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Registro Completo |
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Biblioteca(s): |
Embrapa Agrossilvipastoril; Embrapa Soja. |
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Data corrente: |
29/08/2011 |
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Data da última atualização: |
28/09/2011 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
BROGIN, R. L.; PAGHI, I. D.; RIBAS, L. N.; ALBUQUERQUE, C.; DOMIT, L. A.; MIRANDA, L. C.; FRONZA, V.; MELLO FILHO, O. L.; SILVA NETO, S. P.; FARIAS NETO, A. L.; UTUMI, M. M.; GODINHO, V. P. C.; BORTOLINI, C.; ROCHA, J. Q.; CARLIN, V. J.; ZAMBIASI, T. C. |
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Afiliação: |
RODRIGO LUIS BROGIN, CNPSO; I. D. PAGHI, ABRANGE; L. N. RIBAS, APROSOJA, MT.; C. ALBUQUERQUE, Coordenador do Programa Soja Livre; LINEU ALBERTO DOMIT, CPAMT; LUIZ CARLOS MIRANDA, SNTEEN Londrina; VANOLI FRONZA, CNPSO; ODILON LEMOS DE MELLO FILHO, CNPSO; SEBASTIAO PEDRO DA SILVA NETO, CPAC; AUSTECLINIO LOPES DE FARIAS NETO, CPAMT; MARLEY MARICO UTUMI, CPAF-RO; VICENTE DE PAULO CAMPOS GODINHO, CPAF-RO; C. BORTOLINI, Fundaçao Rio Verde; J. Q. ROCHA, CPAF-RO; V. J. CARLIN, Agrodinâmica Pesquisa Agropecuária; T. C. ZAMBIASI, AgroLab. |
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Título: |
Programa Soja Livre - avaliação de cultivares de soja convencionais da Embrapa no Mato Grosso - safra 2010/11. |
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Ano de publicação: |
2011 |
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Fonte/Imprenta: |
In: REUNIÃO DE PESQUISA DE SOJA DA REGIÃO CENTRAL DO BRASIL, 32., 2011, São Pedro, SP. Resumos expandidos... Londrina: Embrapa Soja, 2011. p. 236-239. ditado por Adilson de Oliveira Junior, Odilon Ferreira Saraiva, Regina Maria Villas Bôas de Campos Leite. |
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Idioma: |
Português |
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Palavras-Chave: |
Soja convencional. |
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Thesagro: |
Soja; Variedade. |
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Thesaurus Nal: |
Cultivars; Soybeans; Varieties. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/40709/1/broginp.236-239.pdf
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/47483/1/2011RA06.pdf
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Marc: |
LEADER 01210nam a2200349 a 4500
001 1899131
005 2011-09-28
008 2011 bl uuuu u00u1 u #d
100 1 $aBROGIN, R. L.
245 $aPrograma Soja Livre - avaliação de cultivares de soja convencionais da Embrapa no Mato Grosso - safra 2010/11.$h[electronic resource]
260 $aIn: REUNIÃO DE PESQUISA DE SOJA DA REGIÃO CENTRAL DO BRASIL, 32., 2011, São Pedro, SP. Resumos expandidos... Londrina: Embrapa Soja, 2011. p. 236-239. ditado por Adilson de Oliveira Junior, Odilon Ferreira Saraiva, Regina Maria Villas Bôas de Campos Leite.$c2011
650 $aCultivars
650 $aSoybeans
650 $aVarieties
650 $aSoja
650 $aVariedade
653 $aSoja convencional
700 1 $aPAGHI, I. D.
700 1 $aRIBAS, L. N.
700 1 $aALBUQUERQUE, C.
700 1 $aDOMIT, L. A.
700 1 $aMIRANDA, L. C.
700 1 $aFRONZA, V.
700 1 $aMELLO FILHO, O. L.
700 1 $aSILVA NETO, S. P.
700 1 $aFARIAS NETO, A. L.
