Evaluation of drought tolerance in wheat genotypes

Drought stress in arid and semiarid regions is the most crop production restricting factor. Reduction of crop productivity of these regions estimated over than 50% due to climate change and global warming at recent decades (Jaha et al., 2014). According to the Mediterranean precipitation pattern in most parts of Iran, near all rainfall happens in winter season and so drought stress usually occurs in flowering and physiological ripening stages of wheat. Understanding the response of these plants to different environmental stresses such as drought stress and other restricting factors is inevitable. Drought resistance is a quantitative trait which isn’t measurable directly. This problem appear in identification of resistant genotypes to drought stress. In order to discriminate resistant genotypes some indices were recommended based on the seed yield at normal and drought conditions. The best index is one which selected genotypes with high yields at both stressed and non-stressed conditions. Shafazadeh et al., (2004) recommended that MP, GMP and STI indices are suitable for detecting drought resistant and productive genotypes because they had significant and positive correlation with seed yield at both conditions after flowering stage.
Material and This investigation was conducted using 20 improved lines of rain-fed wheat genotypes at two places included Dry-land agricultural research station of Shirvan and Agricultural research station of Sisab, Bojnourd, Iran, in RCBD with 4 replications at two conditions included dry-land and complementary irrigation, during 2015-2016. After harvesting and measuring genotype’s yield in each condition, indices were calculated. Stress susceptibility index (SSI), Stress tolerance index (STI), Tolerance (Tol), Mean productivity (MP), Geometric mean productivity ( GMP), Sensitivity drought index (SDI), Relative drought index (RDI), Yield stability index (YSI), Yield index (YI), Relative water content (RWC) and Electrical conductivity (EC). Data analysis was done using Path, SAS and MSTAT-C software. Means comparisons were done using Duncan’s test and graphs were drown by Excel.
Based on the combined analysis of variances, the location effect was significant for all indices. This subject indicates that effect of location on grain yield of genotypes was different. The interaction effect of genotype × location wasn’t significant for grain yield at normal condition (Yp) but it was significant at stressed condition (Ys). These results showed that grain yield of the genotypes at normal condition for both places weren’t different but grain yield of genotypes at stressed condition were different in each place. In other word, dry land yield of genotypes was various at different places. Dry land yield of genotypes at Sisab station (Bojnourd) were higher than Shirvan station due to higher precipitation in Sisab. These results indicated that effect of genotype×environment is significant and these genotypes have enough variation (Mohammadi et al., 2015). These results showed that, genotypes No. 17 and 12 with 2780 and 2608 kg.ha-1 in non-stressed and 2263 and 2119 kg.ha-1 in stressed conditions respectively, were superior to the other genotypes.
In summary, genotypes No. 17 and 12 based on all investigated indices especially STI, GMP and MP indices were superior compared to other genotypes in both stressed and non-stressed conditions. Genotypes No. 17 and 12 had 2780 and 2608 kg.ha-1 grain yield at non-stressed condition and 2263 and 2119 kg.ha-1 grain yield at stressed condition, respectively. Therefore, these genotypes were selected among all genotypes as tolerant genotypes to drought stress. Heritability of grain yield trait at drought stress is reduced due to genotype to environment interaction. So, selecting genotypes with the lowest reduction of grain yield at end season drought stress condition would help improving grain production per unit area.