Study of different Zinc rates effects on yield and yield components of Safflower genotypes in Jiroft region, Iran

Zinc is considered as one of the most important micronutrients for safflower nutrition and has an obvious role on seed yield of this crop. In order to evaluate the effects of different Zinc rates on yield and yield components of 10 safflower genotypes, a field experiment was conducted during growing season of 2008-2009 in Jiroft. The experiment was carried out in a split plot design based on Randomized Complete Blocks with 3 replications. Zinc rates (Zinc sulphate) were arranged as main factor with 3 levels (0, 2 and 4 spraying times with a dosage of 2.5/1000) and 10 safflower genotypes consisting 7-433, Isfahan 28, Shiraz landrace, Gol-sefid, Isfahan landrace, Isfahan 14, Kashan landrace, Arak 2811, 22-191 and IL-111 as sub factor. Traits such as yield and yield components (head number/plant, seed number/head, head diameter, 1000-seed weight), culm length, number of branches, biological yield and harvest index were measured. Variance analysis showed that higher levels of Zinc had significant effect on biological yield, head number/plant, seed yield and harvest index, but it was insignificant for seed number/head, 1000-seed weight and number of branches. The highest seed and biological yields were obtained from 4 times Zinc spraying. The studied genotypes highly significantly affected all studied traits but head diameter. Interactions of Zinc rates and genotypes were highly significant for head number/plant, number of branches, seed yield and harvest index. Genotypes IL-111 and 22-191 with the highest 1000-seed weight, seed yield, biological yield, harvest index, head number/plant in 4 times Zinc spraying showed the best performance. Based on correlation coefficients analysis, seed yield showed positive significant correlation with head number/plant (0.568**), biological yield (0.735**). According to regression analysis results, head number/plant explained 36 percent of seed yield variation and entered as the first significant variable to the regression model, and it could be considered as the most important trait in increasing the yield among the studied traits.