IP X G, non

significant for most of the traits except number of hill, number of leaves, root length and vine

length for IP X G while G X Y interaction effect are highly significant (P<0.001) for all the

traits. Variance due to second order interaction IP X G X Y were highly significant (P<0.001)

for most of the traits except dry fodder weight, fresh fodder weight, number of nodules and

number of plant stand. Variance due to insect protection, genotype and year effects as well as

interaction for reproductive and grain yield components in late season is presented. Variance

due to insect protection, genotype and year main effects were highly significant (P<0.001) for

all the traits sampled. Interactions of IP X G was highly significant (P<0.001) for most of the

traits except number of seed per pod, threshing percentage and harvest index, IP XY was

highly significant (P<0.001) for most of the traits except number of pod per plant while G X

Y variance was highly significant (P<0.001) for most of the traits except number of seed per

pod. Second order interaction variance (IP X G X Y) was highly significant (P<0.001) for

most of the traits except number of pod per plant, and harvest index.

Variance due to main and interactive effects for insect damage in late season is presented.

Insect protection effects was highly significant (P<0.001) for all the traits, variance due to

genotype was highly significant (P<0.001) for most of the traits except aphid score and thrips

count while variance due to year effect was highly significant (P<0.001) for most of the traits

except bruchid count, and Maruca count. Interaction due to IP X G variance was highly

significant for most of the traits except bruchid count, Ootheca score and thrip count, IP X Y

was non significant for most of the traits except for aphid score, and thrip count, while G X Y

variance was non significant for most of the traits except pod sucking bug score and thrip

count. Second order interaction (IP X G X Y) variance was non significant for most of the

traits except aphid score and pod sucking bug score that were highly significant (P<0.001).

Early and late season combined analysis in Mgbakwu in 2007

ANOVA for growth component showed that variance due to main effects were highly

significant (P<0.001) for most of the traits except number of hill, number of inter node,

number of leaves and number of plant stand for insect protection main effects, highly

significant (P<0.001) for all the traits for genotype and season main effects. Interaction

between IP X G was highly significant (P<0.001) for most of the traits except number of

47

branches, number of hills, number of internodes, number of leaves, number of plant stand and

peduncle length, IP X S was non significant for most of the traits while G X S was highly

significant (P<0.001) for most of the traits except dry fodder weight, fresh fodder weight,

number of leaves and root length. Second order interaction (IP X G x S) was non significant

for most of the traits except number of internodes and vine length that were highly significant

(P<0.001).

Reproductive and grain yield component of variance for main and interaction effects were

highly significant (P<0.001) for almost all the traits studies. Insect damage in respect of aphid

score, Maruca count and thrip count were highly significant (P<0.001) for both main and

interaction effects (Appendix 15)

Early and late season combined analysis in Mgbakwu in 2008.

Variances due to genotype and season for all the traits were highly significant (P<0.001) for

growth components. Effects due to first order interaction between IP X S and G X S for most of

the traits were highly significant (P<0.001). Second order interactions of IP X G X S effects were

highly significant (P<0.001) for number of inter nodes and peduncle length (Appendix 16).

Variance due to main effects of genotype and season were highly significant (P<0.001) for all

the traits. Similarly effects due to G X S interaction was highly significant (P<0.001) for most

of the traits while second order interaction was significant for 100 seed weight, number of

seed per pod, pod length and threshing percentage for reproductive and growth components.

Variance due to main and interaction effects for insect damage were highly significant

(P<0.001) for most of the traits studied.

Early season combined analysis over 2007 and 2008 in Mgbakwu

Variances due to genotype and year main effects were highly significant (P<0.001) for most

of the growth component traits. Similarly, most of the reproductive and grain yield traits

were highly significant (P<0.001) for all the main effects.

Variance due to main effect was highly significant (P<0.001) for most of the components of

insect damage traits.

Late season combined analysis over 2007 and 2008 in Mgbakwu.

Component of variance for genotype and year main effect as well as genotype by year

48

interaction were highly significant (P<0.001) for most of the growth parameters. Variance

due to the main and interaction effects for reproductive and grain yield component were

highly significant (P<0.001) (Appendix 23). Variance due to genotype, year and insect

protection X year effects were highly significant (P<0.001) for insect damage traits.

4.2 Main effect of genotype on growth, reproductive, grain yield and insect pest

damage component in early and late season combined in Ishiagu, 2007.

4.2.1 Genotype main effect on growth component.

There was significant genotype effect on dry fodder weight, fresh fodder weight, number of

branches, number of internodes, number of nodules, number of stands, peduncle length and vine

length (Table 4). Among all the growth component traits studied, IT90K–277-2, and local variety

consistently maintained significantly higher dry fodder weight, fresh fodder weight, number of

internodes, number of leaves, number of nodules, root length and vine length. The highest mean dry

fodder weight was produced by local variety (633 g) followed by IT90K-277-2 (610 g), IT97K-

556-4 (579 g) while the lowest was produced by an early maturing genotype, IT93K-452-1 (356 g)

followed by IT84S-2246-4 (362 g) and IT97K-568-18 (362 g). The rest of the genotypes had

statistically similar dry fodder weight. Mean fresh fodder weight followed similar trend with dry

fodder weight. All the genotypes were relatively similar for number of branches and number of

hills, although IT84S-2246-4 was statistically lower for the number of branches (2). Similarly, local

variety was significantly lower for number of hills (13) than all the other genotypes, revealing that

the seeds of improved genotypes were more viable than the seed of local variety. Consequently, the

highest number of plant stand was produced by IT90K-82-2 (47), followed by IT84S-2246-4 (46),

IT97K-499-35(45) and IT97K-556-4-(45) while local produced the least number of plant stands

indicating that the genotypes with high expression of number of plant stand had better plant

establishment (higher plant population) than the local variety. The genotype IT90K-277-2

and local that produced highest dry fodder weight and fresh fodder weight also expressed

significantly higher number of leaves and vine length, suggesting that the higher the number

of leaves and the longer the vines in these genotypes the more the fodder that resulted. The

genotype IT90K-277-2 produced the longest peduncles (29 cm) followed by IT84S-2246-4

(27 cm) while IT97K-499-35 and local produced the shortest peduncles of 15 cm each. Mean

root length ranged between 17-24 cm with IT90K-277-2 expressing significantly longer root

length (24 cm) followed by IT98K-205-8 and local with root length of 21 cm each.

49

Table 4: The main effect of genotype on growth component of 10 cowpea genotypes during the early and late seasons in Ishiagu, 2007

Genotype DFWT(g) FFWT(g) NBRANCH NHILL

INTER

NODE

NLEAF NNODULE NSTAND PEDLT

(cm)

RTLENGTH

(cm)

VINELTH

(cm)

IT 84S-2246-4 362.00 1400.43 2.33 15.92 4.75 19.00 8.58 46.17 26.54 20.21 22.70

IT 90K-277-2 610.34 2800.00 3.33 15.50 8.67 28.08 18.58 41.33 29.42 21.25 61.14

IT 90K-82-2 508.11 2267.09 3.08 16.00 6.33 21.75 4.42 47.00 24.79 18.67 41.20

IT 93K-452-1 357.08 1542.14 3.17 15.33 7.50 21.58 11.67 38.00 22.42 17.42 50.23

IT 97K-499-35 515.43 2158.00 2.58 15.67 6.58 20.92 7.00 45.08 24.83 19.04 30.30

IT 97K-556-4 579.00 2667.02 3.67 15.75 5.33 22.00 17.33 45.67 23.83 17.42 35.56

IT 97K-568-18 362.00 1542.14 3.25 15.58 7.17 20.83 9.08 39.50 25.33 18.25 54.88

IT 98K-131-2 492.35 1825.00 3.00 15.67 6.75 22.33 5.75 37.42 25.75 20.08 45.30

IT 98K-205-8 500.12 2350.02 2.83 15.58 7.00 22.42 8.42 41.25 26.25 21.38 44.27

LOCAL 633.00 2900.04 3.83 13.17 21.67 65.92 22.17 30.17 14.83 21.08 214.80

Mean 491.94 2145.00 3.11 15.42 8.18 26.48 11.30 41.06 24.40 19.48 60.00

F- LSD (0.05) 256.10 1138.3 0.9147 1.229 1.998 8.579 3.730 3.862 5.524 4.109 24.75

DFWT = Dry fodder weight; FFWT = Fresh fodder weight: NBRANCH = Number of branches; NHILL = Number of hills; INTERNODE = Number of internode; NLEAF =

Number of leaves; NNODULE=Number of nodules; NSTAND=Number of plant stand; PEDLT = Peduncle length; RTLENGTH=Root length; VINELTH=Vine length.

50

Similarly, vine length at flowering ranged between 23-215 cm with local variety producing the

longest vine length (215 cm) following by IT90K-277-2 (61 cm), IT97K-568-18 (55 cm) and

IT93K-452-1 (50 cm) while the rest genotypes had vine length less than 50 cm with IT84S-2246-

4 expressing the shortest vine length of 23 cm.

4.2.2 Genotype main effect on reproductive and grain yield component.

Table 5 showed that most genotypes flowered in less than two months except local variety that

flowered after two months. The earliest to flower was IT93K-452-1 (41 days) followed by

IT97K-499-35 and IT98K-205-8(43 days each). Except for IT93K-452-1 that matured in less

than two month (58 days) other genotypes matured above two months (60 days) with local

maturing latest (99 days). Duration of pod filling period followed similar pattern with days to

flowering and maturity, with IT84S-2246-4 and IT90K-82-2 expressing the lowest pod filling

period of 14 days each, while the local variety had the highest pod filling duration (34 days)

followed by IT98K-131-2 (20 days). The highest mean 100 seed weight was recorded by IT97K-

556-4 (14 g), followed by IT90K-277-2, IT93K-452-1 and IT98K-205-8 with mean 100 seed

weight of 13 g each while the least was produced by local (4 g) followed by IT84S-2246-4 and

IT90K-82-2 with 9 g each. Mean number of pod per plant for all the genotypes was statistically

similar, although local variety recorded the lowest value (1) followed by IT97K-499-35 (9).

Similarly, number of seeds per pod was non significant for all the genotypes however, local

variety produced the least value (1) followed by IT 84S-2246-4 (8).

The genotype IT97K-556-4 produced the longest pod (17 cm) followed by IT90K–82-2 (15 cm)

and IT98K-131-2 (15 cm) while local variety had the shortest pods (3 cm). The highest pod

weight, seed weight and grain yield were produced by IT98K-131-2 followed by IT97K-556-4

and IT90K-82-2 while local variety was consistently lower for all the grain yield components.

Furthermore, IT98K-131-2 had the highest grain yield per hectare (556 kg) compared to local

with the lowest grain yield per hectare of 44 kg. The genotype IT98K-131-2 consequently

produced 26 percent higher mean grain yield than the second highest grain yielder, moreover it

recorded the highest threshing percentage (45 percent) and highest harvest index (42 percent).

The genotype IT98K-205-8 produced the next higher threshing percentage (44 percent) followed

by IT97K-499-35 (40 percent), IT93K-452-1(39 percent) and IT9 7K-556-4 (39 percent) while

local variety produced the least (14 percent). The highest harvest index was however produced

by IT98K-131-2 (42 percent) and

51

Table 5: The main effect of genotype on reproductive and grain yield components of 10 cowpea genotypes during the early and late seasons in Ishiagu 2007

Genotype BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(g)

SEED

WT (g)

GYLD/HA

(kg)

THRESH

(%)

HI

(%)

IT 84S-2246-4 47.17 61.00 13.50 8.92 12.83 8.25 14.00 186.60 89.00 297.24 33.88 27.80

IT 90K-277-2 46.17 61.43 18.67 13.02 11.33 10.83 14.38 230.00 96.80 323.09 31.03 17.12

IT 90K-82-2 48.58 63.00 14.00 8.50 12.25 10.25 14.92 268.34 122.63 409.13 32.88 33.85

IT 93K-452-1 41.08 58.22 17.17 12.65 11.33 10.33 13.31 176.72 83.00 277.00 38.62 41.74

IT 97K-499-35 43.42 60.08 17.58 10.78 9.08 9.67 13.92 211.65 103.67 345.00 40.42 23.00

IT 97K-556-4 47.08 64.24 16.67 13.88 11.75 9.67 16.93 286.17 134.93 450.42 38.49 32.25

IT 97K-568-18 44.58 64.75 18.58 11.19 12.33 10.00 13.88 243.73 105.71 352.17 30.59 27.00

IT 98K-131-2 46.50 67.47 19.50 10.76 13.67 11.25 14.67 303.00 169.88 566.03 45.43 42.33

IT 98K-205-8 43.00 62.50 19.25 12.73 12.42 9.67 13.38 213.00 116.61 389.26 44.11 30.17

LOCAL 65.00 99.00 34.00 3.50 1.08 1.08 2.92 23.40 13.22 44.00 13.56 1.68

Mean 47.35 56.23 18.90 10.59 10.81 9.07 13.23 214.23 103.54 345.00 34.74 27.76

F- LSD (0.05) 2.768 11.30 3.949 1.739 5.692 2.238 1.392 134.47 68.60 228.70 11.77 14.12

BLOOM = Days to 50 percent flowering; MATURITY = Days to maturity; PODFILL = Days to Podfilling; 100SWT = 100 Seed weight; NPOD/PLT = Number of pods per

plant; NSEED/POD = Number of seeds per pod; PLENGTH = Pod length; PODWT = Pod weight; SEEDWT = Seed weight; GYLD/HA = Grain yield per hectare; THRESH

percent = Threshing percentage; HI = Harvest Index.

52

IT93K-452-1 (42 percent) followed by IT90K-82-2 (34 percent) while local variety produced

the least (2 percent). IT93K-452-1 and IT98K-131-2 equally produced significantly higher

threshing percentage and harvest index. The genotypes IT90K-277-2 and local variety gave

consistently lower threshing percentage and harvest index, arising from the fact that both also

produced the highest dry fodder and fresh fodder weight.

4.2.3 Genotype main effect on insect damage component.

Table 6 showed that IT84S-2246-4, IT90K-277-2, IT97K-499-35 and IT97K-568-18 had

similar but lowest aphid population of 1.333 while IT98K-205-8 and local variety had the

highest score (1.67) followed by IT90K-82-2 (1.58) and IT93K-452-1 (1.50). Bruchid

damage was highest in IT98K-205-8 (14.08), IT97K-499-35 (12.33), IT97K-556-4(10.08)

and IT93K-452-1 (7.33) but lowest in IT90K-277-2 (0.33), IT90K-82-2 (0.83) and IT98K-

131-2 (1.25), IT90K-277-2 was considered resistant to bruchids while on the other hand

IT98K-205-8 was highly susceptible.

The lowest Maruca population was harbored by IT93K-452-1 (1.08), IT90K-82-2 (1.58),

IT98K 205-8 (1.75) and IT97K-499-35 (1.83) while the highest population was associated

with IT97K-556-4 (2.75), IT 90K-277-2 (2.67), IT84S-2246-4 (2.50) and local variety (2.33).

Most of these genotypes that were highly attacked by Maruca also produced very high dry

and fresh fodder weight, leaf and vine length as well as late maturity. On the other hand

majority of the genotypes that expressed low Maruca population were early maturity

genotypes. The lowest Ootheca damage was associated with IT97K-499-35 (1.58) and

IT98K-131-2(1.58) followed by IT93K-452-1 and IT97K-556-4 with Ootheca damage rating

of 1.667 each. Pod sucking bug population was statistically similar for all the genotypes,

however, IT84S-2246-4 and local had the highest population of 1.75 each while IT97K-556-4

had the least (1.33).

Thrips population was generally high but low for IT84S-2246-4 (6.08) and IT90K-82-2

(8.08), while the highest population was recorded for local (12.33), IT97K-556-4 (11.25) and

IT98K-131-2 (10.75). Genotype IT97K-556-4 consistently harbored significantly higher

population of all the insect pests sampled except pod sucking bugs where it harbored the least

infestation.

53

Table 6: The main effect of genotype on insect damage of 10 cowpea genotypes during the early and late seasons in Ishiagu,

2007

Genotype APHIDSC BRUCHIDCT MARUCT OOTHESC PSBSC THRIPCT

IT 84S-2246-4 1.33 2.67 2.50 1.92 1.75 6.08

IT 90K-277-2 1.33 0.33 2.67 2.17 1.67 9.83

IT 90K-82-2 1.58 0.83 1.58 2.42 1.58 8.08

IT 93K-452-1 1.50 7.33 1.08 1.67 1.42 10.00

IT 97K-499-35 1.33 12.33 1.83 1.58 1.50 9.00

IT 97K-556-4 1.42 10.08 2.75 2.58 1.33 11.25

IT 97K-568-18 1.33 2.00 2.00 1.67 1.50 8.83

IT 98K-131-2 1.42 1.25 2.00 1.58 1.50 10.75

IT 98K-205-8 1.67 14.08 1.75 1.83 1.58 9.58

LOCAL 1.67 3.33 2.33 2.00 1.75 12.33

Mean 1.41 5.42 2.05 1.94 3.00 9.57

F- LSD (0.05) 0.41 7.46 1.59 0.48 0.33 4.46

APHIDSC = Aphid Score; BRUCHIDCT = Bruchid Count; MARUCT = Maruca Count; OOTHESC = Ootheca Score; PSBSC = Pod

Sucking Bug Score; THRIPCT = Thrips Count.

54

4.3 Main effect of genotype on growth, reproductive, grain yield and insect pest damage

component in early and late season combined in Ishiagu, 2008.


Table 7 showed that IT90K-277-2 produced the highest dry fodder weight (1183 g) and fresh

fodder weight (4442 g), followed by IT97K-556-4 with dry fodder weight of 1067 g and fresh

fodder of 4242 g, while IT93K-452-1 produced the lowest dry fodder (342 g) and fresh

fodder (1375 g), followed by local with dry fodder weight (499 g) and fresh fodder weight

(1687 g). Local variety gave the highest number of internodes (15), number of leaves (86),

number of nodules (16) and vine length (139 cm), followed by IT90K-277-2 with number of

internodes (13), number of nodules (13) and vine length (140 cm). On the other hand the

local variety recorded the lowest number of hills (3), number of stands (4), peduncle length

(10 cm) and root length (13 cm) whereas IT84S-2246-4 produced significantly higher number

of hills (16) and number of stands (33), indicating that the genotype had the most viable seed

and consequently produced the highest plant population among the genotypes. On the other

hand local variety had the least viable seeds, and therefore produced the lowest plant

population and consequently resulted in lower dry and fresh fodder weight. The genotype

IT98K-131-2 produced significantly higher number of leaves (43), peduncle length (36 cm),

root length (25 cm) and vine length (121 cm) than most other genotypes.


Table 8 showed that IT98K-131-2 produced significantly higher mean 100 seed weight (16

g), number of pods per plant (24), pod weight (562 g), seed weight (416 g), grain yield per

hectare (1386 kg) and threshing percentage (73 percent) while the local variety supported

statistically lower 100 seed weight (5 g), number of pods per plant (5), number of seeds per

pod (4), pod length (5 cm), pod weight (50 g), seed weight (30 g), grain yield per hectare

(101 kg), threshing percentage (15 percent) and harvest index (7 percent). The genotype

IT93K-452-1 had significantly higher harvest index (90 percent). However, local variety was

the latest to flower (65 days) and to mature (87 days) while IT90K-277-2 and IT90K-82-2

were next to local in days to flowering and maturity and the two genotypes flowered and

matured in similar days.

55

Table 7: The main effect of genotype on growth component of 10 cowpea genotypes during the early and late seasons in Ishiagu, 2008


INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

IT 84S-2246-4 817.41 3032.62 3.17 15.58 6.83 26.70 7.17 32.50 33.42 24.67 56.10

IT 90K-277-2 1183.25 4442.33 4.33 13.08 12.58 39.82 12.58 24.83 34.50 23.75 140.00

IT 90K-82-2 842.00 3417.27 3.50 14.17 11.00 35.80 5.92 27.92 32.17 21.25 72.43

IT 93K-452-1 342.15 1375.12 2.67 13.83 8.42 21.00 12.75 27.00 28.58 19.67 61.11

IT 97K-499-35 575.00 2342.00 2.50 13.82 10.40 24.25 7.00 28.58 30.00 23.92 76.70

IT 97K-556-4 1067.00 4242.20 4.08 14.58 7.00 29.51 10.75 27.92 30.08 22.25 68.85

IT 97K-568-18 932.50 3292.09 3.67 10.17 11.58 40.80 9.92 17.25 34.06 23.67 118.00

IT 98K-131-2 683.07 2583.00 3.66 11.92 11..90 43.00 8.75 19.58 36.08 25.00 121.22

IT 98K-205-8 600.19 2217.23 3.25 13.50 10.00 24.11 7.33 25.83 30.50 22.75 94.26

LOCAL 499.00 1687.04 3.25 3.42 14.50 85.83 15.58 4.25 10.17 13.42 138.80

Mean 754.00 2863.00 3 12.41 10.43 37.00 10.00 23.57 29.96 22.03 94.70

F-LSD (0.05) 188.00 665.50 0.83 1.56 2.47 14.05 4.00 3.60 5.35 3.85 34.75

DFWT = Dry fodder weight; FFWT = Fresh fodder weight: NBRANCH = Number of branches; NHILL = Number of hills; INTERNODE = Number of internode; NLEAF = Number of

leaves; NNODULE=Number of nodules; NSTAND=Number of plant stand; PEDLT = Peduncle length; RTLENGTH=Root length; VINELTH=Vine length.

56

Genotype IT90K-277-2 was next to IT98K-131-2 in expressing significantly higher pod weight (593

g), seed weight (399 g) and grain yield per hectare (1330 kg). IT93K-452-1 gave the highest harvest

index (86 percent). Meanwhile, IT84S-2246-4 produced the lowest mean 100 seed weight (11 g)

after local variety while IT97K-568-18 produced significantly higher 100 seed weight (17 g),

followed by IT98K-131-2 (16 g). The genotype IT97K-556-4 produced significantly higher pod

length (17 cm) with the rest genotypes expressing statistically similar pod length.


Table 9 revealed that aphid and Ootheca population were statistically similar for all the genotypes,

although there were slight differences among the genotypes for these traits. The rest traits differed

significantly among the genotypes. Local variety habored significantly higher infestation by bruchids

(10.00) followed by IT97K-556-4 (9.67). Moreover, IT97K-556-4 produced significantly higher

Ootheca (2.00) and thrips (10.25), while local variety manifested significantly higher level of

infestation by Maruca (4.25) and pod sucking bugs (3.50). IT98K-131-2 however expressed

significantly lower population of aphids (1.00), bruchids (1.83) and Maruca (0.67) while IT98K-205-

8 had low Maruca (1.75) and thrips (6.50) and coincidentally produced higher grain yield traits. As

expected, white seeded genotypes expressed the highest infestation by bruchids, IT98K-205-8 (8.92),

followed by IT93K-452-1(7.67) and IT97K-499-35 (6.25)) than brown rough seeded genotypes.

Although IT97K-556-4 genotype is brown seeded it demonstrated significantly higher bruchids

(9.67), however the genotype possessed smooth seed coat colour.

4.4 Main effect of genotype on growth, reproductive grain yield and insect damage components

early season combined over 2007 and 2008, Ishiagu.


Among the genotypes studied, there was significant genotype effect on almost all the growth

components in early season combined over 2007 and 2008 (Table 10). Genotype IT90K-277-2

produced the highest dry fodder (952 g) and fresh fodder weight (3758 g), followed by IT97K-556-4

with dry fodder (771 g) and fresh fodder (3350 g), IT90K-82-2 with dry fodder (742 g) and fresh

fodder (3133 g) and IT97K-568-18 with dry fodder (696 g) and fresh fodder (2742 g). These

genotypes produced correspondingly higher vine length.

57

Table 8: The main effect of genotype on reproductive and grain yield components of 10 cowpea genotypes during the early and late seasons in Ishiagu, 2008

Genotype BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(g)

SEED WT

(g)

GYLD/HA

(kg)

THRESH

(%)

HI

(%)

IT 84S-2246-4 47.75 65.08 17.33 10.50 23.33 10.25 14.67 472.04 315.30 1051.04 57.22 45.20

IT 90K-277-2 47.50 67.00 19.50 15.33 21.00 11.83 15.25 593.00 399.00 1330.13 59.90 40.91

IT 90K-82-2 47.92 67.06 19.17 12.58 24.25 11.80 14.75 421.10 291.11 970.00 66.31 41.94

IT 93K-452-1 38.08 55.50 17.42 16.08 17.25 11.25 13.79 414.49 306.83 1023.37 72.33 89.68

IT 97K-499-35 41.67 60.92 19.25 13.42 17.28 10.33 13.83 464.00 332.75 1109.25 62.25 65.55

IT 97K-556-4 45.17 65.75 20.58 14.25 20.50 11.75 17.17 485.00 338.30 1128.00 57.00 34.33

IT 97K-568-18 44.67 65.77 21.08 16.58 21.67 11.33 14.88 499.02 347.14 1157.09 66.53 36.93

IT 98K-131-2 45.08 65.92 20.83 16.17 23.92 11.42 15.04 562.40 415.72 1386.11 73.00 75.82

IT 98K-205-8 40.67 60.90 20.25 14.58 19.33 11.08 14.25 439.57 312.71 1042.00 64.94 63.70

LOCAL 65.00 87.33 22.00 4.83 5.25 4.08 4.92 50.06 30.40 101.42 14.88 7.20

Mean 46.40 66.10 19.22 13.43 19.38 10.52 13.85 440.00 308.95 1030.00 59.40 51.70

F-LSD (0.05) 9.70 6.57 3.37 2.79 4.05 2.21 1.63 81.20 62.41 208.00 11.42 20.25

BLOOM = Days to 50 percent flowering; MATURITY = Days to maturity; PODFILL = Days to Podfilling; 100SWT = 100 Seed weight; NPOD/PLT = Number of pods

per plant; NSEED/POD = Number of seeds per pod; PLENGTH = Pod length; PODWT = Pod weight; SEEDWT = Seed weight; GYLD/HA = Grain yield per hectare;

THRESH percent = Threshing percentage; HI = Harvest Index.

58

Table 9: The main effect of genotype on insect damage of 10 cowpea genotypes during early and late season in Ishiagu, 2008


IT 84S-2246-4 1.25 3.90 2.08 1.67 2.58 8.67

IT 90K-277-2 1.00 3.50 2.42 1.50 2.00 9.92

IT 90K-82-2 1.17 3.50 1.92 1.42 2.00 7.67

IT 93K-452-1 1.00 7.67 2.00 1.25 1.80 9.67

IT 97K-499-35 1.50 6.25 2.33 1.25 2.08 8.00

IT 97K-556-4 1.30 9.67 2.58 2.00 2.58 10.25

IT 97K-568-18 1.58 2.83 2.25 1.67 1.75 6.00

IT 98K-131-2 1.00 1.83 0.67 1.50 1.92 8.75

IT 98K-205-8 1.33 8.92 1.75 1.58 2.00 6.50

LOCAL 1.50 10.00 4.25 1.33 3.50 9.67

Mean 1.27 5.89 2.23 1.52 2.22 8.51

F-LSD (0.05) 0.44 4.97 1.82 0.62 0.64 4.72

APHIDSC = Aphid Score; BRUCHIDCT = Bruchid Count; MARUCT = Maruca Count; OOTHESC = Ootheca Score; PSBSC = Pod Sucking Bug Score;

THRIPCT = Thrips Count.

59

On the other hand, IT93K-452-1 supported significantly lower dry fodder (298 g) and fresh

fodders (1475 g) followed by IT84S-2246-4 with dry fodder (554 g) and fresh fodder (2208

g) and local variety with dry fodder (571 g) and fresh fodder (2255 g). Most genotypes with

significantly lower fodder weight also produced shorter vine length except local variety that

expressed the longest vine length (186 kg), although it produced the lowest number of hills

and plant stands.

The significantly lower fodder weight expressed by local variety was probably because it

produced the lowest number of hills (9) and number of stands (14). Local variety expressed

significantly higher number of branches (5) while IT93K-452-1 that expressed the lowest dry

and fresh fodder weight consequently had the least number of branches (2). Genotype IT84S-

2246-4 again expressed the highest number of hills (16) and number of stands (40), although

it produced one of the lowest dry and fresh fodder weights through its production of very low

number of leaves and vine length. Local variety produced significantly higher number of

internodes (20) followed by IT90K-277-2 with number of internodes of 12. Similarly, local

variety produced significantly higher number of leaves (86) followed by IT98K-131-2 with

number of leaves (33). Genotype IT97K-556-4 gave the highest number of nodules (18)

followed by IT90K-277-2 and local with similar number of nodules of 17 each. Local variety

produced statistically lower peduncle length (2) while the rest of the genotypes expressed

statistically similar but higher peduncle length. The genotype IT93K-452-1 and local variety

manifested the lowest root length of 18cm each.


Table 11 showed that there was significant genotype effect on all the reproductive and grain

yield components in both years however narrow differences existed among the genotypes for

these traits. Genotype IT93K-452-1 was the earliest to flower (40 days) and mature (61 days)

followed by IT98K-205-8: days to flower (43 days) and mature (64 days). Genotype IT98K-

131-2 took longer days to flower (52 days) and mature (72 days). The genotypes IT90K-277-

2 and IT98K-131-2 took significantly longer days to fill the pod (22 days) and both produced

relatively high grain yield. Also, IT90K-277-2 produced significantly high mean 100 seed

weight (18 g) followed by IT97K-556-4 (17 g). Genotype IT90K-82-2 had the highest

number of pod per plant (20) while IT97K-499-35 produced the lowest (13).

60

Table 10: The main effect of genotype on growth component of 10 cowpea genotypes during the early season in Ishiagu in 2007 and 2008


INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

IT 84S-2246-4 554.13 2207.72 2.58 15.83 6.00 24.10 10.17 39.50 29.29 22.75 43.70

IT 90K-277-2 952.00 3758.00 3.68 14.67 12.08 28.80 16.66 34.33 30.82 22.50 111.21

IT 90K-82-2 742.09 3132.49 3.00 15.58 10.18 30.00 6.19 38.42 29.71 19.63 72.72

IT 93K-452-1 298.24 1475.02 2.42 15.33 8.50 22.22 15.50 35.17 25.92 17.94 65.70

IT 97K-499-35 640.17 2808.00 2.75 14.83 9.00 21.87 8.25 37.00 29.33 20.67 62.00

IT 97K-556-4 771.00 3350.33 3.94 15.80 7.42 27.85 17.50 38.17 27.58 20.08 72.43

IT 97K-568-18 696.05 2742.42 3.25 13.66 9..92 29.33 14.65 30.75 29.70 20.50 97.21

IT 98K-131-2 625.29 2500.00 3.17 13.91 9.58 32.50 9.92 29.80 30.77 21.76 89.20

IT 98K-205-8 642.43 2832.90 3.08 15.08 9.25 26.00 10.87 34.58 30.42 23.00 83.73

LOCAL 571.00 2255.17 4.50 8.83 20.42 83.50 17.25 14.08 - 18.08 185.79

Mean 649.00 2481.00 3.23 14.36 10.22 32.62 12.69 33.18 26.58 20.70 88.30

F-LSD (0.05) 191.90 760.10 0.94 1.26 2.46 18.72 5.47 3.36 5.10 3.92 34.06



61

Genotype IT97K-556-4 produced significantly longer pod length (17 cm) than all other

genotypes, while IT93K-452-1 produced the least (13 cm). Genotype IT98K-131-2

consistently expressed highest grain yield per hectare (1220 kg), and seed weight (366 g),

followed by IT97K-556-4 with grain yield per hectare (1154 kg) and seed weight (1154 g)

and IT97K-499-35 with grain yield per hectare (1114 kg) and seed weight (334 g).

Meanwhile, IT90K-277-2 produced the highest pod weight (539 g) followed by IT97K-556-4

(533 g) and IT98K-131-2 (526 g). Conversely, IT93K-452-1 gave the lowest grain yield per

hectare (807 kg), seed weight (242 g) and pod weight (352 g) but it resulted in highest harvest

index (93 percent). Although IT98K-131-2 was one of the genotypes that were latest to

flower and mature, it produced the highest grain yield and seed weight and also expressed

very high threshing percentage (69 percent), and harvest index (74 percent).


Table 12 showed that differences between genotypes for all the insect pests sampled was

however low but significant for bruchids and thrips. The rest of the insect damage traits were

non significant. Moreover, it was observed that most of the insect pest sampled had low

population during the early season. Genotype IT98K-131-2 harbored the lowest infestation of

the notable yield limiting pests: Maruca (0.92), pod sucking bugs (1.00) and thrips (1.00).

Again, white seeded genotypes produced grains with significantly higher infestation of

bruchids; IT97K-499-35 (11.83) and IT98K-205-8 (10.67). Meanwhile, IT90K-277-2 (white

seeded genotype) was least infested with bruchids (0.83).

4.5 Main effect of genotype on growth, reproductive, grain yield and insect damage

components in late season combined over 2007 and 2008, Ishiagu.


Genotypes differed significantly for all the growth components studied (Table 13). The

genotype IT97K-556-4 produced the highest dry and fresh fodder weight which did not differ

significantly with IT90K-277-2 but significantly higher than the other genotypes. Genotype

IT93K-452-1 produced the lowest dry fodder weight which was statistically similar with

IT97K-499-35 and IT98K-205-8 but more significantly lower than the other genotypes

including the local variety. The genotype IT84S-2246-4 again expressed the highest number

of hills (16) and number of plant stands (39) while local variety was lowest for the two traits.

62

Table 11: The main effect of genotype on reproductive and grain yield components of 10 cowpea genotypes during the early season in Ishiagu, 2007 and 2008

GENOTYPE BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(g)

SEED WT

(g)

GYLD/HA

(kg)

THRESH

(%)

HI

( %)

IT 84S-2246-4 51.66 68.33 16.65 11.92 17.08 10.25 14.48 430.11 267.70 892.00 58.94 52.90

IT 90K-277-2 50.25 71.83 21.58 17.77 16.94 13.00 14.62 539.04 321.52 1072.03 54.61 31.73

IT 90K-82-2 51.27 70.42 19.17 11.63 19.86 12.08 14.75 480.00 293.33 977.69 58.09 45.55

IT 93K-452-1 39.50 60.50 20.25 16.33 14.50 11.70 13.38 351.75 242.25 807.40 63.90 93.00

IT 97K-499-35 44.00 65.00 21.00 14.71 13.33 11.50 13.67 488.33 334.10 1114.00 65.02 50.40

IT 97K-556-4 50.58 70.42 19.83 17.24 14.79 11.58 16.93 533.00 346.14 1154.00 62.94 50.92

IT 97K-568-18 47.60 68.33 20.97 15.19 16.67 12.00 14.38 448.01 282.90 943.07 54.70 39.23

IT 98K-131-2 50.00 71.68 21.72 15.43 17.58 12.66 14.88 526.00 365.91 1220.25 68.55 74.25

IT 98K-205-8 43.33 64.08 20.81 15.45 15.51 11.68 13.96 455.09 307.00 1023.19 64.18 59.90

LOCAL - - - - - - - - - - - -

Mean 43.50 61.06 18.18 13.57 14.67 10.48 13.11 425.00 276.13 920.00 55.09 49.84

F-LSD (0.05) 5.86 1.98 2.49 0.52 5.18 1.73 0.84 120.50 69.20 230.70 6.49 24.10




63

Table 12: The main effect of genotype on insect damage of 10 cowpea genotypes during the early season in Ishiagu, 2007 and 2008


IT 84S-2246-4 1.42 4.25 1.50 1.92 1.33 5.33

IT 90K-277-2 1.33 0.83 1.33 1.92 1.17 5.58

IT 90K-82-2 1.75 1.58 1.33 1.75 1.17 2.33

IT 93K-452-1 1.50 4.92 1.25 1.58 1.17 3.67

IT 97K-499-35 1.50 11.83 1.17 1.67 1.25 3.00

IT 97K-556-4 1.50 9.00 1.17 2.42 1.17 4.67

IT 97K-568-18 1.75 1.58 1.42 1.83 1.08 2.17

IT 98K-131-2 1.50 2.25 0.92 1.67 1.00 1.00

IT 98K-205-8 1.92 10.67 0.92 1.92 1.17 3.17

LOCAL 1.58 - - 1.87 - -

Mean 1.58 4.69 1.10 1.86 1.18 3.50

F-LSD (0.05) 0.58 5.86 0.60 0.41 0.37 2.61



64

The local variety produced the highest number of internodes followed by IT98K-131-2,

IT97K-568-18 and IT90K-277-2 with number of internodes of 9 each while IT97K-556-4 had

the least number of internodes (5). The local variety produced the highest number of leaves

(68) followed by IT90K-277-2 (39) while IT90K-82-2 and IT97K-568-18 produced the least

of 4 each. The genotype IT90K-277-2 produced the longest peduncle length (33 cm), and root

length (24) while it was second after the local variety in producing the longest vine length

(90cm). On the other hand local variety produced the shortest peduncle length (23 cm) and

root length (16 cm) but gave the longest vine length (168 cm).


Table 14 showed that there was significant effect due to genotype on most reproductive and

grain yield components sampled. The local variety was the last genotype to flower (59 days)

and mature (77 days) and consequently it took longer days to fill the pod (27 days).

Conversely, IT93K-452-1 was the earliest to flower (39 days) and mature (50 days) and it

filled the pods in relatively shorter period of time (14 days) as expected. Mean 100 seed

weight ranged between 8-13 g with IT97K-568-18 producing the highest seed weight (13 g),

while IT84S-2246-4 and local variety produced the least mean 100 seed weight of 8g each.

