Esan Vincent Ishola, Oke Grace Oluwasikemi, Ogunbode Timothy Oyebamiji, Obisesan Idowu Arinola
Environmental Management and Crop Production Unit, B. Agriculture Program, College of Agriculture, Bowen University, Iwo, Nigeria.
Pure and Applied Biology Program, College of Agriculture Bowen University, Iwo, Nigeria.
Front Plant Sci. 2023 Jan 20;13:997429. doi: 10.3389/fpls.2022.997429. eCollection 2022.
The two most common styles to analyze genotype-by-environment interaction (GEI) and estimate genotypes are additive main effects and multiplicative interaction (AMMI) and genotype + genotype × environment (GGE) biplot. Therefore, the aim of this study was to find the winning genotype(s) under three locations, as well as to investigate the nature and extent of GEI effects on Bambara groundnut production.
The experiment was carried out in the fields of three environments with 15 Bambara groundnut accessions using the randomized complete block design (RCBD) with three replications each in Ibadan, Osun, and Odeda. Yield per plant, fresh seed weight, total number of pods per plant, hundred seed weight, length of seeds, and width of seeds were estimated.
According to the combined analysis of variance over environments, genotypes and GEI both had a significant (p < 0.001) impact on Bambara groundnut (BGN) yield. This result revealed that BGN accessions performed differently in the three locations. A two-dimensional GGE biplot was generated using the first two principal component analyses for the pattern of the interaction components with the genotype and GEI. The first two principal component analyses (PCAs) for yield per plant accounted for 59.9% in PCA1 and 40.1% in PCA2. The genotypes that performed best in each environment based on the "which-won-where" polygon were G8, G3, G2, G11, G6, and G4. They were also the vertex genotypes for each environment. Based on the ranking of genotypes, the ideal genotypes were G2 and G6 for YPP, G1 and G5 for FPW, G15 and G13 for TNPP, G3 and GG7 for HSW, G7 and G12 for LOS, and G10 and G7 for WOS. G8 was recorded as the top most-yielding genotype. G8, G4, G7, and G13 were high yielding and the most stable across the environments; G11, G14, and G9 were unstable, but they yielded above-average performance; G14, G12, G15, and G1 were unstable and yielded poorly, as their performances were below average. Bowen was the most discriminating and representative environment and is classified as the superior environment.
Based on the performance of accessions in each region, we recommend TVSU 455 (G8) and TVSU 458 (G3) in Bowen, TVSU 455 (G8) and TVSU 939 (G6) and TVSU 454 (G1) in Ibadan, and TVSU 158 (G2) and TVSU 2096 (G10) in Odeda. The variety that performed best in the three environments was TVSU 455 (G8). They could also be used as parental lines in breeding programs.
分析基因型与环境互作（GEI）和估算基因型的两种最常见方法是加性主效应和乘积互作（AMMI）以及基因型 + 基因型×环境（GGE）双标图。因此，本研究的目的是找出在三个地点表现最佳的基因型，并研究GEI效应在 Bambara 花生生产中的性质和程度。
在三个环境的田间对 15 个 Bambara 花生种质进行试验，采用随机完全区组设计（RCBD），在伊巴丹、奥孙和奥代达各重复三次。估算了单株产量、鲜种子重量、单株荚果总数、百粒重、种子长度和种子宽度。
根据环境、基因型和 GEI 的联合方差分析，它们对 Bambara 花生（BGN）产量均有显著（p < 0.001）影响。这一结果表明 BGN 种质在三个地点的表现不同。利用前两个主成分分析生成二维 GGE 双标图，以分析基因型和 GEI 的互作成分模式。单株产量的前两个主成分分析（PCA）中主成分 1（PCA1）占 59.9%，主成分 2（PCA2）占 40.1%。根据“何处胜出”多边形，在每个环境中表现最佳的基因型是 G8、G3、G2、G11、G6 和 G4。它们也是每个环境的顶点基因型。根据基因型排名，单株产量的理想基因型是 G2 和 G6，鲜种子重量的是 G1 和 G5，单株荚果总数的是 G15 和 G13，百粒重的是 G3 和 GG7，种子长度的是 G7 和 G12，种子宽度的是 G10 和 G7。G8 被记录为产量最高的基因型。G8、G4、G7 和 G13 产量高且在各环境中最稳定；G11、G14 和 G9 不稳定，但产量高于平均水平；G14、G12、G15 和 G1 不稳定且产量低，因为它们的表现低于平均水平。博文是最具鉴别力和代表性的环境，被归类为优越环境。
根据各地区种质的表现，我们推荐在博文种植 TVSU 455（G8）和 TVSU 458（G3），在伊巴丹种植 TVSU 455（G8）、TVSU 939（G6）和 TVSU 454（G1），在奥代达种植 TVSU 158（G2）和 TVSU 2096（G10）。在三个环境中表现最佳的品种是 TVSU 455（G8）。它们也可作为育种计划中的亲本系。
