Title:	Surface Spectroscopy of oxisols, entisols and inceptisol and relationships with selected soil properties
Authors:	Poppiel, Raúl Roberto Lacerda, Marilusa Pinto Coelho Oliveira Junior, Manuel Pereira de Demattê, José Alexandre Melo Romero, Danilo Jefferson Sato, Marcus Vinicius Almeida Júnior, Leonardo Rafael de Cassol, Luiz Felipe Moreira
Assunto::	Relações solo-paisagem Espectroscopia do solo Análise espectral Função Kubelka-Munk
Issue Date:	2018
Publisher:	Sociedade Brasileira de Ciência do Solo
Citation:	POPPIEL, Raúl Roberto et al. Surface Spectroscopy of Oxisols, Entisols and Inceptisol and Relationships with Selected Soil Properties. Revista Brasileira de Ciências do Solo, Viçosa, v. 42, e0160519, 2018. DOI: http://dx.doi.org/10.1590/18069657rbcs20160519. Disponível em: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832018000100300&lng=en&nrm=iso. Acesso em: 03 jun. 2019. Epub Feb 01, 2018.
Abstract:	Traditional method of soil survey is expensive, slow, and must be carried out by experienced researchers. Thus, advances in soil observation technologies and the need to obtain information quickly by modern techniques have intensified the use of proximal sensing. This study characterized surface reflectance spectra (A horizon) and related them to traditional soil classification, based on morphological, physical, and chemical properties of representative pedogenetic profiles, developed in two toposequences of the Distrito Federal, Brazil. In the toposequences, 15 soil profiles were selected for a complete morphological description and sampling for laboratory analyses. Soil-landscape relationships were established, and profiles were classified to the fourth level of the Brazilian Soil Classification System (SiBCS). Classes of similar soils were grouped based on their surface spectra, resulting in spectral curves of 10 representative soils in the studied area. The Morphological Interpretation of Reflectance Spectrum (MIRS) and second derivative of the Kubelka-Munk (KM) function were applied to the soil spectra. The clustered soils were similar, mainly in terms of color, textural class, and organic matter content. Groups based on soil physical and chemical properties and on surface and subsurface colors were similar to those determined by surface reflectance. The identification of soil-landscape relationships was fundamental to understand the genesis and distribution of the soils, which had similar chemical and physical properties to their parent materials. The analysis of clusters based on soil surface reflectance proved efficient in determining groups of soil classes with similar properties. Surface reflectance data were related to the soil surface and subsurface properties determined by traditional soil sample analyses, since the two approaches formed similar groups. The simultaneous interaction of soil properties was assessed by MIRS analysis, while the second derivative of the KM function adequately quantified the mineralogy of the spectra.
metadata.dc.description.unidade:	Faculdade de Agronomia e Medicina Veterinária (FAV)
Licença::	(CC BY) - This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided that the original author and source are credited.
DOI:	https://dx.doi.org/10.1590/18069657rbcs20160519
Appears in Collections:	Artigos publicados em periódicos e afins

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