Suppr超能文献

通过气相色谱-离子迁移谱联用技术记录的花朵和受损叶片挥发性有机化合物排放模式数据集。

Dataset of volatile organic compound emission patterns from flowers and damaged leaves recorded with gas-chromatography coupled ion mobility spectrometry.

作者信息

Losch Florian, Liedtke Sascha, Vautz Wolfgang, Weigend Maximilian

机构信息

University Bonn, Mathematisch-Naturwissenschaftliche Fakultät, Bonner Institut für Organismische Biologie, Department Biodiversität der Pflanzen, 53115 Bonn, Germany.

ION-GAS GmbH, Konrad-Adenauer-Allee 11, 44263 Dortmund, Germany.

出版信息

Data Brief. 2024 May 11;54:110507. doi: 10.1016/j.dib.2024.110507. eCollection 2024 Jun.

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

植物会释放一系列挥发性有机化合物(VOCs),以此与它们的生物和非生物环境进行交互。这些挥发性有机化合物具有多种生态功能,例如吸引传粉者、驱赶食草动物,或者可能是对非生物胁迫做出的反应而释放。对于本数据集,我们使用气相色谱-离子迁移谱联用技术(GC-IMS)来分析不同植物物种在受控条件下释放的挥发性有机化合物。GC-IMS是一种用于气相分析的快速且灵敏的技术,它基于保留时间和漂移时间来分离挥发性有机化合物,从而生成特征性热图,其中信号的xy位置对应化合物的身份,而信号强度反映其丰度。在这个数据集中,通过GC-IMS进行的快速分析被用于记录来自不同分类群的140种植物的排放模式。这包括花香挥发物以及诱导损伤后叶片的排放。数据经过预先评估并列在一张表格中,其中包含所用植物材料的信息以及各自排放模式的信息(包括已鉴定的化合物)。因此,这个数据集提供了关于植物挥发性有机化合物排放的广泛概述。这些数据可用于检查已知物质的分布情况,或用于植物功能、生态或生理研究中的特定植物排放,或作为化学分类学研究的起点。通过合适的设置,这些数据能够非常轻松地生成,这使得它适用于跨植物(或动物)群体甚至生态系统的大规模系统或生态研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0d3/11127169/a645fcc313fb/gr1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验