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Provedor de dados:  Rev. Bras. Ciênc. Solo
País:  Brazil
Título:  Potential of Spectroradiometry to Classify Soil Clay Content
Autores:  Dotto,André Carnieletto
Dalmolin,Ricardo Simão Diniz
Caten,Alexandre ten
Moura-Bueno,Jean Michel
Data:  2016-01-01
Ano:  2016
Palavras-chave:  Soil texture
Diffuse reflectance of the soil
Proximal soil sensing
Resumo:  ABSTRACT Diffuse reflectance spectroscopy (DRS) is a fast and cheap alternative for soil clay, but needs further investigation to assess the scope of application. The purpose of the study was to develop a linear regression model to predict clay content from DRS data, to classify the soils into three textural classes, similar to those defined by a regulation of the Brazilian Ministry of Agriculture, Livestock and Food Supply. The DRS data of 412 soil samples, from the 0.0-0.5 m layer, from different locations in the state of Rio Grande do Sul, Brazil, were measured at wavelengths of 350 to 2,500 nm in the laboratory. The fitting of the linear regression model developed to predict soil clay content from the DRS data was based on a R2 value of 0.74 and 0.75, with a RMSE of 7.82 and 8.51 % for the calibration and validation sets, respectively. Soil texture classification had an overall accuracy of 79.0 % (calibration) and 80.9 % (validation). The heterogeneity of soil samples affected the performance of the prediction models. Future studies should consider a previous classification of soil samples in different groups by soil type, parent material and/or sampling region.
Tipo:  Info:eu-repo/semantics/article
Idioma:  Inglês
Identificador:  http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832016000100301
Editor:  Sociedade Brasileira de Ciência do Solo
Relação:  10.1590/18069657rbcs20151105
Formato:  text/html
Fonte:  Revista Brasileira de Ciência do Solo v.40 2016
Direitos:  info:eu-repo/semantics/openAccess
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