Detection of Anthropogenic Particles in Fish Stomachs: An Isolation Method Adapted to Identification by Raman Spectroscopy
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Microplastic particles (MP) contaminate oceans and affect marine organisms in several ways. Ingestion combined with food intake is generally reported. However, data interpretation often is circumvented by the difficulty to separate MP from bulk samples. Visual examination often is used as one or the only step to sort these particles. However, color, size, and shape are insufficient and often unreliable criteria. We present an extraction method based on hypochlorite digestion and isolation of MP from the membrane by sonication. The protocol is especially well adapted to a subsequent analysis by Raman spectroscopy. The method avoids fluorescence problems, allowing better identification of anthropogenic particles (AP) from stomach contents of fish by Raman spectroscopy. It was developed with commercial samples of microplastics and cotton along with stomach contents from three different Clupeiformes fishes: Clupea harengus, Sardina pilchardus, and Engraulis encrasicolus. The optimized digestion and isolation protocol showed no visible impact on microplastics and cotton particles while the Raman spectroscopic spectrum allowed the precise identification of microplastics and textile fibers. Thirty-five particles were isolated from nine fish stomach contents. Raman analysis has confirmed 11 microplastics and 13 fibers mainly made of cellulose or lignin. Some particles were not completely identified but contained artificial dyes. The novel approach developed in this manuscript should help to assess the presence, quantity, and composition of AP in planktivorous fish stomachs.
KeywordsLignin Raman Spectroscopy Stomach Content NaClO Rose Bengal
The authors thank the Institut Français de Recherche pour l’Exploitation de la Mer (IFREMER), the Thalassa and Europe skippers, Yves Verin and Jean-Louis Bigot, and their scientist teams. This study was funded by the Fonds de la Recherche Scientifique (F.R.S.-FNRS). F. Collard acknowledges a PhD Fund for Research Training in Industry and in Agriculture (F.R.I.A.) grant. K. Das is a F.R.S-FNRS Research Associate. This paper is MARE publication nr. 290.
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