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. 2018 Aug;410(21):5131-5141.
doi: 10.1007/s00216-018-1156-x. Epub 2018 Jul 6.

Reference database design for the automated analysis of microplastic samples based on Fourier transform infrared (FTIR) spectroscopy

Affiliations

Reference database design for the automated analysis of microplastic samples based on Fourier transform infrared (FTIR) spectroscopy

Sebastian Primpke et al. Anal Bioanal Chem. 2018 Aug.

Abstract

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-1. 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.

Keywords: Database; FTIR; Imaging; Infrared; Microplastics; Spectroscopy.

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Conflict of interest statement

The authors declare that they have no conflict of interest.

Figures

Graphical abstract
Graphical abstract
Fig. 1
Fig. 1
Dendrogram of manually generated clusters. For lucidity, the spectra were grouped and the number of contained spectra written in brackets behind the cluster name. All merged clusters (see text for details) were connected by green lines; for all later excluded clusters, the lines are marked red (reduction of clusters) and orange (cluster categories)
Fig. 2
Fig. 2
Image analysis pictures of single particles with different assigned database entries
Fig. 3
Fig. 3
Photograph (a), unclosed image (b), and closed image (c) of a piece of cellulose foil. Closed image (d) of the same particle when silica gel is present in the adaptable database design
Fig. 4
Fig. 4
Polymer-type-dependent false color image of the sample RefEnv1 after automated analysis with the adaptable database design
Fig. 5
Fig. 5
Polymer-type-dependent false color image of the sample RevEnv2 after automated analysis with the adaptable database design
Fig. 6
Fig. 6
Size distribution and polymer composition for plastic particles derived via automated analysis for the sample RevEnv2. The region for particles with a size > 50 μm was highlighted for a better overview

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