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Characterisation of iron oxide-containing pearlescent pigments used as food colourants: nano-labelling required in the EU?

Birgit HetzerVolker GräfElke WalzRalf Greiner
Published in: Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment (2022)
Pearlescent pigments are used as colourants to increase the attractiveness of food products, especially in the patisserie and confectionery sector. They can be seen as composite materials and consist of thin potassium aluminium silicate (E 555, mica) platelets as carrier material, coated with a thin metal oxide layer of TiO 2 (E 171) and/or iron oxides (E 172). The European Food Safety Authority stated in 2020 that mica-based pearlescent pigments as a whole should be evaluated as new food additives. Obtaining dependable data for particle size and layer thickness of these pigments is crucial both for the demanded food additive evaluation itself and also for the nanomaterial labelling assessment of products containing these food colourants according to the 'Food Information to Consumers' regulation. Since it was found in a previous study on TiO 2 -containing pearlescent pigments (silver and golden coloured) that the coating consisted of nanoscaled constituent titanium oxide particles, in this follow-up study we investigated whether Fe 2 O 3 -containing pearlescent pigments exhibit a similar nanostructured morphology. For this purpose, five commercially-available food products containing these pigments were investigated. Static light scattering and flow particle image analysis were used as screening methods to determine the mica platelet size. Scanning electron microscopy combined with energy-dispersive X-ray spectroscopy was used for nanostructure analysis of the metal oxide coating. The carrier mica platelets were 34-96 µm in diameter and 300-800 nm thick. The coating thickness was found to be in the range of 75-105 nm, with the constituent round shaped iron oxide particles contained therein having a minimum Feret diameter of 37-64 nm.
Keyphrases
  • human health
  • electron microscopy
  • iron oxide
  • healthcare
  • mass spectrometry
  • machine learning
  • quantum dots
  • electronic health record
  • deep learning
  • silver nanoparticles