Institute of Water Chemistry, Chair of Analytical Chemistry and Water Chemistry, Technical University of Munich, Lichtenbergstr. 4, 85748, Garching, Germany.
Anal Bioanal Chem. 2023 Jun;415(15):2947-2961. doi: 10.1007/s00216-023-04712-9. Epub 2023 Jun 8.
Accurate quantification of small microplastics in environmental and food samples is a prerequisite for studying their potential hazard. Knowledge of numbers, size distributions and polymer type for particles and fibers is particularly relevant in this respect. Raman microspectroscopy can identify particles down to 1 [Formula: see text]m in diameter. Here, a fully automated procedure for quantifying microplastics across the entire defined size range is presented as the core of the new software TUM-ParticleTyper 2. This software implements the theoretical approaches of random window sampling and on-the-fly confidence interval estimation during ongoing measurements. It also includes improvements to image processing and fiber recognition (when compared to the previous software TUM-ParticleTyper for analysis of particles/fibers [Formula: see text] [Formula: see text]m), and a new approach to adaptive de-agglomeration. Repeated measurements of internally produced secondary reference microplastics were evaluated to assess the precision of the whole procedure.
准确量化环境和食品样品中的小微型塑料是研究其潜在危害的前提条件。在这方面,有关颗粒和纤维的数量、大小分布和聚合物类型的知识尤为重要。拉曼微光谱技术可以识别直径低至 1 微米的颗粒。在这里,提出了一种全自动程序,用于在整个定义的尺寸范围内定量微型塑料,这是新软件 TUM-ParticleTyper 2 的核心。该软件在进行测量时实现了随机窗口采样和实时置信区间估计的理论方法。与用于分析颗粒/纤维 [Formula: see text] [Formula: see text] 微米的先前软件 TUM-ParticleTyper 相比,它还包括对图像处理和纤维识别的改进,以及一种新的自适应解团聚方法。对内部生产的二级参考微型塑料的重复测量进行了评估,以评估整个程序的精度。