Microplastic (MP) contamination is present in the entire marine environment from the sediment to the water surface and down to the deep sea. This ubiquitous presence of MP particles opens the possibility for their ingestion by nearly all species in the marine ecosystem. Reports have shown that MP particles are present in local commercial seafood species leading to the possible human ingestion of these particles. However, due to a lack of harmonized methods to identify microplastics (MPs), results from different studies and locations can hardly be compared. Hence, this study was aimed to detect, quantify, and estimate MP contamination in commercially important mussels originating from 12 different countries distributed worldwide. All mussels were obtained from supermarkets and were intended for human consumption. Using a combinatorial approach of focal plane array (FPA)-based micro- Fourier-transform infrared (FTIR) spectroscopy and micro-Raman spectroscopy allowed the detection and characterization of MP down to a size of 3 μm in the investigated mussels. Further, a gentle sample purification method based on enzymes has been modified in order to optimize the digestion of organic material in mussels. A random forest classification (RFC) approach, which allows a rapid discrimination between different polymer types and thus fast generation of data on MP abundance and size distributions with high accuracy, was implemented in the analytical pipeline for IR spectra. Additionally, for the first time we also applied a RFC approach for the automated characterization of Raman spectra of MPs.

从沉积物到水面再到深海，整个海洋环境中都存在微塑料（MP）污染。MP粒子无处不在的存在为海洋生态系统中几乎所有物种吸收它们提供了可能性。报告表明，MP颗粒存在于当地的商业海产品种中，可能导致人体摄入这些颗粒。但是，由于缺乏统一的方法来识别微塑料（MPs），因此很难比较不同研究和地区的结果。因此，本研究旨在检测，量化和估计源自全球12个不同国家的重要商业贻贝中的MP污染。所有贻贝都是从超级市场获得的，供人类食用。使用基于焦平面阵列（FPA）的微傅里叶变换红外（FTIR）光谱和显微拉曼光谱的组合方法，可以对所研究的贻贝中的MP进行检测和表征，最小至3μm。此外，为了优化贻贝中有机物质的消化，已经修改了基于酶的温和样品纯化方法。在红外光谱分析管线中实施了随机森林分类（RFC）方法，该方法可以快速区分不同的聚合物类型，从而以高精度快速生成MP丰度和尺寸分布的数据。此外，我们还首次将RFC方法应用于MP的拉曼光谱的自动表征。