Citation
Screening Cowpea [Vigna Unguiculata L. Walp] Germplasm for Forage Production and Root-Knot Nematode Resistance (Meloidogyne Spp.)

Material Information

Title:
Screening Cowpea [Vigna Unguiculata L. Walp] Germplasm for Forage Production and Root-Knot Nematode Resistance (Meloidogyne Spp.)
Creator:
Dareus, Rocheteau
Publisher:
University of Florida
Publication Date:
Language:
English

Thesis/Dissertation Information

Degree:
Master's ( M.S.)
Degree Grantor:
University of Florida
Degree Disciplines:
Agronomy
Committee Chair:
Rios,Esteban Fernando
Committee Co-Chair:
Mulvaney,Michael J
Committee Members:
Chase,Carlene Ann
DiGennaro,Peter
Colbert,Raphael Wesly
Graduation Date:
12/13/2019

Subjects

Subjects / Keywords:
thesis

Notes

General Note:
Cowpea [Vigna unguiculata L. WALP] is a legume grown worldwide. In developing countries, cowpea is exploited as a dual-purpose crop for its grain and fodder while it is cultivated as food and cover crop in industrialized countries. However, root-knot nematodes (RKN) (Meloidogyne spp) represent a threat to cowpea production. The UC-Riverside cowpea germplasm collection was characterized in the field for several morphological, phenological and agronomic traits for selection for breeding purpose and they were screened for resistance to Meloidogyne incognita (Mi) and Meloidogyne enterolobii (Me). All the traits measured throughout the research were genetically diverse as assessed by the genotypic variances and PCA analyses. Genotypic variances calculated for agronomic traits in field studies were significant. Besides, the Me screening showed significant genotypic variances and variation among genotypes. Broad sense heritabilities (H2) calculated for the whole germplasm collection, the selected accessions and the Mi screening varied from low to high. Most of the traits that exhibited a high H2 were strongly correlated to each other allowing indirect selection for thoses traits. From the 56 known RKN resistant accessions, 53 effectively showed different levels of resistance to Mi in regard to gall score and reproduction index (RI) while only 12 of them showed resistance to Me confirming the capability of Me to brake resistance in known resistant plant materials. The UC-Riverside germplasm collection has potential to be exploited for breeding purposes.

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Source Institution:
UFRGP
Rights Management:
All applicable rights reserved by the source institution and holding location.
Embargo Date:
12/31/2020

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SCREENING COWPEA [ Vigna unguiculata L. WALP] GERMPLASM FOR FORAGE PRODUCTION AND ROOT KNOT NEMATODE RESISTANCE ( Meloidogyne spp. ) By ROCHETEAU DAREUS A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2019

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© 2019 Rocheteau Dareus

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To my parents, Lionel and Paulia , and my late brother , Jean Ricot

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4 ACKNOWLEDGMENTS First of all, I want to say thank you the almighty God who relentlessly keeps on guiding my paths and fulfilling my life with so many blessings. Without his mercy, I would not be able to do a m I would like to sa y thank you the USAID who funded my graduate studies through a scholarship granted by the AREA project back in Haiti. I would like to express my gratitude to my adviser, Dr. Esteban F. Rios , who accepted to supervi s e my thesis research. Without his help an d support, I would not be able to face all the challenges and earn my degree at the University of Florida. A special thanks to all my committee members: Dr. Carlene A. Chase, Dr. Michael Mulvaney, Dr. Peter DiGennaro, and Dr. Raphael Colbert for their assi stantship anytime I needed their help. My thoughts go to all the labmates at the Forage Breeding and Genetics Lab specially, Yolanda Lopez, Maricela Puluc, Ajaha, Janam, Hermez, Ian, and Kacey Aukema for their help in collecting data for my thesis. A speci al thank you to my friend Beatriz Gouveia Tome for her help analyzing the data. I also want to thank Dr. Dickson and Dr. Maquilan from the Nematology Department of the University of Florida for their help and support. Finally, I especially thank Cassandre Feuill é for her unconditional company , help and support throughout the two years I spent in Gainesville and numerous friends and collabarators I met who contributed to my success.

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5 TABLE OF CONTENT S ACKNOWLEDGMENTS ................................ ................................ ................................ ............... 4 LIST OF TABLES ................................ ................................ ................................ ........................... 7 LIST OF FIGURES ................................ ................................ ................................ ......................... 8 LIST OF ABBREVIATIONS ................................ ................................ ................................ ........ 11 ABSTRACT ................................ ................................ ................................ ................................ ... 12 CHAPTER 1 LITERATURE REVIEW ................................ ................................ ................................ ....... 14 Overvi ew of Cowpea Phenology and Growth ................................ ................................ ........ 14 Temperature and Water Requirements ................................ ................................ ............ 14 Cowpea Plant Growth, Development and Morphology ................................ .................. 14 Soil Fertility Requirements for Cowpea Growth ................................ ............................. 15 Cowpea Cropping System ................................ ................................ ............................... 16 Botanical Characteristics and Genetic Resources ................................ ........................... 17 Major Cowpea Breeding Achievements and New Goals ................................ ................ 18 Root Knot Nematode (RKN) ................................ ................................ ................................ .. 21 Symptoms /Signs, Life Cycle and Disease Environmental Conditions of RKN .............. 22 Meloidogyne incognita and Meloidogyne enterolobii ................................ ..................... 23 Genetic Resistance of Cowpea to Root Knot Nematodes ................................ ............... 25 2 GENETIC PARAMETERS IN COWPEA [ Vigna unguiculata L. Walp] FOR FORAGE PRODUCTION TRAITS ................................ ................................ ................................ ........ 28 Introduction ................................ ................................ ................................ ............................. 28 Materials and Methods ................................ ................................ ................................ ........... 33 Plant Materials ................................ ................................ ................................ ................. 33 Experimental Design and Field Management ................................ ................................ . 34 Data Collection ................................ ................................ ................................ ................ 35 Statistical Analyses ................................ ................................ ................................ .......... 36 Results ................................ ................................ ................................ ................................ ..... 38 Experiment 1 ................................ ................................ ................................ ................... 38 Experiment 2 ................................ ................................ ................................ ................... 38 Variance component e stimates and genotypic values ................................ .............. 39 Genetic correlations ................................ ................................ ................................ .. 41 Discussion ................................ ................................ ................................ ............................... 41 Experiment 1 ................................ ................................ ................................ ................... 41 Experiment 2 ................................ ................................ ................................ ................... 42 Phenotypic diversity in the UC Riverside cowpea germplasm ................................ 42 Trait correlations ................................ ................................ ................................ ...... 45 Conclusion ................................ ................................ ................................ .............................. 47

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6 3 INVESTIGATION OF ROOT KNOT NEMATODE ( Meloidogyne spp .) RESISTANCE IN UC Vigna unguiculata (L.) Walp] GERMPLASM FOR BREEDING PURPOSES ................................ ................................ ..... 63 Introduction ................................ ................................ ................................ ............................. 63 Materials and Methods ................................ ................................ ................................ ........... 65 Plant Materials ................................ ................................ ................................ ................. 65 Nematode Isolates ................................ ................................ ................................ ........... 65 Screening Assay ................................ ................................ ................................ .............. 65 Data Collection ................................ ................................ ................................ ................ 67 Statistical Model, Assumptions and Statistical Analysis ................................ ................ 67 Results ................................ ................................ ................................ ................................ ..... 68 Variance Component Estimates and Genotypic Values ................................ .................. 68 Genetic Correlations ................................ ................................ ................................ ........ 72 Discussion ................................ ................................ ................................ ............................... 73 Phenotypic Diversity in the UC Riverside Cowpea Germplasm and Commercial Cultivars for R KN Resistance ................................ ................................ ...................... 73 Trait Correlations for RKN Resistance ................................ ................................ ........... 75 Conclusions ................................ ................................ ................................ ............................. 76 APPENDIX A PREDICTED VALUES OF SIX MEASURED TRAITS ................................ ...................... 91 B RAW DATA OF GALL SCORE AND REPRODUCTION INDEX IN THE M. Incognita SCREENING ................................ ................................ ................................ .......... 99 C DATA OF GALL SCORE AND REPRODUCTION INDEX IN THE M. Enterolobii SCREENING ................................ ................................ ................................ ........................ 107 D UC RIVERSIDE MINI CORE COLLECTION INFORMATION ................................ ...... 115 LIST OF REFERENCES ................................ ................................ ................................ ............. 128 BIOGRAPHICAL SKETCH ................................ ................................ ................................ ....... 139

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7 LIST OF TABLES 2 1 Phenotypic traits characterized in cowpea. ................................ ................................ ........ 49 2 2 ANOVA ta ble for viral disease severity visually rated in 56 cowpea genotypes in Cabaret, Haiti in the summer 2018. ................................ ................................ ................... 49 2 3 ANOVA table for to tal grain yield in 56 cowpea genotypes in Cabaret, Haiti in the summer 2018. ................................ ................................ ................................ ..................... 49 2 4 ANOVA table for 100 seeds yield in 56 cowpea genotypes in Cabaret, Haiti in the summer 2018. ................................ ................................ ................................ ..................... 50 2 5 Estimates of genotypic (s 2 g ) and residual (s 2 e ) variance components, b road sense heritability ( H 2 ), standard error (SE) of the H 2 , and Likelihood Ratio Test (LRT) for eight traits measured on 292 UC accessions grown in Citra, FL. ................................ ................................ ........................... 50 3 1 Phenotypic and quantitative traits investigated in the Me and Mi screenings of cowpea germplasm. ................................ ................................ ................................ ............ 77 3 2 Estimates of genotypic (s 2 g ) and residual (s 2 e ) variance components, broad sense heritability ( H 2 ), standard error (SE) of the H 2 , and likelihood ratio test (LRT) for five traits measured on 56 UC Riverside germplasm accessions known to be resistant to Mi and Mja . z ................................ ................................ ................................ ................... 77 A 1 List of the predicted values of six measured traits. ................................ ............................ 91 B 1 Gall score and reproduction index per genotype in the M. inc ognita screening. ............... 99 C 1 Gall score and reproduction index per genotype in the M. enterolobii screening. .......... 107 D 1 List of the accessions used in the current study, their PI numbers, origins, ................................ ................................ ............. 115

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8 LIST OF FIGURES 1 1 Sketch of small grain legumes phenological stages from seedlings emergence to plant scenecence. ................................ ................................ ................................ ................ 27 2 1 Cowpea plant attacked by cowpea aphid [ Aphis craccivora , C. L. Koch, 1854] in the cowpea field experiment three weeks after sowing in Cabaret, Haiti in the summer 2018. ................................ ................................ ................................ ................................ ... 51 2 2 Viral disease observed (not identified) in the cow pea field experiment three weeks after sowing in Cabaret, Haiti in the summer 2018. ................................ .......................... 52 2 3 Phenotypic characterization of cowpea germplasm for plant type, Cabaret, Haiti in summer 2018. ................................ ................................ ................................ ..................... 53 2 4 Bar plot of disease severity in the cowpea field experiment in Cabaret, Haiti in the summer 2018. Color code: light blue: disease score < 5; dark red: 5 disease score 8; light red: d isease score > 8 ................................ ................................ ............................. 53 2 5 Phenotypic characterization of cowpea germplasm for growth habit in Citra, Florida ..... 54 2 6 Phenotypic characterization of cowpea germplasm for plant type in Citra, Florida ......... 54 2 7 Phenotypic characterization of cowpea germplasm for plant height Citra, Florida. Color code: light blue: Commercial cultivars and PI; red: UC germplasm ................................ ................................ ................................ .......................... 55 2 8 Phenotypic characterization of cowpea germplasm for days to flower (blue arrows represent the flowering window for commercia l cultivars and PI, and the red arrow highlights the late flowering accession 346), Citra, Florida. ................................ ............. 56 2 9 Phenotypic characterization of cowpea germplasm for days to pod (red arrows represent the flowering window for commercial cultivars and PI, and the blue arrow highlights the early flowering accession 8). ................................ ................................ ...... 57 2 10 Principal component analysis (PCA) of six traits using genotypic values obtained with the single year model in 302 cowpea genotypes. Cowpea accessions are shown as labeled loadings (diff erent colors: check = controls, entry = accessions, and z = others), and the traits are shown as vectors. Traits: Plant height, Days to Flower, Biomass_R1 = biomass at flowering, Days.to.Pod = days to pod maturity, Flower.to.Pod = Days from flowering to po d maturity, Biomass_R6 = biomass at pod maturity. ................................ ................................ ................................ ...................... 58 2 11 Principal component analysis (PCA) of eight traits using genotypic values o btained with the single year model in 100 cowpea genotypes. Cowpea accessions are shown as labeled loadings (different colors: check = controls, and entry = accessions), and the traits are shown as vectors. Traits: Plant height, Days to Flower, Biomass_R1 = biomass at flowering, Days.to.Pod = days to pod maturity, Flower.to.Pod = Days

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9 from flowering to pod maturity, Biomass_R6 = biomass at pod maturity, Seed Yield, Harvest Index. ................................ ................................ ................................ .................... 59 2 12 Comparison between the cowpea germplasm accessions (in red) and the controls (commercial cultivars and PI in blue) for biomass (in kg for 3 harvested plants), Citra, Florida. ................................ ................................ ................................ ..................... 60 2 13 Genetic correlation among six traits (lower diagonal) and standard error of the correlation coefficient (upper diagonal) meas ured in 302 cowpea accessions in Citra, FL. Trait: Plant height, Days to Flower, Biomass_R1 = biomass at flowering, Days.to.Pod = days to pod maturity, Flower.to.Pod = Days from flowering to pod maturity, Biomass_R6 = biomass at pod maturity. ................................ ............................ 61 2 14 Genetic correlation among eight traits (lower diagonal) and standard error of the correlation coefficient (upper diagonal) measured in 10 0 cowpea accessions in Citra, FL. Trait: Plant height, Days to Flower, Biomass_R1 = biomass at flowering, Days.to.Pod = days to pod maturity, Flower.to.Pod = Days from flowering to pod maturity, Biomass_R6 = biomass at pod maturity, Seed Yield, Harvest Ind ex. ............... 62 3 1 Mean gall score of cowpea accessions infected with Meloidogyne incognita in growth pouches in a growth chamber study. Colo r code: dark blue gall score 1; light blue: 1< gall score 2; green: 2 < gall score 3; orange: gall score > 3 ................. 78 3 2 View of the root system of root knot nematode resistant cowpea accession 207 at eight weeks after being infected with Meloidogyne incognita . ................................ ......... 79 3 3 View of the root system of the susceptible US Department of Agriculture accession PI151562 at eight weeks after inoculation with Meloidogyne incognita . .......................... 80 3 4 Mean RI of cowpea accessions infected with Meloidogyne incognita in growth pouches in a growth chamber study. Color code: Blank: RI = 0 (immune); dark blue: (susceptible) ................................ ................................ ................................ ....................... 81 3 5 Principal component analysis (PCA) of five traits in the Meloidogyne incognita screening using genotypic v alues obtained with the single year model in 56 root knot nematode resistant cowpea accessions. Cowpea accessions are shown as labeled loadings (different colors: check = Controls and, RKNR = UC accessions, Susceptible = controls), and the tra its are shown as vectors. Traits: Gall Score, Total Eggs, Eggs.gr.rt = Eggs per gram of root, RI = reproduction index, Root_FW = root fresh weight. ................................ ................................ ........................... 82 3 6 Mean gall scores of cowpea accessions infected with Meloidogyne enterolobii grown in cone tainers in controlled room. Color code: dark blue gall score 1; light blue: 1< gall score 2; green: 2 < gall score 3; orange: 3 < gall score 4; red: gall score > 4. ................................ ................................ ................................ ................................ ..... 83

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10 3 7 View of the root knot nematode resistant acces sions 45 and 338 showing high levels of resistance to Meloidogyne enterolobii both for gall score and RI. ................................ 84 3 8 View of large galls induced by Meloidogyne enterolobii on the roots of the root knot nematode resistant accession 70. ................................ ................................ ....................... 85 3 9 Mean RI of cowpea accessions infected with Meloidogyne incognita in growth (slightly resistant); a ................................ ................................ .... 86 3 10 Principal component analysis (PCA) of five traits in the Meloidogyne enterolobii screening using ge notypic values obtained with the single year model in 56 root knot nematode resistant cowpea accessions. Cowpea accessions are shown as labeled loadings (different colors: check = Controls and, RKNR = accessions, Susceptible = controls), and the traits are shown as vectors. Traits: Gall Score, Total Eggs, Eggs.gr.rt = Eggs per gram of root, RI = reproduction index, Root_FW = root fresh weight. ................................ ................................ ................................ ................................ 87 3 11 Genetic correlation among five traits (lower diagonal) and standard error of the correlation coefficient (upper diagonal) measured in root knot nematode resistant cowpea accessions for resistance to Meloidogyne incognita in growth chambers . Traits: Gall Score, Total Eggs, Eggs.gr.root = Eggs per gram of root, RI = Reproduction Index, Root Fresh Weight. ................................ ................................ .......... 88 3 12 Genetic correlation among five traits (lower diagonal) and standard error of the correlation coefficient (upper diagonal) measured in root knot nematode re sistant cowpea accessions for resistance to Meloidogyne enterolobii in controlled room. Traits: Gall Score, Total Eggs, Eggs.gr.root = Eggs per gram of root, RI = Reproduction Index, Root Fresh Weight. ................................ ................................ .......... 89 3 13 From left to right, cowpea root system of the same genotype infected with Meloidogyne enterolobii (in cone tainer) and M. incognita (in growth pouch) showing bigger galls on the M . enterolobii infected root system, small root length and biomass compared to the M. incognita infected plant. ................................ ............... 90

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11 LIST OF ABBREVIATIONS HI Harvest index Me Meloidogyne enterolobii. Mi Meloidogyne incognita. PCA Principal component analysis PI Plant introduction RI Reproduction index RKN Root knot nematode

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12 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science SCREENING COWPEA [ Vigna unguiculata L. WALP ] GERMPLASM FOR FORAGE PRODUCTION AND ROOT KNOT NEMATODE RESISTANCE ( Meloidogyne spp. ) By Rocheteau Dareus December 2019 Chair: Esteban F. Rios Major: Agronomy Cowpea [ Vigna unguiculata L. WALP ] is a legume grown worldwide . In developing countries , cowp ea is exploited as a dual purpose crop for its grain and fodder while it is cultivated as food and cover crop in industrialized countries. However, root knot nematodes (RKN) ( Meloidogyne spp) represent a threat to cowpea production. The UC Riverside cowpea germplasm collection was characterized in the field for several morphological, phenological and agronomic traits for selection for breeding purpose and they were screened for resistance to Meloi dogyne incognita ( Mi ) and Meloidogyne enterolobii ( Me ). All the traits measured throughout the research were genetically diverse as assessed by the genotypic variances and PCA analyses . Genotypic variances calculated for agronomic traits in field studies w ere significant . Beside s, the Me screening showed significant genotypic variances and variation among genotypes . B road sense heritabilities ( H 2 ) calculated for the whole germplasm collection , the selected accessions and the Mi screening varied from low to high . Most of the traits that exhibited a high H 2 were strongly correlated to each other allowing indirect selection for thoses traits. From the 56 known RKN resistant accessions , 53 effectively showed different levels of resistance to Mi in regard to g all score and reproduction index (RI) while only 12 of them showed resistance to Me confirming the capability of Me to brake resistance in

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13 known resistant plant materials. The UC Riverside germplasm collection has potential to be exploited for breeding pur pose s .

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14 CHAPTER 1 LITERATURE REVIEW Overview of Cowpea Phenology and Growth Temperature and Water Requirements Cowpea [ Vigna unguiculata (L.) Walp.] is an herbaceous annual plant grown in warm seasons under temperatures varying from 16 °C to 36 °C, with its optimal growing temperature ranging from 22 °C to 27 °C (Singh, 2014). Cowpea is typically found in tropical climates in low altitudes near the equator and the subtropics. Cowpea is tolerant to hot and dry climates compared to other crops and legu mes species (Hall et al., 2002; Hall, 2004; Singh, 2014). For instance, according to Hall and Patel (1985), up to 1000 kg/ha of dry grain could be harvested in the Sahel region in Africa with only 181 mm of rainfall, and hot and dry environmental condition s. Cowpea Plant Growth, Development and Morphology Plant growth is defined as an increase in size of different organs of a plant such as leaves, roots (Davies, 2019), while plant development is considered to be the formation of new tissues and structures ( 2019). As a warm season legume, cowpea plant growth and development are similar to common bean ( Phaseolus vulgaris L.) (Figure 1 1) with at least four vegetative stages (VE: Eme rgence; VC: Unrolled unifoliate leaves; V1: First trifoliate; V2: Second trifoliate, Vn: n trifoliate), and eight reproductive stages (R1: beginning flowering; R2: Full flowering; R3: Beginning pod; R4: Full pod; R5: beginning seed; R6: Full seed: R8: seed s mature and plant senesces). The position of the flowers on the plant determines what type of growth habit the plant exhibits. Cowpea plants are either determinate or indeterminate in growth habit, with the non vining types tending to be determinate (Davi s et al., 1991; Singh, 2014). Plants with a determinate growth habit

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15 produce terminal inflorescences on the main stems and branches, thus, stopping the vegetative growth stage once the reproductive stage is reached. Those with an indeterminate growth habit have buds on the axil of their leaves that may become either a branch or an inflorescence. Therefore, they continue to set vegetative parts such as new leaves and branches during reproductive growth (Singh, 2014). Three types of cowpea plant architecture (plant type) are recognized: erect, semi erect, and prostrate (Davis et al., 1991). Cowpea plants with an erect or semi erect plant architecture are bushy and reach between 30 to 60 centimeters in height with their first branches appearing at least 15 cent imeters from the soil level. Cowpea plants exhibiting a prostrate or climbing plant architecture are spreading, and respectively trailing and vine like (Davis et al., 1991). In regard to photoperiodism, cowpea is generally a short day plant; however, photo period insensitive cowpea germplasm is also available. Photoperiod sensitivity can impact insensitive) where they do not rely on day length to set flowers or short day varieties (photo sensi tive) where they require a certain photoperiod threshold to begin flowering. Cowpea plants will normally bloom within 40 to 60 days when the daylength is 12 hours (short day plants), and the photo sensitive ones will not bloom at all or will be late flow ering during longer days (long day plants) (Singh, 2014). Soil Fertility Requirements for Cowpea Growth Cowpea can be grown in diverse soil types; however, it can reach its highest performance on well drained and aerated sandy loams or sandy soils, within a pH range of 5.5 to 6.5 (Singh, 2014). Three macronutrients (nitrogen, phosphorus and potassium) are crucial for soil fertility and plant growth and development. These nutrients, when at low levels in tropical soils, can affect plant dry matter yield and quality. Usually, cowpea is grown in the tropics and subtropics in marginal and nutrient depleted soils (Singh, 2014). Most of these soils consist of more than

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16 85% sand and less than 0.2% organic matter, and low levels of some macro and micronutrients such as: nitrogen, phosphorus, potassium, sulfur, boron and zinc with phosphorus being the most limiting nutrient ( Kolawole et al., 2000; Sanginga et al., 2000; Singh, 2014). Cowpea can withstand soils low in nitrogen content due to its ability to fix nitroge n through symbiosis with Rhizobium bacteria (Elowad and Hall, 1987). It can also develop a symbio tic relationship with mycorrhizae (Kwapata and Hall, 1985) which are species of fungi (arbuscular mycorrhizal fungi: AMF) that assist plant nutrition through e nhanced phosphorus uptake. Cowpea is tolerant to both low and high pH soil conditions (Fery, 1990; Singh, 2014). In acidic tropical soils rich in iron (Fe) and aluminum (Al), phosphorus (P) fertilizer can be fixed and not readily available to cowpea plants due to the presence of Al and Fe oxides in those soils (Sample et al., 1980). Therefore, the mycorrhizal roots of cowpea play a crucial role in enhancing not only the uptake of phosphate in such environments, but also other micronutrients such as zinc and copper (De Faria, 1984; Kwapata and Hall, 1985). Cowpea Cropping System Cowpea can be grown in both monoculture and intercropping systems. In developing countries, cowpea is intercropped with sorghum ( Sorghum bicolor L. Moench), pearl millet ( Pennisetum g laucum L. R. Br.), maize ( Zea mays L.), cassava ( Manihot esculenta Crantz) or cotton ( Gossypium barbadense L.) (Singh, 2014). In industrialized countries, both systems are used depending on the region and farmer need. The use of root knot nematode (RKN) ( Meloidogyne spp. ) resistant cowpea cultivars in crop rotations as cover crop s can also help reduce nematode populations, in addition to restoring soil fertility for succeeding crops (Tarawali et al., 2002; Carsky et al. 2002; Sanginga et al., 2003). Cowpea can also be used as green manure and as fodder to feed livestock (Tarawali et al., 1997, Tarawali et al., 2002).

