Zhu Weihao, Hong Hao, Hong Zhihui, Kang Xianjie, Du Weifeng, Ge Weihong, Li Changyu
College of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou 311402, China.
Research Center of TCM Processing Technology, Zhejiang Chinese Medical University, Hangzhou 311401, China.
J Anal Methods Chem. 2021 Jul 22;2021:1936057. doi: 10.1155/2021/1936057. eCollection 2021.
In order to identify the quality of crude and processed Rhizoma decoction pieces, the research established a simple, fast, reliable, and validated near-infrared qualitative and quantitative model combined with chemometrics. 51 batches of crude and 40 batches of processed Rhizoma from the Zhejiang and Jiangsu provinces of China were collected and analyzed. Crude and processed Rhizoma samples were crushed to obtain NIR spectra. The content of seven alkaloids in crude and processed Rhizoma was determined by high-performance liquid chromatography (HPLC). Pretreatment methods were screened such as normalization methods, offset filtering methods, and smoothing. Combined with partial least squares-discriminant analysis (PLS-DA) and partial least squares (PLS), the qualitative and quantitative models of crude and processed Rhizoma were established, and the correlation coefficient ( ), root mean square error of calibration (RMSEC), and root mean square error of prediction (RMSEP) were used as evaluation indexes. Tetrahydropalmatine was used as an example for screening pretreatment methods; the results showed that MSC combined with the second derivative and no smoothing and the model with the wavelength range of 10000-5000 cm had the best predictive ability and applied to all seven alkaloid components. Among them, the correlation coefficients were all higher than 0.99, and RMSEC and RMSEP were all less than 1%. The qualitative and quantitative model of the seven alkaloids in Rhizoma can effectively identify the crude and processed Rhizoma and determine the content of the seven alkaloids. By studying the NIR qualitative and quantitative models of crude and processed Rhizoma, we can achieve rapid discrimination and quantitative prediction of crude and processed Rhizoma. These methods can greatly improve the efficiency of traditional Chinese medicine analysis and provide a strong scientific basis for the quality identification and control of traditional Chinese medicine.
为鉴别生熟黄连饮片的质量，本研究结合化学计量学建立了一种简单、快速、可靠且经过验证的近红外定性定量模型。收集并分析了来自中国浙江和江苏的51批次生黄连和40批次熟黄连。将生熟黄连样品粉碎以获得近红外光谱。采用高效液相色谱法（HPLC）测定生熟黄连中7种生物碱的含量。筛选了诸如归一化方法、偏移滤波方法和平滑等预处理方法。结合偏最小二乘判别分析（PLS - DA）和偏最小二乘法（PLS），建立了生熟黄连的定性定量模型，并以相关系数（ ）、校正均方根误差（RMSEC）和预测均方根误差（RMSEP）作为评价指标。以延胡索乙素为例筛选预处理方法；结果表明，多元散射校正（MSC）结合二阶导数且不进行平滑处理以及波长范围为10000 - 5000 cm的模型具有最佳预测能力，并应用于所有7种生物碱成分。其中，相关系数均高于0.99，RMSEC和RMSEP均小于1%。黄连中7种生物碱的定性定量模型能够有效鉴别生熟黄连并测定7种生物碱的含量。通过研究生熟黄连的近红外定性定量模型，可实现生熟黄连的快速判别和定量预测。这些方法可大大提高中药分析效率，为中药质量鉴定与控制提供有力的科学依据。
