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  • Karlsson, Therese,1987Gothenburg University,Göteborgs universitet,Institutionen för marina vetenskaper,Department of marine sciences,School of Science and Technology, University of Örebro, Örebro, Sweden; Department of Marine Sciences, Sven Loven Research Centre, University of Gothenburg, Fiskebäckskil, Sweden,MTM Research Centre (author)

Hyperspectral imaging and data analysis for detecting and determining plastic contamination in seawater filtrates

  • Article/chapterEnglish2016

Publisher, publication year, extent ...

  • 2016-01-01
  • Chichester, England :SAGE Publications,2016

Numbers

  • LIBRIS-ID:oai:gup.ub.gu.se/236343
  • https://gup.ub.gu.se/publication/236343URI
  • https://doi.org/10.1255/jnirs.1212DOI
  • https://res.slu.se/id/publ/77718URI
  • https://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-52164URI

Supplementary language notes

  • Language:English

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  • Subject category:ref swepub-contenttype
  • Subject category:art swepub-publicationtype

Notes

  • Funding Agency:European Union 308370
  • One possible way of monitoring plastic particles in sea water is by imaging spectroscopic measurements on filtrates. The idea is that filters from seawater sampling can be imaged in many wavelengths and that a multivariate data analysis can give information on (1) spatial location of plastic material on the filter and (2) composition of the plastic materials. This paper reports on simulated samples with spiked reference plastic particles, and real seawater filtrates containing microplastic pollutants. These real samples were previously identified through visual examination in a microscope. The samples were imaged using three different imaging systems. The different wavelength ranges were 375–970nm, 960–1662nm and 1000–2500nm. Data files from all three imaging systems were analysed by hyperspectral image analysis. The method using the wavelength span 1000–2500nm was shown to be the most applicable to this specific type of samples and gave a 100% particle recognition on reference plastic, above 300 µm and an 84% pixel recognition on household polyethylene plastic. When applied to environmental samples the technique showed an increase in identified particles compared with visual investigations. These initial tests indicate a potential underestimation of microplastics in environmental samples. This is the first study to demonstrate that hyperspectral imaging techniques can be used to study microplastics down to 300µm, which is a common size limit used in microplastic surveys.

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Added entries (persons, corporate bodies, meetings, titles ...)

  • Grahn, Hans,1954-Örebro universitet,Institutionen för naturvetenskap och teknik,Corpus Data & Image Analysis AB, Stockholm, Sweden,MTM Research Centre(Swepub:oru)hsgn (author)
  • van Bavel, Bert,1963-Örebro universitet,Institutionen för naturvetenskap och teknik,Norwegian Institute for Water Resaerch, Oslo, Norway,MTM Research Centre(Swepub:oru)bvl (author)
  • Geladi, PaulSwedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Skogens biomaterial och teknologi,Department of Forest Biomaterials and Technology,Corpus Data & Image Analysis AB,Corpus Data & Image Analysis AB, Stockholm, Sweden; Forest Biomaterials and Technology, Swedish University of Agricultural Sciences, Umeå, Sweden(Swepub:slu)47379 (author)
  • Göteborgs universitetInstitutionen för marina vetenskaper (creator_code:org_t)
  • Sveriges lantbruksuniversitet

Related titles

  • In:Journal of Near Infrared SpectroscopyChichester, England : SAGE Publications24:2, s. 141-1490967-03351751-6552

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