ArticleScientific reports2025
Multi-model-based validation of multi-environment trial results in horse gram (Macrotyloma uniflorum Lam. Verdc.).
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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9 authors.
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Abstract
Analysis of genotype-by-environment interactions (GEI) is critical for evaluating the yield and stability of genotypes in multi-environment experiments (METs). Either fixed models (AMMI and GGE biplots) or random effect models (Linear mixed models: LMM) are utilised to estimate GEI. From our preliminary METs using fixed models, a few potential horse gram mutant genotypes (G1, G3, G25, & G27) were identified. To validate this finding, confirmatory METs were performed during the 2023 (E1, E2, & E3) and 2024 (E4, E5, & E6) cropping seasons using LMM and the yield relative to the environmental maximum (YREM) index at pulses experimental farm, Coimbatore (E1 & E4), sugarcane research station, Melalathur, Vellore (E2 & E5), and farmer's field, Krishnagiri (E3 & E6). The traits positively and significantly correlated with yield were utilized for LMM and YREM analyses. The YREM value ranged from 0.55 to 1.00. The genotype G1 exhibited the highest YREM of 1.00, indicating that the crossover GEI effect did not affect its yield potential. After the likelihood ratio test (LRT), BLUP analysis was performed and identified the promising genotypes G1, G3, G22, G25, G27, and G8 based on higher predicted mean values. The genetic variance components (GVC) estimation showed low R² GEI (0.056 to 0.539), high 'As' (0.993 to 0.785), low to high r
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