Targeting Promising Bread Wheat (Triticum aestivum L.) Lines for Cold Climate Growing Environments Using AMMI and SREG GGE Biplot Analyses

Genotype×environment interactions (GEIs) can affect breeding programs because they often complicate the evaluation and selection of superior genotypes. This drawback can be reduced by gaining insights into GEI processes and genotype adaptation. The objectives of this research were to evaluate: (۱) the yield stability of promising wheat lines across locations and (۲) the relationship among the test environments for selecting superior lines within the cold climate mega-environments of Iran. A total of ۳۵ wheat promising lines were grown at ۷ locations during the ۲۰۰۸-۲۰۰۹ cropping season. Combined analysis of variance showed that the environment (E) accounted for ۷۵.۷% of the model sum of squares. The magnitude of the GEI sum of squares was about three times larger than that for genotypes. To determine the effects of GEI on yields, the data were subjected to the additive main effects and multiplicative interaction (AMMI) and genotype+(genotype×environment) interaction (GGE) biplot analysis. The AMMI۱ model was found to explain up to ۸۸% of the main and interaction effects. According to the AMMI۱ and GGE biplots, the lines G۵ and G۴ were found to produce high and stable yields across environments. There were three mega-environments (Euromieh and Ardebil as mega-environment I, Mashhad, Arak, Hamedan and Jolgerokh as mega-environment II, and Karaj as mega-environment III) according to the site regression genotype (SREG) GGE model. Application of AMMI and GGE biplots facilitated visual comparison and identification of superior genotypes for each target set of environments.

Keywords:

AMMI , GEI , GGE biplot , Wheat , Yield stability