Genotype IT98K-131-2 supported the highest expression of mean number of pods per plant

(20) followed by IT84S-2246-4 (19) while the local variety produced the least (6).

The difference between genotypes for number of seeds per pod was very narrow, however,

local variety produced the least number of seed per pod (5) followed by IT84S-2246-4 (8)

while number of seeds per pod for the rest of the genotypes were statistically similar (9-10).

Genotype IT97K-556-4 produced significantly longer pod length (17 cm) while local vaiety

produced significantly shorter pod length (8 cm). Meanwhile, the rest of the genotypes

expressed similar mean pod lengths. The genotype IT98K-131-2 maintained significantly

higher mean grain yield (732 kg ha-1

) than all other genotypes and the highest seed weight

(220 g) and pod weight (339 g) followed by IT90K-277-2 with grain yield (581 kg ha-1

) and

seed weight (174 g), IT97K-568-18 with grain yield (566 kg ha-1

) and seed weight (170 g).

Local variety on the other hand produced significantly lower grain yield (145 kg ha-1

), seed

weight (44 g) and pod weight (74 g).

65

Table 13: The main effect of genotype on growth component of 10 cowpea genotypes during the late season in Ishiagu in 2007 and 2008


INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

IT 84S-2246-4 624.80 2225.00 2.92 15.67 5.58 21.58 5.58 39.17 30.67 22.12 35.12

IT 90K-277-2 842.37 3483.17 4.08 13.92 9.17 39.08 14.50 31.83 33.08 24.00 89.90

IT 90K-82-2 608.00 2550.09 3.58 14.58 7.25 27.50 4.17 36.50 27.25 20.25 41.00

IT 93K-452-1 399.73 1442.32 3.42 13.83 7.42 20.42 8.92 29.83 25.05 19.17 45.72

IT 97K-499-35 450.07 1691.73 2.33 14.67 8.00 23.25 5.75 36.67 25.50 22.21 44.95

IT 97K-556-4 875.11 3558.00 3.83 14.50 4.92 23.75 10.58 34.42 26.33 19.58 31.80

IT 97K-568-18 600.00 2092.00 3.67 12.08 8.83 32.33 4.33 26.00 29.67 21.42 75.64

IT 98K-131-2 550.01 1908.15 3.50 13.67 9.08 32.83 4.58 27.17 31.08 23.33 77.30

IT 98K-205-8 458.00 1733.24 3.00 14.00 7.75 20.50 4.92 32.50 26.33 21.12 54.70

LOCAL 569.42 1995.00 2.58 7.75 15.75 68.25 9.50 20.33 22.75 16.42 168.00

Mean 598.00 2268.00 3.29 13.47 8.38 30.95 7.28 31.44 27.77 20.83 66.44

F-LSD (0.05) 136.80 612.40 0.73 1.59 2.45 7.18 3.22 4.09 4.32 3.40 24.69



66

Genotype IT90K-277-2 produced relatively higher fodder weight and grain yield as it was the

case in early season. IT98K-131-2 exhibited highest threshing percentage (48 percent)

followed by IT93K-452-2 (47 percent). However, there was a reverse order between the two

genotypes for harvest index with IT93K-452-1 expressing the highest harvest index (54

percent) and IT98K-131-2 the next highest harvest index (44 percent), while local variety

produced the least (9 percent) followed by IT97K-556-4 (16 percent).


Table 15 revealed that the population of aphids and Ootheca was relatively low as expected

in late season combined over the two years but varied among all the genotypes while that of

bruchid, Maruca, pod sucking bugs and thrips were significantly higher, with bruchids and

thrips manifesting the highest level of infestation. Genotype IT98K-131-2 harbored the

lowest population of bruchids (0.83), Maruca (1.75), pod sucking bugs (1.58) and thrips

(8.34) while IT97K-556-4 suffered the highest level of infestation by Maruca (4.17), Ootheca

(2.17), pod sucking bugs (2.75) and thrips (16.83). Genotype IT98K-205-8 a white seeded

genotype harbored the highest infestation of bruchids (12.33), while a brown seeded

genotype, IT98K-131-2 habored the least population of bruchids (0.83).

4.6 Main effect of genotype on growth, reproductive, grain yield and insect pest damage

component in early and late season combined in Mgbakwu, 2007.

4.6.1 Main effect of growth component.

Genotype effects existed for most of the growth components, however differences between

genotypes for number of branches and number of hills were very small (Table 16). Genotype

IT97K-556-4 produced significantly higher dry fodder weight (800 g) and fresh fodder

weight (4126 g) than all other genotypes. The genotype IT90K-277-2 followed with dry

fodder weight (558 g) and fresh fodder weight (2634 g) and IT84S-2246-4 with dry fodder

weight (525 g) and fresh fodder weight (2446 g).

67

Table 14: The main effect of genotype on reproductive and grain yield components of 10 cowpea genotypes during the late season in Ishiagu in 2007 and 2008

GENOTYPE BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(g)

SEED WT

(g)

GYLD/HA

(kg)

THRESH

(%)

HI

( %)

IT 84S-2246-4 43.25 51.00 14.17 7.50 19.08 8.25 14.08 229.00 136.60 455.00 32.22 20.11

IT 90K-277-2 43.42 56.61 16.58 10.58 15.42 9.67 15.00 284.09 174.33 580.64 36.40 26.30

IT 90K-82-2 45.25 51.92 14.00 9.45 16.75 10.00 14.92 208.12 120.42 401.07 41.00 30.25

IT 93K-452-1 38.92 50.00 14.33 12.41 14.08 9.83 13.73 238.69 147.67 492.00 47.00 54.22

IT 97K-499-35 41.08 53.45 15.83 9.48 13.00 8.50 14.08 188.01 102.21 341.27 37.63 38.00

IT 97K-556-4 41.67 55.50 17.42 10.88 17.33 9.83 17.17 238.00 127.20 424.18 32.55 15.65

IT 97K-568-18 41.82 57.00 18.83 12.58 17.37 9.33 14.38 296.41 169.90 566.00 42.44 24.70

IT 98K-131-2 41.58 60.23 18.67 11.50 20.00 10.08 14.84 339.00 219.68 732.19 47.57 43.82

IT 98K-205-8 40.33 59.11 18.75 11.84 16.25 9.08 13.67 198.24 122.32 408.00 44.82 33.84

LOCAL 59.00 76.55 27.42 8.33 6.33 4.92 7.83 74.34 43.66 145.00 28.46 8.80

Mean 43.63 57.42 17.60 10.46 15.56 8.95 13.83 229.00 136.40 454.54 39.00 29.50

F-LSD (0.05) 4.65 12.43 4.26 3.47 4.90 2.33 2.32 77.10 57.40 191.30 14.52 15.80




68

On the other hand IT93K-452-1 produced significantly the least dry fodder weight (267 g),

which did not differ significantly with IT97K-499-35, IT97K-568-18, IT98K-131-2, and

local variety and fresh fodder weight (1375 g) which did not differ significantly with local

variety (1300 g).

The local variety resulted in statistically higher number of branches (5) than the rest of the

genotypes which gave similar number of branches. Genotypes IT84S-2246-4 and IT90K-82-2

supported the highest number of hills (16) while IT93K-452-1 and local variety were the least

(13). Local variety produced significantly higher number of internodes (20) than all the

genotypes, while IT97K-568-18 and IT845-2246-4 expressed the least number of internodes

(8). The local variety also produced significantly higher number of leaves (48) and number of

nodules (22) than all other genotypes, while IT90K-277-2 produced the second highest

number of leaves (39). Genotype IT84S-2246-4 produced the least number of leaves (20) and

number of nodules (3).

The two genotypes IT84S-2246-4 and IT90K-82-2 that produced the highest number of hills

also gave the highest number of stands, indicating that the two genotypes were most viable as

expected. Meanwhile, IT93K-452-1 and local variety that produced the least number of hills

also produced less number of stands revealing their relatively poor viability. Genotype

IT84S-2246-4 produced significantly higher peduncle length (37 cm) while local variety

produced significantly lower peduncle length (19 cm). The rest of the genotypes were

statistically similar with respect to this trait. Root length ranged from 23-31 cm with IT90K-

277-2 producing the highest (31 cm) while IT98K-131-2 was the least (23 cm). Local variety

produced significantly longer vine length (200 cm), than all other genotypes followed by

IT97K-568-18 (135 cm) and IT90K-277-2 (123 cm), which were similar but longer than

other genotypes, whereas IT84S-2246-4 expressed significantly shorter vine length (53 cm)

followed by IT90K-82- 2 (58 cm), which were similar to IT97K-499-35 and IT97K-556-4.

69

Table 15: The main effect of genotype on insect damage of 10 cowpea genotypes during the late season in Ishiagu in 2007 and 2008


IT 84S-2246-4 1.17 2.33 3.08 1.67 3.00 9.42

IT 90K-277-2 1.00 3.00 3.75 1.75 2.67 14.17

IT 90K-82-2 1.00 2.75 2.17 2.08 2.42 13.42

IT 93K-452-1 1.00 10.08 1.83 1.33 2.08 16.00

IT 97K-499-35 1.33 6.75 3.00 1.17 2.33 14.00

IT 97K-556-4 1.17 10.75 4.17 2.17 2.75 16.83

IT 97K-568-18 1.17 3.25 2.83 1.50 2.17 12.67

IT 98K-131-2 1.00 0.83 1.75 1.42 1.58 8.34

IT 98K-205-8 1.08 12.33 2.58 1.50 2.42 12.92

LOCAL 1.08 3.33 2.33 1.67 2.25 16.08

Mean 1.10 5.54 2.75 1.63 2.44 13.99

F-LSD (0.05) 0.29 6.87 2.00 0.60 0.53 6.55



70

Table 16: The main effect of genotype on growth component of 10 cowpea genotypes during the early and late season in Mgbakwu, 2007


INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

IT 84S-2246-4 525.00 2446.42 3.50 15.67 7.75 19.67 3.23 42.75 37.15 28.12 53.10

IT 90K-277-2 558.10 2634.23 4.33 13.00 12.92 39.17 5.67 24.92 28.71 31.08 123.10

IT 90K-82-2 485.32 2309.11 3.75 15.50 9.75 28.67 2.67 41.75 29.96 26.58 57.90

IT 93K-452-1 267.21 1375.00 4.00 12.92 10..33 29.17 9.60 23.42 26.64 24.67 93.00

IT 97K-499-35 391.63 1774.87 3.58 14.50 9.75 25.75 3.83 34.75 28.35 26.00 64.80

IT 97K-556-4 800.40 4126.42 3.75 15.08 8.00 29.08 10.42 38.00 30.04 27.50 61.70

IT 97K-568-18 400.00 1796.00 3.58 14.17 13.25 25.33 5.08 29.08 28.50 24.12 135.20

IT 98K-131-2 384.53 1542.13 3.58 13.58 11.58 29.25 4.58 25.67 28.42 22.93 112.00

IT 98K-205-8 457.72 1957.33 3.55 14.25 9.67 26.58 4.25 30.25 29.37 25.17 86.00

LOCAL 367.00 1300.25 4.58 13.25 20.17 48.08 21.75 25.08 19.25 28.25 199.80

Mean 463.61 2126.33 3.83 14.19 11.32 30.07 7.12 31.57 28.64 26.44 98.70

F-LSD (0.05) 165.00 675.60 0.83 1.40 1.860 8.00 4.63 4.85 4.95 4.28 23.04



71

4.6.2 Main effect of genotype on reproductive and grain yield component.

Table 17 showed that main effect due to genotype was significant for most reproductive and

grain yield traits sampled. The genotype IT93K-452-1 was the earliest to flower (42 days),

mature (57 days) and fill the pod (20 days) as expected, followed by IT98K-205-8 with days

to flower (44 days), maturity (61 days) and days to pod filling (20 days), IT97K-499-35 with

days to flower (44 days), maturity (62 days) and pod fill (20 days) whereas local significantly

took longer days to flower (69 days), mature (94 days) and fill the pod (33 days) followed by

IT98K-131-2 with days to flower (50 days), mature (70 days) and fill the pod (24 days).

Mean 100 seed weight ranged between 6-16 g with IT90K-277-2 and IT93K-452-1 producing

the highest 100 seed weight of 16 g each, while local variety resulted in lowest (6 g), and the

rest of the genotypes were relatively similar (13-14 g) for mean 100 seed weight. The

genotype IT98K-131-2 produced the highest number of pod per plant (22) followed by

IT93K-452-1 (20), while local variety produced the least (3). Genotype IT97K-556-4

produced the longest pod length (19 cm) which was significantly longer than the rest of the

genotypes, next longerst pod length (16 cm) were produced by IT84S-2246-4, IT90K-277-2,

IT90K-82-2, IT97K-568-18 and IT98K-131-2. The highest number of seeds per pod (14) was

produced by IT90K-82-2. Local variety consistently produced significantly lower overall

grain yield traits.

Genotype IT97K-556-4 which had the longest pod length (19 cm) did not translate to higher

number of seed per pod like in IT90K-82-2. Mean grain yield per hectare ranged between 40-

923 kg, with the highest mean grain yield recorded by IT97K-556-4 (923 kg ha-1

) followed

by IT98K-131-2 (743 kg ha-1

), IT97K-568-18 (665 kg ha-1

) and IT84S-2246-4 (628 kg ha-1

),

meanwhile seed weight and pod weight followed similar trend with grain yield for all the

genotypes. The lowest grain yield (40 kg ha-1

), seed weight (12 g) and pod weight (21 g) was

recorded by local variety. Genotype IT98K-131-2 produced the highest threshing percentage

(64 percent) and harvest index (87 percent) followed by IT93K-452-1 with threshing

percentage (55 percent) and harvest index (85 percent), while local variety supported the least

values for these traits.

72

Table 17: The main effect of genotype on reproductive and grain yield components of 10 cowpea genotypes during the early and late season in Mgbakwu, 2007

GENOTYPE BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(g)

SEED WT

(g)

GYLD/HA

(kg)

THRESH

(%)

HI

( %)

IT 84S-2246-4 47.42 63.80 20.00 9.98 14.75 11.75 15.71 308.40 188.51 628.11 51.40 32.70

IT 90K-277-2 46.83 66.60 23.67 15.86 15.17 12.08 16.04 275.82 125.10 417.33 41.92 37.30

IT 90K-82-2 49.75 63.80 23.00 11.52 11.00 13.75 15.83 276.43 160.00 533;40 49.10 43.00

IT 93K-452-1 42.25 57.00 20.17 15.98 20.08 10.58 14.96 276.10 154.23 514.12 54.73 84.80

IT 97K-499-35 44.17 62.12 19.50 12.60 11.83 9.50 16.00 235.31 142.24 473.53 49.20 41.30

IT 97K-556-4 44.50 64.20 23.08 15.20 14.42 11.33 18.96 442.60 276.90 923.00 54.94 43.80

IT 97K-568-18 46.08 64.80 22.50 14.23 19.25 12.25 16.04 326.54 199.61 665.34 52.33 53.30

IT 98K-131-2 50.40 69.83 24.33 14.25 22.00 12.33 15.96 327.83 223.00 742.60 63.90 87.30

IT 98K-205-8 43.50 61.30 21.17 12.84 12.83 10.25 14.83 227.80 137.52 458.00 46.85 39.50

LOCAL 68.83 94.32 33.00 5.57 3.00 4.08 9.54 20.84 11.90 40.42 13.40 2.50

Mean 47.88 66.78 23.08 12.80 14.43 10.79 15.39 271.73 161.93 540.03 47.72 47.00

F-LSD (0.05) 1.16 8.47 3.72 2.61 5.27 1.67 1.59 85.97 57.74 192.50 10.57 21.17




73

4.6.3 Main effect of genotype on insect damage component.

Table 18 revealed that the population of aphids and Ootheca was generally low with respect

to all the genotypes except IT97K-556-4 and IT98K-131-2 which expressed relatively higher

Ootheca score of 2.50 and 2.00 respectively. Again, white seeded genotypes were more

susceptible to attacked by bruchids as follow, IT93K-452-1 (10.92), IT97K-499-35 (9.00)

and IT98K-205-8 (8.83) while brown seeded genotypes recorded the least attack, IT97K-568-

18 (1.17), followed by IT90K-82-2 (1.33) and IT84S-2246-4 (2.08). Brown seeded IT98K-

131-2 again harbored the least expression of Maruca (0.75) followed by IT84S-2246-4 (0.83)

while on the other hand the white seeded IT98K-205-8 harbored the highest population of

Maruca (2.83) followed by local variety with Maruca count of 2.58 and IT90K-277-2 (2.42).

Genotype IT98-131-2 was less attacked by pod sucking bugs (3.33) followed by IT90K-277-

2 (3.42) whereas IT98K-205-8 was most attacked (5.33) followed by local variety (5.17),

IT84S-46-4 (5.00) and IT97K-556-4 (5.00). The least attacked by thrips (1.92) was on

IT97K-499-35 while local variety was the highest attacked 5.42 followed by IT97K-556-4

(5.25). However, the most highly attacked genotype by Ootheca (2.5), pod sucking bugs

(5.00) and thrips (5.25) was brown seeded IT97K-556-4 while IT98K-131-2 was least

attacked by Maruca (0.75) and pod sucking bugs (3.33).

4.7 Main effect of genotype on growth, reproductive, grain yield and insect damage

components in early and late season combined in Mgbakwu, 2008.


Table 19 showed that there was significant genotype differences among all the growth

components studied. Local variety produced significantly higher mean dry fodder weight

(1168 g) and fresh fodder weight (2390 g) than the other genotypes. The genotype IT97K-

556-4 followed with dry fodder weight (701 g) and fresh fodder weight (1570 g). Genotype

IT97K-568-18 supported the lowest dry fodder weight (138 g) and fresh fodder weight (466

g) followed by IT90K-82-2, dry fodder weight (167 g) and fresh fodder weight (545 g). Local

variety expressed significantly higher number of branches (4) than the rest genotypes, while

IT97K-499-35 produced the least (1). Similarly, local variety supported significantly higher

number of internodes (17) and number of leaves (72) while IT84S-2246-4 expressed

significantly lower number of internodes (7) and number of leaves (13).

74

Table 18: The main effect of genotype on insect damage of 10 cowpea genotypes during the early and late season in Mgbakwu, 2007


IT 84S-2246-4 1.58 2.08 0.83 1.92 5.00 2.25

IT 90K-277-2 1.58 4.42 2.42 1.83 3.42 3.00

IT 90K-82-2 1.42 1.33 2.17 1.92 4.42 3.67

IT 93K-452-1 1.67 10.92 1.33 1.42 4.00 2.50

IT 97K-499-35 1.92 9.00 2.00 1.42 4.58 1.92

IT 97K-556-4 1.33 8.00 1.83 2.50 5.00 5.25

IT 97K-568-18 1.50 1.17 2.00 1.75 4.17 3.00

IT 98K-131-2 1.58 3.17 0.75 2.00 3.33 3.25

IT 98K-205-8 1.50 8.83 2.83 1.42 5.33 2.17

LOCAL 1.83 4.17 2.58 1.67 5.17 5.42

Mean 1.59 5.00 1.88 1.78 4.44 3.24

F-LSD (0.05) 0.40 6.81 2.11 0.53 3.20 1.57



75

The highest number of nodules (21) came from IT97K-556-4 followed by local variety (16)

while IT98K-205-8 produced the least (7). Again IT84S-2246-4 expressed significantly

higher number of stands (37) and peduncle length (28cm) while local variety produced the

lowest peduncle length (15 cm). The genotypes IT90K-277-2 and local variety produced

significantly longer root length of 36 cm each and vine length of 87 cm and 128 cm

respectively. Late maturing genotypes produced longer root and vine length than early

maturing genotypes.


Table 20 revealed that differences between genotypes for almost all the reproductive and

grain yield components were highly significant. The local variety was the latest to flower (66

days), mature (98 days) and consequently the latest to fill the pods (32 days) while IT93K-

452-1 was the earliest to flower (41 days), mature (62 days) and fill the pods (20 days). The

rest of the genotypes took similar number of days to flower, mature and fill the pods. Mean

100 seed weight ranged from 6-18 g with IT90K-277-2 producing the highest (18 g) followed

by IT93K-452-1 and IT98K-131-2 with 100 seed weight of 17 g each, while local variety

produced the least, 6 g. Genotype IT97K-568-18 produced highest number of pod per plant

(12) while local variety produced the least (2). The highest number of seed per pod was

produced by IT90K-82-2 (10) while local variety produced the least (4). Differences among

genotypes for pod length were narrow with IT97K-556-4 producing the highest pod length

(16 cm) and local variety the lowest (10 cm). Local variety consistently produced the lowest

pod weight (9 g), seed weight (7 g) and grain yield per hectare (25 kg ha-1

) while IT97K-556-

4 produced significantly higher grain yield (722 kg ha-1

), seed weight (217 g) and pod weight

(318 g) followed by IT93K-452-1 with grain yield (566 kg), seed weight (170 g) and pod

weight (242 g) and IT98K-131-2 with grain yield (504 kg ha-1

), seed weight (151 g) and pod

weight (204 g). IT90K-82-2 and IT98K-131-2 produced the highest threshing percentage (71

percent) each which however did not differ from IT97K-568-18, IT90K-277-2, IT98K-131-2,

IT97K-499-35, IT84S-2246-4 and IT93K-452-1, while local variety produced the least (19

percent). IT98K-131-2 produced the highest harvest index (91 percent) followed by IT90k-

82-2 (79 percent) and then IT97K-568-18 (74 percent) while local variety supported the least

(4 percent).

76

Table 19: The main effect of genotype on growth component of 10 cowpea genotypes during the early and late season in Mgbakwu, 2008


INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

IT 84S-2246-4 333.50 768.11 2.38 15.17 6.92 13.30 8.38 37.25 27.69 32.83 20.60

IT 90K-277-2 404.00 988.44 2.96 12.92 11.67 25.00 14.00 23.92 23.98 35.46 86.81

IT 90K-82-2 167.23 545.00 2.00 13.83 9.00 16.26 9.50 29.50 22.53 34.21 20.40

IT 93K-452-1 271.64 720.00 2.58 15.00 8.75 16.90 13.17 32.42 21.43 31.42 64.84

IT 97K-499-35 211.00 551.55 1.33 15.42 7.58 12.81 7.96 35.33 19.65 33.96 34.00

IT 97K-556-4 701.10 1570.14 3.33 14.67 8.33 24.20 21.02 32.67 23.08 33.42 27.63

IT 97K-568-18 138.24 466.00 2.29 13.25 11.42 18.54 14.71 22.33 23.13 34.88 49.50

IT 98K-131-2 205.42 555.26 2.21 14.08 11.08 21.32 11.58 23.42 24.07 30.08 51.92

IT 98K-205-8 375.45 781.60 1.88 15.33 10..25 15.00 7.38 33.08 22.45 29.46 44.00

LOCAL 1168.00 2390.22 4.21 12.58 16.50 72.33 16.38 23.58 14.93 35.79 128.30

Mean 397.51 934.00 2.52 14.22 10.15 23.60 12.41 29.35 22.29 33.15 52.80

F-LSD (0.05) 252.30 466.50 0.88 1.31 2.35 17.91 7.56 3.97 4.64 5.47 28.92



77

Table 20: The main effect of genotype on reproductive and grain yield components of 10 cowpea genotypes during the early and late season in Mgbakwu, 2008

GENOTYPE BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(g)

SEED WT

(g)

GYLD/HA

(kg)

THRESH

(%)

HI

( %)

IT 84S-2246-4 48.67 69.00 20.33 12.08 7.67 8.00 14.13 174.00 121.10 404.00 64.70 52.60

IT 90K-277-2 49.25 71.40 22.17 17.83 11.00 7.50 15.00 204.50 144.62 482.14 68.00 41.92

IT 90K-82-2 50.58 70.81 22.17 13.08 7.58 10.25 13.52 183.42 132.60 442.25 71.11 79.29

IT 93K-452-1 40.67 62.20 21.58 17.00 10.25 7.42 14.00 242.00 169.84 566.00 63.24 61.12

IT 97K-499-35 42.50 65.10 22.58 15.58 6.62 8.62 14.41 156.56 108.41 358.22 64.70 73.20

IT 97K-556-4 46.50 70.14 23.58 15.50 7.62 7.25 15.68 318.20 216.73 722.43 53.62 31.73

IT 97K-568-18 47.25 70.33 23.08 16.42 12.17 9.12 14.00 144.11 102.80 343.00 69.30 74.36

IT 98K-131-2 48.08 69.20 21.17 17.33 9.12 9.08 14.70 204.44 151.10 504.00 70.52 90.71

IT 98K-205-8 42.83 66.35 23.50 16.42 8.00 8.04 14.00 187.58 129.85 433.35 66.66 72.00

LOCAL 66.00 98.00 32.08 5.58 1.92 3.75 9.92 9.00 7.40 25.00 19.40 3.90

Mean 48. 23 71.25 23.00 14.68 8.20 7.90 14.00 182.13 128.33 428.02 61.10 64.00

F-LSD (0.05) 2.65 11.54 4.62 1.77 3.61 1.75 1.88 93.90 67.69 225.60 7.82 53.52




78

4.7.3 Genotype main effect on insect pest damage component.

Table 21 revealed that all the genotypes differed significantly for bruchids, Maruca and thrips

infestation. Differences among genotypes for aphids, Ootheca and pod sucking bugs were

however marginal. Genotype IT98K-131-2 a consistently high grain yielding genotype

expressed the least infestation of bruchids (2.00), Maruca (1.42), pod sucking bugs (2.00) and

thrips (8.00). Local variety on the other hand habored the highest aphids population of 3.08.

The two genotypes with highest infestation by bruchids are white seeded: IT98K-205-8

(12.17) and IT97K-499-35 (10.83) while brown seeded genotype maintained very low

population of bruchids. Thrips populations on all the genotypes were generally high but low

(8.00) on IT98K-131-2, while the highest population (25.00) was recorded for local variety,

followed by IT93K-452-1 (22.00), IT90K-82-2 (19.00) and IT98K-205-8 (19.00).

4.8 Genotype main effect on growth, reproductive, grain yield and insect damage

components in early season combined over 2007 and 2008, Mgbakwu.


Table 22 showed that there was significant genotype effect for most growth components

studied in early season in Mgbakwu combined over 2007 and 2008. The highest dry fodder

weight (1171 g) and fresh fodder weight (2550 g) was produced by local variety followed by

IT97K-556-4, with dry fodder weight (962 g), however, IT97K-556-4 supported significantly

higher fresh fodder weight (3176 g) than local variety. Conversely, IT93K-452-1 produced

the least dry fodder weight (288 g) and fresh fodder weight (900 g) followed by IT98K-131-2

with dry fodder (296 g) and dry fodder (968 g). Local variety expressed significantly higher

growth component such as number of branches (5), number of internodes (22), number of

leaves (81), number of nodules (29) and vine length (219 cm), but supported significantly

lower number of hills (14) and number of stand (26). As expected, IT84S-2246-4 and IT90K-

82-2 supported significantly higher expression of number of hills and number of stand.

Similarly, IT84S-2246-4 produced significantly higher peduncle length (34 cm) while

IT93K-452-1 produced the least (23 cm). Meanwhile, IT90K-277-2 was next to local variety

in expressing higher number of leaves (32), root length (37cm) and vine length (144 cm).

79

Table 21: The main effect of genotype on insect damage of 10 cowpea genotypes during the early and late season in Mgbakwu, 2008


IT 84S-2246-4 1.50 2.67 2.50 1.42 2.58 14.00

IT 90K-277-2 1.17 2.58 2.08 1.33 2.33 16.00

IT 90K-82-2 1.17 3.00 3.00 1.50 2.33 19.00

IT 93K-452-1 1.17 10.08 3.33 1.42 2.17 22.00

IT 97K-499-35 1.42 10.83 2.42 1.42 2.58 16.00

IT 97K-556-4 1.25 10.25 2.92 1.42 2.25 13.00

IT 97K-568-18 1.42 3.92 2.50 1.50 2.25 12.00

IT 98K-131-2 1.50 2.00 1.42 1.42 2.00 8.00

IT 98K-205-8 1.25 12.17 3.33 1.33 2.33 19.00

LOCAL 3.08 7.33 2.83 1.50 3.92 25.00

Mean 1.49 6.48 2.63 1.425 2.47 16.45

F-LSD (0.05) 0.49 4.56 1.55 0.24 0.577 6.76



80


Table 23 showed that there were significant differences among the genotypes for all the

reproductive and grain yield components studied. The genotype IT90K-277-2 took the

longest time to flower (54 days) and mature (75 days) and consequently the longest time to

fill the pod (25 days). The local variety did not flower at all at this period. On the other hand

IT93K-452-1 was the earliest to flower (42 days) and mature (64 days) and also the earliest to

fill the pod (21 days). Mean 100 seed weight ranged between 12–19 g, with the genotype

IT97K-556-4 expressing the highest 100 seed weight (19 g) while IT84S-2246-4 and IT90K-

82-2 produced the least 12 g each. Genotype IT97K-568-18 supported significantly higher

number of pod per plant (20) while IT97K-499-35 produced the least (12). Genotype IT 90K-

82-2 supported the highest number of seed per pod (14) understandably because it gave the

least seed size. Genotype IT97K-556-4 produced the longest pod length (19 cm) while

IT93K-452-1 expressed the least (14 cm).

Similarly, IT97K-556-4 produced statistically the highest grain yield per hectare (1394 kg),

seed weight (418 g) and pod weight (616 g). The genotype IT98K-131-2 followed with grain

yield per hectare of (921 kg), seed weight (276 g) and pod weight (389 g), IT93K-452-1 with

grain yield per hectare (864 kg), seed weight (259 g) and pod weight (386 g), IT84S-2246-4

with grain yield per hectare (848 kg), seed weight (254 g) and pod weight (398 g). Genotype

IT 97K-499-35 recorded the least grain yield per hectare (638 kg), seed weight (191 g) and

pod weight (297 g). Genotype IT 98K-131-2 manifested statistically higher threshing

percentage (72 percent) and harvest index (93 percent) followed by IT93K-452-1 with

threshing percentage (68 percent) and harvest index (90 percent). The genotype IT90K-82-2

produced the lowest threshing percentage (59 percent) while IT84S-2246-4 supported the

lowest harvest index (43 percent).


Table 24 showed that early season in Mgbakwu combined over 2007 and 2008 habored very

low insect pest population. Again, IT98K-131-2 expressed lowest population of aphids

(1.50), Maruca (0.42), pod sucking bug (1) and thrips (3).

81

Table 22: The main effect of genotype on growth component of 10 cowpea genotypes during the early season of 2007 and 2008 in Mgbakwu


INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

IT 84S-2246-4 608.02 2004.00 2.63 15.83 8.17 18.50 8.83 43.38 33.58 30.38 47.00

IT 90K-277-2 592.00 2050.73 2.96 15.25 14.92 31.64 14.33 31.25 26.78 37.25 143.71

IT 90K-82-2 331.15 1258.48 2.75 15.50 10.50 24.40 8.08 37.75 24.10 32.05 40.70

IT 93K-452-1 288.05 900.15 2.75 15.50 9.08 20.33 17.50 32.25 22.83 27.25 98.40

IT 97K-499-35 350.14 1217.00 2.17 15.33 10.17 17.20 7.50 36.33 25.77 29.58 68.93

IT 97K-556-4 962.00 3176.00 3.33 15.58 9.50 26.51 20.58 38.58 26.18 33.67 57.40

IT 97K-568-18 312.25 1204.36 2.88 14.42 14.75 22.65 14.25 28.50 26.44 31.46 117.22

IT 98K-131-2 296.17 968.11 2.71 14.58 14.25 26.52 10.67 25.53 26.33 27.33 113.00

IT 98K-205-8 588.00 1657.00 2.54 15.25 10.67 21.97 7.08 34.58 28.76 29.00 86.95

LOCAL 1171.00 2550.00 4.79 13.83 22.42 81.00 29.08 26.17 - 33.58 218.90

Mean 550.21 1698.05 2.95 15.11 12.44 29.10 13.79 33.42 26.75 31.18 99.20

F-LSD (0.05) 327.20 884.80 0.82 0.75 2.49 17.16 8.95 3.62 4.03 5.38 34.57



82

Table 23: The main effect of genotype on reproductive and grain yield components of 10 cowpea genotypes during the early season of 2007 and 2008 in Mgbakwu

GENOTYPE BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(kg)

SEED

WT (kg)

GYLD/HA

(kg)

THRESH

(%)

HI

( %)

IT 84S-2246-4 49.42 73.20 23.83 11.50 16.42 11.79 16.42 398.11 254.35 848.00 64.61 43.40

IT 90K-277-2 54.00 75.44 24.92 18.18 15.25 11.29 16.61 386.00 225.00 750.05 58.64 60.33

IT 90K-82-2 50.50 64.00 20.75 12.29 12.50 14.08 15.17 360.34 244.40 815.11 67.44 89.00

IT 93K-452-1 42.00 63.80 21.00 16.30 17.83 11.00 14.42 386.00 259.10 864.35 67.67 89.95

IT 97K-499-35 46.33 68.27 22.50 15.02 11.54 11.83 15.19 297.43 191.33 637.56 64.39 63.11

IT 97K-556-4 49.41 71.33 22.33 18.67 13.04 11.79 19.02 616.25 418.24 1394.00 68.36 57.90

IT 97K-568-18 49.00 72.85 23.83 16.30 20.00 12.46 15.38 351.08 237.50 791.50 67.93 81.43

IT 98K-131-2 49.83 72.30 22.50 16.24 17.21 12.42 16.52 389.00 276.41 921.21 72.05 93.33

IT 98K-205-8 44.75 67.93 23.17 15.78 14.33 11.75 15.19 341.03 227.32 758.00 66.37 51.58

LOCAL - - - - - - - - - - - -

Mean 43. 57 64.00 21.65 14.03 14.33 11.24 15.63 352.00 233.30 778.00 59.65 68.40

F- LSD (0.05) 2.19 11.90 4.83 0.79 4.74 1.64 1.43 132.40 90.60 302.20 4.27 28.91




83

The local variety habored the highest population of aphids (2.25) while the two genotypes

with highest expression of bruchids infestation were white seeded: IT97K-499-35 (5.40) and

IT98K-205-8 (6.17). Conversely, the lowest was IT90K-82-2 (0.50) a brown seeded

genotype. Genotype IT97K-556-4 had the highest infestation by Ootheca (2.00) while

IT93K-452-1 supported the highest population of thrips (7.25).

4.9 Genotype main effect for growth, reproductive, grain yield and insect pest damage

components in late season combined over 2007 and 2008, Mgbakwu.


The growth of genotypes in late season combined over the two years showed that IT97K-556-

4 produced significantly higher dry fodder (538 g) and fresh fodder weight (2520 g), while

IT97K-568-18 produced the least dry fodder (226 g) and fresh fodder (1058 g) (Table 25).

Genotype IT84S-2246-4 again supported higher number of hills (15) and subsequently higher

number of stands (37) while IT 90K-277-2 produced the least number of hills (11) and

number of stand (18). Local variety produced significantly higher number of internodes (14),

number of leaves (39), root length (31 cm) and vine length (109 cm). Meanwhile, IT84S-

2246-4 produced significantly lower number of internodes (7), number of leaves (15),

number of nodules (4) and vine length (27 cm) however; it produced high peduncle length

(31 cm) and root length (31).


Table 26 showed that genotype main effect for late season combined over the two years was

significant for all the reproductive and grain yield parameters sampled. As expected local was

the latest to flower (61 days), mature (89 days) and to fill the pods (30 days) while IT93K-

452-1 took the least number of days to flower (41 days) and mature (54 days). Mean 100 seed

weight ranged from 11-17 g with IT84S-2246-4 and local variety producing the least, 11 g

each, while IT93K-452-1 expressed the highest, 17 g, followed by IT90K-277-2 (16 g).

IT98K-131-2 supported the highest number of pod per plant (14) followed by IT93K-452-1

(13) while local variety produced the least (3) followed by IT84S-2246-4 (6) and IT90K-82-2

(6).

