主成分分析和聚类分析法研究刺玫果黄酮类成分HPLC指纹图谱

发布时间：2018-06-29 06:50

本文选题：刺玫果 + 黄刺玫　；参考：《食品工业科技》2017年24期

【摘要】：采用高效液相色谱法研究了30批不同品种、不同产地的刺玫果黄酮类成分指纹图谱,并进行主成分分析和聚类分析。采用Athena-C18色谱柱,流动相乙腈-0.1%(v/v)磷酸水溶液,梯度洗脱,流速1.0 mL/min,检测波长360 nm,建立刺玫果指纹图谱。结果表明,30批刺玫果相似度在0.772~0.995之间,其中22批黄刺玫果相似度均大于0.958,相对保留时间RSD小于1.0%,通过共有模式筛选出15个共有特征峰,其中指认3个共有峰,分别为芦丁、金丝桃苷和槲皮素;方法的精密度、重复性和稳定性的峰面积RSD分别小于2.9%、4.1%和4.9%,芦丁、金丝桃苷和槲皮素的加样回收率分别为97.3%±1.2%,96.2%±1.9%和98.2%±1.1%,RSD分别为3.2%、2.4%和2.6%,符合指纹图谱的检测要求;运用SPSS 22.0软件进行主成分分析和聚类分析,结果主成分分析将样品分为2大类,2个主成分的累积方差贡献为80.3%,聚类分析分为3类,两种分类方法与相似度评价结果一致。该方法具有良好的精密度、重复性和稳定性,结合相似度评价、主成分分析和聚类分析3种方法,可以快速鉴别不同种类的刺玫果,并为有效控制刺玫果的质量提供方法。
[Abstract]:The fingerprints of flavonoids from different varieties and different habitats of Rosa davidifolia were studied by HPLC, and the principal component analysis and cluster analysis were carried out. Using Athena-C18 column, mobile phase acetonitrile-0.1% (v / v) phosphoric acid aqueous solution, gradient elution, flow rate 1.0 mL / min, detection wavelength 360 nm, the fingerprint of Rosa davidiflora was established. The results showed that the similarity of 30 batches of Rosa davidifolia was between 0.772 and 0.995, of which 22 were more than 0.958, and the relative retention time (RSD) was less than 1.0. Fifteen common characteristic peaks were selected by common mode, of which 3 were identified as rutin. The RSD of precision, repeatability and stability of the method were less than 2.9% and 4.9%, the recoveries of rutin, hyperin and quercetin were 97.3% 卤1.2% 卤1.9% and 98.2% 卤1.1%, respectively. SPSS22.0 software was used to carry out principal component analysis and cluster analysis. The results showed that the samples were divided into two categories by principal component analysis. The cumulative variance contribution of the two principal components was 80.3. The cluster analysis was divided into three categories, and the two classification methods were consistent with the similarity evaluation results. This method has good precision, reproducibility and stability. Combined with similarity evaluation, principal component analysis and cluster analysis, it can quickly identify different species of Rosa davurica and provide an effective method to control the quality of the fruit.
【作者单位】：山西省医药与生命科学研究院;
【基金】：山西省青年基金项目(2015021190) 山西省科技攻关项目(20150311022-1)
【分类号】：O657.72;TS255.7

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