A combined targeted/untargeted screening based on GC/MS to detect low-molecular-weight compounds in different milk samples of different species and as affected by processing

Gabriele Rocchetti, Luigi Lucini, Sudarshana Reddy Bhumireddy, Pavankumar Pallerla, Prabhakar Sripadi

Risultato della ricerca: Contributo in rivistaArticolo in rivistapeer review

Abstract

Low-molecular-weight compounds in milk are of interest from both nutritional and technological perspectives. To analyse potential milk metabolites, acetonitrile extraction followed by ethyl chloroformate derivatisation was developed. A GC/MS (SIM) method was then applied to different animal milk samples (i.e., buffalo, bovine, and donkey) and processed milk samples (i.e., pasteurised and dried). The optimised extraction-derivatisation method is rapid and more comprehensive when compared with the other published methods. The supervised orthogonal projection to latent structure discriminant analysis (OPLS-DA) based on the amino acid profile showed clear discrimination as a function of animal origin and milk processing. In this regard, variable importance in projection (VIP) analysis following an OPLS-DA prediction model showed that aspartic acid and asparagine (VIP scores = 1.26 and 1.19, respectively) were the best markers of the milk origin, whilst proline and glycine (VIP scores = 1.30 and 1.28, respectively) mainly discriminated samples according to different processing conditions.
Lingua originaleEnglish
pagine (da-a)105045-105045
Numero di pagine1
RivistaInternational Dairy Journal
Volume118
DOI
Stato di pubblicazionePubblicato - 2021

Keywords

  • metabolomics
  • milk quality

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