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Article

Predicting Alcohol Concentration during Beer Fermentation Using Ultrasonic Measurements and Machine Learning

1
Food, Water, Waste Research Group, Faculty of Engineering, University Park, University of Nottingham, Nottingham NG7 2RD, UK
2
i2CAT Foundation, Calle Gran Capita, 2-4 Edifici Nexus (Campus Nord Upc), 08034 Barcelona, Spain
3
School of Computer Science, Jubilee Campus, University of Nottingham, Nottingham NG8 1BB, UK
*
Author to whom correspondence should be addressed.
Fermentation 2021, 7(1), 34; https://doi.org/10.3390/fermentation7010034
Received: 16 February 2021 / Revised: 1 March 2021 / Accepted: 2 March 2021 / Published: 4 March 2021
(This article belongs to the Special Issue Implementation of Digital Technologies on Beverage Fermentation)
Beer fermentation is typically monitored by periodic sampling and off-line analysis. In-line sensors would remove the need for time-consuming manual operation and provide real-time evaluation of the fermenting media. This work uses a low-cost ultrasonic sensor combined with machine learning to predict the alcohol concentration during beer fermentation. The highest accuracy model (R2 = 0.952, mean absolute error (MAE) = 0.265, mean squared error (MSE) = 0.136) used a transmission-based ultrasonic sensing technique along with the measured temperature. However, the second most accurate model (R2 = 0.948, MAE = 0.283, MSE = 0.146) used a reflection-based technique without the temperature. Both the reflection-based technique and the omission of the temperature data are novel to this research and demonstrate the potential for a non-invasive sensor to monitor beer fermentation. View Full-Text
Keywords: machine learning; ultrasonic measurements; long short-term memory; industrial digital technologies machine learning; ultrasonic measurements; long short-term memory; industrial digital technologies
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MDPI and ACS Style

Bowler, A.; Escrig, J.; Pound, M.; Watson, N. Predicting Alcohol Concentration during Beer Fermentation Using Ultrasonic Measurements and Machine Learning. Fermentation 2021, 7, 34. https://doi.org/10.3390/fermentation7010034

AMA Style

Bowler A, Escrig J, Pound M, Watson N. Predicting Alcohol Concentration during Beer Fermentation Using Ultrasonic Measurements and Machine Learning. Fermentation. 2021; 7(1):34. https://doi.org/10.3390/fermentation7010034

Chicago/Turabian Style

Bowler, Alexander, Josep Escrig, Michael Pound, and Nicholas Watson. 2021. "Predicting Alcohol Concentration during Beer Fermentation Using Ultrasonic Measurements and Machine Learning" Fermentation 7, no. 1: 34. https://doi.org/10.3390/fermentation7010034

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