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Vol. 11, Issue 1 (2022)

Principal component analysis based on yield and its attributing traits in tomato (Solanum lycopersicum L.) Genotypes

Author(s):
Mukul, Sandhya, Manoj Kumar and RK Agarwal
Abstract:
In the present study thirty genotypes were assessed with principal component analyses (PCA) based on yield and its attributing traits to select genotypes and existence of variability for future breeding program. Based on the PCA with twenty traits, twenty components were formed however, 6 PCs had more than 1 Eigen value with the variability of 78.73%. So, these six PC were used for further relevant information and individual contribution of PC1, PC2, PC3, PC4, PC5 and PC6 were 25%, 17%, 13%, 9%, 8% and 7% respectively. The first principal component explained maximum variability of the total variation presented. Primary branches, secondary branches, clusters per plant, locule number, and average fruit weight, juice-pulp ratio, fruit yield per plan, lycopene and carotene etc. traits showed maximum positive contribution towards genetic divergence in PC1. Therefore, the important traits gather collectively from diverse PCs and influence towards dimorphism may be kept into consideration during utilization of these traits in improvement of tomato breeding programme.
Pages: 1836-1841  |  734 Views  387 Downloads


The Pharma Innovation Journal
How to cite this article:
Mukul, Sandhya, Manoj Kumar, RK Agarwal. Principal component analysis based on yield and its attributing traits in tomato (Solanum lycopersicum L.) Genotypes. Pharma Innovation 2022;11(1):1836-1841.

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