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Diffuse reflectance spectroscopy for estimating soil organic carbon and make nitrogen recommendations Scientia Agricola
Rosin,Nicolas Augusto; Dalmolin,Ricardo Simão Diniz; Horst-Heinen,Taciara Zborowski; Moura-Bueno,Jean Michel; Silva-Sangoi,Daniely Vaz da; Silva,Leandro Souza da.
ABSTRACT: Diffuse reflectance spectroscopy (DRS) has the potential to predict soil organic carbon (SOC). However, it is still little used as a matter of routine in soil laboratories in Brazil. The objective of this study was to make evaluations as to whether SOC predicted by spectral techniques can replace measurement by routine chemical methods with no loss in quality and be applied in the recommendation of nitrogen fertilizer as well as identifying the best prediction strategies to use. A data set containing 2,471 samples from six soil spectral libraries (SSL) was used to develop spectroscopic models for SOC content prediction, including consideration of sample stratification and preprocessing techniques. The SOC was quantified through the...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Soil attributes prediction; Soil fertility; Proximal soil sensing; Chemometric; Green chemistry.
Ano: 2021 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162021000501402
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Potential of Spectroradiometry to Classify Soil Clay Content Rev. Bras. Ciênc. Solo
Dotto,André Carnieletto; Dalmolin,Ricardo Simão Diniz; Caten,Alexandre ten; Moura-Bueno,Jean Michel.
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,...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Soil texture; Diffuse reflectance of the soil; Proximal soil sensing.
Ano: 2016 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832016000100301
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