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dc.contributor.authorQuille Mamani, Javier Alvaro-
dc.contributor.authorPorras Jorge, Rossana-
dc.contributor.authorSaravia Navarro, David-
dc.contributor.authorHerrera, Jordán-
dc.contributor.authorChávez Galarza, Julio César-
dc.contributor.authorArbizu Berrocal, Carlos Irvin-
dc.contributor.authorValqui Valqui, Lamberto-
dc.coverage.spatialPerúes_PE
dc.date.accessioned2022-11-30T16:58:17Z-
dc.date.available2022-11-30T16:58:17Z-
dc.date.issued2022-03-01-
dc.identifier.citationQuille, 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. doi: 10.4067/S0718-34292022000200039.es_PE
dc.identifier.urihttps://hdl.handle.net/20.500.12955/1992-
dc.description7 páginases_PE
dc.description.abstractHere, 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.es_PE
dc.formatapplication/pdfes_PE
dc.language.isoenges_PE
dc.publisherUniversidad de Tarapacáes_PE
dc.relation.ispartofseriesIDESIAes_PE
dc.rightsinfo:eu-repo/semantics/openAccesses_PE
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.sourceInstituto Nacional de Innovación Agrariaes_PE
dc.source.uriRepositorio Institucional - INIAes_PE
dc.subjectVegetation índicees_PE
dc.subjectPrecision agriculturaes_PE
dc.subjectRGB imageses_PE
dc.titleAssessment of vegetation índices derived from UAV images for predicting biometric variables in bean during ripening stagees_PE
dc.typeinfo:eu-repo/semantics/articlees_PE
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#4.05.00es_PE
dc.relation.publisherversionhttps://www.idesia.cl/index.php?option=com_volumenes&view=d&aid=1153&vid=98es_PE
dc.publisher.countryCLes_PE
dc.identifier.doihttp://dx.doi.org/10.4067/S0718-34292022000200039es_PE
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