Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1110823
Registro completo de metadados
Campo DCValorIdioma
dc.contributor.authorROCHA, M. G. daeng
dc.contributor.authorBARROS, F. M. M. deeng
dc.contributor.authorOLIVEIRA, S. R. de M.eng
dc.contributor.authorAMARAL, L. R. doeng
dc.date.accessioned2019-07-25T01:02:19Z-
dc.date.available2019-07-25T01:02:19Z-
dc.date.created2019-07-24
dc.date.issued2019
dc.identifier.citationScientia Agricola, v. 76, n. 4, p. 274-280, July/Aug. 2019eng
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1110823-
dc.descriptionABSTRACT: Knowing the spatial variability of sugarcane biomass in the early stages of development may help growers in their management decision-making. Proximal canopy sensing is a promising technology that can identify this variability but is limited to quantifying plant-specific parameters. In this study, we evaluated whether biometric variables integrated with canopy reflectance data can assist in the generation of models for early-stage sugarcane biomass prediction. To substantiate this assertion, four sugarcane-producing fields were measured with an active crop canopy sensor and 30 sampling plots were selected for manually quantifying chlorophyll content, plant height, stalk number and aboveground biomass. We determined that Random Forest and Multiple Linear Regression models are similarly able to predict biomass, and that associating biometric variables such as number of stalks and plant height with reflectance data can assist model performance, depending on the attributes selected. This indicates that, when estimating biomass in the early stages, sugarcane growers can carry out site-specific management in order to increase yield and reduce the use of inputs.eng
dc.language.isoengeng
dc.rightsopenAccesseng
dc.subjectFloresta aleatóriaeng
dc.subjectÍndice de vegetaçãoeng
dc.subjectMineração de dadoseng
dc.subjectPrecision farmingeng
dc.subjectRandom foresteng
dc.subjectVegetation indiceseng
dc.subjectData miningeng
dc.subjectCanopy sensoreng
dc.titleBiometric characteristics and canopy reflectance association for early-stage sugarcane.eng
dc.typeArtigo de periódicoeng
dc.date.updated2019-10-02T11:11:11Z
dc.subject.thesagroBiomassaeng
dc.subject.thesagroCana de Açúcareng
dc.subject.thesagroAgricultura de Precisãoeng
dc.subject.nalthesaurusBiomasseng
dc.subject.nalthesaurusSugarcaneeng
dc.subject.nalthesaurusPrecision agricultureeng
dc.subject.nalthesaurusVegetation indexeng
riaa.ainfo.id1110823eng
riaa.ainfo.lastupdate2019-10-02 -03:00:00
dc.identifier.doihttp://dx.doi.org/10.1590/1678-992X-2017-0301eng
dc.contributor.institutionMURILLO GRESPAN DA ROCHA, Feagri/Unicamp; FLÁVIO MARGARITO MARTINS DE BARROS, Feagri/Unicamp; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; LUCAS RIOS DO AMARAL, Feagri/Unicamp.eng
Aparece nas coleções:Artigo em periódico indexado (CNPTIA)

Arquivos associados a este item:
Arquivo Descrição TamanhoFormato 
APBiometriccharacteristics.pdf1,1 MBAdobe PDFThumbnail
Visualizar/Abrir
Mostrar registro simples do item Visualizar estatísticas

FacebookTwitterDeliciousLinkedInGoogle BookmarksMySpace