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<p>Fodder maize plays an important role in livestock systems, but productivity is constrained by seasonal variability and unstable genotype performance. This study aimed to evaluate maize inbreds across seasons using an integrated selection framework to identify elite parental lines with high yield, adaptability and desirable forage quality for climate-resilient breeding. A total of 104 maize inbreds were evaluated across three seasons using an alpha-lattice design. Genotype performance and stability were assessed using Additive Main Effects and Multiplicative Interaction (AMMI)-based indices, Best Linear Unbiased Prediction (BLUP)-based indices, Genotype × Environment (G × E) interaction analysis and multi-trait selection indices. Based on these approaches, genotypes were classified into three models representing stability-based selection, integration of mean performance with stability and multi-trait selection. Significant G × E interactions were observed for all traits, indicating differential genotype responses across seasons. Model 2, integrating yield and stability, showed the highest genetic gain and effectively identified superior genotypes. Genotypes G85, G86 and G88 were consistently identified as high-yielding and stable across three models, while G12 and G27 were selected by at least two models. These genotypes also exhibited desirable forage quality, including moderate fibre fractions and higher crude protein. The integrated multi-model framework effectively identified elite maize inbreds combining high yield, stability and nutritional quality, providing valuable parental lines for developing climate-resilient fodder maize hybrids.</p> Graphical abstract <p></p>

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Integrated Stability Models and Multi-Trait Evaluation to Identify Superior Fodder Maize Genotypes Across Seasons

  • 期刊论文

  • 发表日期：

    2026年5月19日

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  • Ajith Periyasamy,
  • Pushpam Ramamoorthy,
  • Ravikesavan Rajasekaran,
  • Senthil Natesan,
  • Senthil Alagarsamy,
  • Uma Doraiswamy,
  • Sathya Sheela KRV,
  • Nivethitha Thangarasu

摘要

Fodder maize plays an important role in livestock systems, but productivity is constrained by seasonal variability and unstable genotype performance. This study aimed to evaluate maize inbreds across seasons using an integrated selection framework to identify elite parental lines with high yield, adaptability and desirable forage quality for climate-resilient breeding. A total of 104 maize inbreds were evaluated across three seasons using an alpha-lattice design. Genotype performance and stability were assessed using Additive Main Effects and Multiplicative Interaction (AMMI)-based indices, Best Linear Unbiased Prediction (BLUP)-based indices, Genotype × Environment (G × E) interaction analysis and multi-trait selection indices. Based on these approaches, genotypes were classified into three models representing stability-based selection, integration of mean performance with stability and multi-trait selection. Significant G × E interactions were observed for all traits, indicating differential genotype responses across seasons. Model 2, integrating yield and stability, showed the highest genetic gain and effectively identified superior genotypes. Genotypes G85, G86 and G88 were consistently identified as high-yielding and stable across three models, while G12 and G27 were selected by at least two models. These genotypes also exhibited desirable forage quality, including moderate fibre fractions and higher crude protein. The integrated multi-model framework effectively identified elite maize inbreds combining high yield, stability and nutritional quality, providing valuable parental lines for developing climate-resilient fodder maize hybrids.

Graphical abstract