Researchers have developed sophisticated machine learning models that can accurately predict the taste, aroma, mouthfeel and overall quality of beer, as well as predict how likely consumers would rate it highly. Over the course of five years, they analyzed 250 commercial beers to measure their chemical properties and flavor compounds which are key determinants of taste. The data set created by combining these detailed chemical analyses with assessments from a trained tasting panel and reviews from an online platform was used to train 10 machine-learning models.
By incorporating a wide range of data sources, the researchers were able to develop models that can help enhance the beer production process. This can benefit food and drink manufacturers in developing new products or improving existing recipes to cater to consumer preferences. Utilizing AI models can save a significant amount of time and money that would have otherwise been spent on conducting trials.
The use of AI models in the food and drink industry is becoming increasingly popular as it allows manufacturers to create products that meet consumer preferences while minimizing costs. By training machine learning models on large datasets, companies can quickly identify trends and make informed decisions about product development. This can lead to innovative products that appeal to consumers while also increasing profit margins for the company.