Food Metabolomics Analysis of Wines Using LCMS™-8060NX Triple Quadrupole Mass Spectrometer

Significance of the topic

Food metabolomics has emerged as a powerful approach for comprehensive profiling of small molecules in food products. In the context of wine, this method enables objective assessment of grape origin, winemaking processes, and fermentation quality. Understanding metabolite patterns helps producers optimize flavor, ensure consistency, and authenticate geographic or varietal claims.

Objectives and study overview

The study aimed to compare six red wines from diverse grape varieties and regions using liquid chromatography–tandem mass spectrometry (LC-MS/MS). Two analytical workflows were applied: one targeting short-chain fatty acids and related organic acids, and another for broad-spectrum hydrophilic metabolites. Multivariate analysis was used to highlight compositional differences linked to origin and grape type.

Methodology and instrumentation

Sample preparation involved filtering each wine and performing derivatization for short-chain fatty acids/organic acids using 3-nitrophenylhydrazine chemistry. Hydrophilic metabolites were analyzed after dilution with water containing an internal standard. Chromatographic separation was carried out on a high-performance liquid chromatograph, followed by detection on a triple quadrupole mass spectrometer operating in multiple reaction monitoring mode.

Used instrumentation

• High-performance liquid chromatograph: Nexera X3
• Triple quadrupole mass spectrometer: LCMS-8060NX with IonFocus unit
• Peak processing software: Peakintelligence (LabSolutions Insight)
• Multivariate analysis: SIMCA 16

Main results and discussion

• Sensitivity enhancement: The IonFocus unit improved ion transmission, delivering approximately 1.5-fold higher signal for about 90% of tested hydrophilic metabolites.
• Short-chain fatty acids/organic acids: Five fatty acids and 13 organic acids were reliably quantified. Principal component analysis (PCA) separated French wines, characterized by high tartaric and succinic acids, from American wine with elevated malic acid, while Chilean and Australian samples clustered together.
• Hydrophilic metabolite profiling: Sixty compounds including amino acids, organic acids, nucleotides and related metabolites were detected. PCA grouped samples by grape variety: Cabernet Sauvignon exhibiting high proline and 4-hydroxyproline, Merlot enriched in phenylalanine, leucine and lysine, and Pinot Noir showing elevated alanine.
• Fermentation indicators: Relative ratios of lactic to malic acid indicated complete malolactic fermentation in most samples except the U.S. wine, where malic acid remained predominant.

Benefits and practical applications

• Quality control: Enables monitoring of fermentation progress and acidity balance.
• Authentication: Differentiates wines by origin and grape variety.
• Product development: Guides optimization of flavor profiles and production protocols.

Future trends and potential uses

• Expansion of metabolite panels through high-resolution MS and complementary techniques.
• Integration with genomics and proteomics for deeper insight into grape biology and fermentation microbiomes.
• Application of artificial intelligence for automated data interpretation and pattern recognition.
• Development of rapid, in-line analysis tools for real-time quality monitoring in wineries.

Conclusion

This study demonstrates that LC-MS/MS–based metabolomics, enhanced by focused ion optics and AI-driven peak processing, can effectively distinguish wines by origin, grape variety and fermentation status. The approach offers a robust platform for quality control, authentication and flavor optimization in the wine industry.

References

No literature references were provided in the original document.