Data/hora: 13/06/2024 01:36:31

Provedor de dados: 	63	
País: 	Brazil	
Título: 	Diffuse reflectance spectroscopy for estimating soil organic carbon and make nitrogen recommendations	
Autores: 	Rosin,Nicolas Augusto; Dalmolin,Ricardo Simão Diniz; Horst-Heinen,Taciara Zborowski; Moura-Bueno,Jean Michel; Silva-Sangoi,Daniely Vaz da; Silva,Leandro Souza da.	
Data: 	2021-01-01	
Ano: 	2021	
Palavras-chave: 	Soil attributes prediction; Soil fertility; Proximal soil sensing; Chemometric; Green chemistry.	
Resumo: 	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 analytical-chemical methods of wet combustion with determination by titration, designated as the reference method (REM), and colorimeter, designated as the routine method (ROM in an independent data set). SOC contents predicted by the spectral analysis method (SAM) were compared to the REM and ROM results, converted to soil organic matter (SOM) and used for N recommendations. The best estimate for SOM content using the SAM was achieved through stratification of the SSL and application of the standard normal variate (SNV) preprocessing. The SOC predicted by spectral techniques proved capable of replacing the SOC measured by routine chemical methods with no loss of quality and supported by an appropriate nitrogen fertilizer recommendation, provided the models met the conditions and possessed the characteristics of the samples to be analyzed.	
Tipo: 	Info:eu-repo/semantics/article	
Idioma: 	Inglês	
Identificador: 	http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162021000501402	
Editor: 	São Paulo - Escola Superior de Agricultura "Luiz de Queiroz"	
Relação: 	10.1590/1678-992x-2019-0246	
Formato: 	text/html	
Fonte: 	Scientia Agricola  v.78 n.5 2021	
Fonte: 	info:eu-repo/semantics/openAccess