Abstract

The feeding system represents one of the main factors driving raw milk composition, thus determining differences in nutritional value and technological properties. In this preliminary study, untargeted metabolomics with ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) coupled with both unsupervised and supervised multivariate statistics was used to investigate the chemical profile of bulk milk collected from dairy cows (n = 103) following different feeding regimens, being corn silage (MS-FS, n = 51), hay (H-FS, n = 35) and a mixed ration consisted in fresh forage and hay (MR-FS, n = 17). Overall, a total of 1686 metabolites was identified by means of UHPLC-QTOF, with significant differences (p < 0.05) between the three feeding regimens under investigation. The metabolites detected mainly belonged to lipids (mainly glycerophospholipids and triglycerides), followed by oligopeptides, steroid derivatives, and secondary metabolites (such as phenolic compounds and terpenoids). Interestingly, multivariate statistics applied to the metabolomics data revealed intriguing differences in the discriminant markers detected. The markers identified included both feed-derived (such as phenolic metabolites) but also animal-derived compounds (such as fatty acids). Therefore, our results provide comprehensive insights into the metabolomics profile of different bulk milk samples, suggesting also an indirect influence of feeding regimens on its chemical signature.
Lingua originaleEnglish
pagine (da-a)N/A-N/A
RivistaFood Research International
Volume134
DOI
Stato di pubblicazionePubblicato - 2020

Keywords

  • Fatty acids
  • Foodomics
  • Milk traceability
  • Secondary metabolites
  • UHPLC-QTOF

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