Better beer: are computers the way forward?

Beer might have an even tastier future say Belgian researchers, who used a machine learning method to make better tasting beers. Their research is reported in Nature Communications.

Kevin Verstrepen and colleagues characterised over 200 chemical properties from 250 Belgian commercial beers across 22 beer styles, such as Blond and Tripel beers. They linked these to descriptive sensory profiling data from a trained tasting panel of 16 people and data from more than 180,000 public consumer reviews from an online beer review database called RateBeer. With this large dataset, the authors trained machine learning models to correlate and predict flavour and consumer appreciation from the beers’ chemical profile. They tested the effectiveness of the model by using its predictions to modify an alcoholic and non-alcoholic commercial beer and achieved higher overall appreciation among trained panellists in blind tastings.

Using the computer predictions, the team were able to modify commercial beers — both alcoholic and non-alcoholic — to receive a higher overall rating from trained panellists in blind tastings.

Understanding and predicting whether consumers will enjoy new food flavours is a complex task that is influenced by numerous chemical compounds and external factors. This presents a challenge in deciphering the relationship between beer chemistry and consumer preferences. Typically, this is investigated through consumer trials, which can be limited and somewhat inefficient.

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