Optimization of Time-Varying Temperature Profiles for Enhanced Beer Fermentation by Evolutive Algorithms
Beer is one of the most popular alcoholic beverages globally, leading to continuous efforts to enhance its production methods. Raw materials and the production process are crucial in the brewing industry, with fermentation being a vital stage that significantly impacts beer quality. The aim of this...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Fermentation |
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| Online Access: | https://www.mdpi.com/2311-5637/11/1/2 |
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| author | Pablo Ruarte Nadia Pantano Marianela Noriega Cecilia Fernández Emanuel Serrano Gustavo Scaglia |
| author_facet | Pablo Ruarte Nadia Pantano Marianela Noriega Cecilia Fernández Emanuel Serrano Gustavo Scaglia |
| author_sort | Pablo Ruarte |
| collection | DOAJ |
| description | Beer is one of the most popular alcoholic beverages globally, leading to continuous efforts to enhance its production methods. Raw materials and the production process are crucial in the brewing industry, with fermentation being a vital stage that significantly impacts beer quality. The aim of this study is to optimize the beer fermentation process by maximizing the ethanol concentration while minimizing species that adversely affect the organoleptic properties of beer. A novel optimization approach has been developed to derive an optimal, smooth, and continuous temperature profile that can be directly applied in real-world processes. This method integrates Fourier series and orthogonal polynomials for control action parameterization, in combination with evolutionary algorithms for parameter optimization. A key advantage of this methodology lies in its ability to handle a reduced parameter set efficiently, resulting in temperature profiles that are continuous and differentiable. This feature eliminates the need for post-smoothing and is particularly advantageous in biotechnological applications, where abrupt changes in temperature could negatively affect the viability of microorganisms. The optimized profiles not only enhance fermentation efficiency, but also improve the ethanol yield and reduce undesirable flavor compounds, providing a substantial improvement over current industrial practices. These advancements present significant potential for improving both the quality and consistency of beer production. |
| format | Article |
| id | doaj-art-9916a713eb5c450e9e7acdc9c5169226 |
| institution | Kabale University |
| issn | 2311-5637 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Fermentation |
| spelling | doaj-art-9916a713eb5c450e9e7acdc9c51692262025-01-24T13:32:00ZengMDPI AGFermentation2311-56372024-12-01111210.3390/fermentation11010002Optimization of Time-Varying Temperature Profiles for Enhanced Beer Fermentation by Evolutive AlgorithmsPablo Ruarte0Nadia Pantano1Marianela Noriega2Cecilia Fernández3Emanuel Serrano4Gustavo Scaglia5Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires 1425, ArgentinaConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires 1425, ArgentinaConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires 1425, ArgentinaConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires 1425, ArgentinaConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires 1425, ArgentinaConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires 1425, ArgentinaBeer is one of the most popular alcoholic beverages globally, leading to continuous efforts to enhance its production methods. Raw materials and the production process are crucial in the brewing industry, with fermentation being a vital stage that significantly impacts beer quality. The aim of this study is to optimize the beer fermentation process by maximizing the ethanol concentration while minimizing species that adversely affect the organoleptic properties of beer. A novel optimization approach has been developed to derive an optimal, smooth, and continuous temperature profile that can be directly applied in real-world processes. This method integrates Fourier series and orthogonal polynomials for control action parameterization, in combination with evolutionary algorithms for parameter optimization. A key advantage of this methodology lies in its ability to handle a reduced parameter set efficiently, resulting in temperature profiles that are continuous and differentiable. This feature eliminates the need for post-smoothing and is particularly advantageous in biotechnological applications, where abrupt changes in temperature could negatively affect the viability of microorganisms. The optimized profiles not only enhance fermentation efficiency, but also improve the ethanol yield and reduce undesirable flavor compounds, providing a substantial improvement over current industrial practices. These advancements present significant potential for improving both the quality and consistency of beer production.https://www.mdpi.com/2311-5637/11/1/2beer fermentationdynamic modelmultivariable systemstemperature profiles |
| spellingShingle | Pablo Ruarte Nadia Pantano Marianela Noriega Cecilia Fernández Emanuel Serrano Gustavo Scaglia Optimization of Time-Varying Temperature Profiles for Enhanced Beer Fermentation by Evolutive Algorithms Fermentation beer fermentation dynamic model multivariable systems temperature profiles |
| title | Optimization of Time-Varying Temperature Profiles for Enhanced Beer Fermentation by Evolutive Algorithms |
| title_full | Optimization of Time-Varying Temperature Profiles for Enhanced Beer Fermentation by Evolutive Algorithms |
| title_fullStr | Optimization of Time-Varying Temperature Profiles for Enhanced Beer Fermentation by Evolutive Algorithms |
| title_full_unstemmed | Optimization of Time-Varying Temperature Profiles for Enhanced Beer Fermentation by Evolutive Algorithms |
| title_short | Optimization of Time-Varying Temperature Profiles for Enhanced Beer Fermentation by Evolutive Algorithms |
| title_sort | optimization of time varying temperature profiles for enhanced beer fermentation by evolutive algorithms |
| topic | beer fermentation dynamic model multivariable systems temperature profiles |
| url | https://www.mdpi.com/2311-5637/11/1/2 |
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