College of Pharmaceutical Engineering of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
Haihe Laboratory of Modern Chinese Medicine, Tianjin 301617, China.
J Agric Food Chem. 2024 Apr 10;72(14):7707-7715. doi: 10.1021/acs.jafc.3c08812. Epub 2024 Mar 26.
In this study, near-infrared (NIR) spectroscopy and high-performance liquid chromatography (HPLC) combined with chemometrics tools were applied for quick discrimination and quantitative analysis of different varieties and origins of samples. Based on NIR data, orthogonal partial least squares discriminant analysis (OPLS-DA) and K-nearest neighbor (KNN) models achieved greater than 90% discriminant accuracy of the three species and two origins of . Moreover, the contents of three active ingredients (atractyloxin, atractylone, and β-eudesmol) in were simultaneously determined by HPLC. There are significant differences in the content of the three components in the samples of from different varieties and origins. Then, partial least squares regression (PLSR) models for the prediction of atractyloxin, atractylone, and β-eudesmol content were successfully established. The complete spectra gave rise to good predictions of atractyloxin, atractylone, and β-eudesmol content with R values of 0.9642, 0.9588, and 0.9812, respectively. Based on the results of this present research, it can be concluded that NIR is a great nondestructive alternative to be applied as a rapid classification system by the drug industry.
在这项研究中，近红外（NIR）光谱和高效液相色谱（HPLC）结合化学计量学工具被应用于快速区分和定量分析不同品种和产地的样品。基于 NIR 数据，正交偏最小二乘判别分析（OPLS-DA）和 K-最近邻（KNN）模型实现了对三种物种和两个产地的样品的大于 90%的判别准确率。此外，HPLC 还同时测定了三种活性成分（苍术素、苍术酮和β-桉叶醇）在中的含量。不同品种和产地的样品中三种成分的含量存在显著差异。然后，成功建立了用于预测苍术素、苍术酮和β-桉叶醇含量的偏最小二乘回归（PLSR）模型。完整的 NIR 光谱对苍术素、苍术酮和β-桉叶醇含量的预测具有很好的效果，其 R 值分别为 0.9642、0.9588 和 0.9812。基于本研究的结果，可以得出结论，NIR 是一种很好的非破坏性替代方法，可以被应用于药物行业的快速分类系统。
