ArticleBMC plant biology2024
Cultivating sustainable futures: multi-environment evaluation and seed yield stability of faba bean (Vicia faba L.) genotypes by using different stability parameters in Ethiopia.
Article in BMC plant biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- Rethinking yield stability through phenotypic plasticity and its link to modern statistical methods.Journal of experimental botany · 2026Review
- Integrating AMMI, Bayesian-AMMI, BLUP, and GGE biplot models to improve the identification of high-yielding and stable barley genotypes.BMC plant biology · 2026Article
- Genotype-by-environment interactions and seed yield stability of narrow-leaf lupin sweet varieties (Lupinus angustifolius L.) based on AMMI and GGE biplot analyses.Scientific reports · 2026Article
- Article
- Yield Stability of Soybean Variety Morkhor 60 in Integrated Rotation Systems of Northeastern Thailand.Plants (Basel, Switzerland) · 2025Article
- Multi-environmental evaluation of barley core collection against spot blotch for genetic variability and identification of promising genotypes exhibiting resistance.BMC plant biology · 2025Article
- Genotype × environment interactions for potato yield and quality traits: Identification of ideotypes adapted in different ecological regions of Northwest China.BMC plant biology · 2025Article
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8 authors.
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Abstract
Faba bean is an important legume crop with significant potential to contribute to sustainable agricultural systems and food security in Ethiopia. Despite its importance, the crop is prone to various biotic and abiotic constraints that can reduce seed yield and affect its stability and adaptability. To identify stable and adaptable genotypes, 10 faba bean genotypes were evaluated at three locations over two growing seasons using different stability parameters. Genotype-by-environment interaction (GGE biplot) and additive main effect and multiplicative interaction (AMMI) analyses are the statistical methods used to evaluate crop genotype performance across different environments to identify high-performing, stable, and adaptable genotypes and to highlight preferable environments for genotype differentiation. This study utilized cultivar superiority, regression coefficients, and deviations from regression parameters that provide valuable insights into genotype performance under varying environmental conditions. This approach helps to identify robust cultivars that can thrive across different agricultural settings and challenges, ultimately contributing to improved crop production and food security. The results revealed that G9, G8, and G7 are the three most stable and adaptable genotypes. These faba bean genotypes showed greater resilience to environmental changes and improved suitability for sustainable production, making them better options for local farmers. They also bolster resilience against climate variability and ultimately ensure agricultural sustainability. The AMMI model indicated that the genotype-environment interaction (GEI) significantly influences seed yield. These findings provide crucial insights into the genetic potential of faba bean genotypes that can help breeding programs to develop high-yielding, adaptable, and stable varieties for the region and other areas with similar agro-ecological conditions.
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