近红外光谱法快速鉴别不同产地的前胡药材

目的应用近红外光谱技术结合化学计量学方法建立一种快速鉴别前胡药材产地的方法。方法首先收集6个产地的90个前胡样本,采集各样本的近红外光谱,并划分为校正集(72个样本)和预测集(18个样本),然后利用校正集,采用化学计量学方法建立前胡药材产地的判别分析模型,最后利用预测集,对判别分析模型进行性能评价。结果优选的判别分析模型参数如下:光谱预处理方法为多元散射校正(MSC)+Savitzky-Golay卷积二阶求导算法(SG)(窗口参数为51,拟合次数为1),光谱波段为8 400~4 200 cm^-1,判别分析模型的主成分数为18。预测集的鉴别结果表明该判别分析模型的正确识别率为100%,6个产地前胡药材之间存在明显的界限。结论研究表明,近红外光谱法能简便、准确地实现前胡药材产地的快速鉴别,为前胡药材产地快速鉴别研究提供了理论支持和实用方法。

Rapid Identification of Different Geographical Origin of Peucedani Radix by Near-infrared Spectroscopy

OBJECTIVE The near-infrared spectroscopy (NIR) combined with chemometric was used to establish a method for rapid identification of geographical origins of Peucedani Radix. METHODS Firstly, the NIR spectra of 90 Peucedani Radix samples from six main origins were collected, which were divided into the calibration set (72 samples) and the prediction set (18 samples). Secondly, chemometric methods were used to establish a model for determination of geographical origins of Peucedani Radix using the calibration set. Finally, the performance of the model was evaluated using the prediction set. RESULTS The parameters of the model were as follows:the spectral preprocessing method was multivariate scatter correction (MSC) with Savitzky-Golay convolution second-order derivation algorithm (SG) (window parameter was 51, fitting times was 1), and the spectral band was 8 400-4 200 cm^-1, the number of principal components of discriminant analysis model was 18. The results of the prediction set indicated that the correct recognition rate was 100%, and there were obvious boundaries between Peucedani Radix samples from 6 different geographical origins. CONCLUSION It was showed that near-infrared spectroscopy can be used to determinate geographical origins of Peucedani Radix quickly and accurately. It provides theoretical support and practical methods for the rapid identification of the geographical origins of Peucedani Radix.