Chip-based nanoflow high performance liquid chromatography coupled to mass spectrometry for profiling of soybean flavonoids
In this work a chip‐based nano HPLC coupled MS (HPLC‐chip/MS) method with a simple sample preparation procedure was developed for the flavonoid profiling of soybean. The analytical properties of the method including the linearity (R2, 0.992–0.995), reproducibility (RSD, 1.50–7.66%), intraday precisi...
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Published in | Electrophoresis Vol. 33; no. 15; pp. 2399 - 2406 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
Germany
Blackwell Publishing Ltd
01.08.2012
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Subjects | |
Online Access | Get full text |
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Summary: | In this work a chip‐based nano HPLC coupled MS (HPLC‐chip/MS) method with a simple sample preparation procedure was developed for the flavonoid profiling of soybean. The analytical properties of the method including the linearity (R2, 0.992–0.995), reproducibility (RSD, 1.50–7.66%), intraday precision (RSD, 1.41–5.14%) and interday precision (RSD, 2.76–16.90%) were satisfactory. Compared with the conventional HPLC/MS method, a fast extraction and analysis procedure was applied and more flavonoids were detected in a single run. Additionally, 13 flavonoids in soybean seed were identified for the first time. The method was then applied to the profiling of six varieties of soybean sowed at the same place. A clear discrimination was observed among different cultivars, three isoflavones, accounting for nearly 80% of total flavonoid contents, were found increased in the spring soybeans compared with the summer cultivars. |
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Bibliography: | ArticleID:ELPS4308 National Grand Project of Science and Technology - No. 2011ZX08012-002 National Natural Science Foundation of China - No. 20835006; No. 21075122 ark:/67375/WNG-T3NNDFR1-N creative research group project - No. 21021004 istex:0E22AED21A733F49682016FE2516A971E135C54B Additional corresponding author: Dr. Chunxia Zhao E‐mail See the article online to view Figs. 1 and 3 in colour. zhaocx@dicp.ac.cn Colour Online ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0173-0835 1522-2683 |
DOI: | 10.1002/elps.201100581 |