84

Table 24: The main effect of genotype on insect damage of 10 cowpea genotypes during the early season of 2007 and 2008 in Mgbakwu


IT 84S-2246-4 1.75 0.58 0.67 1.83 1.50 4.67

IT 90K-277-2 1.58 0.83 0.67 1.67 1.25 4.92

IT 90K-82-2 1.58 0.50 0.92 1.75 1.42 7.17

IT 93K-452-1 1.67 4.67 1.17 1.58 1.40 7.25

IT 97K-499-35 2.00 5.40 1.00 1.67 1.50 6.33

IT 97K-556-4 1.58 5.33 0.75 2.00 1.17 3.25

IT 97K-568-18 1.67 1.83 0.83 1.83 1.33 5.42

IT 98K-131-2 1.50 2.25 0.42 1.83 1.00 3.00

IT 98K-205-8 1.67 6.17 1.00 1.75 1.33 6.25

LOCAL 2.25 - - 1.75 - -

Mean 1.72 2.76 0.74 1.77 1.22 4.83

F –LSD (0.05) 0.76 2.94 0.63 0.36 0.44 3.64



85

Table 25: The main effect of genotype on growth component of 10 cowpea genotypes during the late season of 2007 and 2008 in Mgbakwu


INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

IT 84S-2246-4 284.13 1210.43 3.25 15.00 6.50 14.50 3.88 36.67 31.36 30.58 26.73

IT 90K-277-2 338.00 1572.01 4.33 10.67 9.67 32.92 5.33 17.58 25.91 29.29 66.10

IT 90K-82-2 321.06 1595.00 3.00 13.83 8.25 20.42 4.08 33.50 28.38 28.54 37.50

IT 93K-452-1 252.36 1195.27 3.83 12.42 10.00 25.75 5.33 23.58 25.25 28.83 59.44

IT 97K-499-35 252.14 1111.07 2.75 14.58 7.17 21.42 4.29 33.75 22.23 30.38 29.90

IT 97K-556-4 538.09 2520.33 3.75 14.17 6.83 26.83 10.55 32.08 26.95 27.25 31.92

IT 97K-568-18 226.27 1058.00 3.00 13.00 9. 92 21.29 5.54 22.92 25.18 27.54 67.55

IT 98K-131-2 276.19 1130.00 3.08 13.08 8.42 24.04 5.50 23.58 26.15 25.68 50.97

IT 98K-205-8 247.11 1082.06 2.92 14.33 9.25 19.67 4.54 28.75 22.96 25.62 43.10

LOCAL 382.00 1140.19 4.00 12.00 14.25 39.42 9.04 22.50 17.48 30.46 109.11

Mean 312.00 1361.00 3.39 13.31 9.03 24.62 5.84 27.49 25.19 28.42 52.20

F-LSD (0.05) 121.40 437.00 0.87 1.54 1.44 5.97 2.75 5.46 5.10 5.61 18.76



86

As expected, IT90K-82-2 expressed highest number of seed per pod (10) while local

produced the least, 4. Genotype IT97K-556-4 consistently gave the longest pod length (16

cm) while local variety expressed the least pod length (7 cm).

Genotype IT98K-131-2 produced significantly higher grain yield (326 kg ha-1

), seed weight

(98 g) and threshing percentage (62 percent) followed by IT97K-556-4 with grain yield (251

kg ha-1

) and seed weight (75 g), IT93K-452-1 with grain yield (216 kg ha-1

) and seed weight

(65 g) and IT97K–568-18 with grain yield (216 kg ha-1

) and seed weight (65 g). Local variety

produced significantly the lowest pod weight (30 g), seed weight (19 g), grain yield (64 kg

ha-1

), threshing percentage (33 percent) and harvest index (6 percent). Meanwhile, IT97K-

568-18 produced significantly higher harvest index (83 percent) than the rest genotypes.


Table 27 confirmed the earlier observation that late season supported significantly high

expression of bruchids, Maruca, pod sucking bugs and thrips, while the population of aphids

and Ootheca were significantly low in late season. Local variety harbored more population of

aphids (2.67), pod sucking bugs (6.75) and thrips (27.33) while IT98K-131-2 as usual had the

lowest infestation by bruchids (2.92), Maruca (1.75), pod sucking bugs (4.00) and thrips

(8.00). The lowest expression of aphids (1) was manifested by IT90K-82-2. Bruchids was

highest in IT93K-452-1 (16.33), IT98K-205-8 (14.83), and IT97K-499-35 (14.42) all of

which are white seeded genotypes but lowest in IT98K-131-2 (2.92), IT97K-568-18 (3.25),

IT90K-82-2 (3.83), IT84S-2246-4 (4.17) which are all brown seeded.

The highest Maruca population were expressed by IT98K-205-8 (5.17), IT90K-82-2 (4.25)

but lowest in IT98K-131-2 (1.75) and IT84S-2246-4 (2.67) while Ootheca population across

all the genotypes were however similar. Meanwhile, the highest population of pod sucking

bugs (6.75) was expressed by local variety, IT98K-205-8 (6.33), IT97K-556-4 (6.08), IT84S-

2246-4 (6.08) with least population expressed by IT98K-131-2 (4), IT90K-277-2 (4.50),

IT93K-452-1 (4.75). The least population of thrips (8.00) was linked with IT98K-131-2

followed by IT97K-568-18 (10.00) while the highest infestation was manifested by local

variety (27.33) followed by IT93K-452-1 (17.42), IT90K-82-2 (15.58) and IT98K-205-8

(14.53).

87

Table 26: The main effect of genotype on reproductive and grain yield components of 10 cowpea genotypes during the late season of 2007 and 2008 in Mgbakwu

GENOTYPE BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(kg)

SEED WT

(kg)

GYLD/HA

(kg)

THRESH

(%)

HI

( %)

IT 84S-2246-4 46.67 59.60 16.50 10.56 6.00 7.96 13.42 85.10 55.30 184.00 51.50 41.80

IT 90K-277-2 45.58 62.80 20.92 15.52 10.92 8.29 14.18 94.80 44.70 149.09 51.36 18.91

IT 90K-82-2 46.83 60.22 17.17 12.31 6.08 9.92 14.83 99.64 48.11 160.13 52.70 55.12

IT 93K-452-1 41.33 54.00 19.50 16.68 12.50 7.00 14.67 132.40 64.96 216.00 50.38 30.60

IT 97K-499-35 41.00 61.00 19.58 13.17 6.92 6.29 14.49 95.72 58.50 194.63 49.53 51.33

IT 97K-556-4 42.00 63.00 24.33 12.03 9.00 6.79 15.63 144.20 75.44 251.00 40.20 17.50

IT 97K-568-18 44.33 62.20 21.75 14.35 11.42 8.92 14.72 119.33 64.90 215.47 53.46 83.43

IT 98K-131-2 43.75 66.83 23.00 15.34 13.92 9.00 14.64 142.70 97.79 326.42 62.40 55.70

IT 98K-205-8 41.58 59.80 21.50 13.48 6.50 6.54 13.63 74.35 40.10 134.00 47.00 60.15

LOCAL 61.17 89.00 30.00 11.15 3.33 3.87 7.17 30.27 19.30 64.08 32.70 6.30

Mean 45.42 63.85 22.00 13.46 8.66 7.46 13.74 101.80 56.94 190.01 49.10 42.10

F-LSD (0.05) 1.58 8.29 3.67 3.47 3.49 2.35 1.81 46.95 28.11 93.70 15.54 48.19




88

Table 27: The main effect of genotype on insect damage of 10 cowpea genotypes during the late season of 2007 and 2008 in Mgbakwu


IT 84S-2246-4 1.33 4.17 2.67 1.50 6.08 11.58

IT 90K-277-2 1.25 5.17 3.83 1.50 4.50 13.58

IT 90K-82-2 1..00 3.83 4.25 1.67 5.33 15.58

IT 93K-452-1 1.17 16.33 3.50 1.25 4.75 17.42

IT 97K-499-35 1.33 14.42 3.42 1.17 5.67 11.92

IT 97K-556-4 1.08 12.92 4.00 1.92 6.08 15.33

IT 97K-568-18 1.25 3.25 3.67 1.42 5.08 10.00

IT 98K-131-2 1.50 2.92 1.75 1.58 4.00 8.00

IT 98K-205-8 1.08 14.83 5.17 1.00 6.33 14.50

LOCAL 2.67 11.50 4.58 1.42 6.75 27.33

Mean 1.37 8.93 3.68 1.44 5.46 14.53

F-LSD (0.05) 0.61 7.73 2.34 0.41 3.23 5.44



89

4.10 Interaction effects of year, season and location on genotype performance for some

selected growth, reproductive and grain yield traits (Performance of genotype in each

environment)-Experiment one.

The model that is used for generating the biplot model, along with the percentages of GGE

explained by the two axes, are indicated at the upper-left corner of the biplot. E1 to E8

represents environment one to eight and the interpretation of each environment are presented

in a legend below each figure.

Figure 1a showed the GGE biplot for performance of genotypes across the environments for

grain yield, which explained 86.7 percent (78.7 percent + 8 percent) of the variation in grain

yield per hectare. Figure 1a revealed that local variety produced below average grain yield in

all the environments, while all the improved genotype produced above average grain yield.

Early season (E3, E5, E7, E1) generally supported higher grain yield than late season in both

locations. Of all the environments, E3 (year two, early season in Ishiagu) produced the best

grain yield while E8 (year two, late season in Mgbakwu) produced the worst. Furthermore,

E3 environment favoured higher and more stable grain yield production for all the genotypes.

Genotype IT 97K-556-4 a vetex genotype gave the highest grain yield in E5 (Year one early

season, Mgbakwu) and E7 (Year two early season, Mgbakwu) while IT 98K-131-2 expressed

highest grain yield in E1 (Year one early season, Ishiagu) and E4 (Year two late season,

Ishiagu). With respect to grain yield, IT 97K-556-4 and IT 98K-131-2 were best adapted to

Mgbakwu and Ishiagu environments respectively. However, IT97K-556-4 is strongly adapted

to early season environment having produced the highest grain yield in that environment

while it produced the least grain yield in late season (E8 and E2). Genotypes IT 97K-499-35

and IT 97K-277-2 produced highest grain yield in E3 (year two, early season in Ishiagu).

Figure 1b showed that E1 (Year one early season, Ishiagu) and E4 (Year two late season,

Ishiagu) are the most ideal environment for cowpea grain production as all the genotypes

tested expressed above average grain yield across the two environments. In order words

Ishiagu is the most ideal environment for grain yield compared to Mgbakwu location. Figure

2 showed the biplot for dry fodder yield of genotypes across test environments which

explained 89.7 percent (62 percent + 27.7 percent) of the variation of the trait.

90

Figure 1a. Biplot of genotype by environment- year, season and location (GXE) for

grain yield per hectare.

E1= Year one early season Ishiagu; E2=Year one late season Ishiagu; E3=Year two early

season Ishiagu; E4= Year two late season Ishiagu; E5= Year one early season Mgbakwu;

E6=Year one late season Mgbakwu; E7= Year two early season Mgbakwu; E8= Year two

late season Mgbakwu.

91

Figure 1b. Biplot of genotype by environment- year, season and location (GXE) for

grain yield per hectare indicating ideal environments.





92

Figure 2. Biplot of genotype by environment- year, season and location (GXE) for dry

fodder yield.





93

The genotype IT97K-556-4 produced the highest dry fodder relative to other genotypes in E4

(Year two late season, Ishiagu), E5 (Year one early season, Mgbakwu), E6 (Year one late

season, Mgbakwu) and E3 (Year two early season, Ishiagu), while local produced the highest

dry fodder in the rest environments. Local variety however produced exceptionally high dry

fodder yield in E7 (Year two early season, Mgbakwu). E8 (Year two late season, Mgbakwu)

is the poorest environment as it supported the least overall dry fodder yield for all the

genotypes. The genotypes local, IT 97K-556-4 and IT 90K-277-2 had higher than average

dry fodder yield in all the environments, IT 98K-205-8 and IT 84S-2246-4 had near average

while the rest genotypes had lower than average dry fodder yield. The local variety with the

least grain yield in Figure 1a and highest fodder yield in Figure 2 showed that the local

variety is truly a fodder type cowpea. Genotypes IT 97K-556-4 and IT 90K-277-2 that

produced high grain and dry fodder yield can be classified as dual-purpose while the rest

genotypes are purely grain type cowpea.

Figure 3 showed the biplot for 100 seed weight across the genotypes and environments

which captured 95.3 percent (88.6 percent + 6.7 percent) of the variation of the 100 seed

weight. Generally early season (E1, E3, E5 and E7) supported higher 100 seed weight than

late season. Genotypes local, IT84S-2246-4 and IT90K-82-2 had lower than average 100 seed

weight and never excelled in any particular environment, while the rest genotypes had higher

than average 100 seed weight. Out of those that had higher than average 100 seed weight, IT

97K-556-4, IT 93K-452-1 and IT 90K-277-2 produced the highest 100 seed weight across all

the environments. Highest and consistent 100 seed weight was expressed by IT 97K-556-4

and IT 90K-277-2 in early season across the three environments (E5, E1 and E7) while IT

93K-452-1 on the other hand produced the highest 100 seed weight across all the locations in

late season (E2, E4, E8 and E6). The following medium maturing genotypes: IT 98K-131-2

and IT 90K-568-18 produced the highest 100 seed weight in E4 (late season). Early season

generally expressed higher 100 seed weight than late season probably because of better

environmental resources and less post flowering insect pests in early than late season.

94

Figure 3. Biplot of genotype by environment- year, season and location (GXE) for 100

seed weight.





95

Figure 4 showed the biplot for threshing percentage across the genotypes and environments

which explained 93.2 percent (86.9 percent + 6.3 percent) of the variation of the trait. Figure

4 indicated that local variety produced the least threshing percentage. Genotypes IT98K-131-

2 expressed the highest threshing percentage in all the environments, while the rest improved

genotypes expressed intermediate but similar threshing percentage in most environments. E2

(late season) supported the least threshing percentage across all the genotypes studied. Early

season however supported highest expression of threshing percentage across all the

genotypes than late season.

Figure 5 showed the biplot for harvest index across the environments and explained 76.7

percent (58.8 percent + 17.9 percent) of the variation of the trait. The genotypes local, IT

90K-277-2, IT 97K-556-4 and IT 84S-2246-4 had lower than average harvest index with

local producing the least. The rest genotypes had higher than average harvest index. The

genotypes that expressed low harvest index had high dry fodder weight and vice versa.

Genotypes IT 98K-131-2 and IT 93K-452-1 are the vertex genotypes and manifested highest

harvest index in E5 (Year one early season, Mgbakwu), E1 (Year one early season, Ishiagu),

E2 (Year one late season, Ishiagu), E6 (Year one late season, Mgbakwu) and E3 (Year two

early season, Ishiagu), while IT 97K-499-35 produced highest harvest index in E8 (Year two

late season, Mgbakwu) along with IT 98K-205-8 and IT 90K-568-18. The least expression of

harvest index across all the genotypes was found in E7 (Year two early season, Mgbakwu).

Figure 6 showed the biplot for number of plant stands across the genotypes and

environments. Local variety produced the least number of plant stand in all the environments.

Genotypes IT 97K-568-18, IT 98K-131-2 and IT 90K-277-2 had lower than average number

of plant stand, IT 93K-452-1 had average while the rest genotypes produced higher than

average number of plant stand. The genotype IT 84S-2246-4 produced consistently and

exceptionally higher number of plant stands in all the environments except in E6 (year one

late season in Mgbakwu). The genotype IT 90K-82-2 produced the next highest number of

plant stand after IT 84S-2246-4 particularly in E6. Number of plant stand was more

expressed in early season than late season in both locations and for most genotypes.

96

Figure 4. Biplot of genotype by environment- year, season and location (GXE) for

threshing percentage.





97

Figure 5. Biplot of genotype by environment (year, season and location) interaction for

harvest index.





98


number of plant stand.





99

4.11 Genotype by trait (GXT) relationship combined over Ishiagu and Mgbakwu for

2007 and 2008 (Experiment one).

The GXT biplot (Figure 7) contains marker for each of the ten genotypes indicated in lower

case and different from markers for each of the seven selected traits indicated in upper case.

The model used in generating the biplot along with the percentages of GXT explained by the

two axes is shown at the upper left corner of the biplot. The GXT biplot explained 74.6

percent (59.3 percent + 15.3 percent) of the total variation due to GXT. The convex hull is

drawn on genotypes relatively remote from the biplot into several sectors, and the traits falls

within the convex hull. The perpendicular lines divide the biplot into several sectors. There

are four sectors in Figure 7. The following genotypes: Local, IT 98K-131-2, IT 93K- 452-1

and IT 84S-2246-2 are located at the vertex of the polygon and are referred to as vertex

genotypes, indicating that the genotypes are highly divergent from each other with respect to

the traits studied. These vertex genotypes are different in their maturity as they represent the

three maturity classes of early, medium and late categories (Table1). The genotypes IT 93K-

452-1 and IT 98K-131-2 expressed higher reproductive and grain yield components in both

Mgbakwu and Ishiagu locations since the two genotypes jointly formed the vertex genotypes

where all the grain yield components are found. The genotypes IT 90K-568-18, IT 90K-277-

2 and IT 98K-205-8 equally produced high grain yield component because they are located

within the sector where all the grain yield components are embedded. The genotype IT 84S-

2246-2 manifested the highest number of plant stands (high plant population) in both

locations, followed by IT 97K-556-4, IT 90K-82-2 and IT 97K-499-35. The local variety

flowered latest in both locations while it produced the highest dry fodder weight in Mgbakwu

as expected. Ishiagu location supported higher expression of number of plant stand and grain

yield than Mgbakwu.

4.12 Performance of genotypes across environments (GXE) for insect damaged

components (Experiment one).

Figure 8 showed the biplot for performance of genotypes across all the environments for

aphid damage which explained 94.1 percent (89.5 percent + 4.6 percent) of the variation

within the trait. The local variety had the highest infestation by aphids in all the environments

particularly in E6 (year one, late season in Mgbakwu) and E8 (year two, late season in

Mgbakwu).

100

Figure 7. Biplot on genotype by traits (GXT) for selected growth, reproductive and

grain yield traits.

DFWMGM= Dry fodder weight in mgbakwu; BLOOMISH= Days to 50 percent flowering in

Ishiagu; BLOOMMGB= Days to 50 percent flowering in Mgbakwu; DFWTISH= Dry fodder

weight in Ishiagu; NSTANDMGB= Number of plant stand in Mgbakwu; NSTANDISH=

Number of plant statnd in Ishiagu; GYDMGB= Grain yield Mgbakwu; GYDISH= Grain

yield Ishiagu; T %ISH= Threshing percentage Ishiagu; T%MGB= Threshing percentage

Mgbakwu; HI ISH= Harvest index Ishiagu; HI MGBA= Harvest index Mgbakwu;

100SWTMGB= 100 seed weight Mgbakwu; 100SWTISH= 100 Seed weight Ishiagu.

101

All the rest genotypes had below average infestation by aphids. Aphids were least expressed

in E2 (year one late season, Ishiagu) with IT 84S-2246-4 being least infested by aphids. All

the improved genotypes had higher populations of aphids in early than late season while local

variety was however, more attacked in late season.

Figure 9 showed the biplot for performance of genotypes across all the environments for

Maruca damage which explained 82.1 percent (62.5 percent + 19.6 percent) of the variation

within Maruca damage trait. Genotype IT 98K-131-2 habored the least infestation by Maruca

in all the seasons and locations while local variety was most attacked in late season and in the

second year by Maruca, E6 (year two late season, Ishiagu), E4 (year two late season ishiagu)

and E8 (year two, late season, Mgbakwu). Genotype IT 97K-556-4 was more infested by

Maruca in E2 (year one late season, Ishiagu) while IT 93K-452-1 was more attacked by

Maruca in E7 (year two early season, Mgbakwu). Maruca damage was more in late season

than early season and in second year environment than in first year. E1 (year one early

season, Ishiagu), E3 (year two early season, Ishiagu), E5 (year one early season, Mgbakwu)

and E7 (year two early season, Mgbakwu) are all early season environments and are found

within the inner cycle indicating lower population of Maruca and supporting the observation

earlier made that late season supported higher population of Maruca damage than early

season. The genotypes IT 97K-499-35 and IT 90K-568-18 were more attacked by Maruca in

early season than late season because they are found in the inner cycle where all the early

season environments are situated. However, there was genotypic variation for Maruca

infestation between the two seasons. Compared to other maturity classes early maturing

genotypes were more attacked by Maruca in early season than in late season while medium

to late maturing ones were more attacked in late season.

Figure 10a showed the biplot for Ootheca damage across the environments and explained

92.3 percent (79.4 percent + 12.9 percent) of the variation of the trait.

102

Figure 8. Biplot of genotype by environment (year, season and location) for aphid

damage.





103

Figure 9. Biplot of genotype by environment (year, season and location) for Maruca

damage.





104


Ootheca damage.





105

The local variety was more attacked by Ootheca than the rest genotypes in all the

environments particularly in E3 (year two early season, Ishiagu), E6 (year one late season,

Mgbakwu) and E4 (year two late season Ishiagu). Genotype IT 97K-556-4 was more

damaged by Ootheca in E1 (year one early season, Ishiagu), E2 (year one late season,

Ishiagu) and E5 (year one early season Mgbakwu), indicating more attack by Ootheca on the

genotype in year one than year two. E8 (year two late season, Mgbakwu) being located at the

centre of the biplpt origin, expressed the lowest Ootheca population across all the genotypes.

Genotype IT 97K-499-35 was least attacked by Ootheca along with the rest improved

genotypes besides IT 97K-556-4 in all the environments. Figure 10b showed that compared

to other environments E4 (year two late season, Ishiagu) was the most ideal environment for

screening against Ootheca on cowpea in Southeastern Nigeria, having indicated optimum

attack of Ootheca on all the genotypes.

Figure 11 indicated the biplot for pod sucking bugs across environments and genotypes and

explained 93.5 percent (77 percent + 16.5 percent) of the trait variation. Late season (E6, E4,

E8 and E2) environments favoured more pod sucking bug infestation than early season (E5,

E1, E7 and E3 which are located at the biplot origin), with IT 98K-131-2 and IT 90K-277-2

being least attacked compared with other genotypes. Local variety was however, most

attacked by pod sucking bug in all the late season environments along with all the genotypes

found within the sector where the variety is the vetex genotype. The genotype IT 98K-205-8

habored the highest population of pod sucking bugs after local variety particularly in E7

environment (year two early season Mgbakwu).

106


Ootheca damage showing an ideal environment.





107

Figure 11. Biplot of genotype by environment- year, season and location (GXE) for pod

sucking bug damage.





108

Figure 12 indicated the biplot for bruchids damage across both environments and genotypes

and explained 93.2 percent (78.4 percent + 14.8 percent) of the trait under consideration. Late

season (E8, E6 and E2) environment favoured higher manifestation of bruchids than early

season (E1, E5, E3 and E7). All the genotypes below the centre of the polygon are brown

seeded except IT 90K-277-2 while all the genotypes above the centre of the polygon are

white seeded except IT 97K-556-4 (smooth seeded). This observation revealed that brown

seeded cowpea was less attacked by bruchids than white seeded. Genotypes IT 98K-205-8

and IT 97K-499-35 expressed highest infestation by bruchids in E8 (year two late season

Mgbakwu), E2 (year one late season, Ishiagu), E1 (year one early season, Ishiagu), E5 (year

one early season Mgbakwu) and E7 (year two early season Mgbakwu), while local variety

expressed highest expression of bruchids damage in the rest environments. Among the brown

seeded genotypes, vetex genotypes IT 98K-131-2 and IT 90K-568-18 along with IT 84S-

2246-4 and IT 90K-82-2 found within the sector were least attacked by bruchids in all the

environments. IT 98K-556-4 was more attacked by bruchids in E1 (year one, early season,

Ishiagu), E5 (year one early season, Mgbakwu), E3 (year two early season, Ishiagu) and E7

(year two early season, Mgbakwu). Genotype IT 93K-452-1 was more infested by bruchid in

E6 (year one late season, Mgbakwu) and E4 (year two late season, Ishiagu).

Figure 13a, showed the biplot for thrip damage across both environment and genotypes and

explained 91.8 percent (78.6 percent + 13.2 percent) of the variation of the trait. Again, late

season (E8, E4, E6 and E2) environment promoted highest population of thrips than early

season (E7, E1, E5 and E3). Thrips population was higher in year two (E8 and E4 and E4)

than year one (E1 and E5), indicating a build up of the pest in year two. Besides environment

E3 (year two early season Ishiagu) and E7 (year two early season, Mgbakwu), local variety

haboured the highest population of thrips in the rest environments particularly in E8 (year

two late season, Mgbakwu). The genotypes IT 98K-131-2, IT 90K-568-18 and IT 84S-2246-

4 haboured the least infestation by thrips across all the environments. Genotype IT 93K-452-

1 was highly attacked by thrips in E8 (year two late season, Mgbakwu). E1 (year one early

season Ishiagu) and E5 (year one early season, Mgbakwu) supported the least population of

thrips across all the genotypes supporting the observation that thrip population level is

usually higher in late than early season. This result is similar to that obtained in figure 11

where E1 and E5 environments equally supported the least expression of pod sucking bugs.

109


bruchid damage.





110


thrips damage.





111

Figure 13b revealed that out of all the environments used for this study E4 (year two late

season, Ishiagu) was the most ideal environment for screening and selecting cowpea

genotypes against thrips under natural filed conditions indicating higher than optimum

attacks on all the genotypes.

4.13 Genotype by insect damaged traits (GXT) across 2007 and 2008 (Experiment one).

Figure 14 represents GXT biplot and explained 62.5 percent (40.7 percent + 21.8 percent) of

the variation across genotypes and traits. The genotype IT 98K-131-2 was least attacked by

all the insect pests sampled in both location and years while local variety was most attacked

by all the insect pests apart from bruchids. The genotype IT 98K-205-8 habored the highest

infestation by bruchids in both location and year followed by IT 93K-452-1 and IT 97K-499-

35. It is interesting to note that all the genotypes within the sector where bruchids are found

are all white seeded cowpea indicating again that white seeded cowpea were more attacked

by bruchids than brown seeded. Genotype IT 97K-556-4 was highly attacked by Ootheca in

both locations. This genotype was extraordinarily bunchy, highly vegetative and broad leafed.

The rest genotypes were averagely attacked by the insect pests sampled.

4.14 Interaction effect of spray regime and season on performance of genotype for some

selected growth, reproductive and grain yield components (Experiment one).

Figure 15a showed the biplot for grain yield across genotypes and environments. Only two

genotypes, IT 97K-556-4 and IT 98K-131-2 produced higher than average grain yield while

the rest genotypes produced below average. Genotype IT 97K-556-4 is adapted to early

season environment since it produced its highest grain yield in both locations in early season

whether sprayed or not sprayed (E6, E5 and E2) while IT 98K-131-2 produced the next

highest grain yield after IT 97K-556-4. Genotype IT 98K-131-2 on the other hand is adapted

to late season (E4, E8, E3 and E7) because it produced the highest grain yield in late season

in both locations whether sprayed or not sprayed with insecticide. Zero spray gave the least

grain yield particularly in late season (E7). Local variety produced the lowest grain yield in

all the environments; consequently, it produced zero grain yields in late season when it was

not treated with insecticides. Early season whether sprayed with insectides or not in both

locations (E6 and E5) produced higher grain yield than late season zero spray or spray (E7,

E1 and E3).

112


thrips damage showing ideal environment.





113

Figure 14. Biplot of genotype by traits (GXT) interaction for selected insect damage

traits.

OOTHECSCMGB=Ootheca score Mgbakwu; OOTHECSCISH=Ootheca score Ishiagu;

MARUCTMGB= Maruca count Mgbakwu; MARUCTISH= Maruca count Ishiagu;

PSBSCMGB= Pod sucking bug Mgbakwu; PSBSCISH= Pod sucking bug MgbakwuIshiagu;

APHIDSCMGB= Aphid score Mgbakwu; APHIDSCISH= Aphid score Ishiagu;

THRIPCTMGB= Thrip count Mgbakwu; THRIPCTMGBISH= Thrip count Ishiagu;

BRUCHIDCTMGB= Bruchid count Mgbakwu; BRUCHIDCTISH= Bruchid count Ishiagu.

114

Figure 15a. Biplot of genotype by environment (spray regime and season) for

grain yield per hectare.

E1=Early season zero spray in Ishiagu; E2=Early season insecticide spray in Ishiagu;

E3=Late season zero spray in Ishiagu; E4=Late season insecticide spray in Ishiagu;

E5=Early season zero spray in Mgbakwu; E6=Early season insecticide spray in

Mgbakwu; E7=Late season zero spray in Mgbakwu; E8=Late season insecticide spray

in Mgbakwu.

115

Figure 15b showed that E2 (early season with insecticide spray in Ishiagu) was most ideal for

optimum cowpea grain production. This environment produced consistently higher and stable

grain yield across all the genotypes in both years.

Figure 16 showed the biplot for dry fodder yield across all genotypes and environments.

Early season whether sprayed or not (E5 and E6) generally produced higher dry fodder yield

than late season, although there is genotype variation for this trait. Compared to the improved

genotypes, local variety produced the highest dry fodder yield especially in early season (E5

and E6). This is followed by the genotype IT 97K-556-4 which produced the highest dry

fodder yield in late season (E4, E7 and E8). Genotype IT 90K-277-2 produced the highest

dry fodder yield in E3 (Late season zero spray in Ishiagu), E1 (Early season zero spray in

Ishiagu) and E2 (Early season insecticide spray in Ishiagu). Genotype IT 93K-452-1

produced the least dry fodder yield in all the environments, whether sprayed with insecticide

or not. In either early or late seasons, higher biomass is produced under zero spray (E5).

Figure 17 showed the biplot for 100 seed weight across genotypes and environments.

Although local variety produced the lowest 100 seed weight in most environments,

particularly when untreated with insecticide, it however, produced the highest 100 seed

weight when sprayed with insecticide in late season in Mgbakwu E8 (Late season insecticide

spray in Mgbakwu). In other words, when local variety was sprayed in late season it

produced higher than average 100 seed weight which invariably could compensates for low

grain yield inherent in local cowpea varieties. All the improved genotypes except IT 97K-

556-4, IT 90K-277-2 and IT 97K-499-35 produced the highest 100 seed weight in early

season whether sprayed with insecticides or not, irrespective of the location, for example, E1

(Early season zero spray in Ishiagu), E2 (Early season insecticide spray in Ishiagu), E5 (Early

season zero spray in Mgbakwu) and E6 (Early season insecticide spray in Mgbakwu). The

genotypes IT 97K-556-4, IT 90K-277-2 and IT 97K-499-35 produced the highest 100 seed

weight when sprayed in late season (E4). When cowpea genotypes (whether improved or not)

are not sprayed with insecticides especially in late season they produced the least 100 seed

weight. However, out of all the improved genotypes tested IT 93K-452-1 produced the

highest 100 seed weight under zero spray in late season (E3 and E7) indicating that the

genotype is tolerant to pod sucking bugs and Maruca. Genotypes IT 97K-568-18 and IT 98K-

131-2 found within E3 and E7 are also tolerant to pod sucking bugs and Maruca as they

produced above average 100 seed weight under zero spray in late season.

116

Figure 15b. Biplot of genotype by environment (spray regime and season) for

grain yield per hectare showing ideal environment.





in Mgbakwu.

117

Figure 16. Biplot of genotype by environment (spray regime and season) for dry

fodder yield.





in Mgbakwu.

118

Figure 17. Biplot of genotype by environment (spray regime and season) for 100

seed weight.





in Mgbakwu.

119

Figure 18 showed the biplot for threshing percentage across genotype and environment. Early

season environment in both locations whether sprayed with insecticide or not (E6, E5, E2,

and E1) produced the highest threshing percentage than late season (E8). The genotype IT

98K-131-2 produced the highest threshing percentage in the entire environments except E8

(late season with insecticide spray in Mgbakwu). The fact that this genotype produced

highest threshing percentage under zero spray in late season is an indication that it is tolerant

to pod sucking bugs. Local variety produced the highest threshing percentage in E8 (late

season with insecticides spray in Mgbakwu), just as it produced the highest 100 seed weight

in E8 (Figure 17). Zero spray in late season produced the least threshing percentage as

expected confirming that pod sucking bugs were prevalent in late season and does more

damages on cowpea pod not treated with insecticides.

Figure 19 showed the biplot for harvest index across genotypes and environments. Zero spray

in late season produced the least harvest index. Harvest index was highly expressed in early

season in both spray regime, and in late season when sprayed with insecticide. This

observation indicated that the insect pests sampled negatively impacted harvest index. The

genotypes IT93K-452-1 and IT98K-131-2 produced the highest harvest index in early season

whether sprayed with insecticide or not. Genotypes IT 97K-499-35 along with the associated

genotypes within the sector where it is the vetex genotype produced intermediate harvest

index in late season when sprayed with insecticide, while local variety, IT 90K-277-2, IT

97K-556-4 and IT 84S-2246-4 produced the lowest harvest index but differed in different

environments with respect to the trait. Late season with zero spray in Mgbakwu (E7) and late

season with zero spray in Ishiagu (E3) produced the least harvest index particularly on IT

90K-82-2 and IT 97K-556-18. Consequently, these two environments are located close to the

biplot origin. Meanwhile, zero spray tends to reduce harvest index in cowpea through the

promotion of biological yield to the detriment of economic yield.

120

Figure 18. Biplot of genotype by environment (spray regime and season) for

threshing percentage.





in Mgbakwu.

121

Figure 19. Biplot of genotype by environment (spray regime and season) for

harvest index.





in Mgbakwu.

122

4.15 Main effect of genotypes combined over 2009 and 2010 in Ako location

(Experiment two).


Table 28 showed that there were significant genotype effects for mean dry and fresh fodder

weight with local variety producing significantly higher dry fodder weight (1142 g), followed

by IT 98K-131-2 (1079 g) and IT 97K-568-18 (1078 g). Fresh fodder weight followed similar

pattern with dry fodder weight. As expected, IT 93K-452-1 produced significantly lower dry

fodder (692 g) and fresh fodder (3995 g) weight. Number of branches was statistically similar

for all the genotypes studied. IT 93K-452-1 produced significantly higher number of hills

(15) and number of plant stand (26), followed by IT 98K-131-2 with number of hills (14) and

number of plant stand (25), while on the contrary local variety was the least for number of

hill (8) and number of plant stand (12). However, local variety on the other hand produced

significantly higher mean number of internodes (16), number of leaves (143), number of

nodules (21) and vine length (178 cm). IT 98K-131-2 produced statistically higher peduncle

length (45 cm) while local variety produced the least. IT 93K-452-1 produced significantly

lower root length (17 cm) and vine length (95 cm).

4.15.2. Genotype main effect on reproductive and grain yield component.

The local variety took longest time to flower (58 days), mature (88 days) and consequently

the latest to fill the pods (30 days) while IT 93K-452-1 was the earliest to flower (37 days),

and mature (61 days) (Table 29). The highest mean 100 seed weight (15 g) was expressed by

IT 98K-131-2 and IT 93K-452-1 while Local variety produced significantly lower mean 100

seed weight (9 g). Although, IT 93K-452-1 produced lower number of seed per pod (13) and

pod length (13 cm) it nevertheless produced significantly higher number of pod per plant

(28). Moreover, IT 93K-452-1 produced significantly higher mean pod weight (438 kg), seed

weight (318 kg), grain yield per hectare (1061 kg) and harvest index (57 percent) while IT

97K-499-35 was next to IT 93K-452-1 for these traits. On the other hand local variety

recorded significantly lower performance for these traits.

123

Table 28: The main effect of genotypes on growth component of 5 cowpea genotypes combined over 2009 and 2010 in Ako


INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

IT 97K-499-35 825.00 3928.04 4.46 12.89 10.64 34.90 7.89 21.17 35.50 19.46 100.42

IT 97K-568-18 1078.06 5282.43 4.83 10.96 14.19 72.22 12.35 18.40 37.20 19.62 156.40

LOCAL 1142.13 5445.00 4.65 8.22 16.38 142.90 20.48 12.08 10.50 17.57 177.83

IT 98K-131-2 1079.24 5450.03 4.62 14.02 12.97 56.70 11.43 24.91 45.30 19.07 144.80

IT 93K-452-1 692.11 3195.00 4.52 14.52 10.33 40.10 11.47 25.70 36.00 16.96 95.30

Mean 963.00 4660.00 4.62 12.12 12.90 69.42 12.74 20.45 33.30 18.54 134.90

F-LSD(0.05) 116.20 760.80 0.55 0.76 1.45 14.50 2.74 1.45 7.02 1.71 22.23

DFWT = Dry fodder weight; FFWT = Fresh fodder weight: NBRANCH = Number of branches; NHILL = Number of hills; INTERNODE = Number of internode;

NLEAF = Number of leaves; NNODULE=Number of nodules; NSTAND=Number of plant stand; PEDLT = Peduncle length; RTLENGTH=Root length;

VINELTH=Vine length.

124

4.15.3 Genotype main effect on insect damaged component.

Table 30 showed that all the genotypes expressed low but statistically similar insect pest

infestation with respect to aphids, Ootheca and pod sucking bugs score, IT 93K-452-1

nevertheless haboured significantly higher population of aphids (2.69). Incidences of the rest

insect pests were higher and varied among all the genotypes with IT 98K-131-2 expressing

significantly lower attack by bruchids (15.10), Maruca (2.00), and thrips (7.12). IT 93K-452-

1 was most attacked by bruchids (45.40) and thrips (9.47) while local variety was most

attacked by Maruca (5.00) and Ootheca (1.51). Again, all the white seeded genotypes

haboured higher infestation of bruchids than brown seeded cowpea. Although, IT 93K-452-1

was most attacked by aphids, bruchids and thrips the genotype produced the highest overall

grain yield component, indicating that it was tolurant to these pests.

4.16 Cropping system and genotype effect in early season combined over 2009 and 2010

in Ako.

4.16.1 Cropping system and genotype effects on growth component.

Table 31 indicated that growth component of dry and fresh fodder weight were significantly

higher in sole cropping than intercropping. The rest growth components expressed similarity

between the two cropping systems. Variation among genotypes for dry and fresh fodder

weight however existed.

4.16.2 Cropping system and genotype effects on reproductive and grain yield

component.

Table 32 showed that there was no significant difference between sole cropping and

intercropping for mean days to flowering and pod filling, however, most genotypes matured

earlier in intercropping than sole cropping environment. In both cropping systems, IT 93K-

452-1 produced significantly higher 100 seed weight and number of pod per plant while IT

98K-131-2 produced significantly higher number of seed per pod in both systems.

