UPLC指纹图谱结合化学计量学的多产地藜麦质量控制

发布时间：2018-06-26 07:46

本文选题：藜麦 + 超高效液相色谱法　；参考：《食品科学》2017年20期

【摘要】：采用超高效液相色谱(ultra performance liquid chromatography,UPLC)对来自世界范围多地区的30批次藜麦进行质量控制研究,通过方法学考察建立不同产地藜麦样品UPLC指纹图谱,并分析其相似度。借助聚类分析、主成分分析、偏最小二乘判别分析等化学计量学方法对其产地和质量的相关性进行分析。结果表明,30批藜麦对照图谱存在12个共有峰,样品相似度大于0.7;通过化学计量法,藜麦样品按产地被很好地分为4类,主成分分析和模式识别分析结果提示其质量差异主要与3个化合物相关。UPLC指纹图谱的构建和化学模式的识别为藜麦质量控制提供更全面的参考,为有效控制藜麦质量提供参考依据。
[Abstract]:The quality control of 30 lots of quinoa samples from many regions in the world was studied by using (ultra performance liquid chromatography (ultra performance liquid. The fingerprints of quinoa samples from different producing areas were established by methodological investigation, and their similarity was analyzed. By means of cluster analysis, principal component analysis, partial least squares discriminant analysis and other chemometrics methods, the correlation between its origin and quality was analyzed. The results showed that there were 12 common peaks in the control atlas of 30 lots of quinoa, and the similarity of the samples was greater than 0.7. By chemometrics, the samples of quinoa were well classified into 4 groups according to the area of production. The results of principal component analysis and pattern recognition analysis indicated that the quality differences were mainly related to three compounds. The construction of fingerprints and the recognition of chemical patterns provided a more comprehensive reference for the quality control of quinoa. To provide a reference for the quality control of quinoa.
【作者单位】：西华大学食品与生物工程学院;成都大学农业部杂粮加工重点实验室;成都大学医学院;
【基金】：四川省教育厅项目(17ZB0113) 成都大学校青年基金项目(2080516032)
【分类号】：O657.72;TS210.7

【相似文献】