傅里叶变换红外光谱（FTIR）结合偏最小二乘判别分析（PLS-DA）和偏最小二乘回归（PLSR）对不同采收期滇重楼（Paris polyphylla var yunnanensis）分别进行定性鉴别与定量分析, 以期为滇重楼合理采收和鉴别评价提供科学依据。 采集46份不同采收期滇重楼样品的红外光谱, 对光谱数据进行自动基线校正+纵坐标归一化+自动平滑+小波去噪（WD）预处理后进行PLS-DA分析; 采用超高效液相色谱测定样品中重楼皂苷Ⅰ, Ⅱ, Ⅵ, Ⅶ的含量, 将液相测定数据与红外光谱数据进行拟合, 经自动基线校正+纵坐标归一化+自动平滑+一阶求导+正交信号校正（OSC）优化处理后, 建立滇重楼中重楼皂苷Ⅰ, Ⅱ, Ⅵ, Ⅶ的快速预测模型。 结果显示, （1）原始红外光谱中主要吸收区域在950~700, 1 200~950, 1 800~1 500和2 800~3 500 cm-1附近。 （2）PLS-DA得分图可准确区分不同采收期滇重楼样品。 （3）液相数据显示重楼总皂苷含量随着年限的增加先成倍增加, 再逐渐减少, 最后呈现缓慢增加的趋势。 （4）重楼总皂苷含量定量模型的预测值与真实值间无显著性差异, 表明模型预测效果好。 FTIR结合化学计量学可准确区分不同采收期滇重楼并快速预测其皂苷含量, 为不同采收期滇重楼的鉴别和皂苷含量预测提供一种新方法, 同时为确定滇重楼的最佳采收期提供参考依据。

In order to provide a scientific basis tor find out the best harvest time. Fourier transform infrared (FT-IR) 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 Ⅶ 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 950~700, 1 200~950, 1 800~1 500 and 2 800~3 500 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.