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17 Botanical Characteristics and Genetic Resources Cowpea is a dicotyledonous plant that belongs to the family Fabaceae, subfamily Faboideae, genus Vigna (Singh, 2014). It is a diploid species (2n = 2x = 22) and its genome has been recently sequenced ( 519 Mb) (Lonardi et al., 2019). Cowpea is a self pollinating species; thus, varieties are generally pure lines. The genus Vigna is closely related to the genus Phaseolus comprising the common bean and the genus Dolichos/Lablab comprising the dolichos bean or lablab bean ( Lablab purpureus L.) (Piper, 1912). Frahm Leliveld (1965) reported the existence of 38 wild species of Vigna including the wild species V. dekindtiana, Harms.; V. gracilis, Hook.; V. vexillata, Benth, etc. Piper (1912) reported that 60 spe cies of Vigna have been described and only three species are cultivated: asparagus bean ( Vigna sesquipedalis, A. J. Pieters), the catjang ( Vigna catjang, Burm. Walp.) and cowpea. These three cultivated species are closely related through intermediate varie ties and are difficult to be botanically differentiated (Piper, 1912). Cowpea has several crowder pea, and black Haiti. The International Institute of Tropical Agriculture (IITA) has the largest cowpea germplasm collection in the world. This collection is composed of over 15,700 cultivated accessions, and more than 560 accessions of wild germplasm collected from over 100 countries (Fatokun et al., 2018). The United States Department of Agriculture Genetic Resources Information Network (USDA GRIN) maintai ned at Griffin, GA and University of California, Riverside, USA hold respectively close to 7,737 and 6,000 cowpea germplasm accessions (Fatokun et al., 2018). The IITA and USDA GRIN germplasm accessions are available freely to

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18 cowpea breeders and geneticis ts around the world. The main research focus at IITA includes studying qualitative and quantitative traits in the germplasm collection including plant pigmentation, plant type, plant height, leaf type, growth habit, photosensitivity and maturity, nitrogen fixation, fodder quality and dual purpose, root architecture, pod traits, seed traits and grain quality. Recently, biotic and abiotic stresses (heat and drought, bacterial, fungal and viral diseases, root knot nematodes and insect pests as well as parasiti c weeds affecting cowpea production) have been a major focus to find novel genotypes/alleles using these germplasm (Singh, 1997). Large genetic variation was reported to exist among 422 cowpea landraces and 46 accessions of wild cowpea assessed using sing le nucleotide polymorphism markers (SNP) (Huynh et al., 2013). More than 76% of the landraces come from Africa and 23% from the rest of the world. The 46 accessions of wild cowpea were collected in Africa and have been added to the USDA cowpea germplasm co llection at Griffin, GA (Huynh et al., 2013). A genetic diversity study using molecular markers revealed that all the 468 accessions belong to two different gene pools: gene pool one comprising accessions from countries in west, north, and central Africa a nd, gene pool two having accessions from countries in east, southeast, and southern Africa (Huynh et al., 2013). ). A mini core collection of 384 cowpea accessions, representative of the genetic diversity of the cultivated cowpeas (51,128 SNPs) and collect ed from 60 countries worldwide (Munoz Amatriain et al., 2016) was developed and is available to cowpea breeders (P. A. Roberts and T. J. Close, personal communication, 2017). Major Cowpea Breeding Achievements and New Goals Major efforts have been placed i nto cowpea breeding in the last decades (Singh, 2014). Several abiotic and biotic stresses affect cowpea growth and development and have negative consequences for productivity (Singh, 2005; Timko et al., 2007). Moreover, a major breeding

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19 focus has been pla ced on developing cultivars with regionally desired traits, such as grain characteristics (shape, color and size) (Singh, 2014; Herniter et al., 2018), resistance to specific abiotic/biotic stress (Singh, 2014), productivity (Singh, 2014), and early/late m aturing (Singh and Ntare, 1985). Nowadays, due to breeding efforts, cultivars with resistance to biotic/abiotic factors and with desired agronomic characteristics at a regional level are available in major parts of the world where cowpea is grown such as i n Africa, Asia, Central and South America, and in the USA. Genetic diversity among 768 cowpea germplasm lines from USDA and US breeding programs was studied using genotyping by sequencing (GBS) (Xiong et al., 2018). Re su lts from the same study showed that cowpea germplasm from around the world are closely related to these two following areas of world: West and East Africa (Xiong et al., 2016). Such information is valuable in enhancing cowpea breeding programs. The IITA has developed and released an early ma turing (70 days) and high yielding cowpea cultivar IT84S 2246 4, which is known to be resistant to Meloidogyne incognita [Kofoid and White, 1919; Chitwood, 1949] ( Mi ) and Meloidoyne javanica [Treub, 1885; Chitwood, 1949] ( Mja ) (Roberts et al., 1997). This cultivar also showed a high level of resistance to several diseases and pests, such as cowpea yellow mosaic virus (CYMV), anthracnose ( Colletotrichum lindemuthianum (Sacc. and Magnus) Lams. Scrib.), cercospora leaf spot ( Cercospora canescens Ellis an d G. Martin), web blight fungus ( Rhizoctonia solani Kuhn), bacterial pustule ( Xanthomonas campestris pv vignicola Patel and Jindal), cowpea aphid ( Aphis craccivora Koch), and the cowpea storage weevil ( Callosobruchus maculatus Fabricius). The high yielding west of the US (Helms et al., 1991a; Helms et al., 1991b). Both of these cultivars are known to be resistant to Mi and Fusarium wilt ( Fusarium oxysporium Schlechtend.: Fr. f . sp. trachei philum (E.F. Smith) W.C.

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20 Snyder and Hansen) (Helms et al., 1991a; Helms et al., 1991b). In addition, IITA has developed a breeding program in the 1990s dedicated to developing dual purpose cowpea cultivars (Singh et al., 2003). Through this breeding progra m, scientists at IITA were able to release extra early (60 days) to medium maturing (75 80 days) dual purpose cowpea cultivars with a seed yield potential of at least 2 to 2.5 t/ha and 2 to 3 t/ha of fodder (Singh et al., 2003; Singh, 2006). These dual pur pose cowpea cultivars were released in several countries in Africa, Asia, Central and South America (Singh, 2006). Breeding cowpea for resistance to nematodes has also been successful where many lines have been developed including the line IT89KD 288 which showed resistance to four strains of Mi in USA (Ehlers et al., 2000). Efforts have also been made to develop cowpea cultivars with tolerance to abiotic factors, such as heat and drought tolerance, and root architecture (Matsui and Singh, 2003). Several br eeding lines have been released both for tolerance to drought (IT89KD 374 57, IT88DM 867 11, IT98D 1399, IT98K 131 1, IT97K 568 19, IT98K 452 1, IT98K 241 2), and for tolerance to heat (IT93K 452 1, IT98K 1111 1, IT93K 693 2, IT97K 472 12, IT97K 472 25, IT 97K 819 43, IT97K 499 38) (Timko and Singh, 2008). The same screening methods were used to develop cowpea breeding lines (IT89KD 374 57, IT90K 372 1 2, IT98D 1399, IT99K 1060, IT97K 568 19, IT97K 568 11, IT00K 1148, IT97K1069 6, IT03K 314 1, IT03K 351 2) w ith enhanced nitrogen fixation and tolerance to low phosphorus (Timko and Singh, 2008). The use of recurrent selection technique in the field to combine the resistances found for abiotic factors was a major limitation to the breeding effort made. This caus ed a low heritability of the desirable traits. Eight elite parents were used to develop a new diversified cowpea population to be use d in cowpea breeding (Huynh et al., 2019). Additionally, novel molecular tools have been used in cowpea to accelerate breed ing such as quantitative traits loci (QTL) and marker assisted

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21 selection (MAS). According to Van Boxtel et al. (2000), Singh et al. (2002), and Lale and Kolo (2007), current significant efforts have been made combining field and laboratory screenings to de velop copwpea breeding lines with combined resistance to several diseases and pests, including cowpea yellow mosaic, blackeye cowpea mosaic, many strains of cowpea aphid borne mosaic, Cercospora ( Pseudocercospora cruenta ) , smut , rust, Septori a ( Mycosphaere lla populorum ) , scab, Ascochyta blight, bacterial blight, anthracnose, nematodes, Striga ( St r iga spp.) , Alectra , aphid ( Aphis craccivora ) , thrips (Thrips spp) and bruchid ( Callosobruchus maculatus ) . The whole cowpea genome has been sequenced and is publically available (Lonardi et al., 2019). This is considered a big achievement as it will contribute greatly to the development of cowpea lines with improved traits. As conventional breeding (phenotyping ) is time consuming, marker based selection has been promoted in breeding programs focus ing on RKN resistance in cowpea. The QTL related to the Rk locus for RKN resistance was identified and mapped (Huynh et al., 2015). Ndeve at al. (2019) were able to id entify two QTLs related to root galling and egg masses resistance on two chromosomes (Vu01 and Vu04) in regard to the RKN species Mi and Mja . Research has also been conducted to identify QTLs responsible for domestication related traits in cowpea such as d ays to flowering, pod length, seed number per pod, etc (Lo et al., 2018). All the progress made at the molecular level will help breeders to select more precisely for the desirable traits of their interest to release new, improved cowpea cultivars . Root Kn ot Nematode (RKN) Root knot nematodes (genus Meloidogyne ) are classified in the Phylum Nemata (or Nematoda), Class Chromadorea, Order Tylenchida, Super family Tylenchoidea, and the Family Meloidogynidae. Root knot nematodes are sedentary, obligate endopara sites of plants. They are

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22 the most widespread plant parasitic nematode worldwide affecting plant productivity. They are known to be responsible of ca. 16.9% annual yield losses (Bhatti and Jain, 1977; Sasser, 1979; Agrios, 2005 ). Root knot nematodes are ab le to parasitize a wide range of cultivated plants including agronomic, vegetable, and fruit crops. They infect mainly plant root systems and, therefore, directly impair water and nutrient uptake, which are crucial for plant physiological functioning (plan t growth and reproduction). According to Abad et al. (2008), 95% of the RKN populations are composed of four Meloidogyne species: M. incognita (Kofoid and White) Chitwood, M. javanica (Treub) Chitwood, M. arenaria (Neal) Chitwood, and M. hapla Chitwood wit h M. incognita being the most virulent species. Root knot nematodes cause little to no economic damage when their population levels are low; however, their impact on crop yield is devastating at high population densities in the soil. The use of susceptible crop varieties in irrigated sandy soils is one of the practices that exacerbates the spread and the growth of RKN populations. However, several techniques are used to control RKN including crop rotation using non host plants, fallow flooding, the use resi stant varieties, and the use of nematicides. Identifying RKN species can be difficult due to population mixing; therefore, scientists use several techniques to distinguish among species and races. To differentiate among species, several methods are used i ncluding host ranges, morphological characteristics (stylet shape, perineal pattern, etc.), chromosome number, and polyacrylamide gel electrophoresis (PAGE). The host differential test is used to identify the races within a species. Most of the Meloidogyne species have three to four races, which are distinct groups or populations within a nematode species that are host specific compared to other races within the same nematode species . Symptoms/Signs, Life Cycle and Disease Environmental Conditions o f RKN Root knot nematodes are soilb orne pests that parasitize roots. Several of the most important RKN species, including Mi , reproduce by obligate mitotic parthenogenesis (Jung and

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23 Wyss, 1999). Their life cycle has three main stages: egg, juvenile and adult. The infective stage is the juve nile stage in which plant roots are affected by the juveniles that feed on the plant roots as they grow to their adult stage. The feeding process induces the formation of large cells called root knots or giant cells. There, the females lay hundreds of eggs in a gelatinous matrix (egg watered soils and at temperatures greater than 26 °C, RKN can complete their life cycle in about 25 days. However, their life cycle can be delayed until six weeks depending on many factors such as the species of Meloidogyne , the plant host, and environmental conditions of the nematode. The immediate consequence of infection of hosts by RKN is the suppression of root development and the reduction of crop productivity. Root knot nematode activities are optimal in moist and aerated sandy soils and warm temperature. They are more prevalent in soils near the surface, but they can be found somewhat deeper as they follow plant roots. In poor su rvival conditions, the eggs can survive from months to years (Olsen, 2000). Root knot nematodes are more prevalent in sandy soils where their rate of damage to host plants is maximal. The egg stage is considered the survival stage for RKN where they can st ay quiescent for years until favorable conditions occurs for them to continue their normal life cycle . Meloidogyne incognita a nd Meloidogyne enterolobii Meloidogyne incognita, also known as southern root knot nematode, is a cosmopolitan nematode found wor ldwide in warm regions of the tropics and subtropics with a wide host range of cultivated plant species (Sasser et al., 1983) including cowpea. The most frequent symptoms of Mi infection on cultivated plants are fine roots, chlorosis, wilting, stunting and , in case of severe damage, even death can occur within the plant population. In infected fields, a patchy

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24 distribution of dead plants is often observed due to Mi damage and uprooted plants show swollen roots due to knotlike galling (Thorne, 1961). Meloid ogyne enterolobii (Yang and Eisenback, 1983) ( Me ), also refered to as the RKN of the pacara earpod tree ( enterolobium contortisiliquum ) , is considered as one of the most damaging RKN species alongside the species Mi (Yang & Eisenback , 1983) due to its wide host range and its pathogenicity. Me is able to infect agronomic crops, vegetables, ornamental plants and perennial crops (Yang & Eisenback, 1983; Rammah & Hirschmann, 1988; Rich et al., 2009; Brito et al., 2010; Gomes et al., 2011) . Plants infected with Me exhibit chlorosis, reduced plant growth and root galls (Eppo, 2011). Me is more aggressive than other RKN species inducing more severe root galling on host plant root systems and it can cause yield losses as high as 65% (Cetintas et al., 2007) and can even cause the complete abandonment of crop production in heavily infested fields (Carneiro et al., 2007). Me is seen as an emerging virulent species worldwide due to its negative impact on agricultural economy (Moens et al., 2009; We semael et al., 2011); its tendency to extend its geographic distribution beyond tropical areas and, its ability to breakdown resistance (ability to develop and reproduce) in several crops carrying resistance genes such as resistant cotton, sweet potato, to matoes (Mi 1 gene), potato (Mh gene), soybean (Mir1 gene), bell pepper (N gene), sweet pepper (Tabasco gene) and cowpea (Rk gene) (Brito et al., 2007; Cetintas et al., 2007; Cantu et al., 2009; Kiewnick et al., 2009; Eppo, 2011; Melo et al., 2011; Westeric h et al., 2011; Castagnone Sereno, 2012; Singh et al., 2013). In some countries, quarantine programs have been developed to manage Me (Castagnone Sereno, 2012; Elling, 2013). Even with the high virulence and aggressiveness of Me , genetic resistance of plan ts represents the main focus of scientists for managing Me . A source of resistance to Me has been

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25 species of RKN, and the results found are very promising (Rubio Cabetas et al., 1999). Similar progress has been made in peach using commercial rootstocks carrying the RMia resistance gene (Claverie et al., 2004; Nyczepir et al., 2008) and in the cultivation of guava trees using Psidium sp. accessions originating from native forests in Brazil (Carneiro et al., 2007; De Almeida et al., 2009) . Genetic Resistance of Cowpea to Root Knot Nematodes Resistance of cowpea to RKN is conferred by the single gene or locus Rk (vertical resistance or race specific resistance) (Fery a nd Dukes, 1980; Fery and Dukes, 1982; Roberts et al., 1996) except for the gene rk3, which is a single recessive gene capable of conferring broad based additive resistance when combined with Rk (Ehlers et al., 2000). Three types of resistance were identifi ed in cowpea to RKN, with the first resistance being conferred by the gene Rk; the second type is a broad based resistance conferred by the gene Rk2 and other alleles at the Rk locus distinguishable from the resistance conferred by the gene Rk; and finally , a broad based resistance found in blackeye cultivar CB27 and breeding line H8 8R, which has been shown to be the result of an additive effect of genes Rk and rk3. The broad based form of resistance to RKN found in the high yielding, heat tolerant, large 8R is effective both for Rk virulent and Rk avirulent isolates of Mi and Rk aggressive isolates of Mja (Roberts et al., 1997). This resistance is capable of suppressing by at least half the g alling and reproduction of both Rk avirulent isolates, Rk virulent isolates of Mi and Rk aggressive isolates of Mja , in comparison with Rk type commercial blackeye bean cultivars (Roberts et al., 1992; Ehlers et al., 1996). Rodriguez et al. (1996) have scr eened several cowpea cultivars and have found that the cultivars IITA 3, Habana 82, Incarita 1, IT86D 364, IT87D 1463 8, Vinales 144, P902, and IITA 7 bearing the gene Rk were highly resistant to Mi whereas a local cultivar, Cancharro, deprived of the Rk g ene was highly susceptible. The IT84S -

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26 2049 cowpea line from IITA was found to have the Rk2 gene allowing it to be completely resistant to virulent RKN isolates capable of infecting commercial cultivars in California (CB5 and CB6) bearing the resistant gene Rk (Roberts et al., 1996). It is not well known whether Rk2 is a dominant allele of the Rk locus or another gene very tightly linked to Rk within 0.17 map units (Roberts et al., 1996). The combination of these sources of resistance to RKN (Rk2, rk3, QRk v u9.1, root galling gene) has shown effective broadbased resistance against several RKN populations (Roberts et al., 1997; Roberts et al., 2014; Ehlers et al., 2002; Ehlers et al., 2009; Santos et al., 2018; Ndeve et al., 2018). However, these genes are yet to be fully understood biologically in their function. Added to that, those sets of genes express their resistance to specific RKN populations; and, virulent isolates of Mi and aggressive Mja are able to reproduce on resistant cowpea lines bearing the Rk gene (Roberts et al., 1997). As RKN populations continue to evolve and more virulent pathotypes emerge (Roberts et al., 1997; Petrillo et al., 2006), new sources of resistance will be needed to control these pathogens (Fery et al., 1994; Roberts et al., 19 96; Ehlers et al., 2000; Ehlers et al., 2002).

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27 Figure 1 1. Sketch of small grain legumes phenological stages from seedlings emergence to plant scenecence. Reprinted with permission from Cybercounty.info online, http://cybercounty.info/green bean plant stages/ (June 22 nd , 2019)

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28 CHAPTER 2 GENETIC PARAMETERS IN COWPEA [ Vigna unguiculata L. Wa lp ] FOR FORAGE PRODUCTION TRAITS Introduction Cowpea [ Vigna unguiculata (L.) Walp.] is a legume cultivated for food and fodder in tropical and subtropical regions of the world (Singh, 2005; Timko et al., 2007). The annual cowpea production is estimated at seven million tons of dry grain harvested on about 14 million hectares worldwide (Singh, 2014). Cowpea is also considered an important source of income for growers and grain tradesmen (Singh, 2002; Langyintuo et al., 2003). Cowpea grain and fodder have a h are about 22 to 30% (Bressani, 1985; Nielsen et al., 1997), making it a good substitute for milk/meat products in developing countries. As fodder, its haulms contain be tween 13 to 17% of crude protein with a high digestibility and low fiber level (Tarawali et al., 1997), making it a valuable source of fodder (Fatokun et al., 1992). Based on its high nutritional value and agronomic performance, cowpea is used either for s ole cropping, intercropping or both all over the world. In the United States, cowpea is produced mostly in the southeastern region on a few thousand acres (Fery, 1985; Fery, 1990; Davis et al., 1991) and is used either as a cover crop to improve soil ferti lity or grown as food and feed in sandy soils in Florida. Harrison et al. (2014) selected three cowpea lines from landraces: US 1136, US 1137 and US 1138 that are known to have high biomass yield, high nitrogen fixation rate in the soil (220 kg ha 1 ) and R KN resistance. Plant introduction (PI) numbers were assigned to those lines: PI 664531, PI 664532, and PI 664533 respectively; and were made available by USDA GRIN. In Haiti, the total area of cowpea production is estimated at 40,440 hectares for an annual average production of approximately 28,379 metric tons of grains (FAOSTAT, 2015). Cowpea is used in cropping systems usually in association with several other crops ( Zea mays L.,

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29 Manihot esculenta Crantz, Ipomoea batatas (L.) Lam.) because of its high pot ential to contribute to soil fertility through nitrogen fixation. Cowpea is grown mainly for human consumption in Haiti and its plant residues are used as fodder for livestock. The largest cowpea germplasm collection in the world is maintained at the Int ernational Institute of Tropical Agriculture (IITA). This collection is comprised of over 15,000 cultivated accessions collected from 90 countries, 75% of which are from the West Africa sub region (Fatokun et al., 2018). A first core collection of 2062 acc essions was developed based on accession origins, botanical status, and improved lines through breeding programs (Mahalakshmi et al., 2007). Later, a mini core subset of 290 accessions from IITA germplasm was studied for genetic diversity using genotyping by sequencing (GBS) and more than 90% of the accessions could be traced back to West and Central Africa (Fatokun et al., 2018). Following the IITA is the United States Department of Agriculture Genetic Resources Information Network (USDA GRIN) with a cowpe a germplasm estimated of about 7,737 accessions maintained at Griffin, GA (Fatokun et al., 2018). A mini core collection of 768 accessions was developed and studied for genetic diversity using GBS techniques (Xiong et al., 2016; Xiong et al., 2018). The re sults from the study conducted in 2016 revealed that cowpea germplasm from all over the world traced back to East and West Africa (Xiong et al., 2016). The IITA and USDA GRIN germplasm are available freely to cowpea breeders and geneticists around the worl d. The University of California, Riverside has a cowpea germplasm collection of about 6,000 cowpea accessions (Fatokun et al., 2018). A selection of 422 cowpea landraces with more than 76% coming from Africa and 23% from the rest of the world and 46 accessions of wild cowpea collected from Africa and held within the USDA cowpea germplasm collection at Griffin, GA has been studied for genetic diversity using GBS to identify the SNP (Huynh et al.,

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30 2013). Results from the study pointed out that the accessions originated from two different gene pools: gene pool one comprising accessions from countries in west, north, and centr al Africa and gene pool two having accessions from east, southeast, and southern Africa (Huynh et al., 2013). A mini core collection of 384 cowpea accessions, representative of the genetic diversity of the cultivated cowpeas (51,128 SNPs) and collected fro m 60 countries worldwide (Munoz Amatriain et al., 2016) was developed and is available to cowpea breeders (P. A. Roberts and T. J. Close, personal communication, 2017). Many dual purpose cowpea varieties have been developed and released in several regions in the world including countries in Africa, Asia, and Central and South America. These varieties have the potential to yield at least 2.5 t ons ha 1 of grain and more than 3 t ons ha 1 of fodder in 75 80 days (Singh, 2006). An ideal dual purpose cowpea varie ty is described as a variety of intermediate maturity (75 80 days) with semi spreading growth form and canopy height of 30 cm or more with the potential to yield at least 2 tons ha 1 of grains and 2 tons ha 1 of fodder (Singh et al., 2003). Improved dual p urpose cowpea varieties play a key socio economic and environmental role in developing countries by providing higher quality food and feed for poor people and livestock, and for improving soil fertility (Kristjanson et al., 2002). Cowpea is grown to fulfil l two main objectives in developing countries, first to feed the the remaining plant residues (fodder), which makes cowpea an important dual purpose plant. Bree ding cowpea for dual purpose uses requires the phenotyping of cowpea accessions for several desirable morphological, physiological and agronomic traits such as plant height; days to flower ing ; days to pod maturity; pods per plant; seed per pod; dry biomass yield, grain yield, etc. In addition, harvest index (HI grain biomass /total shoot biomass) and nutritive value of the

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31 fodder are two key traits in dual purpose cultivars (Anele, 2011; Ayan et al., 2012; Ibrahim et Pasternak, 2017; Omokanye et al., 2003 ). The estimation of variance components and genetic parameters (i.e. heritability, genotypic values, trait correlation among traits, genotype by environment interaction, etc.) constitute valuable information for plant breeders and geneticists because the y provide an indication of the potential genetic variation available in a given population. This information will benefit researchers when they are selecting PI for introgression to breeding programs and for designing breeding programs that maximize geneti c improvement. In cowpea, broad sense heritability ( H 2 ) estimates for most of the desirable traits and HI vary from study to study (Omoigui et al., 2006; Shimelis and Shiringani, 2010; Manggoel et al., 2012; Gerrano et al., 2015; Aliyu and Makende, 2016). However, H 2 calculated for days to flower ing was estimated at 0.85, 0.53, 0.71 and 0.84 in research conducted by Omoigui et al. (2006), Shimelis and Shiringani (2010), Gerrano et al. (2015) and Aliyu and Makende (2016) respectively . Omoigui et al. (2006), Shimelis and Shiringani (2010), and Aliyu and Makende (2016) reported H 2 of 0.84, 0.66, 0.82 respectively for days to pod maturity. Heritability estimates for seed yield were reported with the following values: 0.55, 0.74, and 0.82 by Shimelis and Shiringa ni (2010), Gerrano et al. (2015), and Aliyu and Makende (2016) respectively . Harvest indices calculated for dual purpose cowpea varieties have been reported to vary from 0.16 to 0.60 (Moalafi et al., 2010). Similar HI (0.09 to 0.60) values were reported by Gerrano et al. (2015). Combining multiple traits in one cultivar is a challenge for breeders, especially for traits with negative correlations. Indirect selection using various positively correlated traits may also improve selection efficiency. Moderate correlation between days to flower ing and dry biomass yield ( r g = 0.54) and plant height ( r g = 0.51) were reported in cowpea (Gerrano et al., 2015).

