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Registros recuperados : 6 | |
1. | | ALFARO. M. R.; NASCIMENTO, C. W. A. do; BIONDI, C. M.; SILVA, Y. J. A. B. da; SILVA, Y. J. A. B. da; ACCIOLY, A. M. de A.; MONTERO, A.; UGARTE, O. M.; ESTEVEZ, J. Rare-earth-element geochemistry in soils developed in different geological settings of Cuba. Catena, November, 2017. Biblioteca(s): Embrapa Mandioca e Fruticultura. |
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2. | | SILVA, R. J. A. B. da; SILVA, Y. J. A. B. da; VAN STRAATEN, P.; NASCIMENTO, C. W. A. do; BIONDI, C. M.; SILVA, Y. J. A. B. da; ARAUJO FILHO, J. C. de. Influence of parent material on soil chemical characteristics in a semi-arid tropical region of Northeast Brazil. Environmental Monitoring and Assessment, v. 194, n. 5, 331, May 2022. Biblioteca(s): Embrapa Solos. |
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3. | | MAIA, A. J.; NASCIMENTO, R. C.; SILVA, Y. J. A. B. da; NASCIMENTO, C. W. A. do; MENDES, W. de S.; VERAS NETO, J. G.; ARAUJO FILHO, J. C. de; TIECHER, T.; SILVA, Y. J. A. B. da. Near-infrared spectroscopy for prediction of potentially toxic elements in soil and sediments from a semiarid and coastal humid tropical transitional river basin. Microchemical Journal, v. 179, 107544, Aug. 2022. Biblioteca(s): Embrapa Solos. |
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5. | | ALFARO, M. R.; MONTERO, A.; UGARTE, O. M.; NASCIMENTO, C. W. A. do; ACCIOLY, A. M. de A.; BIONDI, C. M.; SILVA, Y. J. A. B. da. Background concentrations and reference values for heavy metals in soils of Cuba. Environmental Monitoring and Assessment, v.187, p. 4198, 2015. Biblioteca(s): Embrapa Mandioca e Fruticultura. |
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6. | | BITTAR, S. M. B.; STRAATEN, P. V.; ACCIOLY, A. M. de A.; SILVA, Y. J. A. B. da; PINHEIRO, T. S. de M.; MORAES, F. G. D. de; SILVA, A, J. da. Caracterização física, química e mineralógica do estéril da mineração de gipsita visando a recuperação ambiental. In: CONGRESSO BRASILEIRO DE CIÊNCIA DO SOLO, 32., 2009, Fortaleza. O solo e a produção de bioenergia: perspectivas e desafios: anais. Fortaleza: SBCS: UFC, 2009. 1 CD-ROM. Trabalho 1270. Biblioteca(s): Embrapa Mandioca e Fruticultura. |
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Registros recuperados : 6 | |
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| Acesso ao texto completo restrito à biblioteca da Embrapa Solos. Para informações adicionais entre em contato com cnps.biblioteca@embrapa.br. |
Registro Completo
Biblioteca(s): |
Embrapa Solos. |
Data corrente: |
05/05/2022 |
Data da última atualização: |
05/05/2022 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
MAIA, A. J.; NASCIMENTO, R. C.; SILVA, Y. J. A. B. da; NASCIMENTO, C. W. A. do; MENDES, W. de S.; VERAS NETO, J. G.; ARAUJO FILHO, J. C. de; TIECHER, T.; SILVA, Y. J. A. B. da. |
Afiliação: |
ANGELO JAMIL MAIA, UFRPE; RENNAN CABRAL NASCIMENTO, UFRPE; YGOR JACQUES AGRA BEZERRA DA SILVA, UFRPE; CLÍSTENES WILLIAMS ARAÚJO DO NASCIMENTO, UFRPE; WANDERSON DE SOUSA MENDES, LEIBNIZ CENTRE FOR AGRICULTURAL LANDSCAPE RESEARCH (ZALF); JOSÉ GERMANO VERAS NETO, UFPB; JOSE COELHO DE ARAUJO FILHO, CNPS; TALES TIECHER, UFRGS; YURI JACQUES AGRA BEZERRA DA SILVA, UFPI. |
Título: |
Near-infrared spectroscopy for prediction of potentially toxic elements in soil and sediments from a semiarid and coastal humid tropical transitional river basin. |
Ano de publicação: |
2022 |
Fonte/Imprenta: |
Microchemical Journal, v. 179, 107544, Aug. 2022. |
DOI: |
https://doi.org/10.1016/j.microc.2022.107544 |
Idioma: |
Inglês |
Conteúdo: |
The input of potentially toxic elements (PTE) in river basins is a major environmental problem. PTE concentrations are determined using traditional analytical methods, which are mostly time consuming, expensive, and reliant on hazardous reagents. An alternative method to traditional chemical analysis is near-infrared (NIR) spectroscopy, which allows for the quantification of several PTEs through chemometric models. The aim of this study is to apply NIR spectroscopy for the prediction of PTE concentrations in the Ipojuca river basin, an area exposed to potential pollutant activities. We collected 145 soil samples and 33 bed sediments samples. All samples were ground and sieved at <- 100-um, and then analyzed for Al, Ce, Co, Cr, Fe, La, Mn, Mo, Ni, Pr, Sc, Sm, Sn, Sr, Th, Ti, V, and Y concentrations by inductively coupled plasma optical emission spectroscopy. Spectral data were retrieved from all samples using an FT-IR/NIR spectrometer in the range of 1000 - 2500 nm. The samples were subdivided into two sets: (i) soil and (ii) soil and bed sediments. Prediction models were built using the random forest algorithm (RF) and partial least squares regression (PLS) combined with different spectral preprocessing methods. Satisfactory results were obtained for Al, Ti, Sc, and V, and reasonable results for Fe, La, Mn, Pr, Sm, Sr, and Th. Our findings indicate that RF models obtains generally better results than PLS, and also that NIR spectroscopy can be a viable alternative assessment tool even in large areas with geochemical and pedological heterogeneity. MenosThe input of potentially toxic elements (PTE) in river basins is a major environmental problem. PTE concentrations are determined using traditional analytical methods, which are mostly time consuming, expensive, and reliant on hazardous reagents. An alternative method to traditional chemical analysis is near-infrared (NIR) spectroscopy, which allows for the quantification of several PTEs through chemometric models. The aim of this study is to apply NIR spectroscopy for the prediction of PTE concentrations in the Ipojuca river basin, an area exposed to potential pollutant activities. We collected 145 soil samples and 33 bed sediments samples. All samples were ground and sieved at <- 100-um, and then analyzed for Al, Ce, Co, Cr, Fe, La, Mn, Mo, Ni, Pr, Sc, Sm, Sn, Sr, Th, Ti, V, and Y concentrations by inductively coupled plasma optical emission spectroscopy. Spectral data were retrieved from all samples using an FT-IR/NIR spectrometer in the range of 1000 - 2500 nm. The samples were subdivided into two sets: (i) soil and (ii) soil and bed sediments. Prediction models were built using the random forest algorithm (RF) and partial least squares regression (PLS) combined with different spectral preprocessing methods. Satisfactory results were obtained for Al, Ti, Sc, and V, and reasonable results for Fe, La, Mn, Pr, Sm, Sr, and Th. Our findings indicate that RF models obtains generally better results than PLS, and also that NIR spectroscopy can be a viable alternative assessment ... Mostrar Tudo |
Palavras-Chave: |
Aprendizado de máquina; Contamination; Espectroscopia; Gestão de recursos hídricos; Hydrological monitoring; Infravermelho; Machine learning; Monitoramento hidrológico; Soil sensing; Water resources management. |
Thesagro: |
Contaminação. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
Marc: |
LEADER 02775naa a2200361 a 4500 001 2142678 005 2022-05-05 008 2022 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.1016/j.microc.2022.107544$2DOI 100 1 $aMAIA, A. J. 245 $aNear-infrared spectroscopy for prediction of potentially toxic elements in soil and sediments from a semiarid and coastal humid tropical transitional river basin.$h[electronic resource] 260 $c2022 520 $aThe input of potentially toxic elements (PTE) in river basins is a major environmental problem. PTE concentrations are determined using traditional analytical methods, which are mostly time consuming, expensive, and reliant on hazardous reagents. An alternative method to traditional chemical analysis is near-infrared (NIR) spectroscopy, which allows for the quantification of several PTEs through chemometric models. The aim of this study is to apply NIR spectroscopy for the prediction of PTE concentrations in the Ipojuca river basin, an area exposed to potential pollutant activities. We collected 145 soil samples and 33 bed sediments samples. All samples were ground and sieved at <- 100-um, and then analyzed for Al, Ce, Co, Cr, Fe, La, Mn, Mo, Ni, Pr, Sc, Sm, Sn, Sr, Th, Ti, V, and Y concentrations by inductively coupled plasma optical emission spectroscopy. Spectral data were retrieved from all samples using an FT-IR/NIR spectrometer in the range of 1000 - 2500 nm. The samples were subdivided into two sets: (i) soil and (ii) soil and bed sediments. Prediction models were built using the random forest algorithm (RF) and partial least squares regression (PLS) combined with different spectral preprocessing methods. Satisfactory results were obtained for Al, Ti, Sc, and V, and reasonable results for Fe, La, Mn, Pr, Sm, Sr, and Th. Our findings indicate that RF models obtains generally better results than PLS, and also that NIR spectroscopy can be a viable alternative assessment tool even in large areas with geochemical and pedological heterogeneity. 650 $aContaminação 653 $aAprendizado de máquina 653 $aContamination 653 $aEspectroscopia 653 $aGestão de recursos hídricos 653 $aHydrological monitoring 653 $aInfravermelho 653 $aMachine learning 653 $aMonitoramento hidrológico 653 $aSoil sensing 653 $aWater resources management 700 1 $aNASCIMENTO, R. C. 700 1 $aSILVA, Y. J. A. B. da 700 1 $aNASCIMENTO, C. W. A. do 700 1 $aMENDES, W. de S. 700 1 $aVERAS NETO, J. G. 700 1 $aARAUJO FILHO, J. C. de 700 1 $aTIECHER, T. 700 1 $aSILVA, Y. J. A. B. da 773 $tMicrochemical Journal$gv. 179, 107544, Aug. 2022.
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