European Food Research and Technology vol:223 issue:3 pages:363-371
There is a strong tendency towards exploring rapid and low cost methods for determining chemical parameters and degree of the ripening of cheeses. The visible-near infrared (VIS-NIR), mid infrared (MIR) and combination of VIS-NIR and MIR spectroscopic methods for measurements of some selected parameters of soft cheeses were compared. Fifteen traditional and stabilised retail soft cheeses, differing in manufacturing process were studied. Fat, dry matter (DM), pH, total nitrogen (TN) and water soluble nitrogen (WSN) contents were determined by reference methods and scanned with VIS-NIR and MIR spectrophotometers in reflectance mode. Three separate prediction models were developed from the VIS-NIR, MIR and the joint VIS-NIR-MIR spectra using the partial least square (PLS) regression and leave one-out cross-validation technique. Results showed that fat, DM, TN and WSN were the best predicted with the VIS-NIR models providing the lowest values of the root mean square error of prediction (RMSEP) of 1.32, 0.70, 0.11 and 0.10, respectively. The combination of the VIS-NIR and MIR spectral improved slightly the prediction of only the pH. This suggests using the VIS-NIR for the determination of fat, DM, TN and WSN. The pH can also be predicted from the two techniques with approximate quantitative prediction, while a difference between low and high levels of WSN/TN ratio could be determined by the VIS-NIR, MIR or joint use of VIS-NIR-MIR.