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Researcher­s use AI model to improve beer taste

- Roberto Ferrer

From lagers and blonds to lambics, there is a wide range of different beers to choose from.

But could artificial intelligen­ce (AI) help predict if a specific beer recipe will be appreciate­d by consumers before they even try it?

A team of scientists at KU Leuven, a university in Belgium, say that it can.

The researcher­s gathered a trained tasting panel of 16 people and asked them to try 250 commercial beers of 22 different styles such as lagers, blonds, and stouts.

Participan­ts rated the beverages on 50 attributes, including different hop, malt, and yeast flavours, off-flavours and spices.

Researcher­s then gathered 180,000 public reviews of the same beers on RateBeer, an online consumer rating platform to complement the data from the panel.

The beers were also carefully analysed for their compositio­n. For each beer, the scientists measured 226 different chemical properties, including alcohol content, pH, and sugar concentrat­ion and more than 200 aromatic compounds.

The researcher­s used these large datasets "to develop predictive models that link chemical data to sensorial features," they explain in the study.

They published their findings in the journal Nature Communicat­ions.

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Training an AI to be a taster

They were able to train an AI model to predict a beer's flavour and whether it would be liked based on its chemical compositio­n.

With this data, scientists were able to improve the taste of an existing commercial Belgian beer by adding certain aromas predicted by the model to increase its quality.

The modified beer scored better than the original in blind tastings.

“The spiked beers were found to have significan­tly improved overall appreciati­on among trained panellists," the researcher­s concluded, with panellists noting "increased intensity of ester flavours, sweetness, alcohol, and body fullness".

Tasters also rated an improved sample of non-alcoholic beer higher.

The challenge of predicting food taste

The study points out that predicting the taste and appreciati­on of foods from their chemical properties remains complicate­d.

One of the main obstacles is the high number of chemical substances that interact and influence taste.

"Flavour perception is highly complex, resulting from hundreds of different molecules interactin­g at the physiochem­ical and sensorial level," the authors say.

Our biggest goal now is to make better alcohol-free beer. Kevin Verstrepen Professor at KU Leuven

The researcher­s also note that human tastes are conditione­d by other factors, such as genetics, environmen­t, culture, and consumer psychology.

That is why they used very large datasets that can only be analysed by machine learning models.

“The flavour of beer is a complex mix of aroma compounds. It is impossible to predict how good a beer is by just measuring one or a few compounds. We really need the power of computers,” Michiel Schreurs, the lead author of the study, said in a statement.

“Our biggest goal now is to make better alcohol-free beer. Using our model, we have already succeeded in creating a cocktail of natural aroma compounds that mimic the taste and smell of alcohol without the risk of a hangover,” said Kevin Verstrepen, a professor at KU Leuven.

The team said the study's findings could be expanded to other food products, which may revolution­ise how new foods are made.

 ?? ?? A worker scrapes the foam off of a glass of beer before serving, in Bruges, Belgium.
A worker scrapes the foam off of a glass of beer before serving, in Bruges, Belgium.

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