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Registro Completo |
Biblioteca(s): |
Embrapa Florestas. |
Data corrente: |
15/10/2018 |
Data da última atualização: |
15/10/2018 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
MELO, T. O.; TOMASI, J. D. C.; PIRES, O. A. B.; MARQUES, F. A.; HANSEL, F. A. |
Afiliação: |
Tamires O. Melo, Bolsista da Embrapa Florestas; Jéssica D. C. Tomasi, Bolsista da Embrapa Florestas; Osmar A. B. Pires, Bolsista da Embrapa Florestas; Francisco A. Marques, UFPR; FABRICIO AUGUSTO HANSEL, CNPF. |
Título: |
Simultaneous pyrolysis and trimethylsilylation with N-methyl - (trimethylsilyl) trifluoroacetamide for the characterisation of lignocellulosic materials from kraft pulping. |
Ano de publicação: |
2018 |
Fonte/Imprenta: |
Holzforschung, v. 72, n. 10, p. 851-862, Oct. 2018. |
DOI: |
doi.org/10.1515/hf-2017-0193 |
Idioma: |
Inglês |
Conteúdo: |
Simultaneous pyrolysis and trimethylsilylation (SPyT) with N-methyl-(trimethylsilyl)trifluoroacetamide (MSTFA) was used to characterise lignocellulosic materials from pine and eucalyptus obtained by kraft pulping. This approach protects the carboxyl groups and helps preserve the original structure of phenolic products during analytical pyrolysis, and so that pyrolysis and derivatisation occur simultaneously and the fragments of underivatised compounds are also silylatated. The SPyT products are representative for the structures present in carbohydrates and lignin of the investigated materials. The method is also suited to semi-quantitative evaluation also in terms of detection of condensed lignin structures in pulps and kraft lignins. |
Palavras-Chave: |
AMDIS; Automated mass spectral deconvolution and identification system; Derivatisation; Espectometria; Kováts retention index; Monomers; Silylation. |
Thesagro: |
Biomassa; Cromatografia Gasosa. |
Thesaurus Nal: |
Biomass; Gas chromatography; Mass spectrometry. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
Marc: |
LEADER 01798naa a2200325 a 4500 001 2097343 005 2018-10-15 008 2018 bl uuuu u00u1 u #d 024 7 $adoi.org/10.1515/hf-2017-0193$2DOI 100 1 $aMELO, T. O. 245 $aSimultaneous pyrolysis and trimethylsilylation with N-methyl - (trimethylsilyl) trifluoroacetamide for the characterisation of lignocellulosic materials from kraft pulping.$h[electronic resource] 260 $c2018 520 $aSimultaneous pyrolysis and trimethylsilylation (SPyT) with N-methyl-(trimethylsilyl)trifluoroacetamide (MSTFA) was used to characterise lignocellulosic materials from pine and eucalyptus obtained by kraft pulping. This approach protects the carboxyl groups and helps preserve the original structure of phenolic products during analytical pyrolysis, and so that pyrolysis and derivatisation occur simultaneously and the fragments of underivatised compounds are also silylatated. The SPyT products are representative for the structures present in carbohydrates and lignin of the investigated materials. The method is also suited to semi-quantitative evaluation also in terms of detection of condensed lignin structures in pulps and kraft lignins. 650 $aBiomass 650 $aGas chromatography 650 $aMass spectrometry 650 $aBiomassa 650 $aCromatografia Gasosa 653 $aAMDIS 653 $aAutomated mass spectral deconvolution and identification system 653 $aDerivatisation 653 $aEspectometria 653 $aKováts retention index 653 $aMonomers 653 $aSilylation 700 1 $aTOMASI, J. D. C. 700 1 $aPIRES, O. A. B. 700 1 $aMARQUES, F. A. 700 1 $aHANSEL, F. A. 773 $tHolzforschung$gv. 72, n. 10, p. 851-862, Oct. 2018.
