Automated Composition Assessment of Natural Extracts: Untargeted Mass Spectrometry-Based Metabolite Profiling Integrating Semiquantitative Detection-Reference-Cited by-同舟云学术

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Automated Composition Assessment of Natural Extracts: Untargeted Mass Spectrometry-Based Metabolite Profiling Integrating Semiquantitative Detection

Published:2023-11-10 Issue:46 Volume:71 Page:18010-18023
ISSN:0021-8561
Container-title:Journal of Agricultural and Food Chemistry
language:en
Short-container-title:J. Agric. Food Chem.

Author:

Rutz Adriano¹²³^ORCID,Wolfender Jean-Luc¹²^ORCID

Affiliation:

1. School of Pharmaceutical Sciences, University of Geneva, 1211 Geneva, Switzerland

2. Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, 1211 Geneva, Switzerland

3. Institute of Molecular Systems Biology, ETH Zürich, 8093 Zürich, Switzerland

Funder

Schweizerischer Nationalfonds zur F?rderung der Wissenschaftlichen Forschung

Publisher

American Chemical Society (ACS)

Subject

General Agricultural and Biological Sciences,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jafc.3c03099

Reference110 articles.

1. Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra

2. Impact of automation on mass spectrometry

3. Quantification for non-targeted LC/MS screening without standard substances

4. Strategies for large-scale targeted metabolomics quantification by liquid chromatography-mass spectrometry

5. Direct‐EI in LC–MS: Towards a universal detector for small‐molecule applications

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1. Comprehensive mass spectrometric metabolomic profiling of a chemically diverse collection of plants of the Celastraceae family;Scientific Data;2024-04-22

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