Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1115064
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dc.contributor.authorVASQUES, G. de M.eng
dc.contributor.authorRODRIGUES, H. M.eng
dc.contributor.authorTAVARES, S. R. de L.eng
dc.contributor.authorCOELHO, M. R.eng
dc.date.accessioned2019-11-25T18:22:39Z-
dc.date.available2019-11-25T18:22:39Z-
dc.date.created2019-11-25
dc.date.issued2019
dc.identifier.citationIn: WORLD CONGRESS OF SOIL SCIENCE, 21., 2018, Rio de Janeiro. Soil science: beyond food and fuel: proceedings... Viçosa, MG: SBCS, 2019. v. 2, p. 535-536. WCSS 2018.eng
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1115064-
dc.descriptionIn this study, data from NIR, gamma ray and XRF curves, and three multivariate methods (partial least squares regression - PLS, random forest - RF, and support vector machine - SVM) were used to predict soil clay content at 0-10-cm depth. Training and validation data included 103 and 25 samples, respectively. Gamma ray and XRF data were taken in situ at the soil surface, using portable sensors, whereas NIR reflectance curves (800-2500 nm) were measured from airdried fine earth samples in the laboratory.eng
dc.language.isoengeng
dc.rightsopenAccesseng
dc.titlePredicting soil clay content from NIR, gamma-ray and XRF curves.eng
dc.typeResumo em anais e proceedingseng
dc.date.updated2020-01-03T11:11:11Z
dc.subject.thesagroSensoriamento Remotoeng
riaa.ainfo.id1115064eng
riaa.ainfo.lastupdate2020-01-03 -02:00:00
dc.contributor.institutionGUSTAVO DE MATTOS VASQUES, CNPS; HUGO MACHADO RODRIGUES, UFRRJ; SILVIO ROBERTO DE LUCENA TAVARES, CNPS; MAURICIO RIZZATO COELHO, CNPS.eng
Appears in Collections:Resumo em anais de congresso (CNPS)

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