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 | Acesso ao texto completo restrito à biblioteca da Embrapa Arroz e Feijão. Para informações adicionais entre em contato com cnpaf.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
23/04/2019 |
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Data da última atualização: |
12/02/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
MORAIS, P. A. de O.; SOUZA, D. M. de; MADARI, B. E.; SOARES, A. da S.; OLIVEIRA, A. E. de. |
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Afiliação: |
PEDRO AUGUSTO DE OLIVEIRA MORAIS, UFG; DIEGO MENDES DE SOUZA, CNPAF; BEATA EMOKE MADARI, CNPAF; ANDERSON DA SILVA SOARES, UFG; ANSELMO ELCANA DE OLIVEIRA, UFG. |
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Título: |
Using image analysis to estimate the soil organic carbon content. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
Microchemical Journal, v. 147, p. 775-781, June 2019. |
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ISSN: |
0026-265X |
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DOI: |
10.1016/j.microc.2019.03.070 |
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Idioma: |
Inglês |
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Conteúdo: |
Soil test for organic carbon content using the Walkley-Black standard method is a laborious task that takes almost 5 working days to report the results. In order to improve lab analysis efficiency, a new analytical method using digital images is proposed. Using multivariate image analysis (MIA) soil organic carbon (SOC) contents can be determined in<3 days. The MIA method for SOC was developed using 177 soil samples collected from 3 regions of Brazil (North, West Central, and Northeast). Digital images of soil samples were correlated with the organic carbon contents determined by the Walkley-Black standard method using multivariate regression algorithms. In the end, MIA model employing a machine learn approach using least squares support vector machine (LS-SVM), presented an excellent correlation, r2 > 0.93, between image data and SOC contents measured by the standard analytical method. The proposed MIA method is eco-friendly, cheap, fast, and a clean alternative that can be employed by soil testing laboratories for measuring SOC contents. |
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Thesagro: |
Carbono; Solo Orgânico. |
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Thesaurus Nal: |
Chemometrics; Green chemistry; Soil test values. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 01785naa a2200253 a 4500
001 2108416
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008 2019 bl uuuu u00u1 u #d
022 $a0026-265X
024 7 $a10.1016/j.microc.2019.03.070$2DOI
100 1 $aMORAIS, P. A. de O.
245 $aUsing image analysis to estimate the soil organic carbon content.$h[electronic resource]
260 $c2019
520 $aSoil test for organic carbon content using the Walkley-Black standard method is a laborious task that takes almost 5 working days to report the results. In order to improve lab analysis efficiency, a new analytical method using digital images is proposed. Using multivariate image analysis (MIA) soil organic carbon (SOC) contents can be determined in<3 days. The MIA method for SOC was developed using 177 soil samples collected from 3 regions of Brazil (North, West Central, and Northeast). Digital images of soil samples were correlated with the organic carbon contents determined by the Walkley-Black standard method using multivariate regression algorithms. In the end, MIA model employing a machine learn approach using least squares support vector machine (LS-SVM), presented an excellent correlation, r2 > 0.93, between image data and SOC contents measured by the standard analytical method. The proposed MIA method is eco-friendly, cheap, fast, and a clean alternative that can be employed by soil testing laboratories for measuring SOC contents.
650 $aChemometrics
650 $aGreen chemistry
650 $aSoil test values
650 $aCarbono
650 $aSolo Orgânico
700 1 $aSOUZA, D. M. de
700 1 $aMADARI, B. E.
700 1 $aSOARES, A. da S.
700 1 $aOLIVEIRA, A. E. de
773 $tMicrochemical Journal$gv. 147, p. 775-781, June 2019.
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Embrapa Arroz e Feijão (CNPAF) |
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| 1. |  | KRESOVICH, S.; BARBAZUK, B.; BEDELL, J. A.; BORRELL, S.; BUELL, C. R.; BURKE, J.; CLIFTON, S.; CORDONNIER-PRATT, M.-M.; COX, S.; DAHLBERG, J.; ERPELDING, J.; FULTON, T. M.; FULTON, B.; FULTON, L.; GLINGLE, A. R.; HASH, C. T.; HUANG, Y.; JORDAN, D.; KLEIN, P. E.; KLEIN, R. R.; MAGALHAES, J.; McCOMBIE, R.; MOORE, P.; MULLET, J. E.; OZIAS-AKINS. P.; PATERSON, A. H.; PORTER, K.; PRATT, L.; ROE, B.; ROONEY, W.; SCHNABLE, P. S.; STELLY, D. M.; TUINSTRA, M.; WARE, D.; WAREK, W. Toward sequencing the sorghum genome. A U.S. National Science Foundation-Sponsored Workshop Report. Plant Physiology, Rockville, v. 138, n. 4, p. 1898-1902, 2005.| Tipo: Artigo em Periódico Indexado |
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