Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1121648
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dc.contributor.authorOSCO, L. P.
dc.contributor.authorRAMOS, A. P. M.
dc.contributor.authorPINHEIRO, M. M. F.
dc.contributor.authorMORIYA, E. A. S.
dc.contributor.authorIMAI, N. N.
dc.contributor.authorESTRABIS, N.
dc.contributor.authorIANCZYK, F.
dc.contributor.authorARAÚJO, F. F.
dc.contributor.authorLIESENBERG, V.
dc.contributor.authorJORGE, L. A. de C.
dc.contributor.authorLI, J.
dc.contributor.authorMA, L.
dc.contributor.authorGONÇALVES, W. N.
dc.contributor.authorMARCATO JUNIOR, J.
dc.contributor.authorCRESTE, J. E.
dc.date.accessioned2022-04-08T11:02:20Z-
dc.date.available2022-04-08T11:02:20Z-
dc.date.created2020-04-14
dc.date.issued2020
dc.identifier.citationRemote Sensing, n. 12, v. 6, a. 906, 2020.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1121648-
dc.languageIngles
dc.language.isoen
dc.rightsopenAccess
dc.subjectProximal sensor
dc.subjectMacronutrient
dc.subjectMicronutrient
dc.titleA machine learning framework to predict nutrient content in valencia-orange leaf hyperspectral measurements.
dc.typeArtigo de periódico
dc.format.extent21 - 21
riaa.ainfo.id1121648
riaa.ainfo.lastupdate2022-04-07
dc.identifier.doi10.3390/rs12060906
dc.contributor.institutionLUCIO ANDRE DE CASTRO JORGE, CNPDIA.
Appears in Collections:Artigo em periódico indexado (CNPDIA)

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