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 | Acesso ao texto completo restrito à biblioteca da Embrapa Instrumentação. Para informações adicionais entre em contato com cnpdia.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Instrumentação. |
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Data corrente: |
24/03/2022 |
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Data da última atualização: |
24/06/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
NICOLODELLI, G.; HERCULANO, R. D.; MARANGONI, B. S.; RIBEIRO, M. C. S.; MILORI, D. M. B. P.; MENEGATTI, C. R. |
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Afiliação: |
DEBORA MARCONDES BASTOS PEREIRA, CNPDIA. |
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Título: |
Differentiation of latex biomembrane with collagen and non-collagen using laser induced breakdown spectroscopy. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Materials Today Communications, v. 30, 103099, 2022. |
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Páginas: |
1 - 7 |
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ISSN: |
2352-4928 |
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DOI: |
https://doi.org/10.1016/j.mtcomm.2021.103099 |
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Idioma: |
Inglês |
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Conteúdo: |
Studies on the interaction of a biomaterial with other components are important to enhance its positive effects and resolve its limitations. Therefore, the search for fast and low-cost techniques is essential for the analysis, characterization and differentiation of these biomaterials. Laser-induced breakdown spectroscopy (LIBS) is a multielemental, fast, with reduced analytical cost and environmentally clean technique that does not require the use of reagents for sample preparation. In this work, an elemental characterization of collagen and non-collagen latex samples was performed by LIBS technique. Multivariate analyzes, such as principal component analysis (PCA) and machine learning (ML) algorithms were applied on LIBS data in order to differentiate the classes. The main elements detected in the LIBS spectra examined were due to C, Fe, Mg, Ca, Na, H, N and K. The best results were achieved using LIBS spectral data from the specific range: 656.15–656.55 nm combined with 744.08–744.48 nm. The elements H and N were identified as the main discriminating factors between the samples studied. The leave one out cross-validation tests indicates that collagen latex biomembrane can be differentiated from non-collagen samples with 94.44% accuracy using the Weighted K-Nearest Neighbor algorithm. |
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Palavras-Chave: |
Chemometric analysis; LIBS; Machine learning algorithms; Natural latex. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02138naa a2200265 a 4500
001 2141291
005 2022-06-24
008 2022 bl uuuu u00u1 u #d
022 $a2352-4928
024 7 $ahttps://doi.org/10.1016/j.mtcomm.2021.103099$2DOI
100 1 $aNICOLODELLI, G.
245 $aDifferentiation of latex biomembrane with collagen and non-collagen using laser induced breakdown spectroscopy.$h[electronic resource]
260 $c2022
300 $a1 - 7
520 $aStudies on the interaction of a biomaterial with other components are important to enhance its positive effects and resolve its limitations. Therefore, the search for fast and low-cost techniques is essential for the analysis, characterization and differentiation of these biomaterials. Laser-induced breakdown spectroscopy (LIBS) is a multielemental, fast, with reduced analytical cost and environmentally clean technique that does not require the use of reagents for sample preparation. In this work, an elemental characterization of collagen and non-collagen latex samples was performed by LIBS technique. Multivariate analyzes, such as principal component analysis (PCA) and machine learning (ML) algorithms were applied on LIBS data in order to differentiate the classes. The main elements detected in the LIBS spectra examined were due to C, Fe, Mg, Ca, Na, H, N and K. The best results were achieved using LIBS spectral data from the specific range: 656.15–656.55 nm combined with 744.08–744.48 nm. The elements H and N were identified as the main discriminating factors between the samples studied. The leave one out cross-validation tests indicates that collagen latex biomembrane can be differentiated from non-collagen samples with 94.44% accuracy using the Weighted K-Nearest Neighbor algorithm.
653 $aChemometric analysis
653 $aLIBS
653 $aMachine learning algorithms
653 $aNatural latex
700 1 $aHERCULANO, R. D.
700 1 $aMARANGONI, B. S.
700 1 $aRIBEIRO, M. C. S.
700 1 $aMILORI, D. M. B. P.
