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Dynamic Image Analysis for Determination of Textile Fibers
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Researchers applied dynamic image analysis to characterize shed fibers in washing effluents from textile processing, combining morphological measurement with chemical pretreatment to identify fiber debris from polyester-cotton blends as an efficient alternative to time-consuming filtration and microscopy methods.
The detection of shed fibers in effluents from textile washing has attracted much attention due to its reported contribution to microplastic pollution. Commonly used analytical methods for fiber detection in liquids are based on filtration with subsequent microscopic analysis and/or gravimetric weighing, which are time-consuming and prone to errors. In this study, an approach based on dynamic image analysis was applied in order to set up an efficient method to analyze fibers in effluents from washing processes. In the first step, information on the amount of fibers and the morphological characteristics by the dynamic image analysis was confirmed. The chemical nature of fiber debris from polyester–cotton blends was determined by combining the dynamic image analysis with a chemical pretreatment. In this study, dynamic image analysis was revealed as a rapid, non-destructive, precise, and reliable technology for the characterization and quantification of fiber debris, offering a promising approach for fiber analysis in liquids.
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