Prediction of sensory score of Italian traditional balsamic vinegars of Reggio-Emilia by mid-infrared spectroscopy

In this study the potential of Fourier Transform Mid-Infrared (FT-MIR) spectroscopy to predict the sensory score of traditional balsamic vinegar (TBV) of Reggio-Emilia was investigated. The composition of two hundred commercial TBV samples was analysed and the sensory scores, ranging from 133 to 306 points, were evaluated by a certified panel of master experts (reference method). Partial least squares (PLS) regression, obtained from selected pre-processing signal techniques, was used for multivariate calibration to relate the sensory score to the MIR spectra. Performance of different models was compared in terms of coefficient of correlation (r) and root mean square error of cross-validation (RMSECV). The overall best prediction results were obtained using second order derivative with autoscaling and mean-centering of spectral data with the correlation coefficient of 0.889 and 0.885, respectively. It was concluded that the MIR spectroscopy is suitable for rapid instrumental screening of TBV sensory quality.