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Título: | 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, Zenaida Rossana Saravia, David Herrera Flores, Jordan Valentin Chávez Galarza, Julio César Arbizu Berrocal, Carlos Irvin |
Palabras clave: | Vegetation índices;Precision agricultura;RGB images | Fecha de emisión: | 4-jun-2021 | Editor: | MDPI | Fuente: | 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. https://doi.org/10.20944/preprints202106.0139.v1 | Revista: | Preprints | 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. |
Descripción: | 11 páginas |
URI: | https://hdl.handle.net/20.500.12955/1854 | DOI: | https://doi.org/10.20944/preprints202106.0139.v1 | Derechos: | info:eu-repo/semantics/openAccess |
Aparece en Colecciones: | Artículos científicos |
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