Tissue-specific phenolic profiling of Castanopsis sieboldii: Validated quantification, metabolite annotation, and...

Castanopsis sieboldii is a phenolic-rich evergreen species in the family Fagaceae, yet comprehensive quantitative and tissue-specific metabolite profiling remains limited. In this study, an integrated analytical workflow comprising UHPLC-PDA quantification, LC-QToF-MS identification, and chemometric analysis was developed to characterize phenolic constituents in leaves, flowers, fruits, and stems. A validated UHPLC-PDA method enabled the simultaneous quantification of six major phenolics, with limits of detection ranging from 0.01 to 0.05 μg/mL and limits of quantification from 0.025 to 0.1 μg/mL. Among all tissues, 3‑O‑galloylshikimic acid (Compound 1) was the predominant metabolite (0.1-204 mg/g), followed by caffeoylquinic acids (Compounds 2-3), ellagic acid (Compound 4), and flavonoid glycosides (Compounds 5-6). LC-QToF-MS analysis facilitated the tentative annotation of 185 metabolites, including phenolic acids, ellagitannins, galloylshikimic acids, and flavonoid glycosides, based on accurate mass measurements and characteristic MS/MS fragmentation patterns. Chemometric evaluation using principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and hierarchical clustering analysis (HCA) revealed clear tissue-specific clustering, with leaves exhibiting the highest chemical diversity and phenolic abundance, whereas fruits showed minimal levels. PCA captured 80% of total variance in the first two components, and the PLS-DA model showed strong predictive performance (R²Y ≈ 1.00; Q² ≈ 0.98) although interpretation should consider the limited sample size. This study provides a comprehensive, tissue-resolved phenolic profile of C. sieboldii, establishing a robust chemical foundation for future pharmacological, ecological, and quality-control applications.