Study on relationships between various quantitative traits with grain yield of wheat under salinity stress.

Similar to other arid-and semiarid regions in the world , a great part of soil and water resources in Iran have salinity problem. Some of these resources are used to produce .sorne crops such as wheat. Cultivation of wheat under this condition result in salt stress and yield reduction . Therefore salinity tolerance can be one of the important objects of wheat breeding in Iran. Study on relationships between grain yield with different quantitative traits under salinity stress, can result in finding some traits that are highly correlated with grain yield . Finding such traits can help breeders in selection for high yielding genotypes under salinity stress. This experiment was conducted at the Roodasht Research station, Isfahan province I in crop year 1999-2000 . The object was comparing of grain yield and some other traits of 42 wheat genotypes and also to determine correlations between grain yield with different quantitative traits under salinity stress . The experiment was conducted using a Triple Rectangular lattice Design . Plants were irrigated with saline water that its electrical conductivity (EC) was about 12 ds/rn . In addition to grain yield , 19 traits include days to stages :stem elongation , heading and physiological maturity , grain filling period , grain yield components, plant height , flag leaf length, width and area, flag leaf area duration, biomass, harvest index, spike length, extrusion length and diameter, kernel weight per spike and kernels number per m2 were studied. Analysis of variance showed that there was significant differences between genotypes in all traits (P=O.01) . There were significant positive correlations between grain yield with traits grain filling period, spikes per m2 , biomass I flag leaf area duration I plant height , extrusion length , kernel weight per spike and kernels number per m2 (P=0.01) , and with 1000 kernels weight (P=0.05). In stepwise regression for grain yield , variables grain filling period, kernel weight per spike , number of spikes per m2 , plant height and harvest index entered to final stage of regression equation and expressed about 72 percent of grain yield variance.