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A Preliminary Study on the Utilization of Hyperspectral Imaging for the On-Soil Recognition of Plastic Waste Resulting from Agricultural Activities
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Researchers explored the use of near-infrared hyperspectral imaging to detect and identify plastic waste in agricultural soils. They developed a classification model that could distinguish different types of plastic from soil and assess the degradation state of the material. The study demonstrates that hyperspectral imaging combined with chemometric analysis offers a rapid, non-destructive approach for monitoring plastic contamination in agricultural environments.
Plastic in agriculture is frequently used to protect crops and its use boosts output, enhances food quality, contributes to minimize water consumption, and reduces the environmental impacts of agricultural activities. On the other hand, end-of-life plastic management and disposal are the main issues related to their presence in this kind of environment, especially in respect of plastic degradation, if not properly handled (i.e., storage places directly in contact with the ground, exposure of stocks to meteoric agents for long periods, incorrect or incomplete removal). In this study, the possibility of using an in situ near infrared (NIR: 1000–1700 nm) hyperspectral imaging detection architecture for the recognition of various plastic wastes in agricultural soils in order to identify their presence and also assess their degradation from a recovery/recycling perspective was explored. In more detail, a Partial Least Squares—Discriminant Analysis (PLS-DA) classifier capable of identifying plastic waste from soil was developed, implemented, and set up. Results showed that hyperspectral imaging, in combination with chemometric approaches, allows the utilization of a rapid, non-destructive, and non-invasive analytical approach for characterizing the plastic waste produced in agriculture, as well as the potential assessment of their lifespan.
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