RESUMEN
This paper proposes to use chromatographic fingerprints coupled to multivariate techniques to authenticate the geographical origin of extra-virgin olive oils (EVOO) of the Arbequina botanical variety. This methodology uses the whole or part of the chromatogram as input data for the classification models but does not identify or quantify the chemicals constituents. Arbequina monovarietal EVOOs from three geographical origins were studied: two from adjacent European Protected Designation of Origin areas, Siurana and Les Garrigues, in Catalonia in the northeast of Spain; and the third from the south of Spain (Andalucia and Murcia). Three chromatographic fingerprints of each sample were obtained by both reverse and normal phase liquid chromatography coupled to charged aerosol detector (HPLC-CAD), and high temperature gas chromatography coupled to flame ionization detector [(HT)GC-FID]. Principal component analysis (PCA) was used as exploratory technique and soft independent modelling of class analogy (SIMCA) and partial least square-discriminant analysis (PLS-DA) were used as classification methods. High and low-level data fusion strategies were also applied to improve the classification results obtained when the data acquired from each analytical technique were separately used. The results were best for the PLS-DA model with low-level fusion of two techniques (HT)GC-FID with HPLC-CAD, independently of the phase mode. Sensitivity and specificity were 100% in almost all classes, error was 0% for all classes and an inconclusive ratio of just 4% was obtained for the Les Garrigues class due to double assignations.