TY - BOOK ID - 146090547 TI - Implementation of Artificial Intelligence in Food Science, Food Quality, and Consumer Preference Assessment PY - 2022 PB - Basel MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - Research & information: general KW - Biology, life sciences KW - Technology, engineering, agriculture KW - sensory KW - physicochemical measurements KW - artificial neural networks KW - near infra-red spectroscopy KW - wine quality KW - machine learning modeling KW - weather KW - consumer acceptance prediction KW - data fusion KW - emotion recognition KW - facial expression recognition KW - galvanic skin response KW - machine learning KW - neural networks KW - sensory analysis KW - avocado KW - cultivars KW - preference mapping KW - sensory evaluation KW - sensory descriptive analysis KW - consumer science KW - unifloral honeys KW - botanical origin KW - physicochemical parameters KW - classification KW - natural language processing KW - deep learning KW - sensory science KW - flavor lexicon KW - long short-term memory KW - sensory KW - physicochemical measurements KW - artificial neural networks KW - near infra-red spectroscopy KW - wine quality KW - machine learning modeling KW - weather KW - consumer acceptance prediction KW - data fusion KW - emotion recognition KW - facial expression recognition KW - galvanic skin response KW - machine learning KW - neural networks KW - sensory analysis KW - avocado KW - cultivars KW - preference mapping KW - sensory evaluation KW - sensory descriptive analysis KW - consumer science KW - unifloral honeys KW - botanical origin KW - physicochemical parameters KW - classification KW - natural language processing KW - deep learning KW - sensory science KW - flavor lexicon KW - long short-term memory UR - https://www.unicat.be/uniCat?func=search&query=sysid:146090547 AB - In recent years, new and emerging digital technologies applied to food science have been gaining attention and increased interest from researchers and the food/beverage industries. In particular, those digital technologies that can be used throughout the food value chain are accurate, easy to implement, affordable, and user-friendly. Hence, this Special Issue (SI) is dedicated to novel technology based on sensor technology and machine/deep learning modeling strategies to implement artificial intelligence (AI) into food and beverage production and for consumer assessment. This SI published quality papers from researchers in Australia, New Zealand, the United States, Spain, and Mexico, including food and beverage products, such as grapes and wine, chocolate, honey, whiskey, avocado pulp, and a variety of other food products. ER -