PDF(Pubmed)
Abstract：
Plants emit a range of volatile organic compounds (VOCs) as a way of interacting with their biotic and abiotic surroundings. These VOCs can have various ecological functions, such as attracting pollinators, repelling herbivores, or may be emitted in response to abiotic stress. For the present dataset, we used gas chromatography coupled ion mobility spectrometry (GC-IMS) to analyse the VOCs emitted by different plant species under controlled conditions. GC-IMS is a rapid and sensitive technique for gas phase analysis, that separates VOCs based on their retention time and drift time, resulting in characteristic heatmaps where the xy-position of a signal corresponds to compound identity, while signal intensity reflects its abundance. In this dataset, rapid analysis by GC-IMS was used to record emission pattern of 140 plant species from different taxonomic groups. This includes both floral volatiles and emission from leaves after induced damage. The data was pre-evaluated and listed in one table, containing information on the plant material used, as well as information on the respective emission patterns (including already identified compounds). Thus, this dataset provides a broad overview over plant VOC emissions. These can be used to either check the distribution of knowns substances, or the specific emissions of plants for functional, ecological or physiological studies or as the starting point for chemotaxonomic studies. The extraordinary ease with which these data can be generated - with the suitable set-up - lends itself to larger scale systematic or ecological studies across plant (or animal) groups and even ecosystems.
摘要：
植物释放出一系列挥发性有机化合物（VOCs），作为与生物和非生物环境相互作用的一种方式。这些挥发性有机化合物可以具有各种生态功能，例如吸引传粉者，驱除食草动物，或者可以响应非生物胁迫而发出。对于当前数据集，我们使用气相色谱耦合离子迁移谱（GC-IMS）分析了不同植物在受控条件下排放的挥发性有机化合物。GC-IMS是一种快速灵敏的气相分析技术，根据保留时间和漂移时间分离挥发性有机化合物，产生特征热图，其中信号的xy位置对应于化合物身份，而信号强度反映了它的丰度。在这个数据集中，通过GC-IMS快速分析用于记录来自不同分类组的140种植物的排放模式。这包括花卉挥发物和诱导损伤后叶片的排放。数据进行了预先评估，并在一个表格中列出，包含有关所用植物材料的信息，以及有关相应发射模式的信息（包括已经确定的化合物）。因此，该数据集提供了对植物VOC排放的广泛概述。这些可以用来检查已知物质的分布，或者功能性植物的特定排放，生态学或生理学研究或作为化学分类学研究的起点。通过适当的设置，可以轻松生成这些数据，这有助于进行跨植物（或动物）群体甚至生态系统的更大规模的系统或生态研究。
