Honey is a natural product which possesses therapeutic, nutritional and industrial value. It can be a high value food commodity especially in the case of certain unifloral honeys used in apitherapy due to their healing and antibacterial properties. Honey can also be the subject of fraud, commonly by adulteration using sugars but also by mislabeling or false declaration of botanical origin. The study demonstrated the successful employment of an untargeted highdefinition metabolomic approach for the floral classification of honey. Initial investigations were undertaken with 5 commercial (shop bought) honeys of polyfloral origin to ascertain whether they could be differentiated by ion mobility coupled non targeted metabolomic analysis combined with multivariate statistics. Once positively confirmed that this was a successful approach the experiment was expanded to unifloral honeys of authentic verified origins. The honeys were collected over multiple years from 20092014 and from multiple countries including Lithuania, Poland, Denmark, New Zealand and Norway. UPLCHDMSE analysis of the samples was completed in triplicate in both positive and negative ESI in a randomised fashion and the resulting data were processed in Progenesis QI. Unsupervised PCA showed a clear differentiation between the unifloral honeys with Rape and Buckwheat showing the closest association. Further investigations were made with OPLSDA analysis to elucidate the analytical components responsible for the differences between the honeys. Unique markers of all of the honeys were identified. Validation of selected identified markers was undertaken using targeted metabolomics on a UPLC Tandem Quad MS. An evaluation of the markers of botanical origin discovered in the nontargeted metabolomic approach were compared to those found using a similar experimental workflow using rapid evaporative ionisation MS (REIMS).