Authentication of honey origin and harvesting year based on Raman spectroscopy and chemometrics

•Raman spectroscopy efficiently employed for honey authentication.•Application of supervised statistical method (PLS-DA) for honey differentiation.•Improving model accuracies through data preprocessing and variable selection. The false declaration of honey authenticity requires the use of rapid and efficient analytical tools in order to be detected. In this study, the use of a green, rapid and emerging approach for food authentication, FT-Raman spectroscopy, proved to obtain reliable and efficient honey botanical and harvesting year differentiation models, when the spectroscopic data was processed by employing a supervised statistical method, namely Partial Least Squares Discriminant Analysis (PLS-DA). The peaks and bands present in the Raman spectra were discussed based on honey composition. In order to increase the efficiency of the models, different preprocessing methods were used and a variable reduction step was employed. The new authentication approach is capable of distinguishing among four botanical sources and two harvesting periods of honey with a correct prediction rate higher than 97 %. The Raman markers that proved to contribute the most to the discrimination were correlated with the honey composition. [Display omitted]