Application of VIS-NIR Hyperspectral Imaging to the Detection and Quantification of MPs in Simulant Shellfish

Abstract

As the world has become increasingly reliant on single-use plastics, plastic litter has increased exponentially, especially in marine ecosystems. One type of plastic litter affecting marine life is microplastics, which are plastics under 5mm in diameter. Microplastics are consumed by marine animals, which are then consumed by people. Study of the environmental and human health effects of these microplastics has proven difficult, in part due to difficulty detecting and quantifying microplastics. This study aims to detect microplastics in shellfish by utilizing the nondestructive method of hyperspectral imaging as an indicator of both marine ecosystem health and food quality. Gelatin models of shellfish were injected with a known concentration of microplastics (polyvinyl chloride (PVC) and polystyrene (PS), specifically). The hyperspectral camera then took 3-dimensional images of the models, with the wavelength dimension ranging from 400 nm to 1000 nm. Next, an algorithm called Partial Least Squares Regression Analysis was developed to analyze the relationship between the wavelengths and the amount of plastic in the sample. Preliminary results have shown slight variation in reflectance spectra between models spiked with microplastics and control models past the 950 nm range. Therefore, hyperspectral imaging might be a viable tool to detect and quantify microplastics in shellfish, but the range of the camera used in this study is a limitation.