[关键词]
[摘要]
目的 采用指纹图谱与化学模式识别方法,以质量标志物(quality marker,Q-Marker)为指标,评价不同种质白芍Paeoniae lactiflora的质量。方法 采用HPLC法,以乙腈-0.1%磷酸水溶液为流动相进行梯度洗脱,柱温30 ℃,体积流量1 mL/min,检测波长230 nm;绘制40批白芍样品的指纹图谱,结合相似度分析、聚类分析(cluster analysis,HCA)、主成分分析(principal component analysis,PCA)和正交偏最小二乘法(orthogonal partial least square,OPLS-DA)等化学模式识别技术,对不同种质的白芍样品进行质量评价。结果 从质量传递与溯源,植物亲缘性及化学成分的特有性、有效性及可测性等方面对白芍Q-Marker的选择进行了分析,推测白芍中芍药苷、氧化芍药苷、苯甲酰芍药苷、芍药内酯苷、儿茶素、没食子酰芍药苷、1,2,3,4,6-五没食子酰葡萄糖和没食子酸可作为白芍的Q-Marker。以40批白芍HPLC指纹图谱标定白芍的Q-Marker,相似度在0.892~1.000;聚类分析初步区分出了不同种质的白芍,四川中江、浙江杭州和河北安国的白芍样品质量较为相近;PCA和OPLS-DA结果显示,筛选出的Q-Marker可作为不同种质白芍的特征化学成分;对Q-Marker进行含量测定,结果不同种质样品间差异较大;TOPSIS分析结果表明山西运城的白芍质量排名最高,人工培育的杂花白芍质量排名最低。结论 通过指纹图谱结合化学模式识别技术,以白芍Q-Marker为评价指标能较为全面地反映白芍的质量,可以为白芍优质种质资源的选育和育种提供参考。
[Key word]
[Abstract]
Objective To evaluate the quality of different germplasms of Baishao (Paeoniae Radix Alba) taking quality marker (Q-Marker) as indicators by using fingerprint and chemical pattern recognition methods. Method Using the HPLC method, acetonitrile-0.1% phosphoric acid aqueous solution was used as mobile phase for gradient elution, column temperature 30 oC, volume flow rate 1 mL/min, detection wavelength 230 nm. The fingerprints of 40 batches of Paeoniae Radix Alba were drawn, combined with chemical pattern recognition techniques such as similarity analysis, cluster analysis (HCA), principal component analysis (PCA), and orthogonal partial least square (OPLS-DA). The quality of different germplasm samples of Paeoniae Radix Alba was evaluated. Results The selection of Q-Marker of Paeoniae Radix Alba was analyzed from the aspects of quality transfer and traceability, plant relationship, and chemical composition specificity, effectiveness and detecability. It was suggested that paeoniflorin, oxypaeoniflorin, benzoyl paeoniflorin, albiflorin, catechin, gallic paeoniflorin, 1,2,3,4, 6-penogalylglucose and gallic acid in paeony could be used as Q-Marker of Paeoniae Radix Alba. The HPLC fingerprints of 40 batches of Paeoniae Radix Alba were used to calibrate the Q-Marker of Paeoniae Radix Alba, and the similarity was between 0.892 and 1. Cluster analysis preliminarily distinguished the Paeoniae Radix Alba of various germplasms. The quality of samples from Zhongjiang in Sichuan, Hangzhou in Zhejiang, and Anguo in Hebei was similar. The results of PCA and OPLS-DA showed that the selected Q-Marker could be used as the characteristic chemical constituents of different germplasm Paeoniae Radix Alba. The content of Q-Marker varied greatly among different germplasm samples. The results of TOPSIS analysis showed that the quality of Paeoniae Radix Alba in Yuncheng, Shanxi was the highest, and the quality of Paeoniae Radix Alba in Zahua was the lowest. Conclusion Through fingerprint combined with chemical pattern recognition technology, taking the Q-Marker of Paeoniae Radix Alba as an evaluation index can comprehensively reflect the quality of Paeoniae Radix Alba, which can provide a reference for the breeding and breeding high-quality germplasm resources of Paeoniae Radix Alba.
[中图分类号]
R286
[基金项目]
国家重点研发计划项目(2017YFC1701600);国家重点研发计划项目(2017YFC1701602);2021年安徽省重点研发项目(202104h04020029);亳州市科技重大专项(BZSKXJSJ2020-59)