International Journal of Plant & Soil Science

This study aimed to characterise agro-morphological variability and assess the phenotypic structure of a BC1 coconut population (Cocos nucifera L.) as a basis for future quantitative trait loci (QTL) mapping analyses. A total of 186 BC1 progenies were evaluated using ten stem and leaf traits measured during the first nine months after planting. Principal component analysis (PCA), hierarchical cluster analysis (HCA), and discriminant factor analysis (DFA) revealed substantial phenotypic variability within the population. The first two PCA axes accounted for 81.5 % of the total variance, with the first axis being primarily associated with a vegetative growth gradient. Hierarchical cluster analysis distinguished three phenotypic groups that showed highly significant differences in all ten traits investigated (p < 0.001), indicating distinct phenotypic profiles within the BC1 population. Discriminant factor analysis confirmed this phenotypic structure, with 97.85 % of individuals correctly reclassified, demonstrating a high level of agreement between the clustering and discriminant approaches. The observed phenotypic differentiation provides valuable information for characterising the genetic material and identifying individuals or groups with contrasting vegetative growth traits. These findings provide a relevant phenotypic basis for integrating morphological and molecular data in subsequent genetic analyses and identifying genomic regions associated with vegetative growth traits in coconut. The results may contribute to the development of more effective strategies for genetic improvement and QTL mapping in coconut breeding programmes.