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Microplastic

Figshare 2019 1 citation ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Benedikt Hufnagl, Dieter Steiner, Elisabeth Renner, Martin G. J. Löder, Christian Laforsch, Hans Lohninger

Summary

This FTIR hyperspectral image dataset shows a plankton environmental sample spiked with microplastics of five polymer types (PE, PP, PS, PMMA, PAN) in the 10-200 micrometer size range, used to develop and train random decision forest classifiers for automated microplastic identification. The dataset supports machine learning approaches to faster and more consistent microplastic detection in complex biological samples.

This FTIR hyperspectral image shows an environmental plankton sample which has been spiked with microplastics in the size range between 10 and 200 µm. The added particles are one of the following polymer types: polyethylene polypropylene polystyrene poly(methyl methacrylate) polyacrylonitrile This hyperspectral image has been used as a source for training data for the creation of random decision forest classifiers. For a closer description of the dataset and the sample preparation see Hufnagl et al. (2019). If you reuse this dataset please cite Hufnagl, B., Steiner, D., Renner, Löder, M. G. J., Laforsch, C. and Lohninger, H. A Methodology for the Fast Identification and Monitoring of Microplastics in Environmental Samples using Random Decision Forest Classifiers, Analytical Methods, 2019, DOI:10.1039/C9AY00252A

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