Digital holographic microscopy (DHM) has proved to be a powerful imaging tool for identifying, analysing and reconstructing the 3D shape of cells and small organisms in their natural environment. In fact, DHM has the advantage, compared to other imaging techniques, to be a non-intrusive, non-destructive and label-free method for in situ measurements. This makes holography the most suitable tool for underwater imaging, where many of the species under investigation are very fragile and can be damaged. In particular, we built up an optofluidic platform based on DHM able to perform such analysis in microfluidic environment, i.e. in dynamic conditions and also in case of a turbid medium. In this work, we take advantage of this technique to identify, sort and reconstruct the morphology of different classes of microplastics (e.g. PVC, PET, PP, etc.) dispersed in water, which are among the major pollutants in the ocean, and to provide an effective assessment of their abundance. By adopting special algorithms for numerical processing of the acquired images, we try to separate the plastics from other materials, such as organic debris (shell fragments, animals parts, diatoms, etc.) and other items (metal paint coatings, tar, glass, etc.).

Detection and sorting of microplastics in marine environment by new imaging tools

Paturzo M;Merola F;Bianco V;Memmolo P;Miccio L;Ferraro P
2018

Abstract

Digital holographic microscopy (DHM) has proved to be a powerful imaging tool for identifying, analysing and reconstructing the 3D shape of cells and small organisms in their natural environment. In fact, DHM has the advantage, compared to other imaging techniques, to be a non-intrusive, non-destructive and label-free method for in situ measurements. This makes holography the most suitable tool for underwater imaging, where many of the species under investigation are very fragile and can be damaged. In particular, we built up an optofluidic platform based on DHM able to perform such analysis in microfluidic environment, i.e. in dynamic conditions and also in case of a turbid medium. In this work, we take advantage of this technique to identify, sort and reconstruct the morphology of different classes of microplastics (e.g. PVC, PET, PP, etc.) dispersed in water, which are among the major pollutants in the ocean, and to provide an effective assessment of their abundance. By adopting special algorithms for numerical processing of the acquired images, we try to separate the plastics from other materials, such as organic debris (shell fragments, animals parts, diatoms, etc.) and other items (metal paint coatings, tar, glass, etc.).
2018
Istituto di Scienze Applicate e Sistemi Intelligenti "Eduardo Caianiello" - ISASI
Digital holography
Detection
Micro-plastics
Machine learning
artificial intelligence
environmental monitoring
Imaging sensors
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/353569
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact