Yield stability of bread wheat genotypes using AMMI and GGE biplot analysis

IntroductionProduction of high-yielding and stable cultivars is the most important objective of crop breeding programs, including wheat. The final yield of each plant is determined by the potential of genotype (G), the effect of environment (E) and the interaction effect of genotype × environment (GE). Several methods have been presented to study the genotype × environment interaction and determine stable genotypes, which can totally be divided into two main categories, univariate and multivariate. Univariate methods do not provide a complete view of the complex and multidimensional nature of GE interaction, therefore, the use of multivariate methods is suggested to solve this problem. Among the multivariate methods, AMMI and GGE-Biplot methods are more important. The objective of the current experiment was to investigate the interaction between genotype and environment for grain yield of 20 wheat genotypes and to identify stable and high-yielding genotypes.Materials and methods The plant materials of this experiment were 20 wheat genotypes including 18 irrigated wheat lines along with two control cultivars, Rakhshan and Baharan. The experiment was carried out in a randomized complete block design with three replications in five temperate regions (Karaj, Kermanshah, Zarghan, Boroujerd and Mashhad stations) during two cropping years 2019-2020. Two multivariate methods, AMMI and GGE-Biplot, were used to investigate the interaction effect of genotype × environment and to evaluate the stability of genotypes. R software was used to analyze the experimental data using the AMMI method, and Genstat software was used to analyze the data using the GGE biplot graphic method.Research findingsThe results of combined analysis of variance showed that the interaction effect of genotype × year and genotype × year × location were significant at the 1% probability level. Based on the results of AMMI analysis, the effect of environment, genotype and genotype × environment interaction were significant. Based on AMMI1 and AMMI2 models, AMMI stability value (ASV) parameter and genotype stability index (GSI), genotype 12 with an avearage grain yield of 8.27 tons per hectare was determined as the best genotype. The study of GGE-biplot polygon led to the identification of three mega-environments, that Boroujerd had the highest power of representation and differentiation among different environments. Genotypes 12 and 9, in addition to having high yield, had higher yield stability. Genotypes 12 and 9 were placed in the center of the circle as the ideal genotype and genotypes 5, 7 and 18 were ranked next. Based on the results of both methods, genotype 12 was identified as the most stable genotype.ConclusionThe results of AMMI, AMMI stability index (ASV) and genotype stability index (GSI) compared to GGE biplot results showed that all these indices have a good potential to evaluate the performance stability of genotypes. Nevertheless, GGE biplot results are more effective and practical in examining the compatibility and stability of genotypes' performance in different environments due to the ease of interpreting graphical results.