Exploring combining ability for the selection of promising parents to harness heterosis for yield and associated traits in Indian mustard (Brassica juncea (L.) Czern & Coss)

The present investigation aimed to explore the combining ability of mutant lines of Indian mustard (Brassica juncea (L.) Czern & Coss) to identify promising parents and hybrid combinations for enhancing seed yield and associated traits through heterosis breeding. Ten mutant lines were crossed with three testers (Giriraj, RH-749, and HUJM-10-6) using a line × tester design during Rabi 2019-20, producing 30 F₁ hybrids. These hybrids, along with 13 parents and one national check (Kranti), were evaluated during Rabi 2020-21 at Banaras Hindu University under a randomized block design with three replications. Data were recorded on 16 agro-morphological and physiological traits, and analyzed using standard statistical methods for variance partitioning and estimation of general (GCA) and specific combining ability (SCA). The analysis revealed significant genetic variability among parents and hybrids for most traits. GCA effects were prominent for days to flowering and maturity, plant height, siliqua characteristics, and seed yield traits. Notably, TM-130, TM-117, and TM-263-3 were identified as superior general combiners for seed yield and biological yield, while RH-749 was the best tester. Hybrids such as RH-749 × TM-143, RH-749 × TM-217, RH-749 × TM-117, and HUJM-10-6 × TM-263-3 exhibited high SCA effects and outperformed the check variety in seed yield per hectare. The higher magnitude of SCA variance compared to GCA for most traits suggested the predominance of non-additive gene action, implying the potential of heterosis breeding. Crosses involving good × good and good × poor general combiners with high SCA effects are particularly valuable for developing superior transgressive segregants. The identified genotypes and hybrids hold significant promise for yield enhancement in mustard breeding programs and warrant further multilocation testing for stability and adaptability.