1Department of Vegetable Science, HC&RI, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India
2Department of Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India
3Department of Plant Pathology, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India
4Department of Nematology, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India
*E-Mail: purushothj14@gmail.com
Online published on 15 October, 2022.
A total of 36 tomato accessions were subjected to principal component analysis (PCA) based on seventeen yield and quality traits. The overall variation was split into seven major principle components, which accounted for 81.62 per cent of the total variation. The bi-plot was constructed using the first two PCs, in which the genotypes CBESL133, CBESL129, CBESL115, CBESL121, CBESL101, CBESL114, CBESL136, CBESL102 and CBESL111 were dispersed across all four quadrates, indicating the greatest genetic divergence. The first two PCs contributed the most divergence due to the yield and yield related traits. In Pearson's correlation analysis, the number of fruits per plant, the number of clusters per plant, plant height, single fruit weight and ascorbic acid content were positive and significantly associated with yield per plant. The lines grouped under PC1 and PC2 were suitable for the yield improvement breeding programme. The lines suitable for processing come under PC4 and PC5.
PCA, Diversity, Tomato, Correlation, Multivariate analysis