Bee-yond Borders: building a comprehensive honey databank with chemometric insights

Honey is a widely consumed natural sweetener, valued for its economic, nutritional and health benefits. The beneficial properties, however, vary significantly among different types of honey, making the assessment of its origin and authenticity crucial [ 1 ]. To address this, various analytical techniques have been developed to link honey’s composition to its origin, revealing its unique traits. While several large-scale studies have focused on the sugar composition and volatile compounds [ 2 ], research on non-sugar metabolites remains relatively limited. The primary aim of this ongoing study is to analyze honeys from multiple countries, evaluate their composition, and establish a comprehensive global honey databank. So far, the workflow involves the extraction of over 300 samples using annular centrifugal extraction (ACE) followed by NMR metabolomics and multivariate analysis (MVA). A key advantage of NMR lies in its high reproducibility and its ability to analyze samples at different time points without being affected by batch effects [ 3 ] – an essential feature when sample collection can be time-consuming. Therefore, alongside the creation of a physical honey bank, a spectral data base is also being created based on NMR data. Additionally, in combination with MVA, a chemical mapping of honey is being generated. Statistical models reveal clusters of honeys with similar chemical profiles, demonstrating high robustness. Interestingly, even honeys harvested from distant countries share similarities in their chemical composition. This project aims to include as many samples as possible from around the world, uncovering new honeys with unique compositions. Publication History Article published online: 05 March 2026 © 2026. Thieme. All rights reserved. Georg Thieme Verlag KG Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany