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Sulfur-fumigated Chinese medicine is a common issue in the process of Chinese medicines. Detection of sulfur dioxide (SO2) residual content in Fritillaria thunbergii Bulbus is important to evaluate the degree of sulfur fumigation and its harms. It helps to control the use of sulfur fumigation in Fritillaria thunbergii Bulbus. Near-infrared hyperspectral imaging (NIR-HSI) was explored as a rapid, non-destructive, and accurate technique to detect SO2 residual contents in Fritillaria thunbergii Bulbus. An HSI system covering the spectral range of 874–1734 nm was used. Partial least squares regression (PLSR) was applied to build calibration models for SO2 residual content detection. Successive projections algorithm (SPA), weighted regression coefficients (Bw), random frog (RF), and competitive adaptive reweighted sampling (CARS) were used to select optimal wavelengths. PLSR models using the full spectrum and the selected optimal wavelengths obtained good performance. The Bw-PLSR model was applied on a hyperspectral image to form a prediction map, and the results were satisfactory. The overall results in this study indicated that HSI could be used as a promising technique for on-line visualization and monitoring of SO2 residual content in Fritillaria thunbergii Bulbus. Detection and visualization of Chinese medicine quality by HSI provided a new rapid and visual method for Chinese medicine monitoring, showing great potential for real-world application

Application of Near-Infrared Hyperspectral Imaging to Detect Sulfur Dioxide Residual in the Fritillaria thunbergii Bulbus Treated by Sulfur Fumigation