In order to identify American ginseng and panax ginseng samples accurately and rapidly, the authors acquired the NIR spectra of the samples’ cross-sections. Then the spectra were respectively analyzed according to the samples’ physical structure factors and chemical factors. The authors selected appropriate bands and built a physical factor leading model, a chemical factors leading model as well as a comprehensive factor model. The authors found that all the three models’ discriminant rates were above 96 percents, which can meet the needs of the rapid detection of raw Chinese medicinal crop materials. While the physical factors model had a simple operation, the discriminant rate was relatively low. The chemical factors model’ discriminant rate was higher, but the computation is much more complex. Among the three models, the mixed factor model had the best result with the highest discrimination rate (100 percents) and a smaller number of principal components (4). The effect was the most ideal. It proved that physical factors play an important part in NIR modeling. The cross section method is accurate and convenient which can be used in the quality control in enterprise, realizing the rapid screening of the medicine raw materials.