Optimizing nitrogen estimates in common bean canopies throughout key growth stages via spectral and textural data from unmanned aerial vehicle (UAV) multispectral imagery.

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dc.contributorDIOGO CASTILHO, UNIVERSIDADE FEDERAL DE GOIÁS; BEATA EMOKE MADARI, CNPAF; MARIA DA CONCEICAO SANTANA CARVALHO, CNPAF; MANUEL EDUARDO FERREIRA, UNIVERSIDADE FEDERAL DE GOIÁS.
dc.creatorCASTILHO, D.
dc.creatorMADARI, B. E.
dc.creatorCARVALHO, M. da C. S.
dc.creatorFERREIRA, M. E.
dc.date2025-07-09T13:19:03Z
dc.date2025-07-09T13:19:03Z
dc.date2025-07-09
dc.date2025
dc.date.accessioned2026-07-01T00:12:16Z
dc.descriptionThis study evaluates the integration of multispectral and texture data from UAV imagery to estimate leaf nitrogen content (LNC) in common bean across different growth stages. Our models were developed using data from a single location over two seasons; thus, broader validation is needed across diverse environmental conditions and cultivars.
dc.identifierIn: LATIN AMERICAN & CARIBBEAN SOIL CARBON RESEARCH SYMPOSIUM, 2025, Rio de Janeiro. Book of abstracts. Rio de Janeiro, 2025.
dc.identifierhttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1177196
dc.identifier.urihttp://hdl.handle.net/123456789/399628
dc.languageeng
dc.rightsopenAccess
dc.subjectFeijão
dc.subjectPhaseolus Vulgaris
dc.subjectNitrogênio
dc.subjectSpectral analysis
dc.subjectMultispectral imagery
dc.subjectBeans
dc.titleOptimizing nitrogen estimates in common bean canopies throughout key growth stages via spectral and textural data from unmanned aerial vehicle (UAV) multispectral imagery.
dc.typeResumo em anais e proceedings

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