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This paper proposes a sorghum adulteration detection model making use of hyperspectral imaging technology (HSI), picture handling technology, and multivariate analysis technology. The model utilized a watershed algorithm to extract hyperspectral information from sorghum grains. Major component analysis (PCA) and clustering analysis (CA) were used to eliminate abnormal types of sorghum. Limited minimum squares discriminant analysis (PLS-DA) had been made