Genetic Divergence and Population Structure in Sprouting Broccoli (Brassica oleracea var. italica Plenck) Revealed through Cluster and Principal Component Analyses
Aasif Fayaz
Division of Vegetable Science, SKUAST-K Shalimar, Srinagar 190025, India.
Rukhsar Ahmad Dar
Division of Vegetable Science, SKUAST-K Shalimar, Srinagar 190025, India.
Asima Amin *
Division of Vegetable Science, SKUAST-K Shalimar, Srinagar 190025, India.
Baseerat Afroza
Division of Vegetable Science, SKUAST-K Shalimar, Srinagar 190025, India.
Rizwan Rashid
Division of Vegetable Science, SKUAST-K Shalimar, Srinagar 190025, India.
Gowhar Ali
Division of Genetics and Plant Breeding (NSP), SKUAST-K Shalimar, Srinagar 190025, India.
Ummyiah H Masoodi
Division of Vegetable Science, SKUAST-K Shalimar, Srinagar 190025, India.
Syed Berjes Zehra
Division of Vegetable Science, SKUAST-K Shalimar, Srinagar 190025, India.
Gazala Nazir
Division of Vegetable Science, SKUAST-K Shalimar, Srinagar 190025, India.
Mudasir Magray
Division of Vegetable Science, SKUAST-K Shalimar, Srinagar 190025, India.
Aabid Ayoub
Division of Vegetable Science, SKUAST-K Shalimar, Srinagar 190025, India.
Aziz Mujtaba Aezum
Division of Soil Science, SKUAST-K Shalimar, Srinagar 190025, India.
*Author to whom correspondence should be addressed.
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.
Keywords: Principal Component Analysis (PCA), cluster mean, broccoli, genetic divergence