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作 者:屠钰 李无双 朗文成 马琳 武国华 TU Yu;LI Wu-Shuang;LANG Wen-Cheng;MA Lin;WU Guo-Hua(School of Environmental and Chemical Engineering,Jiangsu University of Science and Technology,Zhenjiang 212018,China;Laboratory of Risk Assessment for Sericultural Products and Edible Insects,College of Biotechnology,Jiangsu University of Science and Technology,Zhenjiang 212018,China)
机构地区:[1]江苏科技大学,环境与化学工程学院,镇江212018 [2]江苏科技大学生物技术学院,农业农村部蚕桑产品及食用昆虫质量安全风险评估实验室,镇江212018
出 处:《分析化学》2020年第9期1252-1259,共8页Chinese Journal of Analytical Chemistry
基 金:江苏省特聘教授专项基金项目(No.苏教师[2015]17)资助。
摘 要:对茶叶中γ-氨基丁酸(γ-Aminobutyric acid,GABA)等多种功能性活性物质的快速检测,有利于茶叶资源的开发和有效利用。本研究建立了一种利用实时直接分析(DART)离子源与三重四极杆串联质谱联用快速高效定量分析茶叶中GABA含量的方法,测定了10种茶叶中GABA的含量。结果表明,不同茶叶中GABA的含量存在较大差异,其中九香翠芽中GABA含量最高,达到227.2μg/g;其次是信阳毛尖,含量为161.2μg/g;日照绿茶的GABA含量最低,为75.6μg/g。本方法测得的结果与2,4-二硝基氟苯柱前衍生高效液相色谱(HPLC)检测法有较好的一致性。本方法简便、高效,为快速筛选具有高含量GABA的茶叶品种提供了一种简单有效的方法。Tea contains a variety of functional active substances such asγ-aminobutyric acid(GABA),which plays a good role in health care.Rapid identification of active components such asγ-aminobutyric acid in tea is conducive to improving the effective utilization of tea resources.In this work,qualitative and quantitative analysis ofγ-aminobutyric acid in tea by direct analysis in real time(DART)ionization source coupled with triple quadrupole mass spectrometry was developed.The content ofγ-aminobutyric acid in 10 kinds of tea samples was determined by this method.The results showed that the content of GABA in different tea samples were different,among which Jiuxiang green bud tea had the highest GABA content(227.2μg/g),followed by Xinyang Maojian tea(161.2μg/g),and Rizhao green tea had the lowest GABA content(75.6μg/g).The test results are in good agreement with the results of the 2,4-dinitrofluorobenzene pre-column HPLC method.This method is simple and efficient,which can provide an effective method for rapidly screening tea varieties with high content of GABA.DART-MS method also has broad application in the fields of food active substance analysis,environmental organic pollutants,early screening of metabolic diseases and other fields.
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