A Review on the Application of Chemometrics and Machine Learning Algorithms to Evaluate Beer Authentication

Beer is considered one of the top three most popular drinks, being consumed all over the world. During the last few decades, discrimination of beverages and food products has gained attention with many application research studies based on chemical parameters and chemometric or machine learning algorithms. However, no reviews about the evaluation of beers have been reported. Therefore, this review presents applications of beer classification among brands, styles and types, aging, origin, and the prediction of quality attributes of interest based on chemometric, machine learning methods, and chemical parameters. After analyzing the literature, it was found that chemometric and machine learning methods are successful tools for qualitative and quantitative examination of beers. However, more work needs to be done to evaluate machine learning methods and data mining algorithms, such as sampling, feature selection, and advanced classification algorithms.

Automated summary

Beer, recognized as one of the top three most popular drinks globally, has gained attention in research over the past few decades. Chemometric and machine learning methods have proven to be successful tools for qualitative and quantitative examination of beers, but further evaluation is needed for advanced classification algorithms and data mining techniques.