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Updated: Jun 28, 2026

Profiling the Bacterial Community of Fermenting Traminette Grapes during Wine Production using Metagenomic Amplicon Sequencing
Published on: December 1, 2023
Generalised 2D-correlation NMR analysis of a wine fermentation
Gemma M Kirwan1, Shona Clark, Neil W Barnett
1Applied Chemistry, School of Applied Sciences, RMIT University, GPO Box 2476V, Melbourne, Vic. 3001, Australia.
This study monitored wine fermentation using high-resolution nuclear magnetic resonance (NMR) spectroscopy. Two-dimensional correlation mapping effectively interpreted real-time process changes, showcasing NMR
Area of Science:
- Analytical Chemistry
- Food Science
- Biotechnology
Background:
- Wine fermentation is a complex biochemical process.
- Real-time monitoring is crucial for quality control and optimization.
- Traditional methods may lack the detail for comprehensive analysis.
Purpose of the Study:
- To apply high-resolution nuclear magnetic resonance (NMR) spectroscopy for monitoring wine fermentation.
- To utilize generalized two-dimensional correlation techniques for data analysis.
- To demonstrate the utility of 2D correlation mapping in interpreting fermentation dynamics.
Main Methods:
- Daily monitoring of wine fermentation using (1)H NMR spectroscopy.
- Data pre-processing including spectral synthesis for consistent peak width.
- Application of generalized two-dimensional correlation techniques (2D-FTIR).
- Generation and analysis of synchronous and asynchronous data maps.
Main Results:
- Successful application of (1)H NMR spectroscopy to track fermentation progress.
- Identification of key spectral changes correlating with fermentation stages.
- 2D correlation maps provided insights into the temporal relationships between different chemical species.
- Demonstrated the ability to interpret complex fermentation dynamics over time.
Conclusions:
- High-resolution NMR spectroscopy is a powerful tool for wine fermentation process monitoring.
- Multivariate data analysis, specifically 2D correlation mapping, enhances the interpretation of complex spectral data.
- This approach offers a detailed, real-time understanding of fermentation kinetics.
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