An untargeted evaluation of food contact materials by flow injection analysis-mass spectrometry (FIA-MS) combined with independent components analysis (ICA)

Article in press, corrected proofFood contact materials (FCMs), especially plastics, are known to be a potential source of contaminants in food. In fact, various groups of additives are used to protect the integrity of the material during processing and life time. However, these intentionally added substances (IAS) could also lead to degradation products called non-intentionally added substances (NIAS), due to reactions occurring in the polymeric material. Complex mixtures of components may therefore be generated within the material, creating a source of potential migrating substances towards food in contact. In this context, an innovative analytical approach is proposed in order to assess IAS and NIAS in plastic FCMs for a fast screening of their composition. For this purpose, solvent extracts of polyethylene (PE) pellets, containers and films were analyzed by flow injection analysis-mass spectrometry (FIA-MS). This direct approach offers the ability to perform a large number of analyses in a short time. Mass spectral fingerprints were then treated by a multivariate data analysis technique called independent components analysis (ICA) in order to overcome the complexity of such data and to highlight hidden information related to IAS and NIAS molecules. ICA applied on mass spectral fingerprints of PE extracts highlighted group discriminations related to different m/z values which were putatively assigned to IAS and also to NIAS. In order to confirm these putative annotations, a hybrid LTQ-Orbitrap was used for high resolution mass spectrometry analysis. Moreover, MS/MS experiments were performed on some discriminant ions to improve their putative identification. The proposed methodology combining FIA-MS fingerprints and ICA proved its efficiency in identifying IAS and NIAS in plastic FCMs and its capability to discriminate different PE samples, in a relatively fast approach compared to classical analytical techniques. This approach may help the FCMs classification for compounders in the selection of the starting substances in plastic formulation and for plastic converters in the control of manufacturing processes as well as for the monitoring of final products