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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...
Autores principales: | Selvaraj, Michael Gomez, Valderrama, Manuel, Guzman, Diego, Valencia, Milton, Ruiz, Henry, Acharjee, Animesh |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
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 |
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