125

Table 29: The main effect of genotypes on reproductive and grain yield components of 5 cowpea genotypes combined over 2009 and 2010 in Ako

GENOTYPE BLOOM

(days)

MATURITY

(days)

PODFILL

(DAYS)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(kg)

SEED WT

(kg)

GYLD/HA

(kg)

THRESH

(%)

HI

( %)

IT 97K-499-35 42,00 62.81 20.46 14.41 22.54 11.71 16.00 391.75 282.83 942.00 71.59 42.58

IT 97K-568-18 45.57 68.39 23.00 14.29 25.40 11.60 14.24 197.21 140.80 469.05 62.20 22.38

LOCAL 57.92 88.00 30.03 9.18 17.38 4.83 6.03 116.90 70.73 236.12 17.90 7.55

IT 98K-131-2 45.00 67.86 23.11 14.49 25.14 12.96 15.00 327.00 238.20 794.00 71.81 33.06

IT 93K-452-1 37.31 61.02 24.00 14.82 27.60 10.65 13.10 437.50 318.20 1061.33 72.10 56.63

Mean 46.00 70.00 24.00 13.44 23.61 10.35 13.00 294.00 210.10 700.00 59.10 32.44

F-LSD(0.05) 3.85 4.87 1.67 1.37 4.05 0.88 2.14 48.31 36.31 121.00 4.56 8.00

BLOOM = Days to 50 percent flowering; MATURITY = Days to maturity; PODFILL = Days to Podfilling; 100SWT = 100 Seed weight; NPOD/PLT = Number of

pods per plant; NSEED/POD = Number of seeds per pod; PLENGTH = Pod length; PODWT = Pod weight; SEEDWT = Seed weight; GYLD/HA = Grain yield

per hectare; THRESH percent = Threshing percentage; HI = Harvest Index.

126

Table 30: The main effect of genotypes on the insect damage of 5 cowpea genotypes combined over 2009 and 2010 in Ako

GENOTYPE APHIDSC BRUCHIDCT MARUCT OOTHESC PSBSC THRIPCT

IT 97K-499-35 1.79 44.50 3.52 1.16 1.16 7.46

IT 97K-568-18 1.74 16.70 2.56 1.33 1.22 8.49

LOCAL 1.08 40.10 5.00 1.51 1.12 8.30

IT 98K-131-2 1.81 15.10 2.00 1.32 1.20 7.12

IT 93K-452-1 2.69 45.40 4.49 1.17 1.21 9.47

Mean 1.82 32.36 3.68 1.30 1.18 8.17

F-LSD(0.05) 1.32 7.58 1.87 0.17 0.18 3.36



127

Meanwhile, pod length was highly expressed by IT 97K-499-35 while IT 93K-452-1

expressed the least of the trait. In sole cropping IT 93K-452-1 supported significantly higher

grain yield per hectare (1121 kg), seed weight (336 kg), pod weight (464 kg), and harvest

index (68 percent), followed by IT 97K-499-35 with grain yield (1078 kg ha-1

), seed weight

(323 kg) and pod weight (455 kg). In intercropping system however, there was a change

order in which IT 97K-499-35 produced significantly higher grain yield (896 kg ha-1

), seed

weight (269 kg) and pod weight (383 kg) followed by IT 93K-452-1 with grain yield (880 kg

ha-1

), seed weight (264 kg) and pod weight (369 kg). Both IT 93K-452-1 and IT 97K-499-35

produced higher but similar values for threshing percentage and harvest index in both

systems. As expected, local variety could not flower and consequently could not produce any

reproductive and grain yield components. The two early maturing genotypes, IT 93K-452-1

and IT 97K- 499-35 performed better in both systems indicating that the genotypes were

adapted to both systems better than medium maturing genotypes.

4.16.3 Cropping system and genotype effect on insect damaged component.

Table 33 showed that in comparison with sole cropping, intercropping crashed the population

of aphids. The differences between the two systems for the rest insect pests were statistically

similar although there is variability due to genotype for these traits in both systems.

4.17 Cropping system and genotype effect in late season combined over 2009 and 2010

in Ako.

4.17.1 Cropping system and genotype effect on growth component.

Table 34 indicated that dry fodder weight, fresh fodder weight and vine length were

significantly higher in sole cropping than intercropping. Local variety produced the highest

dry and fresh fodder weight in both systems over other genotypes while IT 97K-568-18

produced significantly lower dry fodder weight in both systems. Also, local variety produced

significantly higher number of leaves, number of nodules and vine length in both sole and

intercropping. IT 93K-452-1 produced significantly higher number of hills and number of

stand in both systems while local variety produced the least of these traits. Genotype IT 97K-

499-35 produced significantly lower number of nodules in both systems.

128

Table 31: Effects of cropping systems and genotypes on growth component of 5 cowpea genotypes in early season of 2009 and 2010 in Ako

Cropping

System


INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

Sole Crop IT 97K-499-35 825.04 5483.33 4.75 12.42 10.50 38.80 8.58 20.54 41.70 19.10 154.26

IT 97K-568-18 1592.00 5792.00 4.58 13.67 16.46 79.10 10.56 22.96 43.10 20.29 228.00

LOCAL 1350.01 8067.17 4.17 9.46 15.83 176.20 19.33 13.66 - 18.69 201.40

IT 98K-131-2 1670.55 8900.02 4.83 14.71 12.58 64.73 10.04 26.29 67.00 19.56 177.00

IT 93K-452-1 658.00 4200.00 4.33 14.63 10.29 39.91 10.31 25.67 37.30 18.29 113.44

Mean 1219.10 7088.00 4.53 12.98 13.19 79.80 11.77 21.82 38.00 19.19 174.80

Inter Crop IT 97K-499-35 796.26 5017.43 4.42 13.54 9.83 30.00 7.54 22.29 41.00 19.72 114.73

IT 97K-568-18 1296.09 7310.06 4.58 14.25 15.50 104.23 14.25 25.04 40.92 17.40 212.29

LOCAL 1192.00 6575.00 4.29 10.25 17.75 199.44 20.40 15.42 - 17.95 217.41

IT 98K-131-2 1103.48 7525.35 4.75 14.63 14.46 68.90 11.33 26.95 44.41 19.23 206.40

IT 93K-452-1 575.03 3478.87 4.04 14.21 10.42 36.30 9.92 25.75 39.73 17.65 126.87

Mean 996.00 5981.00 4.42 13.38 13.59 87.80 12.69 23.09 33.50 18.39 175.50

F-LSD(0.05) 124.10 420.00 0.75 0.74 1.93 18.20 3.66 1.49 9.54 2.57 31.07




129

Table 32: Effect of cropping systems and genotypes on reproductive and grain yield components of 5 cowpea genotypes evaluated in early

season of 2009 and 2010 in Ako

CROPPING

SYSTEM

GENOTYPE BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(kg)

SEED WT

(kg)

GYLD/HA

(kg)

THRESH

(%)

HI (%)

Sole Crop IT 97K-499-35 44.08 64.54 21.38 14.75 22.66 11.18 22.00 454.52 323.40 1078.00 70.93 49.60

IT 97K-568-18 47.33 72.29 25.04 13.83 19.00 10.92 17.01 93.80 50.24 166.58 53.49 4.12

LOCAL - - - - - - - - - - - -

IT 98K-131-2 47.42 70.96 25.31 14.04 24.59 13.43 17.09 177.00 114.73 382.00 68.79 7.66

IT 93K-452-1 39.42 63.12 16.00 15.56 33.05 10.71 14.00 464.40 336.20 1121.37 71.16 67.78

Mean 35.65 54.18 19.00 11.76 20.12 9.34 14.36 238.00 164.90 550.00 52.87 25.83

Inter Crop IT 97K-499-35 43.38 63.21 20.19 14.79 27.29 11.75 16.44 382.75 268.95 896.40 68.84 51.89

IT 97K-568-18 47.75 69.88 21.48 14.12 23.46 11.68 14.72 96.97 59.70 199.00 55.36 6.91

LOCAL - - - - - - - - - - - -

IT 98K-131-2 47.50 68.28 21.00 14.08 25.62 13.88 16.00 193.58 131.73 438.59 69.34 15.65

IT 93K-452-1 39.88 61.55 22.00 15.33 30.29 10.71 14.24 369.10 263.95 880.06 69.44 62.59

Mean 35.70 52.58 17.30 11.80 21.52 9.60 12.00 208.44 144.82 483.00 52.60 27.41

F-LSD(0.05) 2.47 3.26 3.17 1.29 4.62 0.95 2.25 51.37 39.49 131.60 6.20 7.94



per hectare; THRESH percent = Threshing percentage; HI (%) = Harvest Index.

130

Table 33: Effect of cropping systems and genotypes on insect damage of 5 cowpea genotypes in early season of 2009 and 2010 in Ako

CROPPING SYSTEM GENOTYPE APHIDSC BRUCHIDCT MARUCT OOTHESC PSBSC THRIPCT

Sole Crop IT 97K-499-35 3.75 45.80 4.92 1.25 1.00 6.08

IT 97K-568-18 3.21 11.50 3.62 1.54 1.10 7.25

LOCAL 1.04 - - 2.04 - -

IT 98K-131-2 3.13 15.80 4.79 1.63 1.00 6.50

IT 93K-452-1 5.33 47.80 5.71 1.29 1.00 5.83

Mean 3.29 24.20 3.82 1.55 0.94 5.13

Inter Crop IT 97K-499-35 1.54 45.40 6.17 1.25 1.00 6.50

IT 97K-568-18 1.29 19.00 3.67 1.71 1.13 5.58

LOCAL 1.08 - - 1.79 - -

IT 98K-131-2 2.21 14.80 3.10 1.54 1.08 7.25

IT 93K-452-1 2.54 52.60 9.33 1.37 0.96 8.71

Mean 1.73 26.40 4.45 1.53 0.97 5.62

F-LSD(0.05) 1.94 8.82 2.74 0.20 0.23 3.22



131

4.17.2 Cropping system and genotype effect on reproductive and grain yield component.

Table 35 revealed that in late season there was significant difference between sole and

intercropping for most of the grain yield components. Cropping system did not significantly

affect reproductive traits (bloom, maturity and days to pod filling). Sole cropping however,

produced significantly higher mean 100 seed weight, number of pod per plant, number of

seed per pod, pod length, pod weighty, seed weight, grain yield, threshing percentage and

harvest index for all the genotypes. Local variety produced significantly higher mean 100

seed weight and number of pod per plant than the rest genotypes. In sole cropping, IT 98K-

131-2 supported significantly higher mean grain yield per hectare (1406 kg), seed weight

(422 kg), pod weight (554 kg), threshing percentage (77 percent) and harvest index (57

percent) followed by IT 93K-452-1 with mean grain yield (1138 kg ha-1

), seed weight (342

kg), pod weight (472 kg), threshing percentage (74 percent) and harvest index (41 percent).

There was a change order in intercropping such that IT 93K-452-1 produced significantly

higher grain yield (1105 kg ha-1

), seed weight (331 kg), pod weight (444 kg), threshing

percentage (74 percent) and harvest index (55 percent) followed by IT 98K-131-2 with grain

yield (948 kg ha-1

), seed weight (284 kg), pod weight (383 kg), threshing percentage (73

percent) and harvest index (52 percent). The local variety produced significantly lower

overall grain yield components compared to the rest genotypes.

Medium to late maturing genotypes were more depressed by intercropping in late season than

early maturing genotypes revealing that medium to late maturing genotypes are more adapted

to sole cropping than intercropping in late season. The performances of grain yield

components between the two systems for early maturing genotypes were marginal indicating

that they are adapted to both systems in late season. Intercropping depressed biomas

production but increased harvest index.

4.17.3 Cropping system and genotype effect on insect damage component

Table 36 showed that in late season intercropping reduced the population of bruchids, pod

sucking bugs and thrips across most genotypes. The populations of other pests were

statistically similar in both systems although there was genotype variability for these insect

damaged traits in both systems.

132

Table 34: Effect of cropping systems and genotypes on growth component of 5 cowpea genotypes in late season of 2009 and 2010 in Ako

Cropping

System


INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

Sole Crop IT 97K-499-35 928.68 2900.00 4.50 12.45 11.38 35.42 6.08 20.75 32.27 19.71 70.11

IT 97K-568-18 862.08 3010.00 4.50 7.88 11.04 58.33 11.79 12.50 33.80 20.54 92.76

LOCAL 1283.11 4414.34 6.08 7.38 18.39 108.65 26.88 10.50 23.99 17.75 165.80

IT 98K-131-2 862.00 2762.02 4.63 13.67 11.00 43.90 11.42 23.92 34.70 17.96 93.99

IT 93K-452-1 867.37 2621.41 4.88 14.38 9.71 44.00 13.83 25.37 34.55 14.46 80.52

Mean 961.09 3141.17 4.92 11.14 12.30 58.10 14.00 18.61 31.80 18.08 100.60

Inter Crop IT 97K-499-35 750.00 2313.00 4.17 13.17 10.83 35.40 9.75 21.08 35.00 19.29 62.30

IT 97K-568-18 560.33 2016.79 5.67 8.04 13.75 47.00 12.79 13.08 31.00 20.25 92.71

LOCAL 743.11 2723.00 4.04 5.79 13.54 87.44 15.33 8.75 15.60 15.88 126.40

IT 98K-131-2 679.35 2613.07 4.25 13.08 13.54 49.11 12.92 22.46 35.13 19.54 101.90

IT 93K-452-1 666.49 2479.00 4.83 14.88 10.88 40.33 11.79 26.00 32.50 17.46 60.55

Mean 680.00 2429.00 4.59 10.99 12.51 51.80 12.52 18.27 29.81 18.48 88.83

F-LSD(0.05) 124.10 420.00 0.75 0.74 1.93 18.20 3.66 1.49 9.54 2.57 31.07

DFWT = Dry fodder weight; FFWT = Fresh fodder weight: NBRANCH = Number of branches; NHILL = Number of hills; INTERNODE = Number of internode; NLEAF = Number

of leaves; NNODULE=Number of nodules; NSTAND=Number of plant stand; PEDLT = Peduncle length; RTLENGTH=Root length; VINELTH=Vine length.

133

Table 35: Effect of cropping systems and genotypes on reproductive and grain yield components of 5 cowpea genotypes evaluated in late season

of 2009 and 2010 in Ako

CROPPING

SYSTEM

GENOTYPE BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(kg)

SEED WT

(kg)

GYLD/HA

(kg)

THRESH

(%)

HI

(%)

Sole Crop IT 97K-499-35 40.00 61.83 22.00 14.58 21.04 12.79 14.00 389.30 283.52 945.00 73.27 32.91

IT 97K-568-18 44.71 66.92 23.06 15.21 35.87 12.42 14.24 363.57 276.34 921.06 70.08 40.09

LOCAL 60.96 78.50 28.01 20.50 43.08 10.79 13.17 261.20 153.33 511.39 45.91 13.00

IT 98K-131-2 42.88 65.58 23.00 15.17 27.62 12.88 15.00 554.15 420.90 1406.00 76.45 55.56

IT 93K-452-1 33.79 59.25 26.40 14.62 24.00 10.46 13.00 472.23 341.50 1138.15 73.66 41.17

Mean 44.47 66.42 24.00 16.02 30.32 11.87 14.03 408.10 295.33 984.00 67.87 36.74

Inter Crop IT 97K-499-35 38.46 61.67 23.02 13.50 19.17 11.13 13.13 340.11 255.27 851.40 73.32 35.91

IT 97K-568-18 43.21 64.46 22.17 14.00 23.25 11.42 13.00 234.50 177.00 590.01 69.48 38.42

LOCAL 56.00 54.58 25.00 14.96 24.17 8.04 9.24 206.36 129.41 431.00 25.68 17.20

IT 98K-131-2 43.75 66.63 23.11 14.67 22.75 11.67 14.00 383.33 284.40 948.00 72.65 52.37

IT 93K-452-1 34.67 60.17 24.00 13.75 23.08 10.71 12.00 444.20 331.39 1105.37 74.14 54.97

Mean 43.22 61.50 23.00 14.18 22.48 10.59 12.00 321.77 235.50 785.13 63.05 39.77

F-LSD(0.05) 2.47 3.26 3.17 1.29 4.62 0.95 2.25 51.37 39.49 131.60 6.20 7.94




134

4.18 Season by genotype effect combined over 2009 and 2010.

4.18.1 Season by genotype effects on growth component.

There were differences between early and late season for all growth components except

number of branches, number of nodules and root length. Generally, across all the genotypes

early season supported higher production of almost all the growth traits sampled.

Consequently, early season recorded 36 percent higher dry fodder yield, 35 percent higher

fresh fodder yield, 18 percent higher number of hills, 8 percent higher number of internode,

53 percent higher number of leaves, 28 percent higher number of plant stand, 16 percent

higher peduncle length and 84 percent higher vine length than late season environment.

Differences between the two seasons for number of branches, number of nodules and root

length were narrow (Table 37).

4.18.2 Season by genotype effects on reproductive and grain yield components.

Table 38 revealed that in late season genotypes flowered earlier but matured at the same time

with early season. However, there was a change in trend such that genotypes took longer days

to fill the pod in late season than early season. Expectedly, the late season that took longer

days to fill the pods also recorded significantly higher grain yield components. For instance

late season revealed 25 percent higher mean 100 seed weight, 31 percent higher mean pod

weight, 71 percent higher mean seed weight, 72 percent higher mean grain yield, 25 percent

higher mean threshing percentage and 41 percent higher mean harvest index. This

observation is apparently due to longer period available for the accumulation of assimilates in

late season than early season. Early season on the other hand recorded 23 percent higher

mean pod length than late season. Based on grain yield component, early maturing genotypes

(IT 97K-499-35 and IT 93K-452-1) had a broader adaptation to both early and late seasons,

while longer duration genotypes (Local, IT 98K-131-2 and IT 97K-568-18) are narrowly

adapted to late season. Meanwhile, seasonal changes depressed mean 100 seed weight in IT

93K-452-1 from 16 g in early season to 14 g in late season and mean number of pod per plant

from 32 in early season to 24 in late season. Conversely, IT 97K-499-35, IT 97K-568-18 and

IT 98K-131-2 exhibited similar performance for mean 100 seed weight in both seasons. The

local variety being photo-sensitive could not flower during the early season as expected while

it produced reasonable grain yield in late season.

135

Table 36: Effect of cropping systems and genotypes on insect damage of 5 cowpea genotypes in late season of 2009 and 2010 in Ako

CROPPING SYSTEM GENOTYPE APHIDSC BRUCHIDCT MARUCT OOTHESC PSBSC THRIPCT

Sole Crop IT 97K-499-35 0.88 43.30 1.58 1.00 1.33 14.67

IT 97K-568-18 1.42 21.50 1.37 1.00 1.46 18.50

LOCAL 1.29 54.60 2.67 1.25 1.88 25.50

IT 98K-131-2 0.96 17.00 1.42 1.00 1.38 16.62

IT 93K-452-1 1.79 39.50 1.46 1.00 1.54 17.17

Mean 1.27 35.20 1.70 1.06 1.52 18.49

Inter Crop IT 97K-499-35 1.00 43.50 1.42 1.13 1.25 2.58

IT 97K-568-18 1.04 15.00 1.58 1.08 1.21 2.62

LOCAL 0.92 25.90 2.58 0.96 1.38 2.96

IT 98K-131-2 0.96 12.70 1.04 1.08 1.29 2.83

IT 93K-452-1 1.10 41.70 1.46 1.00 1.33 6.17

Mean 1.00 27.80 1.62 1.05 1.29 3.43

F-LSD(0.05) 1.94 8.82 2.74 0.20 0.23 3.22



136

Table 37: Effect of season and genotypes on growth component of 5 cowpea genotypes combined over 2009 and 2010 in Ako

Season Genotype DFWT(g) FFWT(g) NBRANCH NHILL

INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

Early IT 97K-499-35 810.00 5250.12 4.58 12.98 10.17 34.40 8.06 21.42 41.33 19.41 134.50

IT 97K-568-18 1444.06 8051.40 4.58 13.96 15.98 91.77 12.41 24.00 42.00 18.85 220.10

LOCAL 1271.11 7321.03 4.23 9.85 16.79 187.80 19.86 14.54 - 18.32 209.43

IT 98K-131-2 1388.00 8212.00 4.79 14.67 13.67 66.80 10.69 26.62 54.70 19.40 191.70

IT 93K-452-1 616.55 3840.00 4.19 14.42 10.35 38.13 10.13 25.71 38.55 17.97 120.15

Mean 1106.00 6535.05 4.48 13.18 13.39 83.80 12.23 22.46 35.70 18.79 175.10

Late IT 97K-499-35 800.08 2606.00 4.33 12.79 11.10 35.41 7.92 20.92 33.60 19.50 66.22

IT 97K-568-18 711.24 2513.21 5.08 7.96 12.40 52.65 12.29 12.79 32.40 20.40 92.87

LOCAL 1013.00 3568.34 5.06 6.58 15.96 98.00 21.10 9.62 19.83 16.81 146.10

IT 98K-131-2 771.17 2688.20 4.44 13.38 12.27 46.51 12.17 23.19 34.90 18.75 97.96

IT 93K-452-1 767.04 2550.00 4.85 14.63 10.29 42.20 12.81 25.69 33.50 15.96 70.50

Mean 812.00 2785.00 4.75 11.07 12.40 55.00 13.26 18.44 30.82 18.28 94.70

F-LSD(0.05) 124.10 826.40 0.75 0.74 1.93 18.20 3.66 1.49 9.54 2.57 31.07




137

Local variety however expressed significantly higher mean 100 seed weight (18 g) over the

rest genotypes in late season. Mean pod length was negatively affected by season with late

season reducing mean pod length in all the genotypes but worse on IT 97K-499-35. Seasonal

changes affected most genotypes with respect to threshing percentage and harvest index with

early season depressing most genotypes for these traits. This is because higher biomas

production will likely reduce harvest index. The genotypes IT 97K-568-18 and IT 98K-131-2

were most affected as their harvest index was drastically reduced in early season. This

observation was largely due to similar effect that season had on pod weight on both

genotypes with early season depressing mean pod weight which reflected directly on harvest

index.

4.18.3. Season by genotype effects on insect damaged component.

Table 39 indicated that the population of aphids, Maruca and Ootheca was higher in early

than late season by 122 percent, 183 percent and 47 percent respectively; however there was

a change order such that pod sucking bugs and thrips population were consistently higher in

late season than early season by 47 percent and 104 percent respectively. It was observed that

in 2009, Maruca population was slightly higher in late than early season. The population

difference between early and late season for bruchids was narrow except for IT 93K-452-1

where late season crashed the population of bruchids from 50.20 in early season to 40.6 in

late season.

4.19 Interaction effects of year, season and cropping system on the performance of

genotypes for some selected growth, reproductive and grain yield components in Ako

location (Experiment two).

Figure 20 indicated the biplot for grain yield across genotypes and environments. Early

maturing genotypes (IT 93K-452-1 and IT 97K-499-35) were adapted to both cropping

systems in either early or late season environments (E1, E2, E4, E5 and E6) while medium

maturing genotype (IT 98K-131-2) was adapted to sole cropping in late season (E3 and E7),

having produced the highest grain yield in those environments. However, IT 93K-452-1

produced the highest grain yield followed by IT 98K-131-2 and then IT 97K-499-35, while

local variety produced the least grain yield. Local variety (late maturing) and IT 90K-568-18

(medium maturing) could not produce the highest grain yield in any of the environments.

138

Table 38: Effect of season and genotypes on reproductive and grain yield components of 5 cowpea genotypes combined over 2009 and 2010

SEASON GENOTYPE BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(kg)

SEED WT

(kg)

GYLD/HA

(kg)

THRESH

(%)

HI

(%)

Early IT 97K-499-35 43.73 63.88 20.00 14.77 24.98 11.46 19.21 418.66 296.10 987.00 69.88 50.75

IT 97K-568-18 47.54 71.08 24.03 13.98 21.23 11.29 16.00 95.40 54.92 183.12 54.42 5.51

LOCAL - - - - - - - - - - - -

IT 98K-131-2 47.46 69.63 23.00 14.06 25.08 13.57 15.53 185.33 123.22 411.00 69.07 11.66

IT 93K-452-1 39.65 62.33 23.09 15.46 31.67 10.71 13.98 416.70 300.00 1000.02 70.30 65.18

Mean 44.60 66.73 23.00 11.78 20.82 9.47 16.00 223.2 154.90 516.00 52.73 26.62

Late IT 97K-499-35 39.23 61.75 23.24 14.04 20.10 11.96 14.33 364.73 269.43 898.22 73.30 34.41

IT 97K-568-18 43.96 65.69 28.16 14.60 29.56 11.92 14.00 299.00 226.67 754.64 69.78 39.25

LOCAL 50.56 76.00 30.00 17.73 33.62 9.42 11.01 233.70 141.30 470.90 74.55 15.10

IT 98K-131-2 43.31 66.10 26.00 14.92 25.19 12.27 13.75 468.70 353.20 1177.00 73.55 54.46

IT 93K-452-1 34.23 60.00 26.00 14.19 23.54 10.58 12.00 458.20 336.40 1121.09 73.90 48.07

Mean 42.26 65.91 27.00 15.10 26.40 11.23 13.00 364.9 265.40 885.00 65.46 38.26

F-LSD(0.05) 2.47 3.26 3.17 1.29 4.62 0.95 2.25 51.37 39.49 131.60 3.16 7.94




139

Figure 21 showed the biplot for dry fodder yield across genotypes and environments. Late

season intercropping (E4) supported less dry fodder yield for early maturing genotypes (IT

93K-452-1 and IT 97K-499-35) while late season sole or intercropping supported highest

production of dry fooder by late maturing genotype (local variety). Generally, early season

sole cropping (E5 and E1) supported the highest production of dry fodder weight.

Figure 22 showed the biplot for 100 seed weight across genotypes and environments.

Although, local variety produced the lowest overall 100 seed weight in early season (E1, E2,

E5 and E6), it however produced the highest 100 seed weight in late season irrespective of

the cropping system (E3, E8 and E7). All the improved genotypes except IT 98K-131-2

produced the highest 100 seed weight in early season whether in sole or intercropping

system: E1 (First year, early season sole cropping), E2 (First year, early season inter

cropping), E5 (Second year, early season sole cropping), E6 (Second year, early season inter

cropping). Genotype IT 93K-452-1 was more influenced by early season sowing in either of

the system with respect to 100 seed weight. None of the cropping system clearly affected 100

seed weight in this study.

Figure 23 indicated the biplot for threshing percentage. Early season irrespective of cropping

system (E5, E2, E1, E6) produced the least threshing percentage while late season whether

sole or intercropping E8 (Second year late season, intercropping), E4 (First year, late season

inter cropping), E3 (First year, late season sole cropping), E7 (Second year, late season sole

cropping) produced the highest threshing percentage. The genotype IT 93K-452-1 along with

IT 97K-499-35 and IT 98K-131-2 produced the highest threshing percentage in all the

environments while local variety produced the least in all the environments. Genotype IT

97K-568-18 could not produce the highest threshing percentage in any particular

environment. The environmental resources in Ako in terms of soil and rainfall distribution are

better than that of Ishiagu and Mgbakwu, which might be responsible for higher threshing

percentage in late than in early season in Ako.

140

Table 39: Effect of season and genotypes on insect damage of 5 cowpea genotypes combined over 2009 and 2010 in Ako

SEASON GENOTYPE APHIDSC BRUCHIDCT MARUCT OOTHESC PSBSC THRIPCT

Early IT 97K-499-35 2.65 45.60 5.54 1.25 1.00 6.29

IT 97K-568-18 2.25 15.20 3.65 1.63 1.10 6.42

LOCAL 1.06 - - 1.92 - -

IT 98K-131-2 2.69 15.30 3.94 1.58 1.00 6.87

IT 93K-452-1 3.94 50.20 7.52 1.33 0.98 7.27

Mean 2.51 31.58 4.13 1.54 0.95 5.37

Late IT 97K-499-35 0.94 43.40 1.50 1.06 1.29 8.62

IT 97K-568-18 1.23 18.30 1.48 1.04 1.33 10.56

LOCAL 1.10 40.30 1.12 1.10 1.63 14.23

IT 98K-131-2 0.96 14.90 1.73 1.06 1.33 9.73

IT 93K-452-1 1.44 40.60 1.46 10.00 1.44 11.67

Mean 1.13 31.50 1.46 1.05 1.40 10.96

F-LSD(0.05) 1.94 8.82 2.74 0.20 0.23 3.22



141

Figure 20. Biplot of genotype by environment (Year, season and cropping

system) for grain yield per hectare.

E1=First year, early season sole cropping; E2=First year, early season inter cropping;

E3=First year, late season sole cropping; E4=First year, late season inter cropping;

E5=Second year, early season sole cropping; E6=Second year, early season inter cropping;

E7=Second year, late season sole cropping; E8=Second year, late season inter cropping.

142


system) for dry fodder weight.





143

Figure 24 showed the biplot for harvest index. Early maturing genotypes (IT 93K-452-1 and

IT 97K-499-35) produced the highest harvest index, in either sole or intercropping in both

season while long duration genotypes produced highest harvest index only in late season.

4.20 Genotype by trait (GXT) relationship across 2009 and 2010 for growth,

reproductive and grain yield components in Ako location (Experiment two).

Figure 25 showed the biplot for genotype by trait relationship. The genotypes IT 93K-452-1,

IT 98K-131-2 and local variety are the vertex genotypes indicating that they are different

from one another with respect to the traits sampled. Consequently, they represented the three

maturity classes of early, medium and late duration.

Genotype IT 93K-452-1 expressed the highest plant population, grain yield, harvest index

and threshing percentage because the traits are found within the sector where IT 93K-452-1 is

the vetex genotype. Genotype IT 97K-499-35 was next to IT93K-452-1 for these traits. The

genotypes IT 98K-131-2 produced high 100 seed weight. As expected, local variety

expressed highest bloom and dry fodder yield.

4.21 Interaction effects of year, season and cropping system on the performance of

genotypes for some selected insect damaged traits (Experiment two).

Figure 26 showed the biplot for aphids damage across genotypes and environments. This

Figure revealed that irrespective of cropping system there is a build up of aphids in year two

and in early season, E5 (Second year, early season sole cropping) and E6 (Second year, early

season inter cropping), indicating that these environments favoured higher aphids population

than first year and late season environments. Conversely, all the first year sowing

environments (E1, E2, E3 and E4) are found within the inner concentric cycle supporting the

fact that aphids population is less in year one than year two. Genotype IT 93K-452-1 was

more attacked by aphids in all the environments while local variety was least attacked. The

rest genotypes were averagely damaged by aphids. Sole cropping harbored more aphids

population (E5) than intercropping.

144


system) for 100 seed weight.





145


system) for threshing percentage.





146


system) for harvest index.





147

Figure 25. Biplot of genotype by traits (GXT) interaction for selected growth,

reproductive and grain yield traits.

148

Figure 27 showed the biplot for Maruca damage across genotypes and environments. Second

year planting irrespective of season or cropping system manifested higher population of

Maruca, example E8 (Second year, late season inter cropping), E6 (Second year, early season

inter cropping), E5 (Second year, early season sole cropping) and E7 (Second year, late

season sole cropping). Maruca population tends to be abundant in both seasons but slightly

lower in late season than early season environment E3 (First year, late season sole cropping)

and E4 (First year, late season inter cropping). This is because E3 and E4 are found within

the centre of biplot origin. Although, Maruca population was lower in late season than early

season, early season sole cropping haboured higher Maruca than intercropping while late

season intercropping haboured more Maruca infestation than sole cropping. Across all the

environments, early maturing genotypes (IT 93K-452-1 and IT 97K-499-35) were more

attacked by Maruca than medium and late maturing genotypes.

Figure 28 showed the biplot of Ootheca damage across genotypes and environments.

Ootheca population was more abundant in early season than late season irrespective of

cropping system: E5 (Second year, early season sole cropping), E1 (First year, early season

sole cropping), E6 (Second year, early season inter cropping) and E2 (First year, early season

inter cropping). Ootheca population was similar in both years. Cropping system did not affect

the population of Ootheca. Local variety was more attacked by Ootheca in all the

environments except in E2 (First year, early season inter cropping) and E4 (First year, late

season inter cropping). E3 (First year, late season sole cropping) was found within the center

of the biplot origin and therefore the environment harbored the least Ootheca infestation

which further support the fact that the pest is more abundant in early than late season. Early

maturing genotypes, IT 93K-452-1 and IT 97K-499-35 were least attacked by Ootheca while

medium maturing genotypes, IT 97K-568-18 and IT 98K-131-2 were intermediately infested

by the pest.

Figure 29 showed the biplot of pod sucking bugs. Second year and late season environments

(E7, E8) supported more population of pod sucking bugs than other environments. All the

early season environments are found within the biplot origin indicating that pod sucking bugs

was lower in early season than in late season environment.

149


system) for aphid damage.





150


system) for Maruca damage.





151

Figure 30 showed the biplot of bruchids damage across all genotypes and environments.

Bruchids attacked cowpea more in late season (E3) than early season. Early maturing

genotypes (IT 93K-452-1 and IT 97K-499-35) were more infested by bruchids in most of the

early season environments, while local variety was attacked by bruchids mostly in late season

environments (E3, E7, E8). Brown seeded medium maturing genotypes (IT 90K-568-18 and

IT 98K-131-2) were least attacked by bruchids in all the environments.

Figure 31 showed the biplot of thrips damage across genotypes and environments. Late

season sole cropping (E3, E7) supported the highest overall thrips population particularly by

local variety. In other words, thrips was most abundant in late season and in sole cropping

than in early season intercropping. Early season environments (E5, E6, E1) in both systems

haboured the least population of thrips since they are found within the inner concentric cycle

(biplot origin).

Local variety was highly infested by thrips in all the environments except early season

intercropping (E4 and E2) as expected. The genotype IT 93K-452-1 was more attacked by

thrips in intercropping environments (E4 and E2).

4.22 Genotype by trait (GXT) relationship across season and cropping system,

combined over 2009 and 2010 for insect damaged components (Experiment two).

Figure 32 showed the biplot for genotype by trait relationship. The vertex genotypes: local,

IT 93K-452-1 and IT 90K-568-18 were all divergent with respect to the insect pest damage

sampled. Local variety harbored above average infestation by most critical yield limiting

pests (Thrips and Maruca). Early maturing and white seeded genotypes (IT 93K-452-1 and

IT 97K-499-35) had below average attack by bruchids and aphids while medium maturing

genotypes (IT 90K-568-18 and IT 98K-131-2) had below average attack by pod sucking

bugs.

152


system) for Ootheca damage.





153


system) for pods sucking bugs damage.





154

Figure 30. Biplot of genotype by environment (Year, season and cropping system) for

bruchid damage.





155

Figure 31. Biplot of genotype by environment (Year, season and cropping system) for

thrips damage.





156

Figure 32. Biplot of genotype by traits (GXT) interaction for selected insect pest damage

traits.

APHIDSC=Aphid score; BRUCHIDCT=Bruchid count; MARUCACT=Maruca count;

THRIPCT= Thrip count; PSBSC=Pod sucking bug score; Oothecasc=Ootheca score.

157

4.23 Barchart showing the effects of spray regime, genotype, cropping system, season,

year, insect pests on grain yield and insect pest population in Ako location.

Fig 33 a, b showed that in comparison between unspray treatment and spray regime that

produced the highest grain yield among genotypes in early season sole cropping, two sprays

increased grain yield in IT 97K-499-35 by 41 percent, three sprays increased grain yield in IT

97K-568-18 by 30 percent, three sprays increased grain yield in IT 98K-131-2 by 48 percent,

two spray increased grain yield in IT 93K-452-1 by 48 percent while three sprays increased

grain yield in local variety by 80 percent. While on the other hand early season intercropping

for IT 97K-499-35 produced 10 percent higher grain yield with two sprays, IT 97K-568-18

produced 20 percent higher grain yield with two sprays, IT 98K-131-2 produced 33 percent

higher grain yield with two sprays, IT 93K-452-1 produced 67 percent higher grain yield with

two sprays and local variety produced 37 percent higher grain yield with three sprays.

Intercropping in early season generally produced higher grain yield at two spray frequency

while in sole cropping most genotypes responded better to higher chemical sprays. In sole

cropping, late and medium maturing genotypes (Local, IT 97K-568-18 and IT 97K-131-2)

required three sprays in late season while early maturity genotypes (IT97K-499-35 and

IT93K-452-1) required two sprays to produce highest grain yield in both systems. Higher

percentage yield increases was observed in sole than in intercropping for all genotypes except

local variety. This showed that there is greater yield of genotypes to higher chemical spray in

monocropping than intercropping. Optimum yield resulting from lower insecticide spray in

intercropping is an important environmental impact mitigation measure and a reliable IPM

strategy for sustainable cowpea production especially among small scale farmers.

In Fig 34 a, b grain yield levels increased significantly with increase in frequency of spray

treatment in both systems and years in late season. Differences however, existed among

genotypes for grain yield across spray regimes in late season.

158

Figure 33. Interaction effects of spray regime and genotype on grain yield evaluated in early

season in sole cropping (a) and intercropping (b) in Ako.

- 500

0

500

1000

1500

2000

IT 97K - 499 - 35 IT 97K - 568 - 18 LOCAL IT 98K - 131 - 2 IT 93K - 452 - 1

Grain yield kg ha

- 1

Genotype

(b) Ӏ=standard errow

Zero spray

One spray

Two sprays

Three sprays

- 1000

- 500

0

500

1000

1500

2000

2500

IT 97K - 499 - 35

IT 97K - 568 - 18

LOCAL IT 98K - 131 - 2 IT 93K - 452 - 1

Grain yield kg ha

- 1

Genotype

(a) Ӏ=standard errow

Zero spray

One spray

Two sprays

Three sprays

159

Figure 34. Interaction effects of spray regime and genotype on grain yield evaluated in late

season, sole cropping (a) and intercropping (b) in Ako.

