Utilizing Selection Indices and Discriminant Function Analysis to Enhance Seed Yield in Sesame (Sesamum indicum L.)

Abstract

The current study focuses on harnessing genetic variation and employing selection indices for evaluating thirty-four advanced sesame breeding lines, alongside four checks (DS-5, DSS-9, JTS-8, and TKG-22). The evaluation encompassed the assessment of fifteen quantitative traits during the summer of 2022 at the AICRP on Sesame and Niger, MARS, UAS, Dharwad. Particularly noteworthy was the high genotypic and phenotypic coefficient variation observed for traits such as the number of secondary branches per plant, yield per plant (g) and seed  yield (Kg/ha). The highest heritability coupled with the greatest genetic advance over the mean was detected for the number of primary branches per plant, suggesting a predominant role of additive genetic components in their expression and indicating a promising avenue for  direct selection. The study involved the construction of thirty-one selection indices using the discriminant function technique, which incorporated five key traits: seed yield per plant (g) (X1), days to maturity (X2), number of productive capsules per plant (X3), thousand seed weight (g) (X4), and oil content (%) (X5). Among these various selection indices, the one comprising all component characters (X1, X2, X3, X4, and X5) exhibited the highest expected genetic advance and relative efficiency.