A Novel High-Throughput Detection Method for Plastic Debris in Organic-Rich Matrices Based on Image Fusion.

ABSTRACT

Plastic pollution pervades natural environments and wildlife. Consequently, high-throughput detection methods for plastic debris are urgently needed. A novel method was developed to detect plastic debris larger than 0.5 mm, which integrated an extraction method with low organic loss and plastic damage alongside a classification method for fused images. This extraction method broadened the size range of the remaining plastic debris, while the fusion solved the low spatial resolution of hyperspectral images and the absence of spectral information in red-green-blue (RGB) images. This method was validated for plastic debris in digestate, compost, and sludge, with extraction demonstrating 100% recovery rates for all samples. After fusion, the spatial resolution of hyperspectral images was improved about five times. Classification recall for the fused hyperspectral images achieved 97 ± 8%, surpassing 83 ± 29% of the raw images. Application of this method to solid digestate detected 1030 ± 212 items/kg of plastic debris, comparable with the conventional Fourier transform infrared spectroscopic result of 1100 ± 436 items/kg. This developed method can investigate plastic debris in complex matrices, simultaneously addressing a wide range of sizes and types. This capability helps acquire reliable data to predict secondary microplastic generation and conduct a risk assessment.