Line × tester analysis is an efficient method to evaluate many entries for GCA (general combining ability) and SCA (specific combining ability) effects. Fifteen lines and three testers of sesame (Sesamum indicum L.) gained evaluation for shattering, yield, and oil quality traits. Crossing selected tolerant and sensitive accessions in line × tester fashion ensued, with the resultant F₁, parent material, and commercially cultivated varieties sown in the field to ascertain the genetic mechanisms to assess heterosis manifestation and generation turnover. Combining ability analysis exhibited variable direction and magnitude of GCA effects among line and testers and SCA effects among crosses. The lines SG-41, G-43, and SG-50 and testers SG-60 and SG-1 were the best general combiners. Crosses SG-44 × SG-60, SG-50 × SG-60, SG-103 × SG-14, SG-103 × SG-60, SG-110 × SG-14, SG-50 × SG-1, and SG-113 × SG-60 had a positive significant SCA effect for maximum yieldrelated traits. SG-39 × SG-60, SG-44 × SG-60, and SG-50 × SG-60 had positive significant SCA effects for maximum oil-related qualities. Crosses SG-41 × SG-1, SG-41 × SG-60, SG-43 × SG-60, SG-50 × SG-14, and SG-50 × SG-60 had positive and significant heterosis over the mid-parent, a better parent, and commercial hybrids for most of the traits. Conditioning on secondary branches, flower initiation, capsule length, and 1000-seed weight were by non-additive genetic effect, with all the other parameters under the control of additive gene action. The variance ratio of GCA to SCA showed less than unity; in contrast, the additive genetic variance was more than the dominant variance for all traits except for secondary branches, flower initiation, capsule length, and 1000-seed weight. The association of traits based on correlation and path analyses suggested that plant height, oil content, and 1000-seed weight can serve as criteria for selecting sesame for a future breeding program.

Keywords: Sesame (Sesamum indicum L.), heterosis, line × tester analysis, GCA and SCA, gene action, correlation

Key findings: Crosses SG-44 × SG-60, SG-50 × SG-60, SG-103 × SG-14, SG-103 × SG-60, SG-110 × SG-14, SG-50 × SG-1, and SG-113 × SG-60 had the positive significant SCA effects for maximum yield-related traits; these crosses were best specific combiners for most of the traits.