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dc.contributor.authorCRUSIOL, L. G. T.
dc.contributor.authorSUN, L.
dc.contributor.authorSIBALDELLI, R. N. R.
dc.contributor.authorFELIPE JUNIOR, V.
dc.contributor.authorFURLANETI, W. X.
dc.contributor.authorCHEN, R.
dc.contributor.authorSUN, Z.
dc.contributor.authorWUYUN, D.
dc.contributor.authorCHEN, Z.
dc.contributor.authorNANNI, M. R.
dc.contributor.authorFURLANETTO, R. H.
dc.contributor.authorCEZAR, E.
dc.contributor.authorNEPOMUCENO, A. L.
dc.contributor.authorFARIAS, J. R. B.
dc.date.accessioned2023-01-19T20:02:52Z-
dc.date.available2023-01-19T20:02:52Z-
dc.date.created2023-01-19
dc.date.issued2022
dc.identifier.citationPrecision Agriculture, v. 23, p. 1093-1123, 2022.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1151089-
dc.language.isoeng
dc.rightsopenAccess
dc.titleStrategies for monitoring within-feld soybean yield using Sentinel-2 Vis-NIR-SWIR spectral bands and machine learning regression methods.
dc.typeArtigo de periódico
dc.subject.thesagroSoja
dc.subject.thesagroMaquina
dc.subject.thesagroRaio Infravermelho
dc.subject.nalthesaurusSoybeans
dc.subject.nalthesaurusYield mapping
dc.subject.nalthesaurusYield monitoring
dc.subject.nalthesaurusMultispectral imagery
dc.subject.nalthesaurusSpectral analysis
riaa.ainfo.id1151089
riaa.ainfo.lastupdate2023-01-19
dc.identifier.doi10.1007/s11119-022-09876-5
dc.contributor.institutionL. G.T. CRUSIOL; LIANG SUN, MINISTRY OF AGRICULTURE; RUBSON NATAL RIBEIRO SIBALDELLI, CNPSO; V. FELIPE JUNIOR, INTEGRADA COOPERATIVA AGROINDUSTRIAL; W. X. FURLANETI, INTEGRADA COOPERATIVA AGROINDUSTRIAL; R. CHEN, MINISTRY OF AGRICULTURE; Z. SUN, MINISTRY OF AGRICULTURE; D. WUYUN, MINISTRY OF AGRICULTURE; Z. CHEN, FOOD AND AGRICULTURAL ORGANIZATION OF THE UNITED NATIONS; M. R. NANNI, STATE UNIVERSITY OF MARINGÁ; R. H. FURLANETTO, STATE UNIVERSITY OF MARINGÁ; E. CEZAR, STATE UNIVERSITY OF MARINGÁ; ALEXANDRE LIMA NEPOMUCENO, CNPSO; JOSE RENATO BOUCAS FARIAS, CNPSO.
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