0

500

1000

1500

2000

2500

3000

3500


Grain yield kg ha

- 1

Genotype


Zero spray

One spray

Two sprays

Three sprays

0

500

1000

1500

2000

2500


Grain yield kg ha

- 1

Genotype


Zero spray

One spray

Two sprays

Three sprays

160

Most genotypes required three sprays treatment to produced highest grain yield in sole

cropping. In intercropping two sprays generally produced highest grain yield for most

genotypes except IT98K-499-35 that produced highest grain yield with three sprays and

IT98K-131-2 where only one spray produced similar grain yield level as two sprays, and for

economic reasons one spray is preferable for this genotype in intercropping. This genotype

was incidentally found to habour the least insect pest population across all the environments

used for this study.

Interaction effects of cropping system and genotype on grain yield in early and late season is

shown in Fig 35 a, b. Early season produced higher grain yield than late season. Across the

two years and in early season, early maturing genotypes (IT 93K-452-1 and IT 97K-499-35)

produced significantly higher grain yield in sole cropping than intercropping while medium

maturing genotype (IT98K-131-2 and IT97K-568-18) produced marginally higher grain yield

in intercropping than in sole cropping. However, in late season grain yield were similar

between the two systems for early maturing genotypes (IT 93K-452-1 and IT 97K-499-35)

and local variety, while the two medium maturing genotypes (IT98K-131-2 and IT97K-568-

18) produced highest grain yield in sole cropping than intercropping. In general, sole crop

cowpea produced higher grain yield than intercrop, however, while early maturing genotypes

(IT 93K-452-1 and IT 97K-499-35) produced higher grain yield under sole cropping in both

seasons, medium maturing genotypes (IT98K-131-2 and IT97K-568-18) produced highest

grain yield under intercropping in early season.

In Fig 36 medium to late maturing genotypes are adapted to late season because they

produced significantly higher grain yield in late season than early season. It is recommended

that they be sown in such environment for optimum productivity.

In both seasons, the grain yield was higher in 2009 than in 2010 among the genotypes except

IT 97K-568-18 where similar yield levels were obtained in both years (Fig 37).

161

Figure 35. Interaction effects of cropping system and genotype on grain yield evaluated in

early season (a) and late season (b) in Ako.

- 400

- 200

0

200

400

600

800

1000

1200

1400

1600

Grain yield kg ha

- 1

Genotype


Sole cropping

Intercropping

0

500

1000

1500

2000

Grain yield kgha

- 1

Genotype


Sole cropping

Intercropping

162

Figs 38 a,b showed that the untreated control plots of IT 93K-452-1 recorded the highest

grain yield in early season followed by IT 98K-499-35, while IT 97K-568-18 produced the

least. On the other hand, in late season untreated control plots of IT 98K-131-2 recorded the

highest grain yield, followed by IT 93K-452-1 while local variety recorded the least. The rest

genotypes were similar with respect to this trait. Genotypes responded better to chemical

spray in early than in late season. The genotypes IT 93K-452-1 and IT 98K-131-2

consistently recorded higher grain yield when sprayed twice in both seasons, one spray is

recommended for IT 98K-499-35 and two spray for IT 97K-568-18 in early season while in

late season three sprays are recommended for IT 98K-499-35, IT 97K-568-18 and local

variety. Genotypes IT 93K-452-1 can produce appreciable grain yield in early and late season

without insecticide treatment while in late season IT 98K-131-2 can produce reasonable grain

yield without chemical spray.

Fig 39 showed the interaction effects of year and insect pest on insect population averaged

over genotypes and seasons. Aphids, Maruca and pod sucking bugs population were

significantly higher in 2010 than 2009 while on the other hand the population of bruchids and

thrips were higher in 2009 and 2010. Planting cowpea in a new environment for example in

year one (2009) reduced the population level of aphids, Maruca and pod sucking bugs by 157

percent, 168 percent and 68 percent respectively in comparison with year two (2010) while

on the other hand year 2010 reduced the population of bruchids and thrips by 410 percent and

255 percent respectively. Second year promoted the build up of aphids, Maruca and pod

sucking bugs while it depressed the population level of bruchids and thrips. There was no

year effect on Ootheca as its population was similar in both years.

163

Ӏ=standard errow

Figure 36. Interaction effects of season and genotype on grain yield averaged over two years

in Ako.

Ӏ=standard errow

Figure 37. Interaction effects of year and genotype on grain yield averaged over season in

Ako.

-400

-200

0

200

400

600

800

1000

1200

1400

Genotype

Early season

Late season

Gra

in y

ield

(k

g h

a)

-1

0

200

400

600

800

1000

1200

1400

1600

1800

Genotype

Year 2009

Year 2010Gra

in y

ield

(kg

ha

)-1

164

Fig 40 showed the interaction effects of cropping system and insect pest on insect population

averaged over genotypes. Intercropping reduced the population of aphids by 66 percent,

bruchids by 10 percent and thrips by 161 percent. Conversely, intercrop increased the

population of Maruca by 10 percent and pod sucking bugs by 9 percent. Cropping system did

not have any effect on the population of Ootheca. Ootheca appeared to be more stable across

years and cropping systems compared to other pests.

Fig 41 indicated the interaction effects of season and insect pest on insect population

averaged over genotypes and years. The population levels of aphids, Maruca and Ootheca

were higher in early than late season while late season on the other hand stimulated higher

expression of bruchids, pod sucking bugs and thrips. The percentage reduction in the

population of aphids, Maruca and Ootheca in late season was 122 percent, 183 percent and

40 percent, respectively while early season reduced the population levels of bruchids by 195

percent, pod sucking bugs by 47 percent and thrips by 104 percent.

Fig 42 showed the interaction effects of spray regime and insect pest on insect population

averaged accross genotypes, season and years. The population levels in insecticide treated

plots across all the insect pests differed significantly with spray regimes. In comparing pest

population level between zero spray and the spray regimes that produced the least insect pest

population, aphids showed 121 percent population reduction between zero spray and two

sprays, bruchids revealed 24 percent reduction between zero spray and three sprays; Maruca

174 percent reduction when sprayed three times; Ootheca 45 percent reduction when sprayed

two times; pod sucking bugs 38 percent reduction when sprayed three times and thrips 270

percent reduction when sprayed three times. This result revealed that for optimum control of

these insect pests irrespective of genotype the following spray regimes are generally

recommended: Aphids require two sprays, bruchids three sprays, Maruca three sprays,

Ootheca two sprays, pod sucking bugs three sprays and thrirps three sprays.

165

Figure 38. Interaction effects of spray regime and genotype on grain yield in early season (a)

and late season (b) averaged over cropping system in Ako.

- 200

0

200

400

600

800

1000

1200

1400

1600

Grain yield kg ha

- 1

Genotype


Zero spray

One spray

Two sprays

Three sprays

0 200 400 600 800

1000 1200 1400 1600 1800

Grain yield kg ha

- 1

Genotype


Zero spray

One spray

Two sprays

Three sprays

166

Ӏ=standard errow

Figure 39. Interaction effects of year and insect pest on insect population averaged over

genotypes in Ako.

Ӏ=standard errow

Figure 40. Interaction effects of cropping system and insect pests on insect population

averaged over genotypes, season and years in Ako.

-10

0

10

20

30

40

50

60

Aphids Bruchids Maruca Ootheca PSB Thrips

Inse

ct p

op

ula

tio

n

Insect pest

Year 2009

Year 2010

-10

-5

0

5

10

15

20

25

30

35

40


Inse

ct p

op

ula

tio

n

Insect pest

Sole crop

Inter crop

167

Ӏ=standard errow

Figure 41. Interaction effects of season and insect pest on insect population averaged

over genotypes and years in Ako.

Ӏ=standard errow

Figure 42. Interaction effects of spray regime and insect pest on insect population

averaged over genotypes, seasons and years in Ako.

-10

-5

0

5

10

15

20

25

30

35

40


Inse

ct p

op

ula

tio

n

Insect pest

Early season

Late season

-10

-5

0

5

10

15

20

25

30

35

40


inse

ct p

op

ula

tio

n

insect pest

Zero spray

One spray

Two sprays

Three sprays

168

4.24. The main effect of maize/cowpea intercropping on maize growth, reproductive and

grain yield components combined over 2009 and 2010 in Ako.

There was significant difference among maize/cowpea intercropping for most parameters

studied (Table 40). The intercropping combination of ACR 9931/IT 98K-131-2 had more

positive effects on maize as it produced higher cob weight (1591 kg), seed weight (1201 kg),

grain yield per hectare (4005 kg) and harvest index (95) followed by ACR9931/IT97K-499-

35 with cob weight (1570 kg), seed weight (1201 kg), grain yield per hectare (4005 kg).

Meanwhile, the intercropping combination of ACR9931/local variety had more negative

effect on maize as it produced lower dry fodder weight (1239 kg), seed weight (1137 kg), and

grain yield per hectare (3791 kg). However, ACR 9931/local variety was the latest to flower

(48 days), mature (78 days) and produced higher threshing percentage (79 percent).

ACR9931/IT 97K-568-18 gave the highest dry fodder weight (1306 kg) followed by ACR

9931/IT 98K-131-2 with dry fodder weight of 1300 kg.

4.25 Season and genotype effects on growth, reproductive and grain yield of maize

variety combined over 2009 and 2010 in Ako.

Table 41 revealed that there was significant difference between early and late season for

mean dry fodder weight, plant height, cob weight, cob length, number of cob per plot, seed

weight, 100 seed weight, grain yield per hectare and harvest index. Season however, had

marginal effect on the rest traits. Early season produced significantly higher mean dry fodder

weight, plant height, cob weight, cob length, number of cob per plot, seed weight, 100 seed

weight, grain yield per hectare and harvest index. Early season produced 81 percent higher

cob weight, 83 percent higher seed weight, 53 percent higher 100 seed weight, 83 percent

higher grain yield per hectare and 28 percent higher harvest index than late season.

169

Table 40: The main effect of maize/cowpea intercropping on growth, reproductive and grain yield components of maize variety combined over

2009 and 2010 in Ako location

MAIZE/COWPEA

COMBINATION

BLOOM

(days)

MATURITY

(days)

DFWT

(kg)

NSTAND PHT

(cm)

COBWT

(kg)

COBLT

(cm)

NBCOB

/PLOT

SEED WT

(kg)

100SWT

(kg)

GYLD

Kg/HA

T

(%)

HI

( %)

ACR9931/IT 97K-499-35 44.90 76.92 1293 14.94 233 1570.00 15.00 14.01 1201.01 23.81 4005.00 77 94

ACR9931/IT 97K-568-18 47.19 77.19 1306 14.98 227 1471.01 14.42 13.17 1138.23 23.95 3794.33 78 89

ACR9931/LOCAL 47.50 77.52 1239 14.94 229 1484.22 14.48 13.23 1137.00 24.23 3791.00 79 90

ACR9931/IT 98K-131-2 47.38 77.40 1300 14.85 229 1591.40 14.89 14.05 1201.40 23.82 4005.42 76 95

ACR9931/IT 93K-452-1 46.94 76.92 1297 15.00 229 1544.00 14.82 13.55 1158.33 23.86 3859.00 75 92

Mean 47.18 77.19 1287 14.94 230 1532.00 14.72 13.60 1167.00 23.94 3891.03 77 92

F-LSD(0.05) 0.64 0.65 68.50 0.33 5.58 98.20 0.48 0.79 78.70 0.66 262.50 4.20 7.90

BLOOM = Days to 50 percent flowering; MATURITY = Days to maturity; DFWT = Dry fodder weight; NSTAND=Number of plant stand; PHT = Plant Height;

COBWT = Cob Weight; COBLT = Cob Length; NCOB/PLOT = Number of cob per plot; SEEDWT = Seed Weight; 100SWT = 100 Seed weight; GYLD/HA =

Grain Yield per hectare; T (%) = Threshing percentage; HI = Harvest index.

170

Table 41: Effects of season and genotypes on growth, reproductive and grain yield of maize variety combined over 2009 and 2010 in Ako

SEASON

Genotype BLOOM

(days)

MATURITY

(days)

DFWT

(g)

NSTAND PHT(cm) COBWT

(g)

COBLT

(cm)

NCOB

/PLOT

SEED

WT (g)

100SWT

(g)

GYLD

kg/HA

T

(%)

HI

( %)

Early ACR9931/ IT 97K-499-35 46.48 76.48 1369.00 14.70 247.00 2028.60 15.00 15.49 1561.02 29.30 5205.07 78.00 87.58

ACR9931/IT 97K-568-18 48.00 78.03 1313.02 14.57 241.05 1865.03 14.70 14.03 1430.34 27.37 4768.11 77.00 80.70

ACR9931/LOCAL 49.04 79.23 1209.18 15.09 239.33 1958.44 14.49 14.37 1487.00 27.47 4958.40 77.37 80.00

ACR9931/IT 98K-131-2 47.59 77.77 1348.40 14.00 243.12 2043.00 16.00 15.02 1561.44 28.90 5206.00 77.25 92.07

ACR9931/IT 93K-452-1 48.00 76.00 1316.08 15.11 239.00 1967.27 15.07 14.78 1503.00 29.55 5010.95 77.00 88.00

Mean 47.82 77.50 1311.14 14.69 241.90 1971.47 15.05 14.74 1508.56 28.52 5028.71 77.32 85.67

Late ACR9931/ IT 97K-499-35 46.75 77.35 1217.00 15.00 219.29 1111.21 15.33 12.48 840.66 19.00 2804.09 77.50 69.62

ACR9931/IT 97K-568-18 47.00 77.04 1300.13 14.81 214.17 1077.09 14.00 11.73 846.03 19.07 2820.27 78.83 66.90

ACR9931/LOCAL 47.09 77.00 1269.50 15.24 220.00 1009.00 14.27 12.00 787.41 17.81 2625.01 74.00 65.00

ACR9931/IT 98K-131-2 46.01 76.17 1252.00 15.17 216.19 1139.75 13.65 12.90 842.00 19.11 2806.00 74.20 68.53

ACR9931/IT 93K-452-1 45.99 76.00 1278.00 15.00 220.00 1121.00 15.00 12.00 812.00 19.00 2706.72 72.13 65.00

Mean 46.57 76.71 1263.33 15.04 217.93 1091.61 13.45 12.22 825.62 18.80 2752.42 75.33 67.01

F-LSD(0.05) 0.87 0.55 105.80 0.46 8.40 133.10 0.68 1.06 102.40 0.90 341.20 2.24 11.30

BLOOM = Days to 50 percent flowering; MATURITY = Days to maturity; DFWT = Dry fodder weight; NSTAND = Number of plant stand;

PHT = plant height; COBWT = Cob weight; COBLT = Cob length; NCOB/PLOT = Number of cob per plot; SEEDWT = Seed weight; 100SWT

= 100 Seed weight; GYLD/HA = Grain yield per hectare; T (%) = Threshing percentage; HI = Harvest index.

171

CHAPTER FIVE

DISCUSSION

Genotype by environment interaction is an important consideration in crop evaluation and

improvement since relative performance of genotypes often changes from one environment to

another (Benmoussa et al., 2005; DeLacy et al., 1990). Association between phenotypic and

genotypic values were modified by the interaction between genotype and environment thus

plant that performs well in one environment may not necessarily perform well in another

environment (Beneye et al., 2011; Falconer and Mackay, 1996). Furthermore, Baker (1988)

stated that GXE interactions are the failure of genotypes to achieve the same relative

performance in different environments. In view of the apparent inconsistencies in the

performance of genotypes across different environments, it is necessary that multi-

environment evaluation trials of crop cultivars be used to measure crop performance across

test environments with a view to selecting promising genotype that will fit a target

environment.

5.1 Test of significance for variance component

Test of significance of components of multi-environment trials is recommended for

estimating relative contribution of the various components to observed variation (Crossa,

1990). This study revealed the presence of significant genotype X season interaction,

genotype X cropping system interaction, genotype X spray regime interaction and genotype

X season X cropping system X spray regime interaction. These obvious interactions indicated

that conclusions based solely on genotype means would not be reliable, since genotypes

responded differently to changes within the environments. The study also revealed that

growth, reproductive, grain yield, and insect damage components were highly significant in

all the environments. This result indicated that the interactions between the environment and

the genotypes with respect to these traits confirmed that these traits changed across the test

environments and across all the genotypes. This observation is in conformity with Baiyeri

(1998) and Kang (1998) who reported that highly significant environmental impact on traits

would indicate that the evaluation environments were actually different justifying the need

for genotype evaluation across several environments. Crop performance in a given

environment can be explained in terms of the resources available in the environment and the

biological and physical hazards that affect the attainment of the potential in the environment

172

(Bidinger et al., 1996). It was necessary that genotype performance was influenced by

environment to aid crop selection and the development of technology options (Ezeaku et al.,

1997; Ezeaku and Awopetu, 1992).

5.2 Seasonal effects

5.2.1 Plant traits

Early and late season sowing dates were utilized to evaluate some selected cowpea genotypes

across various locations and years. Results obtained indicated that yield and yield

components were best expressed in early season in experiment one and decreased in late

season. Ray et al. (2008) working on soybean reported that early planting date produced a

higher seed yield than late planting. Javid et al. (2005), Karungi et al. (2000b) and Ezedinma

(1967) also obtained similar result on cowpea and attributed the yield differences to higher

solar radiation and leaf area index as well as lower pest pressure in early season. This result

confirmed those findings except that differences in yield between the two seasons could also

be attributed to rainfall, since the reproductive period was longer in the early season than late

season owing to adequate moisture. This view was supported by Hall (1992), Ismaila and

Hall (1998) who noted that early sowing enabled cowpea to escape high temperatures during

the flowering stages when the crop was sensitive to heat and the crop would mature before

the rains ceased. Higher grain yield in early season could therefore be attributed to longer

duration of pod filling which was observed in early season in this study. This result was in

line with that of Evans (1993) who observed that the longer the duration of growth period the

higher the potential photosynthates production and consequently the better the crop

performance.

The result further showed that plant population was higher in early season than late season,

indicating that lower soil temperatures at the time of late planting affected seed germination,

and consequently resulted to lower plant population. Lower cowpea grain yield as observed

in this study in late season could be attributed to this phenomenon. Ismail et al. (1997)

reported that warm season annual crop such as cowpea exhibited slow and incomplete

emergence when subjected to cool soils. The threshold soil temperature where cowpea

exhibits incomplete emergence is about 190C. Soil temperatures below 19

OC often occur at

the peak of rainy season. Craufurd et al. (1997) reported that with optimum soil moisture the

rate of seed germination increased linearly as temperature increased. Hall (1992)

recommended that farmers should adopt early sowing at high soil temperature because such

173

practice would result in higher plant population and better crop yield.

In experiment two however, there was a reversal in which yield and yield components were

higher in late season than early season. This apparent inconsistency in cowpea yield between

experiment one (Ishiagu and Mgbakwu locations) and experiment two (Ako location) may be

due mainly to better soil status in Ako location that favoured late season sowing. Higher clay

and silt content inherent in Ako location could have resulted in higher than optimum soil

moisture level in early season and subsequently resulted in observed higher overall growth

traits and lower grain yield components. Grain yield is known to be severely depressed when

cowpea is grown under conditions of excess soil moisture. Moreover, these soil

characteristics in Ako along with its higher organic matter content and cation exchange

capacity could have promoted good moisture retention and availability of soil nutrient both of

which could have contributed to enhanced grain yield in late season. Ishiagu and Mgbakwu

locations that constituted experiment one are predominantly sandy soils, with lower organic

matter content and cation exchange capacity. These soil characteristics hardly conserve

moisture and do not retain nutrients especially in late season when moisture level is usually

limiting, and this could have contributed to the lowered grain yield in late season in the two

locations. Differences in yield between experiment one and two could also be explained from

the point of view of higher Maruca population in early season which affected yield in Ako

location as against its lower population in Ishiagu and Mgbakwu. Although, yield and yield

components in cowpea have been shown to be strongly influenced by season, other factors

such as soil characteristics, rainfall profile and pest dynamics have modifying effects.

The differences in yield pattern across these locations as observed in this study are as

expected, and justified the evaluation of crop species in environments with distinct biotic and

abiotic resources. Germplasm evaluation is the scoring of traits not easily detected and which

is controlled by one or more genes and estimated to be important for crop improvement

programs or for direct use, but usually having a strong genotypic environmental interaction

(Perrino and Monti, 1991; Adu-Gyamfi et al., 2002). Evaluation criteria are based on the use

of crop parameters and characteristics which have been identified in order to build into the

crop higher yield and more resistant to pests. For this reason, a complete evaluation of crop

genotypes cannot take place in one environment as use of the results of the evaluation would

be limited only to that environment. However, even in one environment, evaluation should be

carried out at least for two or more years and in different seasons (Baiyeri, 1998; Perrino and

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Monti, 1991).

In this study, season was found to exhibit significant effect on cowpea flowering. The non-

photosensitive genotypes flowered and produced components of grain yields as expected in

both seasons, while the local variety failed to flower and produced no yield in the first season

owing to its sensitivity to photoperiod. This result is in conformity with Nangju et al. (1979),

Singh et al. (2002) and Kamara et al. (2009). Late season shortened days to flowering in this

study. This is in agreement with Summerfield and Roberts (1985) who noted that warmer

temperature hasten the appearance of flower in both photoperiod sensitive and insensitive

genotypes.

The results in this study also showed that pod length, number of seeds per pod, number of

branches and number of internodes were least influenced by seasonal changes. This result

confirmed the observation made by Karkannavar et al. (1991), Uguru and Uzo (1991) and

Singh et al. (2002) that these traits are moderately to highly heritable. They observed that the

average heritability estimates of these traits ranged between 57 - 85 percent. These are the

only traits that can be reliably selected across seasons since they are stable in such

environments, hence agronomic practices that could improve these traits may not translate

directly to improving grain yield. Selection of crop plants is fundamentally based on yield,

pest and disease resistance and quality which altogether constitute the broad objectives of

crop improvement programmes (Austin, 1993). Traits that can contribute directly or

indirectly to grain yield are usually targeted while traits that are of little or negative value are

discarded in a crop selection programme. Incidentally, most of the yield and yield

components sampled were strongly influenced by environments. The result obtained in this

study supported this fact.

Early season equally stimulated higher production of most growth component especially crop

biomass. This is contrary to Singh (1985) who reported higher cowpea biomass production in

late season and attributed the result to higher activities of foliage beetles and leaf miners in

early than late season. The results showed that aphids and Ootheca beetles although higher in

early season were comparably too low in both seasons to cause any significant reduction in

cowpea foliage. Also, early establishment and cessation of rains in the locations of this study

(Table 3) may have also contributed to higher crop biomass in early than late season.

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The effect of season on threshing percentage and harvest index were similar to that of grain

yield with early season favouring higher expression of both traits. Harvest index is directly

related to some yield components as well as other growth components such as plant

population. The finding is supported by Kwapata and Hall (1990) who noted that harvest

index was positively correlated with yield and yield components in cowpea. This indicated

that the yield potential of cowpea could be raised by selecting for high harvest index.

5.2.2 Genotypes

Expression of genetic potential of crop is intrinsically subject to environmental variables.

Thus, phenotypic traits are influenced by genetic potential, resource availability and use, and

reaction of genotypes to biotic stress (Baiyeri, 1998; Stroup et al., 1993). The ten genotypes

used in this study consisted of materials with different plant types, maturity, and of variable

genetic background (Table 1). According to Plucknett et al. (1987), it was normal that

genotypes display distinct phenological and yield differences. Extensive variability among

germplasm offers the possibility of selection to fit different environments and also allow for

selection based on traits. Most of the local cowpea cultivars in the Nigerian savannas are

photoperiod sensitive and have indeterminate growth habit Patel and Hall (1990). They are

late maturing and very susceptible to pest and diseases (Amatobi, 1995). For example, in this

study local variety failed to flower and produce grain in early season while the improved

genotypes flowered and produced yield. This result confirmed the presence of photoperiod-

insensitivity traits among IITA bred materials and that local variety used in this study truly

exhibited photoperiodic sensitivity in the locations used for the study. This phenomenon was

elucidated by Craufurd et al. (1997) and lend credence to our result that there were significant

differences among genotypes in their relative responses to photoperiod with local varieties

being acutely sensitive. As photoperiods shorten towards the end of the rainy season

(September-October) in West Africa these adaptive features ensure timely flowering of land

race germplasm (Wein and Summerfield, 1980). Local varieties cannot flower in long days

but in short day but photo-insensitive genotypes flower in both photoperiods. Njoku (1958),

Wienk (1963), Lush et al. (1980), Wien and Summerfield (1980), Hadly et al. (1983), Dow

el-Madina and Hall (1986) and Patel and Hall (1990) revealed that traditional cowpea

cultivars respond to photoperiod in a manner typical of quantitative short-day plants

(photoperiods longer than a critical value) which do delay, but do not prevent flowering.

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In comparison with improved genotypes local variety recorded significantly lower yield and

yield components in late season. It however produced significantly higher 100 seed weight

than all the improved genotypes used for this study when sprayed three times in late season.

This finding is supported by Singh and Ajeigbe (2001), Singh (1985), Singh and Ntare (1985)

and Rachie (1985) who reported that the actual grain yields obtainable in farmers‟ fields in

West African sub-region are very low (25-300kg/ha), due to severe attacks from the extensive

pests complex and use of unimproved varieties. Other workers reported that local land races

were poor in resource capture and utilization. The higher yield of improved cowpea over

local variety was supported by Singh et al. (2002) who showed that the use of improved

varieties led to the realization of 4 tonnes per hectare. The genotypes local, IT97K-277-2,

IT97K-556-4 and IT93K-452-1 produced significantly higher 100 seed weight (bigger seed

size) in all environments, while IT84S-2246-4 and IT90K-82-2 consistently expressed

smaller seed size. Seed size in the rest of the genotypes was intermediate but varied with

environmental changes. Variation for this trait was higher in late season under zero spray

than other environments. Genetic study on cowpea seed size (measured as 100–seed weight)

indicated that heritability estimates for the trait was high and averaged 79.7 percent

(Karkannavar et al., 1991). Drabo et al. (1984) concluded that the gene action controlling

seed size is predominantly additive but they also noted that it could be modified by

environment. This is in conformity with the findings in this study. The large seed size

observed in local check was governed by dominant gene according to Karkannavar et al.

(1991). This large seed size observed in local variety could be responsible for its use by

cowpea breeders as donor parent in transferring large seed size to elite materials. Although,

the seed size of IT84S-2246-4 and IT90K-82-2 are below average, the genotypes were very

vigorous, exhibiting outstanding high number of hills and plant stands in all the

environments.

The study showed that the use of number of hills could constitute a more reliable index for

measuring cowpea seed viability and not number of plant stand. We propose that number of

hills be used as an index for measuring crop viability in cowpea because „seedling die back‟

may cause the use of plant stand misleading and unreliable. Moreover, plant stand is known

to be rather used as an index for measuring plant establishment or vigour. Ogunbodede

(1988) reported positive associations between seedling vigour and yield in several crops,

including cowpea, and suggested that specific seedling vigour traits might be useful selection

criteria for high yield in cowpea. This suggestion was not consistent with the performance of

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these two genotypes (IT84S-2246-4 and IT90K-82-2) as indicated in this study since

genotypes with poorer number of hills and plant stand performed better than them. The

performance of IT98K-131-2, for example was significantly higher than IT84S-2246-4 and

IT90K-82-2 even with its poorer plant stands, suggesting that there is yield compensation in

some varieties of cowpea. More studies need to be conducted to further understand the

scientific basis behind yield compensation ability in some cowpea genotypes.

Furthermore, the small seed size as revealed in IT84S-2246-4 may probably be part of the

reasons why the genotype even though released to farmers in several countries are not being

adopted by farmers. Adjadi et al. (1985), Singh and Singh (1990) and Singh (1993, 1994a)

stated that IITA has developed a number of varieties such as IT84S-2246-4 which has a

combined resistance to aphids, thrips and bruchids. Consequently, Jackai and Adalla (1997)

reported that cowpea growers no longer need to spray their crop against aphids if they plant

the right cultivars. One of such best cultivars was IT84S-2246-4, a brown-seeded cultivar

released in Nigeria and other countries. It was further observed that high yield and resistance

of this variety to pests not withstanding, many farmers do not grow the cultivar for reasons

unknown to us which deserve investigation. Seed size as a key factor in the adoption of

cowpea varieties was elucidated by Coulibaly and Lowenberg-DeBoer (2002) who hinted

that farmers would adopt new cowpea varieties with substantial economic benefits. They

concluded that cowpea varieties with large seed size and resistant to bruchids attracts

premium price and that varieties with such traits are quickly adopted by farmers. The small

seed size of IT84S-2246-4 has been found in this study to be responsible for its low adoption

by farmers. This study did not agree with Ogunbodede (1988) who claimed that large seed

size resulted in better crop establishment. On the contrary, this study revealed that genotypes

with larger seed size had poorer crop establishment because they are found to be more

attacked by bruchid weevils which consequently affected their viability and vigour. For

example, poor plant population in local variety as observed in this study may have its

explanation on its inherent large seed size. Getting a good crop stand is paramount to getting

good yield. Damage from Ootheca beetles, leaf hoppers and birds as well as poor seed

storage can cause poor plant stands. Although Jackai and Adalla (1997) recommended the use

of seed dressing chemical as remedy for poor plant stand. However, dressing seeds in this

study did not improve plant population in local variety. Consequently, the poor germination

observed in local variety may be attributable to poor seed storage which may have exposed

the seeds to bruchid attacks.

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The local variety although had lower plant population, it nevertheless produced the highest

fresh and dry fodder yield especially in early season. It also expressed significantly higher

number of branches, leaves, internodes and vine length. This observation is supported by

Singh et al. (1997) and Blade et al. (1992) who reported that while the traditional varieties do

not yield as much grain, they do give large fodder yield. They recommended that research

should be carried out in different agro-ecologies to identify dual-purpose varieties, which will

give reasonable grain as well as fodder. Our study showed that IT90K-227-2 and IT97K-556-

4 exhibited dual-purpose characteristics in both seasons having produced high yield of both

grain and fodder, while the rest of the genotypes were purely grain type. Thus, the earlier

reports by Ajeigbe et al. (2005), Singh et al. (1997) and Kamara et al. (2010) were confirmed

in this study as they also identified these genotypes as dual-purpose cowpea. Genotypes

IT90K-277-2 and IT97K-556-4 that were found to be dual-purpose in this study are both

determinate and medium maturing (Table 1). Determinate growth habits combined with long

duration may have stimulated higher fodder production because after pods were harvested,

fodder was immediately harvested as against indeterminate cultivars where pods are picked

periodically and severally and in the process leaves senescence.

The short growth duration and high mean yield would make IT93K-452-1 the best grain

cowpea as it combined these qualities with tolerance to most post flowering pests. Its high

grain yield was expressed through higher number of pods per plant and seed weight.

Genotype IT93K-452-1 produced reasonable grain yield in late season even without chemical

spray. The genotype will be most preferable in areas where rainfall is unpredictable and

among resource poor farmers who cannot afford agro-chemicals. In an earlier trial by Singh

et al. (1994), IT93K-452-1 was also found to possess superior grain yield potential in

northern Guinea Savanna of Nigeria thereby confirming our result. However, it was not

widely adopted because of its poor fodder yield, which this result also elucidated. The

genotype could be popular among cowpea seed growers who do not keep livestock.

Although early season planting encouraged higher grain yield, Nangju et al. (1979) warned

that it might result in poor seed quality when pod ripening occurs during the rains. In contrast

to this speculation, IT93K-452-1 maintained clean and healthy seeds even though due to its

earliness podded during the rains. The maintenance of clean and healthy seed by this

genotype may not be unconnected with less leaves and high peduncle length observed in this

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study. Owing to the long peduncle attribute of IT93K-452-1 the pods were therefore formed

above the canopy. Meanwhile, all the improved varieties possessed higher peduncle length

than local variety and this could be one of the possible reasons why although the genotypes

podded and matured during the peak rains their seeds were healthier than that of local variety.

It was observed that the local variety expressed lower bruchids attacks than expected in 2008

in Ishiagu and Mgbakwu locations. Short peduncle length characteristics of local variety,

higher number of leaves and vine length as observed in this study could have made the pod to

form under the canopy leading to sever seed spoilage. Bruchids do not hibanate or lay eggs

on an unhealthy seeds (Singh and Singh, 1990); and this may have been responsible for less

bruchid damage observed on the local variety. Furthermore, 2008 recorded higher rainfall

than 2007 in both locations (Table 3) which may have contributed to higher seed damage on

local variety and consequently lower bruchid infestation.

The genotype IT98K-131-2 was an outstanding medium maturing genotype combining

superior grain yield with tolerance to pre-and-post flowering pests. According to Jackai and

Adalla (1997), when genotypes that are resistant to some insect pests are treated with

insecticides, the effects are additive resulting in higher productivity. Similarly, its superior

performance cut across seasons, locations and years showing that IT98K-131-2 had broad

and stable adaptation to these environments. It also produced good grain yield in late season

without chemical spray. Also, genotype IT98K-131-2 was found to be a good example of

grain type cowpea. Although, it produced significantly higher vine length, it nevertheless had

low fodder yield. The long vines did not translate to higher biomass yield. Its indeterminate

growth habit may be implicated for this observation. The result revealed that number of

leaves had higher contribution to fodder yield than vine length especially in determinate

cowpea varieties. Kamara et al. (2010) working in northern Nigeria also identified IT98K-

131-2 as a superior variety and reported that it is being gradually adopted by farmers in the

region. However, the sustainability of its adoption in areas where fodder resources are critical

for feeding livestock is in doubt. The result further showed that when IT98K-131-2 was

grown in early season with chemical spray it behaved like a dual-purpose cowpea.

Consequently, agronomic practices that could prolong the longevity of the leaves on the plant

over a long period of time should be explored. If such practices are developed, it will not only

increase the biomass production that are required by livestock farmers but will further

optimize the grain yield attributes of IT 98K-131-2, and sustainably increase its adoption.

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Most genotypes tested expressed similar I00 seed weight across different environments. For

instance, the genotypes IT90K-277-2, IT98K-556-4, local and IT93K-452-1, produced

significantly higher and more stable 100 seed weight across all the environments compared to

other traits. This result is corroborated by Karkannavar et al. (1991) who pointed out that

seed size in cowpea is highly heritable and is less affected by environment. These improved

varieties listed above had earlier been reported to have larger seed size (IITA, 1995). Our

result did not totally agree with that of Kitch et al. (1998) who reported that large seed size

was peculiar to longer duration genotypes which had limited seed filling characteristics and

poor yield. Such claim may be applicable to local cowpea cultivars, but not to improved

genotypes developed for better performance, as revealed in this study.

Genotype IT97K-556-4 exhibited superior grain and fodder yield attributes in early season

particularly in Mgbakwu location. This genotype exhibited narrow adaptation to seasonal

characteristics because when it was planted in late season with or without spray, its yield and

yield components as well as fodder production were significantly depressed. Similarly, our

result showed that IT97K-556-4 harboured the highest population of most of the insect pests

sampled in both seasons, indicating that the genotype was susceptible to these pests. This

observation may have accounted in part for the low productivity of the genotype in late

season in all the environments as revealed in this study. Furthermore, IT97K-556-4 clearly

expressed significantly higher number of leaves in all the environments. This plant

characteristic may have made the genotype vulnerable to pest attacks and enhanced excessive

water loss through transpiration process in late season which may have been responsible for

its significantly lower yield in that environment. Although, soil moisture may not constitute a

limitation in the study sites, this genotype was found to express lower root length in

Mgbakwu location and since Mgbakwu soil was classified as sandy soil (Table 2) minor dry

spell in late season could have had adverse effects on the genotype resulting in its low grain

yield. The poor performance of the genotype in Ishiagu could invariably be attributed to

higher clay content that could have further suppressed root elongation. According to

Robinson (1996), sustained high crop productivity is dependent on porous, loose soils

allowing unimpeded root extension. Impeded horizontal and vertical root growth in clay soil

will reduce both crop vigour and yield.

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The medium to late maturing genotypes were better adapted to late season while early

maturing genotypes could be sown profitably in both seasons. In support of our result, earlier

reports showed that IT93K-452-1 an early maturing genotype can produce optimally in early

and late seasons (Singh et al., 2002). Moreover, genotypes local and IT90K-277-2 (Late and

medium maturing genotypes, respectively) were found to perform best in late season (IITA,

1995), which is also in conformity with our results.

Indeterminacy in cowpea has been established as a trait that confers tolerance to pests,

improved soil nutrient and produce better quality fodder. Supporting this view Snapp and

Silim (2002) reported that indeterminacy is related to higher pest tolerance, consistent growth

on low nutrient soils, and production of high quality residues. They further clarified that

indeterminacy improves pest resistance through a compensatory ability to re-grow and thus

mitigate pest damages. The soil benefits through high nitrogen fixation rate stimulated through

production of new leaf flushes and due to the ability to exploit favourable growth periods and

providing quick protective soil cover by biomass and senescent material. This study partly

confirmed this observation with respect to IT98K-131-2 (a high yielding, indeterminate

genotype with tolerance to all the pests sampled in all the environments). Kitch et al. (1998)

however reported that indeterminacy is associated with high labour demand.

