Interpreting Genotype×Environment Interaction in Rice (Oryza sativa L.) Using Eberhart and Russell Model

Abstract

The experiment was laid during kharif (June–November, 2022) in three paddy growing regions of Middle Gujarat, India to determine the magnitude of G×E interaction and detect stable high-yielding and specifically performed genotypes for target environment(s). Thirty-two rice genotypes including the standard checks were evaluated for fifteen yield and their attributing characters at three locations (Nawagam, Dabhoi and Thasara) in Randomized Block Design. The results revealed that the mean sum of squares due to genotypes was significant for all of the traits evaluated in all individual environments indicating a sufficient amount of diversity among the different genotypes tested. The linear component of G×E interaction was found significant for days to 50% flowering, productive tillers plant^-1, panicle weight, number of grains panicle^-1, grain yield plant^-1 and harvest index, which indicated linear response of genotypes to changing environments and hence genotype performance would be predictable for those characters. The predominance of linear components suggested that linear regression accounted for a large portion of the G×E interaction for these traits and may help in the accurate forecasting of genotype performance across environments. Four genotypes i.e., IET-28354, IET-29538, IET-29774 and IET-28703 were found stable in all the environments with wider adaptability for grain yield plant^-1.