Honey is a natural product, highly appreciated by society as a natural sweetener and for its important health benefits. It isproduced by bees from nectar and other non-floral secretions. The great diversity of botanical varieties and the various countries of production have given rise to products with disparities in quality and prices, while also increasing fraudulent practices. In this line, developing methods capable of characterizing honey and authenticating and certifying not only its botanical variety but also its geographical origin is essential in order to avoid distrust within society or economic losses in the beekeeping sector.

The potential to use HPLC-UV fingerprints to assess honey geographical production regions via chemometrics was evaluated. One hundred and fifty-seven honey samples produced in different countries (Spain, Italy, France, The Netherlands, Serbia, Japan, China, Costa Rica, and New Zeeland) were analyzed after simple sample treatment (1 g of honey dissolved in 10 mL of water and diluted in a ratio of 1:1 with methanol). Reversed-phase C18 HPLC-UV (at 280 nm) fingerprints showed that there were chemical descriptors with which to assess honey geographical production region via partial least squares-discriminant analysis (PLS-DA). Results obtained via PLS-DA classification based on a decision tree showed cross-validation calibration sensitivity and specificity values of 100% (except for Japanese samples, 76.5%) and > 81.3%, respectively; prediction sensitivity and specificity values of 100% (except for French samples, 75%) and >82.4%, respectively; and calibration and prediction errors below 18.0% and 12.5%, respectively. The obtained fingerprints were also evaluated for the detection and quantitation of honey adulterations via partial least squares (PLS) regression based on blended adulterated honey produced in two different countries (adulteration levels from 15 to 85%). Calibration and prediction errors below 15% were achieved. Thus, HPLC-UV fingerprinting is a simple, cost-effective, and reliable classification technique with which to authenticate honey and to prevent fraudulent practices involving blended honey from different production regions.