5.2.3 Insect pest components

5.2.3.1 Aphids

The population of aphids was found to be generally low in the locations used for this study;

however, it was higher in early than late season and more on local variety than on improved

genotypes. Our finding is similar to that of Blade and Singh (1994); Afun et al. (1991);

Alghali (1991a) who observed lower aphids population in southern Nigeria but reported that

they occurred throughout the year because groundnut, cowpea and other leguminous hosts

were always available. Aphids could be carried all the year round by prevailing winds over

long distances. They also reported higher infestation of aphids on unimproved cultivar than

improved ones. This was because Singh et al. (1990); Jackai and Adalla (1994) reported that

IITA has developed and released several aphids resistance cowpea varieties in Nigeria.

Besides being unimproved, local varieties could have been more attacked than improved

cultivars because of its higher foliage production with the associated humid environment

within the canopy which supported rapid aphids multiplication. Our result is further

corroborated by Bottenberg et al. (1997) who reported that aphids are present all the year

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round but predominatly higher during the early season in the south and dry season in the

north. The higher population of aphids in late season as reported by researchers in Northern

Nigeria which is contrary to our result could be attributed to the fact that besides being

widely grown in northern Nigeria, the crop has been in the traditional farming systems over a

long period of time. Also, groundnut an important alternative host to aphid is predominantly

grown in late season in that region.

There was no location X year interaction for aphids in both experiments. Kamara et al.

(2010) observed that this pest is sporadic and differed across locations and years. Our result

may be attributed to grain cowpea being a new crop in some of the study locations, however,

this result may likely change if cowpea is continuously grown in the study areas. It was

observed that the genotypes identified by IITA as being resistance to aphids were assessed

only at the seedling stage (Singh and Jackai, 1985). In a study to determine the reaction of

these resistance cultivars to aphids challenge at different growth stages, locations and years

revealed that some cultivars were susceptible to infestation at the post flowering stage, thus

suggesting growth stage, location and year specific tolerance rather than a generalized form

of resistance. This finding confirmed reports from several workers (Singh and Jackai, 1985)

in national programs in West and Central Africa that a number of aphid resistance cowpea

cultivars developed in IITA were susceptible to this insect at the reproductive phase. This

observation is also in line with our result where there was variability among improved

genotypes for aphid infestation.

5.2.3.2 Bruchids

This study showed that bruchids was significantly higher in late than early season and varied

widely among the genotypes studied. This result is in agreement with Murdock et al. (1997)

and Nangju et al. (1979) who observed that higher storage losses on cowpea seed was

observed in warmer temperature than cooler temperature. We found that brown seeded

cowpea consistently harboured lower infestation of bruchids than white seeded types.

Although IITA scientists claimed that some of the genotypes used in this research are

bruchids resistant (IITA Report, 1982). This finding did not confirm the claim in all cases,

except IT90K-277-2 that was stable for this trait in all the environments.

Over the years, researchers have sought practical and low-cost techniques to solving the

problem of bruchids pest on cowpea. Most of the approaches developed were hazardous to

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human health and detrimental to the environment. This finding appeared environmentally

friendly, safe and sustainable method of controlling bruchids on cowpea as it combined the

use of identified traits that confered genetic resistance with targeted spray regime.

Development of thick pod wall as a means of reducing bruchid damage by breeders did not

seem to effectively provide physical barrier against bruchids attack on cowpea as observed in

this study. This is because both thick and light pod walled genotypes were similarly attacked

as long as they are white seeded. It appeared that certain substances may exit within brown

seeded cowpea genotypes that repelled bruchids larva. In this regard, more study as a priority

is required to further confirm or otherwise our finding.

According to Jackai et al. (1988); Breniere (1967), poor plant stands caused by bruchid

infestation are persistent problem in many cowpea fields. Optimum plant population is

however paramount to obtaining high cowpea grain and fodder production. Most commonly

recommended method of controlling bruchid weevils did not recognise the protection that

chemical spray in the field confers on stored cowpea seed. This result revealed that field

application of insecticide targeted at the critical crop growth stages especially 50 percent

podding stage significantly reduced cowpea seed damage by bruchids at storage. The study

further demonstrated that three insecticides spray reduced bruchid population on cowpea seed

by 240 percent.

5.2.3.3 Ootheca

Ootheca population was found to be low in the study sites. However, early season harboured

higher population than late season. Although, variation among genotype existed for this trait,

they were considerably similar except for local variety and IT97K-556-4 that varied widely.

The high population of Ootheca on these two varieties could probably be because the two

varieties are highly vegetative and long duration cowpea. The generally lower population of

Ootheca on improved varieties as observed in this study is supported by Jackai and Adalla

(1997) who reported that cowpea growers no longer need to spray their crop against Ootheca

if they plant improved cultivars. Also, some IITA cowpea lines had been confirmed to be

resistance to Ootheca in Philippines (Adalla, 1994) and in Taiwan (IITA, 1986). Our finding

was however at variance with Nangju et al. (1979) who reported that insect damage to foliage

caused by Ootheca was much lower in the first than in the second season, since its population

was lower in the beginning of the rains and reached their peaks in the second season. This

discrepancy could be due to effects of climate change on insect pest dynamics. For instance,

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according to Porter et al. (1991), projected climatic changes could alter geographical

distributions of agricultural insect pests and stimulate rates of early season population

growth, reduce generation time and increase the number of generations per year, lengthen the

seasonal development period, alter crop and pest synchrony and upset natural control by

predator. Increased and accelerated rates of population development of pests will generate

greater pressure in the vulnerable early season stages of crop growth. Furthermore, there was

no significant year X location interaction for Ootheca population in this study. It is possible

that with continuous cultivation of cowpea in the study sites and increase in global climate

variability the result may differ in subsequent years. The higher grain and dry fodder yield in

early season than late season as revealed in this study is an indication that Ootheca did not

cause any significamt economic loss.

5.2.3.4 Pod sucking bugs

Pod sucking bugs were highly prevalent in the locations used for this study with higher

population in late than early season. Local variety and IT97K-556-4 genotypes were more

infested by pod sucking bugs than the rest of the improved genotypes. Pod sucking bugs

attacked cowpea more in Mgbakwu than the other two locations and the population was more

in year two than year one. The finding of Javaid et al. (2005); Karungi et al. (2000a) and

Kamara et al. (2010) are in support of our result that pod sucking bugs attacked cowpea more

in late season than in early season but at variance with Nangju et al. (1979) and Jackai and

Adalla (1997) who reported that pod sucking bugs infestation was higher in early than late

season. Considerable pod and seed yields of all the genotypes in early season without any

insecticide application clearly confirmed our finding. In late season however, cowpea yields

were extremely low without insecticide application, invariably due to heavy depredation by

pod sucking bugs. This observation further supports our result. The prevalence of this pest as

observed in this study is supported by Jackai and Adalla (1997); Singh et al. (2002) who

noted that pod sucking bugs is one of the most dominant pest species in tropical Africa. The

two genotypes (Local and IT 97K-556-4), found to habour more pod sucking bugs in this

study are late maturing and possess significantly large seed size. Chambliss and Hunter

(1997); Jackai and Adalla (1997) reported that several of the newly identified resistant

germplasm that are resistant to pod sucking bugs have small seed size. They concluded that

seed size was directly related to damage by the pod borer and pod bugs which is also in line

with our finding. Long duration cowpea genotypes expectantly will be attacked more since

they will pod late in the season when the activities of pod sucking bugs would naturally reach

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its peak as reported by Nangju et al. (1979).

Although total amount of rainfall and mean relative humidity was higher in Ishiagu and Ako

locations, than Mgbakwu, yet pod sucking bugs was more in Mgbakwu. This is contrary to

Alghali (1991a, 1992b) who reported that high rainfall with associated relative humidity

usually increases insect pest pressure in cowpea in West Africa. The higher population of pod

sucking bugs in Mgbakwu may not be unconnected with the large scale cultivation of

vegetable cowpea in the area. Significantly higher population in subsequent years than first

year of planting is an indication of population build up of the pest. Denlinger (1986) reported

that non migratory pests such as pod sucking bugs may survive locally over the dry season on

alternate hosts, or on cowpea planted in soils with residual moisture or in irrigated land. In

our case vegetable cowpea in this environment became ready alternate hosts that aided the

carry over of the pest from one season to another. Hammond (1983) found inactive,

quienscent pod sucking bugs adults in cowpea leaf litter during the dry season in Mokwa and

concluded that the pest population multiplies subsequently when the environment became

favourable.

5.2.3.5 Maruca

This study showed that Maruca pest pressure was considerably higher in late season and

almost absent in early season in experiment one. The pest was generally low in Ako,

intermediate in Ishiagu and high in Mgbakwu. Also in experiment one the population was

higher in second year than first year. This result that showed that the population of Maruca

was higher in late than early season is similar to the result of Kamara et al. (2010); Chambliss

and Hunter (1997); Jackai and Adalla (1997) and Nangju et al. (1979). Our result is further

corroborated by Taylor (1967) who reported that light trapping in Ibadan showed that flight

activities in Maruca results in its population reaching the peak in late season. On the

contrary, Alghali (1991a) reported very low infestation levels of Maruca in the dry season in

northern Nigeria. The lower population of Maruca in dry season in northern Nigeria

according to Taylor (1967) is due to the fact that Maruca is a migratory pest and does not

diapause during the dry season and was not found in association with any alternate hosts or

cowpea during the dry season in northern Nigeria. Maruca populations move from south to

north over a period of several months or generations following the northward progression of

rainfall, cowpea planting and possibly the flowering pattern of leguminous trees. The further

north, the latter the moth arrive; also, the fewer the generations that can be completed and the

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lower the population build up in the north (Bottenberg et al., 1997). Singh et al. (1997) found

Maruca unable to survive the dry season in the north, even if cowpea is available in the

fadamas, possibly because of some unfavourable climatic conditions other than the absence

of rain, such as temperature and relative humidity. This low population of Maruca in northern

Nigeria could probably be responsible for higher productivity of cowpea in that region.

Maruca was reported by Bottenberg et al. (1997) as being one of the most destructive pests

and drastically reduced cowpea grain production because they feed on the flowers and pods.

Unfortunately, there is no reliable source of resistance against this pest yet as against the rest

post-flowering cowpea pests that have reliable sources of resistance.

Akingbohungbe (1982) reported too periods of peak activity of Maruca at Ile-Ife, from April

to July and October to December. This biomodal population pattern was confirmed by

Alghali (1993b), who not only found that larval counts are significantly related to cumulative

rainfall and number of rainy days but also stressed that even distribution of rainfall over time

is more critical. The result of Leumann (1994); Arodokoun (1996) supported our finding that

the population of Maruca is cumulative and increased from year to year.

The plausible explanation to the reason for higher population of this pest in late season as

revealed in this study was given by Harris (1962) and Usua (1973), who noted that maize

stem borer, Busseola Fusca fuller, which are prevalent in late maize in southern Nigeria, was

responsible for higher population of Maruca pod borer on cowpea in late season. On the

contrary, the higher population of the pest in early season in experiment 2 (Ako location)

could be attributed to the peculiarity of the location, as it is bounded by two lakes and one

perennial flowing river. This environment encouraged ever green vegetative cover all year

round which could have provided alternative host to Maruca through out the dry season and

subsequently increased its population rapidly in early season. This result revealed that early

planting coupled with lower frequency of insecticide application resulted in higher grain yield

while in late planting, low frequency of insecticide application resulted in no or zero grain

yield. This formed the underlying justification for IPM. Some authors have argued that early

planting in West Africa will allow the plant to flower in the middle of the year when rainfall

is heavy and cowpea would usually require frequent spraying. These results have provided

sufficient evidence to the effect that early sowing of cowpea in southeastern Nigeria results in

higher grain yield which is environmentally safe and economically feasible.

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5.2.3.6 Thrips

The population of thrips was higher than other post-flowering pests in all the locations used

for this study implicating the pest as one of the most important insect pest of cowpea in

Southeastern Nigeria. In confirmation of our result Amatobi (1995) and Jackai et al. (1985)

reported that thrips population is in abundance in West Africa and can cause 100 percent

yield loss in cowpea if not controlled. This result also agrees with Alghali, (1992a) who

found thrips to be the most prevalent insect pests of cowpea in southern Guinea and Sudan

savanna agro-ecological zone of Nigeria. Similarly, Alghali (1992b) and Amatobi (1995)

identified thrips as the most limiting insect pest in terms of grain yield loss. Attacks by this

pest on cowpea begin at flower bud formation and continues through flowering (Ezueh and

Taylor, 1983). Our findings that thrips was more abundant in late season than early season

was further supported by the results of Nangju et al. (1979) who noted that the population of

thrips was low at the beginning of the rainy season but rose dramatically and reaches the peak

in October and November. The lower number of pods observed in this study in late season

across all the genotypes and locations was probably due to greater damage by this pest on

cowpea planted in late season which further corroborated our findings. The higher attacks on

local genotype by thrips may not be unconnected with its late flowering and maturity. In

2008, the population level of thrips increased by 195 percent over the 2007 level. This

astronomical increase is explained by Ng and Marechal (1985) who reported that the pest

problem on cowpea is clearly more severe in humid regions of Africa than elsewhere,

because many of the pests are considered indigenous to this region and have had ample time

to co-evolve with the crop, and they tend to cumulatively increase from year to year.

5.3 Insecticides spray regime effects

5.3.1 Growth, reproductive and grain yield components

In comparison with zero application, insecticide treatment reduced fresh and dry fodder yield

in both seasons. This result is in agreement with Ajeigbe et al. (2005) who reported that the

reduction in fodder yield was partly because of greater grain yield and delay in cutting of the

fodder due to multiple grain harvest resulting in the loss of leaves due to senescence. This

situation affects both quality and quantity of fodder. This was also the conclusion of Tarawali

et al. (1997) and Tarawali et al. (2002). Conversely, Schulzet et al. (2001) observed that if

cowpea is not adequately protected from insect damage, it produced less grain and more leaf

and vine dry matter. Also, thrips and Maruca damage stimulated higher fodder production

because photosynthates that would have been invested in flowers and pods are used for

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foliage development. Alghali (1991a) confirmed that fodder production was enhanced by

non-application of insecticides, and concluded that when pest attack is heavy and grain yield

is minimized fodder production increased significantly.

Insecticides treatment was found to stimulate significantly longer vines in most genotypes

and in both seasons compared to untreated plots. This observation is a clear evidence that the

insecticide used in this study was effective in controlling aphids which is believed to be

responsible for stuntedness in cowpea growth. Ansari et al. (1992) revealed that delay in

controlling aphids early in the growth and development of cowpea could result in stunted

plant growth, lower foliage and poor quality fodder. Furthermore, Ram et al. (1990) stated

that if insect pests are not controlled on time, it generally reduce the quality of cowpea

fodder. This result also showed that early to medium maturing genotypes produced more

grain than fodder. This result is supported by Singh et al. (1994) who reported that early and

medium maturing varieties yielded higher grain but lower fodder than late maturing and

fodder type cowpea. When pest attack is heavy especially thrips and Maruca and grain yield

is minimized; fodder production for animal nutrition guarantees the supply of animal protein

for human diet. Insecticide application increased the number of nodules while zero

application was found to depress nodule formation in early and late season. Okeleye and

Okelana (1997) observed a high correlation between grain yield and nodulation in cowpea.

The positive response between chemical treatment and grain yield as observed in this study

showed that chemical spray enhanced vegetative growth which in turn increased nodule

formation resulting in improved grain yield.

Meanwhile, our result further revealed that insecticide sprays resulted in earlier flowering of

cowpea than unsprayed plot in both seasons. This is in line with Ajeigbe et al. (2005) who

explained that flower bud and flower abortions were reduced when cowpea was sprayed and

this accounted for earlier flowering in the spray plots compared to untreated plots. The

prolonged days to pod fill when insecticides was applied as observed in this study enhanced

production of components of grain yield. Corroborating this result, Baiyeri (1998) found that

resource base of any environment dictates genotype performance, and concluded that highest

banana and plantain yield and yield components are obtained when the duration to harvest

was longest. The observed delay in days to maturity and pod fill when sprayed as against zero

spray suggests that insecticides application in cowpea increased grain yield through the

process of prolonged maturity and pod fill duration. The delay in maturity and pod fill

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provided ample opportunity for higher assimilate accumulation. Singh (1985) in support of

this view reported that management practices that delay duration of pod filling translates to

greater assimilate accumulation, and invariably higher grain yield in crop species.

Application of insecticide significantly increased all the yield and yield components in late

season. The yield increases implied that the major yield limiting pests were effectively

controlled by the insecticides used in this study. Singh and Allen (1980) maintained that

application of appropriate insecticides improved the yield of cowpea ten fold. Other studies in

West and East Africa have found application of insecticides to significantly reduce insect pest

populations and increased the yield and yield components of cowpea (Alghali, 1992b;

Karungi et al., 2000b). This study revealed that all the genotypes tested produced

significantly higher grain yield with insecticide spray in early season in Ishiagu than other

locations making the environment the most ideal one for cowpea production in the region. In

order word all the cowpea genotypes tested produced above average grain yield in Ishiagu

location. This result is in line with Parh (1993) who revealed that application of insecticide in

early season when the population of major post flowering cowpea pest is lower enhanced

grain yield considerably.

Insecticide spray positively affected the threshing percentage and harvest index of cowpea in

late season but not in early season. Consequently, the sprayed plots produced significantly

higher threshing percentage and harvest index than zero spray treatment. This result is in

agreement with Ajeigbe et al. (2005) who pointed out that insecticide spraying improved the

threshing percentage and harvest index as a result of increased seed per pod, pod per plant

and grain yield. Hall et al. (1997) stated that harvest index correlated positively with grain

yield in cowpea. Apparently, any agronomic practices that promoted higher harvest index

would equally enhance grain yield. The damage caused by Maruca podborer and pod sucking

bugs in zero spray treatment was reduced or eliminated when the plants were sprayed,

thereby increasing the threshing percentage. In early season however, spray regime did not

significantly affect any of the yield and yield components, probably because of lower insect

pressure and better environmental variables. Insecticide application did not affect the

resulting 100 seed weight implying that the higher grain yield obtained from sprayed

treatment was as a result of higher formation of number of pods per plant and seeds per pod

both of which were significantly higher under sprayed treatment than unsprayed treatment as

indicated in this study. The untreated cowpea plots in late season resulted in zero grain yield

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for most genotypes. This finding is confirmed by Singh and Allen (1980); Jackai et al. (1985)

that insect pest attack on cowpea if left uncontrolled often leads to total yield loss.

5.3.2 Insect pest’s management

Insecticide application was effective in reducing the population of all the pests sampled and

consequently increased cowpea productivity. Studies conducted elsewhere by Singh and

Allen (1980), Parh (1993), Prince et al. (1993), Raheja and Apeji (1980) and Alghali (1992)

clearly confirmed our result. Most of these workers obtained grain yield similar to ours with

6-8 sprays per season, which may have adverse environmental and eonomic consequences.

Kyamanywa (1996) and Amatobi (1995) suggested that lower spray rate could achieve

optimum grain yield if they are applied at the critical stages of plant growth. This result

confirmed that minimum use of agro-chemicals targeting stages when pest pressure is high

appeared to be the best approach. The highest reduction in pest population due to insecticide

application as revealed in this study was on bruchids and thrips. Schulz (1993) pointed out

that though the existing methods of controlling bruchids are workable yet they pose serious

health hazards. Bruchid infestations start in the field and continued into storage which makes

its control difficult. However, three insecticides sprays targeting the critical stages when pest

pressure is high was able to significantly reduce the population of bruchids and successfully

reduced the amount of bruchid damage in all the genotypes. Controlling bruchids in cowpea

is becoming an intractable problem because most methods used are storage based approaches.

Bruchid infestations cause weight and quality losses leading to a reduction in commercial

value and seed viability (Okeola et al., 2002). These findings could constitute one of the best

methods of controlling bruchids in cowpea since it tackled the problem right from the field

level where bruchids infestations and damage actually starts from. Jackai and Adalla (1997)

reported that thrips attack were sporadic in nature but timely application of recommended

insecticides tended to effectively control them.

The grain yield loss assessment revealed that yield loss due to zero spray application was

negligible in early season while in late season it was 100 percent for local variety, 34 percent

for best yielding medium maturing genotype (IT98K-131-2) and 30 percent for best yielding

early maturing genotype (IT93K-452-1). This result is much lower than what other authors

had reported but their result supported ours on percentage yield loss on local variety,

confirming the fact that the test genotypes were tolerant to most of the pests sampled.

Percentage reduction in insect population between zero spray and 3 sprays averaged across

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genotypes, seasons and years for aphids, bruchids, Maruca, Ootheca, pod sucking bugs and

thrips were, 121 percent, 240 percent, 174 percent, 45 percent, 38 percent and 270 percent

respectively. This result compared well with results of Amatobi (1994) and Singh et al.

(1984). Conversely, our result on percentage reduction in bruchids damage (240 percent) was

incomparable to those of Singh and Jackai (1985) who reported only 70 percent reduction in

bruchid damage. However, the wide gap could be due to their six months period of

incubation as against three months used for the present study as well as the targeted chemical

application employed in this study.

5.4 Cropping system effects

5.4.1 Cowpea genotypes and plant traits

Significant cropping system effect on crop performance had been documented by Wilson and

Kang (1981), Benities et al. (1993) and Wortmann and Sengaaba (1993). Maize was

intercropped with cowpea across two seasons and two years in Ako location. In this study,

intercropping was found to depress cowpea biomass production (by reducing most growth

components) in both early and late season while it increased the harvest index. For example,

intercropping in early season reduced fodder yield by 22 percent while in late season it

reduced fodder yield by 41 percent. This was similar to the results obtained by Wiley (1985)

in sorghum-pigeon pea intercropping system, where he concluded that sorghum competition

suppressed early growth and biomass yield of pigeon pea, and consequently the harvest index

of intercropping pigeon pea was increased.

Maize affected cowpea vine length more in late season than in early season. This observation

might be due in part to stress arising from shading effect and pressure due to competition for

essential environmental resources in late season. This is confirmed by the results of

Egharevba (1984) who noted that the competition imposed by sorghum on cowpea when

intercropped not only affect leaf area development and grain yield but also dry matter and a

number of other morphological characters such as plant heights and number of branches per

plant. Intercropping did not significantly reduce number of branches, internodes number,

number of leaves, number of nodules, plant population, and root length in this study. This

observation may not be unconnected with better environmental variables in Ako location

where this experiment was carried out in addition to the fact that most of these traits are more

or less genetically controlled. Lal and Maurya (1982) reported that the total root mass of the

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maize/cowpea intercrop was larger than either of the monoculture. In a humid forest

experiment, it was observed that water-use efficiency was higher in maize/cowpea intercrop

than in sole crop when water was not limiting, but in drought conditions the water use

efficiency of sole maize was greater than that of the intercrop (Hulugalle and Lah, 1986).

Similarly, Ofori and Stern (1987) stated that cereal and legume intercrops used water equally,

and that competition for soil water may not be a detrimental factor for most growth traits in

intercrop systems. Meanwhile, Ntare and Williams (1992) found intercropping to affect both

growth and reproductive components of cowpea in semi-arid regions where water is limiting.

In our intercropped study, maize was found to reduce cowpea peduncle length in both early

and late season but varied widely among genotypes. The local variety was, however, most

affected. Peduncle length may probably be sensitive to stress imposed by intercropping and

could be effectively used as indices in determining cowpea cultivars adapted to intercropping

system.

The local variety produced significantly higher fresh and dry fodder yield above all other

genotypes in both systems and seasons, supporting the report by Ng (1995) that local cowpea

co-evolved with cereals in a traditional cropping system and was grown primarily for fodder.

Similarly, local variety produced significantly higher 100 seed weight and number of pods

per plant in both systems in late season. This is in line with Blade et al. (1997) who noted that

the local cowpea varieties are highly adapted to intercropping systems than improved

varieties but they have a very low harvest index. The higher 100 seed weight and number of

pods per plant observed in local variety did not translate to higher grain yield since local

produced the lowest overall grain yield. This suggests that 100 seed weight and number of

pods per plant cannot be reliably used to estimate grain yield potential in cowpea that are

susceptible to Maruca and pod sucking bugs. Moreover, this study showed that local variety

harboured the least population of thrips in intercropping. This observation incidentally

revealed that although pods were not significantly aborted because of lower thrips population,

pods were therefore formed but were either partially filled or empty of seeds due to high

population of pod sucking bugs, and could however not result in higher grain yield.

Intercropping in both seasons significantly reduced yield and yield components in cowpea but

more in late than early season. Also, intercropping reduced grain yield in early season by 14

percent while it reduced grain yield in late season by 25 percent. This finding is similar to

that of Haizel (1974), Isenmilla et al. (1981), Olufajo (1988) and Cardoso et al. (1993) who

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reported a reduction in cowpea yields in maize-cowpea mixtures, while maize was

unaffected. IITA (1986) reported that cowpea yield were reduced by only 41 percent in

spreading cowpea intercropped with maize, whereas the determinate, early cowpea sustained

54 percent yield loses. Davis and Garcia (1983) also found a highly significant cultivar X

cropping system interaction for grain yield with semi-climbing beans when intercropped with

maize. Wien and Nangju (1976) reported that shading of cowpea by cereals resulted in the

reduction in cowpea yield. Our result showed that cowpea grain yield in early season sole

cropping ranged from 167-1121 kg/ha (with an average of 550 Kg/ha) and for early season

intercropping it ranged from 199-896 kg/ha (with an average of 483kg/ha). On the other hand

late season sole cropping ranged from 511-1406kg/ha (with an average of 984 kg/ha) and

intercropping ranged from 431-1105 kg/ha (with an average of 785 kg/ha). Greater grain

yield reduction by intercropping in late season was expectedly due to poorer environmental

resources in late season than in early season.

The cropping systems in early season did not affect 50 percent flowering and pod filling

duration. However, intercropping reduced maturity date. This result is contrary to Wien and

Nangju (1976) who found intercropping to reduce 50 percent flowering under mid-season

seeding condition. This result may not be unconnected with favourable environment in early

season that favoured both systems, while above ground stress imposed by intercropping

hastened maturity. Meanwhile, in late season genotypes flowered and matured earlier than in

early season. On the other hand, genotypes took longer days in late season to fill their pods

when compared with early season. The higher grain yield observed in late season in

experiment two may not be unconnected with this scenario. In both seasons, sole cropping

generally produced higher grain yield than intercropping. This finding was obviously because

of absence of shading on sole cropping.

Early maturing genotypes produced significantly higher grain yield than medium maturing

genotypes in both seasons and systems while medium maturing genotypes expressed their

highest yield potentials in late season sole cropping. Early maturing genotypes may probably

be more tolerant to shading than medium maturing genotypes. Moreover, the higher plant

population exbited by IT93K-452-1 (early maturing genotype) in both seasons may have

contributed to its higher yield potential in early and late seasons. Medium maturing

genotypes, IT 98K-131-2 may not be shade tolerant as it was found to perform best in late

season sole cropping across the locations and years used for the studies. This genotype

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possessed better agronomic effectiveness and was able to exploit residual moisture in late

season better than other genotypes. Some specific plant traits that confer adaptation to

intercropping have been identified. Terao et al. (1997) stated that the type of cowpea adapted

to intercropping is the spreading type, improved to retain a substantial root system. The

number of branches and increased internodes length are plant traits that are important under

intercropping (Nelson and Robichaux, 1997). Meanwhile, the cultivar with a bushy-type

growth habit has been reported to exhibit higher yield potential under sole cropping, whereas

the cultivar with a spreading growth habit was higher yielding under intercropping (Nelson

and Robichaux, 1997). Medium maturity, long peduncle, and indeterminate in growth habit

were the traits found in this study to confer adaptation to intercropping.

This result revealed that cowpea fodder yield in early season sole cropping ranged from 658-

1671 kg/ha (1219 kg/ha) while intercropping ranged from 575-1296 kg/ha (997 kg/ha). On

the other hand fodder yield in late season sole cropping ranged from 862-1283 kg/ha (961

kg/ha) while in intercropping, it ranged from 560-750 kg/ha (680 kg/ha). This result

confirmed that early season supported higher fodder production and that intercropping

depressed fodder yield when compared with sole cropping.

5.4.2 Insect pest infestation

Cowpea grain yield in intercropping were generally higher than yields from the sole crop

when no insecticide was applied, suggesting less insect damage under intercropping.

Furthermore, our result revealed that intercropping in late season significantly reduced the

population of bruchids, pod sucking bugs and thrips but did not reduce the population of

other pests. Similarly, early season intercropping reduced the population of aphids. Baker and

Norman (1975) stated that cowpea is better protected in intercrop than sole crop and that the

yield of cowpea in lately planted sole crop was virtually zero if not protected. Mensah (1997)

reported a low population density of post-flowering pests (Maruca and pod sucking bugs) but

a higher population density of thrips in a crop mixture consisting of one row of sorghum

alternating with two rows of cowpea. Although, he observed a reduction in pests and damage

to cowpea in mixture compared with monoculture, he recommended one to two insecticide

applications to maximize cowpea yields. Agboh–Noameshie et al. (1997) studied pest

population on cowpea intercropped with cassava and found that the micro-environment

created by intercrop reduced the populations of flower thrips and pod-sucking bugs but

increased those of the pod borer.

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The grain yield results presented in this study were much higher than those reported by

Ajeigbe et al. (2005) and Singh and Ajeigbe (2002) working in northern guinea savanna of

Nigeria. This apparent disparity was explained by Rachie (1985) who reported that the actual

farm yields of cowpea obtainable in the drier region of West African are much lower (25-100

Kg/ha) compared to yield obtainable in longer season environments. Although, the

population of pests on cowpea may increase progressively with continuous cultivation of

cowpea in Southeastern Nigeria and yields affected, yet the potentials of commercializing

cowpea production in the region is quite high. Intercropping was found to reduce the

population of aphids, bruchids, pod sucking bugs and thrips by 40 percent, 9 percent, 8

percent, 100 percent respectively. On the other hand, intercropping increased the infestation

of Maruca by 9 percent while cropping system did not affect Ootheca. This result is in

conformity with work conducted in Nigeria (Perfect et al., 1978) and in Tanzania (Karel et

al., 1982) that the populations of leaf hoppers, thrips and bruchids were reduced in cowpea–

maize intercrops. Ampong-Nyarko et al. (1994) obtained 32 percent reduction in thrips by

intercropping. Similar trend were reported for flower thrips by Matteson (1982), and Ezueh

and Taylor (1983). Further more, in supporting our result, mixed cropping was found to

reduce cowpea aphids Bottenberg et al. (1997), thrips (Ezueh and Taylor, 1984; Kyamanywa

and Ampofo 1988; Alghali 1993a; Kyamanywa et al., 1993), and pod-sucking bugs (Alghali

1993a). Damage by Maruca is not reduced by cropping system (Taylor, 1978; Perfect et al.

1978; IITA, 1982). These finding on Maruca is in conformity with our result but contrary to

Seshu Reddy and Masyanga (1987) who claimed to have got a 46 percent reduction of

Maruca in a 1:3 sorghum-cowpea intercrop. However, for pod sucking bugs the reports have

been mixed. Perfect et al. (1978) and Matteson (1982) indicated a decrease in numbers of pod

sucking bugs in cowpea–maize intercrop in South West Nigeria which is in line with our

findings; whereas at the other locations in same region increased number of pod sucking bugs

were reported in cowpea–maize and cowpea–sorghum intercrops (Ochieng, 1977; Perfect et

al., 1978; Matteson, 1982).

5.5 Cropping system X season X spray regime X genotype interactions

Our result revealed that maximum grain yield was obtained in sole cropping with two sprays

on IT97K-499-35, three sprays on IT97K-568-18, three sprays on IT98K-131-2, two sprays

on IT93K-452-1, and three sprays on local variety. In order words early maturing genotypes

(IT97K-499-35 and IT93K-452-1) requires two sprays while medium maturing genotypes

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(IT97K-568-18 and IT98K-131-2) and late maturing genotype (local variety) requires three

sprays to produce highest grain yield under sole cropping system. The local variety responded

well with insecticides spray and this observation was reflected by its high grain yield in late

season with three sprays. Meanwhile, in intercropping system maximum grain yield was

obtained in IT97K-499-35 with two sprays, IT97K-568-18 with two sprays, IT98K-131-2

with two sprays, IT93K-452–1 with two sprays and local variety with three sprays. Generally,

the genotypes tested whether early, medium or late maturing required two sprays to produce

highest grain yield components under intercropping while in sole cropping early maturing

genotypes required two sprays while medium and late maturing genotypes required three

sprays. Moreover, medium to late maturing genotypes required higher spray frequency under

sole cropping in late season. This result is supported by Singh et al (1984) who reported that

intercropping required lower spray frequency irrespective of the maturity category of the

genotypes while sole cropping required higher spray frequency especially in late season.

The population of aphids, Maruca and Ootheca was higher in early season than late season.

Consequently, one way of managing these pests is to plant in late season. This result showed

that late season planting reduced the population of aphids, Maruca and Ootheca by 122

percent, 183 percent, and 40 percent respectively, while early season sowing reduced the

population levels of bruchids by 195 percent, pod sucking bugs by 47 percent and thrips by

104 percent. Parh (1993) found that insect pests of flower buds, flowers, and pods are the

most limiting in terms of cowpea grain yield in Cameroon. Furthermore, pre-flowering pests

required two sprays in late season. But since the damage done by some of the pre-flowering

pests does not lead to serious economic loss, it is advisable that both early and medium

maturing genotypes be sown in early season.

The genotypes IT93K-452-1, IT98K-131-2 and IT90K-277-2 were most tolerant to the pests

sampled while local variety and IT97K-556-4 was the most susceptible. The rest genotypes

behaved unpredictably across the environments. Local variety responded best with three

sprays in late season. Resource poor farmers who cannot afford agro-chemicals can grow

IT93K-452-1, IT98K-131-2 or IT90K-277-2 profitably without insecticides application,

while if they must plant local variety because of its large seed size and higher fodder

production, it must be planted in late season either in sole or intercropping system but must

be sprayed three times. Our recommendations are similar to that of Kamara et al. (2010), that

early and medium maturing cowpea varieties should be sown in Mid-August and sprayed

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twice while late maturing indeterminate varieties should be planted in late season and sprayed

thrice. Ajeigbe et al. (2005); Kamara et al. (2009) also found, IT 98K-131-2 and IT 90K-277-

2 to express significant resistance to most pests, with substantial grain yield attributes. The

results also supported the findings of Raheja and Apeji (1980) and Parh (1993), working in

Northern Nigeria and Cameroon, respectively, that two insecticides sprays (each at the onset

of flowering and podding) could significantly increase seed yield. In Uganda, Karungi et al.

(2000a) recommended three sprays once each at bud initiation, flowering, and podding for

effective control of insect pests in cowpea.

5.6 Cropping system X season interaction on maize productivity

Our result showed that the intercropping combination of ACR9931/IT98K-131-2 had positive

effects on maize as it resulted in overall higher yield and yield components of maize, while

ACR9931/local combination depressed components of maize yields. Our finding is in

contrast with Adetiloye (1980) who reported that a cowpea cultivar with a climbing growth

habit performed satisfactorily in association with maize. However, our finding is supported

by Wien and Nangju (1976) who reported that local cowpea variety with climbing growth

habit caused increased lodging in maize and lowered maize yields. Moreover, N‟tare and

Williams (1992), Terao et al. (1997) and N‟tare (1989, 1990) found that late maturing

cowpea is more competitive and reduced cereal yields. Meanwhile, Wien and Nangju (1976)

further confirmed our finding that medium maturing cowpea cultivars with indeterminate

growth habit is better adapted to cropping system involving maize. Interestly, the cowpea

variety, IT 98K-131-2 that gave the best combination with maize is both medium maturing

and indeterminate. Although N‟tare (1990) found early maturing erect cowpea lines to have

less negative effects on millet in semi-arid zone of Niger, we found improved medium

maturing, indeterminate cowpea variety with long peduncle length more suitable for

intercropping system in moist savanna of Southeastern Nigeria.

This study showed that maize performed better in intercropping than sole cropping, in early

than late season and in 2009 than 2010. These findings agree with Oluranti et al. (2008) that

early season favours maize performance. Furthermore, rainfall amount and distribution was

better in 2009 than 2010 (Table 3), and this could have been responsible for better

performance of maize in 2009. This result showed that maize was very sensitive to

environmentally induced stress and seasonal changes. This result also revealed that the yield

reduction in maize from cropping system, season and year effects was caused by reduction in

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cob length, cob weight, number of cobs per plot, seed weight, 100 seed weight and harvest

index and not by number of plant stands. This revealed that maize productivity is more

influenced by these traits. Any management practices that enhance the performance of these

traits will invariably increase grain yield in maize. Nakono et al. (2002) noted that to improve

the selection efficiency of crop species, it is necessary to identify secondary traits associated

with grain yield or biomass productivity that can be measured easily in field-based

evaluation. Terao et al. (1997) reported that local spreading type of cowpea had a lower yield

potential in intercropping with maize because of its low harvest index and inadequate root

system (compared to the shoot system). In a resource rich environment such as Ako, cowpea

should be sown in late season along with appropriate spray regime and system as

recommended in this study.

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CHAPTER SIX

CONCLUSION AND RECOMMENDATIONS

The population dynamics of major cowpea insect pests, improved cowpea genotypes,

cropping systems and spray regime effects were studied in a non-traditional cowpea growing

region of Nigeria (southeastern region) over a period of four years. In each year, early and

late season sowing were adopted across the three different locations used for the study. There

was significant genotype X season interaction, genotype X cropping system interaction,

genotype X spray regime interaction and genotype X season X cropping system X spray

regime interactions. These obvious interactions indicated that conclusions based solely on

genotypes means would not be reliable, since genotypes responded differently to changes

within the environments, and thus justifying the need for multi-environment trials. Significant

differences were observed among genotypes for growth, reproductive, grain yield and insect

damage components. Individual genotypes varied in their response to sowing dates, cropping

systems and spray regimes. The result of this study has implication for designing appropriate

strategies for selecting suitable cowpea cultivars along with associated production packages.

