Rapid detection of microplastics in plastic-covered soils using FT-NIR and ATR-FTIR spectral data fusion

Agricultural soils are significant reservoirs of microplastic pollution, making efficient quantification methods crucial for assessment and control. The study employed Fourier transform near-infrared (FT-NIR) spectroscopy and attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy to acquire spectral data from soils in plastic-covered fields. Microplastic concentrations in soil samples were determined through density separation and digestion methods to establish truth values. Middle-level and low-level data-fusion strategies were integrated with support vector regression (SVR) to construct mathematical models linking spectral data to truth values. The experimental results demonstrated that the spectral fusion strategy significantly outperformed single-technique models. The principal component analysis (PCA) combined with the middle-level method showed optimal performance, achieving a root mean square error (RMSEP) of 2.1110 and a limit of detection (LOD) of 6.9258<i>m</i><i>g</i><i>k</i><i>g</i>^-1 on the prediction set, while exhibiting good generalization capability on the test set (<i>R</i><i>M</i><i>S</i><i>E</i><i>T</i>=3.8727). The spectral fusion technology integrating FT-NIR and ATR-FTIR enables rapid quantitative detection of soil microplastics, offering an innovative approach for monitoring microplastic pollution in farmland.