Hydrophilic interaction ultra-performance liquid chromatography coupled with triple-quadrupole tandem mass spectrometry for highly rapid and sensitive analysis of underivatized amino acids in functional foods
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- 作者：Guisheng Zhou (1)
Hanqing Pang (1)
Yuping Tang (1)
Xin Yao (1)
Xuan Mo (1)
Shaoqing Zhu (1)
Sheng Guo (1)
Dawei Qian (1)
Yefei Qian (1)
Shulan Su (1)
Li Zhang (1) (2)
Chun Jin (3)
Yong Qin (3)
Jin-ao Duan (1) - 关键词：Underivatized amino acids analysis ; HILIC ; UPLC鈥揟Q ; MS/MS ; PCA ; Functional foods ; Ginkgo seed
- 刊名：Amino Acids
- 出版年：2013
- 出版时间：May 2013
- 年：2013
- 卷：44
- 期：5
- 页码：1293-1305
- 全文大小：493KB
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Hanqing Pang (1)
Yuping Tang (1)
Xin Yao (1)
Xuan Mo (1)
Shaoqing Zhu (1)
Sheng Guo (1)
Dawei Qian (1)
Yefei Qian (1)
Shulan Su (1)
Li Zhang (1) (2)
Chun Jin (3)
Yong Qin (3)
Jin-ao Duan (1)
1. Jiangsu Key Laboratory for High Technology of TCM formulae Research, Nanjing University of Chinese Medicine, Nanjing, 210046, China
2. Department of Analysis of Chinese Medicine, Nanjing University of Chinese Medicine, Nanjing, 210046, China
3. Jiangsu Shenlong Pharmaceutical Co., Ltd, Yancheng, 224200, China - ISSN：1438-2199
文摘
This work presented a new analytical methodology based on hydrophilic interaction ultra-performance liquid chromatography coupled with triple-quadrupole tandem mass spectrometry in multiple-reaction monitoring mode for analysis of 24 underivatized free amino acids (FAAs) in functional foods. The proposed method was first reported and validated by assessing the matrix effects, linearity, limit of detections and limit of quantifications, precision, repeatability, stability and recovery of all target compounds, and it was used to determine the nutritional substances of FAAs in ginkgo seeds and further elucidate the nutritional value of this functional food. The result showed that ginkgo seed turned out to be a good source of FAAs with high levels of several essential FAAs and to have a good nutritional value. Furthermore, the principal component analysis was performed to classify the ginkgo seed samples on the basis of 24 FAAs. As a result, the samples could be mainly clustered into three groups, which were similar to areas classification. Overall, the presented method would be useful for the investigation of amino acids in edible plants and agricultural products.