The present study was conducted to assess the physico-biochemical variability in
seventeen genotypes, including the check variety SolanLalima, using a Randomized Complete
Block Design with three replications. The aim was to estimate variability, heritability, genetic
advance, correlation, and path coefficient analysis for yield and other horticultural traits. The
estimates of phenotypic and genotypic coefficients of variation (PCV and GCV) were high for
titratable acidity (31.96% and 31.08%). High heritability and genetic gain were observed for
titratable acidity (94.53% and 62.24%) and 100 seed weight (93.71% and 51.06%). Correlation
studies at genotypic and phenotypic levels revealed significant positive correlations between fruit
yield per plot and traits such as the number of clusters per plant, number of fruits per cluster,
average fruit weight, fruit width, fruit length, pericarp thickness, number of seeds per fruit, 100
seed weight, harvest duration, plant height, total soluble solids, and ascorbic acid. Path
coefficient analysis indicated that the number of clusters per plant (1.028) had the maximum
positive direct effect on fruit yield per plot, followed by 100 seed weight (0.719), number of
fruits per plant (0.741), average fruit weight (0.468), total soluble solids (0.416), fruit width
(0.275), pericarp thickness (0.252), days to 50% flowering (0.227), number of locules per fruit
(0.083), and harvest duration (0.013). Principal Component Analysis showed that the first four
principal components captured most of the dataset variance, emphasizing traits like average fruit
weight, fruit dimensions, plant height, and days to first flowering. This dimensionality reduction
simplifies data analysis and highlights critical patterns, providing valuable insights for future
crop improvement.