عنوان مقاله [English]
More than 90% of the total oil consumed in the country is imported abroad. Therefore, the development of oilseed cultivation and research programs in this field should be considered. Water deficit stress is one of the most important environmental stresses that has limited the successful production of crops, especially in dry and semi-arid regions. Sesame is one of the most important seed economical products that has good compatibility with dry and semi-arid regions such as Iran. Since yield is a bit complicated trait and controlled by a large number of genes, the effect of each gene is small and environmental factors can have a great effect on it. Therefore, identifying yield components that have more inheritance than yield and, on the other hand, have high correlation with it, can increase the efficiency of selection. So in breeding programs, it is important to examine the components of yield and how they affect each other to achieve high yield. One of the methods for analyzing the components of yield is stepwise regression. In this method, traits that have the greatest share in explaining the variation of yield are distinguished among a large number of traits. Identifying the appropriate and effective traits of yield can be the basis for selection in breeding programs and can be used to increase grain yield.
Materials and Methods: This research was conducted as split plot based on a randomized complete block design with three replications in the research field of seed and plant improvement institute, agricultural research, education and extension organization of Karaj, in summer of 2016. Two factors including irrigation regimes (as main factor) and cultivars (as sub factor) were investigated. Two irrigation regimes including irrigation after 40% soil moisture utilization in soil (no stress) and irrigation after 80% moisture utilization in soil (low irrigation stress) in main plots and 6 sesame cultivars named Halil, Dashtestan 2, Darab 1, Oltan, Yellow White and Naz tak shakheh in sub plots were considered. Correlation analysis, stepwise regression, principal components analysis and path analysis were used to analyze the components of yield. Correlation analysis, stepwise regression and path analysis were performed using SPSS software version 23, principal components analysis and two-dimensional diagram (bi-plot) with Minitab software version 17. The measured traits included seed yield, dry weight of plant, height, secondary branches number, number of capsules per plant, number of seeds per capsule, 1000 seed weight, seed oil percentage, oil yield, seed protein percentage and seed protein yield.
Results: In non-stress and stress conditions, the highest positive and significant correlation was observed between seed yield and oil yield. In non-stress condition, seed number per capsule and number of capsules in the plant and seed oil percentage were the most effective positive variables on seed yield. 1000 seed weight had the most direct positive effect on seed oil percentage. In stress condition, seed protein percentage and secondary branches number had the highest negative effects on seed yield, respectively. Seed protein percentage had the most direct positive effect on oil percentage. The main components analysis showed that in non-stress condition, seed yield, capsule number, oil yield and protein yield had high correlation with the first component and 51.1% of the variation was explained. Based on this component, Oltan and Dashtestan cultivars were better in terms of seed, oil and protein yield than other cultivars.
In stress condition, seed yield, oil yield and protein yield had high correlation with the first component and explained 37.5% of the variation. Halil, Oltan and Yellow White cultivars were not desirable on the basis of this component, which was the component of seed, oil and protein yield.