Identification of fermented soy sauce and blended soy sauce based on dielectric spectra

A new method based on dielectric properties has been developed to distinguish blended soy sauce from fermented soy sauce. Fifty samples of pure fermented soy sauce and blended soy sauce with different contents of hydrolyzed vegetable protein (HVP) were prepared. The dielectric constant and dielectric loss factor of all soy sauce samples in the 30 MHz–3000 MHz frequency range were measured using an impedance analyzer. The sample set was divided into a correction set and a prediction set using the joint x-y distances (SPXY) algorithm, and the partial least squares (PLS) and support vector machine (SVM) models were adopted to distinguish the different samples. The effects of selecting characteristic variables on model prediction using the full spectra (FS), principal component analysis (PCA), and successive projection algorithm (SPA) were compared. Results indicate that the discriminant effect of the PLS model was better than that of the SVM model overall. The SPA–PLS model had the best predictive performance among the six developmental models. The correlation coefficients of the correction set and prediction set were 0.9205 and 0.9096, respectively. The root mean square error of the calibration set was 1.3699 and that of the prediction set was 1.5950. The study demonstrated that the combination of dielectric spectra and stoichiometry can be utilized to determine whether soy sauce has been adulterated.