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生态学杂志 ›› 2005, Vol. ›› Issue (8): 970-974.

• 技术与方法 • 上一篇    下一篇

采用多次顶空固相微萃取分析拟南芥绿叶挥发性物质

邓晓军1,2, 杜家纬1   

  1. 1. 中国科学院上海生命科学研究院植物生理生态研究所, 上海, 200032;
    2. 中国科学院研究生院, 北京, 100039
  • 收稿日期:2004-09-04 修回日期:2004-12-08 出版日期:2005-08-10
  • 通讯作者: 邓晓军,男,1977年生,博士研究生.主要从事植物次生代谢途径的表达及其调控研究.
  • 基金资助:
    中国科学院知识创新工程项目(VSCX2-2-02);上海市科委资助项目(023912004).

Multiple headspace solid phase microextraction and analysis of volatiles from Arabidopsis green leaf

DENG Xiaojun1,2, DU Jiawei1   

  1. 1. Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200032, China;
    2. Graduated School of Chinese Academy of Sciences, Beijing 100039, China
  • Received:2004-09-04 Revised:2004-12-08 Online:2005-08-10

摘要: 顶空固相微萃取作为一种新的挥发性和半挥发性物质分析技术,被广泛应用于植物样品的定性分析。由于进行顶空分析时,挥发性组分间的基质效应以及较为复杂的扩散和吸附过程,定量分析一直是SPME分析应用的难题。目标分析物的量看作是达到吸附平衡后单一萃取的物质量的总和,则无需考虑分析样品在顶空、萃取涂层间的分配,同时可以消除基质效应。在利用标准物质进行校正后只需要一次顶空萃取,即可求出分析物质的总量。首先利用DVB/CAR/PDMS定性得到拟南芥挥发性物质的组成,然后采用CAR/PDMS涂层定量,分析了拟南芥的3种绿叶挥发性物质,优化后萃取条件为40℃萃取20min,相对标准偏差小于12%,在3株植物样品中这些挥发性物质的量为78.6~158.4ng·g-1

关键词: 水稻, 干旱胁迫, 叶水势, 光合作用, 干物质分配

Abstract: Headspace solid phase microextraction (HS-SPME) has been widely used in qualitative characterization of volatile or semi-volatile organic compounds released by plant samples.The quantitative determination of volatile components in headspace analysis was proved to be difficult due to the so-called "matrix effect" and the complicated diffusion and adsorption processes of analytes.In this paper,a direct quantitative method for monitoring volatiles from Arabidopsis thaliana green leaf was presented,based on multiple HS-SPME.The chemical composition of emissions from Arabidopsis was firstly investigated by using SPME coated with DVB/CAR/PDMS fiber.After the extraction parameters were optimized,the total mass of three main green leaf volatiles was calculated by using the peak area of the first single extraction,combined with the calibration of standard solution.The absolute mass of three green leaf volatiles was from 78.6 to 158.4 ng穏-1.

Key words: Rice, Water deficit stress, Leaf water potential, Photosynthesis, Dry matter partitioning

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