0
Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Detection Methods Environmental Sources Gut & Microbiome Policy & Risk Sign in to save

Rapid Detection of Microplastics in Plastic-covered Soil Using FT-NIR and ATR-FTIR Spectral Data Fusion

Figshare 2026 Score: 40 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Jingyu Jiang, Jingyu Jiang, Yujiang Gou, Yujiang Gou, Jiaxin Cao, Jiaxin Cao, Fu Jiao, Fu Jiao, Shixiang Ma, Shixiang Ma, Wu Xin, Wu Xin, Guanglin Li, Guanglin Li, Xinglan Fu

Summary

Scientists developed a new method to quickly detect tiny plastic particles in farm soil by combining two different light-based detection techniques. This method can accurately measure microplastic pollution in agricultural fields where plastic covers are used for growing crops. This matters because microplastics in farm soil can potentially enter our food chain through the fruits and vegetables we eat.

Agricultural soils are significant reservoirs of microplastic pollution, making efficient quantification methods crucial for assessment and control. The study employed Fourier Transform Near-Infrared Spectroscopy (FT-NIR) and Attenuated Total Reflection Fourier Transform Infrared Spectroscopy (ATR-FTIR) 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. 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 mg·kg-1 on the prediction set, while exhibiting good generalization capability on the test set (RMSET = 3.8727). 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.

Share this paper