Characters associations and principal component analysis for quantitative traits of sesame (Sesamum indicum L.) genotypes from Ethiopia

Abstract

To identify sesame genotypes with superior yield performance and related agronomic traits, a field experiment was conducted using a simple lattice design with two replications comprising of 196 accessions and released varieties. Principal component analysis (PCA) indicated that among the twelve extracted components, the first three PC1 (eigenvalue = 3.97), PC2 (eigenvalue = 1.88), and PC3 (eigenvalue = 1.03) accounted for the majority of the variability associated with yield and yield-contributing characteristics. The three principal components PC-I through PC-III with eigenvalues greater than one account for 57 % of total variance among 196 genotypes. Yield per plot showed significant and positive correlation with plant height (0.63), pod per plant (0.43), days to fifty percent flowering (0.27), and primary branch (0.39). In phenotypic path analysis diameter plant height (0.547), branch per plant (0.085), days to fifty percent flowerung (0.019), and pod per plant (0.112) showed positive direct effect on yield per plot. Traits viz., plant height, pod per plant, and height from ground to first branch exhibited a positive direct effect on yield per plant. This comprehensive study provides key insights into the intricate relationships among sesame traits, highlighting how genotype selection using a multi-trait index can effectively guide future breeding and cultivation strategies.