NMR and LC-HRMS metabolomics with correlation-based dereplication strategies for honey authentication

Botanical and geographical mislabelling of honey remains analytically challenging because minor-metabolite composition varies with floral source, environment and processing, whereas biomarker assignments based on a single platform may remain ambiguous. Here, an annular centrifugal extraction (ACE) workflow was combined with nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) to profile 264 Greek honey samples. Unsupervised and supervised multivariate approaches were used for exploratory classification and marker selection. Statistical total correlation spectroscopy (STOCSY) and statistical heterospectroscopy (SHY) linked covarying NMR resonances and LC-HRMS features, while selected constituents were isolated for structural characterization. Six botanical classes were more consistently discriminated than geographical regions. Isolation and multidimensional NMR distinguished 4-quinolone-3-carboxylic acid from previously reported chestnut-honey quinoline isomers. Overall, this integrated workflow enabled honey-type discrimination and authenticity assessment, revealed candidate biomarkers, and highlighted the complementary value of NMR and HRMS for reliable biomarker discovery and unambiguous structural elucidation.