返回 
加入收藏
青皮药材的HPLC指纹图谱建立及聚类分析和主成分分析
x
请在关注微信后，向客服人员索取文件
| 篇名： | 青皮药材的HPLC指纹图谱建立及聚类分析和主成分分析 |
| TITLE： | |
| 摘要： | 目的：建立青皮药材的高效液相色谱（HPLC）指纹图谱，并进行聚类分析和主成分分析。方法：采用HPLC法。色谱柱为XSelect® HSS T3-C18，流动相为乙腈-0.5％醋酸溶液（梯度洗脱），流速为1.0 mL/min，检测波长为360 nm，柱温为25 ℃，进样量为10 μL。以橙皮苷峰为参照，绘制10批药材样品的HPLC图谱，采用《中药色谱指纹图谱相似度评价系统（2012版）》进行相似度评价，确定共有峰，并采用SPSS 17.0软件进行聚类分析和主成分分析。结果：10批药材样品的HPLC指纹图谱有11个共有峰，相似度为0.919～1.000，表明10批药材样品的化学成分一致性较好，均含有11个成分，但各成分含量存在差异。欧氏距离为20时，10批药材样品可聚为2类，S4为一类，其余聚为一类；欧氏距离为5时，后一类又可聚为2类，S1、S10聚为一类，S2、S3、S5～S9聚为一类。经主成分分析，2个主成分因子的累积方差贡献率为92.797％，以S7药材样品的主成分因子综合得分最高、整体质量最好。结论：所建HPLC指纹图谱及聚类分析和主成分分析结果可为青皮药材的质量控制提供参考。 |
| ABSTRACT： | OBJECTIVE： To establish HPLC fingerprint of Citrus reticulata， and to conduct cluster analysis and principle component analysis. METHODS： HPLC method was adopted. The determination was performed on XSelect® HSS T3-C18 column with mobile phase consisted of acetonitrile-0.5％ acetic acid solution （gradient elution） at the flow rate of 1.0 mL/min. The detection wavelength was set at 360 nm， and the column temperature was 25 ℃. The sample size was 10 μL. With hesperidin as reference peak， HPLC fingerprints of 10 batches of C. reticulata were determined. The similarity 10 batches of samples was evaluated by TCM Chromatographic Fingerprint Evaluation System （2012 edition） to determine the common peak. Cluster analysis and principal component analysis were performed by using SPSS 17.0 statistical software. RESULTS： There were 11 common peaks in the HPLC fingerprints of 10 batches of medicinal materials， and the similarity was 0.919-1.000， which indicated that in 10 batches of medicinal materials， the chemical composition was consistent， and there were 11 components in 10 batches of samples， but the contents of these components were different. When euclidean distance was equal to 20， 10 batches of sample were divided into two categories； S4 was included in the first category， and others were included in the second category. When euclidean distance was equal to 5， the second category can be divided into two sub-categories； one sub-category was S1， S10； one sub-category was S2， S3， S5， S6， S7， S8， S9. Through the principal component analysis， the cumulative contribution rate of two main component factors was 92.797％， and comprehensive score of S7 was the highest with the best quality. CONCLUSIONS： Established fingerprints， cluster analysis and principal component analysis results can provide reference for the quality control of C. reticulata. |
| 期刊： | 2018年第29卷第24期 |
| 作者： | 靳贝贝，裴香萍，梁惠珍 |
| AUTHORS： | JIN Beibei，PEI Xiangping，LIANG Huizhen |
| 关键字： | 青皮；高效液相色谱法；指纹图谱；聚类分析；主成分分析 |
| KEYWORDS： | Citrus reticulata； HPLC； Fingerprint； Cluster analysis； Principal component analysis |
| 阅读数： | 583 次 |
| 本月下载数： | 9 次 |
* 注：未经本站明确许可，任何网站不得非法盗链资源下载连接及抄袭本站原创内容资源!在此感谢您的支持与合作！
