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Detection of microplastics stress on rice seedling by visible/near-infrared hyperspectral imaging and synchrotron radiation Fourier transform infrared microspectroscopy
Summary
Researchers used visible/near-infrared hyperspectral imaging combined with synchrotron radiation analysis and deep learning to detect physiological and biochemical stress responses in rice seedlings exposed to microplastics, developing a rapid and interpretable early-detection method for microplastic stress in crops.
In conclusion, the combination of spectral technology and deep learning to capture the physiological and biochemical reactions of leaves could provide a rapid and interpretable method for detecting rice seedlings under MPs stress. This method could provide a solution for the early detection of external stress on other crops.