Data fusion for food authentication. Combining rare earth elements and trace metals to discriminate 'Fava Santorinis' from other yellow split peas using chemometric tools

摘要

"Fava Santorinis", is a protected designation of origin (PDO) yellow split pea species growing only in the island of Santorini in Greece. Due to its nutritional quality and taste, it has gained a high monetary value. Thus, it is prone to adulteration with other yellow split peas. In order to discriminate "Fava Santorinis" from other yellow split peas, four classification methods utilising rare earth elements (REEs) measured through inductively coupled plasma-mass spectrometry (ICP-MS) are studied. The four classification processes are orthogonal projection analysis (OPA), Mahalanobis distance (MD), partial least squares discriminant analysis (PLS-DA) and k nearest neighbours (KNN). Since it is known that trace elements are often useful to determine geographical origin of food products, we further quantitated for trace elements using ICP-MS. Presented in this paper are results using the four classification processes based on the fusion of the REEs data with the trace element data. Overall, the OPA method was found to perform best with up to 100% accuracy using the fused data.