Evaluation of Some Physiological Traits and Grain Yield of Ten Iranian Bread Wheat Cultivars Under Two Irrigation Conditions

This study was conducted in Research Farm of Isfahan University of Technology to evaluate some of the agronomic and physiological traits and grain yield potentials of ten bread wheat cultivars using a split plot design with three replications. Main and sub plot consisted of optimum and stress moisture treatments (irrigation after 70±3 and 130±3 mm evaporation from class A pan) and wheat cultivars, respectively. The results of analysis of variance revealed significant effect of moisture treatments on all traits except 1000-grain weight, harvest index, specific leaf weight, assimilate redistribution and difference of peduncle weights at heading. Significant differences were found among genotypes in the stress condition except for chlorophyll b and chlorophyll a to b ratio. Significant differences were detected among genotypes in optimum moisture condition for all characters, except for chlorophyll b, chlorophyll a to b ratio, harvest index and assimilate redistribution. Grain yields in two moisture conditions had significant positive phenotypic and genetic correlations with harvest index, number of grain/spike, RWC, chlorophyll a and sum of chlorophylls a and b and had significant negative correlation with RWL. Significant positive correlation was observed between peduncle weight at heading stage and difference of peduncle weights at stages heading and maturity with grain yield and RWC in moisture stress condition. The results of path analysis for phenotypic correlation coefficients between grain yield and their corresponding traits in the regression model showed that in stress condition harvest index had the highest direct and positive effect on grain yield and in non stress condition chlorophyll a had the highest direct and positive effect on grain yield. Results of stepwise regression analysis in non stress condition revealed that chlorophyll a, plant height and harvest index explained more than 90% of grain yield variability. Based on stepwise regression analysis in non stress condition, RWL, harvest index and RWC explained 95% of grain yield variability.