الملخص
Objective:To realize the rapid and accurate discrimination of Swertia plants by Fourier transform infrared spectroscopy (FTIR) and chemometrics. Method:The original infrared spectra data from different parts (roots,stems,leaves) of all of the 543 samples of S. davidii,S. mileensis,S. punicea,S. angustifolia and S. cincta were collected and preprocessed by multiplicative scatter correction (MSC),standard normal variate (SNV),Savitzky-Golay filter (SG),first derivative (1D),second derivative (2D),third derivative (3D). Then,the spectral ranges of 4 000-3 700,2 799-1 800 cm-1 and 682-653 cm-1 were deleted before PLS-DA and SVM analysis. Result:The samples of the five species could not be distinguished with similar averaged infrared spectra in the same part. The characteristic peaks of different parts in the same species were different, and the sequence of complexity was leaves > stems > roots. The five species of Swertia could accurately be identified by PLS-DA and SVM models established by spectra data in roots, stems and leaves. MSC+SG+2D showed the best preprocessing effect,and the prediction accuracies of all models were 100%. The values of R2Y in PLS-DA of all of the parts were more than 0.8, and the RMSEP was less than RMSECV,indicating that the model was stable and more effective. Furthermore,the value of Q2 exceeded 0.6, and the accuracy of prediction set reached 100%, indicating a high classification accuracy. It showed that PLS-DA models had a strong prediction ability. The c values in SVM model of roots,stems and leaves were 22.627 4,2 and 1.414 2,respectively,which were all within the normal ranges. The accuracy of prediction set was 100%, suggesting a high accuracy. Conclusion:FTIR combined with PLS-DA and SVM could accurately distinguish different species from Swertia, and the model has a good prediction effect and provides certain reference for the identification of other plants.