Abstract: Partial least-square (PLS) method was applied to establish quantitative analysis model using near-infrared (NIR) spectra for determination of shikimic acid content in aniseed (Illicium verum Hook.f.). Various spectrometric pretreatment methods were used respectively for conversion of NIR spectra of aniseed powdered samples in order to remove the noise in spectra. The pretreated spectra were applied to develop PLS quantitative analysis model respectively. Each model was optimized by selecting the most efficacious spectrometric pretreatment method and the most suitable number of factors. The optimum model was selected depending on the root mean squares of calibration set calculated by cross-validation(RMSECV), the correlation coefficient of the values prediction by cross-validation method and actual values and the root mean squares of prediction set(RMSEP). The results demonstrated that the optimum model possessed good stability and high precision. This method has great prospect for quantitative analysis of Chinese traditional medicine.

Key words: shikimic acid, Illicium verum Hook.f, near-infrared spectroscopy, partial least-square method