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32 Moderate to high positive correlations were reported between days to flower ing and days to pod maturity ( r g = 0.50; r g = 0.63) (Shimelis and Shiringani, 2010; Aliyu and Makende, 2016). However, the relationships between days to flower ing and seed yield and days to pod maturity and seed yield were negatively correlated (respectively, r g = 0.09; r g = 0.27) (Ali yu and Makende, 2016), while Shimelis and Shiringani (2010) and Manggoel et al. (2012) reported respectively low and moderate positive genetic correlations between days to flower ing and grain yield ( r g = 0.40; r g = 0.52). Similarly, a low positive value wa s reported for the genetic correlation between days to pod maturity and seed yield ( r g = 0.30; Shimelis and Shiringani, 2010). Harvest index is a good indicator of dual potential to produce grains while m aintaining high shoot biomass. Genetic correlations reported between HI and days to flower ing and biomass es were low and moderate negative (respectively, r g = 0.11, r g = 0.55) while it was low positive for seed yield ( r g = 0.14 ) ( Ger r ano et al., 2015) . C owpea is a good source of income for growers based on its multiple usages. Therefore, the development of dual purpose cultivars is of crucial importance in cowpea production to make this crop more marketable. Although research has been conducted to develop dual purpose cultivars around the world, they are mostly regionally adapted. Therefore, the need to develop dual purpose cultivars that are adapted to Florida and Haiti is vital. In general, in Florida, the dual purpose aspect of cowpea production is bare ly exploited, meanwhile in Haiti, the lack of improved cultivars makes it less productive. Therefore, for this study, we hypothesized that core collection (UC Riverside germplasm) for desirable traits tha t can be exploited to develop dual purpose cowpea cultivars. The use of best linear unbiased prediction (BLUP), which is a method for predicting genetic and breeding values, not only helps to gather accurate and unbiased prediction of genotypic values even for

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33 unbalanced experimental designs and datasets but also, helps with the estimation of genetic correlation among performance of the same genotypes in different environments (Piepho et al., 2008). Therefore, based on the need for reliable phenotypic data and genetic parameters, the goals of this study were to: i) phenotypically characterize the UC and 10 commercial cultivars for a total eight traits under field conditions; ii) estimate variance components with linear mixed mode ls and calculate genetic parameters; and iii) obtain rankings based on genotypic values to select accessions with improved desirable agronomic performance . Materials and Methods Plant Material s The cowpea germplasm used in all experiments was obtained from cowpea mini core collection (Munoz Amatriain et al., 2016). Mature pods were harvested from an experimental area in Riverside, CA in October 2017. Only accessions (292) that had mature pods were harvested, threshed using a seed thresher (Almaco BT14 Belt thresher) and transported to Florida. Some accessions produced only a few pods; therefore, seed was increased in greenhouses at the UF Forage Breeding and Genetics Lab during the Fall/Winter 2017/2018. Commercial cultivars were purchased in local seed stores, and USDA GRIN accessions were requested through GRIN portal. Experiment 1. The trial was conducted in Cabaret, Haiti in the summer 2018 consisted of 56 cowpea accessions from the UC Riverside germplasm known to be RKN resistant (P. A. Experiment 2. A total of 302 cowpea genotypes were screened in Citra, FL at the Plant Science Research and Education Unit in Fall 2018. The 292 accessions from mini core collection and seven commercial cultivars were included in the study as controls:

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34 cowpea lines from the USDA GRIN were included in the study: US 1136, US 1137, and US 1138 (Harrison et al., 2014). Experimental Design and Field Management The field screening trials were conducted on a loamy soil in Cabaret, West Department of Haiti (18.7 339° N, 72.4169° W) in the Summer 2018 (Mid May to late July), and in Citra, FL (29.4119° N, 82.1098° W) in the Fall 2018 on a sandy soil (September 7 to December 4, 2018). During these field experiments, the following morphological, ph eno logical and, agro nomic traits were phenotyped: p lant ype; growth habit; plant height; days to flower ing ; days to pod; flower ing to pod; seed yield ; total biomass es ; and harvest index. Experiment 1. The experiment was laid out as a randomized complete block design (RCBD) w ith three replicat ions . Each experimental unit (3 m x 0.6 m) consisted of 10 plants manually seeded and spaced 0.3 m within row and 0.6 m row spacing. The seeding rate was equivalent to 55,555 plants ha 1 . The field experiment was irrigated after sowing to enhance seed Weed management was performed manually. Soil in the field was a loamy soil and was manually plowed using hoes. No chemicals (pesticides and fertil izer) were applied throughout the course of the study. Experiment 2. The experiment was planted under a row/column design with two replicat ion s and augmented representation (two observations per replication) of the 10 controls in Citra, FL on September 7, 2018. Each experimental unit (3 m x 0.6 m) consisted of 10 plants manually seeded and spaced 0.3 m within row and 0.6 m row spacing. The seeding rate was equivalent to 55,555 plants ha 1 . Seeds were sowed using a hand planter at a rate of two seeds per hol e and, one week after germination, seedlings were t h inned to keep only one plant per hole. Ten days after planting, plots were fertilized with 34 kg ha 1 of 10 10 10 (N P 2 O 5 K 2 O ). Two

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35 weeks after planting, the post emergent herbicide clethodim (Select, 70.76 g a.i. L 1 ; Valent, USA) was applied to the field at the rate of 226.8 g acre 1 with crop oil concentrate 5% solution to control weeds. The herbicide was tank mixed with the insecti cide bifenthrin (Bifenture 2EC, 70.76 g a.i. L 1 ) at the rate of 181.4 g acre 1 to control insects. After crop establishment, weed management was performed manually . Data Collection Experiment 1. Due to unexpected aphid infestation three weeks after planti ng (Figure 2 1) followed by viral disease spread (Figure 2 2), data were collected for only three traits: plant type, disease severity, and seed weight (Table 2 1). Plant type and disease severity were visually rated, while seed weight was measured by bulk ing all pods per plot. The plots were scored for viral disease using a scale of 0 to 10 (0 = resistant and 10 = susceptible plants). Experiment 2. Morphological, phenological and agronomic traits were measured on all 302 cowpea genotypes in Citra, FL. Dat a collection began when experimental units exhibited at least 10% plants bearing flowers and days to first flower ing was recorded. Plant type and plant growth habit were assessed through visual observations (Table 2 1). Plant height was measured as canopy height for all accessions using a ruler from the soil level to the average height of the plot canopy, and three measurements were averaged by plot. Plant biomass was assessed by harvesting three plants per plot cut at the soil level, avoiding the border pl ants. Dry matter yield was then obtained by drying samples at 44 50 degrees Celcius for at least one week. D ry weights were recorded (Table 2 1). In addition, plots were visually assessed for pod maturity and it was expressed as the number of days from sow ing to pod physiological maturity. A genotype was considered to be at the pod maturity stage when more than 50% of pods were mature (pods turning from green to yellow and/or dried). A second biomass harvest occurred at pod maturity to determine dry matter yield by harvesting another three plants and following the same process

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36 as the first harvest. A selection of 100 accessions ex h ibiting erect/semi erect growth habit and high biomass w as made for further testing. The three plants harvested at pod maturity f rom these 100 accessions were screened for seed yield by threshing pods using a seed thresher (Almaco BT14 Belt thresher). Finally, harvest index (HI) for seed production was calculated using the ratio HI = seed yield/ total shoot biomass (Table 2 1). Stat istical A nalyses Experiment 1. Analysis of Variance (ANOVA) was conducted using R (R Development Core Team, 2019) for all the three response variables. The statistical model for data analysis was: Y= + B +T +e w here Y was the response variable; was the overall population mean; B and T represent ed the block and treatment effects; and were the vectors of the fixed block and random treatment (genotypes) effects respectively ; and e was the vector of random errors. Statis tical significance among treatments w as tested and assessed at and the means were pairwise compared using the Tukey Honestly Significant Difference (HSD) test. Experiment 2. Data were analyzed using linear mixed models in ASReml R v.4 (Gilmour et al., 2009). Two data subsets were made to analyze all the traits: i) using all the 302 genotypes, and, ii) using only the 90 selected accessions and the 10 controls. The following mixed model was fitted for single trait analysis: y = + X 1 + X 2 Z 1 g Z 2 h Z 3 j + e ; where was the overall population mean; X 1 , X 2 , and Z 1 , Z 2 , Z 3 were design matrices; was the vector of the fixed replication effect; was the vector of the fixed control effects; g and

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37 h were respectively vectors for random effects due to row and column; j was the vector for random effects due to populations (genotypic values); and e was the vector for random errors. The significant effect of genotypic variances was tested using Likelihood Rat io Tests (LRT). Broad sense heritability ( H 2 ) was calculated using variance components for each trait. G enotypic values obtained with single trait models were used to rank genotypes for selection of the best 90 accessions and are given in Appendix A . Princ ipal component analysis (PCA) was performed with prcomp in R with a correlation matrix using genotypic values. The PCA was visually plotted using ggbiplot2 in R (Vu, 2011). Genetic correlations among traits (Typ e A correlation) were calculated using genotypic values and plotted using ggplot2 (Vu, 2011). Multiple traits models were used to obtain genetic correlations among traits where y i was partitioned for a 2 trait analysis y 1 and y 2 . We used the 2 trait (bivari ate) model fitted below: y i X i i X i Z i g i Z i h i Z i j i e i ; where y i was the vector of the two phenotypic responses; i was the overall population mean for each trait; X i , and Z i were design matrices for each trait, i and i were respectively the vectors of the fixed replicates and controls effects for each trait; g i , h i , j i were respectively the vectors of the random effects of row, column and genotypic values, with g i ~ MVN (0, G g ); and e i was the vector of random errors for each trait, with e i ~ MVN (0, D). G g was a CORGH variance covariance matrix of genetic effects with a genetic correlation between traits ( r g ) and a different genetic variance for each trait; and the matrix D was a diagonal variance covariance matrix of error effects with a different variance for each trait.

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38 Results Experiment 1 Data were collected for only three traits in this experiment as aphid infestation and viral disease occurred within three weeks after sowi ng (Figures 2 1 and 2 2). A visual assessment after aphid infestation and viral disease outbreak indicated that most plots exhibited significant plant stunting and abnormal growth, and for this reason flowering and biomass yield were not assessed. At the t ime of seed harvest, plants were stunted with tiny pods and few seed per pod. Data collected for plant type showed that phenotypic variability exists across these accessions for this trait (Figure 2 3). More than 80% of the accessions screened in the field exhibited either an erect or semi erect type of plant architecture (Figure 2 3). Significant difference was observed for disease severity among genotypes (Table 2 2). Only two accessions (83, 333) rated lower than 5, while 70% of the accessions were rated higher than 6 indicating high disease severity (Figure 2 4). Close to half of the accessions affected by viral disease and aphids did not set pods, thus no seed weight was measured. Total grain yield varied from 16.67 kg ha 1 to 938 .89 kg ha 1 with no significant differences among genotypes (Table 2 3). Seeds weight (100) varied from 10 to 21grams per accession with no significant differences observed among genotypes (Table 2 4). Experiment 2 All of sm collection , in addition to commercial cultivars were screened in the field for their phenotypic characterization. Nearly 89 % of the genotypes exhibited an indeterminate growth habit (Figure 2 5), and 66 % exhibited an erect or semi erect plant architectu re (Figure 2 6). Plant height varied from 22 cm to 64 cm and more than 20% of the accessions were taller than commercial cultivars (Figure 2 7). Commercial cultivars flowered between 38 and 49 days after planting, while more than 50

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39 accessions flowered ear lier than the controls, with the earliest accession flowering 33 days after planting (Figure 2 8). The accession 346 flowered later than the commercial cultivars (62 days after planting), exhibiting a broad range of flowering window within this germplasm ( Figure 2 8). V ariance component estimates and genotypic values Variance component estimates were used to calculate H 2 for eight phenotypic traits using linear mixed models. Two data subsets were created to run analyses: i) the larger UC Riverside germplasm population (302 genotypes), and ii) the 90 selected accessions and 10 commercial cultivars. Overall, variance components and H 2 estimates obtained with the two data subsets were similar, and large genetic variability was observed in this germplasm for all traits (Table 2 5). All traits exhibited highly significant (P < 0.001) genetic variance, and H 2 varied from 0.21 to 0.72 for the larger UC Riverside germplasm population and from 0.26 to 0.83 for the selected population (Table 2 5). Plant height and d ays to flower ing exhibited the highest genotypic variances and H 2 within the UC Riverside germplasm population . Flower ing to p od resulted in the lowest H 2 , but its genetic variance was still significant (Table 2 5). Days to pod maturity varied from 56 to 75 days after planting date (Figure 2 9). Both biomass harvests exhibited the lowest genotypic variances and moderate H 2 (Table 2 5). For the selected accessions, p lant h eight and d ays to flower ing exhibited the highest genotypic variances while biomass at both harvests had the lowest. Days to flower ing and harvest index exhibited high H 2 , while f lower ing to p od and b iomass_ R6 were low . A ll the other traits exhibited moderate H 2 (Table 2 5). Principal component analys e s (PCA) were performed using genotypic values estimate s using single trait analyses. Once again, large genetic variability was found across genotypes for all trai ts (Figures 2 10 and 2 11). In the PCA using the whole population, the first two components (PCA1 and PCA2) accounted for 66% of the total variability. The first component

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40 (43% of total variability; eigenvalue = 2.57) included traits associated with Biomas s_ R6 , Biomass_ R1 , d ays to flower ing and d ays to p od (positive values). For PCA1, accession 346 and the PI US 1137 clustered together exhibiting associations with d ays to fl ower ing and b iomass_ R1 (Figure 2 10). Several accessions from the mini core collecti on ha d great er biomass than all commercial cultivars and the PI (except US 1137) tested in this study (Figure 2 12). For PCA2 (23% of the total variability; eigenvalue = 1.37), f lower ing to p od had a strong association and several commercial cultivars exhibited longer periods between flowering and pod maturity than most accessions from the mini core (Figure 2 10). The line US_1137 from USDA exhibited the third highest biomass at flowering (Fig ure 2 12) and the highest biomass at pod maturity. In the PCA for the selected population, the first two components (PCA1 and PCA2) accounted for 64% of the total variability. The first component (37% of the total variability; eigenvalue = 2.95) included t raits associated with p lant h eight, b iomass_ R6 , b iomass_ R1 , d ays to f lower ing and d ays to p od (positive values), and f lower ing to p od and HI (negative values). Once again, accession 346 and USDA PI US 1137 clustered in one side exhibiting associations with d ays to f lower ing and b iomass_ R1 and b iomass_ R6 (Figure 2 11). Several accessions from the mini core collection were taller and exhibited greater biomass than all commercial cultivars and the PI (except US 1137) tested in this study (Figure 2 11). However , it took more days for those accessions to flower and set pods. The PCA2 (27% of total variability; eigenvalue = 2.12) was primarily associated with HI , s eed y ield and f lower ing to p od (Figure 2 11). Commercial cultivars White Acre, Zipper Cream GC , acces sions 75 and 266 were grouped together due to the long period to set pods after flowering (Figure 2 11). Several accessions exhibited higher seed yield than the controls (Figure 2 11).

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41 G enetic correlations Genetic correlations were calculated for all the six traits measured in the 302 genotypes. Most traits exhibited a positive correlation, with the exception of f lower ing to p od and d ays to f lower ing (Figure 2 13). The correlation between p lant h eight and al l the other traits were low positive ( r g < 0.29), with the exception of b iomass_ R6 that was moderate positive ( r g = 0.57) (Figure 2 13). Moderate to high positive correlations (0.66 < r g < 0.87) were found between d ays to f lower ing and both biomass harvests, d ays to p od, and both biomass harvests (Figure 2 1 3 ), while a negative correlation was found between d ays to f lower ing and f lowering to p od. Days to p od exhibited a moderate positive correlation to b iomass_ R6 (r g = 0.68). But, i ts correlation to f lower ing to p od was low ( r g = 0.15) (Figure 2 13). Genetic correlations were also calculated for the 100 selected genotypes, and similar trends considering positive/negative correlations were found (Figure 2 14). Flower ing to p od was neg atively correlated to all but one trait ( 0.67 < r g < 0.07) (Figure 2 14). Plant h eight exhibited a low to high positive correlation to d ays to f lower ing , d ays to p od and the two biomasses (0.22 < r g < 0.74). Days to f lower ing was highly positively correlated to d ays to p od and both biomass es (0.73 < r g < 0.86) while b iomass_ R1 was moderately correlated to d ays to p od ( r g = 0.51) and highly correlated to b iomass_ R6 ( r g = 0.95) (Figure 2 14). Seed y ield the six other traits were low negative to low positive ( 0.40 < r g < 0.40). H I was low to moderate negatively correlated to all of the six traits ( 0.65 < r g < 0.01). However, its correlation to s eed y ield was high positive ( r g = 0.89) (Figure 2 14). Discussion Experiment 1 T he experiment conducted in Cabaret, Haiti was compromised by a severe aphid infestation followed by a viral disease outbreak three weeks after the field experiment was

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42 established. Thus, only a few traits we re phenotyped. Data collected on plant architecture showed large phenotypic variability within these accessions, and 82% of the accessions exhibited either an erect or semi erect plant type of growth (Figure 2 3). This indicates that there is potential for selecting novel accessions exhibiting these desirable traits for breeding dual purpose cultivars. The significant difference observed among treatments for disease severity (Table 2 2, Figure 2 4) suggests that there is potential to select for cowpea viral disease resistance within these accessions. Due to the high disease pressure at early stages of the crop cycle, total grain yield ( 16.67 kg ha 1 to 938.89 kg ha 1 ) and 100 seed weight ( 10 to 21gram s ) were low, as previously reported by Annan et al. (1995) , Hall et al. (2003), and Booker et al. (2005). Annan et al. (1995) showed that prolonged aphid infestations in cowpea starting at the early seedling stage will significantly impact plant growth and yield. Furthermore, cowpea affected by aphids results in stunt ed plants, damaged pods and grain, and even plant death if occurr ing at the early stage of the plant growth. Booker et al. (2005) stated that mosaic viral disease in cowpea will drastically decrease cowpea yield (50 to 85% yield loss) if the disease occurs within 12 days after seeding. Experiment 2 The UC nine traits. The level of phenotypic diversity in the UC assessed using pheno typic data collected and analyzed with linear mixed models through the estimation of variance components and the calculation of the genetic parameters. P henotypic diversity in the UC Riverside cowpea germplasm Significant genetic diversity exists within t he UC 2 5). More than 50% of the total phenotypic variance for the traits: p lant h eight, da ys to f lower ing , and d ays to p od were due to the contribution of the genotypic variance, i . e . , they were

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43 controlled by genetic fa ctors rather than environmental factors (Table 2 5). E rect or semi erect growth architecture are desired traits for develop ping dual purpose cowpea cultivars due to the fact that genotypes with prostrate and vine like plant type exhibit low biomass per uni t area because of their low canopy height (< 15 cm) (Singh et al., 2003). The H 2 for dry b iomass es were lower ( H 2 = 0.43, H 2 = 0.35) compared to the findings ( H 2 = 0.93) of Gerrano et al. (2015). The H 2 for d ays to f lower ing was high, this suggests that this trait may be a good candidate for QTL studies and GWAS to either identify the locus (loci) and/or the actual genes cont r olling this trait. The H 2 estimate ( H 2 = 0.72) obtained for d ays to f lower ing is within the range of the values found from previous studies in cowpea (0.50 < H 2 < 0.96) (Omoigui et al., 2006; Shimelis and Shiringani, 2010; Manggoel et al., 2012; Gerrano et al., 2015; Aliyu and Makende, 2016). Flowering is an important agronomic trait from a breeding stand point . Therefore, having both early and late maturing accessions compared to the commercial cultivars offers a broader scope for breeders to select for this trait. The H 2 of d ays to p od ( H 2 = 0.55) was lower compared to previous findings (0.66 < H 2 < 0.84) (Omoigui et al., 2006; Shimelis and Shiringani, 2010; Aliyu and Makende, 2016). A high H 2 suggests that the expression of a trait is controlled by genetic factors (Rashwan, 2010; Manggoel et al., 2012). Thus, improvement of a trait with moderate/high H 2 can be achieved through plant selection (Gerrano et al., 2015). The same trend was observed for the 10 0 selected accessions in regard to the genetic variances and H 2 of the six traits bein g analyzed for the whole cowpea germplasm with slightly lar ger values for the 10 0 selected accessions (Table 2 5). The H 2 estimate for d ays to f lower ing ( H 2 = 0.83) fits into the range of the values reported by previous studies in cowpea (0.50 < H 2 < 0.96) (Omoigui et al., 2006; Shimelis and Shiringani, 2010; Manggoel et al., 2012; Gerrano et al., 2015; Aliyu and Makende, 2016). Low and moderate H 2 found for both Biomass es were the

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44 contrary to the findings of Gerrano et al. (2015) who reported a high H 2 ( H 2 = 0.93). Plant h eight and d ays to p od which exhibited moderate H 2 were lower compared respectively to the findings of previous studies ( H 2 = 0.93) (Gerrano et al., 2015) and (0.66 < H 2 < 0.84) (Omoigui et al., 2006; Shimelis and Shi ringani, 2010; Aliyu and Makende, 2016). The estimate of s eed y ield H 2 (0.56) was similar to the value reported by Shimelis and Shiringani (2010) ( H 2 = 0.55). However , other studies reported higher values (0.74 < H 2 < 0.90) for the same trait ( Manggoel et al., 2012; Gerrano et al., 2015; Aliyu and Makende, 2016). Reports from studies conducted by Omoigui et al. (2006) and Gerrano et al. (2015) found higher values (respectively H 2 = 0.77 and H 2 = 0.90) for the estimate of HI ( H 2 = 0.70). Moalafi et al. (2010) have reported values lower 0.16 < H 2 < 0.60 for HI calculated for dual purpose cowpea cultivars. High genotypic variances and H 2 found for most of the traits being investigated indicate high potential in the UC accession s for cowpea breeders to select desirable traits to develop dual purpose cowpea cultivars. In the PCA analysis, all of the accessions were scattered within the four quadrants of the biplot (Figure 2 10) , which indicates that genetic variability exists for all the se traits (G erran o et al., 2015). The clear cluster formed by the PI US 1137 and the accession 346 indicates that these two cowpea lines performed similar ly, particularly for d ays to f lower ing and b iomass_ R1 . Two clusters were identified in the biplot for the 100 selected accessions (Figure 2 11). One cluster formed with the accession 346 and the USDA PI US 1137, and one cluster with the commercial cultivars: White A cre and Zipper Cream GC , and the accessions 75 and 266. This suggests that genotypes within a cluster are genetically distinct from genotypes from other cluster s , while those within the same cluster are genetically similar (White A cre and Zipper Cream GC ).

