Objective: Near infrared (NIR) spectroscopy and chemometrics were used to identify the origins of Aceranthus sagittatus samples and to quantitatively analyze their active ingredients. Method: Nine different samples collected from different areas were analyzed

using vector normalization and/or first-order derivative processing methods. The active ingredients of these Aceranthus sagittatus samples were determined using HPLC method

and then they were used as the training data to generate the NIR quantitative analysis model using partial least square (PLS) method. Result: The results suggest that the vector normalization data processing gave us better qualitative identification model

the cluster analysis gave us satisfactory results. The classification error rate was 0. It can effectively identify the different origins of the samples thus this resulted qualitative analysis model can be used to quickly identify the origin of unknown samples. The PLS method indicated that the standard deviation of the prediction was 0.020 6

which means that it has very good accuracy of prediction. Conclusion: This analysis method is fast

simple and low-cost

which provides us a novel way for the qualitative identification of herbal medicine.