In developing cowpea genotypes that are suitable for sole and intercropping, emphasis should

be given to traits that confer adaptability to the cropping systems (number of branches,

peduncle length, number of internodes, growth duration, etc) and offer other alternative uses

such as weed control, maintenance of soil fertility and health, sustainability of the system as

well as niche opportunities. Similarly, high grain yield and resistance to pests are not a

guarantee that farmers will adopt new varieties of cowpea. Other benefits are considered

important by farmers and consumers such as seed size, seed quality and fodder yield.

Management practices that will promote cowpea value addition and productivity were

highlighted. There may be need to investigate the profitability or otherwise as well as the

environmental impact assessment of the spray schedule recommended in this study.

Improved genotypes produced higher yields in early season than late season whether

protected or not protected with insecticides. But in a resource rich environment like Ako

location and in a year with extended rains, late season planting could perform better than

early season planting with 2-3 sprays. Non-application of insecticide in late season resulted in

zero grain yields for most genotypes. This is because the populations of all the yield limiting

pests are highest in late season. Sole cropping produced higher cowpea grain yield than

200

intercropping. But it favored more pest population and more attacks by pests and therefore

required higher frequency of agro-chemical treatment. When productivity of cowpea and

maize are considered, intercropping was more productive than sole cropping, but resulted in

lower cowpea productivity due to shading effects and competition for other environmental

variables. Intercropping can be viewed as a justifiable component of IPM as it reduced pest

levels and yield losses. Since cowpea crop is attacked by multiple pests, reduction in the

population density of any single pests by intercropping will contribute to the success of the

programme, and provide substantial benefit to the system. Maruca, thrips, pod sucking bugs

and bruchids were the most important cowpea pests in Southeastern region while Ootheca

and aphids are the minor pests. These pests are present all the year round by surviving on

alternate hosts. The population of pests builds up in subsequent years and cause more

damages. The importance of seasonal changes relative to pest complex, spray regime,

genotypes, cropping system and their implication for integrated pest management

underscores the relevance of this study. Medium and late maturing genotypes are better

adapted to late season while early maturing genotypes could be sown profitably in both

seasons. Minimum use of agro-chemical by targeting crop growth stages when pest pressure

is highest is the best approach in managing most of the pests studied.

Plant population was higher in early season than late season; therefore farmers should adopt

early sowing when soil temperature is high. The non-photosensitive genotypes flowered and

produced components of grain yields as expected in both seasons, while local variety failed to

flower and produced no yield in first season owing to its sensitivity to photoperiod. Pod

length, number of seed per pod, number of branches and number of internodes were least

influenced by seasonal changes this is because of their high heritability. Cowpea biomass was

more expressed in early than late season. Large seed size was significantly higher in local,

IT97K-277-2, IT97K-556-4 and IT93K-452-1 genotypes in all environments, while IT84S-

2246-4 and IT90K-82-2 consistently expressed small seed size. Evidence of yield

compensation was found in IT98K-131-2 since it produced the highest grain yield although it

had poor plant population. The genotypes IT90K-227-2, IT97K-556-4 and local variety

exhibited dual-purpose characteristics in both seasons having produced high yield of both

grain and fodder, while the rest of the genotypes were purely grain type. All the dual-purpose

cowpeas are determinate and long duration.

201

Short growth duration and high mean yield would make IT93K-452-1 the best grain cowpea

as it combined these qualities with tolerance to most post flowering pests. Its high grain yield

was expressed through higher number of pods per plant and seed weight. IT93K-452-1

produced reasonable grain yield in late season even without chemical spray. IT93K-452-1

will be most preferable in areas with unpredictable and short rains and among resource poor

farmers who cannot afford agro-chemicals. All the improved varieties possessed higher

peduncle length than local variety with their pods direction above the canopies and this pod

orientation could be one of the reasons why though the genotypes podded and matured during

the peak rains their seeds were healthy and clean. Genotype IT98K-131-2 was an outstanding

medium maturing genotype combining superior grain yield with tolerance to pre-and-post

flowering pests. Similarly, its superior performance cut across seasons, locations and years

showing that IT98K-131-2 had broad adaptation to these environments. It also produced good

grain yield in late season without chemical spray. The genotypes IT90K-277-2, IT98K-556-4,

local and IT93K-452-1 produced consistently higher and more stable 100 seed weight across

all the environments. Genotype IT97K-556-4 harboured the highest population of the pests

sampled in both seasons, indicating that the genotype was susceptible to these pests.

Improved cowpea cultivars recorded higher grain yield than the local check at all the

environments. Bruchids, Maruca, pod sucking bugs and thrips were more abundant in late

season than early season while the population of aphids and Ootheca was prevalent in early

season than late season. Planting cowpea early in the season reduced bruchids by 195 percent.

We also found that brown seeded cowpeas consistently harboured lower infestation of

bruchids than white seeded types. Three sprays reduced bruchid population by 240 percent.

Early planting coupled with lower frequency of insecticide application resulted in higher

grain yield. Application of insecticide significantly increased all the yield and yield

components in late season. The yield increases implied that the major yield limiting pest was

effectively controlled by the insecticide used in this study.

Cowpea farmers in Nigeria often apply a minimum of five insecticide sprays per season to

control insect pests on cowpea. However, this study has revealed that applying insecticide at

the critical growth stages when insect pests does greater damages would reduce the number

of spray regime to a maximum of three per season. Consequently, the percentage reduction in

insect population when sprayed three times as against zero spray averaged across genotypes,

seasons and years for aphids, bruchids, Maruca, Ootheca, pod sucking bugs and thrips were

202

121 percent, 240 percent, 174 percent, 45 percent, 38 percent and 270 percent respectively.

Intercropping was found to depress cowpea biomass production (by reducing most growth

components) in both early and late season while it increased the harvest index. Intercropping

in early season reduced dry fodder yield by 22 percent while in late season it reduced fodder

yield by 41 percent. Intercropping did not significantly reduce number of branches,

internodes number, number of leaves, number of nodules, plant population, and root length.

Maize was found to reduce cowpea peduncle length in both early and late season which

varied with genotypes. This trait could be useful in determining cowpea cultivars that are

adapted to intercropping. Local variety produced significantly higher fresh and dry fodder

yield above others in both systems and seasons. Cowpea grain yield in intercropping were

generally higher than yields from the sole crop when no insecticide was applied, indicating

less insect damage under intercropping. Late season intercropping significantly reduced the

population of bruchids, pod sucking bugs and thrips but did not reduce the population of

other pests. Early season intercropping however, crashed the population of aphids.

Two sprays increased grain yield in IT97K-499-35 by 41 percent, three sprays increased

grain yield in IT97K-568-18 by 30 percent, three sprays increased grain yield in IT98K-131-2

by 48 percent, two sprays increased grain yield in IT93K-452-1 by 48 percent, while three

sprays increased grain yield in local by 80 percent. Local variety responded well to

insecticides spray and this observation was reflected in its high grain yield in late season with

three sprays. Meanwhile, in intercropping, grain yield increased by 106 percent in IT97K-

499-35 with two sprays, 20 percent in IT97K-568-18 with two sprays, 33 percent in IT98K-

131-2 with two sprays, 67 percent in IT93K-452–1 with two sprays and 37 percent in local

with three sprays. Generally, the genotypes tested required two sprays to produce highest

grain yield under intercropping while in sole cropping early maturing genotypes required two

sprays, medium maturing genotype required three sprays. This result confirmed further that

intercropping required lower spray frequency whether the genotype is early or medium

maturing while sole cropping on the other hand required higher spray frequency. The

population of aphids, Maruca and Ootheca was higher in early season than late season. One

way of managing these pests is to plant in late season. Our result showed that late season

planting reduced the population of aphids, Maruca and Ootheca by 122 percent, 183 percent,

and 40 percent respectively, while early season sowing reduced the population levels of

bruchids by 195 percent, pod sucking bugs by 47 percent and thrips by 104 percent.

203

Intercropping combination of ACR9931/IT 98K-131-2 had positive effects on maize which

resulted in overall higher yield and yield components of maize, while ACR9931/Local

combination depressed components of maize yields. We found improved medium maturing,

indeterminate cowpea cultivar with longer peduncle most suitable for intercropping system in

Southeastern Nigeria. Maize performed better in intercropping than sole cropping, early than

late season and in 2009 than 2010. The yield reduction in maize from cropping system,

season and year effects was caused by reduction in cob length, cob weight, number of cobs

per plot, seed weight, 100 seed weight and harvest index and not by number of plant stands.

This revealed that maize productivity is more influenced by these traits. Any management

practices that maximize the performance of these traits will invariably increase maize

productivity.

Based on the above findings, we recommend the following:

1. Resource poor farmers who cannot afford agro-chemicals should plant either of these

resistant genotypes: IT98K-131-2 or IT93K-452-1;

2. In areas with limited and erratic rainfall, farmers should plant early maturing and high

yielding variety such as IT93K-452-1;

3. Livestock farmers requiring cowpea fodder can plant any of these dual-purpose

varieties: IT90K-277-2 or IT97K-556- 4;

4. Cowpea seed growers should plant any of these grain type cowpeas: IT93K-452-1 or

IT97K-131-2 to optimize seed yield;

5. Breeders wishing to screen breeding lines for insect pests under natural field

conditions can use IT97K-556-4 as susceptible check;

6. IT98K-131-2, IT93K-452-1 and IT90K-277-2 are resistant to most of the pests

sampled and can be used as donor parents for transferring resistant genes to elite

materials;

7. Large seeded genotypes such as local variety, IT90K-277-2, IT97K-556-4 and IT93K-

452-1 can be used as source parents to improve seed size in cowpeas;

8. Scientists wishing to screen for thrips in southeastern Nigeria should carry it out in

late season in Ishiagu;

9. Brown seeded genotypes especially IT97K-131-2 should be used as donor parent in

developing bruchid resistant genotypes while white seeded genotype especially

IT98K-205-8 and IT93K-452-1 should be used as susceptible check in bruchid

screening experiment;

204

10. Cowpea farmers should adopt early season sowing when soil temperature is high to

achieve optimum plant population and higher productivity;

11. IT97K-131-2 and IT93K-452-1 were the best grain yielders. IT97K-131-2 should be

planted in late season under sole cropping while IT93K-452-1 can be sown in both

seasons and systems;

12. Maize should be sown under inter cropping and in early season for maximum

productivity; and

13. Medium maturing cowpea genotypes with long peduncle, indeterminate in growth

habit but not climbing type is recommended for use in intercropping involving maize

in the region.

Furthermore, the following integrated pest management packages are recommended to

effectively deal with the insect pests sampled in this study:

1. Aphids: Plant in late season under intercropping system and spray two times;

2. Bruchids: Plant recommended brown seeded genotypes in early season under

intercropping, with three sprays;

3. Maruca: Plant in either early or late season in sole cropping and spray three times;

4. Ootheca: Plant in late season either sole or intercropping with two sprays;

5. Pod sucking bugs: Plant in early season, adopt intercropping practice and spray three

times; and

6. Thrips: Plant in early season in intercropping and spray three times.

These recommendations showed that to efficiently manage the critical yield limiting post-

flowering pests of cowpea in southeastern Nigeria, farmers should adopt early season sowing,

plant under intercropping and spray three times, while pre-flowering pests can be managed by

sowing in late season, under intercropping with two insecticide applications.

205

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Appendix 1: The analysis of variance showing degree of freedom (DF) and mean squares on the growth component of 10 cowpea genotypes

during the early and late seasons in Ishiagu, 2007

Source DF DFWT(g) FFWT(g) NBRANCH NHILL

INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

Replication 2 55363 1058083 6.0333 1.458 11.575 119.31 119.28 58.56 0.27 33.63 1991.5

Insect Prot (IP) 1 6307ns 884083ns 0.4083ns 0.533ns 0.075ns 4.03ns 14.70ns 291.41*** 1.88ns 6.3ns 120ns

Error 2 63930 333583 0.8333 6.358 2.275 38.51 8.17 17.91 37.36 13.65 105.6

Genotype (G) 9 98195*** 2923046*** 2.5009*** 7.944*** 283.842*** 2368.98*** 433.26*** 312.54*** 175.98*** 28.09ns 37057***

IP x G 9 86176ns 1981120ns 0.6120ns 2.237ns 3.649ns 155.57ns 41.87*** 24.54ns 30.70ns 41.75*** 1370***

Error 36 95666 1890000 1.2204 2.205 5.823 107.37 20.29 21.75 44.51 24.63 893.5

Season (S) 1 1917741*** 22620083*** 0.6750ns 0.3ns 336.675*** 218.70*** 187.5*** 238.01*** 874.8*** 8.8ns 15368***

IP x S 1 71541*** 5852083*** 0.0750ns 6.533*** 3.675ns 2.70ns 53.33ns 1.01ns 7.01ns 31.52*** 2083.3***

G x S 9 164035*** 2823417*** 1.6194*** 1.633ns 22.138*** 57.39ns 44.15ns 93.25*** 226.01*** 7.12ns 1802.6***

IP x G x S 9 27854ns 746528*** 0.7231ns 2.015*** 5.360*** 103.46*** 40.98ns 11.1ns 25.56*** 18.15ns 333.5ns

Error 40 20314 326583 0.8417 1.358 4.269 46.17 41.1 24.18 16.22 15.88 448.4

*** = Significant at P<0.01; ns = Not Significant


NLEAF = Number of leaves; NNODULE=Number of nodules; NSTAND=Number of stand; PEDLT = Peduncle length; RTLENGTH=Root length;

VINELTH=Vine length

239

Appendix 2: The analysis of variance showing degree of freedom (DF) and mean squares on the reproductive and grain yield components of 10

cowpea genotypes during the early and late seasons in Ishiagu, 2007




per hectare; THRESH percent = Threshing percentage; HI = Harvest Index

Source DF BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(kg)

SEED

WT (kg)

GYLD/HA

(kg)

THRESH

(%)

HI

(%) Replication 2 21.233 161.9 96.03 7.922 29.91 0.4 0.276 4735 839 9324 13.82 717.8

Insect Prot (IP) 1 37.408*** 1555.2*** 203.41*** 1257.121*** 429.47*** 102.675*** 19.602*** 923551*** 179336*** 1992018*** 12470.95*** 7127***

Error 2 3.033 145.4 13.43 4.857 0.61 0.7 0.336 11411 5523 61365 69.43 114.3

Genotype (G) 9 342.786*** 342.3*** 50.92*** 111.171*** 157.67*** 108.397*** 170.441*** 74229*** 19675*** 218608*** 934.49*** 1715.9***

IP x G 9 10.779ns 152ns 27.80ns 4.176ns 47.82ns 10.582ns 4.51*** 36192ns 7661ns 85125ns 77.2ns 271.3ns

Error 36 11.180 186.2 22.74 4.409 47.26 7.309 2.827 26377 6864 76266 202.11 291

Season (S) 1 110.208*** 1840.8*** 1.41ns 818.496*** 134.41*** 407.008*** 27.17*** 889241*** 249031*** 2767005*** 10660.35*** 32693.6***

IP x S 1 8.008ns 2133.6*** 147.41*** 1341.345*** 134.41*** 114.075*** 18.33*** 119852*** 30350*** 337221*** 12978.37*** 1059.7***

G x S 9 1432.245*** 4034.4*** 441.76*** 58.959*** 28.33ns 13.694*** 9.247*** 27166*** 7621*** 84673*** 897.66*** 891.4***

IP x G x S 9 5.416ns 223.6ns 16.39ns 2.612ns 18.45ns 4.501ns 1.894ns 10118ns 2844ns 31599ns 185.42*** 190.4ns

Error 40 4.908 178.0 22.76 4.275 23.09 7.017 2.697 7624 2176 24182 85.18 288.8

240

Appendix 3: The analysis of variance showing degree of freedom (DF) and mean squares on the insect damage of 10 cowpea genotypes during

the early and late seasons in Ishiagu, 2007

Source DF APHIDSC BRUCHIDCT MARUCT OOTHESC PSBSC THRIPCT

Replication 2 0.1333 155.33 37.975 0.1333 1.4083 75.82

Insect Prot (IP) 1 18.4083*** 200.21*** 90.133*** 8.0083*** 12.675*** 66.01***

Error 2 0.0333 47.36 16.758 0.4333 0.325 4.76

Genotype (G) 9 0.2491ns 314.92*** 3.263ns 1.4824*** 0.2231ns 36.45ns

IP x G 9 0.2787ns 43.26ns 3.948ns 0.4898ns 0.2676ns 10.27ns

Error 36 0.25 81.18 3.7 0.3389 0.1537 28.95

Season (S) 1 20.008*** 20.01ns 53.333*** 1.0083*** 37.4083*** 9030.68***

IP x S 1 18.4083*** 249.41*** 67.5*** 0.6750*** 12.675*** 7.01ns

G x S 9 0.2491ns 63.77ns 3.556ns 0.5639*** 0.2231ns 38.71ns

IP x G x S 9 0.2787ns 83.50*** 4.056ns 0.2306ns 0.2676ns 9.93ns

Error 40 0.2333 45.92 6.417 0.3167 0.225 31.7



THRIPCT = Thrips Count

241


during the early and late seasons in Ishiagu, 2008


INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

Replication 2 254632 1540013 1.433 6.553 36.30 251.3 14.43 6.41 84.03 20.66 12514

Insect Prot (IP) 1 249341*** 3286830** 0.008ns 1.008*** 3.01ns 396ns 261.07*** 14.70ns 46.88ns 0.00ns 195ns

Error 2 60466 593280 0.633 0.133 29.03 172.3 16.72 12.47 114.10 25.68 1835

Genotype (G) 9 1234139*** 19113526*** 3.916*** 146.305ns 72.01*** 4259.2*** 91.95*** 787*** 647.88*** 141.23*** 12486***

IP x G 9 112339*** 960015*** 3.434*** 4.490*** 14.79*** 1575.4*** 16.91ns 13.83ns 20.43ns 97.87*** 3077***

Error 36 51568 646110 1.006 3.528 8.92 284.8 23.58 18.9 41.68 21.56 1762

Season (S) 1 1744841*** 50258963*** 2.408ns 106.408*** 3.67ns 9.6ns 2075.07*** 1190.70*** 273.01*** 17.63ns 13547***

IP x S 1 13441ns 1094430ns 8.008*** 3.675ns 10.21ns 997.6*** 161.01*** 3.33ns 15.41ns 86.70*** 4600***

G x S 9 247304*** 3078297*** 3.538*** 4.927ns 10.53ns 315.5ns 33.21ns 21.20ns 118.53*** 27.13ns 2910ns

IP x G x S 9 98941*** 872874ns 0.953ns 4.934ns 19.54ns 810.7*** 52.73*** 12.65ns 77.33*** 30.46*** 2047ns

Error 40 63499 864497 1.292 5.392 13.38 552.7 25.77 25.41 29.18 20.41 2271


DFWT = Dry fodder weight; FFWT = Fresh fodder weight: NBRANCH = Number of branches; NHILL = Number of hills; INTERNODE = Number of internode; NLEAF = Number of leaves; NNODULE=Number of nodules; NSTAND=Number of stand; PEDLT = Peduncle length; RTLENGTH=Root length; VINELTH=Vine length

242


cowpea genotypes during the early and late seasons in Ishiagu, 2008

Source DF BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(kg)

SEED WT

(kg)

GYLD/HA

(kg)

THRESH

(%)

HI

(%) Replication 2 54.475 24.70 15.21 2.01 114.70 2.858 0.627 23730 15041 167123 156.1 356

Insect Prot (IP) 1 0.533ns 255.21*** 104.53*** 213.33*** 407.01ns 12.033*** 6.302ns 749236*** 418310*** 4647882*** 5872*** 24028***

Error 2 154.408 55.83 2.16 10.66 164.93 2.608 3.602 25224 13399 148879 10 9

Genotype (G) 9 573.293*** 1542.26*** 111.99*** 151.07*** 370.36*** 65.089*** 129.168*** 264177*** 133782*** 1486464*** 3314*** 8754***

IP x G 9 37.607ns 326.75*** 41.14*** 40.46*** 37.93*** 7.756ns 9.177*** 18337*** 10055*** 111720*** 278.8*** 1153***

Error 36 138.192 62.95 16.55 11.36 23.94 7.094 3.860 9627 5681 63127 190.3 598

Season (S) 1 1.633ns 7.01ns 26.13ns 30*** 476.01*** 2.700ns 17.252*** 1444969*** 1063518*** 11816848*** 5371.5*** 1672ns

IP x S 1 70.533*** 126.08*** 86.70*** 163.33*** 243.68*** 0.300ns 0.919ns 911763*** 397095*** 4412159*** 4227*** 22719***

G x S 9 285.633*** 1307.43*** 218.52*** 57.69*** 35.75ns 24.756*** 31.072*** 63758*** 40363*** 448480*** 896.3*** 669ns

IP x G x S 9 358.422*** 344.80*** 41.13*** 43.98*** 52.71*** 13.022*** 14.405*** 27810*** 12605*** 140060*** 213.4*** 1224ns

Error 40 8.433 66.53 19.63 10.39 29.44 4.225 3.573 13205 7008 77863 144.5 1475





243


the early and late seasons in Ishiagu, 2008


Replication 2 1.3583 66.13 4.225 0.2333 0.0333 81.26

Insect Prot (IP) 1 7.5*** 249.47*** 91.875*** 1.2000ns 21.6750*** 1184.41***

Error 2 0.9750 59.23 0.025 0.7000 0.30000 45.21

Genotype (G) 9 0.5333*** 121.09*** 4.064ns 0.6259ns 1.0380*** 25.43***

IP x G 9 0.4630*** 15.76ns 9.153*** 0.3111ns 0.7491ns 20.69ns

Error 36 0.2870 36.06 4.847 0.5685 0.6019 32.45

Season (S) 1 0.5333ns 190.01*** 88.408*** 1.6333*** 60.2083*** 180.08***

IP x S 1 0.8333*** 0.21ns 14.008*** 2.1333*** 7.0083*** 304.01***

G x S 9 0.3111ns 30.32ns 1.871ns 0.4481ns 1.0602*** 43.91***

IP x G x S 9 0.4630ns 18.19ns 8.990*** 0.2074ns 2.0824*** 40.58***

Error 40 0.3917 31.89 4.108 0.4583 0.6750 22.28



THRIPCT = Thrips Count. 1=No sign of damage; 2=25 percent damaged; 3=50 percent damaged; 4=75 percent damaged; 5=100 percent damaged

244


during the early seasons in Ishiagu, 2007 and 2008


INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

Replication 2 409013 1897583 5.625 2.158 37.98 212.7 107.26 63.96 38.45 12.02 14329

Insect Prot (IP) 1 9541ns 126750ns 1.008ns 1.408ns 0.008ns 36.3ns 78.41ns 100.83*** 0.67ns 9.63ns 2ns

Error 2 26863 252250 3.908 2.808 2.308 147 52.41 9.36 58.58 16.51 166

Genotype (G) 9 851358*** 13804824*** 4.797*** 51.797*** 185.353*** 3984*** 201.76*** 661.14*** 904.49*** 39.89*** 18398***

IP x G 9 21002ns 215639ns 0.694ns 0.760ns 2.805ns 26.5ns 55.13ns 11.94ns 38.47ns 13.65ns 595ns

Error 36 53736 844176 1.276 2.298 8.818 511.4 43.59 16.49 37.95 22.43 1692

Year (Y) 1 7286541*** 94874083*** 0.208ns 122.008*** 16.875*** 2707.5*** 2.41ns 5018.13*** 2861.63*** 108.30*** 34714***

IP x Y 1 81641ns 1260750*** 3.675*** 4.408ns 2.408ns 32ns 399.68*** 64.53*** 4.41ns 38.53*** 3050ns

G x Y 9 229243*** 2325935*** 0.782ns 12.582*** 61.338*** 283,1ns 185.95*** 41.17*** 31.23ns 20.28ns 9719***

IP x G x Y 9 89324*** 1374824*** 1.805*** 4.982*** 5.279ns 298.2ns 70.25*** 20.24ns 19.55ns 38.18*** 1317ns

Error 40 53889 683583 1.108 3.050 8.367 315.7 34.02 14.89 28.50 14.85 1909


DFWT = Dry fodder weight; FFWT = Fresh fodder weight: NBRANCH = Number of branches; NHILL = Number of hills; INTERNODE = Number of internode; NLEAF = Number

of leaves; NNODULE=Number of nodules; NSTAND=Number of stand; PEDLT = Peduncle length; RTLENGTH=Root length; VINELTH=Vine length

245


cowpea genotypes during the early seasons in Ishiagu, 2007 and 2008

Source DF BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(kg)

SEED WT

(kg)

GYLD/HA

(kg)

THRESH (%) HI (%)

Replication 2 34.30 19.808 84.03 2.03 33.77 3.108 2.48 40 97 1078 14.77 4085.6

Insect Prot (IP) 1 81.68ns 1.01ns 2.41*** 0.11ns 46.88ns 3.008ns 0.72ns 69048*** 17673*** 196371*** 21.92ns 788.2ns

Error 2 59.20 0.81 0.26 1.9 24.77 3.358 2.84 5156 1032 11465 14.55 426.0

Genotype (G) 9 2272.11*** 5683.686*** 514.80*** 320.41*** 355.88*** 174.075*** 265.95*** 305701*** 129503*** 1438921*** 4747.78*** 7353.9***

IP x G 9 45.23ns 3.656ns 5.72ns 0.48ns 8.54ns 3.045ns 3.15*** 16891ns 6430ns 71450ns 89.72ns 1326.5***

Error 36 50.05 5.716 9.08 0.39 39.19 4.363 1.03 21172 6986 77618 61.40 847.5

Year (Y) 1 185.01*** 102.675*** 99.00*** 15.99*** 913.01*** 9.075ns 15.62*** 1866435*** 1934997*** 21499928*** 14550.08*** 3792.8***

IP x Y 1 0.01ns 33.075*** 0.41ns 2.24*** 5.21ns 5.208ns 0.49ns 123938*** 13532*** 150355*** 48.04ns 566.1ns

G x Y 9 86.79*** 3.064ns 12.88*** 2.25*** 19.49ns 2.556ns 1.3ns 38395*** 31406*** 348958*** 274.08*** 1080.0ns

IP x G x Y 9 68.08ns 10.686*** 4.13ns 0.64*** 42.43ns 7.764ns 2.03ns 31598*** 10213*** 113478*** 69.27*** 871.6ns

Error 40 49.57 5.125 8.5 0.43 31.65 5.383 2.1 14699 5019 55764 46.54 853.0





246


the early seasons in Ishiagu, 2007 and 2008


Replication 2 0.3 18.63 0.6750 0.058 1.075 21.41

Insect Prot (IP) 1 37.41*** 533.41*** 12.6750*** 2.7*** 1.01ns 126.08***

Error 2 0.43 63.03 0.175 0.325 0.758 18.33

Genotype (G) 9 0.38ns 223.59*** 0.445ns 0.685*** 0.138ns 23.25***

IP x G 9 0.45ns 78.78*** 0.2676ns 0.237ns 0.286ns 15.46***

Error 36 0.49 50.03 0.5176 0.247 0.204 9.93

Year (Y) 1 7*** 156.41*** 3.01*** 4.8*** 3.675*** 1222.41***

IP x Y 1 6.08*** 46.88ns 5.208*** 4.03*** 1*** 33.08***

G x Y 9 0.68ns 38.78ns 0.97*** 0.707ns 0.138ns 20.65***

IP x G x Y 9 0.67ns 44.21ns 0.394ns 0.2ns 0.286ns 17.20***

Error 40 0.51 37.26 0.525 0.525 0.275 10.01




247


during the late seasons in Ishiagu in 2007 and 2008


INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

Replication 2 71208 2588563 0.908 9.508 10.525 159.5 14.36 104.76 125.78 26.26 918.1

Insect Prot (IP) 1 231441ns 9667363*** 2.408ns 0.300ns 1.875ns 572.0*** 12.03ns 118.01*** 54.67ns 0.35ns 554.7ns

Error 2 72641 138363 1.808 8.575 6.475 99.9 13.76 3.61 20.43 24.01 1189.3

Genotype (G) 9 294256*** 6345608*** 3.801*** 58.467*** 104.264*** 2525.1*** 142.80*** 395.41*** 124.22*** 49.59*** 19905.7***

IP x G 9 143756*** 1983623*** 1.075ns 2.893ns 14.968*** 1134.8*** 9.79ns 13.16ns 43.01*** 68.86*** 1581.2***

Error 36 27295 547037 0.766 3.699 8.741 75.1 15.10 24.37 27.23 16.84 889.3

Year (Y) 1 41ns 4431363*** 8.008*** 480.00*** 421.875*** 4060.0*** 918.53*** 14586.08*** 54.68*** 308.80*** 37594.8***

IP x Y 1 18007ns 62563ns 1.408ns 5.635*** 12.675ns 760*** 0.00ns 27.08ns 11.41ns 76.00*** 3392***

G x Y 9 368837*** 5461919*** 2.194*** 37.963*** 37.560*** 208.9*** 72.07*** 116.26*** 108.45*** 93.81*** 6233.2***

IP x G x Y 9 71248ns 986452ns 2.149*** 5.041*** 20.286*** 1205.6*** 17.31ns 16.78ns 53.00*** 67.54*** 3334***

Error 40 81241 1470313 1.025 3.033 8.833 109 18.05 30.10 35.43 28.41 868.2



248


cowpea genotypes during the late seasons in Ishiagu in 2007 and 2008

Source DF BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(kg)

SEED

WT (kg)

GYLD/HA

(kg)

THRESH

(%)

HI

(%)

Replication 2 0.26 108.6 21.77 7.30 10.56 12.025 3.522 39384 23196 257733 239.1 1898.4

Insect Prot (IP) 1 4.80ns 3182.7*** 529.2*** 2473.39*** 1159.41*** 140.833*** 37.074*** 2445564*** 878547*** 9761616*** 33716.5*** 44671.2***

Error 2 45.33 301.2 18.03 29.42 71.81 15.258 5.817 1126 1349 14993 51.1 53.9

Genotype (G) 9 98.36*** 657.7*** 186.61*** 35.66*** 178.93*** 28.781*** 67.915*** 62495*** 26579*** 295324*** 527.1*** 2198.2***

IP x G 9 159.95*** 338.2*** 39.76*** 56.67*** 88.33*** 9.278ns 19.408*** 24528*** 7855*** 87275*** 317.8ns 424.8ns

Error 36 31.48 225.4 26.46 17.52 35.13 7.882 7.825 8682 4806 53394 307.5 364.1

Year (Y) 1 3.33ns 1254.5*** 36.30ns 736.07*** 4048.41*** 353.633*** 8.374*** 1225676*** 737540*** 8194874*** 22674.9*** 40604.3***

IP x Y 1 30.00ns 853.3*** 12.03ns 499.39*** 3.01ns 80.033*** 6.864*** 65852*** 115334*** 1281537*** 1761.9*** 8907.8***

G x Y 9 176.70*** 881.9*** 108.86*** 20.56*** 37.82*** 6.522ns 4.764*** 22738*** 13952*** 155022*** 493.5*** 1398.8***

IP x G x Y 9 138.96*** 694.6*** 76.85*** 33.45*** 17.60ns 15.774*** 5.398*** 19440*** 8667*** 96303*** 278.1*** 215.9ns

Error 40 29.54 253.5 37.41 11.55 26.53 6.442 1.722 12634 5300 58894 200.8 357.4





249


the late seasons in Ishiagu, 2007 and 2008


Replication 2 0.1750 31.41 31.67 0.1750 4.2583 101.16

Insect Prot (IP) 1 0.8333*** 46.88*** 240.83*** 5.2083*** 52.0083*** 980.41***

Error 2 0.0583 76.58 21.01 0.8583 1.6083 27.86

Genotype (G) 9 0.1444ns 202.91*** 7.43*** 1.1898*** 0.9639*** 54.49ns

IP x G 9 0.1852*** 19.62ns 20.69*** 0.4120ns 2.1194*** 26.00ns

Error 36 0.1259 68.77 5.87 0.5259 0.4056 62.57

Year (Y) 1 1.2000*** 33.07ns 0.13ns 6.0750*** 12.6750*** 2176.01***

IP x Y 1 0.8333*** 72.08ns 4.80ns 0.0750ns 0.0083ns 421.87***

G x Y 9 0.1444ns 64.82ns 3.91ns 0.5380ns 1.3046*** 46.12***

IP x G x Y 9 0.1852*** 18.11ns 4.80ns 0.3898ns 0.6750*** 22.80ns

Error 40 0.1250 46.07 12.22 0.3750 0.4750 35.88




250


during the early and late seasons in Mgbakwu, 2007


INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

Replication 2 109503 826352 6.4000 1.433 6.308 17.1 45.08 80.56 59.19 6.58 874.9

Insect Prot (IP) 1 385333*** 14504653*** 1.0083*** 0.208ns 3.333ns 4.4ns 11.41*** 0.03ns 15.84*** 83.67*** 7339.9***

Error 2 27043 1003276 0.033 1.033 2.058 24 20.41 7.36 0.74 0.66 1295

Genotype (G) 9 253295*** 8321392*** 1.6194*** 12.112*** 156.015*** 764.2*** 387.48*** 634.24*** 227.40*** 68.58*** 25024.7***

IP x G 9 88674*** 3668803*** 0.3602ns 1.060ns 6.944ns 58.7ns 97.67*** 23.07ns 17.50ns 54.79*** 1286.7***

Error 36 39718 665775 1.0037 2.900 5.035 95.3 31.21 34.33 35.80 26.66 774.2

Season (S) 1 363000*** 16192053*** 18.4083*** 190.008*** 40.833*** 541.9*** 696.01*** 2100.03*** 1168.13*** 316.23*** 28783.5***

IP x S 1 122880ns 4136653*** 0.0750ns 0.075ns 0.000ns 0.2ns 0.67ns 3.33ns 4.56ns 123.63*** 383.4ns

G x S 9 80489ns 1141326ns 1.6491*** 8.231*** 16.370*** 140.2ns 225.82*** 100.48*** 78.14*** 18.19ns 2158.5***

IP x G x S 9 50132ns 1553581ns 0.7972ns 1.594ns 9.167*** 65.0ns 31.71ns 24.15ns 27.30ns 17.60ns 2083.6***

Error 40 94673 1252796 0.6750 3.250 3.283 117.7 27.65 34.42 25.48 28.33 683.6



NLEAF = Number of leaves; NNODULE=Number of nodules; NSTAND=Number of stand; PEDLT = Peduncle length; RTLENGTH=Root length;

VINELTH=Vine length

251


cowpea genotypes during the early and late seasons in Mgbakwu, 2007

Source DF BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(kg)

SEED WT

(kg)

GYLD/HA

(kg)

THRESH

(%)

HI

(%)

Replication 2 18.433 1598.6 288.1 78.20 259.41 47.008 3.025 22068 14360 159555 1541.6 616.4

Insect Prot (IP) 1 3.333ns 2270.7ns 197.63ns 465.31*** 874.80*** 63.075ns 33.602ns 929262*** 295656*** 3285058*** 4744.9*** 11187.0***

Error 2 3.733 1869.3 237.73 68.16 164.32 38.125 10.033 4041 4055 45055 604.9 1116.5

Genotype (G) 9 705.115*** 488.4*** 81.2*** 121.86*** 353.13*** 84.190*** 65.699*** 137237*** 58631*** 651457*** 2138.3*** 7320.4***

IP x G 9 3.148*** 157.3*** 33.21*** 28.38*** 17.24ns 2.538ns 10.755*** 20799*** 8159*** 90652*** 267*** 624.1ns

Error 36 1.954 104.6 20.15 9.96 40.50 4.067 3.661 10782 4864 54044 163.1 653.5

Season (S) 1 580.800*** 403.3ns 45.63*** 145.42*** 346.80*** 165.675*** 26.602*** 1683625*** 794855*** 8831702*** 7711.9*** 88873.1***

IP x S 1 12.033*** 2412*** 218.7*** 528.78*** 104.53*** 88.408*** 48.769*** 164361*** 31720*** 352444*** 3925.7*** 5348.8***

G x S 9 71.356*** 3638.2*** 468.36***

77.98*** 74.95*** 14.249*** 6.625*** 45301*** 22098*** 245533*** 830.7*** 3907.5***

IP x G x S 9 2.478ns 152.8ns 29.01ns 28.59*** 24.31ns 20.723*** 27.597*** 38749*** 9786*** 108729*** 254.6ns 990.9***

