Genotype and genotype × environment interaction effects on the grain yield performance of cowpea genotypes in dryland farming system in South Africa

The identification of stable and adaptable high yielding cowpeas ( Vigna unguiculata (L.) Walp.) and highly discriminative environments will be useful for elite cultivar development in South Africa. Two statistical models, the Additive main effects multiplicative interaction (AMMI) and the genotype,...

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Bibliographic Details
Published in:Euphytica 2020-05, Vol.216 (5), Article 80
Main Authors: Gerrano, Abe Shegro, Jansen van Rensburg, Willem Sternberg, Mathew, Isack, Shayanowako, Admire I. T., Bairu, Michael Wolday, Venter, Sonja Louise, Swart, Wijnand, Mofokeng, Alina, Mellem, John, Labuschagne, Maryke
Format: Article
Language:English
Subjects:
Arid zones
Biomedical and Life Sciences
Biotechnology
Cowpeas
Crop yield
Cultivars
Dryland farming
Environmental effects
Farming systems
Genotype & phenotype
Genotype-environment interactions
Genotypes
Life Sciences
Mathematical models
Original Paper
Performance evaluation
Plant Genetics and Genomics
Plant Pathology
Plant Physiology
Plant Sciences
Seasonal variations
Stability analysis
Statistical analysis
Statistical models
Variance analysis
Vigna unguiculata
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Summary:The identification of stable and adaptable high yielding cowpeas ( Vigna unguiculata (L.) Walp.) and highly discriminative environments will be useful for elite cultivar development in South Africa. Two statistical models, the Additive main effects multiplicative interaction (AMMI) and the genotype, genotype by environment biplot analysis have been used extensively to identify superior genotypes and ideal testing environments. Hence, the objective of this study was to identify elite cowpea lines and testing environments using the two models to inform future cultivar development strategies. Fifteen cowpea genotypes were evaluated for yield performance and stability across 3 different locations during 2016 and 2017 growing seasons in South Africa. Genotype main effects were significant for grain yield, while genotype × environment interaction effect was insignificant for grain yield. However, genotypic perfomance for grain yield was significantly affected by seasonal variability. The AMMI analysis of variance showed that genotypes (G), environments (E) and their interaction were significant for grain yield. The G and GE effects accounted for about 10% of the total variation in grain yield, while the environment accounted for 66%. The high yielding genotypes, Vigna Onb, TVU-5431 and Kisumu mix, were adapted to Mafikeng and Potchefstroom sites. Kisumu mix, followed by Vigna Onb, were the most stable genotypes, while Veg cowpea 1, Veg cowpea dacama cream and Veg cowpea 2 were the least stable genotypes across the three sites and seasons. The analysis also showed that Environment 4 (Potchefstroom) was the most ideal site for cowpea production among the test sites.
ISSN:0014-2336
1573-5060
DOI:10.1007/s10681-020-02611-z