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Analytical tools for identification and quantification of migrants from food packaging
KTH, School of Chemical Science and Engineering (CHE), Fibre and Polymer Technology, Polymer Technology.
2011 (English)Conference paper (Other academic)
Abstract [en]

Polymers are frequently used as packaging material for food and therefore it is of concern that migrating substances such as additives or degradation products could contaminate the food. Sometimes also processing or microwave heating of food is performed directly inside the food package, which could lead to increased migration. Chromatographic and mass spectrometric analysis techniques can be used to detect, identify and quantify compounds that are released from polymers during such scenarios and, with suitable extraction and analysis techniques for example solid phase micro extraction coupled to gas chromatography – mass spectrometry (SPME-GC-MS), the migrating substances can be identified and quantified. We have previously detected the emission of low molecular weight substances from polymers using SPME-GC-MS [1,2]. With these analysis techniques we have shown that significant antioxidant degradation takes place during microwave heating of the polypropylene (PP) packages in the fatty food simulants, which further led to increased migration of potentially toxic degradation products into the food [3]. No antioxidant degradation was observed in aqueous food simulants or during conventional heating at the same temperature. Electrospray ionization-mass spectrometry (ESI-MS) was shown to be a valuable tool for studying the less volatile migrants. Antioxidant migration rates from three PP materials to fatty food simulants differed largely with respect to the PP type and increased with decreasing degree of crystallinity in the materials, as determined by high performance liquid chromatography (HPLC) [4]. The extraction efficiency of a headspace - solid phase microextraction (HS-SPME) method could be predicted from the analyte properties using a partial least squares (PLS) regression model [5].



[1] M Gröning, M Hakkarainen, Journal of Chromatography, (2001) 932, 1-11

[2] M Hakkarainen, Journal of Chromatography, (2003)  1010, 9-16

[3] J. Alin and M. Hakkarainen, Journal of Agricultural and Food Chemistry, (2011) DOI: 10.1021/jf1048639

[4] J. Alin and M. Hakkarainen, Journal of Applied Polymer Science, (2010) 118, 1084-1093

[5] J. Alin and M. Hakkarainen, manuscript

Place, publisher, year, edition, pages
National Category
Polymer Technologies
URN: urn:nbn:se:kth:diva-49604OAI: diva2:459866
Nordic Polymer Days, 2011. Stockholm. June 15-17, 2011
Formas, 2007-793
QC 20111130Available from: 2011-11-28 Created: 2011-11-28 Last updated: 2012-03-29Bibliographically approved

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