KARIMIZADEH, Rahmatollah and Mohtasham MOHAMMADI, 2010. AMMI adjustment for rainfed lentil yield trials in Iran. Bulg. J. Agric. Sci., 16: 66-73
Genotype x environment interaction plays an important role in identifying genotypes for high and stable yield. Multiplicative methods used the AMMI model and Principal Components Analysis (PCA) are singular value decomposition (SVD) based statistical analyses often applied to yield trial data. The goal of this research was to provide biologically meaningful interpretation of GE interactions and determine stable genotypes by using AMMI and AMMI adjusted. This study was carried out to determine the yield performances of ten lentil genotypes across five environments in Iran for two years in 2003-2004 growing season. The experimental layout was a randomized complete block design with four replications. FGH1 and FGH2 tests calculated for better control of Type-1 error rates. AMMI ANOVA showed that environments, genotypes and GE interactions were highly significant (P<0.01) and they accounted for 89%, 2% and 8.6% of the treatment combinations sum of square respectively. F-test of Gollob used to measure significant of this components at the 0.01 probability level recommended inclusion of the first three interactions PCA axes in the model. FGH1 and FGH2 indicated only first two IPCA axes of AMMI model were significant at the 0.05 probability level and reminded in the model.