Genetic Divergence and Population Structure in Sprouting Broccoli (Brassica oleracea var. italica Plenck) Revealed through Cluster and Principal Component Analyses

Abstract

The present investigation was carried out on 28 genotypes of broccoli (Brassica oleracea var. italica Plenck) at the Experimental Vegetable Farm, ETC Malangpora, Pulwama, during the Rabi season of 2023. The trial was laid out in a Randomized Complete Block Design (RCBD). To evaluate genetic divergence and identify promising genotypes, Principal Component Analysis (PCA) and cluster analysis were utilized. Three principal components (PC1 to PC3) with eigenvalues greater than one accounted for 88.66% of the total phenotypic variation. Traits like curd weight (0.97%), curd depth (0.96%), and curd yield (0.97%) contributed predominantly to PC1, while total soluble solids (0.91%) and acidity (0.83%) influenced PC2. PC3 was primarily explained by plant height (0.55%) and curd diameter (0.12%). Based on cluster analysis, the genotypes were grouped into four distinct clusters, indicating substantial genetic diversity. Cluster 1 comprised the most genotypes (12), followed by cluster 2 (11), while clusters 3 and 4 included three and one genotype(s), respectively. The highest inter-cluster distance was observed between clusters 1 and 4 (1159.60), highlighting significant divergence, while the lowest was between clusters 1 and 2 (77.81). The analysis of cluster means provided essential insights for selecting diverse and superior genotypes for future breeding efforts.