Comprehensive Study of Sunflower Traits through Principal Component Analysis and Character Association

Abstract

This research evaluated the genetic diversity and character association among 45 sunflower inbred lines. Principal component analysis (PCA) and hierarchical cluster analysis were used to estimate diversity among the inbred lines. The PCA revealed that the first three principal components (PC1, PC2, and PC3) accounted for 64.80% of the total variation, with eigen values of 3.62, 1.96, and 1.54, respectively. The biplot analysis identified RHA-1013, CMS-249B, NDSI-3, ARM-243B, CMS-104B, NDLR-32, and NDLR-1 as the most diverse lines. Inbred lines were grouped into five clusters using Wards method, with Cluster V having the highest number of lines (13), followed by Cluster II (11). Clusters V and IV exhibited the highest mean values for most of the traits studied. Correlation analysis demonstrated a strong positive relationship between seed yield (kg ha-1) and days to 50% flowering, plant height, head diameter, volumetric weight, 100 seed weight, oil yield, seed yield (g/plant) and final plant stand. Path analysis revealed that seed yield (g/plant) and oil yield (kg ha-1) exhibited high and positive direct effects on seed yield (kg ha-1). All the traits exhibited positive indirect effects on seed yield (kg ha-1) via seed yield (g/plant) and oil yield. Plant height, head diameter and seed yield (g/plant) were found as key traits with respect to diversity and also correlation with seed yield (kg ha-1). Therefore, simultaneous selection for these traits is suggested for improvement of seed yield (kg ha-1) in sunflower.