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Microplastics characterization by hyperspectral imaging in the SWIR range

2019 33 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 40 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.

Ludovica Fiore, Giuseppe Bonifazi Giuseppe Bonifazi Silvia Serranti, Silvia Serranti, Silvia Serranti, Giuseppe Bonifazi Silvia Serranti, Giuseppe Bonifazi Silvia Serranti, Giuseppe Bonifazi Shosaku Kashiwada, Silvia Serranti, Ludovica Fiore, Silvia Serranti, Silvia Serranti, Silvia Serranti, Silvia Serranti, Silvia Serranti, Giuseppe Bonifazi Giuseppe Bonifazi Shosaku Kashiwada, Ludovica Fiore, Ludovica Fiore, Giuseppe Bonifazi Giuseppe Bonifazi Giuseppe Bonifazi Giuseppe Bonifazi Silvia Serranti, Silvia Serranti, Shosaku Kashiwada, Silvia Serranti, Silvia Serranti, Silvia Serranti, Ayaka Takeshima, Giuseppe Bonifazi Ayaka Takeshima, Silvia Serranti, Giuseppe Bonifazi Silvia Serranti, Giuseppe Bonifazi Hisato Takeuchi, Silvia Serranti, Silvia Serranti, Giuseppe Bonifazi Giuseppe Bonifazi Giuseppe Bonifazi Giuseppe Bonifazi Shosaku Kashiwada, Giuseppe Bonifazi Shosaku Kashiwada, Silvia Serranti, Silvia Serranti, Giuseppe Bonifazi Giuseppe Bonifazi

Summary

Researchers developed a hyperspectral imaging methodology operating in the short-wave infrared range (1000-2500 nm) combined with chemometric classification to rapidly identify polymer types in microplastic samples collected from marine environments. The non-destructive approach enabled polymer characterisation across samples from multiple geographical regions without requiring chemical pre-treatment.

The aim of this study is to develop a new methodology based on optical sensors able to recognize and characterize microplastics collected in the marine environment. In recent years, this pollution represents an environmental emergency with serious effects on human health and marine organisms. The study was carried out on microplastics collected in different geographical areas. Through the hyperspectral imaging (HSI) based approach, performed in the SWIR range (1000-2500 nm), a classification model based on chemometric techniques was implemented in order to identify in a rapid, non invasive and non-destructive way the polymers in the investigated samples.

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