Review of technology advances to assess rice quality traits and consumer perception.

Aznan, Aimi; Gonzalez Viejo, Claudia; Pang, Alexis; Fuentes, Sigfredo

Aznan, Aimi; Gonzalez Viejo, Claudia; Pang, Alexis; Fuentes, Sigfredo.

Afiliación

Aznan A; Digital Agriculture, Food and Wine Group, School of Agriculture, Food and Ecosystem Sciences, Faculty of Science, University of Melbourne, Parkville, VIC 3010, Australia; Department of Agrotechnology, Faculty of Mechanical Engineering and Technology, Universiti Malaysia Perlis, 02600 Perlis, Malaysi
Gonzalez Viejo C; Digital Agriculture, Food and Wine Group, School of Agriculture, Food and Ecosystem Sciences, Faculty of Science, University of Melbourne, Parkville, VIC 3010, Australia.
Pang A; Digital Agriculture, Food and Wine Group, School of Agriculture, Food and Ecosystem Sciences, Faculty of Science, University of Melbourne, Parkville, VIC 3010, Australia.
Fuentes S; Digital Agriculture, Food and Wine Group, School of Agriculture, Food and Ecosystem Sciences, Faculty of Science, University of Melbourne, Parkville, VIC 3010, Australia; Tecnologico de Monterrey, School of Engineering and Sciences, Ave. Eugenio Garza Sada 2501, Monterrey, N.L., México 64849, Mexico

Food Res Int ; 172: 113105, 2023 10.

Article en En | MEDLINE | ID: mdl-37689840

Asunto(s)

Oryza; Inteligencia Artificial; Tecnología; Agricultura; Percepción

Palabras clave

Artificial intelligence; Biometrics; Computer vision; Digital sensors; Sensory analysis

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Oryza Idioma: En Revista: Food Res Int Año: 2023 Tipo del documento: Article