Abstract:Near infrared(NIR) transmission spectroscopy was applied to the discrimination of three brands of Huoxiang Zhengqi Tincture with the aid of chemometrics.Near infrared spectra data was compressed by wavelet transform(WT) and the optimal wavelengths were selected by genetic algorithm(GA).Then the principal component analysis(PCA) was chosen to analyze the reduced data to obtain well-grouped results.The NIR data was further predicted with different supervised pattern recognize method,back propagation-artificial neural network(BP-ANN),and recognition rates of 100% were achieved.It indicated that the model set up by the combination of WT technology and BP neural network could be the rapidest in analysis and precise in discrimination of Huoxing Zhengqi Tincture.