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Integrating line × tester analysis and GGE biplot to identify superior sweet corn hybrids in tropical environments

agricultural-science
genetics
plant-science

Abstract

Sweet corn (Zea mays saccharata L.) is a high-value crop for both food and industry, yet its productivity is constrained by strong genotype × environment (G × E) interactions that reduce yield stability. Developing superior hybrids requires accurate estimation of general combining ability (GCA) and specific combining ability (SCA). This study evaluated 20 inbred lines and 4 testers (80 hybrids) across two contrasting seasons in Garut, Indonesia, using a line × tester design and GGE biplot analysis. Significant variation was observed for all yield-related traits, with dominance effects exceeding additive effects, illustrating the value of non-additive gene action in hybrid development. GGE biplot identified L18 as the best general combiner for ear diameter and length, L2 for kernel row number, L9 for ear weight, L4 for biomass, L12 for brix, and L20 for yield. Optimal testers were T1 for brix, T2 for ear length and kernel row number, and T3 for ear weight and diameter. Superior hybrids with strong SCA included L2 × T4, L5 × T4, and L12 × T1, which consistently outperformed across seasons.

This is the first comprehensive application of GGE biplot for dissecting GCA and SCA in tropical sweet corn under dual-season conditions in Indonesia. The identified parental lines and hybrids provide a valuable resource for breeding stable, high-yielding sweet corn adapted to tropical environments.

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