Innovative SALLE-GC-Orbitrap-HRMS-based metabolomics and multi-technique data fusion: A combined approach for botanical marker identification of monofloral and multifloral honey

The botanical origin of honey influences its physicochemical properties, sensory attributes, and commercial value. This study applied an untargeted metabolomics approach using gas chromatography coupled to high-resolution mass spectrometry (GC-Orbitrap-HRMS) to differentiate monofloral (eucalyptus, rosemary, and orange blossom) and multifloral honey. A salt-assisted liquid-liquid extraction (SALLE) was performed for metabolite profiling, followed by multivariate statistical analysis using principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA), achieving strong classification performance (R 2 Y > 0.8, Q 2 > 0.7). Seven different key metabolomic markers, including sesquiterpenes, naphthalenes, methyl xanthines, and cyclohexenones, were identified as botanical origin indicators. Additionally, a novel data fusion approach integrated GC-Orbitrap-HRMS with ultra-high performance liquid chromatography (UHPLC-Q-Orbitrap-HRMS) analysis, enhancing the classification accuracy and demonstrating the complementarity of both techniques. These findings highlight the potential of GC-Orbitrap-HRMS combined with chemometric tools as a powerful strategy for honey authentication, quality control, and fraud detection in the food industry. • Salt-assisted liquid-liquid extraction used for honey fingerprint obtention. • Eucalyptus, rosemary and orange blossom honey were distinguished by OPLS-DA. • Chemometrics allowed differentiating between monofloral and multifloral honey. • Seven novel metabolites were identified as reliable honey markers. • First study applying GC-HRMS and UHPLC-HRMS mid-level data fusion in honey.