Estimation of AMMI and GGE Biplots for some Bread and Durum Wheat Genotypes

Abstract

Wheat breeders face environmental conditions and factors when developing and releasing a new cultivar from a breeding program, which considering a challenge especially with climate change. Genotype-byenvironment interaction analysis is key for selection and cultivar release, and to identify suitable production and test environments. Therefore, the grain yield of 12 bread and 12 durum wheat genotypes were evaluated in six different locations from Nile valley to newly reclaimed land in the west desert of Egypt, in two successive 2018/19 and 2019/20 seasons. The mega-environment was tested with the winner genotypes, the stable genotypes, and the individual ideal genotypes by using additive main effect and multiplicative interaction (AMMI), and genotype main effect plus genotype × environment interaction (GGE) biplot methods. The results of AMMI and GGE biplot revealed four mega-environments, one of them had several environments with winner G7 as well as a stable genotype. But the ideal genotype was G2 for the bread wheat genotypes set. On the other hand, the durum wheat genotypes set is divided into two mega-environments with winners G16 and G17 (breeding lines) of grain yield. But the stable genotype and ideal genotype was G18 according to AMMI and GGE biplot analyses across tested environments.

Evaluation of Wheat Genotypes under Water Regimes Using Hyperspectral Reflectance and Agro-Physiological Parameters via Genotype by Yield*Trait Approaches in Sakha Station, Delta, Egypt

“…These results were aligned with [30,31,49,50,55]. At the same time, from the GGE view, the same genotypes had the top-ranked genotypes along with genotype 36 Figure 2, similar findings reported by authors [21,56,57].…”

“…over four tested environments, the environments, genotypes, and their interaction were varied significantly, which the similar trend in other reports [47,57,58]. And the same row data of grain yield is used to generate the GGE biplot [21,56,57]. In addition, Table 4 shows the significant differences in environments, genotypes, and their interactions for most studied traits over 21 the season by season separately.…”

Hyperspectral reflectance and agro-physiological traits for field identification of salt-tolerant wheat genotypes using the genotype by yield*trait biplot technique

“…Findings of grain yield data presented in Table S4 (combined) over the four studied environments showed significant differences for environments, genotypes, and their interaction, which are similar to other reports (Ali et al, 2012;Enyew et al, 2021;Msundi et al, 2021;El-Hendawy et al, 2022). Additionally, similar findings were pointed out for the combined data and GGE biplot by (Enyew et al, 2021;Darwish et al, 2022;Darwish et al, 2023). Tables 5, 6 show significant differences in genotypes, environments, and their interactions for most studied traits over season by season separately.…”

Dissecting Genotype by Environment Interactions in Moroccan Wheat: An Advanced Biplot and Heatmap Analysis Unveiling Agronomic, Quality Traits, and Genotypic Stability for Tailored Breeding Strategies

“…The methodologies employed, especially elucidating environmental discrimination and representativeness through biplot analysis, significantly advance our understanding of how different environments influence principal traits like yield and protein content in wheat. This approach resonates with earlier efforts focused on the genotype by environment interaction, pivotal in plant breeding programs, as highlighted by Mohammadi et al [39], Sakin et al [40], and Mohamed et al [41]. The discrimination vs. representativeness biplot analysis highlighted the heterogeneity among the analyzed environments, supporting the idea that specific environments can significantly differentiate genotypes based on these traits.…”