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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Main Authors:	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
Format:	info:eu-repo/semantics/article
Language:	Inglés
Published:	MDPI 2024
Subjects:	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
Online Access:	https://hdl.handle.net/20.500.12955/2599 https://doi.org/10.3390/rs16193720