700 1 $aUTUMI, M. M.
700 1 $aGODINHO, V. P. C.
700 1 $aBORTOLINI, C.
700 1 $aROCHA, J. Q.
700 1 $aCARLIN, V. J.
700 1 $aZAMBIASI, T. C.
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Registro original: |
Embrapa Soja (CNPSO) |
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Biblioteca |
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Registro |
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Registro Completo
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Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
04/01/2023 |
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Data da última atualização: |
24/03/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 5 |
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Autoria: |
NOVOTNY, E. H.; GARCIA, R. H. S.; AZEVEDO, E. R. de. |
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Afiliação: |
ETELVINO HENRIQUE NOVOTNY, CNPS; RODRIGO H. S. GARCIA, UNIVERSIDADE DE SÃO PAULO; EDUARDO R. DE AZEVEDO, UNIVERSIDADE DE SÃO PAULO. |
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Título: |
Pulse sequence induced variability combined with multivariate analysis as a potential tool for 13C solid-state NMR signals separation, quantification, and classification. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Journal of Magnetic Resonance Open, v. 14/15, 100089, Jun. 2023. |
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DOI: |
https://doi.org/10.1016/j.jmro.2022.100089 |
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Idioma: |
Inglês |
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Conteúdo: |
Multivariate Curve Resolution (MCR) is a multivariate analysis procedure commonly used to analyze spectroscopic data providing the number of components coexisting in a chemical system, the pure spectra of the components as well as their concentration profiles. Usually, this procedure relies on the existence of distinct systematic variability among spectra of the different samples, which is provided by different sources of variation associated to differences in samples origin, composition, physical chemical treatment, etc. In solid-state NMR, MCR has been also used as a post-processing method for spectral denoising or editing based on a given NMR property. In this type of use, the variability is induced by the incrementation of a given parameter in the pulse-sequence, which encodes the separation property in the acquired spectra. In this article we further explore the idea of using a specific pulse sequence to induce a controlled variability in the 13C solid-state NMR spectra and then apply MCR to separate the pure spectra of the components according to the properties associated to the induced variability. We build upon a previous study of sugarcane bagasse where a series of 13C solid-state NMR spectra acquired with the Torchia-T1 CPMAS pulse sequence, with varying relaxation periods, was combined with different sample treatments, to estimate individual 13C solid-state NMR spectra of different molecular components (cellulose, xylan and lignin). Using the same pulse sequence, we show other application examples to demonstrate the potentiality, parameter optimization and/or establish the limitations of the procedure. As a first proof of principle, we apply the approach to commercial semicrystalline medium density polyethylene (MDPE) and polyether ether ketone (PEEK) providing the estimation of the individual 13C ssNMR spectra of the polymer chains in the amorphous (short ) and crystalline (long ) domains. The analysis also provided the relative intensities of each estimated pure spectra, which are related to the characteristic decays of the amorphous and crystalline domain fractions. We also apply the analysis to isotactic poly (1-butene) (iPB-I) as an example in which the induced variability occurs due to the mobility difference between the polymer backbone and side-chains. A jack-knifing procedure and a student t text allow us to stablish the minimum number of spectra and the range of relaxation periods that need to be used to achieve a precise estimation of the individual pure spectra and their relative intensities. A detail discussion about possible drawbacks, applications to more complex systems, and potential extensions to other type of induced variability are also presented. MenosMultivariate Curve Resolution (MCR) is a multivariate analysis procedure commonly used to analyze spectroscopic data providing the number of components coexisting in a chemical system, the pure spectra of the components as well as their concentration profiles. Usually, this procedure relies on the existence of distinct systematic variability among spectra of the different samples, which is provided by different sources of variation associated to differences in samples origin, composition, physical chemical treatment, etc. In solid-state NMR, MCR has been also used as a post-processing method for spectral denoising or editing based on a given NMR property. In this type of use, the variability is induced by the incrementation of a given parameter in the pulse-sequence, which encodes the separation property in the acquired spectra. In this article we further explore the idea of using a specific pulse sequence to induce a controlled variability in the 13C solid-state NMR spectra and then apply MCR to separate the pure spectra of the components according to the properties associated to the induced variability. We build upon a previous study of sugarcane bagasse where a series of 13C solid-state NMR spectra acquired with the Torchia-T1 CPMAS pulse sequence, with varying relaxation periods, was combined with different sample treatments, to estimate individual 13C solid-state NMR spectra of different molecular components (cellulose, xylan and lignin). Using the same pulse sequence, ... Mostrar Tudo |
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Palavras-Chave: |
13C Solid-state NMR; Análise multivariada de dados; Multivariate curve resolution; Multivariate data analysis; Polímeros semicristalinos; Semicrystalline polymers; Spectral editing. |
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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/doc/1150609/1/Pulse-sequence-induced-variability-combined-with-multivariate-analysis-2023.pdf
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Marc: |
LEADER 03628naa a2200241 a 4500
001 2150609
005 2023-03-24
008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.jmro.2022.100089$2DOI
100 1 $aNOVOTNY, E. H.
