Evaluation and identification of high yielding and stable cowpea genotypes using GGE biplot and joint regression analysis for varietal development in East and Southern Africa

Malawi, Mozambique, and Tanzania's cowpea breeding programs have been collaborating on pre-breeding trials in different locations, focusing on key traits such as grain yield. However, there is a lack of information regarding the nature of genotype-environment interaction patterns among these environments. The study was conducted to assess and identify high-yielding and stable cowpea genotypes for the development of improved varieties in these three countries. Thirty genotypes were evaluated in ten environments using an incomplete block design with three replications. Grain yield data was analyzed using genotype (G) × genotype-environment interaction (GGE) biplot and joint regression analysis. The joint analysis of variance showed highly significant differences (P < 0.001) for the main effects of genotypes and environment, as well as their interaction effects. This suggested that the environments assessed were distinct and that the genotypes exhibited varying performances in response to environmental variations. The environmental indices showed that only four environments were favorable for high grain yield, and overall, Guariba was the topmost yielder (1973.5 kg ha −1 ) across all environments. The analysis identified IT10K-817-7 and MWcp08 as superior and stable genotypes, making them highly desirable and potentially recommended across test environments for their expected ability to achieve economically viable yields. Overall, Chitedze Research Station in Malawi and Nametil Research Station in Mozambique were both discriminating and representative, indicating that they are good test environments for selecting best-performing genotypes that can perform well across a wide range of conditions. These environments can be recommended as the best environments for future cowpea genotype evaluations targeting the release of varieties in the three countries (Malawi, Mozambique and Tanzania) where the METs were carried out. • Use of discriminating and representative environments can reduce breeding costs. • Desirable genotypes were those that were high yielding and stable across environments. • Cowpea exhibits high interaction effects with the environment.

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Publication Details

Journal
Journal of Agriculture and Food Research
Published
2024-10-16
DOI
https://doi.org/10.1016/j.jafr.2024.101456
Citations
3
Primary Topic
Genetics and Plant Breeding
Type
article
Field-Weighted Citation Impact
1.80
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article

Evaluation and identification of high yielding and stable cowpea genotypes using GGE biplot and joint regression analysis for varietal development in East and Southern Africa

Esnart Nyirenda Yohane, Michael M. Chipeta, John Kafwambira, Henriques Colial et al.
3 citations
Journal of Agriculture and Food Research
Genetics and Plant Breeding
1.80
article

Evaluation and identification of high yielding and stable cowpea genotypes using GGE biplot and joint regression analysis for varietal development in East and Southern Africa

Esnart Nyirenda Yohane, Michael M. Chipeta, John Kafwambira, Henriques Colial, Mussa Tamba
article en
3 citations

Abstract

Malawi, Mozambique, and Tanzania's cowpea breeding programs have been collaborating on pre-breeding trials in different locations, focusing on key traits such as grain yield. However, there is a lack of information regarding the nature of genotype-environment interaction patterns among these environments. The study was conducted to assess and identify high-yielding and stable cowpea genotypes for the development of improved varieties in these three countries. Thirty genotypes were evaluated in ten environments using an incomplete block design with three replications. Grain yield data was analyzed using genotype (G) × genotype-environment interaction (GGE) biplot and joint regression analysis. The joint analysis of variance showed highly significant differences (P < 0.001) for the main effects of genotypes and environment, as well as their interaction effects. This suggested that the environments assessed were distinct and that the genotypes exhibited varying performances in response to environmental variations. The environmental indices showed that only four environments were favorable for high grain yield, and overall, Guariba was the topmost yielder (1973.5 kg ha −1 ) across all environments. The analysis identified IT10K-817-7 and MWcp08 as superior and stable genotypes, making them highly desirable and potentially recommended across test environments for their expected ability to achieve economically viable yields. Overall, Chitedze Research Station in Malawi and Nametil Research Station in Mozambique were both discriminating and representative, indicating that they are good test environments for selecting best-performing genotypes that can perform well across a wide range of conditions. These environments can be recommended as the best environments for future cowpea genotype evaluations targeting the release of varieties in the three countries (Malawi, Mozambique and Tanzania) where the METs were carried out. • Use of discriminating and representative environments can reduce breeding costs. • Desirable genotypes were those that were high yielding and stable across environments. • Cowpea exhibits high interaction effects with the environment.

Journal of Agriculture and Food ResearchVol. 18
Lilongwe University of Agriculture and Natural Resources (MW), Mikocheni Agricultural Research Institute (TZ), Instituto de Investigação Agrária de Moçambique (MZ)
Zero hunger
Openalex Percentile: Top 13%
Genetics and Plant Breeding
1.80
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