Principal component analysis and agglomerative clustering of morphological variations in two different species of oil palm (Elaeis oleifera and Elaeis guineensis)

This study investigated morphological diversity in 40 oil palms comprising Elaeis oleifera (23 genotypes) and Elaeis guineensis (17 genotypes) using 14 morphological traits. Principal Component Analysis (PCA) revealed that structural vigour traits - palm height, girth, rachis length, and leaflet dimensions - dominated variation (PC1, 50.64%), while leaf production (PC2, 13.53%), growth-reproduction trade-offs (PC3, 9.75%), and leaflet number versus reproductive allocation (PC4, 7.45%) accounted for additional variability. Agglomerative Hierarchical Clustering (AHC) partitioned genotypes into three clusters: two dominated by E. oleifera, characterized by taller palms, broader canopies, and lower reproductive ratios, and one dominated by E. guineensis, marked by shorter palms and higher reproductive allocation. The analyses highlight inter- and intra-specific variation, revealing trade-offs between vegetative robustness and reproductive efficiency. These findings underscore the value of PCA and clustering in identifying genotypes with desirable trait combinations, supporting breeding strategies aimed at combining structural vigour with yield efficiency in oil palm improvement programs.