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Determination of 18 Kinds of Amino Acids in Fresh Tea Leaves by HPLC Coupled with Pre-column Derivatization

机译:色谱-柱前衍生-高效液相色谱法测定鲜茶叶中的18种氨基酸

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摘要

A rapid and accurate quantitative method of high performance liquid chromatography( HPLC) with fluorescence detector has been developed for the analysis of 18 kinds of amino acids in fresh tea leaves. The samples were minced and mixed,and extracted with ultra pure water at 90℃ for 20 min. The 6-aminoquinolyl N-hydroxy-succinimidyl carbamate( AQC) was used as pre-column derivatization reagent. Gradient HPLC separation was performed on a C18 column( Symmetry C18,3. 9 mm × 15 cm,4 μm). Good linearity between concentrations and peak areas was achieved in the concentration range of 5. 0-250 μmol/L for 18 kinds of amino acids. The method was validated by the analysis of five replicates. The 18 kinds of amino acid standards were spiked in fresh tea leaf samples and the average recovery rate was 86. 25%-109. 05% with relative standard deviations( n = 5) ranging from 6. 03% to 10. 56%. The limit of detection( LOD) for the analytes was0. 05-1. 27 μmol/L. The method was successfully applied to the analysis of the 18 kinds of amino acids in fresh tea leaves from east Dongting and west Dongting mountains in Suzhou. The results indicate that the method is simple,rapid,precise and reliable.
机译:建立了一种快速,准确的高效液相色谱-荧光检测器定量方法,用于分析鲜茶叶中的18种氨基酸。将样品切碎并混合,并在90℃下用超纯水萃取20分钟。以6-氨基喹啉基N-羟基琥珀酰亚胺基氨基甲酸酯(AQC)为柱前衍生试剂。在C18柱(对称性C18,3。9 mm×15 cm,4μm)上进行梯度HPLC分离。在18种氨基酸中,浓度范围为5。0-250μmol/ L时,浓度与峰面积之间具有良好的线性关系。通过分析五个重复实验验证了该方法。在新鲜茶叶样品中加标了18种氨基酸标准品,平均回收率为86. 25%-109。 05%,相对标准偏差(n = 5)在6. 03%至10. 56%之间。分析物的检出限(LOD)为0。 05-1。 27μmol/升。该方法已成功用于苏州东洞庭山和西洞庭山新鲜茶叶中18种氨基酸的分析。结果表明,该方法简便,快速,准确,可靠。

著录项

  • 来源
    《亚洲农业研究:英文版》 |2018年第002期|P.55-58|共5页
  • 作者单位

    Suzhou No.10 High School of Jiangsu Province;

    Suzhou Academy of Agricultural Sciences;

    Suzhou No.10 High School of Jiangsu Province;

    Suzhou Academy of Agricultural Sciences;

    Suzhou No.10 High School of Jiangsu Province;

    Suzhou Academy of Agricultural Sciences;

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  • 原文格式 PDF
  • 正文语种 CHI
  • 中图分类 O657.72;
  • 关键词

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