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<p>Genetic variability among genotypes is essential for crop improvement. This variability supports varietal development through selection, inbreeding, and hybridization. In this study, we assessed genetic variability in maize genotypes and identified high-yielding, stable lines for Meghalaya. We evaluated 115 maize genotypes over three years using an augmented block design. There was significant variation in agro-morphological traits. Plant height, ear length, and number of rows showed strong positive associations with yield per plant. Morphological clustering grouped the landraces into two main clusters. The first principal component explained the most variation (26.01%), followed by the next four components. AMMI analysis, GGE biplot, and multi-trait stability index identified RCMGP28 and RCMGP126, along with RCMGP27, RCMGP120, and RCMGP27, as stable, high-yielding landraces. Some others performed well in specific environments. Overall, the study found considerable genetic variability and divergence among the landraces, and the selected ones can be used in breeding programs.</p>

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Genetic variability and genotype by environment interaction studies using AMMI and GGE biplot analysis for maize (Zea Mays L.) in the north eastern Himalayas

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月24日

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  • Amit Kumar,
  • Nivedita Shettigar,
  • Avinash Pandey,
  • Shiv Poojan Singh,
  • W. S. Philanim,
  • Simardeep Kaur,
  • S. P. Das,
  • E. Lamalakshmi Devi,
  • Vinay Kumar Mishra

摘要

Genetic variability among genotypes is essential for crop improvement. This variability supports varietal development through selection, inbreeding, and hybridization. In this study, we assessed genetic variability in maize genotypes and identified high-yielding, stable lines for Meghalaya. We evaluated 115 maize genotypes over three years using an augmented block design. There was significant variation in agro-morphological traits. Plant height, ear length, and number of rows showed strong positive associations with yield per plant. Morphological clustering grouped the landraces into two main clusters. The first principal component explained the most variation (26.01%), followed by the next four components. AMMI analysis, GGE biplot, and multi-trait stability index identified RCMGP28 and RCMGP126, along with RCMGP27, RCMGP120, and RCMGP27, as stable, high-yielding landraces. Some others performed well in specific environments. Overall, the study found considerable genetic variability and divergence among the landraces, and the selected ones can be used in breeding programs.