A new FT-IR method combined with multivariate analysis for the classification of vinegars from different raw materials and production processes.

BACKGROUND

Due to the diversity of vinegars on the market and the increase in demand, it is considered necessary to investigate and establish criteria for classifying them in order to obtain more information concerning their real origin. New spectroscopic techniques such us mid-infrared spectroscopy with Fourier transform (FT-IR) are capable of providing information in relation to these aspects. FT-IR combined with multivariate analysis has been used to classify vinegars according to the raw materials and production processes (with or without ageing in wood). Principal component analysis (PCA), partial least-squares discriminant analysis regression (PLS-DA) and stepwise linear discriminant analysis (SLDA) were used.

RESULTS

The results obtained have been compared to those achieved using different analytical parameters (polyphenolic content, organic acids and volatile compounds). SLDA and PLS-DA results show the ability of mid-FT-IR spectra to discriminate among vinegars from different raw materials and with or without ageing in wood, with correct classification percentages similar to those obtained using different analytical parameters.

CONCLUSION

The discriminative ability combined with other advantages (e.g. rapid and non-destructive analysis, low cost) makes this new FT-IR method a promising tool for the classification and/or differentiation of vinegars.