Graphical Analysis of Multi-Environment Trials for Barley Yield Using AMMI and GGE-Biplot Under Rain-Fed Conditions

The AMMI and SREG GGE are among the models that effectively capture the additive and multiplicative components of genotype × environment interaction (GEI) and provide meaningful interpretation of multi-environment trials’ data set in the breeding programs. The objective of this study was to assess the effect of GEI on grain yield of barely advanced lines and exploit the positive GEI effect using AMMI and SREG GGE biplot analysis. Therefore, 18 lines were evaluated at four research stations (Gorgan, Mogan, Lorestan and Gachsaran) of Dryland Agricultural Research Institute (DARI), located in the semi-warm regions in Iran, in 2004, 2005 and 2006 cropping seasons under rain-fed conditions. Analysis of variance showed that grain yield variation due to environments, genotypes and GEI were highly significant (p<0.01), which accounted for 70.4%, 6.8% and 22.8% of treatment combination sum of squares, respectively. To determine the effects of GEI on yields, the data were subjected to AMMI and GGE biplot analysis. The first four AMMI model terms were highly significant (p<0.01) and of which the first two terms explained 48% of the GEI. There were two mega-environments according to the SREG GGE model. The best genotype in one location was not always the best in other test locations. According to AMMI1 biplot, the ideal-genotype biplot and by visualizing the mean yield and stability of the genotypes, lines G2 and G11 were better than all other lines across environments. G11 was the ideal genotype to plant in Gachsaran and Lorestan and G2 was the best for Gorgon and Mogan.