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45 The fact that the PI US 1137 had the best performance for biomass production among the controls (USDA lines and commercial cultivars) in both populations (Figures 2 10 and 2 11) would suggest that this line might be considered as a true forage type. This statement further aligns with the report o f Harrison et al. (2014) stating that the PI US 1137 is capable of rapid grow th , exhibiting high biomass production and a long vegetative growth period. However, our findings for the PI US 1136 and US 1138 were different form the findings of Harrison et al . (2014) as they did not perform as well as in our study in regard to biomass production. O n the other hand, o ur findings showed the PI US 1136, US 1138, the commercial cultivar Iron Clay exhibit ed the highest HI. This may suggest that these three genotype s might also have potential for dual purpose use . F inally, several commercial cultivars exhibited a long period between flowering and pod maturity. This would suggest that these cultivars could be good candidates to be exploited in dual purpose breeding pr ograms as such a trait is desirable for develop ping dual purpose cultivars with more or less a n adequate time frame for biomass accumulation during the reproductive stage but short enough to avoid terminal drought with yielding potentials of at least 2 t ons ha 1 grain and 2 t ons ha 1 fodder (Singh et al., 2003). T rait correlations The high negative correlation found b etween f lower ing to p od and d ays to f lower ing indicates that the longer the plants take to set flowers, the shorter the period for pod formation/maturity. As stated above, such information is valuable from a dual purpose breeding standpoint as genotypes wi th such characteristics have the potential to accumulate large quantities of biomass and escape dry seasons. They would be a good fit for cropping systems in developing countries as most of the farmers practice rainfed agriculture. The correlation between p lant h eight and all the other traits were low, with the exception of b iomass_ R6 (Figure 2 13); this would suggest that genotypes with prostrate and vine like

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46 growth habit in the experiment exhibited high yields , which negatively impact the correlation bet ween p lant h eight and the other traits. Strong positive genetic correlations were found between d ays to fl ower ing and both b iomass es (respectively r g = 0.77; r g = 0.67). Those values are higher than previous findings by Ge r r an o et al. (2015) ( r g = 0.54). Adversely, d ays to fl ower ing p lant h eight was very low ( r g = 0.03) while it was high from Ger r r g = 0.51). Our res ults ( r g = 0.86) contrasted with those of Shimelis and Shiringani (2010) and Aliyu and M d ays to f lower ing and d ays to p od that were moderate ( r g = 0.50; r g = 0.63). Genetic correlations calcu lated for the 10 0 selected accessions drew a more contrasting pattern with many highly positive and highly negative correlations between the traits being investigated (Figure 2 14). Negative values were observed for f lower ing to p od, s eed y ield , HI in relationship with the other traits (Figure 2 14). A negative value between two traits suggests that an increase in time period or in number of one trait has an adverse effect on the other trait, also, a positive correlation between two traits would supposedly imply that an increase in one trait would affect positively the other trait. Almost the same pattern was observed for the 6 traits measured for the UC Riverside germplasm accessions with higher values found for the selected accessions (Figure 2 14). Days to f lower ing and d ays to p ( r g = 0.86) in both dataset s, which explain how closely related those two traits are (Gerrano et al., 2015). Genetic correlations between d ays to f lower ing ; d ays to p od and s eed y ield were low negative (respectively, r g = 0.18; r g = 0.39). S imilar results were found by Aliyu and M akende (2016) (respectively, r g = 0.09; r g = 0.27) while, those values contrasted with the findings of Shimelis and Shiringani (2010) and Manggoel et al. ( 2012 ) who report ed a correlation of ( r g =

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47 0.40; r g = 0.52) between d ays to f lower ing and s eed y ield . They also contrasted with Shimelis and Shiringani (2010) report of a low positive genetic correlation ( r g = 0.30) between d ays to p od and s eed y ield . Results for HI relationships with d ays to f lower ing ( r g = 0.53) and b iomass _R 1 and b iomass_R 6 (respectively, r g = 0.25 and r g = 0.31) showed the same trend (negative correlation) as the findings of Ge r rano et al. (2015) ( r g = 0.11: d ays to f lower ing , r g = 0.55: b iomass), but, with higher negative value for d ays to f lower ing and lower negative values for b iomass. Genetic correlation between HI and s eed y ield was high positive ( r g = 0.89) which contrasted with Ge rr a n r g = 0 .14). The high positive genetic correlation between two phenotypic traits implies that breeders can easily select and improve only one desirable quantitative trait (Ge rran o et al., 2015) with positive concurrent effect to the other, thus, improving simulta neously both traits. Conclusion A selected number of accessions (56 accessions known to be resistant to RKN) from among the UC Riverside germplasm accessions was phenotyped in Haiti to assess their potential f or adapatability to the country. Although the e xperiment was impaired by a pest and disease outbreak at an early stage, data collected showed that genetic diversity exists for most traits that can be exploited for breeding purpose. The range of viral disease severity showed that breeding for viral dise ase resistance can be achieved using those plant materials. Results from the field trial in Citra, F L showed significant genetic diversity within the germplasm for most of the traits of interest. For most of the traits, the genetic variance components poi nted out high genetic contributions at the expense of environmental factors influencing plant phenotypic variability. We found traits with h igh H 2 and high positive correlations , indicating that improvement in t hose traits can be made through indirect selection , and those traits can be exploited for breeding purposes and germplasm evaluation. Several

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48 accessions outperformed the commercial cultivars in most of the quantitative traits measured. These results show that there is potential in the ge rmplasm to select for high yielding plant materials to develop dual purpose cowpea cultivars. Furthermore, the performance of the USDA PI US 1137 would make it a good candidate for forage breeding purpose while the PI US 1136, US 1138 and the cultivar Iron and Clay would best fit for dual purpose due to their high HI. Added to that, the other commercial cultivars in the trial also show potential to be exploited for some desirable traits for breeding dual purpose.

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49 Table 2 1 . Phenotypic traits characterized in cowpea. Trait Specifications Plant type Refers to the plant architecture. Plots were visually rated for plant type at flowering. Scale: 1= erect; 2 = semi erect; 3 = prostrate; 4 = climbing (vine like). Plant h eight Average plant height was measured (three plants) from the ground to the canopy level using a ruler. Unit: cm Disease severity Refers to the incidence and ag g ressiveness of viral diseases observed in the field. The plots were scored for viral disease using a scale of 0 to 10 (0 = resistant and 10 = susceptible plants). Growth h abit Refers to an indeterminate or determinate growth habit. Plots were visually rated for growth habit at flowering. Scale: 1 = indeterminate; 2 = determinate Days to f lower ing Number of days from sowing to flowering where at least one plant (10%) is blooming within a plot. Biomass_ R1 Dry shoot biomass of three plants per plot harvested at ground level at flowering stage and dried for one week at 44 ° C . Unit: k g /ha Day s to p od Number of days from sowing to flowering where at least 50% of the pods are ripening (turning from green to yellow and sun dried). Biomass_ R6 Dry shoot biomass of three plants per plot harvested at ground level at pod maturity stage (full seed) and dried for 1 week at 44°C . Unit: k g /ha Flower ing to p od Number of days from flowering date to pod maturity. Seed y ield Seed yield collected from th e three plants harvested at pod maturity stage per plot . Unit: kg /ha Harvest index T he ratio of the economic harvest (seed weight) to the total above ground biomass harvested at pod maturity (varies from 0 to 1). Table 2 2 . ANOVA table for viral disease severity visually rated in 56 cowpea genotypes in Cabaret, Haiti in the summer 2018. Sources of Variations df Sum Sq Mean Sq F value Pr(>F) Block 2 2.7 1.4 1.3 0.3 Genotype 55 148.5 2.70 2.5 2.48e 05 *** Residuals 110 119.3 1.08 Signif Table 2 3 . ANOVA table for total grain yield in 56 cowpea genotypes in Cabaret, Haiti in the summer 2018. Sources of Variations df Sum Sq Mean Sq F value Pr(>F) Block 2 3630 1815 1.6 0.2 Genotype 38 67674 1781 1.6 0.1 Residuals 46 52042 1131 81 missing values

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50 Table 2 4 . ANOVA table for 100 seeds yield in 56 cowpea genotypes in Cabaret, Haiti in the summer 2018. Sources of Variations df Sum Sq Mean Sq F value Pr(>F) Block 2 9.5 4.7 0.6 0.6 Genotype 37 384.2 10.4 1.3 0.2 Residuals 38 313.7 8.3 90 missing values Table 2 5 . Estimates of genotypic ( s 2 g ) and residual ( s 2 e ) variance components, b road sense heritability ( H 2 ), standard error (SE) of the H 2 , and Likelihood Ratio Test (LRT) for eight traits measured on 292 UC 100 selected accessions grown in Citra, FL. Whole po pulation Selected population Traits s 2 g s 2 e H 2 ±SE LRT Test s 2 g s 2 e H 2 ±SE LRT Test Plant h eight 71.45 27.78 0.67 ± 0.45 *** 50.02 27.57 0.55 ± 0.88 *** Days to f lower ing 11.01 2.93 0.72 ± 0.06 *** 15.46 2.14 0.83 ± 0.06 *** Days to p od 7.87 5.87 0.55 ± 0.15 *** 6.75 5.11 0.55 ± 0.22 *** Flower ing to p od 2.65 7.78 0.21 ± 0.13 *** 3.41 6.82 0.32 ± 0.29 *** Biomass_ R1 0.00047 0.00053 0.43 ± 0.05 *** 0.0008 0.001 0.55 ± 0.07 *** Biomass_ R6 0.0031 0.0047 0.35 ± 0.05 *** 0.003 0.01 0.26 ± 0.09 ** Seed y ield 0.001 0.001 0.56 ± 0.07 *** Harvest Index 0.01 0.003 0.70 ± 0.05 *** s 2 g : genotypic variance component s 2 e : residual variance component

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51 Figure 2 1 . Cowpea plant attacked by cowpea aphid [ Aphis craccivora , C. L. Koch, 1854] in the cowpea field experiment three weeks after sowing in Cabaret, Haiti in the summer 2018. Source: Photo courtesy of Rocheteau Dareus.

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52 Figure 2 2 . Viral disease observed (no t identified) in the cowpea field experiment three weeks after sowing in Cabaret, Haiti in the summer 2018. Source: Photo courtesy of Rocheteau Dareus.

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53 Figure 2 3 . Phenotypic characterization of cowpea germplasm for plant type, Cabaret, Haiti in summer 2018. Figure 2 4 . Bar plot of disease severity in the cowpea field experiment in Cabaret, Haiti in the summer 2018. Color code: light blue: disease score < 5; dark red: 5 disease score 8; light red: disease score > 8 37% 7% 45% 11% Erect Prostrate Semi-Erect Vine-Like 0 1 2 3 4 5 6 7 8 9 10 333 83 70 351 61 iron-Clay 199 204 338 242 272 296 322 212 237 295 297 179 205 210 220 314 201 274 294 299 57 62 64 42 46 52 4 45 Disease Score Genotypes

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54 Figure 2 5 . Phenotypic characterization of cowpea germplasm for growth habit in Citra, Florida Figure 2 6 . Phenotypic characterization of cowpea germplasm for plant type in Citra, Florida 89% 11% Indeterminate Determinate 34% 24% 10% 32% Erect Semi-erect Prostate Viny

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55 Figure 2 7 . Phenotypic characterization of cowpea germplasm for plant h eight Citra, Florida . Color code: light blue: Commercial cultivars and PI; red: UC germplasm 0 10 20 30 40 50 60 70 80 Zipper Pea White Acre Black eye Mississipi Purple Texas Cream 40 Mississipi Silver US-1136 Iron Clay US-1137 US-1138 41 347 261 270 287 145 144 105 44 344 359 260 169 212 348 108 102 269 357 40 202 158 101 378 Height (cm) Genotypes

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56 Figure 2 8 . Phenotypic characterization of cowpea germplasm for days to flower (blue arrows represent the flowering window for commercial cultivars and PI, and the red arrow highlights the late flowering accession 346), Citra, Florida.

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57 Figure 2 9 . Phenotypic characterization of cowpea germplasm for d ays to p od (red arrows represent the flowering window for commercial cultivars and PI, and the blue arrow highlights the early flowering accession 8).

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58 Figure 2 10 . Principal component analysis (PCA) of six traits using genotypic values obtained with the single year model in 302 cowpea genotypes. Cowpea accessions are shown as labeled loadings (different colors: check = c ontrols, entry = accessions, and z = others), and the traits are shown as vectors. Traits: Plant height, D ays to F lower, Biomass_ R1 = bi o mass at flowering , Days.to.Pod = days to pod maturity, Flower.to. Pod = Days from flowering to pod maturity , Biomass_ R6 = biomass at pod maturity .

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59 Figure 2 11 . Principal component analysis (PCA) of eight traits using genotypic values obtained with the single year model in 100 cowpea genotypes. Cowpea accessions are shown as labeled loadings (different colors: check = c ontrols, and entry = accessions), and the traits are shown as vectors. Traits: Plant he ight, Days to Flower, Biomass_ R1 = bi o mass at flowering, Days.to.Pod = days to pod maturity, Flower.to.Pod = Days from flowering to pod maturity, Biomass_ R6 = biomass at pod maturity, Seed Yield , Harvest Index.

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60 Figure 2 12 . Comparison between the cowpea germplas m accessions (in red) and the controls (commercial cultivars and PI in blue) for biomass (in kg for 3 harvested plants ), Citra, Florida. 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 White Acre US-1138 Iron Clay Mississipi Purple Texas Cream 43 Mississipi Silver Black eye Zipper Pea US-1136 80 322 247 384 204 51 320 158 293 160 101 202 226 355 260 375 343 29 106 377 213 US-1137 258 346 Biomass at Flowering (kg) Genotypes

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61 Figure 2 13 . Genetic correlation among six traits (lower diagonal) and stand ard error of the correlation coefficient (upper diagonal) measured in 302 cowpea accessions in Citra, FL. Trait: Plant height, Days to Flower, Biomass _R1 = bi o mass at flowering, Days.to.Pod = days to pod maturity, Flower.to.Pod = Days from flowering to pod maturity, Biomass_ R6 = biomass at pod maturity.

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62 Figure 2 14 . Genetic correlation among eight traits (lower diagonal) and standard error of the correlation coefficient (upper diagonal) measured in 100 cowpea accessions in Citra, FL. Trait: Plant height, Days to Flower, Biomass_ R 1 = bi o mass at flowering, Days.to.Pod = days to pod maturity, Flower.to.Pod = Days from flowering to pod maturity, Biomass_ R6 = biomass at pod maturity, Seed Yield , Harvest Index.

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63 CHAPTER 3 INVESTIGAT ION OF R OOT K NOT N EMATODE ( Meloidogyne spp .) RESISTANCE IN UC [ Vigna u nguiculata ( L. ) Walp ] GERMPLASM FOR BREEDING PURPOSE S Introduction Cowpea is a grain legume grown in the tropics and subtropics for its grain and fodder (Singh , 2005; Timko et al. , 2007). Cowpea production covers a large acreage worldwide (Singh et al., 1997) , and is considered a good source of income for farmers (Singh , 2002; Langyintuo et al. , 2003). ti on al values both in the diet of households and livestock (Fatokun et al., 1992). In the southern part of the United States, cowpea is used as cover crop to enhance soil fertility, grown for its grain as food for people and as forage for the cattle industry. However, i n Haiti, cowpea is used in a subsistence farming approach as a staple in intercropping systems with other crops while its residue is used as fodder for livestock. Although cowpea production is profitable, environment friendly and socially accep table ( Meloidogyne spp.) (RKN). R oot knot nematodes are known as the most devastating group of plant parasitic nematodes (Jones et al., 2013) affecting cro ps worldwide and resulting in b illions of dollars losses annually in agricultural production (Abad et al., 2008). RKN affect plant s root system and impair the normal uptake of minerals and water necessary for normal plant physiological functioning (vegetative and reproductive stages). T he root deterioration can even lead to the development of vascular diseases complexes caused by other pathogens such as Fusarium wilt ( Fusarium oxysporum f. sp . phaseoli ) and root rots (Roberts et al. , 1995). The genus Meloidogyne is the most important among RKN and is composed of about 100 species with Meloidogyne incognita ( Mi ) being considered the most prevalent species (Elling, 2013). Added to that,

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64 Meloidogyne enterolobii ( Me ) has been reported as an emerging RKN species capab le of breaking resistance in several plants genotypes known to be resistant to RKN (Brito et al., 2007; Cetintas et al., 2007; Cantu et al., 2009; Kiewnick et al., 2009; Eppo, 2011; Melo et al., 2011; Westerich et al., 2011; Castagnone Sereno, 2012; Singh et al., 2013, Diniz et al., 2016). Me has been put in quarantine in several countries due to its virulence and aggressiveness on cultivated crops (Castagnone Sereno, 2012; Elling, 2013). The multiple usage of cowpea makes it a good source of income for growers . Hence , developing dual purpose cowpea cultivars will boost the agricultural economy both in the forage and the food sector of the market . However, both in United States and in Haiti, cowpea production faces RKN damage, which is a major threat that severely affect yields. The use of chemicals (nematicides), although effective against nematodes, are costly and they may be hazardous to humans and animals. Therefore, host resistance is one of the most successful ways to control RKN under an Integrated Pest Management (IPM) approach. The use of resistant cowpea cultivars is a suitable alternative to address the problem of RKN in cowpea production both in Florida and in Haiti. M any studies have been conducted in terms of research on cowpea resistance and/ or tolerance to biotic and abiotic stresses (pests, diseases, drought, heat). However, stud ies conducted to create dual purpose cowpea cultivars which are resistant to Meloidogyne species are lacking . For this study, we hypothesized that several cowpea acc essions Mi and Me . Th e objectives of this study were to screen and select cowpea accessions that show resistan ce to M i and Me in order to use the sources of resistance to start dual purpose cowpea breeding programs.

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65 Materials and Methods Plant M aterial s The cowpea germplasm used in both screening experiments consisted of 60 accessions a c quired from the University of California R . Previous studies reve a led that 57 accessions are resistant to Mi and M eloidogyne ja vanica ( Mja ) , and three are susceptible to RKN ( P. A. Roberts et al., unpublished data ) . Additionally, c ontrols consisted of plant introduction s (PI) from the USDA GRIN ( PI 151562, PI 148681: susceptible to Mi ) ( PI 664531, PI 664532, and PI 664533 respectively for the USDA lines: US 1136, US 1137, US 1138: resistant to Mi ) , and commercial cowpea cultivars : White Acre, Black Eye d Pea , Zipper Cream GC , Texas Cream 40 , Mississi p pi Silver , Mississip p i Purple, Iron Clay , and the susceptible tomato cultivar BHN589 w ere used in the Me screening experiment . Nematode I solates The Division of Plant Industry (DPI) accession #N01 514 3B collected from Redland in Miami Dade Co was used for the Me screening and it was obtained through the Department of Nematology and Entomology , University of Florida (UF) . Howe ver, the original host is unknown . Mi inoculum was provided by the UF Nematology Lab (Dr. Peter at the Department of Nematology and Entomology, UF, and was extracted by the method of Hussey and Baker (1973). However, the origin of the strain and the host are unknown. Screening A ssay Scree n ing Mi . The Mi screening experiment was carried out in growth chambers at the Agronomy Department Weed Science Lab , University of Florida . The methodology used for this scre ening was described by Atamian et al. (2012). The experiment began on March 24, 2019 and lasted for eight weeks after inoculation. Briefly , cowpea seed s were sterilized using 10 m L of

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66 ethanol 95% for 2 minutes, rinsed, and placed in 10% bleach for 5 minute s , rinsed again a nd sown i n the top of a growth pouch (17 x 16 cm) ( HC Blue Blotter seed germination pouch , CYG TM ). The pouches were placed vertically in a rack inside a growth chamber (Seed Germination Chamber, Percival) kept at 28 ° C / 25 ° C temperature and 16 hours light/8 hours dark cycle. T wo weeks after germination, each plant was inoculated with 250 Mi 2 nd stage i nfective j uveniles (J2 s ) evenly spread over the surface of the roots. Commercial cultivars: Iron Clay, Texas Cream 40 and USDA PI US 1136 were screened as both positive and negative controls in the experiment. The plants were watered once or twice a day wi th half strength Hoagland's solution (Hoagland Modified Basal Salt Mixture [Phyotechnology Laboratories, KS: H353]) and/or water as needed. The pouches were set up in a r andomized c omplete b lock d esign (RCBD) in two growth chambers using the growth chambers as the blocking component s . Each genotype was pseudo replicated twice within each block. Screening Me . The Me experiment w as conducted in the Forage Breeding and Genetics Lab, Agronomy Department, University of Florida . The experiment began on Mar ch 29, 2019 and lasted for eight weeks after inoculation. The Me screening was carried out in a c los ed chamber at the Forage B reeding U nit of the UF . Plants were grown in cone tainers ( height: 20 cm; diameter: 4 cm) filled with sterilized sandy soil ( Quikrete Premium Play Sand , Quikrete ) . The growth room was kept at 30 ° C temperature during the whole experiment. Two weeks after germination, plants were inoculated with 250 Me 2 nd stage infective juveniles ( J2s ) using a calibrated pipette . The plants were either watered or fertilized using Scotts 10 10 10 granular fertilizer diluted before application. A RCB D was used to set up the experiment, with four replicat ions of each treatment.

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67 Data C ollection The same procedure to collect data was applied to both screening experiments. A summary of the measurement s for each response variable is provided in Table 3 1. Eight weeks after inoculation, plants were visually rated for galling response using the 0 5 gall index, with 0 (Immune), 1 (Highly resistant), 2 (Resistant), 3 (Moderately resistant), 4 (Moderately susceptible to susceptible), and 5 (Highly susceptible). Fresh weight of r oot samples was measured prior to being immersed in 10% bleach to extract nematode eggs. Eggs were collected and counted under a stereo microscope, and the number of eggs per gra m of cowpea roots was calculated. The reproduction index (RI) was calculated as follow s to assess the degree of resistance or susceptibility of each genotype (Taylor, 1967; Karuri et al., 2017): RI = the nu mber of eggs per gram of cowpea roots divided by the number of eggs per gram of susceptible control roots multiplied by 100. Plants were rated for RI as follows: RI = 0 (immune), RI < 1 (highly Karuri et al., 2017 ). Statis ti cal M odel, Assumptions and Statistical A nalysis Data from the two experiments were analyzed separately using linear mixed models ASRML v.4 (Gilmour et al., 2009) in R (R Development Core Team, 201 9 ) to detect treatment effects and their interactions for each response variable. ANOVA assumptions were tested, and square root transformation were made for response variables that did not meet the normality assumption. The following mixed model was fitted: Y= + X +Zg+e

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68 X , and Z were design matrices was the vector of block which g was the vector for random effects due to populations and e was the vector of random errors Multiple traits models were used to obtain genetic correlations among traits. The vector y i was partitioned f or a 2 trait analysis y 1 and y 2 . Thus , the bivariate model was fitted as follows for a pair of traits (i = 1 and 2): y i X i I Z i g i e i ; where y i was the vector of the two phenotypic responses; was the overall population mean for each trait; X i and Z i were design matrices for each trait, i was the vector of the fixed block effects for each trait; g i was the vector of genotypic values, with g i ~ MVN (0, G g ); and e i was the vector of random errors for each trait, with e i ~ MVN(0, D). G g represent ed a CORGH variance covariance matrix of genetic effects with a genetic correlation between traits ( r g ) and a different genetic variance for each trait; and the matrix D was a diagonal variance covariance matrix of error effects with a different variance for each trait. Results Variance C omponent E stimates and G enotypic V alues Screening Mi . All traits exhibited highly significant (P < 0.001) genetic variance, and H 2 varied from 0.60 to 0.78 (Table 3 2). Besides root fresh weight, the genotypic variance of all the

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69 traits controlled more than 70% of the total phenotypic variability observed within the accession and the calculated H 2 values were high H 2 > 0.70 (Table 3 2). Gall score varied from 1 to 4 (Figure 3 1) . From the 56 accessions known to be resistant to RKN tested, 53 showed resistance to Mi (30 highly resistant; 13 RKN resistant accessions resistant including the accession 207 (Figure 3 2 ) ; 10 moderately resis tant ) and three were susceptible (moderately susceptible to susceptible) (Figure 3 1 ) ( Appendix B ) . All the commercial cultivars, the USDA PI 115674, and the USDA PI US 1136, US 1137 and US 1138 were resistant to Mi while the PI 148681 and 151562 (Figure 3 3) were susceptible as indicated by high gall score (Figure 3 2 ). Twenty five genotypes (23 RKN resistant accessions , the USDA PI US 1138 and the commercial cultiva r Zipper Cream GC ) were found to be immune to Mi as their reproduction index (RI) was equal to 0 (Figure 3 4) ( Appendix B ) . Seven genotypes (5 RKN resistant accessions, Iron Clay and US 1136) were highly resistant: RI < 1; ten genotypes (5 RKN resistant ac cessions, commercial cultivars Mississip p i Silver and Mississippi Purple, USDA PI US 1137 and PI 115674, and resistant accessions, commercial cultivar Black Eye and susce ptible PI 148681) were moderately four RKN resistant accessions were slightly resistant to Mi < 50. Twelve genotypes ( seven RKN resistant accessions, cultivars Texas Cream 40 and White A cre, susceptible PI 151562 and, susceptible accessions 249 and 347) were found to susceptible to Mi (Figure 3 4) (Appendix B) . Some divergence was observed from the results found for gall score and RI. For instance, the susceptible accession 6 that was found to be moderately resistant with a gall score of 3, was also very resistant in regard to RI; the susceptible PI 148681 with a gall score of 4 (moderately susceptible to susceptible) was found to be moderately resistant in regard to RI; seven RKN -

