"How sweet are your strawberries?": Predicting sugariness using non-destructive and affordable hardware.

Wen, Junhan; Abeel, Thomas; de Weerdt, Mathijs

Wen, Junhan; Abeel, Thomas; de Weerdt, Mathijs.

Afiliación

Wen J; Algorithmics Group, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, Netherlands.
Abeel T; Delft Bioinformatics Lab, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, Netherlands.
de Weerdt M; Delft Bioinformatics Lab, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, Netherlands.

Front Plant Sci ; 14: 1160645, 2023.

Article en En | MEDLINE | ID: mdl-37035076

Palabras clave

computer vision; crop management; data fusion; feature selection; in-field test; machine learning; non-destructive analysis; total soluble solid

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Plant Sci Año: 2023 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Suiza

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google