Genotype × environment interaction and stability analyses of grain yield in rainfed winter bread wheat

Abstract

The genotype × environment (GE) interaction analysis is fundamental in crop breeding programs to guide selection and for recommendation of high performing and stable genotypes for breeding objectives. This study aimed at quantifying the GE interaction effects and determines grain yield stability among winter bread wheat genotypes under rainfed conditions of Iran. Twenty-four winter wheat genotypes were evaluated under nine test locations using a randomized complete blocks design with four replications during three cropping seasons (2019–21). The additive main effects and multiplicative interaction (AMMI) model and several parametric and nonparametric stability statistics were applied for analysis of grain yield data collected from the experiments. AMMI analysis of variance for grain yield revealed significant effects (p < 0.01) for genotype, environment, and GE interaction. The environment was the main source of variation and accounted for 83.5% of the total yield variation, followed by GE (6.5%) and genotype (1.0%) effects. The AMMI biplot analysis indicated the genotypes G3, G23, G22, G10, and G19 as high yielding with stability performance across environments. Genotypes G14, G13, G20, and G9 showed large positive interaction with the environments featuring the highest rainfall during growing season, while genotypes G7, G6, and G21 had a large positive interaction with environments with low rainfall. Spearman’s rank correlation analysis revealed that the AMMI stability value, Shukla’s stability variance (σ2i), Wricke’s ecovalence (W2i), coefficient of determination (R2i), variance in regression deviations (S2di), and nonparametric statistic of S2(i) were not correlated with mean yield in tested genotypes, showing they are related to static/biological concept of stability. In contrast, the genotypic superiority index (Pi) and regression coefficient (bi) were significantly correlated (p < 0.01) with mean yield and corresponded to dynamic/agronomic concept of stability. These findings suggest that selection of genotypes should be considered based on selection objectives of using the various stability parameters described here. In conclusion, the selected genotypes in this study should be recommended as new cultivars or parental lines for grain yield and stability improvement under rainfed conditions of Iran or similar agro-ecologies.

Yield Stability Analysis of Barley Mutants Using Parametric and Nonparametric Statistics

“…Also, significant impacts (P < 0.05) emerged from the environment by location interaction (26.2%), genotype by environment interaction (9.5%), genotype (9.1%), and location (0.7%) (Table 3). The trait different degrees of variations in diverse genotypes can be observed in response to environmental variations (Oral et al, 2019;Roostaei et al, 2022).…”

“…In barley breeding programs, along with the quality of the resulting products and resistance to biotic and abiotic stress factors (Kumar et al, 2020), grain yield has become one of the vital indicators of success and stipulate for the promising cultivar of barley (Friedt and Ordon, 2013). Grain yield is a highly complex, multifaceted phenomenon of genotype-environment interactions (Roostaei et al, 2022). This imperative interaction elucidates the different degrees of variations in a single trait in different genotypes in response to identical variations in environmental conditions (Oral et al, 2019).…”

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

“…Continuing with this inquiry, the environmental ranking through biplot analysis provides a hierarchical lens to evaluate the alignment of different environments with ideal conditions for yield and protein. This concept has been addressed in various studies, including those by Roostaei et al [ 45 ], Tanin et al [ 7 ], and Chairi et al [ 46 ], which have explored the interactions between genotypes and environments, especially in durum wheat, and their implications for yield and other agronomic traits. Switching to a multi-metric assessment, the genotypic stability analysis exhibited commendable depth, employing notable stability metrics from the literature, as highlighted by Alemu Dabi et al [ 47 ], Lin and Binns [ 48 ], and Shukla [ 14 ].…”

Country-wide, multi-location trials of Green Super Rice lines for yield performance and stability analysis using genetic and stability parameters

“…Univariate stability analysis was performed for the above-mentioned yield and yield-related components of all genotypes by using AMMI Stability Value (ASV) 38 , 39 and AMMI Stability Index (ASI) 40 , Shukla’s stability variance (σ 2 ) 41 and Wricke’s ecovalence (Wi 2 ) 42 .…”