基于傅里叶变换红外光谱技术与多元统计分析相结合的中药葛根快速定量研究

Rapid quantitative study of Pueraria lobata in traditional Chinese medicine based on Fourier transform infrared spectroscopy combined with multivariate statistical analysis

利用傅里叶变换红外光谱技术结合多元统计分析,建立中药葛根中有效物质快速检测的质量评价体系,以期为葛根的快速、精准含量测定提供新方法,推动其质量控制,缓解当前野葛的品质危机。分别利用烘干法、HPLC法和紫外分光光度法测定葛根中的水分、葛根素、总黄酮、葛根多糖的含量,并对其中红外光谱进行聚类分析和主成分分析,后运用化学计量学方法,建立关于目标组分的快速鉴别的红外预测模型。发现葛根各产地含量测定结果表明其含量差异明显,其中陕西咸阳产地葛根素、以及总黄酮含量均最多,广西南宁葛根多糖含量最高。聚类分析显示各产地葛根中红外光谱具有相似性和差异性,可作为产地鉴别的依据。主成分分析表明前三个主成分的累计方差贡献率为88.32%,湖北恩施产地葛根样品的综合得分最高。红外定量模型结果表明水分以PLS+CONSTANT+2ndDer+SG模型最优,葛根素以SmLR+MSC+2ndDer+ND模型最优,葛根总黄酮以PLS+SNV+2ndDer+SG模型最优,葛根多糖以PLS+MSC+2ndDer+SG模型最优,其红外预测模型相关系数均大于0.8,表明其预测模型精密度高,稳定性强。结论:通过傅里叶变换光谱技术建立的葛根有效成分的定量模型可以实现对未知葛根有效成分的含量测定,且该法方便快捷,定量预测模型能够准确预测目标组分的含量,为葛根有效成分的快速、无损测定提供了新的方法依据。

To establish a quality evaluation system for the rapid detection of effective substances in Pueraria Mirifica,a traditional Chinese medicine,by using Fourier transform infrared spectroscopy,with a view to providing a new method for the rapid and accu-rate content determination of P.lobata,to promote its quality control,and to alleviate the current quality crisis of P.lobata.The con-tents of water,puerarin,total flavonoids and puerarin polysaccharides in P.lobata were determined by drying,HPLC and UV spec-trophotometry,respectively,and the infrared spectra of which were subjected to cluster analysis and principal component analysis,and then the infrared prediction model about the rapid identification of the target components was established by applying chemo-metrics methods.It was found that the determination of the content of P.lobata from various origins showed obvious differences in content,among which the content of puerarin,as well as total flavonoids was the highest in Xianyang,Shaanxi,and the content of P.lobata polysaccharides was the highest in Nanning,Guangxi.Cluster analysis showed that the mid-infrared spectra of P.lobata from different origins were similar and dfferent,which could be used as the basis for origin identification.The principal component analy-sis showed that the cumulative variance contribution of the first three principal components was 88.32%,and the composite score of P.lobata samples from Enshi,Hubei was the highest.The results of the infrared quantitative models showed that the PLS+CON-STANT+2nd Der+SG model was the best model for moisture,the SmLR+MSC+2nd Der+ND model for P.lobata,the PLS+SNV+2nd Der+SG model for P.lobata total flavonoids,the PLS+MSC+2nd Der+SG model for P.lobata polysaccharides,and the correla-tion coefficients were all greater than 0.8,and the predictive models were all more than 0.8,and the correlation coefficient of the first three principal components was greater than O.8.The correlation coefficients of the IR prediction models were all greater than O.8,indicating that the prediction models were highly precise and stable.The quantitative model of effective components of P.lobata established by Fourier transform spectroscopy can achieve the determination of the content of unknown P.lobata active components,and the method is convenient and fast,and the quantitative prediction model can accurately predict the content of the target compo-nents,which provides a new methodological basis for the rapid and nondestructive determination of P.lobata active components,en-riches the quality evaluation system of P.lobata.