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70 resistant accessions were found to be either moderately resistant (gall score = 3) or moderately susceptible to susceptible (gall score = 4) and they were all susceptible in regard to RI; the cult ivars Texas Cream 40 and White A cre that were respectively moderately resistant and resistant for their gall score were found to be susceptible with Large genetic variability was exhibited by all traits from the principal component analysis (PCA) conduct ed with data collected from the Mi screening experiment (Figure 3 5 ). The PCA associated with the accessions in the Mi screening has the first two components (PCA1 and PCA2) accounted for 91. 9 % of the total variability, thus, reflecting the more variation patterns. W ith an eigenvalue of 3.89, PCA1 accounted for 77.9% of the total variability and was influenced by the traits : gall s core, total eggs, eggs per gram of root, an d RI . T wo clear genotype clusterings were generated by PCA1 with the first cluster in the left side of the Mi biplot including the accessions 242, 294, 237, 347, 4, 249 and 126 , which were found to be susceptible to Mi . These accessions exhibited associations with RI, total eggs, eggs per gram of root and gall score , and they were the most heavily damaged by Mi . The second cluster included accessions, PI and commercial cultivars in the right side of the Mi biplot , which were found to be resistant to Mi (Figure 3 5 ). Fourteen percent of the total variability was contributed by PCA2 with an eigenvalue of 0.69 and was primarily associated with root fresh weight (Figure 3 5 ). No clear cluster was observed. Scree n ing Me . Large genetic variability was found to exist among the cowpea genotypes used in this study. All traits exhibited highly significant (P < 0.001) genetic variance, and H 2 varied from 0.22 to 0.42 (Table 3 2) . All the traits contributed genetically to less than 23% to the total observed phenotypic variability (Table 3 2). Gall score varied from 1 to 5 (Figure 3 6 ) . In the Me screening, two RKN resistant accessions were highly resistant to Me with a gall score of

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71 1 (Figure 3 7 ). Eight RKN resistant accessions were resistant. Thirty four genotypes were moderately resistant including five commercial cultivars (Iron Clay, Mississip p i Silver, Mississip p i Purple, Texas Cream 40, Zipper Cream GC ), the USDA PI US 1136, the susceptible accession 347 and 27 RKN resista nt accessions (Figure 3 6 ) ( Appendix C ) . Twenty two genotypes were moderately susceptible to susceptible including the USDA PI US 1137 and US 1138, the cultivar Black Eye, 16 RKN resistant accessions , two susceptible accessions and the tomato cultivar BHN589 (Figure 3 9) ( Appendix C ) . Two RKN resistant accessions were found to be highly susceptible (accessions 126 and 70) (Figure s 3 6 and 3 8 ). R eproduction indices calculated for the Me screening varied , w ith genotypes being very resistant to susceptible (Figure 3 9) . Three RKN four others were (Figure 3 9) . Eight genotypes were slightly resistant to Me : 25 50 including five RKN resistant accessions, the USDA PI US 1136, the susceptible tomato cultivar BHN589, and the susceptible accession 347. The remaining fifty three genotypes were all susceptible including six commercial cultivars (Iron Clay, Mississip p i Silver, Mississi p pi Purple, Zipper Cream GC , Black Eye and Texas Cream 40), the USDA PI US 1137 and US 1138, and forthy three RKN resistant accessions (Figure 3 9) (Appendix C ) . Results for gall sc ore and RI in the Me screening revealed some inconsistency for the susceptible tomato cultivar BHN589 , which was heavily galled but was found to be moderately resistant in regard to RI. The PCA analysis associated with the accessions in the Me screening experiment had the first two components (PCA1 and PCA2) account ing for 9 1.0 % of the total variability, thus, r eflecting the most variation patterns (Figure 3 10 ). The PCA1 accounted for 69.8% of the total variability (eigenvalue = 3.48) and included traits associated with total eggs, gall score, eggs per

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72 gram of root and RI. A clear genotype clustering was generat ed with the accession 126 associated with the trait total eggs (Figure 3 10 ) . The PCA2 accounted for 21.1% of the total variability with an eigenvalue of 1.05 and was associated with the trait root fresh weight. No clear genotype clust e ring was observed (F igure 3 10 ). A constrasting trend was observed from the results for all the traits analyzed where the variance components and the calculated broad sense heritabilit ies in the Mi screening experiment were high while the values were low in the Me screening e xperiment (Table 3 2 ). Plants were more heavily galled in the Me screening experiment than in the Mi screening experiment. Also, higher total number s of eggs and higher RI were observed in the Me screening experiment. Most of the RKN resistant accessions, all but two of the commercial cultivars, and all of the USDA PI showed some level of resistance to Mi while all but 12 of the RKN resistant accessions, all the commercial cultivars and the USDA PI US 1137 and US 1138 were susceptible to Me . Genetic C orrelations Screening Mi . Genetic correlations calculated for all the traits in the Mi experiment varied from r g = 0.55 to r g = 1 with strong positive correlations between most of the traits 0.91 r g 1 but only moderate correlation between root fresh weight and the other traits 0.55 r g 0.64 (Figure 3 11 ). Screening Me . In the Me screening experiment, g enetic correlations were also calculated for all the traits and varied from r g = 0.12 to r g = 1 (Figure 3 1 2 ). Correlation between r oot fresh weight and all the traits but total eggs ( r g = 0.38) was low and negative . Relationships between the other traits were moderate to highly positive 0.64 r g 1 (Figure 3 1 2 ).

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73 Discussion Phenotypic Diversity in the UC Riverside Cowpea Germplasm and Commercial Cultivars for RKN Resistance Plant materials tested in both RKN screening experiment s ( respectively Mi and Me screening s ) were genetically diverse for all traits . Genotypic variances and calculated H 2 for the Mi screening experiment were high for all traits while they were low in the Me screening experiment (Table 3 2 ). This would suggest that the total phenotypic variances obser v ed in the Mi screening experiment were controlled by genetic factors while environmen tal factors were more influen t ial on the phenotypic variability ob serv ed in the Me screening experiment. The same germplasm was used in both experiments and most of the genotypes were more heavily galled, had more eggs, and resulted in higher reproduction ind ices for Me than for Mi (Figure 3 1 3 ) indicat ing that genetic resistance is higher for Mi than Me in this germplasm. Previous reports by Jacquet et al. (2005) and Castagnone Sereno (2006) showed that h ost resistance and susceptibility are g enetically controlled . Genetic diversity was observed within each experiment among the genotypes with some lines showing different levels of resistance , and others being completely susceptible. In the Mi screening exp eriment, 53 of the 56 known resistant accessions to Mi showed resistance to Mi (gall scores : 1 to 3) as expected from previous screenings ( P. A. Roberts et al., unpublished data). The USDA PI US 1136, US 1137 and US 1138, and the cultivars Mississip p i Silver, Mississip p i Purple, Iron Clay , Zipper Cream GC exhibited high levels of resistance to RKN because they have been selected for RKN ( Fery, 2009; Harrison et al., 2014 ; and Swanson and Van G undy , 1984 ) . This suggests that those accessions may carry the same resistan t single dominant gene Rk , which is effective against three RKN species ( M . i ncognita , M . javanica, M . hapla ) (Fery and Dukes, 1980). Our findings for the USDA PI U S 1136, US 1137, US 1138 and the commercial cultivar Mississip p i Silver related to gall score (1

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74 for all the genotypes) were s imilar to the findings of Harrison et al. (2014) w ho reported gall scores varying from 1.4 to 1.7 for the same genotypes. Even though the plant materials showed similar levels of resistance from the two studies, total eggs varied significantly. From our study, total eggs for thes e three lines varied from 0 to 258 eggs per plant , w hereas Harrison reported total eggs o f 2,644 to 7,622 eggs per plant for th ese four genotypes . This may be due to the fact that the methods utiliz ed were different as we used growth pouches placed in growth chamber s greenhouse. Moreo ver, the inoculation rate may be responsible for such a difference as our inoculation rate was about 250 J2s per pouch . The USDA PI US 1138 , the commercial cultivar Zipper Cream GC , and 23 RKN resistant accessions had a RI of 0 (immune) , meaning no eggs were found even though the had some galls in duc ed by female Mi . This may be explained by the findings from studies conducted by Das et al. (2008) where Rk resistance was involved in preventing the Mi females from develo p ping and reproduc ing rather than blocking root penetration by infective J2s. Different levels of resistance were found for 26 RKN resistant accessions which is related to their genetic s (Fery and Dukes, 1980). Only 10 RKN resistant accessions were highly resistant (2) and resistant (8) based on gall score ; while three accessions were very resistant and four moderately resistant to Me based on RI . These accessions can be considered as good source of resistance to Me to exploit in breeding programs . Based on gall score, 18 RKN resistant accessions were susceptible to Me and 43 based on RI. Those findings confirm the findings of other studies suppor ting the tendency for Me to break resistance in known RKN resistant crop cultivars (Brito et al., 2007; C etintas et al., 2007; Cantu et al., 2009; Kiewnick et al., 2009; Eppo, 2011; Melo et al., 2011; Westerich et al., 2011;

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75 Castagnone Sereno, 2012; Singh et al., 2013, Diniz et al., 2016). Inconsistencies in this study for some of the genotypes and their unu sual behavior in regard to their resistance or susceptibility may be due to the nematode isolate used in the study as the same plant material may react differently from one isolate to another one in the same nematode species (Wang and McSorley, 2004). The PCA analys es conducted for both experiments demonstrated genetic variability for the traits as the evaluated accessions were scattered within the four quadrants of the biplot s (Figures 3 5 ; 3 10 ) (Ge rr a n o et al., 2015). Two clusters were clearly identified in the Mi biplot and only one in the Me biplot suggesting that there are genetic similarities among the genotypes within a cluster (Ge rran o et al., 2015). Most of the resistant genotypes are located o n the ri ght side of the Mi biplot highlightin g their low gall score and RI and thus their resistance , while genotypes are scattered throughout the quadrants of the Me biplot showing a mixed response to Me infection. Trait Correlations for RKN Resistance High positive correlation s w ere found between most pair s of traits in the Mi screening (Figure 3 11 ) and the H 2 calculated for those traits were also high (Table 3 2). Rios et al. ( unpublished paper ) stated that t raits that are highly correlated and have high heritability allow breeders to genetically improve both traits by making phenotypic selection in only one trait. Furthermore, traits with high genetic correlations are useful in breeding purposes. Phenotyping of one trait can allow the estimation of the other trait as they are highl y correlated. This would decrease the amount of work required for phenotyping both traits. Hence, as total eggs and egg s per gram of roots are highly correlated to RI, selection could be made for RI using either total eggs or eggs per gram of root . In the Me screening, the low negative correlation between root fresh weight and the other traits would suggest that an increase in root biomass leads to a

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76 decrease of the nematode reproduction factors. Strong correlation between gall score and RI is supported by findings of Roberts et al. (1998) , which indicate that root ga lling is generally highly correlated with nematode reproduction. Conclusion s Known RKN resistant plant materials (5 6 ) selected from th e UC Ri collection were used to be screened for resistance to Mi and Me with the goal of select ing the best perform ing plant materials as sources of resistances to be exploited in dual purpose cowpea breeding programs. Genotypic variances found from the two experiments were highly significant ( P < 0.001). Results from the Mi experiment showed strong relationships between the traits and high H 2 . More than 90% of the accessions were effectively resistant to Mi, meaning that the resistance of those lines to Mi is genetically controlled and can be exploited for breeding purposes. However, results from the Me experiment showed that 43 of the resistant accessions were susceptible confirming the potential for that RK N species to break resistance in know n resistant plant materials. A few accessions showed some level of resistance , which seems to be promising but results showed low genotypic variances for the traits that were analyzed in the Me experiment. Therefore, fu rther research should be conducted with those accessions to verify the level of their resistance and to make progress by using novel breeding tech n iques to increase their genetic gain.

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77 Table 3 1 . Phenotypic and quantitative traits investigated in the Me a nd Mi screening s of cowpea germplasm . Trait Specifications Gall Score Scale of 0 to 5 used to visually rate the cowpea root systems for galls: 0 (immune) = no galls; 1 (highly resistant) = very few and tiny galls observed on lateral roots covering less than 10% of the root system, tap root is intact; 2 (resistant) = tiny galls on lateral roots covering 15% to 25% of the root system, tap root is intact; 3 (moderately r esistant) = a mixed of tiny and medium sized galls on tap root and lateral roots covering 30% to 50% of the root system; 4 (moderately susceptible to susceptible) = a mixed of tiny, medium sixed and big galls covering 51% to 75% of the root system; 5 (high ly susceptible) = a mixed of tiny, medium sized and big galls covering 75% to 100% of the root system with big galls on the tap root. Total eggs T otal number of eggs extracted per plant and counted under a stereo microscope. Root fresh weight T otal root biomass in grams (g). Eggs per gram of root N umber of eggs per gram of root. It was calculated as the total number of eggs extracted in one plant divided by the root fresh weight. Reproduction Index RI = the number of eggs per gram of root divided by the number of eggs per gram of susceptible control roots multiplied by 100. The best susceptible control was used based on their average eggs count for each experiment. RI = 0 (immune), RI < 1 (highly resist (susceptible) Table 3 2 . Estimates of genotypic ( s 2 g ) and residual ( s 2 e ) variance components, broad sense heritability ( H 2 ), standard error (SE) of the H 2 , and likelihood ratio test (LRT) for five traits measured on 56 UC Riverside germplasm accessions known to be resistant to Mi and Mja . z Traits Mi screening Me screening s 2 g s 2 e H 2 ±SE LRT Test s 2 g s 2 e H 2 ±SE LRT Test Gall Score 0.90 0.36 0.71 ± 0.05 *** y 0.25 0.85 0.23 ± 0.08 *** Total eggs 14.26 4.05 0.78 ± 0.09 *** 10.65 38.30 0.22 ± 0.77 *** Root fresh weight 0.13 0.09 0.60 ± 0.06 *** 0.16 0.22 0.42 ± 0.08 *** Eggs gram 1 root 8.06 2.62 0.75 ± 0.07 *** 3.53 12.65 0.22 ± 0.29 *** Reproduction Index 0.93 0.36 0.72 ± 0.05 *** 0.25 0.90 0.22 ± 0.08 *** z s 2 g : genotypic variance component, s 2 e : residual variance component y

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78 Figure 3 1 . Mean gall score of cowpea accessions infected with Meloidogyne incognita in growth pouches in a growth chamber study. Color code: dark blue gall score 1; light blue: 1< gall score 2; green: 2 < gall score 3; orange: gall score > 3 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 Iron Clay-NC Texas Cream 40-NC US-1136-NC 51 205 45 338 26 42 Mississipi Silver US-1136 US-1138 58 Iron Clay US-1137 53 158 Mississipi Purple 8 297 Zipper Pea 333 White Acre 207 PI 115674 274 299 96 111 199 Black eye Texas Cream 40 4 242 PI 148681 126 PI 151562 Gall score Genotypes

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79 Figure 3 2 . View of the root system of root knot nematode resistant cowpea accession 207 at eight weeks after being infected with M eloidogyne i ncognita . Source: Photo courtesy of Rocheteau Dareus.

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80 Figure 3 3 . View of the root system of the susceptible US Department of Agriculture accession PI151562 at eight weeks after inoculation with Meloidogyne incognita . Source: Photo courtesy of Rocheteau Dareus.

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81 Figure 3 4 . Mean RI of cowpea accessions infected with Meloidogyne incognita in growth pouches in a growth chamber study. Color code: Blank: RI = 0 (immune); dark blue : RI < 1 (highly resistant); light blue: ; green: (moderately resistant) ; orange: ly resistant) ; (susceptible) 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 US-1138 58 204 Zipper Pea 53 Iron Clay US-1136 US-1137 PI 115674 Mississipi Silver Mississipi Purple 297 112 206 Black eye 314 PI 148681 8 201 210 274 220 322 111 4 294 Texas Cream 40 207 White Acre PI 151562 126 347 Reproduction Index Scores Genotypes

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82 Figure 3 5 . Principal component analysis (PCA) of five traits in the Meloidogyne incognita screening using genotypic values obtained with the single year model in 56 root knot nematode resistant cowpea accessions. Cowpea accessions are shown as labeled loadings (different colors: check = Controls and, RKNR = UC accessions, Susceptib le = controls), and the traits are shown as vectors. Traits: G all S core, T otal E ggs, Eggs.gr.rt = E ggs per gram of root, RI = reproduction index , R oot_FW = root fresh weight .

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83 Figure 3 6 . Mean gall scores of cowpea accessions infected with Meloidogyne en terolobii grown in cone tainers in controlled room. Color code: dark blue gall score 1; light blue: 1< gall score 2; green: 2 < gall score 3; orange: 3 < gall score 4; red: gall score > 4. 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 45 338 193 46 58 53 56 83 201 297 322 26 52 Mississipi Purple Zipper Pea 347 Iron Clay Texas Cream 40 US-1136 Mississipi Silver 64 US-1138 61 6 135 US-1137 8 Black eye 249 BHN589 126 70 Gall score Genotypes

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84 A) B) Figure 3 7 . View of the root knot nematode resistant accessions 45 and 338 showing high levels of resistance to Meloidogyne enterolobii both for gall score and RI . Source: Photo courtesy of Rocheteau Dareus.

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85 Figure 3 8 . View of large galls induced by Meloidogyne enterolobii on the roots of the root knot nematode resistant accession 70. Source: Photo courtesy of Rocheteau Dareus.

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86 Figure 3 9 . Mean RI of cowpea accessions infected with Meloidogyne incognita in growth pouches in a growth chamber study. Color code: dark blue: resistant) ; light blue: (slightly resistant); a 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 338 45 53 193 179 58 51 BHN589 US-1136 111 201 46 Zipper Pea Mississipi Purple 322 70 42 299 US-1137 297 158 Black eye 295 55 Mississipi Silver 52 294 Iron Clay 112 US-1138 274 57 143 135 333 Texas Cream 40 Reproduction Index Scores Genotypes

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87 Figure 3 10 . Principal component analysis (PCA) of five traits in the Meloidogyne enterolobii screening using genotypic values obtained with the single year model in 56 root knot nematode resistant cowpea accessions. Cowpea acce ssions are shown as labeled loadings (different colors: check = Controls and, RKNR = accessions, Susceptible = controls), and the traits are shown as vectors. Traits: Gall Score, Total Eggs, Eggs.gr.rt = Eggs per gram of root, RI = reproduction index, Root _FW = root fresh weight.

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88 Figure 3 11 . Genetic correlation among five traits (lower diagonal) and standard error of the correlation coefficient (upper diagonal) measured in root knot nematode resistant cowpea accessions for resistance to Meloidogyne incognita in growth chambers. Traits: Gall Score, Total Eggs, Eggs.gr.root = Eggs per gram of root, RI = Reproduction Index, Root Fresh Weight.

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89 Figure 3 1 2 . Genetic correlation among five traits (lower diagonal) and standard error of the correlation coefficient (upper diagonal) measured in root knot nematode resistant cowpea accessions for resistance to Meloidogyne enterolobii in controlled room. Traits: Gall Score, Total Eggs, Eggs.gr.root = Eggs per gram of root, RI = Reproduction Index, Root Fresh Weight.

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90 A) B) Figure 3 1 3 . From left to right, cowpea root system of the same genotype infected with Meloidogyne enterolobii (in cone tainer) and M. incognita (in growth pouch) showing bigger galls on the M. enterolobii infected root system, small root length and biomass compared to the M. incognita infected plant. Source: Photo courtesy of Rocheteau Dareus

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91 APPENDIX A PREDICTED VALUES OF SIX MEASURED TRAITS Table A 1. List of the predicted values of six measured traits . Type Genotype Biomass Yield_R1 Plant Height Biomass Yield_R6 Days to Flower Days to Pod Flower to Pod entry 1 0.14 43.22 0.31 38.34 67.88 28.47 entry 3 0.15 43.04 0.32 34.37 66.75 29.44 entry 4 0.16 33.93 0.33 40.75 71.89 29.33 entry 5 0.15 35.34 0.26 43.16 71.33 28.00 entry 6 0.15 31.49 0.29 42.65 71.59 28.58 entry 7 0.14 43.70 0.28 40.26 68.27 27.86 entry 8 0.14 25.02 0.20 34.79 59.76 25.51 entry 13 0.17 47.82 0.33 41.15 69.65 28.24 entry 14 0.13 46.18 0.27 36.09 67.14 29.27 entry 20 0.14 33.71 0.33 42.76 70.55 27.85 entry 21 0.16 44.04 0.32 41.37 69.15 27.84 entry 23 0.13 43.30 0.29 37.21 67.22 28.72 entry 24 0.18 53.15 0.39 44.27 70.71 27.16 entry 25 0.14 41.97 0.36 43.39 68.74 26.87 entry 26 0.17 43.88 0.37 44.41 71.55 27.68 entry 27 0.17 34.14 0.45 47.02 71.90 26.96 entry 28 0.17 44.04 0.34 42.61 68.38 27.16 entry 29 0.19 38.26 0.37 42.62 71.42 28.27 entry 30 0.18 42.84 0.32 39.96 70.46 29.13 entry 31 0.15 47.37 0.30 35.92 67.99 29.44 entry 32 0.15 47.61 0.33 41.82 69.70 28.12 entry 33 0.13 39.57 0.27 37.25 66.02 27.97 entry 34 0.17 45.22 0.35 40.50 71.46 29.40 entry 35 0.16 49.97 0.30 41.82 68.89 27.83 entry 36 0.19 49.88 0.36 39.79 67.73 27.94 entry 37 0.17 51.44 0.35 40.48 68.77 27.86 entry 38 0.16 45.62 0.38 42.85 71.47 28.01 entry 39 0.16 44.33 0.35 42.04 67.79 26.98 entry 40 0.18 56.81 0.37 42.94 70.73 27.99 entry 41 0.17 52.00 0.34 42.10 68.31 27.78 entry 42 0.14 34.96 0.29 41.41 70.99 29.25 entry 43 0.17 42.35 0.31 41.76 68.11 26.96 entry 44 0.18 53.82 0.32 43.20 69.00 26.88 entry 45 0.12 39.45 0.32 36.44 71.60 31.41 entry 46 0.15 46.44 0.28 39.83 71.18 29.40

PAGE 92

92 Table A 1. Continued Type Genotype Biomass Yield_R1 Plant Height Biomass Yield_R6 Days to Flower Days to Pod Flower to Pod entry 47 0.13 48.01 0.25 36.11 63.23 26.64 entry 48 0.16 42.75 0.29 39.14 67.95 28.22 entry 49 0.15 40.81 0.32 45.93 73.35 27.96 entry 50 0.13 40.12 0.31 35.93 67.71 29.45 entry 51 0.17 39.01 0.32 43.84 71.43 28.19 entry 52 0.15 42.59 0.29 43.00 68.88 26.95 entry 53 0.17 40.85 0.32 40.46 71.50 29.51 entry 54 0.14 45.40 0.31 41.03 68.10 27.07 entry 55 0.14 41.83 0.27 41.36 67.70 26.94 entry 56 0.13 37.94 0.37 36.46 68.95 29.92 entry 57 0.17 44.69 0.29 42.91 71.73 28.39 entry 58 0.15 40.11 0.28 42.25 71.10 28.59 entry 59 0.15 47.91 0.34 40.13 71.75 29.78 entry 60 0.16 45.36 0.32 38.89 68.46 28.79 entry 61 0.14 38.48 0.28 39.52 67.78 27.85 entry 62 0.12 36.90 0.25 37.85 67.80 28.66 entry 63 0.16 47.27 0.31 42.38 71.13 28.24 entry 64 0.16 44.25 0.36 40.71 70.68 28.99 entry 66 0.15 37.45 0.28 41.93 71.61 29.14 entry 67 0.14 45.09 0.29 36.57 66.87 28.82 entry 69 0.16 49.72 0.32 40.85 71.13 29.15 entry 70 0.13 44.92 0.25 36.57 67.03 28.68 entry 71 0.18 39.59 0.39 42.82 73.21 29.28 entry 72 0.16 33.84 0.35 45.00 71.33 27.67 entry 73 0.16 44.86 0.32 39.29 71.87 29.70 entry 74 0.16 50.22 0.47 45.66 73.35 28.05 entry 75 0.14 31.35 0.27 40.36 71.06 29.60 entry 76 0.16 55.57 0.33 43.50 71.77 28.12 entry 77 0.16 41.01 0.33 41.77 70.71 28.31 entry 78 0.16 38.36 0.27 42.94 71.65 28.45 entry 79 0.16 29.48 0.24 44.29 71.47 27.97 entry 80 0.17 40.67 0.32 40.85 68.35 27.73 entry 81 0.16 40.93 0.31 43.33 71.46 28.28 entry 82 0.16 44.04 0.32 41.37 69.15 27.84 entry 83 0.15 41.30 0.30 42.17 70.35 28.19 entry 85 0.14 49.66 0.32 36.19 68.08 29.26 entry 86 0.14 38.68 0.31 43.60 71.68 28.33 entry 87 0.15 52.20 0.31 37.74 67.07 28.41 entry 88 0.17 48.75 0.32 40.94 69.84 28.40

