UPLC指纹图谱结合化学计量学的多产地藜麦质量控制

doi:10.7506/spkx1002-6630-201720042

食品科学 ›› 2017, Vol. 38 ›› Issue (20): 286-291.doi: 10.7506/spkx1002-6630-201720042

UPLC指纹图谱结合化学计量学的多产地藜麦质量控制

曹亚楠，白雪，赵钢，邹亮，胡一晨

（1.西华大学食品与生物工程学院，四川?成都 610039；2.成都大学农业部杂粮加工重点实验室，四川?成都 610106；3.成都大学医学院，四川?成都 610106）

出版日期:2017-10-25 发布日期:2017-09-29
基金资助:
四川省教育厅项目（17ZB0113）；成都大学校青年基金项目（2080516032）

Application of UPLC Fingerprint Coupled with Chemometry for Quality Control of Quinoa from Different Geographical Origins

CAO Yanan, BAI Xue, ZHAO Gang, ZOU Liang, HU Yichen

(1. College of Food and Bioengineering, Xihua University, Chengdu 610039, China;2. Key Laboratory of Coarse Cereal Processing, Ministry of Agriculture, Chengdu University, Chengdu 610106, China; 3. College of Medicine, Chengdu University, Chengdu 610106, China)

Online:2017-10-25 Published:2017-09-29

摘要/Abstract

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。

关键词: 藜麦, 超高效液相色谱法, 指纹图谱

Abstract: In this research, a method for the quality control of 30 batches of quinoa from many different areas of the world was established by ultra-performance liquid chromatography (UPLC). UPLC fingerprints were established after evaluation of figures of merit. The similarity was analyzed by similarity evaluation software. The relationship between geographical origin and quality was analyzed by cluster analysis, principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA) and other chemometric methods. The results showed that there were 12 peaks common to 30 batches of quinoa, and the similarity among samples was greater than 0.7. Using the chemometric methods, the quinoa samples were classified into four categories according to their geographical orgins. The PCA and pattern recognition analysis indicated that the quality difference was mainly related to three compounds. Therefore, UPLC fingerprinting and chemical pattern recognition can provide detailed references for the quality control of quinoa.

Key words: quinoa, ultra performance liquid chromatography (UPLC), fingerprinting

中图分类号:

TS201.1

曹亚楠，白雪，赵钢，邹亮，胡一晨. UPLC指纹图谱结合化学计量学的多产地藜麦质量控制[J]. 食品科学, 2017, 38(20): 286-291.

CAO Yanan, BAI Xue, ZHAO Gang, ZOU Liang, HU Yichen. Application of UPLC Fingerprint Coupled with Chemometry for Quality Control of Quinoa from Different Geographical Origins[J]. FOOD SCIENCE, 2017, 38(20): 286-291.

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UPLC指纹图谱结合化学计量学的多产地藜麦质量控制

Application of UPLC Fingerprint Coupled with Chemometry for Quality Control of Quinoa from Different Geographical Origins

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