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The main purpose of the study was to determine the suitable selection method for genetic improvement in chickpea. The current investigation was conducted at the research area of the Arid Zone Research Institute, Bhakkar, Punjab, Pakistan. Twelve chickpea genotypes were sown in RCBD following three replicates. Data regarding primary & secondary per plant, days for maturity, plant height as well as potential yield were recorded. The measured data were analyzed to principal component analysis (PCA), correlation, and path coefficient analysis. Analysis of variants revealed good variation among the accessions for the data recorded traits. Principal coefficient analysis differentiates all the traits into six PCs. Two components expressed more than one Eigenvalue which collectively contributed 80.12% towards the genetic variation. High positive loadings were expressed by the secondary branches per plant and pods per plant in all components. Path analysis revealed that secondary branches/plants expressed the highest direct positive effect (0.872) grain yield followed by the pods per plant (0.623). Analysis of correlation coefficient also confirmed the highest significant contribution of secondary branches per plant (91.57%) followed by pods (78.12%) and each plant's primary branches (64%). It was proved from the current experiment that Plants with secondary branches as well as pods may be focused on while assessing meaningful selection criteria for genetic improvement in chickpea. [ABSTRACT FROM AUTHOR]

The main purpose of the study was to determine the suitable selection method for genetic improvement in chickpea. The current investigation was conducted at the research area of the Arid Zone Research Institute, Bhakkar, Punjab, Pakistan. Twelve chickpea genotypes were sown in RCBD following three replicates. Data regarding primary & secondary per plant, days for maturity, plant height as well as potential yield were recorded. The measured data were analyzed to principal component analysis (PCA), correlation, and path coefficient analysis. Analysis of variants revealed good variation among the accessions for the data recorded traits. Principal coefficient analysis differentiates all the traits into six PCs. Two components expressed more than one Eigenvalue which collectively contributed 80.12% towards the genetic variation. High positive loadings were expressed by the secondary branches per plant and pods per plant in all components. Path analysis revealed that secondary branches/plants expressed the highest direct positive effect (0.872) grain yield followed by the pods per plant (0.623). Analysis of correlation coefficient also confirmed the highest significant contribution of secondary branches per plant (91.57%) followed by pods (78.12%) and each plant's primary branches (64%). It was proved from the current experiment that Plants with secondary branches as well as pods may be focused on while assessing meaningful selection criteria for genetic improvement in chickpea. [ABSTRACT FROM AUTHOR]