Toward automated chromatographic fingerprinting: A non-alignment approach to gas chromatography mass spectrometry data

In contrast to targeted analysis of volatile compounds, non-targeted approaches take information of known and unknown compounds into account, are inherently more comprehensive and give a more holistic representation of the sample composition. Although several non-targeted approaches have been develo...

Full description

Saved in:
Bibliographic Details
Published in:Analytica chimica acta 2016-03, Vol.911, p.42-58
Main Authors: Vestner, Jochen, de Revel, Gilles, Krieger-Weber, Sibylle, Rauhut, Doris, du Toit, Maret, de Villiers, André
Format: Article
Language:English
Subjects:
Automation
Chemical and Process Engineering
Chromatography
Data processing
Engineering Sciences
Fingerprinting
Food engineering
Gas chromatography
Gas Chromatography-Mass Spectrometry - methods
Life Sciences
Mass spectrometry
Matlab
Metabolomics
Multi-way analysis
Non-alignment
Non-targeted analysis
Principal Component Analysis
Solid Phase Microextraction
Vitaceae
Volatile compounds
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In contrast to targeted analysis of volatile compounds, non-targeted approaches take information of known and unknown compounds into account, are inherently more comprehensive and give a more holistic representation of the sample composition. Although several non-targeted approaches have been developed, there's still a demand for automated data processing tools, especially for complex multi-way data such as chromatographic data obtained from multichannel detectors. This work was therefore aimed at developing a data processing procedure for gas chromatography mass spectrometry (GC–MS) data obtained from non-targeted analysis of volatile compounds. The developed approach uses basic matrix manipulation of segmented GC–MS chromatograms and PARAFAC multi-way modelling. The approach takes retention time shifts and peak shape deformations between samples into account and can be done with the freely available N-way toolbox for MATLAB. A demonstration of the new fingerprinting approach is presented using an artificial GC–MS data set and an experimental full-scan GC–MS data set obtained for a set of experimental wines. [Display omitted] •A novel data processing procedure for non-targeted gas chromatography mass spectrometry (GC–MS) data is proposed.•Basic matrix manipulation of segmented GC–MS chromatograms and PARAFAC multi-way modelling is used.•Retention time shifts and peak shape deformations between samples are taken into account.•The procedure is demonstrated on an artificial and an experimental full-scan GC–MS data set.
ISSN:0003-2670
1873-4324
DOI:10.1016/j.aca.2016.01.020