Genotype-by-environment (G×E) interaction reduces the correlation between genotypic and phenotypic parameters and complicates progress of selection. Among several models proposed for evaluation of the G×E interaction, the Additive main effects and multiplicative interaction (AMMI) and GGE-biplot are the most informative models. The objective of this study was to estimate the G×E interaction in 55 maize genotypes to identify maize genotypes of stability and/or adaptability across two irrigation treatments at two locations using the AMMI and GGE-biplot models. A randomized complete block design was used in each environment with three replications. The AMMI analysis of variance indicated that the genotype (G), environment (E) and G×E interaction for Feddan Yielg data showed highly significant due to treatments, genotypes and environments this pointed out that all sources of variance are important in analysis, however genotypes contributed with (48.36%) in treatments variances, the environment contributed with (44.0%) in treatments variance also interaction principal component axis (IPCA) accounted for (53.52% and 39.44%) respectively, were found to be highly significant, the (IPCA1 and IPCA2) together with had a total (92.96%) variances of the interaction. GGE biplot analysis environments showed that the genotype (10, 20, 32 and 36) was found promising in normal irrigation treatment at Assuit location in descending order. The genotypes (22, 27 and 44) was promising in normal irrigation treatment at Minia location in descending order. The genotypes (14, 17, 25, 45 and 49) are suitable to stress irrigation treatment at Minia location. The genotypes (6 and 50) are suitable to drought irrigation treatment at Assuit location. The polygon reflects that G11, G33, G34, G53, and G56 are poor grain yielding and not suitable to either of the environments and relationships between genotypes and environments showed that the environments with a small angle between them are highly positively correlated, and they provide similar information on genotypes. Present investigations showed that N1 and N2 for grain yield. The two environments S1 and S2 are similar; they had small angle between them and they provide similar information on genotypes. In contrast, either N1 or S1 and N2 or S2 were dissimilar, since the angle was obtuse, and they provide different information on genotypes.
            The greater IPCA-1 shows greater discriminating ability of an environment. This gives the importance of determining the discriminating ability to enhance separation through differences in performances of different genotypes. The results revealed that N1 and N2 gave more information on the tested genotypes than the other environments. So this study provides important information on selecting and releasing best and ideal genotypes which are good for production in specific and widely adapted environments as well as determine the most effective and necessary environments which gives more information on varieties in future breeding N1 and N2 lied closest to the origin and, therefore, contributed the least to GEI; these environments are the most representative (stable) environments, but with poor discriminating ability, S1 and N2 are the most unstable.