Geographical Authentication of Tequila According to its Mineral Content by Means of Support Vector Machines

The elemental profile of tequila samples from the three main production areas of the State of Jalisco, namely Amatitlan, Guadalajara, and Tequila, was used to carry out their geographical characterization. With this aim, the concentration of Al, Ba, Ca, Cu, Fe, K, Mg, Mn, Na, S, Sr, and Zn was determined by inductively coupled plasma atomic emission spectroscopy. Principal component analysis was addressed to visualize data trends. The number of input variables was reduced by means of backward stepwise linear discriminant analysis and support vector machines were used to construct an adequate classification model. The best classification performance was obtained by a linear support vector machine model with 100% of prediction ability.