Predictive modeling of nutritional quality in Urochloa pastures from multispectral sensors and images using machine learning approaches

Detalles Bibliográficos
Autores principales: Camelo-Munevar, Rodrigo Andrés, Hernández, Luis Miguel, Jauregui, Rosa, Cardoso Arango, Juan Andrés
Formato: Póster
Lenguaje:Inglés
Publicado: International Center for Tropical Agriculture 2023
Materias:
Acceso en línea:https://hdl.handle.net/10568/132880
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author Camelo-Munevar, Rodrigo Andrés
Hernández, Luis Miguel
Jauregui, Rosa
Cardoso Arango, Juan Andrés
author_browse Camelo-Munevar, Rodrigo Andrés
Cardoso Arango, Juan Andrés
Hernández, Luis Miguel
Jauregui, Rosa
author_facet Camelo-Munevar, Rodrigo Andrés
Hernández, Luis Miguel
Jauregui, Rosa
Cardoso Arango, Juan Andrés
author_sort Camelo-Munevar, Rodrigo Andrés
collection Repository of Agricultural Research Outputs (CGSpace)
format Poster
id CGSpace132880
institution CGIAR Consortium
language Inglés
publishDate 2023
publishDateRange 2023
publishDateSort 2023
publisher International Center for Tropical Agriculture
publisherStr International Center for Tropical Agriculture
record_format dspace
spelling CGSpace1328802025-11-05T12:31:02Z Predictive modeling of nutritional quality in Urochloa pastures from multispectral sensors and images using machine learning approaches Camelo-Munevar, Rodrigo Andrés Hernández, Luis Miguel Jauregui, Rosa Cardoso Arango, Juan Andrés plant nutrition machine learning productivity pastures nutritive value unmanned aerial vehicles models urochloa 2023-10-23 2023-11-09T15:35:23Z 2023-11-09T15:35:23Z Poster https://hdl.handle.net/10568/132880 en Open Access application/pdf International Center for Tropical Agriculture Camelo-Munevar, R.A.; Hernández, L.M.; Jauregui, R.; Cardoso-Arango, J.A. (2023) Predictive modeling of nutritional quality in Urochloa pastures from multispectral sensors and images using machine learning approaches. Poster prepared for African Plant Breeders Association 2023 Conference - Leveraging Genetic Innovation for Resilient African Food Systems in the wake of Global Shocks. Benguerir, Morocco, 23-26 October 2023. Cali (Colombia): International Center for Tropical Agriculture. 1 p.
spellingShingle plant nutrition
machine learning
productivity
pastures
nutritive value
unmanned aerial vehicles
models
urochloa
Camelo-Munevar, Rodrigo Andrés
Hernández, Luis Miguel
Jauregui, Rosa
Cardoso Arango, Juan Andrés
Predictive modeling of nutritional quality in Urochloa pastures from multispectral sensors and images using machine learning approaches
title Predictive modeling of nutritional quality in Urochloa pastures from multispectral sensors and images using machine learning approaches
title_full Predictive modeling of nutritional quality in Urochloa pastures from multispectral sensors and images using machine learning approaches
title_fullStr Predictive modeling of nutritional quality in Urochloa pastures from multispectral sensors and images using machine learning approaches
title_full_unstemmed Predictive modeling of nutritional quality in Urochloa pastures from multispectral sensors and images using machine learning approaches
title_short Predictive modeling of nutritional quality in Urochloa pastures from multispectral sensors and images using machine learning approaches
title_sort predictive modeling of nutritional quality in urochloa pastures from multispectral sensors and images using machine learning approaches
topic plant nutrition
machine learning
productivity
pastures
nutritive value
unmanned aerial vehicles
models
urochloa
url https://hdl.handle.net/10568/132880
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