Work

Nonparametric stability analysis of grass pea genotypes under rainfed conditions

Year: 2025
Type: article
Abstract: 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 × 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 (Hühn’s S1–S6; Thennarasu’s N1–N4) highlighted contrasting stability concepts. A sequential sieving procedure was therefore applied: genotypes with mean yield < ∼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.
Language: English
Subfield: Plant Science
Open Access status: diamond
OpenAlex ID: W7117301272
FWCI: 0.511
Cites: 40
Cited by: 1
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