Untargeted food chemical safety assessment: A proof-of-concept on two analytical platforms and contamination scenarios of tea

• Published in: Food control Vol. 98; pp. 510 - 519
• Main Authors: Delaporte, Grégoire, Cladière, Mathieu, Camel, Valérie
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-04-2019; Elsevier
• Subjects: Chemical and Process Engineering; Engineering Sciences; Food engineering; Food safety; Independent components analysis; LC-HRMS; Life Sciences; Orbitrap; ToF; XCMS; Independent components analysis; XCMS; Food safety; ToF; Orbitrap; LC-HRMS; lc-hfims; food safety; independent components analysis; tof; orbitrap
• ISSN: 0956-7135; 1873-7129
• DOI: 10.1016/j.foodcont.2018.12.004

This study aims at assessing the capability of comparing and combining different instrumental platforms in an untargeted approach with a view of detecting chemical contaminants in food matrices at low levels. A strategy based on liquid chromatography-high resolution mass spectrometry (LC-HRMS) and chemometrics has been applied on two different complex food contamination scenarios, with tea as study product. The first scenario aimed at mimic the presence of a dozen of contaminants at levels just above regulatory limits (i.e. 10 and 30 μg/kg); the second scenario, more complex, aimed at simulate the presence of several different contaminations at levels close to regulatory limits (10 μg/kg) in different samples. This work was carried on two LC-HRMS platforms (with respectively ToF and Orbitrap mass analyzer technologies), and a highly automated data treatment workflow was implemented to deal with data acquired on both platforms. The untargeted approach performed well on all scenarios (even the most complex) and analytical platforms. Performance comparison between LC-HRMS technologies was made possible thanks to a vendor-neutral data treatment process.
•Untargeted approach combining data acquired on two different LC-HRMS platforms.•Blind detection of non-conformities related to chemical food safety.•Overall detection rates of 64 and 100% depending on the contamination scenario.•Discrimination of sample groups that differ by only 3 contaminants at levels as low as to 10 μg/kg.•Application of the approach to both green and black tea samples.