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目的:建立一种分析药用菊花中14个成分的HPLC方法,并结合化学计量学方法对不同产地菊花的化学成分进行比较分析。方法:样品以70%甲醇超声提取,采用TC-C_(18)色谱柱(250 mm×4.6 mm,5μm),以乙腈-0.3%磷酸水溶液为流动相,梯度洗脱,流速1.0 mL·min~(-1),检测波长348 nm,柱温30℃;应用高效液相色谱法同时测定菊花中14个化合物(绿原酸、木犀草苷、3,5-O-二咖啡酰奎宁酸、4,5-O-二咖啡酰奎宁酸、1,3-O-二咖啡酰奎宁酸、木犀草素、木犀草素-7-O-β-D-葡萄糖醛酸苷、槲皮苷、芹菜素、黄芩苷、芦丁、咖啡酸、蒙花苷、香叶木素)的含量,并建立指纹图谱,运用主成分分析与聚类分析对指纹图谱进行模式识别研究。结果:14个化合物的线性范围为0.01~150.0μg·mL~(-1),线性相关系数均大于0.999,3个浓度水平加样回收率为91.6%~100%,RSD为0.40%~3.36%。28批样品中绿原酸、木犀草苷、3,5-O-二咖啡酰奎宁酸含量分别为2.38~7.27、1.98~32.66、3.66~14.01 mg·g~(-1)。聚类分析结果表明28批样品可分为两大类(昆仑雪菊与其他品种菊花),或依据不同品种细分为8小类;主成分分析(PCA)结果显示不同来源的菊花在化学成分的组分和含量上存在不同程度的差异,同时验证了上述分类结果。结论:通过对菊花样品的指纹图谱进行聚类分析和主成分分析,为菊花药材的化学计量学及其质量评价提供参考。结果表明:不同产地菊花中化学成分及含量的差异不仅与菊花品种有关,还与产地、成熟度、储存及加工条件有关。
OBJECTIVE: To establish a HPLC method for the analysis of 14 components in medicinal chrysanthemum, and to compare the chemical components of chrysanthemum from different areas by using chemometric method. Methods: The sample was extracted with 70% methanol by ultrasonic wave and eluted with acetonitrile-0.3% phosphoric acid aqueous solution at a flow rate of 1.0 mL · min-1 using a TC-C 18 column (250 mm × 4.6 mm, (-1), the detection wavelength was 348 nm, and the column temperature was 30 ℃. Simultaneous determination of 14 compounds in chrysanthemum (chlorogenic acid, luteolin, 3,5-O-dicaffeoylquinic acid, 4,5-O-dicaffeoylquinic acid, 1,3-O-dicaffeoylquinic acid, luteolin, luteolin-7-O-β-D-glucuronide, quercetin , Apigenin, baicalin, rutin, caffeic acid, mandarin glycosides, and safranin), and the fingerprints of the fingerprints were established. The principal component analysis and cluster analysis were used to identify the fingerprints. Results: The linear range of the 14 compounds ranged from 0.01 to 150.0 μg · mL -1, and the linear correlation coefficients were all above 0.999. The recoveries of the three concentrations ranged from 91.6% to 100% with RSDs of 0.40% -3.36% . The contents of chlorogenic acid, luteolin and 3,5-O-dicaffeoylquinic acid in 28 batches of samples were 2.38 ~ 7.27, 1.98 ~ 32.66 and 3.66 ~ 14.01 mg · g -1, respectively. Cluster analysis showed that 28 batches of samples could be divided into two categories (Kunlun Xueju and other varieties of chrysanthemums) or subdivided into 8 sub-categories according to different varieties. Principal component analysis (PCA) results showed that the chemical constituents The differences of the components and contents between the two groups were also observed. The results of the above classification were also validated. Conclusion: The fingerprint of chrysanthemum samples were analyzed by cluster analysis and principal component analysis to provide references for the chemometrics and quality evaluation of chrysanthemum medicinal materials. The results showed that the differences of chemical composition and content in chrysanthemum from different areas were not only related to the varieties of chrysanthemum, but also to the origin, maturity, storage and processing conditions.