Combining Ability and Genetic Analysis of Grain Yield and its Component Traits in Maize Lines Differing in Turcicum Leaf Blight (TLB) Response
Susmita Cherukuri, Vipparthi Hemalatha, Kondajji Rangappa Yathish, Chikkappa Gangadhar Karjagi, Mallikarjuna N, Prema G U, Rakesh Kumar Develash, Omkar Kumar, Sunil Neelam, Sushil Pandey, Jyoti Kumari, Sherry Rachel Jacob, Badal Singh
Journal of Advances in Biology & Biotechnology · pp. 1377–1393 · Published 29 Dec 2025
10.9734/jabb/2025/v28i123479Abstract
The present study employed a 9 × 9 half-diallel mating design to estimate GCA and SCA effects among TLB-contrasting maize inbred lines, enabling the precise identification of superior parents and hybrid combinations for yield enhancement. Nine inbred lines were crossed during rabi 2023-24, and the resulting hybrids along with their parents were evaluated during kharif 2024 at Mandya and Dharwad in RBD with two replications for phenology, plant traits, grain yield and its components. A combined analysis across locations was conducted to assess parental and hybrid performance and to estimate key genetic parameters underlying trait inheritance. Combining ability ANOVA revealed significant GCA and SCA effects for most traits, indicating the contribution of both additive and non-additive gene actions, as well as substantial genetic variability among crosses. Significant site × genotype interactions for several traits further emphasized the influence of environmental variation on additive and dominance effects, underscoring the need for multi-environment testing to identify stable, high-performing genotypes. Genetic parameter estimates indicated that flowering traits were predominantly governed by additive gene action, whereas plant stature, major yield components, and grain yield were largely influenced by non-additive effects, as supported by GCA-SCA ratio, Baker’s ratio, and variance components. Although broad-sense heritability was moderate to high for most traits, narrow-sense heritability remained low, suggesting limited additive variance and highlighting the relevance of hybrid breeding, recurrent selection, or marker-assisted approaches over direct phenotypic selection. GCA analysis identified P5 as a strong general combiner for multiple yield traits, while P6 was superior for early flowering and reduced plant height. SCA analysis highlighted promising cross combinations, particularly P3 × P7, P2 × P6, P6 × P8, and P3 × P5 for improving key yield-related traits and overall maize productivity.
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