Novel 2D-NMR Approach for the Classification of Balsamic Vinegars of Modena.

The aim of this work is to evaluate the possibility of using 2D-NMR for the construction of classification models for balsamic vinegars of Modena. The goal was to obtain an indirect indicator of authenticity and a quality control tool. The spectral data were analyzed by chemometric methods, aiming to discriminate the samples in relation to their origin. Application of general discriminant analysis (GDA) revealed a good discrimination; the two obtained models explained 83.9% and 97.3% of the total variance with a predictive capacity of 98.6% and 98.4%, respectively. The signals of 5-HMF, β-glucose, 2,3-butanediol, 6-acetyl glucose, and different aliphatic signals of sugars were the most significant variables. These results are very promising for giving an important contribution in quality control and characterization of such very valuable foods.