Mbali Thembi Gumede, A. Gerrano, A. Modi, Zamalotshwa Thungo
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引用次数: 3
Abstract
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.
在豇豆改良计划中,寻找适合不同产区栽培的高产稳定基因型是关键育种目标之一。本研究旨在确定籽粒产量的基因型-环境相互作用(GEI),以选择高产稳定的豇豆基因型,用于南非和相同的农业生态系统的生产和品种开发。在2019/2020和2020/2021种植季节,使用重复三次的10 × 5 α晶格设计,测试了南非七种环境下50种豇豆基因型的粮食产量。对籽粒产量数据进行方差分析(ANOVA)、加性主效应和乘法互作(AMMI)以及基因型-环境互作(GGE)双图分析。方差分析和AMMI显示了显著的基因型、环境和GEI效应。基因型G35 (0.47 t ha - 1)、G1 (0.45 t ha - 1)和G47 (0.43 t ha - 1)在不同试验环境下均获得高产。AMMI稳定值(ASV);鉴定出Acc-Cowp44是所有位点中最稳定的基因型,ASV最低,为0.03。GGE双图比较显示,Acc-Cowp29、Acc-Cowp38和Acc-Cowp5是理想的基因型,产量分别为0.19、0.47和0.36 t / ha - 1。鉴定出的基因型推荐用于生产和随后的育种活动。