European food research and technology vol:226 issue:4 pages:861-870
Ten traditional M1 (n = 5) and M2 (n = 5) soft cheeses produced from raw milk, and five other stabilised M3 (n = 5) cheeses manufactured from pasteurised milk, were studied using mid infrared (MIR) and front face fluorescence (FFFS) spectroscopies. MIR (3000-900 cm(-1)), tryptophan (excitation: 290 nm, emission: 305-450 nm), 400-640 emission spectra (excitation: 380 nm) and vitamin A (excitation: 280-350 nm, emission: 410 nm) spectra were recorded at two sampling zones (external (E) and central (C)) of the investigated cheeses. When the factorial discriminant analysis (FDA) was applied to the MIR spectra, the classification was not satisfactory. With tryptophan fluorescence spectra, correct classification of 94.4 and 69.4% was observed for the calibration and validation spectra, respectively. Better classification was obtained using vitamin A fluorescence spectra, since 91.8 and 80.6% of the calibration and validation spectra, respectively, were correctly classified. When the first five principal components (PCs) of the PCA extracted from each data set were pooled into a single matrix and analysed by FDA, the classification was considerably improved, obtaining a percentage of correct classification of 100 and 91.7% for the calibration and validation samples, respectively. It was concluded that concatenation of the physico-chemical and spectroscopic data sets is an efficient technique for the identification of soft cheese varieties.