Identification of Spring Bread Wheat Genotypes with High Yield and Desirable Stability in Golestan Province

Identification of Spring Bread Wheat Genotypes with High Yield and Desirable Stability in Golestan Province
Abstract
Introduction: Wheat is one of the most important crops in the world and plays a fundamental role in ensuring national food security. In Iran, it is also considered the main focus of agricultural self-sufficiency policies. Grain yield in wheat is a quantitative trait influenced by genotype, environment, and genotype × environment (G × E) interaction. This interaction makes the selection of high-yielding and stable genotypes difficult for breeders. To evaluate stability, various parametric and non-parametric methods have been developed, each with its own advantages and limitations. In addition, the multivariate GGE biplot method is an efficient tool for simultaneous analysis of genotype performance and stability. The objective of this study was to investigate the genotype × environment interaction and to identify stable spring bread wheat genotypes using parametric and non-parametric approaches.
Materials and Methods: In this study, 23 spring bread wheat genotypes were evaluated over two cropping years (2019–2020 and 2020–2021) at two agricultural research stations, Gorgan and Gonbad (Golestan Province, Iran), using a randomized complete block design with three replications. Grain yield was measured after uniform agronomic management and harvesting using a plot combine harvester. After testing homogeneity of variances, a combined analysis of variance was performed using SAS software, and due to the significance of genotype × environment interaction, stability analyses were conducted. Parametric and non-parametric stability indices were calculated using STABILITYSOFT software. Graphical analysis of genotype × environment interaction was performed using GGE biplot 4 software.
Results: The combined analysis of variance for grain yield showed that the genotype × environment interaction was statistically significant. Stability analysis based on univariate parametric (Eberhart and Russell, Wricke’s ecovalence, Shukla’s variance, and Plaisted’s stability index) and non-parametric statistics (Nassar and Huhn’s, Thennarasu’s, and Kang’s rank-sum methods) indicated that genotype 4 was the most stable across all environments. Genotype 15 was also identified among the top three stable genotypes based on most parametric and non-parametric indices. Multivariate analysis using the GGE biplot model confirmed these findings, indicating that genotypes 4 and 15 were the most stable and best adapted genotypes with high mean yield performance. The ideal genotype biplot also showed that these two genotypes had superior stability and yield performance compared to other genotypes and exhibited high general adaptability across all tested environments.
Conclusion: The results of this study demonstrated that genotype × environment interaction had a substantial effect on wheat grain yield variation, highlighting the necessity of stability evaluation under different environmental conditions. Comparison of parametric and non-parametric stability indices showed that genotype 4 was identified as the most stable genotype across most criteria, while genotype 15 was also ranked among the superior stable genotypes. Multivariate GGE biplot analysis further confirmed the superiority of these two genotypes in terms of both stability and general adaptability. Moreover, genotypes 4 and 15 can be considered valuable resources in wheat breeding programs and promising candidates for the development and release of new high-yielding and stable cultivars.