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

• Beste egile batzuk: Fuentes, Sigfredo (Argitaratzailea)
• Formatua: Baliabide elektronikoa Liburu kapitulua
• Hizkuntza: ingelesa
• Argitaratua: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
• Gaiak: 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
• Sarrera elektronikoa: 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 implem...