Qualitative and Quantitative Analysis of Paris polyphylla var. yunnanensis in Different Harvest Times with Infrared Spectroscopy Combined with Chemometrics

In order to provide a scientific basis tor find out the best harvest time. Fourier transform infrared (FTIR) spectroscopy combined with partial least squares discriminant analysis (PLS-DA) and partial least squares regression (PLSR) were used for the identification and evaluation of Paris polyphylla var. yunnanensis from different harvest times. Infrared spectra of 46 samples from different harvest times were collected. The original spectra were pretreated with automatic baseline correction, ordinate normalization, automatic smoothing and wavelet denosing prior to PLS-DA. The contents of polyphyllin I, II, VI and VII were determined with ultra performance liquid chromatography (UPLC). The PLSR model was established combining the spectral data with the reference data performed by UPLC data for evaluating the quality of polyphyllin I, II, VI and VI after the preprocessing of automatic baseline correction, ordinate normalization, automatic smoothing, first derivative and Orthogonal signal correction (OSC). Results showed that: (1) The main absorptions of the original spectra were in the ranges of 950 similar to 700, 1 200 similar to 950, 1 800 similar to 1 500 and 2 800 similar to 3 500 cm(-1). (2) The PLS-DA score plot could accurately distinguish P. polyphylla var. yunnanensis from different harvest times. (3) According to the UPLC data, it was found that the total content of polyphyllin I, II, VI and VII got a fold increase, then elicited a decline, and finally showed a slow upward trend with the growth period. (4)There was no significant differences between the predicted value based on quantitative model and measured value with UPLC, and the effect of the model was good. FT-IR spectroscopy combined with chemometrics could clearly distinguish P. polyphylla var. yunnanensis from different harvest times and reach a fast prediction for the content of polyphyllin. Furthermore, it could provide a method for distinguishing and forecasting polyphyllin and a theoretical basis for best harvest time of P. polyphylla var. yunnanensis.