A promising P NMR-multivariate analysis approach for the identification of milk phosphorylated metabolites and for rapid authentication of milk samples.

A fast and reliable method for the identification of milk from different mammalians was developed by using P NMR metabolite profile of milk serum coupled to multivariate analysis (PCA and classification models UNEQ, SIMCA and K-NN). Ten milk samples from six different mammalians, relevant to human nutrition (human, cow, donkey, mare, goat, sheep), were analyzed and eight monophosphorylated components were identified and quantified: phosphocreatine (PCr), glycerophosphorylcholine (GPC), glycerophosphorylethanolamine (GPE), -acetylglucosamine-1-phosphate (NAcGlu-1P), lactose-1-phosphate (Lac-1P), galactose-1-phosphate (Gal-1P), phosphorylcholine (PC), glucose-6-phosphate (Glu-6P). PCA showed interesting clustering based on the animal genus. K-NN can be successfully used to discriminate between donkey and cow samples while UNEQ class-modeling resulted more suitable for compliance verification. Results confirm the natural variability of milk samples among different species. These data highlight the great potentials of NMR/multivariate analysis combined method in the rapid analysis of phosphorylated milk serum metabolites for milk origin assessment and milk adulteration detection.