This study evaluated the usefulness of front-face fluorescence spectroscopy for predicting some selected chemical parameters in soft cheeses in external (E) and central (C) zones. Fat, dry matter (DM), pH, total nitrogen (TN) and water-soluble nitrogen (WSN) contents were determined by reference methods. Tryptophan (excitation: 290 nm; emission: 305-450 nm), riboflavin (excitation: 380 nm; emission: 400-640 nm) and vitamin A fluorescence spectra (emission: 410 nm; excitation: 270-350 nm) were recorded on the investigated cheeses. Three separate prediction models were developed from the tryptophan, riboflavin and vitamin A spectra using partial least squares (PLS) regression and the leave-one-out cross-validation technique. The results showed that fat, DM, fat in dry matter and WSN were the best predicted with the vitamin A fluorescence spectra models providing the highest values of the determination coefficient (R 2 ) of 0.88, 0.86, 0.86 and 0.84, respectively. The prediction of the pH was also successful using riboflavin fluorescence spectra (R 2 = 0.85). The WSN/TN ratio can also be predicted from the three intrinsic probes, but with much lower precision. soft cheese / tryptophan / riboflavin / vitamin A / partial least squares regression - pH ( ex: 290 nm, em: 305 ~ 450 nm), (ex: 380 nm, em: 400 ~ 640 nm), A (ex: 270 ~ 350 nm, em: 410 nm) 3 A (PLS) 3 A (R 2 ) 0.88 0.860.86 0.84 pH ( ) (R 2 = 0.85) 3 (WSN/ TN),
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Karoui et al. (2006) studied this question.
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