Abstract: A novel method for the identification of the floral origins of honeys was established by high performance liquid chromatography with electrochemical detection (HPLC-ECD). The HPLC-ECD fingerprints of three monofloral honeys collected from different areas of China were established. From the HPLC-ECD fingerprints, the areas of the common peaks were obtained and principal component analysis (PCA) and hierarchical cluster analysis (HCA) were performed to classify 45 honey samples (15 medlar honey samples, 15 vitex honey samples, and 15 litchi honey samples) according to their floral origins. These samples were successfully classified by PCA and HCA with 100% correct classification rates. To evaluate the reliability of the model based on 45 honey samples, some medlar honey, vitex honey and litchi honey samples which were not included in the modeling sample set were validated with correct prediction rates of 100%, 80% and 100%, respectively. The results indicated that HPLC-ECD combined with PCA and HCA may be used as a fast, accurate and environmentally safe method to differentiate honeys according to their floral origins.

Key words: honey, high performance liquid chromatography-electrochemical detection (HPLC-ECD), fingerprint, principal component analysis, hierarchical cluster analysis