MULTIVARIATE ANALYSIS OF YIELD-CONTRIBUTING TRAITS IN SOYBEAN (GLYCINE MAX (L.) MERRILL.): INSIGHTS FROM CORRELATION AND PRINCIPAL COMPONENT APPROACHES

Abstract

The present study aimed to assess the interrelationship among eight key agronomic traits in 247 diverse soybean genotypes to identify yield-contributing factors for effective selection. Field evaluation data were analysed using correlation and Principal Component Analysis (PCA). Correlation results showed that seed yield per plant had strong positive correlations with number of pods per plant (0.719**), seeds per pod (0.643**), and seed yield efficiency (0.787**). Conversely, it showed significant negative correlations with plant height (-0.761**), primary branches (-0.682**), and number of nodes (-0.611**). Days to maturity was negatively correlated with seed yield (-0.619*) and plant height (-0.428*), but positively associated with primary branches (0.67*). PCA revealed that PC1 and PC2 accounted for 58.95% and 13.32% of total variance, respectively. PC1 showed positive loadings for seed yield (0.393) and yield efficiency (0.3409), and negative for pods per plant (-0.4257). Findings suggest compact, early-maturing genotypes with higher pod and seed counts are ideal for yield improvement.