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

1
School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Parkville, VIC 3010, Australia
2
Department of Wine, Food and Molecular Biosciences, Faculty of Agriculture and Life Sciences, Lincoln University, 7647 Lincoln, New Zealand
*
Author to whom correspondence should be addressed.
Beverages 2019, 5(4), 62; https://doi.org/10.3390/beverages5040062
Received: 23 August 2019 / Revised: 9 October 2019 / Accepted: 10 October 2019 / Published: 1 November 2019
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. View Full-Text
Keywords: robotics; machine learning; computer vision; biometrics; artificial intelligence robotics; machine learning; computer vision; biometrics; artificial intelligence
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MDPI and ACS Style

Gonzalez Viejo, C.; Torrico, D.D.; Dunshea, F.R.; Fuentes, S. Emerging Technologies Based on Artificial Intelligence to Assess the Quality and Consumer Preference of Beverages. Beverages 2019, 5, 62. https://doi.org/10.3390/beverages5040062

AMA Style

Gonzalez Viejo C, Torrico DD, Dunshea FR, Fuentes S. Emerging Technologies Based on Artificial Intelligence to Assess the Quality and Consumer Preference of Beverages. Beverages. 2019; 5(4):62. https://doi.org/10.3390/beverages5040062

Chicago/Turabian Style

Gonzalez Viejo, Claudia, Damir D. Torrico, Frank R. Dunshea, and Sigfredo Fuentes. 2019. "Emerging Technologies Based on Artificial Intelligence to Assess the Quality and Consumer Preference of Beverages" Beverages 5, no. 4: 62. https://doi.org/10.3390/beverages5040062

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