Classification and Authentication of Honey by Chromatographic Profiles and Chemometric Methods

Abstract

Nowadays, food industry is suffering a hard competitiveness that has led to a fraud increase in order to achieve greater economical profits. These irregular actions have raised the interest in the quality and authentication of commercialized food products, not only from the consumers and producers, but also from the scientific research. Honey can be found among the most vulnerable products to be adulterated and it is mostly affected by two fraud types: the mixing of monofloral honeys with multifloral honeys, which are considered of less quality, and the addition of cheaper sweeteners as syrups or industrial sugars. Even though these honeys are adulterated, they are labelled without all the information and they are sold as products of higher quality. This project aims to stablish a simple method to characterize honeys from different botanical and geographical origins and to classify them considering the results. A non-targeted method and a simple sample pre-treatment has been chosen to obtain chromatographic fingerprints, using high-performance liquid chromatography with an ultraviolet detector (HPLC-UV). The chromatographic profiles are evaluated as chemical descriptors by using different chemometric methods such as principal component analysis (PCA), partial least-squares discriminant analysis (PLS-DA) and, in some cases, hierarchical cluster analysis (HCA). The PCA results prove that the proposed method is robust and reproducible, and that separation of honey samples in different groups is possible. PLS-DA has shown a classification between different botanical origins of samples and this clustering has been supported by HCA, firstly between honeydew honeys and blossom honeys, and then between some floral varieties. On the other side, a good classification according to the region of production has not been accomplished, and it will be studied in further research