Implementation of Artificial Intelligence in Food Science, Food Quality, and Consumer Preference Assessment

• Other Authors: Fuentes, Sigfredo (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
• Subjects: Research & information: general; Biology, life sciences; Technology, engineering, agriculture; sensory; physicochemical measurements; artificial neural networks; near infra-red spectroscopy; wine quality; machine learning modeling; weather; consumer acceptance prediction; data fusion; emotion recognition; facial expression recognition; galvanic skin response; machine learning; neural networks; sensory analysis; avocado; cultivars; preference mapping; sensory evaluation; sensory descriptive analysis; consumer science; unifloral honeys; botanical origin; physicochemical parameters; classification; natural language processing; deep learning; sensory science; flavor lexicon; long short-term memory; n/a
• Online Access: DOAB: download the publication; DOAB: description of the publication

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.