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A fractal analysis of the holographic diffraction patterns for detecting microplastics among diatoms
Summary
Researchers developed a fractal analysis approach applied to holographic diffraction patterns to distinguish microplastics from diatoms in water samples, enabling automated identification of plastic particles in complex biological matrices.
Water pollution is one of the main global emergencies that must be quickly addressed in order to hinder its growing effects, which represent a danger for the environmental and the human health. It is mostly due to the production of microplastics from the larger plastic items released more and more into the water environment during the last decades. Therefore, the accurate identification of microplastics is strongly requested in order to assess the degree of pollution of a certain water area and then to apply suitable ecological strategies to clean it. However, this goal has not yet been achieved, because of the wide heterogeneity of objects that can be found in a water sample, and their microscopic dimensions. In particular, a lot of species of diatoms (i.e., unicellular microalgae) share the same range size and shape with microplastics. Digital holography (DH) has been exploited to realize a quantitative analysis of the microplastics’ and diatoms’ properties at the microscopic scale. Recently, we demonstrated the fruitful combination between the DH and the fractal geometry, in order to measure a very distinctive fractal signature related to the scattering properties of the imaged samples. Here we demonstrate that, by properly combining some of these fractal parameters with each other, also subsets of the fractal features allow to reach high accuracy in detecting microplastics among diatoms. These results, combined to the flow cytometric applications of DH, could open the route for fast and accurate tools for the microplastics’ identification and quantification in water.
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