Development of a Rapid Method to Assess Beer Foamability Based on Relative Protein Content Using RoboBEER and Machine Learning Modeling

Development of a Rapid Method to Assess Beer Foamability Based on Relative Protein Content Using RoboBEER and Machine Learning Modeling

Foam-related parameters are associated with beer quality and dependent, among others, on the protein content. This study aimed to develop a machine learning (ML) model to predict the pattern and presence of 54 proteins. Triplicates of 24 beer samples were analyzed through proteomics. Furthermore, sa...

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Bibliographic Details
Main Authors: Claudia Gonzalez Viejo, Christopher H. Caboche, Edward D. Kerr, Cassandra L. Pegg, Benjamin L. Schulz, Kate Howell, Sigfredo Fuentes
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Beverages
Subjects:
proteomics
artificial neural networks
robotics
artificial intelligence
Online Access:https://www.mdpi.com/2306-5710/6/2/28

Internet

https://www.mdpi.com/2306-5710/6/2/28

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