245 $aPulse sequence induced variability combined with multivariate analysis as a potential tool for 13C solid-state NMR signals separation, quantification, and classification.$h[electronic resource]
260 $c2023
520 $aMultivariate Curve Resolution (MCR) is a multivariate analysis procedure commonly used to analyze spectroscopic data providing the number of components coexisting in a chemical system, the pure spectra of the components as well as their concentration profiles. Usually, this procedure relies on the existence of distinct systematic variability among spectra of the different samples, which is provided by different sources of variation associated to differences in samples origin, composition, physical chemical treatment, etc. In solid-state NMR, MCR has been also used as a post-processing method for spectral denoising or editing based on a given NMR property. In this type of use, the variability is induced by the incrementation of a given parameter in the pulse-sequence, which encodes the separation property in the acquired spectra. In this article we further explore the idea of using a specific pulse sequence to induce a controlled variability in the 13C solid-state NMR spectra and then apply MCR to separate the pure spectra of the components according to the properties associated to the induced variability. We build upon a previous study of sugarcane bagasse where a series of 13C solid-state NMR spectra acquired with the Torchia-T1 CPMAS pulse sequence, with varying relaxation periods, was combined with different sample treatments, to estimate individual 13C solid-state NMR spectra of different molecular components (cellulose, xylan and lignin). Using the same pulse sequence, we show other application examples to demonstrate the potentiality, parameter optimization and/or establish the limitations of the procedure. As a first proof of principle, we apply the approach to commercial semicrystalline medium density polyethylene (MDPE) and polyether ether ketone (PEEK) providing the estimation of the individual 13C ssNMR spectra of the polymer chains in the amorphous (short ) and crystalline (long ) domains. The analysis also provided the relative intensities of each estimated pure spectra, which are related to the characteristic decays of the amorphous and crystalline domain fractions. We also apply the analysis to isotactic poly (1-butene) (iPB-I) as an example in which the induced variability occurs due to the mobility difference between the polymer backbone and side-chains. A jack-knifing procedure and a student t text allow us to stablish the minimum number of spectra and the range of relaxation periods that need to be used to achieve a precise estimation of the individual pure spectra and their relative intensities. A detail discussion about possible drawbacks, applications to more complex systems, and potential extensions to other type of induced variability are also presented.
653 $a13C Solid-state NMR
653 $aAnálise multivariada de dados
653 $aMultivariate curve resolution
653 $aMultivariate data analysis
653 $aPolímeros semicristalinos
653 $aSemicrystalline polymers
653 $aSpectral editing
700 1 $aGARCIA, R. H. S.
700 1 $aAZEVEDO, E. R. de
773 $tJournal of Magnetic Resonance Open$gv. 14/15, 100089, Jun. 2023.
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Embrapa Solos (CNPS) |
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