The combine ANOVA analysis for grain yield of 10 wheat genotypes at 12 environments showed that bread wheat grain yields were significantly affected by E (environment), which explained 75.01% of the total treatment (G+E+GEI) variation, whereas the G (Genotype) and GEI were significant and accounted for 9.48 and 15.5% respectively. Additive main effects and multiplicative interaction (AMMI) analysis indicated that three principal components (PCAs) were significant (P < 0.01). PCA 1, PCA 2, and PCA 3 accounted for 65.49, 17.10 and 10.11% of the GE interaction, respectively. A GGE-biplot based on genotype-focused scaling was depicted in order to detect the locations of genotypes, whereas the wheat genotypes were divided into 4 groups based on their scores of PCA1 and PCA2. The first group included on 3 stable genotypes (G2, G10 and G6) that were highest yielding. As for Group 2 included 2 unstable genotypes (G4 and G1) that were higher yielding, while the Group 3 (G5, G7 and G8) were low yielding and stable genotypes, and Group 4 consist of 2 genotypes (G9 and G3) that were low yielding and genotypic instability. The correlation coefficients among the 12 test environments and the vector view of the GGE-biplot provide a succinct summary of the interrelationship between the environments. Among 67 correlation coefficients, 38 of which were significant. All environments were positively correlated except that environment E5 negatively correlated with E9, E12 and E10.
Key words: Additive main effects and multiplicative interaction (AMMI), additive main effects and multiplicative interaction, bread wheat, genotype-by-environment interaction (GEI), genotype x environment interaction, GGE-biplot, multi environment trials (METs), principal component (PC).
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