Error 40 3.867 271.5 30.71

16.55 21.63 5.517 3.594 9553 4719 52436 296.5 720.6





252


the early and late seasons in Mgbakwu, 2007


Replication 2 0.5583 27.26 6.700 2.2583 26.36 0.508

Insect Prot (IP) 1 42.0083*** 49.41ns 185.008*** 5.6333*** 1248.08*** 330.008***

Error 2 0.5583 67.26 3.633 0.4083 24.52 7.908

Genotype (G) 9 0.3787*** 153.06*** 5.968*** 1.3556*** 6.02ns 18.008***

IP x G 9 0.3787*** 67.06ns 2.397ns 0.2815ns 6.76ns 3.860***

Error 36 0.2343 67.66 6.519 0.4074 14.98 3.579

Season (S) 1 8.0083*** 648.68*** 249.408*** 1.2000*** 1505.21*** 550.408***

IP x S 1 8.0083*** 54.67ns 91.875*** 4.800*** 1248.08*** 95.408***

G x S 9 0.1935ns 53.29ns 4.982ns 0.6259*** 9.15ns 12.260***

IP x G x S 9 0.1935ns 73.88ns 1.856ns 0.2630ns 6.76ns 2.631***

Error 40 0.8000 60.32 5.217 0.3500 16.03 3.392




253


during the early and late seasons in Mgbakwu, 2008


INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

Replication 2 660455 1844162 0.53 0.93 2.28 335.5 25.07 44.1 22.44 8.67 36

Insect Prot (IP) 1 64450ns 159287ns 0.03ns 0.01ns 4.03ns 17.6ns 344.42*** 0.03ns 4.8ns 73.63*** 3017ns

Error 2 344452 1979843 0.208 7.91 22.71 596.2 1.01 53.63 24.62 4.63 5390

Genotype (G) 9 1197169*** 4378634*** 7.964*** 13.15*** 91.64*** 3739.3*** 225.04*** 373.05*** 131.41*** 57.69*** 13557***

IP x G 9 135997*** 409016*** 1.418*** 2.45ns 10.83ns 414.4ns 53.35ns 18.13ns 36.64ns 50.67*** 1094ns

Error 36 92846 317499 1.139 2.51 8.06 468.1 83.40 22.95 31.36 43.7 1220

Season (S) 1 10316535*** 59561248*** 0.30ns 35.21*** 963.33*** 5148.3*** 3688.53*** 367.5*** 1625.09*** 154.13*** 119152***

IP x S 1 44815ns 76407ns 2.7*** 0.01ns 43.2*** 120ns 74.73*** 0.03ns 97.92*** 6.53ns 32ns

G x S 9 915997*** 3257887*** 1.305ns 10.06*** 36.2*** 1779.3*** 77.12*** 143.41*** 56.82*** 59.42ns 6065***

IP x G x S 9 92251ns 252243ns 0.899ns 1.56ns 14.44*** 313.4ns 38.25ns 12.94ns 33.38*** 11.87ns 799ns

Error 40 133430 476183 1.329 2.12 9.77 390.3 69.65 18.71 17.7 81.58 1467



254


cowpea genotypes during the early and late seasons in Mgbakwu, 2008

Source DF BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(kg)

SEED WT

(kg)

GYLD/HA

(kg)

THRESH

(%)

HI

(%)

Replication 2 31.86 19.4 2.8 11.158 36.86 12.17 12.46 125959 67306 747844 275.9 22587

Insect Prot (IP) 1 0.13ns 1280.5ns 1170.41*** 145.2*** 302.42*** 159.85*** 45.26*** 30020ns 16380ns 182000ns 3181.2*** 31464***

Error 2 0.26 414.5 44.63 9.325 1.53 5.5 1.96 14608 6980 77556 163.7 2939

Genotype (G) 9 594.24*** 569.7*** 46.96*** 162.57*** 95.5*** 36.02*** 27.67*** 73183*** 34770*** 386336*** 2883.5*** 13047***

IP x G 9 5.84ns 994.7*** 123.22*** 49.81*** 14.21ns 9.26*** 14.96*** 13465ns 7683ns 85364ns 460*** 4856***

Error 36 10.23 194.3 31.1 4.57 18.99 4.46 5.15 12863 6683 74254 89.2 4178

Season (S) 1 1128.53*** 1116.3*** 11.41ns 34.13*** 1566.02*** 813.8*** 243.39*** 2095106*** 1084521*** 12050204*** 749.7*** 86ns

IP x S 1 16.13*** 177.6ns 29.01ns 158.7*** 0.1ns 0.47ns 48.51*** 6135ns 2746ns 30507ns 2937.5*** 46517***

G x S 9 13.5*** 16.2ns 36.08ns

54.93*** 35.18*** 9.04*** 13.88*** 61366*** 30587*** 339850*** 905.3*** 5023ns

IP x G x S 9 2.58ns 259.1ns 15.49ns 41.2*** 4.67ns 10.24*** 18.44*** 11967ns 6781ns 75339ns 403*** 4943ns

Error 40 10.52 214.6 41.72

5.5 10.35 6.92 4.56 13421 7053 78362 120.9 4827


BLOOM = Days to 50 percent flowering; MATURITY = Days to maturity; PODFILL = Days to Podfilling; 100SWT = 100 Seed weight; NPOD/PLT = Number of pods per plant; NSEED/POD = Number of seeds per pod; PLENGTH = Pod length; PODWT = Pod weight; SEEDWT = Seed weight; GYLD/HA = Grain yield per hectare; THRESH percent = Threshing percentage; HI = Harvest Index

255


the early and late seasons in Mgbakwu, 2008


Replication 2 1.46 101.63 48.01 1.58 0.48 1814.02

Insect Prot (IP) 1 2.41*** 853.33*** 340.03*** 8.01*** 69.01*** 3921.63***

Error 2 0.41 175.27 35.41 0.41 1.11 490.91

Genotype (G) 9 3.97*** 208.52*** 4.130*** 0.05ns 0.56*** 293.56***

IP x G 9 0.89*** 129.44*** 2.55ns 0.05ns 0.75*** 62.08ns

Error 36 0.29 30.32 3.52 0.08 0.49 66.74

Season (S) 1 1.01*** 1778.7*** 240.83*** 21.68*** 52.01*** 6249.63***

IP x S 1 1.41*** 172.8*** 213.33*** 8.01*** 1.41*** 740.03***

G x S 9 1.12*** 96.14*** 2.46ns 0.05ns 0.93*** 292.86***

IP x G x S 9 0.22ns 98.95*** 1.78ns 0.05ns 0.37ns 38.66ns

Error 40 0.78 43.87 8.74 0.18 0.63 77.54




256


during the early seasons in Mgbakwu for 2007 and 2008


INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

Replication 2 1888908 9539552 6.1750 1.4333ns 1.858 771.2 116.06 16.83 231.37 129.92 550

Insect Prot (IP) 1 135341ns 1500803ns 1.2000ns 0.0083ns 11.408ns 45.6ns 151.88*** 0.68ns 22.79ns 246.53*** 5973ns

Error 2 860366 7239076 1.8250 2.1333 6.458 596.3 12.18 41.28 23.02 22.06 6166

Genotype (G) 9 1120109*** 6624524*** 6.0917*** 4.7046*** 219.371*** 4214.5*** 594.32*** 398.86*** 221.08*** 117.62*** 34384***

IP x G 9 172758ns 1628676ns 0.9824ns 1.7120*** 8.816ns 389.3ns 83.06ns 21.90ns 45.11*** 29.55ns 1823ns

Error 36 156132 1141960 0.9815 0.8111 9.010 429.7 116.85 19.09 23.68 42.14 1744

Year (Y) 1 2388541*** 434403ns 28.0333*** 14.0083*** 35.208*** 145.2ns 2075.01*** 648.68*** 6.21ns 1159.41*** 26749***

IP x Y 1 9541ns 302003ns 0.1333ns 0.0083ns 27.075*** 70.5ns 221.41*** 0.67ns 8.59ns 20.83ns 782ns

G x Y 9 1189013*** 6311472*** 0.7324ns 3.4528*** 8.208ns 1468.2*** 252.49*** 121.86*** 52.22*** 17.89ns 2134ns

IP x G x Y 9 110550*** 1291876*** 0.1565ns 1.3417*** 20.779*** 366.0ns 90.89ns 6.34ns 24.07*** 51.83ns 2165ns

Error 40 74833 439279 0.6083 0.9083 9.758 473.6 68.99 14.98 15.33 38.63 1586



257


cowpea genotypes during the early seasons in Mgbakwu for 2007 and 2008

Source DF BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT (g) NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(kg)

SEED WT

(kg)

GYLD/HA

(kg)

THRESH

(%)

HI

(%)

Replication 2 106.81 0.7 82.52 0.0896 126.03 8.444 6.470 117279 69422 771359 50.14 4188

Insect Prot (IP) 1 1.87ns 110.2ns 112.03ns 0.9720ns 331.67*** 27.552*** 0.507ns 106768*** 48670*** 540780*** 17.77ns 8ns

Error 2 1.43 349.3 33.51 0.3183 35.33 5.315 0.827 18699 11732 130356 89.32 3347

Genotype (G) 9 916.50*** 2499.3*** 202.37*** 352.2120*** 309.17*** 87.009*** 35.120*** 269992*** 124775*** 1386383*** 5412.57*** 15339***

IP x G 9 5.38ns 64.1ns 17.33ns 1.0742ns 36.48ns 8.172*** 3.233ns 46820*** 18679*** 207549*** 24.65ns 3512***

Error 36 6.97 206.4 33.97 0.9078 32.79 3.907 2.997 25578 11989 133211 26.60 1220

Year (Y) 1 44.41*** 902*** 4.03ns 1.8253*** 561.17*** 63.802*** 5.985ns 171249*** 11850ns 131672*** 1883.72*** 3397***

IP x Y 1 9.08ns 143ns 17.63ns 0.1920ns 1.30ns 45.019*** 0.225ns 53738*** 21033*** 233700*** 4.05ns 1258ns

G x Y 9 27.17*** 858*** 169.70***

1.4298*** 26.05ns 7.598*** 5.700*** 22400*** 12668ns 140755ns 130.70*** 2694***

IP x G x Y 9 1.57ns 62.9ns 18.26ns 0.5572*** 14.89ns 3.898ns 1.752ns 21505*** 8299ns 92210ns 9.37ns 1270ns

Error 40 10.23 205.5 32.49

0.3557 30.55 3.346 3.720 14591 8774 97486 44.98 1790



258


the early seasons in Mgbakwu for 2007 and 2008


Replication 2 2.5083 12.43 0.175 5.0083 0.4333 419.11

Insect Prot (IP) 1 36.3500*** 232.41*** 15.408*** 26.1333*** 12.6750*** 480***

Error 2 0.4750 0.43 0.658 0.6083 0.7000 15.63

Genotype (G) 9 0.6704ns 68.29*** 0.545*** 0.1630ns??? 1.3972*** 30.17***

IP x G 9 0.3000ns 33.02*** 0.242ns 0.2074ns 0.3231ns 15.39ns

Error 36 0.8435 12.57 0.574 0.1880 0.2796 19.34

Year (Y) 1 2.1333*** 6.07ns 18.408*** 0.8333*** 15.4083*** 1984.53***

IP x Y 1 10.8000*** 0.67ns 0.008ns 0.3000ns 12.6750*** 182.53***

G x Y 9 0.2444ns 11.20ns 1.205ns 0.2778ns 0.1306ns 39.33ns

IP x G x Y 9 0.4667ns 8.69ns 0.397ns 0.2630ns 0.3231ns 15.66ns

Error 40 0.3917 12.94 1.042 0.2500 0.3083 40.67




259


during the late seasons in Mgbakwu for combined over 2007 and 2008


INTER

NODE


(cm)

RTLENGTH

(cm)

VINELTH

(cm)

Replication 2 88718 821222 1.108 0.258 2.575 265.44 3.19 13.11 13.11 118.77 24.7

Insect Prot (IP) 1 256780*** 8895497*** 0.075ns 0.075ns 10.208ns 21.67ns 8.16*** 0.68ns 8.91ns 4.11ns 4009***

Error 2 39198 121623 1.825 0.675 12.308 45.04 0.95 7.52 3.04 24.97 100.2

Genotype (G) 9 103682*** 2437463*** 3.519*** 21.575ns 60.149*** 613.66*** 62.80*** 475.58*** 167.87*** 41.39ns 7442.7***

IP x G 9 47226*** 1581178*** 1.186ns 2.575*** 5.319*** 32.15ns 28.85ns 30.51ns 27.56ns 24.45ns 824.3***

Error 36 21502 278542 1.106 3.439 3.034 51.99 11.04 43.49 37.91 45.86 513.5

Year (Y) 1 5148012*** 153775408*** 81.675*** 16.875*** 350.208*** 6885.68*** 125.46*** 1.41ns 5183.73*** 1553.76*** 114973.1***

IP x Y 1 215816*** 8178697*** 2.408*** 0.208ns 1.875ns 4.41ns 49.79*** 1.41ns 82.83*** 15.99ns 7.7ns

G x Y 9 34146ns 1725781*** 2.194*** 13.819*** 12.505*** 126.57*** 5.86ns 254.87*** 52.60*** 26.96ns 2838.2***

IP x G x Y 9 36520ns 1381915*** 1.149ns 1.042ns 6.468ns 64.07ns 18.18ns 19.54ns 18.08ns 29.12ns 451ns

Error 40 25921 292802 1.258 5.842 4.742 72.69 14.32 38.72 24.69 41.65 365.9



260


cowpea genotypes during the late seasons in Mgbakwu for combined over 2007 and 2008

Source DF BLOOM

(days)

MATURITY

(days)

PODFILL

(days)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(kg)

SEED WT

(kg)

GYLD/HA

(kg)

THRESH

(%)

HI

(%)

Replication 2 0.925 1320.6 107.51 140.92 90.13 56.727 14.656 31771 13252 147250 2505.3 13352

Insect Prot (IP) 1 0.675ns 5320.0*** 559.01*** 1197.64*** 826.87*** 235.200*** 175.208*** 656898*** 203503*** 2261144*** 14657.9*** 81785***

Error 2 3.475 1713.5 198.26 121.12 65.20 12.944 9.409 9192 4071 45238 1459.4 6606

Genotype (G) 9 424.212*** 204.5*** 77.83*** 48.21*** 139.97*** 36.250*** 68.669*** 14613*** 5415*** 60162*** 766.3*** 6694***

IP x G 9 2.990ns 469.3*** 61.21*** 133.45*** 3.58ns 18.723*** 63.142*** 8912*** 3239*** 35984*** 956.5*** 3880ns

Error 36 3.654 100.3 19.62 17.59 17.78 8.021 4.781 3215 1153 12810 352.1 3388

Year (Y) 1 8.008*** 279.1ns 29.01ns 370.66*** 1992.67*** 559.008*** 166.145*** 317786*** 66934*** 743714*** 10781.0*** 62051***

IP x Y 1 20.008*** 567.7*** 27.07ns 99.19*** 122.01*** 4.033ns 0.208ns 312375*** 73295*** 814385*** 109.6ns 11465***

G x Y 9 16.323*** 1150.7*** 182.69***

15.49ns 83.56*** 12.643*** 4.375ns 10082*** 3229*** 35876*** 448.3*** 4571ns

IP x G x Y 9 4.101*** 967.4*** 104.13*** 12.89ns 5.49ns 11.964*** 3.625ns 7743*** 2191*** 24341*** 394.1*** 2751ns

Error 40 2.642 299.4 45.40

13.34 16.73 6.994 5.165 3236 1274 14151 182.8 3948



261


the late seasons in Mgbakwu, combined over 2007 and 2008


Replication 2 1.8083 350.76 30.23 0.4083 26.76 684.98

Insect Prot (IP) 1 4.0333ns 440.83ns 790.53*** 0.0083ns 1606.01*** 3466.87***

Error 2 2.0083 417.31 25.43 0.1083 21.26 437.42

Genotype (G) 9 2.7630*** 364.68*** 11.11*** 0.8157*** 9.28ns 338.11***

IP x G 9 0.4407ns 246.69*** 4.76ns 0.0824ns 5.56ns 35.17ns

Error 36 0.5380 87.17 7.95 0.2491 15.18 43.14

Year (Y) 1 0.1333ns 202.80*** 16.13*** 23.4083*** 765.07*** 10028.41***

IP x Y 1 2.7000*** 456.30*** 24.30ns 0.0083ns 935.21*** 957.67***

G x Y 9 1.9852*** 66.84ns 4.69ns 0.8157*** 5.85ns 209.08***

IP x G x Y 9 0.4778*** 80.93ns 3.19ns 0.0824ns 8.43ns 41.01ns

Error 40 0.2250 69.17 16.14 0.2500 16.52 85.12




262


evaluated during the early season in Ako, 2009

Source DF DFWT(g)

NBRANCH NHILL

INTER

NODE


(CM)

RTLENGTH

(CM)

VINELTH

(CM)

Replication 2 459083 0.0083 3.733 11.81 5420 117.23 23.86 1867 33.08 27807

Cropping System (CS) 1 2241333*** 3.6750*** 2.408ns 8.53ns 13251*** 91.88ns 26.13ns 2679*** 38.53*** 5454***

Error 2 319083 0.9750 11.633 19.81 3391 97.50 66.81 1722 52.51 3621

Number of Spray (NS) 3 66667ns 0.9417ns 5.542*** 55.02*** 917ns 3.16ns 60.47*** 2387*** 25.90*** 4746ns

CS x NS 3 47556ns 0.9639ns 3.431ns 28.89*** 7666*** 5.54ns 28.64*** 1941*** 39.73*** 14180***

Error 12 72194 1.4694 2.161 19.73 2715 47.61 15.69 2246 39.36 8096

Genotype (G) 4 2902500*** 5.8958*** 149.321*** 288.77*** 131987*** 88.35*** 618.85*** 15525*** 20.20*** 35896***

CS x G 4 320500 1.1958*** 5.596*** 17.10ns 8438*** 77.77*** 11.86*** 2398*** 47.43*** 12433***

NS x G 12 72778ns 0.5458ns 3.326ns 29.15*** 2110ns 51.53*** 17.50*** 1759*** 10.66ns 4634ns

CS x NS x G 12 75889ns 0.9569ns 4.090ns 43.09*** 7151*** 35.49*** 16.76*** 1967*** 13.77ns 12421***

Error 64 109125 0.7250 3.052 17.37 2825 24.11 12.88 2069 24.96 7968


DFWT = Dry fodder weight; FFWT = Fresh fodder weight: NBRANCH = Number of branches; NHILL = Number of hills; INTERNODE = Number of internodes; NLEAF = Number of leaves; NNODULE=Number of nodules; NSTAND=Number of stand; PEDLT = Peduncle length; RTLENGTH=Root length; VINELTH=Vine length

263

Appendix 26: The analysis of variance showing degree of freedom (DF) and mean squares on the reproductive and grain components of 5 cowpea

genotypes evaluated during the early season in Ako, 2009

SOURCE DF BLOOM

(days)

MATURITY

(days)

PODFILL

(DAYS)

100SWT (g) NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(kg)

SEED WT

(kg)

GYLD/HA

(kg)

THRESH

(%)

HI

(%)

Replication 2 0.308 5.7000 7.258 0.625 251.11 4.908 188.8 20400 13550 144964 232.4 126

Cropping System (CS) 1 0.033ns 67.500*** 64.533*** 0.300ns 249.41*** 32.033*** 261.1*** 488ns 2562ns 25911*** 172.2*** 79.4ns

Error 2 0.058 0.400 0.658 13.075 14.66ns 3.008 133.7 43486 27474 297947 13.5 347.7

Number of Spray (NS) 3 2.856ns 0.956ns 1.100ns 7.022*** 8.21ns 7.089*** 149.3*** 91917*** 70093*** 791339*** 831.6*** 813.8***

CS x NS 3 2.322ns 2.633ns 1.467ns 4.033ns 108.03*** 5.344ns 188.4*** 7277ns 5794*** 65784*** 118.3*** 7.5ns

Error 12 2.006 1.728 4.758 4.294 72.43 10.392 178.6 13844 7148 80855 97.6 169.9

Genotype (G) 4 10649.229*** 23394.104*** 2569.854*** 970.717*** 3962.26*** 603.292*** 1537.3*** 1358347*** 723780*** 8067228*** 22475.4*** 9767.7***

CS x G 4 5.096*** 6.521*** 6.388*** 3.467ns 171.47*** 5.533*** 181.3*** 50703*** 23951*** 266682*** 68.0ns 241.6***

NS x G 12 1.446ns 1.087ns 2.510ns 3.522ns 30.34ns 5.547*** 171.7*** 30223*** 22330*** 244906*** 120.8*** 298.1***

CS x NS x G 12 1.746ns 0.793ns 2.154ns 7.783*** 41.76ns 1.400ns 167.6*** 11164*** 4408ns 48553ns 46.4ns 12.3ns

Error 64 2.425 1.308 3.579 3.569 55.42 5.596 172.6 13336 7445 81488ns 127.1 122.7





264

Appendix 27: The analysis of variance showing degree of freedom (DF) and mean squares on the insect damage of 5 cowpea genotypes evaluated

during the early season in Ako, 2009

SOURCE DF APHIDSC BRUCHIDCT MARUCT OOTHESC PSBSC THRIPCT

Replication 2 1.4083 2632.5 0.313 1.5083 0.05833

113.11

Cropping System (CS) 1 0.6750ns

83.3ns 1.722ns 0.4083*** 0.03333***

91.88***

Error 2 0.6750ns

310.8 6.638 0.5583 0.00833

7.53

Number of Spray (NS) 3 1.4083ns

1505.6*** 3.914*** 9.0306*** 0.06667***

698.10***

CS x NS 3 0.6750ns

190.0ns 1.778*** 1.2306*** 0.01111ns

7.01ns

Error 12 1.0417

389.4 1.432 1.3222 0.02222

34.46

Genotype (G) 4 0.11167ns

26638.8*** 17.493*** 1.6042*** 2.93750***

350.64***

CS x G 4 0.2167ns 302.1ns 1.024ns

0.3875*** 0.09583*** 143.77***

NS x G 12 0.1167ns 838.1*** 1.365ns

0.2319*** 0.05972*** 63.72***

CS x NS x G 12 0.2167ns 117.1ns 0.705ns

0.4042*** 0.01806*** 60.57***

Error 64

0.1667 440.2 1.163 0.1875

0.04583 26.51




265


during the late season in Ako, 2009


INTER

NODE


(CM)

RTLENGTH

(CM)

VINELTH

(CM)

Replication 2 422111 4425698 4.275 4.008 55.60 923 54.5 36.63 37.06 237.7 4173

Cropping System (CS) 1 5722954*** 47523477*** 58.800*** 6.533ns

49.41ns 10868*** 86.7ns 31.01ns 476.01*** 17.6ns 48844***

Error 2 259766 5007446 1.825 15.808

64.63 1982 120.5 18.03 95.16 240.0 9234

Number of Spray (NS) 3 273503*** 7021720*** 0.556ns 10.900***

38.96*** 2208ns 248.2*** 34.39*** 145.28*** 20.7ns 8200***

CS x NS 3 182582*** 1350825*** 3.444ns 11.978*** 26.30ns

1921ns 11.9ns 12.70ns 196.25 62.6ns 949ns

Error 12 52844 324280 2.983 4.431 21.17

1545 91.5 9.43 36.03 50.1 5046

Genotype (G) 4 436634*** 6585430*** 1.083ns 772.571***

26.58ns 10409*** 508.2*** 2556.07*** 2790.48 152.9ns 11453***

CS x G 4 561532*** 6143413*** 6.925ns

12.096*** 108.99*** 477ns 375.7*** 20.95*** 351.09*** 46.3ns 4160ns

NS x G 12 83660*** 1741563*** 3.833ns

3.532ns 22.41ns 1267ns 98.9ns 14.03ns 40.69ns 54.8ns 3362ns

CS x NS x G 12 67171ns 1105099*** 3.931ns 4.735*** 29.94ns 2887ns 172.6*** 24.94*** 94.50ns 24.8ns 4064ns

Error 64

58627 800224 5.062 3.415 36.23 2263 115.9 11.43 94.35 112.3 6507


DFWT = Dry fodder weight; FFWT = Fresh fodder weight: NBRANCH = Number of branches; NHILL = Number of hills; INTERNODE = Number of internodes; NLEAF = Number of leaves; NNODULE=Number of nodules; NSTAND=Number of stand; PEDLT = Peduncle length; RTLENGTH=Root length; VINELTH=Vine length

266

Appendix 29: The analysis of variance showing degree of freedom (DF) and mean squares on the reproductive and grain components of 5 cowpea

genotypes during the late season in Ako, 2009

SOURCE DF BLOOM

(days)

MATURIT

Y (days)

PODFILL

(DAYS)

100SWT

(g)

NPOD/

PLT

NSEED/

POD

PODLT

(cm)

PODWT

(kg)

SEED WT

(kg)

GYLD/HA

(kg)

THRESH

(%)

HI

(%)

Replication 2 190.2 714.0 168.06 132.52 785.2 41.425 62.358 188757 92277 1025299 1493.2 1028.5

Cropping System (CS) 1 2340.8ns 3040.1*** 45.63ns 572.03*** 4320.0ns 75.208ns 297.675*** 939870ns 417956ns 4643947*** 257.2ns 0.9ns

Error 2 759.0 800.1 15.81 86.61 1228.7 21.258 31.825 272788 122455 1360607 399.2 1267.4

Number of Spray (NS) 3 63.9ns 78.8ns 3.04ns 7.33ns 32.2ns 5.808ns 15.297*** 170715*** 105180*** 1168661*** 181.3ns 6692.2***

CS x NS 3 53.5ns 82.1ns 4.28ns 12.92ns 486,9*** 2.786ns 2.097ns 13329ns 12076ns 134180ns 232.6ns 378.1ns

Error 12 62.7 117.7 16.41 16.34 94.6 4.997 5.314 18761 16831 187007 200.3 395.4

Genotype (G) 4 675.7*** 317.1*** 1373.97*** 57.07*** 2113.0*** 69.863*** 84.479*** 845285*** 517814*** 5753474*** 6640.9*** 11684***

CS x G 4 1894.6*** 2786.5*** 127.24*** 135.55*** 1026.1*** 43.229*** 33.529*** 75821*** 59265*** 658502*** 475.9ns 1470.4***

NS x G 12 39.7ns 96.9ns 16.45ns 11.55ns 165.6ns 4.857ns 3.207ns 29800ns 22061ns 245121ns 332.3ns 893.7***

CS x NS x G 12 34.8ns 81.3ns 14.97ns 7.55ns 125.5ns 4.779ns 4.201ns 18838ns 12904ns 143381ns 185.0ns 406.4ns

Error 64 123.5 243.9 28.71 29.10 367.2 7.406 7.560 27872 17581 195343 342.3 525.9





267


the late season in Ako, 2009


Replication 2 0.13333 1141 3.175 0.13333 0.13333

75.9

Cropping System (CS) 1 0.53333***

4441*** 3.675*** 0.53333*** 0.53333***

23324.4***

Error 2 0.13333

736 0.775 0.13333 0.13333

526.5

Number of Spray (NS) 3 0.02222ns

2590*** 20.608*** 0.02222ns 0.02222ns

2207.5***

CS x NS 3 0.02222ns

356ns 1.186ns 0.02222ns 0.02222ns

1658.7***

Error 12 0.02222

1034 1.697 0.02222 0.02222

138.0

Genotype (G) 4 0.38750***

13485*** 2.946*** 0.38750*** 0.38750***

278.8***

CS x G 4 0.38750*** 2030*** 3.488***

0.38750*** 0.38750*** 421.6***

NS x G 12 0.01528ns 633ns 1.990***

0.01528ns 0.01528ns 271.9***

CS x NS x G 12 0.01528ns 674ns 2.054***

0.01528ns 0.01528ns 218.0***

Error 64

0.03958 1021 1.340 0.03958

0.03958 147.0




268

Appendix 31: The analysis of variance showing degree of freedom (DF) and mean squares on the growth component of 5 cowpea genotypes, combined over early and late season in Ako, 2009

Source DF DFWT(g) NBRANCH NHILL

INTER

NODE


(CM)

RTLENGTH

(CM)

VINELTH

(CM)

Replication 2 861112 1.954 7.237 56.35 2389 152.33 44.03 1196 106.75 26479

Cropping System (CS) 1 7563630*** 16.538*** 0.504NS 8.44NS 59NS 0.04NS 0.10NS 2707NS 2.02NS 43470***

Error 2 13913 0.162 6.704 72.01 464 0.61 21.58 1272 245.03 4090

Number of Spray (NS) 3 43067NS 0.360NS 10.482*** 31.30NS 2508NS 138.29NS 46.44*** 1151NS 15.78NS 6177NS

CS x NS 3 120818*** 3.626NS 10.726*** 37.26*** 7050*** 14.85NS 38.59*** 1594NS 29.08NS 9928NS

Error 12 42101 2.964 1.904 20.39 1642 95.12 7.68 1042 49.10 6327

Genotype (G) 4 908492*** 3.156NS 678.042NS 209.96*** 105272*** 420.59*** 2318.38*** 15134*** 129.97*** 37392***

CS x G 4 333215*** 3.506NS 10.858NS 45.45*** 2609NS 293.29*** 22.19*** 979NS 44.80NS 6809NS

NS x G 12 32848NS 2.037NS 2.725NS 24.22NS 2184NS 62.15NS 13.85NS 944NS 47.34NS 4507NS

CS x NS x G 12 89403NS 3.470NS 3.608NS 45.98NS 6943*** 107.52NS 21.69*** 833NS 16.32NS 10076NS

Error 64 74124 2.842 3.634 32.38 2639 80.43 12.54 1111 71.62 8271

Season (S) 1 22734108*** 37.604*** 519.204*** 47.70*** 43605*** 1219.50*** 1368.04*** 1804*** 91.27NS 351594***

CS x S 1 400657*** 45.937*** 8.438*** 49.50*** 24060*** 178.54*** 57.04*** 448NS 54.15NS 10827***

NS X S 3 297103*** 1.137NS 5.960*** 62.68*** 617NS 113.12*** 48.42*** 1382NS 30.78NS 6769NS

G x S 4 2430642*** 3.823NS 243.850*** 105.38*** 37124*** 175.92*** 856.54*** 3181*** 43.09NS 9957***

CS x NS x S 3 109320*** 0.782NS 4.682NS 17.93NS 2537NS 2.57NS 2.75NS 543NS 73.26NS 5201NS

CS x G x S 4 548817*** 4.615*** 6.833*** 80.64*** 6306*** 160.16*** 10.62NS 1770*** 48.95NS 9783***

NS x G x S 12 123589 2.342NS 4.133NS 27.35NS 1192NS 88.28NS 17.68NS 855NS 18.11NS 3489NS

CS x NS x G x S 12 53658 1.417NS 5.217*** 27.05NS 3096NS 100.53*** 20.01*** 1229NS 22.27NS 6409NS

Error 80 101968 2.704 3.500 20.65 2573 60.18 14.02 1059 63.88 6343

*** = Significant at P<0.01; ns = Not Significant DFWT = Dry fodder weight; FFWT = Fresh fodder weight: NBRANCH = Number of branches; NHILL = Number of hills; INTERNODE = Number of internodes; NLEAF = Number of leaves; NNODULE=Number of nodules; NSTAND=Number of stand; PEDLT = Peduncle length; RTLENGTH=Root length; VINELTH=Vine length

269

Appendix 32: The analysis of variance showing degree of freedom (DF) and mean squares on the reproductive and grain components of 5 cowpea genotypes, combined over early and late season in Ako, 2009 Source DF

BLOOM (days)

MATURITY (days)

PODFILL (DAYS)

100SWT (g)

NPOD/ PLT

NSEED/ POD

PODLT (cm)

PODWT (kg)

SEED WT (kg)

GYLD/HA (kg)

THRESH

(%) HI

(%)

Replication 2 95.26 417.4 116.89 66.95 962.2 10.454 73.91 165556 83077 949667 1447.6 0.09128

Cropping System (CS) 1 1179.27NS 2006.8*** 109.35*** 273.07*** 1246.7NS 4.538NS 558.15*** 491596NS 237303*** 2681815*** 425.2NS 0.00485NS

Error 2 385.30 384.3 8.21 16.22NS 660.1 9.688 98.26 76005 34539 387641 133.2 0.04492

Number of Spray (NS) 3 26.01NS 39.4NS 2.27NS 14.11NS 33.8NS 4.471NS 92.32NS 249502*** 172016*** 1874960*** 813.6*** 0.58345***

CS x NS 3 22.28NS 40.7NS 4.05NS 13.02 149.3 5.082NS 91.72NS 18552NS 15598NS 173194NS 153.8NS 0.2400NS

Error 12 36.97 60.9 10.56 14.38 98.8 5.610 85.39 14177 12233 134535 155.1 0.03366

Genotype (G) 4 4293.09*** 14442.2*** 3652.81*** 289.32 314.0NS 503.442*** 1138.94*** 1912747*** 1092180*** 12069617*** 26529.3*** 1.62793***

CS x G 4 949.44*** 1294.3*** 56.31*** 89.24*** 550.3*** 34.892*** 70.22NS 9961NS 10502NS 111651NS 223.8NS 0.07129

NS x G 12 20.56NS 46.9NS 8.01NS 8.48NS 98.7NS 6.436NS 85.87NS 35037*** 27964*** 318319*** 257.0NS 0.06705***

CS x NS x G 12 19.02NS 43.5NS 11.65NS 7.66NS 90.7NS 3.853NS 87.80NS 16204NS 9167NS 102923NS 138.7NS 0.02060NS

Error 64 61.86 121.8 17.11 17.61 214.8 5.537 88.48 20724 12968 142666 273.4 0.03577

Season (S) 1 20.42NS 3465.6*** 2954.02*** 375.00*** 7560*** 92.504*** 224.27*** 3191043*** 1801505*** 19893082*** 8572.7*** 7.24509***

CS x S 1 1161.60*** 1100.8*** 0.82NS 299.27*** 3322.7*** 102.704*** 0.60NS 448762*** 182453*** 198843*** 4.2NS 0.00318NS

NS X S 3 40.78NS 40.4NS 1.87NS 0.24NS 6.5NS 8.426NS 72.23NS 13131NS 7276NS 85040NS 199.3NS 0.16715***

G x S 4 7031.82*** 9269*** 291.02 738.47*** 5761.2*** 169.713*** 482.88*** 290885*** 157462*** 1751084*** 2587.0*** 0.51723***

CS x NS x S 3 33.52NS 44.1NS 1.69NS 3.93NS 445.6*** 3.049NS 98.77NS 2055NS 2765NS 26770NS 197.0NS 0.01456NS

CS x G x S 4 950.26*** 1498.1*** 77.32*** 49.78*** 647.3*** 13.871*** 144.65NS 116564*** 72941*** 813532*** 320.1*** 0.09991***

NS x G x S 12 20.56NS 51.1NS 10.96NS 6.59NS 97.2NS 3.968NS 89.08NS 24985NS 15459NS 171709NS 196NS 0.05212***

CS x NS x G x S 12 17.53NS 38.6 5.47NS 7.68NS 76.6NS 2.326NS 84NS 13798NS 8059NS 89012NS 92.7NS 0.02127

Error 80 67.11 125.5 15.40 16.72 192.9 8.700 94.21 26249 14985 164619 187.7 0.03022



270

Appendix 33: The analysis of variance showing degree of freedom (DF) and mean squares on the insect damage of 5 cowpea genotypes evaluated

combined over early and late season in Ako, 2009


Replication 2 0.5542 3135.4 2.617 0.5042 0.07917 182.15

Cropping System (CS) 1 1.2042NS 1653.8NS 4.965NS 0.0042NS 0.15000NS 10244.27***

Error 2 0.5542 926.2 1.991 0.5292 0.08750 268.12

Number of Spray (NS) 3 0.5708NS 171.5NS 18.078*** 4.1153*** 0.07778*** 2451.17***

CS x NS 3 0.4486NS 519.3NS 1.760NS 0.5931NS 0.02778NS 785.21***

Error 12 0.5431 812.5 1.779 0.7000 0.02778 58.57

Genotype (G) 4 0.2083*** 32618.1*** 15.190*** 0.3708*** 2.71458*** 146.64NS

CS x G 4 0.1208NS 996.5NS 2.534*** 0.6708*** 0.05625NS 414.92***

NS x G 12 0.0500NS 490.6NS 2.103*** 0.1292NS 0.05347NS 160.32***

CS x NS x G 12 0.1292*** 299.5NS 1.068NS 0.2181*** 0.01736NS 97.30NS

Error 64 0.0927 769.7 1.344 0.1073 0.04167 101.88

Season (S) 1 1.8375*** 19260.4*** 2.113NS 36.0375*** 0.60000*** 8954.82***

CS x S 1 0.0042NS 2870.4*** 0.233NS 0.9375*** 0.41667*** 13172.02***

NS X S 3 0.8597*** 3923.8*** 6.720*** 4.9375*** 0.01111 454.43***

G x S 4 0.2958NS 7505.2*** 5.906*** 1.6208*** 0.61042*** 482.81***

CS x NS x S 3 0.2486NS 27.1NS 1.081NS 0.6597*** 0.00556NS 880.49***

CS x G x S 4 0.4833*** 1336.0*** 1.992*** 0.1042NS 0.42708*** 150.49***

NS x G x S 12 0.0819NS 981.0*** 1.148NS 0.1181NS 0.02153NS 175.32***

CS x NS x G x S 12 0.1028NS 491.3NS 1.687NS 0.2014NS 0.01597NS 181.28***

Error 80 0.2000 664.2 1.282 0.2250 0.04167 81.20***

*** = Significant at P<0.01; ns = Not Significant APHIDSC = Aphid Score; BRUCHIDCT = Bruchid Count; MARUCT = Maruca Count; OOTHESC = Ootheca Score; PSBSC = Pod Sucking Bug Score; THRIPCT = Thrips Count.

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PRODUCTIVITY OF GRAIN COWPEA (Vigna unguiculata (L.) Walp.) … EZEORAH... · 2015-09-16 · ii productivity of grain cowpea (vigna unguiculata (l.) walp.)as influenced by season,