Targeted lipidomics coupled with machine learning for authenticating the provenance of chicken eggs

Sung-Tong Chin; Gerhard Hoerlendsberger; Kok Wai Wong; Sirui Li; Sze How Bong; Luke Whiley; Julien Wist; Reika Masuda; Johan Greeff; Elaine Holmes; Jeremy K Nicholson; Ruey Leng Loo

doi:10.1016/j.foodchem.2022.135366

Targeted lipidomics coupled with machine learning for authenticating the provenance of chicken eggs

Food Chem. 2023 Jun 1:410:135366. doi: 10.1016/j.foodchem.2022.135366. Epub 2022 Dec 30.

Authors

Affiliations

¹ Australian National Phenome Centre, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia.
² Discipline of Information Technology, Murdoch University, 90 South Street, Perth, WA 6150, Australia.
³ Australian National Phenome Centre, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia; Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia.
⁴ Department of Primary Industries and Regional Development, 3 Baron-Hay Court, South Perth, WA 6151, Australia.
⁵ Australian National Phenome Centre, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia; Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia; Nutrition Research, Department of Metabolism, Nutrition and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, London SW7 2AZ, U.K.
⁶ Australian National Phenome Centre, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia; Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia. Electronic address: rueyleng.loo@murdoch.edu.au.

PMID: 36641906
DOI: 10.1016/j.foodchem.2022.135366

Abstract

Free-range eggs are ethically desirable but as with all high-value commercial products, the establishment of provenance can be problematic. Here, we compared a simple one-step isopropanol method to a two-step methyl-tert-butyl ether method for extracting lipid species in chicken egg yolks before liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. The isopropanol method extracted 937 lipid species from 20 major lipid subclasses with high reproducibility (CV < 30 %). Machine learning techniques could differentiate conventional cage, barn, and free-range eggs using an external test dataset with an accuracy of 0.94, 0.82, and 0.82, respectively. Lipid species that differentiated cage eggs were predominantly phosphocholines and phosphoethanolamines whilst the free-range egg lipidomes were dominated by acylglycerides with up to three fatty acids. The lipid profiles were found to be characteristic of the cage, barns, and free-range eggs. The lipidomic analysis together with the statistical modeling approach thus provides an efficient tool for verifying the provenance of conventional chicken eggs.

Keywords: Authenticity; Chemometrics; Eggs; Lipidomics; Machine learning; Ultra performance liquid chromatography-mass spectrometry.

MeSH terms

2-Propanol
Animals
Chickens*
Chromatography, High Pressure Liquid / methods
Chromatography, Liquid / methods
Eggs / analysis
Lipidomics*
Lipids
Reproducibility of Results
Tandem Mass Spectrometry / methods

Substances

2-Propanol
Lipids