Estimation of forage biomass in oat (Avena sativa) using agronomic variables through UAV multispectral imaging

Accurate and timely estimation of oat biomass is crucial for the development of sustainable and efficient agricultural practices. This research focused on estimating and predicting forage oat biomass using UAV and agronomic variables. A Matrice 300 equipped with a multispectral camera was used for 1...

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Autores principales:	Urquizo Barrera, Julio Cesar, Ccopi Trucios, Dennis, Ortega Quispe, Kevin, Castañeda Tinco, Italo, Patricio Rosales, Solanch, Passuni Huayta, Jorge, Figueroa Venegas, Deyanira, Enriquez Pinedo, Lucia, Ore Aquino, Zoila, Pizarro Carcausto, Samuel
Formato:	Artículo
Lenguaje:	Inglés
Publicado:	MDPI 2024
Materias:	Germination rate Machine learning Remote sensing Photogrammetry Vegetation indices https://purl.org/pe-repo/ocde/ford#4.01.06 Germinability Poder germinativo Aprendizaje automatico Teledeteccion Fotogrametría Vegetation index Índice de vegetación
Acceso en línea:	https://hdl.handle.net/20.500.12955/2599 https://doi.org/10.3390/rs16193720