Milk is a foodstuff widely consumed around the world originating from a variety of different species, animal management and production systems. In recent years, consumers have placed a much greater emphasis on the authenticity and origin of some food products often willing to pay a premium price for such products that is, for example ‘Grass-Fed Dairy’. Therefore, it is important to establish methods to assess both quality and authentication of milk and dairy products for increased food security and consumer protection. Accordingly, NMR-based, GC–MS-based, and LC–MS-based metabolomics have been established as useful tools in the analysis of dairy products, such as raw and processed milk. This short-review provides an updated and critical overview on the most useful metabolomics-based platforms and the most useful multivariate statistical tools available for metabolomic data interpretation.
Rocchetti, G., O'Callaghan, T. F., Application of metabolomics to assess milk quality and traceability, <<CURRENT OPINION IN FOOD SCIENCE>>, 2021; 40 (N/A): 168-178. [doi:10.1016/j.cofs.2021.04.005] [https://hdl.handle.net/10807/258063]
Application of metabolomics to assess milk quality and traceability
Rocchetti, Gabriele;
2021
Abstract
Milk is a foodstuff widely consumed around the world originating from a variety of different species, animal management and production systems. In recent years, consumers have placed a much greater emphasis on the authenticity and origin of some food products often willing to pay a premium price for such products that is, for example ‘Grass-Fed Dairy’. Therefore, it is important to establish methods to assess both quality and authentication of milk and dairy products for increased food security and consumer protection. Accordingly, NMR-based, GC–MS-based, and LC–MS-based metabolomics have been established as useful tools in the analysis of dairy products, such as raw and processed milk. This short-review provides an updated and critical overview on the most useful metabolomics-based platforms and the most useful multivariate statistical tools available for metabolomic data interpretation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.