Assessment of Genetic Variability and Trait Associations for Quantitative Characters in Chilli (Capsicum annuum L.)

Abstract

Chilli (Capsicum annuum L.) is an herbaceous annual crop propagated by seeds, originating from Central and South America, including Mexico, Guatemala, and possibly Bulgaria. Genetic and environmental factors influence chilli variability, crucial for breeding programs. Heritability is essential for understanding trait expression and improving selection efficiency. Yield is a complex trait shaped by multiple contributing factors, and it requires a systematic breeding approach to effectively optimise selection indices. The study aimed to estimate genetic variability, heritability, and genetic advance for 15 quantitative traits. A field experiment was conducted during 2023-2024 at the School of Agricultural Sciences (SOAS), Malla Reddy University, Hyderabad, using 51 genotypes of chilli (Capsicum annuum L.) in a Randomised Complete Block Design with two replications. Data were recorded for several traits, including plant height (cm), Number of primary and secondary branches, Days to first flowering and 50% flowering, Stem girth (mm), Fruit girth (mm) and length (cm), Number of green fruits per plant, Average green fruit weight (g), Days to first harvest, Number of seeds per fruit, 1000-seed weight (g), Ascorbic acid content (mg/100g).  The analysis of variance and mean performance revealed significant differences among the genotypes for all yield-contributing traits. Both the genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) showed substantial variation across all traits, with PCV consistently higher than GCV. High GCV and PCV values were recorded for traits such as the number of secondary branches, ascorbic acid content, and fruit girth, whereas days to harvest exhibited low variability. Correlation analysis revealed that key traits influencing fruit yield include the number of green fruits per plant, fruit weight, branching, ascorbic acid, flowering time, and plant height. Path analysis indicated that the number of green fruits per plant and plant height are crucial traits for selection in yield improvement programs.  A low residual effect of 0.11 suggests that the traits analysed sufficiently accounted for yield variation. Enhancing these traits collectively can significantly boost overall yield. These findings suggest strong potential for improving these traits through an effective selection program.