Multivariate analysis in chickpea genotypes under timely sown condition

Abstract

Yield, a multifaceted trait influenced by genetic and environmental factors, requires a comprehensive assessment beyond emphasizing only on yield alone. Thus, understanding the intricate relationship between yield and its associated traits across diverse chickpea genotypes is essential. The current investigation was undertaken at the Breeder seed production unit, JNKVV, Jabalpur, Madhya Pradesh, during the 2021-22 cropping season. Significant variations were found by analysis of variance (ANOVA) among the 40 genotypes under study, indicating substantial variability. Post hoc DMRT analysis further confirmed notable genetic diversity across all traits. Regression and Principal component analysis highlighted the significance of optimizing biological yield per plant, effective pods, total number of pods, and secondary branches to enhance grain yield. Strategic selection prioritizing these traits can facilitate the development of high-yielding chickpea varieties with enhanced agronomic characteristics. This analysis identified five principal components explaining 80.74% of genotypic variability. Ultimately, the genotypes ICCV 211210, RVG-204, and ICCV 211206 emerged as promising based on PC scores.

Keywords

• chickpea
• dmrt
• regression
• pca
• yield