A promising 31P NMR-multivariate analysis approach for the identification of milk phosphorylated metabolites and for rapid authentication of milk samples

Abstract

A fast and reliable method for the identification of milk from different mammalians was developed by using 31P 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), N-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.