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Microplastic

Zenodo (CERN European Organization for Nuclear Research) 2019
Benedikt Hufnagl, Dieter Steiner, Elisabeth Renner, Martin G. J. Löder, Christian Laforsch, Hans Lohninger

Summary

This entry describes a FTIR hyperspectral image dataset of an environmental plankton sample spiked with microplastics ranging from 10 to 200 micrometers, covering common polymer types including polyethylene, polypropylene, and polystyrene. The dataset was used to train machine learning classifiers for automated microplastic identification.

Polymers
PAN PE PP PS

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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