1Department of Vegetable Science, Chaudhary Charan Singh Haryana Agricultural University, Hisar-125 004, Haryana, India.
*Corresponding Author: S.K. Dhankhar, Department of Vegetable Science, Chaudhary Charan Singh Haryana Agricultural University, Hisar-125 004, Haryana, India. Email: dhankharsk@gmail.com
Cowpea (Vigna unguiculata L.) is a nutritionally valuable pulse crop with considerable scope for improving dietary protein and mineral intake. Assessing genetic variability in yield and yield related attributes is necessary in finding promising cowpea genotypes for breeding initiatives under semi-arid conditions of Haryana.
A pot experiment was conducted at Chaudhary Charan Singh Haryana Agricultural University, Hisar during the summer season of 2023-24 to evaluate genotypic variability in seed yield and yield attributes of ten cowpea varieties. The experiment was laid out in a completely randomized design (CRD) using three replications with uniform agronomic and nutrient management practices. Growth and yield parameters including plant height, number of branches, days to 50% flowering, number of pods per plant, number of seeds per pod, seed yield per plant and test weight were recorded at harvest while pod weight, pod length and pod yield per plant were recorded at tender green pod stage.
Correlation analysis revealed that seed yield per plant showed strong and significant positive associations with number of pods per plant (r = 0.812), pod length (r = 0.866), number of seeds per pod (r = 0.813), pod weight (r = 0.860) and test weight (r = 0.840). Similarly, pod yield per plant was strongly correlated with number of pods per plant (r = 0.849), pod length (r = 0.871), pod weight (r = 0.885) and seed yield per plant (r = 0.878). Principal component analysis (PCA) explained 96.17% of total variation among the first three components, with PC1 representing a yield axis dominated by number of pods per plant, pod length, pod weight, test weight, seed yield per plant and pod yield per plant. Genotypes Kashi Kanchan and Cowpea-263 consistently had highvalue of yield attributes, highlighting their effectiveness of multivariate analysis in identifying promising cowpea genotypes for breeding under semi-arid conditions.
Correlation, Cowpea, Genotypic variation, Principal component analysis, Yield attributes