NDLI: Determining Wine Authenticity : A Metabolomics Analysis Using UHPLC ESI / Q-TOF MS

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Determining Wine Authenticity : A Metabolomics Analysis Using UHPLC ESI / Q-TOF MS

Content Provider	Semantic Scholar
Author	Zhou, Qi
Copyright Year	2014
Abstract	This application note demonstrates the advantages of using an Agilent 1290 Infinity LC system combined with the Agilent 6530 Q-TOF LC/MS and multivariate statistical analysis for metabolic profiling of wines. This resulted in the differentiation of wines from different geographical areas including France and China, and it potentially allows for the identification of wine biomarkers. Introduction The chemical compositions of wines can vary by a wide range of factors. This is caused primarily by the variety of grapes, their growing conditions such as climate and soil, and the viticultural practices of the winemaker. In addition, the yeast strain, fermentation, and aging processes may also impact the taste and quality of wine. Chromatography coupled with accurate and high resolution mass spectrometry is currently a well accepted method for the metabolic profiling of wine. It is routinely used to analyze wine chemodiversity [1-3] and is beneficial for the discovery of wine biomarkers. This application note provides additional insight into the potential for improved quality control and authenticity assessments of wines. This study used ultra high performance liquid chromatography (UHPLC) with electrospray ionization quadrupole time-of-flight (ESI-Q-TOF) mass spectrometry, as well as multivariate statistical analysis for wine profiling. The goal of this study was the discovery of characteristic features that could discriminate wines from different geographical regions of China and France.
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://www.agilent.com/cs/library/applications/5991-3335EN.pdf
Alternate Webpage(s)	http://www.ingenieria-analitica.com/downloads/dl/file/id/1717/product/294/determining_wine_authenticity_a_metabolomics_analysis_using_uhplc_esiqtof_ms.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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