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

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dc.creatorCamelo-Munevar, Rodrigo Andrés
dc.creatorHernández, Luis Miguel
dc.creatorJauregui, Rosa
dc.creatorCardoso Arango, Juan Andrés
dc.date2023-10-23
dc.date2023-11-09T15:35:23Z
dc.date2023-11-09T15:35:23Z
dc.date.accessioned2026-06-27T13:34:50Z
dc.formatapplication/pdf
dc.identifierhttps://hdl.handle.net/10568/132880
dc.identifier.urihttp://hdl.handle.net/123456789/63858
dc.languageen
dc.publisherInternational Center for Tropical Agriculture
dc.rightsOpen Access
dc.sourceCamelo-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.
dc.subjectplant nutrition
dc.subjectmachine learning
dc.subjectproductivity
dc.subjectpastures
dc.subjectnutritive value
dc.subjectunmanned aerial vehicles
dc.subjectmodels
dc.subjecturochloa
dc.titlePredictive modeling of nutritional quality in Urochloa pastures from multispectral sensors and images using machine learning approaches
dc.typePoster

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