Please use this identifier to cite or link to this item: https://pgc-snia.inia.gob.pe:8443/jspui/handle/20.500.12955/1992
Title: Assessment of vegetation índices derived from UAV images for predicting biometric variables in bean during ripening stage
Authors: Quille Mamani, Javier Alvaro 
Porras Jorge, Rossana 
Saravia Navarro, David 
Herrera Flores, Jordan Valentin 
Chávez Galarza, Julio César 
Arbizu Berrocal, Carlos Irvin 
Valqui Valqui, Lamberto 
Keywords: Vegetation índice;Precision agricultura;RGB images
Issue Date: Mar-2022
Publisher: Universidad de Tarapacá
Source: 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
Journal: IDESIA 
Abstract: 
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.
Description: 
7 páginas
URI: https://hdl.handle.net/20.500.12955/1992
ISSN: 0073-4675
Rights: info:eu-repo/semantics/openAccess
Appears in Collections:Artículos científicos

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