GGE Biplot Model Based Yield Stability Analysis in Chickpea (Cicer arietinum L.)

Abstract

The present study evaluates the yield stability of eight chickpea genotypes across three locations in two seasons to identify high-yielding, stable genotypes suitable for Odisha. The analysis of variance (ANOVA) indicated significant effects of genotypes, environments, and their interactions (G×E) on the traits measured. Pooled ANOVA indicated highly significant differences for key agronomic traits such as days to 50% flowering, plant height, number of pods per plant, and 100-seed weight, while seed yield exhibited significant variation. The GGE biplot analysis was used to assess genotype stability and adaptability. Mean vs. stability analysis showed that ICCV 14102 had the highest mean grain yield, whereas ICCV 15114 was the most stable genotype. The ‘which-won-where’ biplot demonstrated three distinct mega-environments: the first, containing E6, was dominated by ICCV 15118 and JAKI 9218; the second, comprising E4 and E5, was led by ICCV 14108; and the third, covering E1, E2, and E3, identified ICCV 14102 as the best performer. When ranking genotypes in relation to an ideal genotype indicated ICCV 14108 as the most preferred, followed by ICCV 14102, ICCV 15115, and JAKI 9218. Similarly, environments were ranked based on their discriminating power and representativeness, with E4 emerging as the most ideal environment, followed by E5, E2, and others. The results highlight the effectiveness of GGE biplot analysis in genotype selection by providing insights into adaptability, stability, and performance across diverse environments. These findings provide valuable insights for the development of high-yielding and stable chickpea varieties in Odisha, with potential applications in other regions facing similar environmental challenges.