Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Biologische Anstalt Helgoland, Kurpromenade 201, 27498, Helgoland, Germany.
Leibniz Institute for Baltic Sea Research Warnemünde, Seestraße 15, 18119, Rostock, Germany.
Anal Bioanal Chem. 2018 Aug;410(21):5131-5141. doi: 10.1007/s00216-018-1156-x. Epub 2018 Jul 6.
The identification of microplastics becomes increasingly challenging with decreasing particle size and increasing sample heterogeneity. The analysis of microplastic samples by Fourier transform infrared (FTIR) spectroscopy is a versatile, bias-free tool to succeed at this task. In this study, we provide an adaptable reference database, which can be applied to single-particle identification as well as methods like chemical imaging based on FTIR microscopy. The large datasets generated by chemical imaging can be further investigated by automated analysis, which does, however, require a carefully designed database. The novel database design is based on the hierarchical cluster analysis of reference spectra in the spectral range from 3600 to 1250 cm. The hereby generated database entries were optimized for the automated analysis software with defined reference datasets. The design was further tested for its customizability with additional entries. The final reference database was extensively tested on reference datasets and environmental samples. Data quality by means of correct particle identification and depiction significantly increased compared to that of previous databases, proving the applicability of the concept and highlighting the importance of this work. Our novel database provides a reference point for data comparison with future and previous microplastic studies that are based on different databases. Graphical abstract ᅟ.
随着颗粒尺寸的减小和样品异质性的增加,识别微塑料变得越来越具有挑战性。傅里叶变换红外(FTIR)光谱分析是一种多功能、无偏的工具,可以成功完成这项任务。在本研究中,我们提供了一个适应性强的参考数据库,该数据库可用于单颗粒识别以及基于 FTIR 显微镜的化学成像等方法。化学成像生成的大型数据集可以通过自动化分析进一步研究,然而,这需要精心设计的数据库。新的数据库设计基于参考光谱在 3600 至 1250 cm 光谱范围内的层次聚类分析。由此生成的数据库条目经过优化,可用于具有定义参考数据集的自动化分析软件。该设计还通过附加条目进一步测试了其可定制性。最终的参考数据库在参考数据集和环境样品上进行了广泛测试。与之前的数据库相比,通过正确的颗粒识别和描述提高了数据质量,证明了该概念的适用性,并强调了这项工作的重要性。我们的新数据库为未来和基于不同数据库的先前微塑料研究的数据比较提供了参考点。