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Creation and validation of a reactor engineering model for multiphase red wine fermentations
Konrad V Miller1, Anita Oberholster2, David E Block1,2
1Department of Chemical Engineering, University of California, Davis, California.
Biotechnology and Bioengineering
|November 20, 2018
Summary
This study developed a complex reactor model for red wine fermentation, accounting for spatial variations. The model accurately predicts fermentation kinetics and profiles, aiding in optimizing wine production.
Area of Science:
- Enology and Viticulture
- Chemical Engineering
- Biochemical Engineering
Background:
- Red wine fermentation involves grape solids (skins and seeds) forming a "cap," creating spatial heterogeneity.
- Accurate modeling of red wine fermentation requires consideration of fermentation kinetics, heat transfer, diffusion, and fluid flow.
- Existing models often simplify the complex, multiphase nature of red wine fermentations.
Purpose of the Study:
- To develop and validate a comprehensive reactor-engineering model for red wine fermentation.
- To incorporate fundamental principles of fermentation kinetics, heat transfer, diffusion, and fluid flow into the model.
- To investigate the impact of key parameters, such as nitrogen availability, on fermentation outcomes.
Main Methods:
- Experimental determination of grape heat transfer properties throughout fermentation.
- Development of a multiphase reactor model using COMSOL software.
- Utilization of finite element analysis to solve model components simultaneously.
- Validation of model predictions against experimental data.
Main Results:
- The developed model demonstrated excellent agreement with experimental data.
- The model successfully predicted spatial profiles of active yeast cell concentration and ethanol productivity.
- Predicted liquid velocity profiles within the fermentor were obtained.
- The model was used to simulate the effects of varying initial bioavailable nitrogen concentrations.
Conclusions:
- The reactor-engineering model provides a robust framework for understanding and predicting red wine fermentation dynamics.
- The model's ability to capture spatial heterogeneity is crucial for accurate kinetic predictions.
- This tool can aid in optimizing fermentation conditions, particularly in nitrogen-limited environments, to improve wine quality.
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