Real-time monitoring of fermentation processes in wine production with benchtop 1H NMR spectroscopy

The flexibility, affordability and ease of use of benchtop <sup>1</sup>H NMR spectroscopy makes it potentially very interesting for assessing the quality of wine types and monitoring the fermentation process. However, the low spectral resolution of benchtop <sup>1</sup>H NMR spectroscopy and the complexity of the mixtures hinder the direct quantification of important wine parameters and, thus, prevent its widespread use as an analytical tool in wineries. We show here that these problems can be solved using model-based data processing. In a first step, the accuracy of the new approach was evaluated by analyzing gravimetrically prepared test mixtures representing different fermentation stages. Good agreement was found, demonstrating the reliability of the new method. In a second step, benchtop <sup>1</sup>H NMR spectroscopy combined with model-based data processing was used for the real-time monitoring of real fermentation media. Wine fermentation processes with different feed strategies (batch and fed-batch) were investigated and compared and the evolution of important wine constituents as well as effects caused by the different feeding strategies were monitored, demonstrating the applicability of the new approach also in demanding applications. This opens the way to using benchtop NMR spectroscopy for optimization and decision making in wine production.

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Institutions

Publication Details

Journal
Food Research International
Published
2025-01-22
DOI
https://doi.org/10.1016/j.foodres.2025.115741
Citations
8
Primary Topic
Fermentation and Sensory Analysis
Type
article
Field-Weighted Citation Impact
9.30

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article

Real-time monitoring of fermentation processes in wine production with benchtop 1H NMR spectroscopy

Ellen Steimers, Johnnie Phuong, Hans Hasse, Lena Keller et al.
8 citations
Food Research International
Fermentation and Sensory Analysis
9.30
article

Real-time monitoring of fermentation processes in wine production with benchtop 1H NMR spectroscopy

Ellen Steimers, Johnnie Phuong, Hans Hasse, Lena Keller, Patrick Nickolaus, Erik von Harbou, Daniel J. Holland, Fabian Jirasek, Ulrich Fischer, J. H. Heiss, Kerstin Münnemann, Billy Salgado
article en
8 citations

Abstract

The flexibility, affordability and ease of use of benchtop <sup>1</sup>H NMR spectroscopy makes it potentially very interesting for assessing the quality of wine types and monitoring the fermentation process. However, the low spectral resolution of benchtop <sup>1</sup>H NMR spectroscopy and the complexity of the mixtures hinder the direct quantification of important wine parameters and, thus, prevent its widespread use as an analytical tool in wineries. We show here that these problems can be solved using model-based data processing. In a first step, the accuracy of the new approach was evaluated by analyzing gravimetrically prepared test mixtures representing different fermentation stages. Good agreement was found, demonstrating the reliability of the new method. In a second step, benchtop <sup>1</sup>H NMR spectroscopy combined with model-based data processing was used for the real-time monitoring of real fermentation media. Wine fermentation processes with different feed strategies (batch and fed-batch) were investigated and compared and the evolution of important wine constituents as well as effects caused by the different feeding strategies were monitored, demonstrating the applicability of the new approach also in demanding applications. This opens the way to using benchtop NMR spectroscopy for optimization and decision making in wine production.

Food Research InternationalVol. 203
University of Kaiserslautern (DE), University of Canterbury (NZ), Dienstleistungszentrum Ländlicher Raum (DE), Schön Klinik Neustadt (DE), Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (DE)
Deutsche Forschungsgemeinschaft, Ministry of Business, Innovation and Employment, Forschungskreis der Ernährungsindustrie
Zero hunger
Openalex Percentile: Top 2%
Fermentation and Sensory Analysis
9.30
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