Department of Animal Ecology I and BayCEER, University of Bayreuth, Universitätsstr. 30, 95440, Bayreuth, Germany.
Alfred-Wegener-Institute Helmholtz Centre for Polar and Marine Research, Biologische Anstalt Helgoland, Kurpromenade 201, 27498, Helgoland, Germany.
Anal Bioanal Chem. 2023 Jun;415(15):2975-2987. doi: 10.1007/s00216-023-04630-w. Epub 2023 Mar 20.
One of the biggest issues in microplastic (MP, plastic items <5 mm) research is the lack of standardisation and harmonisation in all fields, reaching from sampling methodology to sample purification, analytical methods and data analysis. This hampers comparability as well as reproducibility among studies. Concerning chemical analysis of MPs, Fourier-transform infrared (FTIR) spectroscocopy is one of the most powerful tools. Here, focal plane array (FPA) based micro-FTIR (µFTIR) imaging allows for rapid measurement and identification without manual preselection of putative MP and therefore enables large sample throughputs with high spatial resolution. The resulting huge datasets necessitate automated algorithms for data analysis in a reasonable time frame. Although solutions are available, little is known about the comparability or the level of reliability of their output. For the first time, within our study, we compare two well-established and frequently applied data analysis algorithms in regard to results in abundance, polymer composition and size distributions of MP (11-500 µm) derived from selected environmental water samples: (a) the siMPle analysis tool (systematic identification of MicroPlastics in the environment) in combination with MPAPP (MicroPlastic Automated Particle/fibre analysis Pipeline) and (b) the BPF (Bayreuth Particle Finder). The results of our comparison show an overall good accordance but also indicate discrepancies concerning certain polymer types/clusters as well as the smallest MP size classes. Our study further demonstrates that a detailed comparison of MP algorithms is an essential prerequisite for a better comparability of MP data.
微塑料（MP，尺寸小于 5 毫米的塑料物品）研究中最大的问题之一是缺乏所有领域的标准化和协调，从采样方法到样品净化、分析方法和数据分析都存在这个问题。这不仅影响了研究之间的可比性，也影响了其再现性。关于 MPs 的化学分析，傅里叶变换红外（FTIR）光谱学是最强大的工具之一。在这里，基于焦平面阵列（FPA）的微傅里叶变换（µFTIR）成像允许快速测量和识别，而无需手动预选假定的 MPs，因此可以实现具有高空间分辨率的大样本通量。由此产生的大量数据集需要自动化算法在合理的时间范围内进行数据分析。虽然已经有解决方案，但对于它们的输出的可比性或可靠性水平知之甚少。在我们的研究中，我们首次比较了两种成熟且经常应用的数据分析算法，以比较从选定环境水样中得出的 MPs（11-500μm）的丰度、聚合物组成和尺寸分布的结果：(a) siMPle 分析工具（环境中微塑料的系统识别）与 MPAPP（微塑料自动颗粒/纤维分析管道）相结合和 (b) BPF（拜罗伊特粒子查找器）。我们比较的结果表明总体上一致性很好，但也表明某些聚合物类型/聚类以及最小的 MPs 尺寸类别存在差异。我们的研究进一步表明，详细比较 MPs 算法是提高 MPs 数据可比性的必要前提。
