Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/20.500.12955/1854
Título : Prediction of biometric variables through multispectral images obtained from UAV in beans (Phaseolus vulgaris L.) during ripening stage
Autor : Quille Mamani, Javier Alvaro
Porras Jorge, Rossana
Saravia Navarro, David
Herrera, Jordán
Chávez Galarza, Julio César
Arbizu Berrocal, Carlos Irvin
Fecha de publicación : 4-jun-2021
Resumen : 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.
Palabras clave : Vegetation índices
Precision agricultura
RGB images
Editorial : MDPI
Citación : Quille, J.; Porras, R.; Saravia, D.; Herrera, J.; Chavez, J.; Arbizu, C.I. (2021). Prediction of Biometric Variables Through Multispectral Images Obtained From Uav in Beans (Phaseolus vulgaris L.) During Ripening Stage. Preprints, 2021060139. doi: 10.20944/preprints202106.0139.v1
URI : https://hdl.handle.net/20.500.12955/1854
metadata.dc.identifier.doi: https://doi.org/10.20944/preprints202106.0139.v1
metadata.dc.subject.ocde: https://purl.org/pe-repo/ocde/ford#4.04.00
Aparece en las colecciones: Artículos científicos

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