MTBLS679: From Field to Feature in Ecometabolomics: LC-MS Based Metabolite Profiles of Thirteen Grassland Plant Species Reflecting Environmental Dynamics

  • Sue Marr (Creator)
  • Jos Hageman (Creator)
  • Ron Wehrens (Creator)
  • Nicole M. van Dam (Creator)
  • Helge Bruelheide (Creator)
  • Steffen Neumann (Creator)

Dataset

Description

In plants, secondary metabolites provide a unique opportunity to explore seasonal variation and responses to the environment. These include both abiotic and biotic factors. In field experiments, such stress factors occur in combination. This variation alters the plant metabolic profiles in yet uninvestigated ways.

This data set contains trait and mass spectrometry data of thirteen grassland species collected at four time points in the growing season in 2017. We collected above-ground vegetative material of seven grass and six herb species that were grown in plant communities with different levels of diversity in the Jena Experiment. For each sample, we recorded visible traits and acquired shoot metabolic profiles on a UPLC-ESI-Qq-TOF-MS. We performed the feature detection, grouping, and annotation in Galaxy-W4M and prepared the data for statistical analysis in R by applying missing data imputation, batch correction, and validity checks on the features. Together with this comprehensive data set, we also provide a detailed tutorial for the processing steps in R.
Date made available23 Dec 2020
PublisherLeipzig University

Keywords

  • Phleum pratense
  • Ranunculus acris
  • Dactylis glomerata
  • Plantago lanceolata
  • Knautia arvensis
  • Centaurea jacea
  • Anthoxanthum odoratum
  • Geranium pratense
  • Holcus lanatus
  • Leucanthemum vulgare
  • Poa pratensis
  • Festuca rubra
  • Avenula pubescens
  • QC_pool
  • blank

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