Protein fingerprinting using gold nanoparticle-assisted SPE and HPLC-UV: A promising tool for chemometric authentication of monofloral honeys

Authentication of honey according to its botanical origin is essential for quality control. Traditional melissopalynological methods are time-consuming and subjective, motivating the search for faster alternatives. In this work, HPLC-UV protein fingerprinting approach was developed to classify honeys of different floral origins. Previously, proteins were isolated and preconcentrated using a gold nanoparticle-assisted solid-phase extraction. 61 Spanish honey samples from chestnut, heather, and thyme origins were studied where 27 different bee-derived proteins were identified. Distinct protein fingerprint patterns were observed where heather showed the most diverse SPE protein fingerprint, chestnut honey a more balanced distribution and thyme honey displayed higher levels of stress-related proteins. A linear discriminant analysis model was developed using sum-normalized protein abundances. The model was trained with 40 samples and externally validated with 21 independent samples, achieving 100% correct classification. The results demonstrate that bee-origin proteins reflect floral influences and can serve as stable biomarkers for honey authentication. • Gold nanoparticle-assisted SPE enabled efficient isolation of honey proteins. • HPLC-UV protein fingerprints discriminated chestnut, heather, and thyme honeys. • Chemometric modeling enabled 100% correct classification of the three studied monofloral honey types.