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Discrimination of rosé wines using shotgun metabolomics with a genetic algorithm and MS ion intensity ratios

Abstract : A rapid Ultra performance Liquid chromatography coupled with Quadrupole/time of flight Mass Spectrometry (UpLc-Qtof-MS) method was designed to quickly acquire high-resolution mass spectra metabolomics fingerprints for rosé wines. An original statistical analysis involving ion ratios, discriminant analysis, and genetic algorithm (GA) was then applied to study the discrimination of rosé wines according to their origins. After noise reduction and ion peak alignments on the mass spectra, about 14 000 different signals were detected. The use of an in-house mass spectrometry database allowed us to assign 72 molecules. Then, a genetic algorithm was applied on two series of samples (learning and validation sets), each composed of 30 commercial wines from three different wine producing regions of France. Excellent results were obtained with only four diagnostic peaks and two ion ratios. This new approach could be applied to other aspects of wine production but also to other metabolomics studies. Wine is a widely consumed alcoholic beverage with a high commercial value. More specifically, the worldwide consumption of rosé wine has increased by 20% since 2002 1. Because of its high commercial value, it can become a subject of fraud, and authenticity control is required in order to maintain wine quality and to detect any adulteration 2. Thousands of molecules can be found in wines, including polyphenols 3. Recently, more than one hundred polyphenols have been quantified in various rosé wines 4. They are key components involved in color, taste and quality of wines. Their amount and composition depend on many different factors such as grape variety, geographic origin, winemaking, age. Several methods have already been developed for wine authentication purpose 5. They can be divided into two categories: metabolite profiling 6-8 or metabolomic fingerprinting 9,10. The first one is a targeted analysis focusing on a limited number of representative components while the second one is a non-targeted approach. Both methods were applied to red or white wines. In a previous work 11 , a very fast UPLC-QTOF-MS method was developed to characterize red wines from different grape varieties. One specific ion ratio was used to discriminate commercial red wines from three grape varieties. In this paper, we focused on the influence of the geographic origin of some rosé French wines. The chemical composition of grapes depends on the sum of different environmental conditions, which can be defined as a "terroir" that should influence the grape and wine composition. The goals of this paper were to develop: • A new and very fast UPLC-QTOF-MS wine metabolomics method with a focus on wine pigments. • An original statistical method and workflow that allow the robust discrimination of rosés wines according to their origins by using mass spectrometry ion ratio fingerprints. Results and Discussions UPLC-QTOF-MS analysis. First, a fast UPLC-QTOF-MS method was developed to rapidly acquire high-resolution mass spectra. In accordance with previous work and conclusions, we have used a short gradient instead of isocratic elution conditions or direct injections 11. It was shown that the last two methods gave limited results probably due to ionization suppression effect. In this work, we chose to work on the positive ionization
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Mélodie Gil, Christelle Reynes, Guillaume Cazals, Christine Enjalbal, Robert Sabatier, et al.. Discrimination of rosé wines using shotgun metabolomics with a genetic algorithm and MS ion intensity ratios. Scientific Reports, Nature Publishing Group, 2020, 10 (1), pp.1-7. ⟨10.1038/s41598-020-58193-2⟩. ⟨hal-02935106⟩

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