Harnessing Genetic Variability, Correlation and Path Analysis among Garden Pea (Pisum sativum L.) Genotypes for Food Security and Sustainability

Background: A field experiment was conducted at Lovely Professional University, Punjab (2022-23) to evaluate fourteen garden pea (Pisum sativum L.) genotypes for genetic variability, trait associations and direct and indirect effects of yield-related traits through path coefficient analysis. Understanding genetic variation and interrelationships among yield-contributing characters is essential for improving selection efficiency and enhancing productivity in garden pea breeding programs. Methods: Genotypes were evaluated in a randomized complete block design (RCBD) with three replications. Observations were recorded on morphological and yield-related parameters including plant height, number of nodes to first flower, number of primary branches/plants, pod length, number of pods/plants, 100-seed weight and pod yield/plant. Data were statistically analysed for analysis of variance (ANOVA), phenotypic coefficient of variation (PCV), genotypic coefficient of variation (GCV), heritability, genotypic and phenotypic correlations and path coefficient analysis to determine direct and indirect effects of various traits on pod yield. Result: Analysis of variance revealed significant genetic variability among genotypes for all studied traits. PCV values exceeded GCV for most traits, indicating environmental influence, except for nodes/plant. High GCV, PCV and heritability were observed for traits like number of primary branches/plants, pod yield/plant, 100-seed weight and numbers of pods/plant. Pod yield showed strong positive correlations with number of pods, 100-seed weight and node to first pod appearance. Path analysis indicated that number of primary branches, pod length, plant height and nodes to first flower appearance had the strongest direct effects on yield, suggesting these as key selection criteria in breeding programs.