Prediction of biometric variables through multispectral images obtained from UAV in beans (Phaseolus vulgaris L.) during ripening stage

• Autores: Quille Mamani, Javier Alvaro, Porras Jorge, Rossana, Saravia Navarro, David, Herrera, Jordán, Chávez Galarza, Julio César, Arbizu Berrocal, Carlos Irvin
• Formato: documento de trabajo
• Fecha de Publicación: 2021
• Institución: Instituto Nacional de Innovación Agraria
• Repositorio: INIA-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:null:20.500.12955/1854
• Enlace del recurso: https://hdl.handle.net/20.500.12955/1854; https://doi.org/10.20944/preprints202106.0139.v1
• Nivel de acceso: acceso abierto
• Materia: Vegetation índices; Precision agricultura; RGB images; https://purl.org/pe-repo/ocde/ford#4.04.00

Here, we report the prediction of vegetative stages variables of canary bean crop by means of RGB and multispectral images obtained from UAV during the ripening stage, correlating the vegetation indices with biometric variables measured manually in the field. Results indicated a highly significant correlation of plant height with eight RGB image vegetation indices for the canary bean crop, which were used for predictive models, obtaining a maximum correlation of R2 = 0.79. On the other hand, the estimated indices of multispectral images did not show significant correlations.