700 1 $aMENEGATTI, C. R.
773 $tMaterials Today Communications$gv. 30, 103099, 2022.
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Registro original: |
Embrapa Instrumentação (CNPDIA) |
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Registro Completo
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Biblioteca(s): |
Embrapa Amazônia Oriental; Embrapa Solos. |
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Data corrente: |
28/11/2018 |
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Data da última atualização: |
11/11/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
C - 0 |
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Autoria: |
QUIJAS, S.; BOIT, B.; THONICKE, K.; MURRAY-TORTAROLO, G.; MWAMPAMBA, T.; SKUTSCH, M.; SIMÕES, M.; ASCARRUNZ, N.; PEÑA-CLAROS, M.; JONES, L.; ARETS, E.; JARAMILLO, V. J.; LAZOS, E.; TOLEDO, M.; MARTORANO, L. G.; FERRAZ, R. P. D.; BALVANERA, P. |
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Afiliação: |
SANDRA QUIJAS, CENTRO UNIVERSITARIO DE LA COSTA, UNIVERSIDAD DE GUADALAJARA, PUERTO VALLARTA, MEXICO; ALICE BOIT, INSTITUTE OF BIOCHEMISTRY AND BIOLOGY, UNIVERSITY OF POTSDAM, POTSDAM, GERMANY; KIRSTEN THONICKE, RESEARCH DOMAIN I EARTH SYSTEM ANALYSIS, POTSDAM INSTITUTE FOR CLIMATE IMPACT, RESEARCH, POTSDAM, GERMANY; GUILLERMO MURRAY-TORTAROLO, INSTITUTO DE INVESTIGACIONES EN ECOSISTEMAS Y SUSTENTABILIDAD, UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO, MORELIA, MEXICO; TUYENI MWAMPAMBA, INSTITUTO DE INVESTIGACIONES EN ECOSISTEMAS Y SUSTENTABILIDAD, UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO, MORELIA, MEXICO; MARGARET SKUTSCH, CENTRO DE INVESTIGACIONES EN GEOGRAFÍA AMBIENTAL, UNIVERSIDAD NACIONAL AUTÓNOMA DE, MÉXICO, MORELIA, MEXICO; MARGARETH GONCALVES SIMOES, CNPS; NATALY ASCARRUNZ, EXECUTIVE DIRECTION, INSTITUTO BOLIVIANO DE INVESTIGACIÓN FORESTAL, SANTA CRUZ DE LA SIERRA, BOLIVIA; MARIELOS PEÑA-CLAROS, FOREST ECOLOGY AND FOREST MANAGEMENT GROUP, WAGENINGEN UNIVERSITY, WAGENINGEN, THE NETHERLANDS; LAURENCE JONES, CENTRE FOR ECOLOGY & HYDROLOGY, NATURAL ENVIRONMENT RESEARCH COUNCIL, BANGOR, UNITED KINGDOM; ERIC ARETS, WAGENINGEN ENVIRONMENTAL RESEARCH, WAGENINGEN UR, WAGENINGEN, THE NETHERLANDS; VÍCTOR J. JARAMILLO, INSTITUTO DE INVESTIGACIONES EN ECOSISTEMAS Y SUSTENTABILIDAD, UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO, MORELIA, MEXICO; ELENA LAZOS, INSTITUTO DE INVESTIGACIONES SOCIALES, UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO, CIUDAD DE MEXICO, MEXICO; MARISOL TOLEDO, RESEARCH CORDINATION, INSTITUTO BOLIVIANO DE INVESTIGACIÓN FORESTAL, SANTA CRUZ DE LA SIERRA, BOLIVIA; LUCIETA GUERREIRO MARTORANO, CPATU; RODRIGO PECANHA DEMONTE FERRAZ, CNPS; PATRICIA BALVANERA, INSTITUTO DE INVESTIGACIONES EN ECOSISTEMAS Y SUSTENTABILIDAD, UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO, MORELIA, MEXICO. |
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Título: |
Modelling carbon stock and carbon sequestration ecosystem services for policy design: a comprehensive approach using a dynamic vegetation model. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
Ecosystems and People, v. 15, n. 1, p. 42-60, 2018. |
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DOI: |
https://doi.org/10.1080/26395908.2018.1542413 |
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Idioma: |
Inglês |
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Conteúdo: |
