指纹图谱和多成分定量结合化学模式识别法评价不同产地杉木叶质量

Quality evaluation of leaves of Cunninghamia lanceolata from different habitats by fingerprint and multi-component quantification combined with chemical pattern recognition

目的:基于指纹图谱、多成分定量及化学模式识别法结合的方法,评价不同产地杉木叶质量,为其深入开发利用提供依据。方法:采用HPLC法测定杉木叶中穗花杉双黄酮、7-去甲基银杏双黄酮、扁柏双黄酮、银杏双黄酮、异银杏双黄酮、金松双黄酮的含量;建立10批不同产地杉木叶指纹图谱;基于指纹图谱共有峰峰面积结果,采用主成分分析(PCA)、正交偏最小二乘判别分析(OPLS-DA)、统计学分析、模式识别的化学计量学方法评价杉木叶整体质量。结果:10批杉木叶共确定14个共有峰,相似度范围为0.955~1.000,具有较好的一致性;样品中穗花杉双黄酮、7-去甲基银杏双黄酮、扁柏双黄酮、银杏双黄酮、异银杏双黄酮、金松双黄酮6个双黄酮成分的质量分数分别为2.42~5.24、0.10~0.24、1.55~3.67、0.21~0.89、0.10~0.24、0.51~2.39 mg·g^(-1);通过PCA,进一步评价不同产地间杉木叶质量差异,将10批药材分为三大类,得到4个影响杉木叶分类的主要因子,最后采用OPLS-DA筛选出色谱峰6、12、7(7-去甲基银杏双黄酮)、13(金松双黄酮)、5(穗花杉双黄酮)、9(扁柏双黄酮)、2等7个差异标志物,可用于区分不同批次杉木叶。结论:建立的杉木叶质量评价方法稳定,结果可信,结合化学模式识别可用于杉木叶药材的质量品质评价。

Objective:To base on the method of HPLC fingerprint,multi-component quantification and chemical pattern recognition,to evaluate the quality of leaves of Cunninghamia lanceolata from different producing areas and to provide basis for further development and utilization.Methods:High-performance liquid chromatography(HPLC)was used to determine the contents of amentoflavone,bilobetin,hinokiflavone,ginkgetin,isoginkgetin and sciadopitysin in the Cunninghamia lanceolata.Fingerprints of 10 batches of Cunninghamia lanceolata from different habitats were established.Based on the common peak area of the fingerprint,the overall quality of Cunninghamia lanceolata was evaluated by principal component analysis(PCA),orthogonal partial least squares discriminant analysis(OPLS-DA),statistical analysis,and pattern recognition chemometrics methods.Results:A total of 14 common peaks in 10 batches of leaves of Cunninghamia lanceolata,and the similarity ranged from 0.955 to 1.000 with good consistency.The mass fractions of six biflavones in the sample were 2.42-5.24 mg·g^(-1),0.10-0.24 mg·g^(-1),1.55-3.67 mg·g^(-1),0.21-0.89 mg·g^(-1),0.10-0.24 mg·g^(-1)and 0.51-2.39 mg·g^(-1),respectively,including amentoflavone,bilobetin,hinokiflavone,ginkgetin,isoginkgetin and sciadopitysin.According PCA,the difference in the quality of Cunninghamia lanceolata from different habitats was further evaluated.Ten batches of medicinal materials were divided into three major categories,and four main factors affecting the classification of Cunninghamia lanceolata were found.Finally,OPLS-DA screened the excellent spectral peaks 6,12,7(7-demethylated ginkgo biloba biflavone),13(kumatsu biflavone),5(Amentotaxus argotaenia biflavone),9(chamaecypress biflavone)and 2,etc,seven differential markers can be used to distinguish different batches of Cunninghamia lanceolata.Conclusion:The established method is simple to stable and reliable.Combined with chemical pattern recognition,it can be used for the quality evaluation of Cunninghamia lanceolata.