This study proposes a method based on hyperspectral image superpixels and the use of light gradient boosting machine (LightGBM) classifier to categorize tobacco stems and impurities.  Subsequently, an improved LightGBM is applied and trained with the spectral and textural features of superpixels as a classification model. 
LightGBM