Rapid Assessment of Rice Quality Traits Using Low-Cost Digital Technologies.

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 (DAFW), School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Melbourne, VIC 3010, Australia.
Gonzalez Viejo C; Faculty of Chemical Engineering Technology, University Malaysia Perlis, Arau 02600, Perlis, Malaysia.
Pang A; Digital Agriculture, Food and Wine Group (DAFW), School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Melbourne, VIC 3010, Australia.
Fuentes S; Digital Agriculture, Food and Wine Group (DAFW), School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Melbourne, VIC 3010, Australia.

Foods ; 11(9)2022 Apr 19.

Article en En | MEDLINE | ID: mdl-35563907

Palabras clave

artificial neural networks; electronic nose; machine learning; near-infrared; rice aroma

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Contexto en salud: 1_ASSA2030 Problema de salud: 1_financiamento_saude Tipo de estudio: Health_economic_evaluation / Prognostic_studies Idioma: En Revista: Foods Año: 2022 Tipo del documento: Article País de afiliación: Australia

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google