Rapid authentication and adulteration detection of Sherry wine vinegar using ATR-FTIR spectroscopy coupled with
Veranur Gungor-Bilgicer1, Hakan Taşkıran2, Murat Ozdemir1
1Department of Chemical Engineering, Gebze Technical University, 41400 Gebze, Kocaeli, Türkiye.
Abstract:
Chemometric methods and artificial neural network (ANN) modeling was used to classify aging categories and quantify adulteration of Sherry wine vinegars using ATR-FTIR spectroscopy as a non-destructive analytical technique for authenticity verification. A total of 48 vinegar samples, including fresh, Jerez, Reserva, Gran Reserva, and non-Sherry vinegars, were analyzed to obtain ATR-FTIR spectral fingerprints. Principal Component Analysis (PCA) differentiated between Sherry and non-Sherry vinegars and revealed compositional changes associated with aging categories. Quantitative models were developed using Partial Least Squares (PLS), Principal Component Regression, and ANN. The PLS model showed strong predictive performance (R2cal = 0.938, R2val = 0.937, RMSEP = 8.73), while the ANN model achieved the highest calibration accuracy (R2cal = 0.996) with high validation performance (R2val = 0.932, RMSEP = 9.97). These findings demonstrate that ATR-FTIR combined with chemometric and ANN modeling provides a rapid, reliable, and practical approach for industrial aging classification and adulteration detection in Sherry vinegar.
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