Principal Component Analysis for Assessing Genetic Variation and Key Traits in Bottle Gourd [Lagenaria siceraria (Molina) Standl.] Genotypes
Year: 2024
Type: article
Abstract: The present investigation was carried out at the Experimental field of Urban Technological Park Habbak, Srinagar, Jammu and Kashmir during kharif-2022. The experiment was laid out in Augmented Randomized Block Design with three blocks and plant spacing of 2×1 m for seventy-seven genotypes including two checks, Pusa Naveen and Pusa Santushti. Observations were recorded for growth and yield traits, seed traits and quality parameters. Principal Component Analysis (PCA) was carried out based on twenty-one quantitative and four quality characters in bottle gourd. Six out of the ten principal components, with eigen values above 1.0, explained 69.56% of the total variation. The first PC accounts for the maximum variability in the data i.e., 20.08%. The remaining variability of 17.90%, 10.05%, 8.23%, 6.82% and 6.48% was consolidated in PC2, PC3, PC4, PC5 and PC6 respectively. This population panel can be used for trait improvement in breeding programs for the traits contributing to major variation because the results of the principal component analysis used in the study have shown the high level of genetic variation and the traits contributing to the variation.
Language: English
Subfield: Genetics
Domain: Life Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W4404666367