Ecosystem service (ES) models can only inform policy design adequately if they incorporate ecological processes. We used the Lund-Potsdam-Jena managed Land (LPJmL) model, to address following questions for Mexico, Bolivia and Brazilian Amazon: (i) How different are C stocks and C sequestration quantifications under standard (when soil and litter C and heterotrophic respiration are not considered) and comprehensive (including all C stock and heterotrophic respiration) approach? and (ii) How does the valuation of C stock and C sequestration differ in national payments for ES and global C funds or markets when comparing both approach? We found that up to 65% of C stocks have not been taken into account by neglecting to include C stored in soil and litter, resulting in gross underpayments (up to 500 times lower). Since emissions from heterotrophic respiration of organic material offset a large proportion of C gained through growth of living matter, we found that markets and decision-makers are inadvertently overestimating up to 100 times C sequestrated. New approaches for modelling C services relevant ecological process-based can help accounting for C in soil, litter and heterotrophic respiration and become important for the operationalization of agreements on climate change mitigation following the COP21 in 2015. |
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Palavras-Chave: |
Carbono do solo; Mercados globais de carbono; Modelo dinâmico de vegetação global; Pagamento por serviços ecossistêmicos; Respiração heterotrófica; Tomadores de decisão. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/187185/1/2018-056.pdf
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Marc: |
LEADER 02580naa a2200397 a 4500
001 2100223
005 2021-11-11
008 2018 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1080/26395908.2018.1542413$2DOI
100 1 $aQUIJAS, S.
245 $aModelling carbon stock and carbon sequestration ecosystem services for policy design$ba comprehensive approach using a dynamic vegetation model.$h[electronic resource]
260 $c2018
520 $aEcosystem service (ES) models can only inform policy design adequately if they incorporate ecological processes. We used the Lund-Potsdam-Jena managed Land (LPJmL) model, to address following questions for Mexico, Bolivia and Brazilian Amazon: (i) How different are C stocks and C sequestration quantifications under standard (when soil and litter C and heterotrophic respiration are not considered) and comprehensive (including all C stock and heterotrophic respiration) approach? and (ii) How does the valuation of C stock and C sequestration differ in national payments for ES and global C funds or markets when comparing both approach? We found that up to 65% of C stocks have not been taken into account by neglecting to include C stored in soil and litter, resulting in gross underpayments (up to 500 times lower). Since emissions from heterotrophic respiration of organic material offset a large proportion of C gained through growth of living matter, we found that markets and decision-makers are inadvertently overestimating up to 100 times C sequestrated. New approaches for modelling C services relevant ecological process-based can help accounting for C in soil, litter and heterotrophic respiration and become important for the operationalization of agreements on climate change mitigation following the COP21 in 2015.
653 $aCarbono do solo
653 $aMercados globais de carbono
653 $aModelo dinâmico de vegetação global
653 $aPagamento por serviços ecossistêmicos
653 $aRespiração heterotrófica
653 $aTomadores de decisão
700 1 $aBOIT, B.
700 1 $aTHONICKE, K.
700 1 $aMURRAY-TORTAROLO, G.
700 1 $aMWAMPAMBA, T.
700 1 $aSKUTSCH, M.
700 1 $aSIMÕES, M.
700 1 $aASCARRUNZ, N.
700 1 $aPEÑA-CLAROS, M.
700 1 $aJONES, L.
700 1 $aARETS, E.
700 1 $aJARAMILLO, V. J.
700 1 $aLAZOS, E.
700 1 $aTOLEDO, M.
700 1 $aMARTORANO, L. G.
700 1 $aFERRAZ, R. P. D.
700 1 $aBALVANERA, P.
773 $tEcosystems and People$gv. 15, n. 1, p. 42-60, 2018.
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