Selection of potential molecular markers for cheese ripening and quality prediction by NMR spectroscopy

Predicting cheese quality as early possible after ripening is important for control in the industry. The main aim of this study was to investigate potential metabolites predictive models Cheddar quality. Metabolites aqueous extracts were identified by Nuclear Magnetic Resonance. used measure kinetics up 450 days cheese. proton ratios citrulline and arginine relative overall content extract are most indices assessing decrease 59% 69%, respectively, ripening. In comparison premium batch B cheese, C which predicted attain a lower level, had higher serine β-galactose well lactic acid levels also less mature sensorial profile. Tyrosine, tyramine lysine highly correlated with sensory attributes. β-Galactose glycerol young These can be predict