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Here we present evidence of the feasibility of sensing plastics in water using hyperspectral near-infrared to shortwave-infrared imaging techniques. We captured hyperspectral images of nine polymers submerged to four depths (2.5\u201315\u00a0mm) in water using a hyperspectral imaging system that utilizes near-infrared to shortwave-infrared light sources. We also developed algorithms to predict the reflectance spectra of each polymer in water using the spectra of the dry plastics and water as independent variables in a multiple linear regression model after a logarithmic transformation. A narrow 1100\u20131300\u00a0nm wavelength range was advantageous for detection of polyethylene, polystyrene, and polyvinyl chloride in water down to the 160\u2013320\u00a0\u00b5m size range, while a wider 970\u20131670\u00a0nm wavelength range was beneficial for polypropylene reflectance spectrum prediction in water. Furthermore, we found that the spectra of the other five polymers, comprising polycarbonate, acrylonitrile butadiene styrene, phenol formaldehyde, polyacetal, and polymethyl methacrylate, could also be predicted within their respective optimized wavelength ranges. Our findings provide fundamental information for direct sensing of plastics in water on both benchtop and airborne platforms.<\/jats:p>","DOI":"10.1038\/s41598-023-39754-7","type":"journal-article","created":{"date-parts":[[2023,10,6]],"date-time":"2023-10-06T06:01:26Z","timestamp":1696572086000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Eliminating the interference of water for direct sensing of submerged plastics using hyperspectral near-infrared imager"],"prefix":"10.1038","volume":"13","author":[{"given":"Chunmao","family":"Zhu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yugo","family":"Kanaya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,10,6]]},"reference":[{"key":"39754_CR1","doi-asserted-by":"publisher","first-page":"1622","DOI":"10.1038\/s41467-019-09506-1","volume":"10","author":"C Ostle","year":"2019","unstructured":"Ostle, C. et al. 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