Novel application of computer vision to determine bubble size distributions in beer

Emerging Technologies Based on Artificial Intelligence to Assess the Quality and Consumer Preference of Beverages

Beverages is a broad and important category within the food industry, which is comprised of a wide range of sub-categories and types of drinks with different levels of complexity for their manufacturing and quality assessment. Traditional methods to evaluate the quality traits of beverages consist of tedious, time-consuming, and costly techniques, which do not allow researchers to procure results in real-time. Therefore, there is a need to test and implement emerging technologies in order to automate and facilitate those analyses within this industry. This paper aimed to present the most recent publications and trends regarding the use of low-cost, reliable, and accurate, remote or non-contact techniques using robotics, machine learning, computer vision, biometrics and the application of artificial intelligence, as well as to identify the research gaps within the beverage industry. It was found that there is a wide opportunity in the development and use of robotics and biometrics for all types of beverages, but especially for hot and non-alcoholic drinks. Furthermore, there is a lack of knowledge and clarity within the industry, and research about the concepts of artificial intelligence and machine learning, as well as that concerning the correct design and interpretation of modeling related to the lack of inclusion of relevant data, additional to presenting over- or under-fitted models.

Computer Vision Method in Beer Quality Evaluation—A Review

Beers are differentiated mainly according to their visual appearance and their fermentation process. The main quality characteristics of beer are appearance, aroma, flavor, and mouthfeel. Important visual attributes of beer are foam appearance (volume and persistence), as well as the color and clarity. To replace manual inspection, automatic, objective, rapid and repeatable external quality inspection systems, such as computer vision, are becoming very important and necessary. Computer vision is a non-contact optical technique, suitable for the non-destructive evaluation of the food product quality. Currently, the main application of computer vision occurs in automated inspection and measurement, allowing manufacturers to keep control of product quality. This paper presents an overview of the applications and the latest achievements of the computer vision methods in determining the external quality attributes of beer.