Chan Chi-On, Chu Ching-Ching, Mok Daniel Kam-Wah, Chau Foo-Tim
State Key Laboratory of Chinese Medicine and Molecular Pharmacology, Shenzhen, PR China.
Anal Chim Acta. 2007 Jun 5;592(2):121-31. doi: 10.1016/j.aca.2007.04.016. Epub 2007 Apr 19.
This paper developed a rapid method using near infrared spectroscopy (NIRS) to differentiate two species of cortex phellodendri (CP), cortex phellodendri chinensis (PCS) and cortex phellodendri amurensis (PAR), and to predict quantitatively the content of berberine and total alkaloid content in all cortex phellodendri samples. Three alkaloids, berberine, jatrorrhizine and palmatine were analyzed simultaneously with a Thermo ODS Hypersil column by gradient elution with a new mobile phase under high-performance liquid chromatography-diode array detection (HPLC-DAD). Berberine content determined by HPLC-DAD was exploited as a critical parameter for successful discrimination between them. Multiplicative scatter correction (MSC), second derivative and Savitsky-Golay (S.G.) were utilized together to correct the scattering effect and eliminate the baseline shift in all near infrared diffuse reflectance spectra as well as to enhance spectral features in order to give a better correlation with the results obtained by HPLC-DAD. With the use of principal component analysis (PCA), samples datasets were separated successfully into two different clusters corresponding to two species. Furthermore, a partial least squares (PLS) regression method was built on the correlation model. The results showed that the correlation coefficients of the prediction models were R=0.996 for the berberine and R=0.994 for total alkaloid content. The influences of water absorption bands present in the NIR spectra on the models were also investigated in order to explore the practicability of NIRS in routine use. The outcome showed that NIRS possibly acts as routine screening in the quality control of Chinese herbal medicine.
本文开发了一种利用近红外光谱（NIRS）区分两种黄柏（CP）的快速方法，即川黄柏（PCS）和关黄柏（PAR），并定量预测所有黄柏样品中黄连素和总生物碱的含量。采用新型流动相在高效液相色谱 - 二极管阵列检测（HPLC - DAD）下，使用Thermo ODS Hypersil柱通过梯度洗脱同时分析三种生物碱，即黄连素、药根碱和巴马汀。将HPLC - DAD测定的黄连素含量作为成功区分它们的关键参数。同时使用多元散射校正（MSC）、二阶导数和Savitsky - Golay（S.G.）方法来校正散射效应，消除所有近红外漫反射光谱中的基线漂移，并增强光谱特征，以便与HPLC - DAD获得的结果有更好的相关性。通过主成分分析（PCA），样品数据集成功地分为对应于两个物种的两个不同聚类。此外，基于相关模型建立了偏最小二乘（PLS）回归方法。结果表明，黄连素预测模型的相关系数R = 0.996，总生物碱含量预测模型的相关系数R = 0.994。还研究了近红外光谱中存在的吸水带对模型的影响，以探讨近红外光谱在常规使用中的实用性。结果表明，近红外光谱可能作为中药材质量控制中的常规筛选方法。