PAGE 93

93 Table A 1. Continued Type Genotype Biomass Yield_R1 Plant Height Biomass Yield_R6 Days to Flower Days to Pod Flower to Pod entry 91 0.15 30.58 0.34 45.59 71.38 27.02 entry 92 0.17 35.21 0.34 39.85 69.15 28.51 entry 94 0.16 44.00 0.35 42.79 71.72 28.30 entry 95 0.14 43.09 0.34 37.04 68.14 29.13 entry 96 0.14 42.99 0.29 39.85 68.51 28.25 entry 97 0.16 30.48 0.30 40.05 67.11 27.56 entry 98 0.13 40.30 0.26 36.72 63.45 26.83 entry 99 0.16 36.20 0.31 41.41 71.70 28.67 entry 101 0.17 55.16 0.36 42.53 71.69 28.57 entry 102 0.16 57.90 0.39 45.99 71.56 26.76 entry 103 0.15 50.95 0.31 38.02 67.23 28.31 entry 104 0.14 58.11 0.38 45.61 71.26 27.03 entry 105 0.18 54.15 0.35 44.53 71.74 27.66 entry 106 0.19 50.40 0.38 40.50 66.82 27.10 entry 108 0.18 60.02 0.40 42.38 68.13 26.62 entry 109 0.15 53.38 0.37 43.73 67.77 25.98 entry 110 0.18 48.63 0.29 40.28 67.01 27.37 entry 111 0.17 53.81 0.30 42.13 67.05 26.08 entry 112 0.15 46.79 0.39 36.90 68.68 29.61 entry 113 0.14 42.95 0.36 37.29 67.77 28.85 entry 117 0.16 48.74 0.33 41.08 71.73 29.37 entry 119 0.16 49.18 0.37 40.06 70.45 28.97 entry 120 0.18 46.43 0.33 40.83 67.24 27.03 entry 121 0.14 45.93 0.30 42.19 71.39 28.94 entry 122 0.17 39.61 0.39 41.83 68.25 27.05 entry 123 0.16 50.60 0.31 38.87 66.97 27.78 entry 124 0.14 45.42 0.30 38.29 66.99 28.10 entry 125 0.16 54.63 0.34 41.43 68.38 27.37 entry 126 0.15 37.05 0.28 42.03 66.75 26.03 entry 127 0.16 40.11 0.31 43.96 69.11 27.04 entry 128 0.16 37.06 0.28 43.51 68.19 26.50 entry 129 0.15 37.61 0.30 38.15 64.59 26.69 entry 131 0.17 41.04 0.34 43.84 68.47 26.56 entry 134 0.15 54.41 0.36 43.77 71.96 28.32 entry 135 0.15 52.85 0.26 40.11 64.17 25.78 entry 136 0.16 42.77 0.30 42.01 70.57 28.42 entry 137 0.13 47.80 0.31 37.40 65.79 27.84 entry 138 0.14 37.39 0.26 36.67 63.63 26.87 entry 139 0.16 41.98 0.28 39.94 67.05 27.29

PAGE 94

94 Table A 1. Continued Type Genotype Biomass Yield_R1 Plant Height Biomass Yield_R6 Days to Flower Days to Pod Flower to Pod entry 140 0.18 45.95 0.37 42.05 67.09 26.39 entry 141 0.15 43.08 0.35 44.77 72.61 27.97 entry 142 0.15 44.60 0.27 42.59 70.39 27.66 entry 143 0.16 45.41 0.29 43.74 70.37 27.57 entry 144 0.14 50.92 0.30 36.64 66.60 28.65 entry 145 0.16 54.23 0.34 40.11 67.92 27.78 entry 146 0.13 49.37 0.26 34.03 63.58 27.83 entry 147 0.14 45.41 0.30 37.16 67.98 29.11 entry 149 0.16 38.66 0.38 41.32 71.27 29.17 entry 155 0.15 47.65 0.36 42.71 71.87 28.47 entry 156 0.16 42.51 0.29 43.03 67.76 26.45 entry 158 0.18 59.50 0.37 46.62 72.24 27.22 entry 159 0.16 44.99 0.32 42.25 71.25 28.69 entry 160 0.18 48.31 0.36 43.82 68.18 26.34 entry 161 0.16 40.20 0.33 41.82 68.86 27.42 entry 162 0.16 31.21 0.23 42.21 67.75 26.57 entry 166 0.17 43.55 0.31 42.78 67.19 26.33 entry 167 0.18 42.61 0.38 39.93 67.19 27.25 entry 169 0.16 56.97 0.34 43.80 70.73 27.71 entry 172 0.15 32.15 0.27 41.13 67.12 26.94 entry 173 0.16 38.81 0.28 41.46 67.93 27.07 entry 174 0.18 52.17 0.33 39.85 67.03 27.18 entry 175 0.13 47.39 0.30 41.99 71.49 28.95 entry 176 0.14 47.32 0.30 39.70 67.75 28.07 entry 178 0.17 49.64 0.31 42.53 70.71 27.84 entry 179 0.13 41.39 0.31 36.41 66.68 28.99 entry 180 0.15 44.61 0.38 36.71 70.41 30.16 entry 181 0.16 39.59 0.27 41.82 71.32 28.79 entry 182 0.14 39.24 0.27 37.10 67.73 29.14 entry 183 0.17 39.61 0.28 40.40 71.47 29.52 entry 184 0.16 44.04 0.32 41.37 69.15 27.84 entry 188 0.16 34.43 0.31 43.40 67.88 26.06 entry 189 0.15 53.32 0.36 43.51 71.45 28.13 entry 190 0.17 50.59 0.33 46.05 71.39 26.85 entry 191 0.16 38.60 0.30 41.39 68.86 27.55 entry 192 0.14 42.51 0.34 36.80 67.39 28.80 entry 193 0.15 52.32 0.31 42.21 68.82 27.11 entry 194 0.15 30.71 0.25 39.83 69.04 28.58 entry 196 0.17 27.06 0.31 42.07 68.00 27.30

PAGE 95

95 Table A 1. Continued Type Genotype Biomass Yield_R1 Plant Height Biomass Yield_R6 Days to Flower Days to Pod Flower to Pod entry 197 0.14 45.45 0.29 34.62 65.72 28.85 entry 198 0.13 26.04 0.28 41.43 67.16 26.49 entry 199 0.14 32.54 0.33 43.58 70.72 27.76 entry 201 0.14 36.24 0.29 43.05 68.16 26.53 entry 202 0.18 60.37 0.37 40.30 66.69 26.82 entry 204 0.17 38.56 0.29 43.48 72.86 28.70 entry 205 0.14 40.61 0.34 42.07 70.36 28.38 entry 206 0.15 42.69 0.26 41.92 67.78 26.72 entry 207 0.14 40.49 0.28 40.89 66.99 26.93 entry 208 0.15 54.26 0.32 41.58 67.18 26.74 entry 209 0.16 42.50 0.36 46.21 71.50 26.88 entry 210 0.18 41.19 0.30 43.15 69.78 27.49 entry 211 0.17 41.95 0.34 43.23 71.22 28.23 entry 212 0.19 58.51 0.39 44.83 73.18 28.18 entry 213 0.20 51.90 0.35 45.60 71.74 27.29 entry 214 0.16 54.29 0.32 39.42 68.14 28.12 entry 215 0.12 39.35 0.23 37.66 62.86 26.52 entry 216 0.17 36.38 0.28 43.59 68.16 26.47 entry 218 0.15 49.43 0.31 43.91 70.85 27.49 entry 219 0.14 32.07 0.27 42.96 70.66 27.69 entry 220 0.17 48.63 0.35 44.12 71.76 27.91 entry 221 0.15 43.92 0.34 43.56 71.73 28.25 entry 222 0.15 44.84 0.32 41.57 68.20 27.17 entry 223 0.16 53.41 0.32 40.36 71.69 29.62 entry 224 0.14 39.67 0.27 37.66 63.58 26.73 entry 225 0.17 50.57 0.36 43.40 70.68 27.39 entry 226 0.17 42.12 0.29 42.49 72.31 28.81 entry 227 0.15 47.65 0.32 34.55 71.57 31.81 entry 228 0.14 42.43 0.26 34.85 63.51 27.30 entry 231 0.14 41.57 0.30 37.15 66.96 28.47 entry 232 0.17 58.84 0.34 41.50 70.68 28.45 entry 233 0.14 42.06 0.26 39.89 63.62 25.50 entry 234 0.17 43.62 0.29 39.72 67.94 28.02 entry 235 0.13 50.58 0.32 35.76 64.90 27.93 entry 236 0.15 57.01 0.31 42.10 69.04 27.46 entry 237 0.15 48.04 0.30 41.70 68.02 26.98 entry 238 0.16 45.17 0.32 41.17 70.88 28.62 entry 239 0.17 47.97 0.34 41.72 67.70 26.86 entry 242 0.18 51.04 0.40 43.76 71.63 27.73

PAGE 96

96 Table A 1. Continued Type Genotype Biomass Yield_R1 Plant Height Biomass Yield_R6 Days to Flower Days to Pod Flower to Pod entry 243 0.15 35.72 0.27 44.96 68.90 26.41 entry 247 0.17 31.43 0.31 45.33 71.79 27.34 entry 248 0.20 55.57 0.38 44.74 73.34 28.60 entry 249 0.17 47.32 0.32 41.20 67.75 27.10 entry 251 0.17 48.32 0.38 42.29 71.36 28.72 entry 253 0.14 26.99 0.28 45.76 68.84 25.79 entry 254 0.16 45.57 0.36 42.03 68.64 27.17 entry 256 0.15 36.09 0.29 42.25 71.96 28.96 entry 257 0.16 35.92 0.31 41.59 70.72 28.62 entry 258 0.19 41.58 0.44 43.81 71.42 27.58 entry 259 0.16 52.47 0.37 44.99 71.31 27.10 entry 260 0.19 57.00 0.40 40.81 68.25 27.40 entry 261 0.17 52.52 0.44 45.05 71.75 27.74 entry 264 0.13 43.87 0.26 35.97 67.13 29.07 entry 266 0.14 38.54 0.27 41.59 70.70 28.57 entry 267 0.19 50.67 0.31 42.42 71.11 28.47 entry 268 0.17 41.30 0.34 47.56 73.15 27.18 entry 269 0.17 59.64 0.38 43.40 69.61 27.11 entry 270 0.18 53.61 0.35 43.73 70.67 27.98 entry 271 0.15 40.49 0.32 39.02 67.90 28.34 entry 272 0.16 50.30 0.28 43.55 68.93 26.78 entry 273 0.17 39.47 0.28 40.81 68.87 27.96 entry 274 0.13 49.87 0.26 42.17 67.03 26.27 entry 275 0.17 36.60 0.31 41.76 68.65 27.36 entry 277 0.14 31.92 0.27 42.91 68.70 26.64 entry 278 0.15 43.82 0.31 39.32 69.72 29.12 entry 287 0.17 53.50 0.31 41.82 71.62 28.42 entry 288 0.16 40.28 0.34 43.00 70.56 27.80 entry 292 0.17 42.50 0.42 45.71 72.81 27.89 entry 293 0.17 42.18 0.38 45.44 71.53 27.15 entry 294 0.16 45.97 0.34 43.21 68.83 27.01 entry 295 0.16 42.62 0.31 41.11 68.82 27.90 entry 296 0.18 40.81 0.29 41.67 67.71 26.87 entry 297 0.17 48.24 0.32 42.94 67.75 26.44 entry 298 0.16 30.25 0.31 42.09 68.21 27.16 entry 299 0.17 40.80 0.30 39.98 67.00 26.95 entry 302 0.15 26.30 0.26 44.95 70.74 27.03 entry 303 0.15 42.28 0.30 43.25 68.68 26.78 entry 305 0.13 42.76 0.25 33.61 62.97 27.90

PAGE 97

97 Table A 1. Continued Type Genotype Biomass Yield_R1 Plant Height Biomass Yield_R6 Days to Flower Days to Pod Flower to Pod entry 307 0.17 42.09 0.35 42.85 68.18 26.75 entry 308 0.16 54.32 0.31 41.71 68.07 26.70 entry 310 0.16 34.20 0.36 47.09 72.86 27.09 entry 311 0.18 31.26 0.34 43.36 71.60 28.17 entry 313 0.16 30.47 0.29 40.91 68.12 27.40 entry 314 0.14 22.60 0.27 39.93 67.43 27.74 entry 315 0.17 58.29 0.41 44.93 71.57 27.24 entry 316 0.17 27.66 0.35 43.98 68.38 26.42 entry 317 0.17 27.00 0.33 43.53 67.10 25.79 entry 320 0.17 43.89 0.36 43.18 71.92 28.68 entry 322 0.17 26.11 0.28 41.69 68.62 27.35 entry 323 0.16 37.40 0.31 41.44 68.66 27.54 entry 329 0.18 42.80 0.30 40.88 67.66 27.24 entry 330 0.15 51.87 0.32 42.73 68.66 26.94 entry 333 0.16 47.08 0.32 42.47 68.83 27.45 entry 334 0.13 40.04 0.31 36.55 66.78 28.36 entry 335 0.13 42.23 0.25 37.18 63.31 26.06 entry 336 0.15 39.37 0.28 43.84 70.91 27.74 entry 338 0.15 41.41 0.31 40.75 68.48 27.97 entry 339 0.15 48.43 0.34 44.29 70.38 27.06 entry 340 0.17 43.23 0.39 47.23 73.72 27.60 entry 341 0.16 45.74 0.30 41.87 71.62 28.78 entry 342 0.15 46.11 0.32 43.06 71.74 28.32 entry 343 0.19 45.57 0.43 40.99 68.22 27.38 entry 344 0.14 52.28 0.32 42.50 71.42 27.94 entry 345 0.15 48.80 0.30 38.90 67.16 28.08 entry 346 0.24 48.96 0.32 62.86 69.15 27.84 entry 347 0.16 52.31 0.33 42.97 70.70 27.88 entry 348 0.18 56.11 0.33 41.98 71.77 29.00 entry 350 0.17 41.35 0.30 45.27 71.53 27.21 entry 351 0.13 40.62 0.26 36.19 63.26 26.93 entry 352 0.18 48.02 0.33 41.03 68.73 27.90 entry 353 0.16 46.04 0.31 40.19 66.99 26.88 entry 354 0.19 49.83 0.34 41.07 67.05 26.87 entry 355 0.18 51.04 0.37 42.07 70.74 28.80 entry 356 0.15 44.42 0.33 41.52 68.37 27.28 entry 357 0.16 59.26 0.34 43.49 70.26 27.31 entry 358 0.18 50.16 0.35 45.59 70.39 26.78 entry 359 0.15 56.21 0.32 41.11 69.49 28.15

PAGE 98

98 Table A 1. Continued Type Genotype Biomass Yield_R1 Plant Height Biomass Yield_R6 Days to Flower Days to Pod Flower to Pod entry 360 0.17 29.62 0.33 40.82 71.71 28.59 entry 361 0.16 44.16 0.30 42.32 68.82 27.29 entry 362 0.12 35.38 0.23 37.57 63.50 26.47 entry 363 0.14 42.60 0.32 36.65 67.77 29.08 entry 366 0.15 50.15 0.31 41.90 69.31 27.66 entry 368 0.15 53.43 0.39 40.27 67.91 27.66 entry 369 0.14 34.27 0.34 35.98 67.84 29.22 entry 371 0.17 48.79 0.31 43.08 69.05 26.89 entry 372 0.12 51.91 0.27 37.11 67.78 28.99 entry 373 0.16 44.16 0.31 40.54 70.72 29.07 entry 374 0.15 35.32 0.29 37.14 68.24 28.99 entry 375 0.19 37.64 0.35 42.63 67.94 26.75 entry 377 0.20 46.00 0.35 44.02 71.43 28.14 entry 378 0.13 64.66 0.33 35.07 64.68 28.30 entry 379 0.14 53.25 0.30 34.66 64.47 28.27 entry 380 0.16 48.51 0.36 42.67 68.83 27.31 entry 383 0.15 47.53 0.33 43.51 69.13 27.06 entry 384 0.17 45.04 0.35 42.09 71.57 28.80 entry 385 0.17 37.78 0.35 43.51 71.78 28.33 entry 386 0.17 28.38 0.31 39.67 72.35 30.21 entry 388 0.15 43.48 0.28 41.39 66.78 26.48 entry 389 0.14 48.20 0.30 36.65 65.92 27.86 entry 390 0.15 42.00 0.29 39.40 66.97 27.74 check 391 0.13 47.25 0.26 42.89 73.01 30.24 check 392 0.14 45.24 0.40 43.17 72.11 29.01 check 393 0.13 49.30 0.30 42.58 71.98 29.21 check 394 0.11 36.12 0.24 41.64 72.11 30.73 check 395 0.16 35.75 0.31 43.02 72.12 29.06 check 396 0.14 41.68 0.32 39.47 69.32 29.87 check 397 0.14 55.27 0.37 41.12 68.14 27.60 check 398 0.17 50.55 0.35 39.79 67.84 27.69 check 399 0.24 53.66 0.50 49.45 75.18 25.93 check 400 0.13 53.41 0.36 38.23 67.84 30.56

PAGE 99

99 APPENDIX B RAW DATA OF GALL SCORE AND REPRODUCTION INDEX IN THE M . Incognita SCREENING Table B 1. Gall score and reproduction index per genotype in the M. incognita screening . block type genotype gall_score RI 1 RKNR 4 3 10.34 1 RKNR 4 4 96.69 1 entry 6 2 1.34 1 entry 6 4 9.58 1 RKNR 8 1 31.95 1 RKNR 8 2 0.00 1 RKNR 26 1 0.00 1 RKNR 26 1 0.38 1 RKNR 42 1 0.00 1 RKNR 42 NA NA 1 RKNR 45 1 0.00 1 RKNR 45 1 0.00 1 RKNR 46 1 0.00 1 RKNR 46 NA NA 1 RKNR 49 1 0.00 1 RKNR 49 1 0.00 1 RKNR 51 0 0.00 1 RKNR 51 1 0.76 1 RKNR 52 1 0.00 1 RKNR 52 2 0.00 1 RKNR 53 1 0.00 1 RKNR 53 2 0.00 1 RKNR 54 1 0.00 1 RKNR 54 1 0.00 1 RKNR 55 0 0.00 1 RKNR 55 1 0.00 1 RKNR 56 1 0.00 1 RKNR 56 1 0.00 1 RKNR 57 1 0.00 1 RKNR 57 1 0.00 1 RKNR 58 1 0.00 1 RKNR 58 1 0.00 1 RKNR 61 0 0.00 1 RKNR 61 0 0.00

PAGE 100

100 Table B 1. Continued block type genotype gall_score RI 1 RKNR 62 1 0.00 1 RKNR 62 NA NA 1 RKNR 64 1 0.00 1 RKNR 64 1 0.00 1 RKNR 69 1 0.00 1 RKNR 69 1 0.00 1 RKNR 70 1 0.00 1 RKNR 70 1 0.00 1 RKNR 72 1 0.00 1 RKNR 72 1 0.00 1 RKNR 83 1 0.00 1 RKNR 83 1 0.00 1 RKNR 96 2 7.62 1 RKNR 96 3 24.54 1 RKNR 111 3 51.91 1 RKNR 111 3 76.94 1 RKNR 112 2 8.03 1 RKNR 112 2 22.10 1 RKNR 123 0 0.00 1 RKNR 123 1 0.00 1 RKNR 126 4 145.98 1 RKNR 126 4 220.27 1 RKNR 135 1 0.00 1 RKNR 135 2 9.07 1 RKNR 143 1 0.00 1 RKNR 143 1 3.72 1 RKNR 158 1 1.28 1 RKNR 158 2 18.03 1 RKNR 179 1 0.00 1 RKNR 179 1 0.00 1 RKNR 193 1 0.00 1 RKNR 193 1 0.00 1 RKNR 199 3 35.09 1 RKNR 199 3 204.79 1 RKNR 201 2 26.96 1 RKNR 201 4 48.26 1 RKNR 204 1 0.00 1 RKNR 204 2 0.00

PAGE 101

101 Table B 1. Continued block type genotype gall_score RI 1 RKNR 205 1 0.00 1 RKNR 205 NA NA 1 RKNR 206 1 0.00 1 RKNR 206 4 48.81 1 RKNR 207 1 36.44 1 RKNR 207 3 156.05 1 RKNR 210 3 33.30 1 RKNR 210 4 35.64 1 RKNR 212 2 0.00 1 RKNR 212 2 1.24 1 RKNR 219 1 0.00 1 RKNR 219 2 4.07 1 RKNR 220 3 50.50 1 RKNR 220 4 56.50 1 RKNR 237 4 125.78 1 RKNR 237 4 113.82 1 RKNR 242 3 118.68 1 RKNR 242 4 91.18 1 entry 249 4 100.14 1 entry 249 4 56.74 1 RKNR 272 1 0.00 1 RKNR 272 NA NA 1 RKNR 274 3 16.24 1 RKNR 274 3 56.53 1 RKNR 294 3 45.50 1 RKNR 294 3 119.61 1 RKNR 295 1 17.68 1 RKNR 295 2 21.99 1 RKNR 296 1 13.17 1 RKNR 296 3 38.54 1 RKNR 297 1 7.07 1 RKNR 297 2 7.82 1 RKNR 299 3 138.81 1 RKNR 299 4 128.71 1 RKNR 314 1 11.38 1 RKNR 314 1 15.41 1 RKNR 322 1 26.75 1 RKNR 322 2 86.38

PAGE 102

102 Table B 1. Continued block type genotype gall_score RI 1 RKNR 333 1 14.65 1 RKNR 333 3 25.54 1 RKNR 338 0 0.00 1 RKNR 338 1 0.59 1 entry 347 2 11.17 1 entry 347 4 502.62 1 RKNR 351 1 0.00 1 RKNR 351 1 38.50 1 Check Black eye 3 20.44 1 Check Black eye 3 31.40 1 Check Iron Clay 1 0.00 1 Check Iron Clay 1 0.72 1 Check Iron Clay NC 0 0.00 1 Check Iron Clay NC 0 0.00 1 Check Mississipi Purple 1 0.00 1 Check Mississipi Purple 1 13.65 1 Check Mississipi Silver 1 7.38 1 Check Mississipi Silver NA NA 1 entry PI 115674 1 0.00 1 entry PI 115674 3 0.00 1 entry PI 148681 4 23.58 1 entry PI 148681 4 40.57 1 entry PI 151562 3 75.73 1 entry PI 151562 4 124.27 1 Check Texas Cream 40 3 50.47 1 Check Texas Cream 40 3 196.66 1 Check Texas Cream 40 NC 0 0.00 1 Check Texas Cream 40 NC NA NA 1 Check US 1136 1 1.00 1 Check US 1136 1 1.72 1 Check US 1136 NC 0 0.00 1 Check US 1136 NC 0 0.00 1 Check US 1137 1 1.31 1 Check US 1137 2 0.00 1 Check US 1138 1 0.00 1 Check US 1138 1 0.00 1 Check White Acre 1 20.99 1 Check White Acre 3 238.06

PAGE 103

103 Table B 1. Continued block type genotype gall_score RI 1 Check Zipper Pea 1 0.00 1 Check Zipper Pea 2 0.00 2 entry 4 3 7.04 2 entry 4 4 42.27 2 entry 6 1 0.00 2 entry 6 3 1.17 2 entry 8 2 5.92 2 entry 8 2 34.67 2 entry 26 1 0.00 2 entry 26 1 0.47 2 entry 42 1 0.00 2 entry 42 1 0.00 2 entry 45 0 0.00 2 entry 45 1 0.00 2 entry 46 1 0.00 2 entry 46 1 0.00 2 entry 49 0 0.00 2 entry 49 1 0.00 2 entry 51 0 0.00 2 entry 51 1 0.00 2 entry 52 0 0.00 2 entry 52 1 0.00 2 entry 53 1 0.22 2 entry 53 2 0.00 2 entry 54 NA NA 2 entry 54 NA NA 2 entry 55 1 0.00 2 entry 55 1 0.00 2 entry 56 1 0.00 2 entry 56 NA NA 2 entry 57 1 0.00 2 entry 57 1 0.00 2 entry 58 1 0.00 2 entry 58 2 0.00 2 entry 61 1 0.00 2 entry 61 1 0.00 2 entry 62 1 0.00 2 entry 62 NA NA

