A multi-model evaluation framework for breeding-oriented germplasm selection in Camellia oleifera

Camellia oleifera is an important woody industrial oil crop, and rapid identification of elite germplasm is essential for oil-yield improvement and cultivar breeding. In this study, 166 C. oleifera accessions were evaluated using a breeding-oriented framework integrating seed and oil traits, 1 H NMR-based fatty acid profiling, multivariate analysis, clustering, and comprehensive ranking models. Ten traits, including six seed related traits and four major fatty acid components, were analyzed. PCA extracted four principal components explaining 83.771% of the total variation. Using the elbow method and NbClust multi-index voting, K = 3 was identified as the optimal cluster number, and the accessions were classified into three trait-defined clusters. Cluster 2 showed the most favorable profile for oil yield related traits and fatty acid composition. Comprehensive ranking based on PCA scoring, entropy weighting, and entropy-weighted TOPSIS consistently identified YUE-39 as the top-performing accession, with significant agreement confirmed by Kendall’s coefficient of concordance. These findings provide a practical framework for high-throughput C. oleifera germplasm screening and breeding-oriented utilization of woody oil crop resources.