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Registro original: |
Embrapa Florestas (CNPF) |
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Registro Completo
Biblioteca(s): |
Embrapa Solos. |
Data corrente: |
05/11/2019 |
Data da última atualização: |
11/11/2021 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
PINHEIRO, H. S. K.; BARBOSA, T. P. R.; ANTUNES, M. A. H.; CARVALHO, D. C. de; NUMMER, A. R.; CARVALHO JUNIOR, W. de; CHAGAS, C. da S.; FERNANDES-FILHO, E. I.; PEREIRA, M. G. |
Afiliação: |
HELENA S. K. PINHEIRO, UFRRJ; THERESA P. R. BARBOSA, UFRRJ; MAURO A. H. ANTUNES, UFRRJ; DANIEL COSTA DE CARVALHO, UnB; ALEXIS R. NUMMER, UFRRJ; WALDIR DE CARVALHO JUNIOR, CNPS; CESAR DA SILVA CHAGAS, CNPS; ELPÍDIO I. FERNANDES-FILHO, UFV; MARCOS GERVASIO PEREIRA, UFRRJ. |
Título: |
Assessment of phytoecological variability by red-edge spectral indices and soil-landscape relationships. |
Ano de publicação: |
2019 |
Fonte/Imprenta: |
Remote Sensing, v. 11, n. 20, 2448, 2019. |
DOI: |
https://doi.org/10.3390/rs11202448 |
Idioma: |
Inglês |
Conteúdo: |
There is a relation of vegetation physiognomies with soil and geological conditions that can be represented spatially with the support of remote sensing data. The goal of this research was to map vegetation physiognomies in a mountainous area by using Sentinel-2 Multispectral Instrument (MSI) data and morphometrical covariates through data mining techniques. The research was based on red-edge (RE) bands, and indices, to classify phytophysiognomies at two taxonomic levels. The input data was pixel sampled based on field sample sites. Data mining procedures comprised covariate selection and supervised classification through the Random Forest model. Results showed the potential of bands 3, 5, and 6 to map phytophysiognomies for both seasons, as well as Green Chlorophyll (CLg) and SAVI indices. NDVI indices were important, particularly those calculated with bands 6, 7, 8, and 8A, which were placed at the RE position. The model performance showed reasonable success to Kappa index 0.72 and 0.56 for the first and fifth taxonomic level, respectively. The model presented confusion between Broadleaved dwarf-forest, Parkland Savanna, and Bushy grassland. Savanna formations occurred variably in the area while Bushy grasslands strictly occur in certain landscape positions. Broadleaved forests presented the best performance (first taxonomic level), and among its variation (fifth level) the model could precisely capture the pattern for those on deep soils from gneiss parent material. The approach was thus useful to capture intrinsic soil-plant relationships and its relation with remote sensing data, showing potential to map phytophysiognomies in two distinct taxonomic levels in poorly accessible areas. MenosThere is a relation of vegetation physiognomies with soil and geological conditions that can be represented spatially with the support of remote sensing data. The goal of this research was to map vegetation physiognomies in a mountainous area by using Sentinel-2 Multispectral Instrument (MSI) data and morphometrical covariates through data mining techniques. The research was based on red-edge (RE) bands, and indices, to classify phytophysiognomies at two taxonomic levels. The input data was pixel sampled based on field sample sites. Data mining procedures comprised covariate selection and supervised classification through the Random Forest model. Results showed the potential of bands 3, 5, and 6 to map phytophysiognomies for both seasons, as well as Green Chlorophyll (CLg) and SAVI indices. NDVI indices were important, particularly those calculated with bands 6, 7, 8, and 8A, which were placed at the RE position. The model performance showed reasonable success to Kappa index 0.72 and 0.56 for the first and fifth taxonomic level, respectively. The model presented confusion between Broadleaved dwarf-forest, Parkland Savanna, and Bushy grassland. Savanna formations occurred variably in the area while Bushy grasslands strictly occur in certain landscape positions. Broadleaved forests presented the best performance (first taxonomic level), and among its variation (fifth level) the model could precisely capture the pattern for those on deep soils from gneiss parent material. The a... Mostrar Tudo |
Thesagro: |
Conservação; Recurso Natural; Sensoriamento Remoto. |
Thesaurus NAL: |
Conservation areas; Remote sensing. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/204270/1/Assessment-of-phytoecological-variability-by-red-edge-spectral-indices-and-soil-landscape-relationships-2019.pdf
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Marc: |
LEADER 02609naa a2200289 a 4500 001 2113915 005 2021-11-11 008 2019 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.3390/rs11202448$2DOI 100 1 $aPINHEIRO, H. S. K. 245 $aAssessment of phytoecological variability by red-edge spectral indices and soil-landscape relationships.$h[electronic resource] 260 $c2019 520 $aThere is a relation of vegetation physiognomies with soil and geological conditions that can be represented spatially with the support of remote sensing data. The goal of this research was to map vegetation physiognomies in a mountainous area by using Sentinel-2 Multispectral Instrument (MSI) data and morphometrical covariates through data mining techniques. The research was based on red-edge (RE) bands, and indices, to classify phytophysiognomies at two taxonomic levels. The input data was pixel sampled based on field sample sites. Data mining procedures comprised covariate selection and supervised classification through the Random Forest model. Results showed the potential of bands 3, 5, and 6 to map phytophysiognomies for both seasons, as well as Green Chlorophyll (CLg) and SAVI indices. NDVI indices were important, particularly those calculated with bands 6, 7, 8, and 8A, which were placed at the RE position. The model performance showed reasonable success to Kappa index 0.72 and 0.56 for the first and fifth taxonomic level, respectively. The model presented confusion between Broadleaved dwarf-forest, Parkland Savanna, and Bushy grassland. Savanna formations occurred variably in the area while Bushy grasslands strictly occur in certain landscape positions. Broadleaved forests presented the best performance (first taxonomic level), and among its variation (fifth level) the model could precisely capture the pattern for those on deep soils from gneiss parent material. The approach was thus useful to capture intrinsic soil-plant relationships and its relation with remote sensing data, showing potential to map phytophysiognomies in two distinct taxonomic levels in poorly accessible areas. 650 $aConservation areas 650 $aRemote sensing 650 $aConservação 650 $aRecurso Natural 650 $aSensoriamento Remoto 700 1 $aBARBOSA, T. P. R. 700 1 $aANTUNES, M. A. H. 700 1 $aCARVALHO, D. C. de 700 1 $aNUMMER, A. R. 700 1 $aCARVALHO JUNIOR, W. de 700 1 $aCHAGAS, C. da S. 700 1 $aFERNANDES-FILHO, E. I. 700 1 $aPEREIRA, M. G. 773 $tRemote Sensing$gv. 11, n. 20, 2448, 2019.
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