Center for Analytical Chemistry, Department IFA-Tulln, University of Natural Resources and Life Sciences, Vienna, Konrad-Lorenz-Str. 20, 3430 Tulln, Austria.
Phytochem Anal. 2012 Jul-Aug;23(4):345-58. doi: 10.1002/pca.1364. Epub 2011 Oct 18.
Volatile organic compounds (VOCs) occurring in leaves of plants carry information about the physiological state of the plant. Monitoring of VOCs assists in detecting plant stress before visible signs are present.
To establish and apply a simple workflow for the automated extraction, measurement and annotation/identification of Vitis vinifera cv. Pinot Noir leaf metabolites.
Leaf samples were harvested, cooled with liquid nitrogen and homogenised under cooled conditions. VOCs were extracted and enriched by solid phase microextraction (SPME) and analysed by GC-MS. Samples were measured on two columns with different polarity of stationary phases. Mass spectral deconvolution and identification was done by AMDIS software. Strict identification criteria were applied: match factor ≥ 90; relative retention index deviation ≤ 2% from reference value on both columns. Data of two sampling dates were analysed with multivariate statistics.
We found ~600 components in a single chromatogram. Applying the mentioned criteria resulted in annotation of 63 metabolites of which 47 were confirmed with authentic standards. For the majority of the compounds technical variability was < < 40% (RSD), biological variability among plants was 7-119%. Principal component analysis (PCA) scores plot of leaf samples from two different sampling dates showed two clearly separated clusters. The presented workflow enabled for the first time the detection and identification of 19 metabolites that have so far not been described for Vitis spp.
The developed workflow enabled the identification of grapevine leaf metabolites, which allowed the separation of leaves from two sampling dates by PCA.
植物叶片中存在的挥发性有机化合物（VOCs）携带着植物生理状态的信息。监测 VOCs 有助于在出现可见迹象之前检测到植物的压力。
建立并应用一种简单的工作流程，用于自动提取、测量和注释/鉴定酿酒葡萄品种黑比诺叶片代谢物。
采集叶片样本，用液氮冷却，在冷却条件下匀浆。采用固相微萃取（SPME）提取和富集 VOCs，并通过 GC-MS 进行分析。样品在具有不同固定相极性的两根柱子上进行测量。通过 AMDIS 软件进行质谱解卷积和鉴定。应用严格的鉴定标准：匹配因子≥90；在两根柱子上与参考值的相对保留指数偏差≤2%。对两个采样日期的数据进行了多变量统计分析。
我们在单个色谱图中发现了约 600 个成分。应用上述标准，鉴定出 63 种代谢物，其中 47 种用标准品确证。对于大多数化合物，技术变异性<40%（RSD），植物间的生物学变异性为 7-119%。来自两个不同采样日期的叶片样本的主成分分析（PCA）得分图显示出两个明显分离的聚类。所提出的工作流程首次实现了对 19 种迄今为止尚未描述过的酿酒葡萄代谢物的检测和鉴定。
所开发的工作流程使鉴定葡萄叶片代谢物成为可能，通过 PCA 可以区分来自两个采样日期的叶片。
