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Título: | Assessment of vegetation índices derived from UAV images for predicting biometric variables in bean during ripening stage | Autores: | 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 |
Palabras clave: | Vegetation índice;Precision agricultura;RGB images | Fecha de emisión: | mar-2022 | Editor: | Universidad de Tarapacá | Fuente: | 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 | Revista: | 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. |
Descripción: | 7 páginas |
URI: | https://hdl.handle.net/20.500.12955/1992 | ISSN: | 0073-4675 | Derechos: | info:eu-repo/semantics/openAccess |
Aparece en Colecciones: | Artículos científicos |
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