Document Type : Research Article
Authors
1
Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
2
Seed and Plant Improvement Research Department, South Kerman Agricultural and Natural Resources Research and Education Center, AREEO, Jiroft, Iran
3
Seed and Plant Improvement Dept., Ardabil Agricultural and Natural Resources Research Center, AREEO, Ardabil, Iran
10.22067/jcesc.2025.91336.1368
Abstract
Introduction
The importance of sesame as a key crop in numerous regions can be attributed to its adaptability to dry climates, the nutritional value of its oil, and its health advantages. The necessity of improving the sesame plant is important by its comparatively low yield. The use of improved cultivars by plant breeding and breeding methods has resulted in a higher yield and higher quality of crops, which in the case of sesame plants include a greater increase in the seed yield and improvement in its quality. In a breeding program, the increase in genetic diversity allows the selection of better genotypes, and a more effective selection process will lead to a more successful breeding program. The utilization of local sesame cultivars is crucial in breeding programs because of their potential to create superior genotypes. The better the relationships between yield and other related traits are known, the better and more effective they can be used as selection indicators for improvement purposes. The nature of the relationship between yield and its components determines what appropriate traits should be used in plant breeding.
Materials and Methods
To discover the correlations among seed yield and some important agricultural traits in order to determine the direct and indirect effects of each trait on seed yield and finally to choose the ideal genotypes in terms of various characteristics, a total of 36 local sesame cultivars were evaluated in 3 regions (Karaj, Moghan and Jiroft) by using a randomized complete block design for two years (2017-2018). A total of 14 quantitative traits were studied in this study, including measurements like the number of days from germination to the beginning of flowering, the number of days from germination to the beginning of maturity, the height of the first capsule from the plant crown, the height of the plant, the number of branches, the number of capsules in one plant, the number of seeds in one Capsule, seed weight of one capsule, the weight of 1000 seeds, capsule length, capsule width, capsule diameter, biological performance and seed yield.
Results and Discussion
The calculation of simple correlation coefficients showed that the height of the first pod from the plant crown, seed weight of a capsule, biological yield, number of seeds in a capsule and plant height have the highest correlation coefficients with seed yield. The height of the first capsule from the plant crown, the number of seeds in the capsule and the height of the plant were demonstrated by path analysis had the most positive direct effect and the number of days until the start of maturity had the most negative direct effect on seed yield and it is suggested that they be used as selection indicators for the improvement of seed yield. Five components were identified through the results of the principal components analysis which explained 77.92% of the variations in the data. Out of all the genotypes analyzed in terms of yield, genotypes 78-730, 78-229, and 78-570, displayed the greatest seed yield on the biplot generated by the first and second components. All evaluated traits led to the identification of four separate groups through cluster analysis. In general, it was concluded that the cultivars in the first group include late-flowering cultivars with high height and high yield, the cultivars of the second group include late-flowering and low-capsule cultivars with low yield, the cultivars of the third group include early-flowering and early-maturing cultivars with long capsules, the cultivars of the fourth group included cultivars with small capsules but with a high number of seeds.
Conclusion
It was shown by cluster analysis that there was no connection between the classification of genotypes and their geographical placement and predominantly, the genotypes were classified by their physical distinctions and morphological differences. It can be concluded from the results that principal components analysis and cluster analysis exhibit similarities in their ability to segregate cultivars and genotypes. Their analysis outcomes give us a better understanding of the genetic structure and helps identifying specific genetic populations that have the potential to improved breeding programs.
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