PAGE 104

104 Table B 1. Continued block type genotype gall_score RI 2 entry 64 1 0.00 2 entry 64 1 0.00 2 entry 69 1 0.00 2 entry 69 1 0.00 2 entry 70 1 0.00 2 entry 70 1 0.00 2 entry 72 1 0.00 2 entry 72 NA NA 2 entry 83 1 0.00 2 entry 83 NA NA 2 entry 96 3 5.70 2 entry 96 3 20.66 2 entry 111 2 1.01 2 entry 111 3 3.21 2 entry 112 2 0.00 2 entry 112 2 10.63 2 entry 123 1 0.00 2 entry 123 1 0.00 2 entry 126 3 5.41 2 entry 126 4 40.51 2 entry 135 2 6.60 2 entry 135 3 4.98 2 entry 143 1 0.00 2 entry 143 2 4.47 2 entry 158 1 0.00 2 entry 158 2 0.00 2 entry 179 1 0.00 2 entry 179 1 0.00 2 entry 193 1 0.00 2 entry 193 1 0.00 2 entry 199 3 5.07 2 entry 199 3 6.66 2 entry 201 2 7.57 2 entry 201 3 6.73 2 entry 204 1 0.00 2 entry 204 1 0.00 2 entry 205 0 0.00 2 entry 205 1 0.00

PAGE 105

105 Table B 1. Continued block type genotype gall_score RI 2 entry 206 1 0.00 2 entry 206 1 2.71 2 entry 207 2 12.12 2 entry 207 3 59.53 2 entry 210 3 2.72 2 entry 210 3 20.58 2 entry 212 1 0.30 2 entry 212 2 0.41 2 entry 219 1 2.01 2 entry 219 2 3.01 2 entry 220 2 1.09 2 entry 220 3 12.83 2 entry 237 2 6.94 2 entry 237 3 22.72 2 entry 242 3 21.81 2 entry 242 4 18.21 2 entry 249 3 42.45 2 entry 249 4 41.56 2 entry 272 1 0.00 2 entry 272 1 0.00 2 entry 274 2 4.01 2 entry 274 2 18.25 2 entry 294 3 10.42 2 entry 294 3 47.21 2 entry 295 1 1.63 2 entry 295 2 12.17 2 entry 296 2 2.05 2 entry 296 2 2.73 2 entry 297 2 1.22 2 entry 297 2 7.87 2 entry 299 1 2.29 2 entry 299 2 3.52 2 entry 314 1 6.60 2 entry 314 2 33.10 2 entry 322 1 0.59 2 entry 322 1 14.41 2 entry 333 2 2.95 2 entry 333 2 10.22

PAGE 106

106 Table B 1. Continued block type genotype gall_score RI 2 entry 338 1 0.00 2 entry 338 1 0.51 2 entry 347 3 13.03 2 entry 347 4 5.31 2 entry 351 1 12.59 2 entry 351 2 4.83 2 Check Black eye 3 2.86 2 Check Black eye 3 8.45 2 Check Iron Clay 1 0.00 2 Check Iron Clay 2 1.02 2 Check Iron Clay NC 0 0.00 2 Check Iron Clay NC 0 0.00 2 Check Mississipi Purple 2 0.33 2 Check Mississipi Purple 2 2.39 2 Check Mississipi Silver 1 0.39 2 Check Mississipi Silver 1 1.38 2 entry PI 115674 1 1.39 2 entry PI 115674 4 9.36 2 entry PI 148681 3 0.00 2 entry PI 148681 3 5.35 2 entry PI 151562 4 57.02 2 entry PI 151562 4 142.98 2 Check Texas Cream 40 3 7.09 2 Check Texas Cream 40 4 5.91 2 Check Texas Cream 40 NC 0 0.00 2 Check Texas Cream 40 NC 0 0.00 2 Check US 1136 1 0.00 2 Check US 1136 1 0.59 2 Check US 1136 NC 0 0.00 2 Check US 1136 NC 0 0.00 2 Check US 1137 1 0.77 2 Check US 1137 1 2.24 2 Check US 1138 1 0.00 2 Check US 1138 1 0.00 2 Check White Acre 2 2.68 2 Check White Acre 2 4.72 2 Check Zipper Pea 2 0.00 2 Check Zipper Pea 2 0.00

PAGE 107

107 APPENDIX C DATA OF GALL SCORE AND REPRODUCTION INDEX IN THE M . Enterolobii SCREENING Table C 1. Gall score and reproduction index per genotype in the M. enterolobii screening . Rep Type genotype gall_score RI 1 entry 4 4 232.56 2 entry 4 4 32.55 3 entry 4 4 61.57 4 entry 4 5 255.66 4 entry 6 3 54.95 1 entry 6 4 279.02 2 entry 6 4 161.89 3 entry 6 4 149.72 1 entry 8 2 69.58 2 entry 8 4 505.80 3 entry 8 5 15.37 4 entry 8 5 139.78 1 entry 26 2 28.00 2 entry 26 3 128.82 4 entry 26 3 498.16 3 entry 26 4 461.21 1 entry 42 4 153.19 3 entry 42 4 25.13 2 entry 42 NA NA 4 entry 42 NA NA 2 entry 45 1 6.18 3 entry 45 1 6.50 1 entry 45 NA NA 4 entry 45 NA NA 1 entry 46 2 70.74 4 entry 46 2 30.93 2 entry 46 NA NA 3 entry 46 NA NA 3 entry 51 1 0.00 4 entry 51 2 1.55 1 entry 51 3 71.67 2 entry 51 NA NA 2 entry 52 3 124.68 1 entry 52 NA NA

PAGE 108

108 Table C 1. Continued block type genotype gall_score RI 3 entry 52 NA NA 4 entry 52 NA NA 1 entry 53 2 9.34 3 entry 53 2 9.34 4 entry 53 3 9.20 2 entry 53 NA NA 1 entry 54 2 25.71 2 entry 54 NA NA 3 entry 54 NA NA 4 entry 54 NA NA 4 entry 55 2 25.78 1 entry 55 4 264.80 3 entry 55 4 40.42 2 entry 55 NA NA 2 entry 56 2 22.40 4 entry 56 3 42.82 1 entry 56 NA NA 3 entry 56 NA NA 1 entry 57 3 226.98 4 entry 57 3 62.36 2 entry 57 NA NA 3 entry 57 NA NA 3 entry 58 1 0.00 1 entry 58 2 6.19 2 entry 58 3 36.46 4 entry 58 3 29.19 2 entry 61 3 121.85 3 entry 61 4 93.82 4 entry 61 4 12.00 1 entry 61 NA NA 1 entry 62 2 45.05 2 entry 62 2 2.63 3 entry 62 4 32.97 4 entry 62 4 174.21 1 entry 64 3 176.01 4 entry 64 4 190.28 2 entry 64 NA NA 3 entry 64 NA NA

PAGE 109

109 Table C 1. Continued block type genotype gall_score RI 1 entry 69 3 36.25 4 entry 69 3 72.16 2 entry 69 NA NA 3 entry 69 NA NA 4 entry 70 5 82.62 1 entry 70 NA NA 2 entry 70 NA NA 3 entry 70 NA NA 1 entry 72 3 125.46 4 entry 72 3 128.91 2 entry 72 NA NA 3 entry 72 NA NA 3 entry 83 1 0.00 2 entry 83 2 34.68 1 entry 83 3 31.96 4 entry 83 4 44.95 1 entry 96 3 180.41 2 entry 96 3 128.81 4 entry 96 3 92.41 3 entry 96 5 113.82 1 entry 111 3 32.52 4 entry 111 3 47.69 2 entry 111 NA NA 3 entry 111 NA NA 1 entry 112 3 370.49 4 entry 112 3 23.73 2 entry 112 4 54.44 3 entry 112 4 56.88 1 entry 123 1 0.00 2 entry 123 1 2.06 4 entry 123 2 49.52 3 entry 123 4 286.72 4 entry 126 4 146.14 1 entry 126 5 550.99 2 entry 126 5 295.59 3 entry 126 5 248.83 2 entry 135 1 4.27 1 entry 135 4 344.61

PAGE 110

110 Table C 1. Continued block type genotype gall_score RI 3 entry 135 5 291.95 4 entry 135 5 575.05 1 entry 143 4 239.17 3 entry 143 4 323.06 2 entry 143 NA NA 4 entry 143 NA NA 1 entry 158 3 85.83 2 entry 158 3 82.09 4 entry 158 3 134.70 3 entry 158 4 115.02 1 entry 179 2 8.20 2 entry 179 2 28.11 4 entry 179 2 6.56 3 entry 179 NA NA 4 entry 193 1 16.25 1 entry 193 2 2.88 2 entry 193 NA NA 3 entry 193 NA NA 4 entry 199 2 73.59 1 entry 199 3 767.20 2 entry 199 3 39.30 3 entry 199 4 238.13 3 entry 201 2 29.26 1 entry 201 3 63.20 2 entry 201 3 33.61 4 entry 201 NA NA 1 entry 204 3 280.26 4 entry 204 4 37.25 2 entry 204 NA NA 3 entry 204 NA NA 2 entry 205 1 0.00 4 entry 205 2 179.14 3 entry 205 3 41.22 1 entry 205 4 156.63 1 entry 206 2 65.85 4 entry 206 3 101.08 3 entry 206 4 88.51 2 entry 206 NA NA

PAGE 111

111 Table C 1. Continued block type genotype gall_score RI 1 entry 207 1 299.67 2 entry 207 3 223.88 3 entry 207 3 451.26 4 entry 207 3 74.67 4 entry 210 2 19.28 1 entry 210 4 805.89 2 entry 210 4 151.65 3 entry 210 5 543.53 2 entry 212 3 218.12 1 entry 212 4 456.86 3 entry 212 4 78.43 4 entry 212 4 274.95 1 entry 219 3 65.62 2 entry 219 3 64.86 4 entry 219 3 47.94 3 entry 219 NA NA 1 entry 220 3 86.27 2 entry 220 3 74.30 3 entry 220 3 30.73 4 entry 220 5 608.97 1 entry 237 3 151.75 2 entry 237 3 106.33 3 entry 237 3 20.42 4 entry 237 NA NA 2 entry 242 3 187.38 1 entry 242 4 66.50 3 entry 242 4 62.48 4 entry 242 4 305.45 2 entry 249 3 100.00 1 entry 249 4 100.00 3 entry 249 5 100.00 4 entry 249 5 100.00 2 entry 272 1 13.21 1 entry 272 4 183.42 3 entry 272 4 65.49 4 entry 272 4 112.57 4 entry 274 2 61.22 1 entry 274 3 177.65

PAGE 112

112 Table C 1. Continued block type genotype gall_score RI 2 entry 274 3 140.57 3 entry 274 3 195.23 2 entry 294 2 45.16 3 entry 294 2 7.63 4 entry 294 3 123.77 1 entry 294 4 325.86 4 entry 295 2 29.24 2 entry 295 3 78.18 3 entry 295 3 89.65 1 entry 295 4 225.77 1 entry 296 1 12.92 2 entry 296 3 135.14 3 entry 296 3 54.07 4 entry 296 4 45.58 2 entry 297 1 0.33 3 entry 297 3 257.32 4 entry 297 3 76.54 1 entry 297 4 76.55 4 entry 299 2 25.99 1 entry 299 4 205.48 3 entry 299 4 46.46 2 entry 299 NA NA 1 entry 314 3 478.51 3 entry 314 3 326.03 2 entry 314 4 168.31 4 entry 314 4 23.73 3 entry 322 2 27.88 1 entry 322 3 80.06 2 entry 322 3 70.08 4 entry 322 3 143.65 2 entry 333 3 63.74 3 entry 333 3 91.32 4 entry 333 3 277.75 1 entry 333 4 1107.31 2 entry 338 1 15.15 3 entry 338 1 0.58 4 entry 338 1 0.00 1 entry 338 2 3.29

PAGE 113

113 Table C 1. Continued block type genotype gall_score RI 1 entry 347 3 31.70 2 entry 347 3 19.99 3 entry 347 3 35.02 4 entry 347 4 45.38 3 entry 351 3 78.27 1 entry 351 4 721.46 2 entry 351 4 393.50 4 entry 351 4 82.23 1 Check BHN589 4 23.46 3 Check BHN589 4 7.17 4 Check BHN589 4 70.40 2 Check BHN589 5 29.89 1 Check Black eye 4 168.21 2 Check Black eye 4 104.33 4 Check Black eye 4 44.48 3 Check Black eye NA NA 4 Check Iron Clay 2 50.59 1 Check Iron Clay 3 210.71 2 Check Iron Clay 4 86.17 3 Check Iron Clay 4 154.98 3 Check Mississipi Purple 2 0.00 2 Check Mississipi Purple 3 117.97 4 Check Mississipi Purple 3 42.72 1 Check Mississipi Purple 4 153.05 3 Check Mississipi Silver 2 0.00 1 Check Mississipi Silver 4 96.49 4 Check Mississipi Silver 4 249.91 2 Check Mississipi Silver NA NA 3 Check Texas Cream 40 1 12.43 2 Check Texas Cream 40 3 209.02 1 Check Texas Cream 40 4 20.43 4 Check Texas Cream 40 5 1607.64 1 Check US 1136 3 35.63 3 Check US 1136 3 48.47 4 Check US 1136 3 16.51 2 Check US 1136 4 44.07 4 Check US 1137 3 34.71 1 Check US 1137 4 231.87

PAGE 114

114 Table C 1. Continued block type genotype gall_score RI 2 Check US 1137 4 81.07 3 Check US 1137 4 61.68 2 Check US 1138 3 62.00 4 Check US 1138 3 14.62 1 Check US 1138 4 292.33 3 Check US 1138 4 190.01 4 Check Zipper Pea 1 0.00 1 Check Zipper Pea 3 19.66 2 Check Zipper Pea 5 135.46 3 Check Zipper Pea NA NA

PAGE 115

115 APPENDIX D UC RIVERSIDE MINI CORE COLLECTION INFORMATION Table D 1. List of the accessions used in the current study, their PI numbers, origins, . Accessi on # Accession name PI Number Country of origen Cultivar name Biological status of accession 1 1393 1 2 3( ) USA Breeding 2 24 125 B 1 Cameroon Breeding 3 524 B USA Breeding 4 58 53 Senegal Landrace 5 58 57 Senegal Landrace 6 Apagbaala Ghana Breeding 7 Bambey 21 Senegal Breeding 8 Bun 22 Ghana Ghana Landrace 10 Cameroon 12 58 Cameroon 11 Cameroon 7 29 Cameroon 12 CB27 USA Breeding 13 CB3 USA Breeding 14 CB46 USA Breeding 16 CB50 USA Breeding 17 CC 110 1 USA Breeding 18 CC 36 USA Breeding 19 CC 85 2 USA Breeding 20 China 501 China Landrace 21 CRSP Niebe Cameroon 22 Danila Nigeria Landrace 23 Early Scarlet USA Breeding 24 Ecute Mozambiq ue Landrace 25 Faef 14 Inhaca E Mozambiq ue Landrace 26 FN 1 13 04 Mozambiq ue Landrace 27 FN 1 14 04 Mozambiq ue Landrace 28 FN 2 11 04 Mozambiq ue Landrace 29 FN 2 13 04 Mozambiq ue Landrace 30 French Bean Thailand Breeding 31 Gorda Puerto Rico Breeding 32 IAR7/8 4 5 1 Nigeria Breeding

PAGE 116

116 Table D 1. Continued Accession # Accession name PI Number Country of origen Cultivar name Biological status of accession 33 Ife Brown Nigeria Breeding 34 INIA 120 Mozambiq ue Landrace 35 INIA 31 Mozambiq ue Landrace 36 INIA 34 Mozambiq ue Landrace 37 INIA 40 Mozambiq ue Landrace 38 INIA 41 Mozambiq ue Landrace 39 INIA 5E Mozambiq ue Landrace 40 INIA 72 Mozambiq ue Landrace 41 Iron Clay USA Breeding 42 IT00K 901 6 Nigeria Breeding 43 IT82E 18 Nigeria Breeding 44 IT83D 442 Nigeria Breeding 45 IT84S 2049 Nigeria Breeding 46 IT84S 2246 Nigeria Breeding 47 IT85F 867 5 Nigeria Breeding 48 IT86D 364 Nigeria Breeding 49 IT89KD 288 Nigeria Breeding 50 IT93K 452 1 Nigeria Breeding 51 IT93K 503 1 Nigeria Breeding 52 IT95K 1093 5 Nigeria Breeding 53 IT95K 1105 5 Nigeria Breeding 54 IT95K 1479 Nigeria Breeding 55 IT95K 1491 Nigeria Breeding 56 IT95M 190 Nigeria Breeding 57 IT96D 610 Nigeria Breeding 58 IT97K 207 15 Nigeria Breeding 59 IT97K 207 21 Nigeria Breeding 60 IT97K 461 4 Nigeria Breeding 61 IT97K 499 35 1 1 Nigeria Songotra Breeding 62 IT97K 499 39 1 1 Nigeria Breeding 63 IT97K 556 6 Nigeria Breeding 64 IT97K 569 9 Nigeria Breeding 66 IT98D 1399 Nigeria Breeding

PAGE 117

117 Table D 1. Continued Accession # Accession name PI Number Country of origen Cultivar name Biological status of accession 67 IT98K 1111 1 Nigeria Breeding 69 IT98K 128 4 Nigeria Breeding 70 IT98K 205 8 Nigeria Breeding 71 IT98K 428 2 Nigeria Breeding 72 IT98K 498 1 Nigeria Breeding 73 IT98K 555 1 Nigeria Breeding 74 IT98K 589 2 Nigeria Breeding 75 IT99K 124 5 Nigeria Breeding 76 KVx 396 4 5 20 Burkina Faso Breeding 77 KVx 403 P 20 T Burkina Faso Breeding 78 KVx 421 25 Burkina Faso Breeding 79 KVx 442 3 Burkina Faso Breeding 80 KVx 525 Burkina Faso Breeding 81 KVx61 1 1 Burkina Faso Breeding 82 Lori Niebe Cameroon Breeding 83 Lyg 321 2 USA Breeding 84 Massava 11 Mozambiq ue Landrace 85 Melakh Senegal Breeding 86 Montiero Brazil Landrace 87 Mougne Senegal Breeding 88 Mouride Senegal Breeding 89 Moussa Local Senegal Breeding 90 Muinana Lawe Mozambiq ue Landrace 91 NamuesseD Mozambiq ue Landrace 92 N'diambour Senegal Breeding 93 Nhacoongo 1 Mozambiq ue Landrace 94 Nhacoongo 3 Mozambiq ue Landrace 95 Pakau Senegal Breeding 96 Prima Nigeria Breeding

PAGE 118

118 Table D 1. Continued Accession # Accession name PI Number Country of origen Cultivar name Biological status of accession 97 Sanzi Ghana Landrace 98 SASAQUE Japan Breeding 99 Suvita 2 Burkina Faso Landrace 100 Tete 2 Mozambiq ue Landrace 101 Timbawene Moteado Mozambiq ue Landrace 102 TVu 1000 PI 579279 Ghana VARIEGATED 103 TVu 1004 PI 579282 USA MISC 51 104 TVu 10100 Colombia P 6 Landrace 105 TVu 1016 USA PARAGUAY 1 Breeding 106 TVu 10179 India P 773 Landrace 107 TVu 10281 Benin KABA KOUDEGOU NO.4 Landrace 108 TVu 1036 PI 579306 USA EARLY RED Breeding 109 TVu 10366 India EX TVU 7181 Landrace 110 TVu 1037 PI 579307 USA INST. 0154 111 TVu 10466 Burkina Faso Landrace 112 TVu 10513 Nigeria TVX 5882 O4E (FROM GLIP) Breeding 113 TVu 1059 PI 579322 USA HIB CANELS Breeding 114 TVu 10892 India EX GANIGUNTA Landrace 115 TVu 1124 Nigeria NGALO BUL Landrace 116 TVu 113 Uganda SVS 140 117 TVu 12565 India APC 44 Landrace 118 TVu 12710 PI 581720 India APC 336 Landrace 119 TVu 12746 PI 581750 India APC 410 Landrace 120 TVu 1280 PI 579467 Tanzania NO. 24 121 TVu 12804 PI 581804 India APC 535 Landrace 122 TVu 12873 PI 581869 India APC 676 Landrace 123 TVu 12897 PI 581886 India APC 735 Landrace 124 TVu 12923 PI 581909 India APC 790 Landrace 125 TVu 12937 PI 581921 India APC 821 Landrace 126 TVu 12968 India APC 890 Landrace 127 TVu 13017 PI 581992 Madagasc ar EX TANANARIVE MARKET Landrace 128 TVu 132 Uganda V.U. 9

PAGE 119

119 Table D 1. Continued Accession # Accession name PI Number Country of origen Cultivar name Biological status of accession 129 TVu 1330 PI 579479 Uganda MAKERERE SEL. 1 Breeding 130 TVu 13305 Zambia NEW ERA GREY Landrace 131 TVu 13388 Burkina Faso KVU 71 Landrace 132 TVu 13463 PI 582222 Kenya OM 07 Landrace 133 TVu 13485 PI 582244 Kenya EX SIAYA Landrace 134 TVu 13778 Brazil CuCx 177 8W Breeding 135 TVu 13939 Botswana B164 Landrace 136 TVu 13950 Botswana B301 Landrace 137 TVu 13958 USSR K579 Landrace 138 TVu 13965 USSR K1090 Landrace 139 TVu 13968 USSR K1115 Landrace 140 TVu 13979 USSR K1311 Landrace 141 TVu 14172 Nigeria IT81D 1020 Breeding 142 TVu 14190 Nigeria IT84D 449 Breeding 143 TVu 14195 Nigeria IT84S 2246 4 Breeding 144 TVu 14224 Botswana B 024B Landrace 145 TVu 14248 Botswana B 067A Landrace 146 TVu 14253 Botswana B 076 Landrace 147 TVu 14272 Botswana B 171 Landrace 148 TVu 14321 Botswana B 343 Landrace 149 TVu 14336 Senegal AG86 2 Landrace 150 TVu 14345 Senegal AG86 12 Landrace 151 TVu 14346 Senegal AG86 29 Landrace 152 TVu 14393 Senegal AG86 125 Landrace 153 TVu 14401 Senegal AG86 149 Landrace 154 Tvu 14533 Mali AO86 25 Landrace 155 TVu 14621 Mali ILCA 12734 Landrace 156 TVu 14632 Central African Republic AG 122 Landrace 157 TVu 14633 Central African Republic AG 129 Landrace 158 TVu 14691 Botswana B 278A Landrace 159 TVu 14759 Botswana B 432 Landrace 160 TVu 1477 PI 579558 Mali IR 58 67

PAGE 120

120 Table D 1. Continued Accession # Accession name PI Number Country of origen Cultivar name Biological status of accession 161 TVu 14862 China WAN QING JIANG Landrace 162 TVu 14875 China ZHN CHENG QING TIAO DOU JIAO Landrace 163 TVu 14949 Niger AO87N 143 Weedy 164 TVu 14970 Niger AO87N 165 Landrace 165 TVu 14971 Niger AO87N 166 Landrace 166 TVu 15114 Malawi AG87M 247 Landrace 167 TVu 15143 Malawi AG87M 361 Landrace 168 TVu 15315 Chad PS87CH 456 Landrace 169 TVu 1536 Turkey PI 175959 170 TVu 15391 Lesotho BEREA VILLAGE Landrace 171 TVu 15400 Lesotho HA KORANTA Landrace 172 TVu 15411 Lesotho HARABOLILANE VILLAGE Landrace 173 TVu 15426 Lesotho TSIKOANE VILLAGE Landrace 174 TVu 15445 Swaziland PS88S 216 Landrace 175 TVu 15500 Burkina Faso KVX 60 K26 2 Breeding 176 TVu 1556 Nigeria PI 189374 177 TVu 15591 Niger SABO GIDA (SE MADAONA) Landrace 178 TVu 15610 Nigeria IT82D 709 Breeding 179 TVu 15636 Nigeria IT84S 2049 Breeding 180 TVu 15639 Nigeria IT83S 797 Breeding 181 TVu 15653 Nigeria IT86F 2062 5 Breeding 182 TVu 15661 Nigeria IT86D 1038 Breeding 183 TVu 15687 Nigeria IT86D 719 Breeding 184 TVu 15775 Nigeria IT85F 1992 Breeding 185 TVu 1583 Nigeria PI 255785 187 TVu 15861 Yemen HR90 2 Landrace 188 TVu 15878 Ghana GH 2288 Landrace 189 TVu 15926 Oman OM 7099 Landrace 190 TVu 15973 Botswana B 030A Landrace 191 TVu 15995 Botswana B 228 Landrace 192 TVu 1609 PI 579627 USA DIXIE LEE Breeding 193 TVu 16220 Italy MG 110849 Landrace 194 TVu 16237 Italy MG 113247 Landrace

