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This experiment was conducted during 2013-2014 in Tabriz University research farm, Iran. In this research, the inheritance of some agronomic and physiological traits in different generations of Bam (tolerant to drought) and Artha (sensitive to drought) cross was studied in field conditions by generation mean analysis. The experiment was a split plot design using randomized complete blocks with two replications with the irrigation conditions in the main plots and generations in the sub-plots. The interaction between generations and irrigation conditions was significant only for grain yield. Based on the result of generation means analysis for the spike length and straw weight, the threeparameter model was found fitting the analysis. For the thousand-seed weight in the water stress condition and for the plant weight in the irrigation condition, a non-significant chi-square suggesting that the six-parameter model for these traits is suitable. For the other traits, the chi-square was significant in both conditions. For spike length and leaf area, the degree of dominance was greater than one (2.3 and 1.53, respectively) which showed the existence of over-dominance gene action in controlling these traits. Straw weight in normal condition, leaf area and thousand seed weight in the stress condition had a high broad-sense heritability. The narrow-sense heritability for all other traits was low, suggesting the need for exploiting dominance gene action in the breeding programs if hybrid varieties are produced in the bread wheat.

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In this research, 15 bread wheat genotypes along with Aftab variety as a control variety were implemented with 4 replications in the form of randomized complete block design for 3 crop years (2016-2019) at Sarab Chengai Station in Khorramabad. The likelihood ratio test (LRT) showed that the genotype-year interaction effect was significant for grain yield. Based on this, singular value analysis (SVD) was performed on the matrix of best linear unbiased predictions (BLUP) of genotype × year interaction to evaluate the stability of genotypes. The scree plot showed that the first principal component accounted for 71.7% and the second principal component accounted for 28.3% of the matrix changes resulting from the best unbiased predictions of the genotype interaction per year. The biplot of the first principal component of the environment against the nominal yield also showed that genotypes No. 9, 12 and 13 had a negligible contribution to the genotype × year interaction and had higher general stability. Also, the biplot of grain yield against the weighted average of absolute scores (WAASB) placed the genotypes in four regions, so that genotypes No. 15, 16, 12, 11, and 10 are in the fourth region due to high stability (low values WAASB) and magnitude of response variable (high performance) were identified as superior genotypes. The WAASBY index (weighted average of WAASB stability and performance) identified genotypes No. 15, 16, 12, 10, 11, 14, 9 and 4 as stable and high yielding genotypes. In general, based on WAASB and WAASBY indices and their comparison, genotypes 15, 16, 12, 11 and 10 were selected as the best genotypes that can be recommended for cultivation in similar climates.