Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous Abstract"Fungal and herbivore elicitation of the novel maize sesquiterpenoid, zealexin A4, is attenuated by elevated CO(2)"    Next AbstractIsolation and partial characterization of the insulin binding sites of Tetrahymena pyriformis »

Food Chem


Title:gc-ims-tools - A new Python package for chemometric analysis of GC-IMS data
Author(s):Christmann J; Rohn S; Weller P;
Address:"Institute for Instrumental Analytics and Bioanalysis, Mannheim University of Applied Sciences, Paul-Wittsack-Strasse 10, 68163 Mannheim, Germany; Hamburg School of Food Science, University of Hamburg, Grindelallee 117, 20146 Hamburg, Germany. Hamburg School of Food Science, University of Hamburg, Grindelallee 117, 20146 Hamburg, Germany; Department of Food Chemistry and Analysis, Institute of Food, Technology and Food Chemistry, Technische Universitat Berlin, TIB 4/3-1, Gustav-Meyer-Allee 25, 13355 Berlin, Germany. Institute for Instrumental Analytics and Bioanalysis, Mannheim University of Applied Sciences, Paul-Wittsack-Strasse 10, 68163 Mannheim, Germany. Electronic address: p.weller@hs-mannheim.de"
Journal Title:Food Chem
Year:2022
Volume:20220613
Issue:
Page Number:133476 -
DOI: 10.1016/j.foodchem.2022.133476
ISSN/ISBN:1873-7072 (Electronic) 0308-8146 (Linking)
Abstract:"Due to its high sensitivity and resolving power, gas chromatography ion mobility spectrometry (GC-IMS) is an emerging benchtop technique for non-target screening of complex sample materials. Given the wide range of applications, such as food authenticity, custom data analysis workflows are needed. As a common basis, they necessarily share many functionalities such as file input/output, preprocessing methods, exploratory or supervised analysis and visualizations. This study introduces a new open source, fully customizable Python package for handling and analysis of GC-IMS data. A workflow to classify olive oils by geographical origin exemplarily demonstrates functionality and ease of use. Key preprocessing steps, exploratory - and supervised data analysis and feature selections are visualized. All code and detailed documentation are freely available as open source under the BSD 3-clause license at https://github.com/Charisma-Mannheim/gc-ims-tools"
Keywords:Chemometrics Gas Chromatography-Mass Spectrometry/methods *Ion Mobility Spectrometry/methods Olive Oil/chemistry *Volatile Organic Compounds/analysis Food authenticity Gc-ims Non-target screening Python;
Notes:"MedlineChristmann, Joscha Rohn, Sascha Weller, Philipp eng England 2022/06/20 Food Chem. 2022 Nov 15; 394:133476. doi: 10.1016/j.foodchem.2022.133476. Epub 2022 Jun 13"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 04-12-2024