Application of hierarchical classification models and reliability estimation by bootstrapping, for authentication and discrimination of wine vinegars by UV–vis spectroscopy

Abstract

In recent years, three Spanish wine vinegars have obtained the indication of Protected Denomination of Origin (PDOs) due to their unique characteristics and traditional method of production: “Vinagre de Jerez”, “Vinagre de Condado de Huelva” and “Vinagre de Montilla-Moriles”. These vinegars are expensive due to their high quality, the long aging time and the high cost of production, reason why the adulteration and unfair competition in the vinegar industry are frequent practices. To avoid these frauds, several analytical techniques have been already studied for the characterization and authentication of these high quality vinegars. Nevertheless, ultraviolet–visible (UV–vis) spectroscopy, especially attractive for its simplicity and low cost, has not been previously used to assess PDO or other qualities as type of production or aging, in wine vinegars. For this reason, the potential of UV–vis spectroscopy was investigated for the first time as a rapid and inexpensive methodology for developing classification models to discriminate wine vinegars according to the production method, the PDO and the aging category. Spectra from 70 wine vinegars -including different categories within the 3 PDOs and also vinegars without PDO as known as rapid vinegars-have been analyzed and compared in the selected region of 280–600 nm. Principal components analysis (PCA) was used as exploratory method, while soft independent modelling-class (SIMCA) and partial least squares-discriminant analysis (PLS-DA) were employed for the development of a hierarchical classification model. Differences between categories and PDOs, as well as between PDO and Non-PDO wine vinegars, were observed according to the spectral regions around 300 nm and the visible regions around 500 nm. Furthermore, bootstrap resampling method was employed to generate distributions of classification results and to obtain confidence intervals in the classification. The hierarchical classification results open up the possibility of developing a tool that provides an easy and fast differentiation for the authentication of wine vinegars from different categories and denomination of origins.