Machine learning for high-throughput field phenotyping and image processing provides insight into the association of above and below-ground traits in cassava (Manihot esculenta Crantz)

BACKGROUND: Rapid non-destructive measurements to predict cassava root yield over the full growing season through large numbers of germplasm and multiple environments is a huge challenge in Cassava breeding programs. As opposed to waiting until the harvest season, multispectral imagery using unmanne...

Descripción completa

Detalles Bibliográficos
Autores principales: Selvaraj, Michael Gomez, Valderrama, Manuel, Guzman, Diego, Valencia, Milton, Ruiz, Henry, Acharjee, Animesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7296968/
https://www.ncbi.nlm.nih.gov/pubmed/32549903
http://dx.doi.org/10.1186/s13007-020-00625-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7296968/
https://www.ncbi.nlm.nih.gov/pubmed/32549903
http://dx.doi.org/10.1186/s13007-020-00625-1

Ejemplares similares