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Application of a high-throughput process analytical technology metabolomics pipeline to Port wine forced ageing process
•A process analytical technology pipeline for GC–MS data processing is proposed.•MetAlign™ software was used to chromatograms preprocessing before multivariate analysis.•Metabolites related to Port wine degradation in “forced ageing” can be identified.•Kinetical correlations between metabolites prom...
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Published in: | Food chemistry 2014-01, Vol.143, p.384-391 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •A process analytical technology pipeline for GC–MS data processing is proposed.•MetAlign™ software was used to chromatograms preprocessing before multivariate analysis.•Metabolites related to Port wine degradation in “forced ageing” can be identified.•Kinetical correlations between metabolites promote the network reconstruction.•The pipeline can be extended to other fields increasing the knowledge about it.
Metabolomics aims at gathering the maximum amount of metabolic information for a total interpretation of biological systems. A process analytical technology pipeline, combining gas chromatography–mass spectrometry data preprocessing with multivariate analysis, was applied to a Port wine “forced ageing” process under different oxygen saturation regimes at 60°C.
It was found that extreme “forced ageing” conditions promote the occurrence of undesirable chemical reactions by production of dioxane and dioxolane isomers, furfural and 5-hydroxymethylfurfural, which affect the quality of the final product through the degradation of the wine aromatic profile, colour and taste. Also, were found high kinetical correlations between these key metabolites with benzaldehyde, sotolon, and many other metabolites that contribute for the final aromatic profile of the Port wine. The use of the kinetical correlations in time-dependent processes as wine ageing can further contribute to biological or chemical systems monitoring, new biomarkers discovery and metabolic network investigations. |
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ISSN: | 0308-8146 1873-7072 |
DOI: | 10.1016/j.foodchem.2013.07.138 |