ABSTRACT

The identification of high-yielding and stable genotypes for cultivation across differential production regions is among the key breeding objectives in cowpea improvement programs. This study was aimed to determine genotype-by-environment interaction (GEI) for grain yield to select high-yielding and stable cowpea genotypes for production in South Africa and identical agro-ecologies, and for cultivar development. Fifty cowpea genotypes were tested for grain yield across seven environments of South Africa using a 10 × 5 alpha lattice design replicated three times, during the 2019/2020 and 2020/2021 planting seasons. Grain yield data were subjected to analysis of variance (ANOVA), additive main effects and multiplicative interaction (AMMI) and the genotype-by-environment interaction (GGE) biplot analyses. ANOVA and AMMI showed significant genotype, environment and GEI effects. High grain yield was recorded for genotypes G35 (0.47 t ha⁻¹), G1 (0.45 t ha⁻¹) and G47 (0.43 t ha⁻¹) across test environments. AMMI stability values (ASV); identified Acc-Cowp44 as the most stable genotype across all sites, recording the lowest ASV of 0.03. The comparison view of GGE biplot revealed Acc-Cowp29, Acc-Cowp38 and Acc-Cowp5 as ideal genotypes, possessing high grain yield of 0.19, 0.47 and 0.36 t ha⁻¹, respectively. The identified genotypes are recommended for production and inclusion in subsequent breeding activities.

摘要

识别高产和稳定的基因型用于不同产区的栽培是豇豆改良计划的关键育种目标之一。本研究旨在确定谷物产量的基因型与环境的相互作用 (GEI)，以选择高产和稳定的豇豆基因型用于南非的生产和相同的农业生态，并用于品种开发。在 2019/2020 和 2020/2021 种植季节，使用 10 × 5 α 晶格设计重复三次，对南非 7 个环境中的 50 个豇豆基因型进行了谷物产量测试。对谷物产量数据进行方差分析 (ANOVA)、加性主效应和乘性相互作用 (AMMI) 以及基因型与环境相互作用 (GGE) 双图分析。ANOVA 和 AMMI 显示出显着的基因型，环境和 GEI 效应。基因型 G35（0.47 吨 ha^-1 )、G1 (0.45 t ha ^-1 ) 和 G47 (0.43 t ha ^-1 ) 跨测试环境。AMMI 稳定性值 (ASV)；将 Acc-Cowp44 确定为所有站点中最稳定的基因型，记录的最低 ASV 为 0.03。GGE biplot 的比较图显示 Acc-Cowp29、Acc-Cowp38 和 Acc-Cowp5 是理想的基因型，分别具有 0.19、0.47 和 0.36 t ha ^-1的高产量。建议将鉴定出的基因型用于生产并纳入随后的育种活动。