University Presentation Showcase: Undergraduate Poster Gallery
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Creation Date
2022
Major
Computer Science (Artificial Intelligence in Data Science Concentration)
Department
Computer Science
Degree
Undergraduate
Mentor
Li Li Zyzak
Mentor Department
Chemistry
Abstract
Food and beverages are necessities of life and consumer goods companies dedicate significant resources to develop innovative concepts that consumers prefer. In a space where consumer has few choices, it’s easy to understand why they prefer one brand over the other. However, as category options expand it becomes more challenging. This is the case in the craft brew industry. In 2018, beer sales decline 1% while the craft brew sales volume grew 4% reaching 13% of the total beer market by volume1. Craft brews are sold at a higher premium and accounted for $27.6 billion in 2018, 24% of the $114.2 billion US beer market1. One of the biggest challenges for craft breweries is the ability to continue developing new taste perceptions. The goal of our project is to utilize science to develop an algorithm and blending tool enabling the user to create new and interesting flavor concepts for the craft brew industry. We leveraged the science of linking important flavor compounds from craft brews with similar flavor compounds in other food products. The uniqueness of our approach is two-fold: (1) we placed weighing factors (multipliers and rankings) on the flavor compounds in the food products, (2) we have created a flavor wheel description to aid in the user-friendliness of the tool. Our tool will provide a simpler and cost effective prototyping device for creation of new flavors for the brewing industry.
1 https://www.brewersassociation.org/statistics-and-data/national-beer-stats/
