Ginseng is a valuable variety of traditional Chinese medicine with high economic value. The growth is very regional, and the effective ingredients of ginseng from different origins are different. Whether ginseng is “authentic” or not, it will cause differences in its quality, medical utility and economic value, so the identification of ginseng origin is of great significance. After powder extraction and other preparations, chemical or optical methods are used to test the origin of ginseng, but this will cause damage to the sample. Besides, the identification based on appearance traits or rhizome head characteristics can not be used as a standardized recognition method because of human subjective differences or easy to be falsified. The main standpoint of this article is how to use high-precision, non-destructive, and rapid detection and identification methods to identify and analyze the origin of ginseng. This experiment uses hyperspectral imaging technology, for ginseng samples with known origin information, the hyperspectral reflectance dataset was constructed by obtaining reflectance spectra from 400 to 2 500 nm, after absolute and relative radiometric corrections based on the whiteboard. A full spectrum ginseng origin recognition model based on hyperspectral data was constructed, and the accuracy of origin recognition was verified for different scales of regional division rules. It was found that the ginseng spectra from different origins were significantly different. The accuracy of origin identification of the northeastern provinces or not can reach 98.2%. The spectral importance results of ginseng origin recognition were given, indicating the characteristic spectrum for developing a special lightweight instrument. As a strict non-destructive detection method, hyperspectral ginseng origin identification research will provide theoretical support and technical means for identifying the origin of authentic Chinese medicinal materials such as ginseng, fingerprint recognition and mining of medicinal materials, identification and quality evaluation, etc.