Identification of Nonvolatile Migrates from Food Contact Materials Using Ion Mobility-High-Resolution Mass Spectrometry and in Silico Prediction Tools.

ABSTRACT: The identification of migrates from food contact materials (FCMs) is challenging due to the complex matrices and limited availability of commercial standards. The use of machine-learning-based prediction tools can help in the identification of such compounds. This study presents a workflow to identify nonvolatile migrates from FCMs based on liquid chromatography-ion mobility-high-resolution mass spectrometry together with in silico retention time (RT) and collision cross section (CCS) prediction tools. The applicability of this workflow was evaluated by screening the chemicals that migrated from polyamide (PA) spatulas. The number of candidate compounds was reduced by approximately 75% and 29% on applying RT and CCS prediction filters, respectively. A total of 95 compounds were identified

SUBMITTER: Song XC 

PROVIDER: S-EPMC9354260 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature