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Genotype × environment (G × E) interactions play a crucial role in identifying mungbean genotypes with stable performance across diverse environments. Understanding these interactions enables breeders to select adaptable genotypes that maintain high yield potential and stress resistance under varying climatic and environmental conditions. This study focuses on analyzing G × E interactions to identify mungbean genotypes with superior adaptability and stability, contributing to the development of resilient varieties for sustainable production. The present study was conducted to examine the genotype × environment (G × E) interactions for seed yield of mungbean genotypes in order to identify adaptable and stable genotypes over diverse environments. The trials were conducted in six locations during yala 2020 and maha 2020/21. Location × season combination was taken as an environment so that 12 environments were included in the study. Six mungbean genotypes were evaluated for their adaptability over diverse environments using regression and variance component methods for data analysis. In the regression method the linear regression coefficient and deviation from regression and in the variance component method variance of the genotypic deviations from the environmental means were used as stability parameters. In the study, adequate environmental diversity for a successful adaptability evaluation of mungbean genotypes was achieved. In both the regression and variance component methods, the GE interaction was found to be significant. Both the methods, evaluated adaptability of mungbean genotypes over diverse environments similarly. However, use of the variance component method and interpretation of results of that method appeared comparatively less complicated and much easier. The genotypes MMIB 14-254 and MIMB 14-156 were identified as the most and least adaptable genotypes, respectively. Both ANK 118 and MI 6 exhibited similar level of adaptability but less adaptable than ANK 41 Meanwhile, ANK 48 was identified as a genotype with low adaptability.

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Analysis of Genotype × Environment Interactions to Identify Adaptable Mungbean (Vigna radiate (L) Wilezelc) Genotypes Over Diverse Environments

  • 会议论文

  • 发表日期：

    2025年

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  • M. J. M. P. Kumararathna,
  • D. S. De. Z. Abeysiriwardena,
  • E. K. E. C. Nayana,
  • W. M. R. Kumari,
  • R. R. P. S. Ariyawansha

摘要

Genotype × environment (G × E) interactions play a crucial role in identifying mungbean genotypes with stable performance across diverse environments. Understanding these interactions enables breeders to select adaptable genotypes that maintain high yield potential and stress resistance under varying climatic and environmental conditions. This study focuses on analyzing G × E interactions to identify mungbean genotypes with superior adaptability and stability, contributing to the development of resilient varieties for sustainable production. The present study was conducted to examine the genotype × environment (G × E) interactions for seed yield of mungbean genotypes in order to identify adaptable and stable genotypes over diverse environments. The trials were conducted in six locations during yala 2020 and maha 2020/21. Location × season combination was taken as an environment so that 12 environments were included in the study. Six mungbean genotypes were evaluated for their adaptability over diverse environments using regression and variance component methods for data analysis. In the regression method the linear regression coefficient and deviation from regression and in the variance component method variance of the genotypic deviations from the environmental means were used as stability parameters. In the study, adequate environmental diversity for a successful adaptability evaluation of mungbean genotypes was achieved. In both the regression and variance component methods, the GE interaction was found to be significant. Both the methods, evaluated adaptability of mungbean genotypes over diverse environments similarly. However, use of the variance component method and interpretation of results of that method appeared comparatively less complicated and much easier. The genotypes MMIB 14-254 and MIMB 14-156 were identified as the most and least adaptable genotypes, respectively. Both ANK 118 and MI 6 exhibited similar level of adaptability but less adaptable than ANK 41 Meanwhile, ANK 48 was identified as a genotype with low adaptability.