PhenolFingerprint DB: an open-access platform for phenolic fingerprinting, quantification, and automated species authentication, validated on 93 floral and herbal plants.

This study introduced PhenolFingerprint DB, a freely accessible online database designed for visualization, management, querying, and evaluation of fingerprint data. Its core functions include chromatographic profile visualization, species authentication through database searching, and automated quantification of 17 phenolic compounds. As a proof of concept, 93 edible flowers and herbs were analyzed. Using 409 built-in samples, we characterized phenolic-content distributions and fingerprint patterns for species discrimination and quality assessment. Quantitative phenolic analysis enabled only partial species differentiation but proved effective for content evaluation. In contrast, phenol-based fingerprints clearly distinguished nearly all species (92 of 93) through hierarchical clustering. The performance of PhenolFingerprint DB was further evaluated. Cross-validation demonstrated an overall accuracy of 99.8%. When applied to 38 unknowns, the database flagged two cases with mismatches, which were verified as quality issues. PhenolFingerprint DB also allows users to analyze their own data, presenting prospects for broad applications across different fields.