PAGE 121

121 Table D 1. Continued Accession # Accession name PI Number Country of origen Cultivar name Biological status of accession 196 TVu 16269 Italy MG 113783 Landrace 197 TVu 16278 Italy MG 113794 Landrace 198 TVu 16304 Italy MG 113838 Landrace 199 TVu 16368 Benin RB89 533 Landrace 200 TVu 1637 Puerto Rico PI 339564 Landrace 201 TVu 16403 Benin DAMADAMI (LOCAL) Landrace 202 TVu 16408 Benin KPODJI NOIR Landrace 203 TVu 16449 Australia NI 148 204 TVu 16465 Nigeria IT86D 716 Breeding 205 TVu 16504 Nigeria IT90K 77 Breeding 206 TVu 16505 Nigeria IT90K 76 Breeding 207 TVu 16521 Guinea GIN89 30 Landrace 208 TVu 16574 Guinea GIN89 573 Landrace 209 TVu 16594 ILCA 9329 210 TVu 1715 PI 579683 USA BLACKEYE NO 1239 Breeding 211 TVu 1727 PI 579685 USA SHIRO Breeding 212 TVu 1775 PI 579701 Paraguay PYTA Landrace 213 TVu 1780 Japan TURU NASHI WASE SASAGE Landrace 214 TVu 1811 Puerto Rico PI 170962 Landrace 215 TVu 1886 Pakistan LUBIYA Landrace 216 TVu 1916 Iran PI 146113 Landrace 217 TVu 201 USA CALIFORNIA BLACK EYE 5A(VITA1) Breeding 218 TVu 21 PI 582520 Philippine s SITAO BUSH 219 TVu 2168 PI 579903 220 TVu 2280 Peru BOCANEGRA Landrace 221 TVu 2322 PI 179555 Turkey PI 179555 Landrace 222 TVu 2398 Iran LOBIA Landrace 223 TVu 2418 PI 250587 United Arab Emirates PI 250587 Landrace 224 TVu 2449 PI 271258 India PI 271258 Landrace 225 TVu 2548 USA JACKSON ALABAMA Breeding

PAGE 122

122 Table D 1. Continued Accession # Accession name PI Number Country of origen Cultivar name Biological status of accession 226 TVu 264 USA TEXAS PURPLE HULL 49 Breeding 227 TVu 2680 Nigeria PI 189103 Landrace 228 TVu 2723 India NO. 1 Landrace 229 TVu 2736 India 954/A Landrace 231 TVu 2845 India PI 352998 Landrace 232 TVu 2933 PI 353088 India PI 353088 Landrace 233 TVu 2968 India PI 353124 Landrace 234 TVu 2971 PI 353127 India PI 353127 Landrace 235 TVu 3043 PI 353204 India PI 353204 Landrace 236 TVu 3076 PI 353240 India PI 353240 Landrace 237 TVu 3156 India PI 353326 Landrace 238 TVu 3282 PI 354503 India PI 354503 Landrace 239 TVu 3360 India PI 354594 Landrace 240 TVu 3552 PI 354857 India PI 354857 Landrace 241 TVu 3565 India PI 354873 Landrace 242 TVu 3652 PI 579985 Australia SUBS. SESQUIPEDALIS Landrace 243 TVu 3657 PI 579988 China SUBS. CYLINDRICA Landrace 244 TVu 3804 PI 447554 Nigeria KR149 A Landrace 245 TVu 3817 PI 447566 Nigeria KR162 Landrace 246 TVu 3830 PI 447579 Nigeria INTROGRESSION Weedy 247 TVu 3842 Nigeria WEEDY Weedy 248 TVu 393 PI 579094 USA TAYLOR BLUE GOOSE Breeding 249 TVu 3947 Nigeria EX EJULE Landrace 250 TVu 3965 PI 447647 Nigeria KR257 Landrace 251 TVu 408 USA 1 C 2238C 252 TVu 4097 Nigeria KR379 Landrace 253 TVu 415 USA OHAWA MOTTLED Breeding 254 TVu 43 PI 578931 Nigeria II V 5 6 Landrace 255 TVu 4316 Nigeria KR462 Landrace 256 TVu 4535 PI 580011 Nigeria IF H144 1 Breeding 257 TVu 4545 PI 406293 Nigeria IF H 62 1 1 Breeding 258 TVu 4557 Nigeria IF H 53 1 Breeding 259 TVu 456 PI 579128 USA C 5714 9 260 TVu 4622 Tanzania SVS 190 Landrace 261 TVu 4632 Tanzania I.V.S. 6121 Landrace

PAGE 123

123 Table D 1. Continued Accession # Accession name PI Number Country of origen Cultivar name Biological status of accession 262 TVu 4669 Niger KR491 Landrace 263 TVu 467 PI 579134 Mauritania MAURITIUS A Breeding 264 TVu 4711 PI 448054 Niger KR497 Landrace 265 TVu 4984 Niger KR539 Landrace 266 TVu 53 Nigeria C 20 41 Landrace 267 TVu 5444 PI 448658 Nigeria KR607 Landrace 268 TVu 6356 USA PREVIOUS TVU 240 2 Landrace 269 TVu 6365 USA PREVIOUS TVU 298 2 Landrace 270 TVu 6439 South Africa PREVIOUS TVU 911 2 Landrace 271 TVu 6464 PI 580132 Uganda PREVIOUS TVU 1177 2 Landrace 272 TVu 6477 PI 580134 Suriname PREVIOUS TVU 1268 2 Landrace 273 TVu 6493 PI 580143 South Africa PREVIOUS TVU 1468 2 Landrace 274 TVu 6641 Liberia GUINEA PEA Landrace 275 TVu 6642 PI 580192 Liberia ASPARAGUS BEAN Landrace 276 TVu 6643 Liberia YARD LONG BEAN Landrace 277 TVu 6644 Liberia YARD LONG BEAN Landrace 278 TVu 6663 Nigeria IF H 13 1 Breeding 279 TVu 6837 Turkey PREVIOUS TVU 2301 2 Landrace 282 TVu 6968 PI 449180 Niger EX TVU 4879 Landrace 287 TVu 7362 PI 615171 Ghana 8 Km N TARKWA TO BOGOSO Landrace 288 TVu 7382 PI 580445 Ghana EX KPEVE Landrace 289 TVu 7559 Nigeria 40 Km S PANYAM TO SHENDAM Landrace 290 TVu 7625 Mali 16 Km BANDIGARA TO SANGHA Landrace 291 TVu 7642 Mali 8 Km N DIDIEMI Landrace

PAGE 124

124 Table D 1. Continued Accession # Accession name PI Number Country of origen Cultivar name Biological status of accession 292 TVu 7647 Mali EX KAMIKA (95 Km N KOLOKANI) Landrace 293 TVu 7684 PI 580510 Mali 117 Km BORGOUNI TO SIKASO Landrace 294 TVu 7719 Cote d'Ivoire EX FERKESSEDOUG OU Landrace 295 TVu 7739 Cote d'Ivoire EX BOUAKE MARKET Landrace 296 TVu 7755 Cote d'Ivoire EX KORHOGO MARKET Landrace 297 TVu 7778 Cote d'Ivoire EX TARDA Landrace 298 TVu 7798 Papua New Ginea PANJANG JAYAPURA Landrace 299 TVu 7971 PI 580669 Cote d'Ivoire EX TARDA Landrace 300 TVu 7991 Nigeria DAN BUMA Landrace 301 TVu 8 Nigeria C 1 Landrace 302 TVu 8059 Cote d'Ivoire EX TARIFE MARKET Landrace 303 TVu 8072 PI 580692 Papua New Ginea WACHIE Landrace 304 TVu 8082 Cote d'Ivoire EX BONDOUKOU MARKET Landrace 305 TVu 8123 PI 580708 Nigeria MAI BAKIN HANCHI Landrace 306 TVu 8262 Burkina Faso 37 Km BOBO -TO DEDOUGOU Landrace 307 Tvu 8389 PI 580798 Papua New Ginea KACANG PANJANG JAYAPURA Landrace 308 TVu 84 PI 578943 South Africa BECHUANA WHITE (TAN SEED) Landrace 309 TVu 8612 Togo NOEPE NO.6 Landrace 310 TVu 8622 Togo EX AVENTONOU Landrace 311 TVu 8631 Togo TABLIGBO NO.1 Landrace

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125 Table D 1. Continued Accession # Accession name PI Number Country of origen Cultivar name Biological status of accession 312 TVu 8641 Togo VOGAN NO.2 Landrace 313 TVu 8656 Benin ABOMEY CALAVI SMOOTH TAN Landrace 314 TVu 8671 Benin NIAOULI NO.12 Landrace 315 TVu 8673 Benin NIAOULI NO.15 Landrace 316 TVu 8702 Benin OUANDO NO.3 Landrace 317 TVu 8713 Benin AFFAME NO.1 Landrace 318 TVu 8775 POLON ME Landrace 319 TVu 8779 Benin EX GABE Landrace 320 TVu 8812 Benin SWII EX OUARI Landrace 321 TVu 8834 Benin EX KOKIBEROU Landrace 322 TVu 8877 Benin KLOUEKANME NO.4 Landrace 323 TVu 8883 Benin APLAHOUE NO.6 Landrace 324 TVu 889 PI 579245 Nigeria AMPER LOCAL Landrace 325 TVu 8923 Nigeria MAFANRA NO.1 Landrace 326 TVu 8934 Nigeria UNGWAN DANLADI NO.5 Landrace 327 TVu 9031 Nigeria 83 Km JALINGO TO MAYO BELWA Landrace 328 TVu 9073 India IC 20548 Landrace 329 TVu 9095 India IC 20152 Landrace 330 TVu 9256 Burkina Faso KADOMBA NO.2 Landrace 331 TVu 9257 Burkina Faso EX KOUNDOUGOU Landrace 332 TVu 9259 Burkina Faso EX KOUNDOUGOU Landrace 333 TVu 9265 Burkina Faso TENGRELA NO.1 Landrace 334 TVu 9393 India EX MODASA Landrace 335 TVu 946 Nigeria AB 2461 336 TVu 9468 Egypt MANSURA NO EYE 5 Landrace 337 TVu 9469 Egypt MANSURA RED EYE 6 Landrace 338 TVu 9474 Egypt MANSURA RED EYE 11 Landrace

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126 Table D 1. Continued Accession # Accession name PI Number Country of origen Cultivar name Biological status of accession 339 TVu 9486 Egypt MANSURA RED EYE 17 Landrace 340 TVu 9492 Egypt MANSURA SPECKLED CREAM NO.2 Landrace 341 TVu 9506 Egypt KAFR WESTANY NO EYE 6 Landrace 342 TVu 9508 Egypt KAFR WESTANY BLACK EYE 2 Landrace 343 TVu 9516 Egypt EL HAWASHM BLACK EYE 5 Landrace 344 TVu 9522 Egypt EL HAWASHM NO EYE 3 Landrace 345 TVu 9556 Egypt ZAGAZIG NO. 5 Landrace 346 TVu 9557 Egypt ZAGAZIG NO. 6 Landrace 347 TVu 9620 Egypt IBYAR RED EYE 6 Landrace 348 TVu 9651 Egypt KAFR EL SHEIK NO.4 Landrace 350 TVu 969 PI 579263 Nigeria EX LOKOJA Landrace 351 TVu 972 PI 579265 Nigeria EX LOKOJA Landrace 352 TVu 9749 Egypt EL FAIYUM RED EYE Landrace 353 TVu 9801 Malawi BANGULA NO.1 Landrace 354 TVu 9820 Malawi PENDI NO.2 Landrace 355 TVu 9848 Malawi NYEZANI NO.2 Landrace 356 TVu 9866 Malawi LUNZU NO.1 Landrace 357 UCR 11 Iran Landrace 358 UCR 1340 India IC 2899 Landrace 359 UCR 1342 India 360 UCR 1432 Nigeria 361 UCR 162 Afghanista n 362 UCR 193 India BBR 37 363 UCR 24 USA COLUMBIA 366 UCR 288 Nigeria 368 UCR 3301 Senegal 58 20 Landrace 369 UCR 3326 Senegal 58 116 Landrace 370 UCR 3399 Nigeria Landrace 371 UCR 4539 Senegal DIOURBEL SELECTION Landrace

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127 Table D 1. Continued Accession # Accession name PI Number Country of origen Cultivar name Biological status of accession 372 UCR 5164 Nigeria Landrace 373 UCR 5272 Ghana EJURA RED Landrace 374 UCR 5275 Australia HOLSTEIN (90 98) 375 UCR 5279 Ghana Landrace 376 UCR 5280 Sudan Landrace 377 UCR 5329 Kenya NUVG 15 378 UCR 5353 Italy M. G. 103264 Landrace 379 UCR 5385 Italy M. G. 113251 Landrace 380 UCR 707 Kenya EX LUANDA Landrace 381 UCR 739 Botswana BOTS 5C Landrace 382 UCR 779 Botswana BOTS 19A Landrace 383 UCR 830 Botswana BOTS 53B Landrace 384 VAR 10B Mozambiq ue Landrace 385 VAR 3A Mozambiq ue Landrace 386 Vya Cameroon 387 Xingove Mozambiq ue Landrace 388 Yacine Senegal Breeding 389 Vazzano Brown Italy Landrace 390 Vazzano Black Italy Landrace 391 Cp 4877 Portugal Landrace 392 Cp 4906 Portugal Landrace 393 Cp 5556 Portugal Landrace 394 Cp 5647 Portugal Landrace 395 Vg48 Portugal Landrace 396 Vg50 Portugal Landrace 397 Vg56 Portugal Landrace 398 Vg58 Portugal Landrace 399 Vg62 Portugal Landrace 401 Vg72 Portugal Landrace 402 Vg73 Portugal Landrace

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128 LIST OF REFERENCES Abad, P., Gouzy, J., Aury, J M., Castagnone Sereno, P., Danchin, E. G. J., Deleury, E., ... Wincker, P. (2008). Genome sequence of the metazoan plant parasitic nematode Meloidogyne incognita . Nature Biotechnology, 26(8), 909 915. DOI: 10.1038/nb t.1482 Agrios, G. N. (2005). Plant diseases caused by viruses. In Plant Pathology. Fifth Edition. Elsevier Academic Press, pages 724 820. Aliyu, O. M., & Makinde, B. O. (2016). Phenotypic analysis of seed yield and yield components in cowpea ( Vigna unguic ulata L., Walp). Plant Breeding and Biotechnology, 4(2), 252 261. https://doi.org/10.9787/pbb.2016.4.2.252 Almeida, E. J. D., Santos, J. M. D., & Martins, A. B. G. (2009). Resistance of guava and ar aca to Meloidogyne mayaguensis . Pesquisa Agropecuária Brasileira, 44(4), 421 423. Anele, U. Y. (2011). Evaluation of dual purpose cowpea varieties for dry season feeding of ruminant animals. Ph.D. Thesis, University of Bonn, Germany. Annan, I. B., Schaefer s, G. A., & Tingey, W. M. (1995). Influence of duration of infestation by cowpea aphid (Aphididae) on growth and yield of resistant and susceptible cowpeas. Crop Protection, 14(7), 533 538. Atamian, H. S., Roberts, P. A., & Kaloshian, I. (2012). High and l ow throughput screens with root knot nematodes Meloidogyne spp. Journal of Visualized Experiments, 61, 3629. Ayan, I., Mut, H., Basaran, U., Acar, Z., & Asci, O. O. (2012). Forage potential of cowpea ( Vigna unguiculata L. Walp). Turkish Journal of Field Crops, 17(2), 135 138. Bhatti, D. S., & Jain, R. K. (1977). Estimation of loss in okra, tomato and brinjal yield due to Meloidogyne incognita . Indian Journal of Nematology, 7(1), 37 41. Booker, H. M., Umaharan, P., & McDavid, C. R. (2005). Effect of cowpea severe mosaic virus on crop growth characteristics and yield of cowpea. Plant disease, 89(5), 515 520. Bressani, R., 1985. Nutritive value of cowpea. In Cowpea Research, Production and Utilization. Singh, S.R., Rachie, K.O. (Eds.), Wiley, Winchester , UK, pages 353 359. Brito, J. A., Kaur, R., Cetintas, R., Stanley, J. D., Mendes, M. L., Powers, T. O., & Di, D. W. (2010). Meloidogyne spp. infecting ornamental plants in Florida. Nematropica, 40(1), 87 104. Brito, J. A., Stanley, J. D., Mendes, M. L., C etintas, R., & Dickson, D. W. (2007). Host status of selected cultivated plants to Meloidogyne mayaguensis in Florida. Nematropica, 37(1), 65 72. Cantu, R. R., Wilcken, S. R. S., Rosa, J. M. O., Goto, R. (2009). Rea o de porta enxertos comerciais de to mateiro a Meloidogyne mayaguensis . Sum. Phytopathol. 35:216 218.

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131 Fery, R. L., & Dukes, P. D. (1980). Inheritance of root knot resistance in the cowpea ( Vigna unguiculata (L. ) Walp.). Journal of the American Society for Horticultural Science, 105(5), 671 674. Fery, R. L., & Dukes, P. D. (1982). Inheritance and assessment of a second root knot resistance factor in southernpea [ Vigna unguiculata (L.) Walp.]. HortScience, 17(2), 152. Fery, R. L., Dukes, P. D., & Thies, J. A. (1994). Characterization of new sources of resistance in cowpea to the southern root knot nematode. HortScience, 29(6), 678 679. Frahm Leliveld , J. A. (1965). Cytological data on some wild tropical Vigna species and cultivars from cowpea and asparagus bean. Euphytica, 14(3), 251 270. Gerrano, A. S., Adebola, P. O., Jansen Van Rensburg, W. S., & Laurie, S. M. (2015). Genetic variability in cowpea ( Vigna unguiculata (L.) Walp.) genotypes. South African Journal of Plant and Soil, 32(3), 165 174. https://doi.org/10.1080/02571862.2015.1014435 . Gilmour, A. R., Gogel, B. J., Cullis, B. R., Th ompson, R., & Butler, D. (2009). ASReml user guide release 3.0. VSN International Ltd, Hemel Hempstead, UK. decline: a complex disease involving Meloidogyne mayagu ensis and Fusarium solani . Journal of Phytopathology, 159(1), 45 50. Hall, A. E. (2004). Breeding for adaptation to drought and heat in cowpea. European Journal of Agronomy, 21(4), 447 454. Hall, A. E., & Patel, P. N. (1985). Breeding for resistance to dr ought and heat. In Cowpea Research, Production and Utilization. Singh, S. R. & Rachie, K. O. (Eds). Wiley, New York, pages 137 151. K. H. (2003). Development of cowpea cultivars and germplasm by the Bean/Cowpea CRSP. Field Crops Research, 82(2 3), 103 134. https://doi.org/10.1016/S0378 4290(03)00033 9 . Hall, A. E., Ismail, A. M., Ehlers, J. D., Marfo, K. O., Cisse, N., Thiaw, S., & Close, T. J. (2002). Breeding cowpea for tolerance to temperature extremes and adaptation to drought. In Challenges and Opportunities for Enhancing Sustainable Cowpea Production. Fatokun, C. A., Tarawali, S. A., Singh, B. B., Kormawa, P. M. & Tamo, M. (Eds.). International Institute of Tropical Agriculture, Ibadan, pages 14 21. Harrison, H. F., Jackson, D. M., Thies, J. A., Fery, R. L., & Smith, J. P. (2014). US 1136, US 1137, and US 1138 cowpea lines for cover crop use. HortS cience, 49(3), 364 366. Helms, D., Panella, L., Buddenhagen, I. W., Tucker, C. L., Gepts, P. L., Foster, K. W., ... & Tai, P. Y. P. (1991). 2214501. Registration of'California Blackeye 46'cowpea. Crop science, 31(6), 1703 1704.

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133 Kolawole, G. O., Tian, G., & Singh, B. B. (2000). Differential response of cowpea lines to aluminum and phosphorus application. Journal of Plant Nutrition, 23(6), 731 740. Kristjanson, P., Tarawali, S., Okike, I., Singh, B.B., Thornton, P.K., Manyong, V.M., Kruska, R.L., Hoogenboom, G., (2002). Genetically Improved Dual purpose Cowpea: Assessment of Adoption and Impact in the Dry S avannah of West Africa. Impact Assessment Series No. 9, International Livestock Research Institute, Nairobi. 68 pages. Kwapata, M. B., & Hall, A. E. (1985). Effects of moisture regime and phosphorus on mycorrhizal infection, nutrient uptake, and growth of cowpeas ( Vigna unguiculata (L.) Walp.). Field Crops Research, 12, 241 250. Lale, N. E. S., & Kolo, A. A. (1998). Susceptibility of eight genetically improved local cultivars of cowpea to Callosobruchus maculatus (F.) (Coleoptera: Bruchidae ) in Nigeria. Int ernational Journal of Pest Management, 44(1), 25 27. Langyintuo, A. S., Lowenberg DeBoer, J., Faye, M., Lambert, D., Ibro, G., Moussa, B., ... & Ntoukam, G. (2003). Cowpea supply and demand in West and Central Africa. Field Crops Research, 82(2), 215 231. Lo, S., Muñoz Amatriaín, M., Boukar, O., Herniter, I., Cisse, N., Guo, Y. N., ... & Close, T. J. (2018). Identification of QTL controlling domestication related traits in cowpea ( Vigna unguiculata L. Walp). Scientific Reports, 8(1), 6261. Lonardi, S., Muño H. (2019). The genome of cowpea ( Vigna unguiculata [L.] Walp.). The Plant Journal, 98(5), 767 782. Mahalakshmi, V., Ng, Q., Lawson, M., & Ortiz, R. (2007). Cowpea [ Vigna unguicu lata (L.) Walp.] core collection defined by geographical, agronomical and botanical descriptors. Plant Genetic Resources: Characterisation and Utilisation, 5(3), 113 119. https://doi.org/10.1017/S14 79262107837166 . Manggoel, W., Uguru, M. I., Ndam, O. N., & Dasbak, M. A. (2012). Genetic variability, correlation and path coefficient analysis of some yield components of ten cowpea [ Vigna unguiculata (L.) Walp] accessions. Journal of Plant Breeding and Crop Science, 4(5), 80 86. Matsui, T., & Singh, B. B. (2003). Root characteristics in cowpea related to drought tolerance at the seedling stage. Experimental Agriculture, 39(1), 29 38. Melo, O. D., Maluf, W. R., Gon alves, R. J. S., Gon alves Neto, A. C. , Gomes, L. A. A., Carvalho, R. C. (2011). Triagem de gen tipos de hortali as para resist ncia a Meloidogyne enterolobii . Pesqui. Agropecu. Bras. 46:829 835. Moalafi, A. I., Asiwe, J. A. N., & Funnah, S. M. (2010). Germplasm evaluation and enhancement for the development of cowpea ( Vigna unguiculata (L.) Walp dual purpose F2 genotypes. African Journal of Agricultural Research, 5(7), 573 579.

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139 BIOGRAPHICAL SKETCH Rocheteau Dareus was born in Acul du Nord, North Department, Haiti. He a ttended and graduated in 200 7 . In 200 7 , Rocheteau got admitted to the where he s tudied a gronomy for five years at the with a concentration in Natural Resources and Environment. He spent 2 more years running field experiment s working on the effects of mulch on crops yields and writing hi s thesis research . He graduated in 2014 and received the Agronomy Engineer d egree . Rocheteau worked for three years as a Junior Environmental Compliance Officer in a USAID funded agricultural project in Haiti before he g ot granted a scholarship to pursue a m a gronomy at the University of Florida in 2017. Rocheteau knew little about plant breeding, genetics and nematodes when he joined the forage breeding program and worked with Dr. Esteban F. Rios on investigating the UC Riverside cowpea mi purpose breeding purposes and resistance to root knot nematodes . In December 201 9 , he was awarded the Master of Science degree in agronomy. Rocheteau is now back to his home country Haiti to continue to work in the agricultural sector .