Discrimination of Milk from Different Animal Species by a Foodomics Approach Based on High-Resolution Mass Spectrometry.
Wei JiaXuyang DongLin ShiXiaogang ChuPublished in: Journal of agricultural and food chemistry (2020)
An untargeted foodomics strategy based on ultra-high-performance liquid chromatography coupled with quadrupole orbitrap and chemometrics was used to observe subtle differences in the molecule profiles of raw milk from different animal species (cow milk, goat milk, and water buffalo milk), which could prevent the fraud activities in the dairy industry. In data-dependent acquisition (DIA), spectra for all precursor ions facilitated the comprehensive identification of unknown compounds in untargeted foodomics. Chemometrics techniques were used to analyze large amounts of complex data to observe the separation of different sample groups and find the potential markers of sample groups. Finally, five markers were putatively identified by the potential marker identification workflow. The quantification results showed that β-carotene was found only in cow milk; ergocalciferol was found only in water buffalo milk; and the contents of nonanoic acid, decanoic acid, and octanoic acid were higher in goat milk than those in cow milk and water buffalo milk. The quantification of β-carotene enabled the detection of cow milk with a sensitivity threshold of 5% (w/w). This work provided an efficient approach for the discrimination of cow milk, goat milk, and water buffalo milk. Compared with proteomics and genomics, the simpler analytical procedures, lower costs, and higher speed of this work make it of great benefit for routine operations.
Keyphrases
- high resolution mass spectrometry
- liquid chromatography
- mass spectrometry
- ultra high performance liquid chromatography
- tandem mass spectrometry
- electronic health record
- machine learning
- high resolution
- simultaneous determination
- high performance liquid chromatography
- big data
- single cell
- clinical practice
- molecular dynamics
- data analysis