Título:	Predicting soil clay content from NIR, gamma-ray and XRF curves.
Autoria:	VASQUES, G. de M. RODRIGUES, H. M. TAVARES, S. R. de L. COELHO, M. R.
Afiliação:	GUSTAVO DE MATTOS VASQUES, CNPS; HUGO MACHADO RODRIGUES, UFRRJ; SILVIO ROBERTO DE LUCENA TAVARES, CNPS; MAURICIO RIZZATO COELHO, CNPS.
Ano de publicação:	2019
Referência:	In: 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.
Conteúdo:	In 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.
Thesagro:	Sensoriamento Remoto
Tipo do material:	Resumo em anais e proceedings
Acesso:	openAccess
Aparece nas coleções:	Resumo em anais de congresso (CNPS)