Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/20.500.12955/1992
Título : Assessment of vegetation índices derived from UAV images for predicting biometric variables in bean during ripening stage
Autor : Quille Mamani, Javier Alvaro
Porras Jorge, Rossana
Saravia Navarro, David
Herrera, Jordán
Chávez Galarza, Julio César
Arbizu Berrocal, Carlos Irvin
Valqui Valqui, Lamberto
Fecha de publicación : mar-2022
Publicado en: IDESIA
Resumen : Here, we report the prediction of vegetative stages variables of canary bean crop employing 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 vegetation indices derived from UAV images from the canary bean, which were evaluated by multiple regression 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 índice
Precision agricultura
RGB images
Editorial : Universidad de Tarapacá
Citación : Quille, J.; Porras, R.; Saravia, D.; Herrera, J.; Chávez, J.; Arbizu, C. & Valqui, L. (2022). Assessment of vegetation índices derived from UAV images for predicting biometric variables in bean during ripening stage. IDESIA, 40(1), 1-7. https://www.idesia.cl/index.php?option=com_volumenes&view=d&aid=1153&vid=98
Descripción : 7 páginas
URI : https://hdl.handle.net/20.500.12955/1992
metadata.dc.subject.ocde: https://purl.org/pe-repo/ocde/ford#4.05.00
Aparece en las colecciones: Artículos científicos

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