Emerging Spectrophotonic Technologies to Predict the Maturation Time of Swiss-Type Cheese: Dielectric Spectroscopy vs. Portable NIR

The cheese maturation process involves complex physicochemical and structural changes that directly influence its final quality and consumer acceptance. The development of non-destructive and rapid analytical techniques is therefore essential for monitoring these changes and optimizing quality control strategies. This study evaluated the potential of dielectric spectroscopy and near-infrared (NIR) spectroscopy as tools to predict properties associated with the quality of Swiss-type cheese during the maturation process. The cheese samples were matured for 60 days, and NIR profiles (900–1700 nm), dielectric profiles (401–106 Hz) and physical characteristics (color and texture) were obtained every 15 days. Based on these data, models were developed to predict the maturation time (days) and physical properties using partial least squares regression (PLSR). The performance of the model was evaluated using the determination coefficient (R2) and the root mean square error (RMSE). The results showed that dielectric spectroscopy provided a better fit for all the parameters evaluated (Rday2=0.999, RL*2=0.912, Ra*2=0.983, Rb*2=0.982, and Rfirmness2=0.625), with prediction errors of RMSEday=0.219, RMSEL*=1.184, RMSEa*=0.163, RMSEb*=0.308, and RMSEfirmness=91.094. In conclusion, dielectric spectroscopy combined with PLSR showed slightly superior performance to predict maturation time and physical changes in Swiss-type cheese.