Nonparametric stability analysis of grass pea genotypes under rainfed conditions

Vaezi, Behrouz , Zeinalzadeh-Tabrizi, Hossein , Pirooz, Reza , Hatami Maleki, Hamid

2026-12-31 COGENT FOOD & AGRICULTURE 2026   12(卷), 1(期), (null页)

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A study evaluated the stability of 16 grass pea genotypes across 12 diverse rainfed environments in western and southwestern Iran over three years (2017-2020) using nonparametric stability measures. Significant genotype-by-environment (G x E) interactions highlighted challenges in selecting stable, high-yielding genotypes. The grand mean yield was 1.39 t/ha. Negative correlations between yield-oriented measures (Kang's Yield-Stability Index, YS; Fox's TOP) and rank-consistency statistics (H & uuml;hn's S-1-S-6; Thennarasu's N-1-N-4) highlighted contrasting stability concepts. A sequential sieving procedure was therefore applied: genotypes with mean yield < similar to 1.50 t/ha were excluded, followed by retention of those with YS >= population mean (5.44) and TOP >= 4; rank-consistency parameters characterized residual sensitivity without further elimination. This approach identified genotypes 3, 1, 4, and 6 as superior, combining high grain yield (>1.48 t/ha) with reasonable stability across variable rainfed conditions. These genotypes are recommended for breeding programs targeting climate-resilient cultivars in marginal environments. Integrating multiple nonparametric metrics with prioritized yield potential proved essential for robust selection, supporting sustainable agriculture and food security in arid and semi-arid regions.