Multivariate and Association Analyses of Various Seed Yield Contributing Traits Divulge Genetic Diversity Among Pisum sativum L. Genotypes

Parveen, N.; Umer, S.; Tan, C.; Jabbar, A.; Kanwal, B.; Haider, I.; Raza, W.; Usma, A.; Mehmood, A.; Junaid, M.B.; Abbasi, S.H.; Alfagham, A.T.; Iqbal, R. 2025. Multivariate and Association Analyses of Various Seed Yield Contributing Traits Divulge Genetic Diversity Among Pisum sativum L. Genotypes. Plant Molecular Biology Reporter. ISSN 1572-9818. https://doi.org/10.1007/s11105-025-01533-1

Genetic variability plays a pivotal role in enhancing yield-related traits. A diverse genetic pool offers the potential for combining desirable allelic combinations to improve yield and related characteristics. This study analyzed data from 99 genotypes, focusing on various morphological traits. Correlation analysis revealed significant and positive associations among seed yield per plant, hundred fresh seed weight, and hundred dry seed weight. Principal component analysis (PCA) identified the first four principal components (PCs) with eigenvalues exceeding one, accounting for 64.186% of total variability in morphological traits. PC-1 exhibited positive factor loadings for all morphological traits except number of pods per plant, number of branches per plant, number of seeds per pod, and pod length with hundred fresh seed weight, being the highest contributor. Cluster analysis categorized genotypes into three distinct clusters with Cluster-II, displaying the highest hundred fresh seed weight. Using the Ward’s method, greater distance was observed between Cluster-I and Cluster-III, suggesting that crosses between genotypes from these clusters may yield hybrid vigor in breeding programs and contribute to the selection of desirable genotypes.