Goa Yasin, Mohammed Hussein, Worku Walelign, Urage Elias
Southern Agricultural Research Institute, P. O. Box 79, Areka, Ethiopia.
Hawassa University, School of Plant and Horticultural Sciences, P. O. Box 5, Hawassa, Ethiopia.
Heliyon. 2022 Feb 24;8(3):e09013. doi: 10.1016/j.heliyon.2022.e09013. eCollection 2022 Mar.
Genotype by environment interaction (GEI) markedly influences the success of breeding strategies in a versatile crop such as cowpea (Vigna unguiculata (L.) Walp.). Twenty cowpea genotypes were tested in a randomized complete block design with three replications at Gofa, Kucha, and Humbo in Meher seasons of 2016 and 2017 (E1 to E6) and Belg seasons of 2017 and 2018 (E7 to E12) to quantify and evaluate the effects of genotypes, environments and their interactions for grain yield of cowpea genotypes and to identify stable and/or high-yielding genotypes. The environment, genotype, and GEI effects were highly significant (p < 0.001), with the contribution of 42.3%, 23.0%, and 34.7%, respectively to the TSS. Additive main effect and multiplicative interaction (AMMI), genotype main effects plus genotype-environment interaction (GGE), ASV (AMMI stability value), and Genotype stability index (GSI) were used to identify stable genotypes. The GGE-biplot model showed that the twelve environments used for the study clustered under three mega-environments. Our results showed that IT96D-604(G12), IT-89KD (G16), IT93K-293-2-2 (G14), 93K-619-1(G13), IT97K-569-9(G20), and IT99K-1060(G15) scored the highest grain yield (1.67, 1.62, 1.55, 1.51, 1.51, and 1.45 t ha), respectively, over environments. AMMI and GGE biplots analyses identified G16 (IT-89KD) and G14 (IT93K-293-2-2) as stable and high-yielding genotypes across environments and can be further tested in variety verification and later on released as varieties and can also be used for different breeding purposes in all cowpea growing areas in southern Ethiopia. The four high-yielding genotypes IT96D-604, 93K-619-1, IT97K-569-9, and IT99K-1060 could be recommended to be included in breeding or variety verification trials for release. Moreover, our results denoted the effectiveness of AMMI and GGE biplot techniques for selecting stable genotypes, high yielding, and responsive.
基因型与环境互作（GEI）显著影响豇豆（Vigna unguiculata (L.) Walp.）这种适应性强的作物育种策略的成效。2016年和2017年梅赫尔季（E1至E6）以及2017年和2018年贝尔格季（E7至E12），在戈法、库查和洪博采用随机完全区组设计对20个豇豆基因型进行了三次重复试验，以量化和评估基因型、环境及其互作对豇豆基因型籽粒产量的影响，并鉴定稳定和/或高产基因型。环境、基因型和GEI效应极显著（p < 0.001），对总平方和的贡献率分别为42.3%、23.0%和34.7%。采用加性主效应和乘积互作（AMMI）、基因型主效应加基因型 - 环境互作（GGE）、ASV（AMMI稳定性值）和基因型稳定性指数（GSI）来鉴定稳定基因型。GGE双标图模型表明，用于该研究的12个环境聚为3个大环境。我们的结果表明，IT96D - 604（G12）、IT - 89KD（G16）、IT93K - 293 - 2 - 2（G14）、93K - 619 - 1（G13）、IT97K - 569 - 9（G20）和IT99K - 1060（G15）在各环境下的籽粒产量最高（分别为1.67、1.62、1.55、1.51、1.51和1.45吨/公顷）。AMMI和GGE双标图分析确定G16（IT - 89KD）和G14（IT93K - 293 - 2 - 2）为跨环境稳定且高产的基因型，可在品种验证中进一步试验，之后作为品种发布，也可用于埃塞俄比亚南部所有豇豆种植区的不同育种目的。可推荐将四个高产基因型IT96D - 604、93K - 619 - 1、IT97K - 569 - 9和IT99K - 1060纳入育种或品种验证试验以供发布。此外，我们的结果表明AMMI和GGE双标图技术在选择稳定、高产且响应性好的基因型方面是有效的。
