Grain Yield Stability Evaluation of Bread Wheat Genotypes Using AMMI Multivariate Methods

Knowledge about genotype × environment interaction helps breeders to select the best adaptable and stable genotypes for different regions. The main objective of this research was to select higher yielding bread wheat genotypes, compared to control cultivar, that are adaptable to the climatic conditions of the tropical and subtropical rainfed regions of Iran. Thus, 15 bread wheat genotypes selected from advanced yield comparison experiments, along with the check cultivar of Aftab, were studied in a randomized complete block design with three replications for three cropping seasons (2017-2020) in four regions (Gachsaran, Gonbad, Khorramabad and Moghan). In order to analyze the genotype × environment interaction the multivariate method of Additive Main Effects and Multiplicative Interaction (AMMI) was used. The Results of combined analysis of variance indicated that 91.49, 1.54 and 5.03 percentage of the total variations are related to environment, genotype and genotype × environment interaction, respectively. Moreover, results showed that the first seven principal components of the AMMI model were significant and explained 97.94% of genotype × environment interactions. The biplot of mean grain yield and the first principle component of genotypes and environments revealed that genotypes G1, G12 and G11 with a higher grain yield than the overall mean and lowest genotype × environment interaction were stable with high grain yield. Among them, genotype 11 with suitable general adaptability can be selected as promising genotype and a candidate for introducing a new cultivar for arid and semiarid rainfed regions. In this research, Khorramabad, with high proportion of genotype × environment interaction was recognized as the ideal environment for differentiation and separation of bread wheat genotypes. The cluster analysis classified the studied environments into three groups. The inclusion of all three years experiments related to Moghan location in one group indicates the high predictability and repeatability of this region.