LAUSR

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