NMR-based approach to detect white wine vinegar fraud.

ABSTRACT

Low-Field Nuclear Magnetic Resonance (LF-NMR) can be a valid tool in food fingerprint analyses to detect commercial frauds. Thus, the work aims at exploring the potential of LF-NMR, coupled with chemometrics, in discriminating authentic white wine vinegars from products adulterated with alcohol vinegars (i.e., 5-25% v/v adulteration levels). The monodimensional spectra and transverse relaxation times (T2) of 88 samples, including 32 authentic vinegars and 56 adulterated samples, were collected. Three different spectral regions were investigated (i.e., 3.75-0.90, 3.75-2.00, and 1.50-0.90 ppm) and, for each, fifteen variables were selected from the pretreated monodimensional spectra. Linear Discriminant Analysis (LDA) on monodimensional spectra in the range 3.75-0.90 ppm gave 100% correct classification of authentic and adulterated vinegars in prediction, whereas LDA models developed with acetic acid or water T2 failed. In conclusion, LF-NMR spectra can be effectively used to detect, in a rapid and non-destructive way, white wine vinegar adulteration with alcohol vinegar.