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 | Acesso ao texto completo restrito à biblioteca da Embrapa Florestas. Para informações adicionais entre em contato com cnpf.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
08/04/2016 |
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Data da última atualização: |
11/04/2016 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
HORNUNG, P. S.; OLIVEIRA, C. S. de; LAZZAROTTO, M.; LAZZAROTTO, S. R. da S.; SCHNITZLER, E. |
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Afiliação: |
Polyanna Silveira Hornung, UEPG; Cristina Soltovski de Oliveira, UEPG; MARCELO LAZZAROTTO, CNPF; Simone Rosa da Silveira Lazzarotto, UEPG; Egon Schnitzler, UEPG. |
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Título: |
Investigation of the photo-oxidation of cassava starch granules: thermal, rheological and structural behaviour. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
Journal of Thermal Analysis and Calorimetry, v. 123, n. 3, p. 2129-2137, Mar. 2016. |
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DOI: |
10.1007/s10973-015-4706-x |
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Idioma: |
Inglês |
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Conteúdo: |
In this study, the combined and simultaneous actions of H2O2 and UV radiation on cassava starch granules were applied and the thermal, rheological, structural and colour properties were investigated. Samples of native cassava starch were oxidised with standard H2O2 solutions (0.1, 0.2 and 0.5 mol L-1) and exposed for 1 h under UV light (UVC radiation with k = 256 nm), with constant stirring. The solutions were subsequently filtered, washed, dried and analysed. The thermogravimetric curves showed similar behaviour, with three main mass losses and an increase in the thermal stability of each sample. The oxidative modification performed caused a strong decrease in the setback and final viscosity parameters (RVA), a gradual decrease in the gelatinisation enthalpy (DSC) and relative crystallinity (XRD) and significant differences in the average roughness of the granules (NC-AFM). The X-ray diffraction powder patterns displayed the ??A?? type for all the starch granules. The colour parameters showed a decrease in the -a* value (trend to green) for all the treated samples. |
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Palavras-Chave: |
Análise térmica; Difração de raio X; Peróxido hidrogenado. |
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Thesagro: |
Amido; Mandioca. |
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Thesaurus Nal: |
Cassava starch; Hydrogen peroxide; Thermal analysis; Ultraviolet radiation; X-ray diffraction. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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Marc: |
LEADER 02034naa a2200301 a 4500
001 2042926
005 2016-04-11
008 2016 bl uuuu u00u1 u #d
024 7 $a10.1007/s10973-015-4706-x$2DOI
100 1 $aHORNUNG, P. S.
245 $aInvestigation of the photo-oxidation of cassava starch granules$bthermal, rheological and structural behaviour.$h[electronic resource]
260 $c2016
520 $aIn this study, the combined and simultaneous actions of H2O2 and UV radiation on cassava starch granules were applied and the thermal, rheological, structural and colour properties were investigated. Samples of native cassava starch were oxidised with standard H2O2 solutions (0.1, 0.2 and 0.5 mol L-1) and exposed for 1 h under UV light (UVC radiation with k = 256 nm), with constant stirring. The solutions were subsequently filtered, washed, dried and analysed. The thermogravimetric curves showed similar behaviour, with three main mass losses and an increase in the thermal stability of each sample. The oxidative modification performed caused a strong decrease in the setback and final viscosity parameters (RVA), a gradual decrease in the gelatinisation enthalpy (DSC) and relative crystallinity (XRD) and significant differences in the average roughness of the granules (NC-AFM). The X-ray diffraction powder patterns displayed the ??A?? type for all the starch granules. The colour parameters showed a decrease in the -a* value (trend to green) for all the treated samples.
650 $aCassava starch
650 $aHydrogen peroxide
650 $aThermal analysis
650 $aUltraviolet radiation
650 $aX-ray diffraction
650 $aAmido
650 $aMandioca
653 $aAnálise térmica
653 $aDifração de raio X
653 $aPeróxido hidrogenado
700 1 $aOLIVEIRA, C. S. de
700 1 $aLAZZAROTTO, M.
700 1 $aLAZZAROTTO, S. R. da S.
700 1 $aSCHNITZLER, E.
773 $tJournal of Thermal Analysis and Calorimetry$gv. 123, n. 3, p. 2129-2137, Mar. 2016.
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Registro original: |
Embrapa Florestas (CNPF) |
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Registro Completo
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Biblioteca(s): |
Embrapa Semiárido. |
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Data corrente: |
18/11/2019 |
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Data da última atualização: |
01/10/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
MIRANDA, R. de Q.; NÓBREGA, R. L. B.; MOURA, M. S. B. de; RAGHAVANE, S.; GALVÍNCIO, J. D. |
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Afiliação: |
Rodrigo de Queiroga Miranda, UFPE; Rodolfo Luiz Bezerra Nóbrega, University of Reading, Reading, UK; MAGNA SOELMA BESERRA DE MOURA, CPATSA; Srinivasan Raghavane, Texas A&M University, College Station, TX, USA; Josiclêda Domiciano Galvíncio, UFPE. |
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Título: |
Realistic and simplified models of plant and leaf area indices for a seasonally dry tropical forest. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
International Journal of Applied Earth Observation and Geoinformation, v. 85, 2020. |
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DOI: |
10.1016/j.jag.2019.101992 |
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Idioma: |
Inglês |
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Conteúdo: |
Leaf Area Index (LAI) models that consider all phenological stages have not been developed for the Caatinga, the largest seasonally dry tropical forest in South America. LAI models that are currently used show moderate to high covariance when compared to in situ data, but they often lack accuracy in the whole spectra of possible values and do not consider the impact that the stems and branches have over LAI estimates, which is of great influence in the Caatinga. In this study, we develop and assess PAI (Plant Area Index) and LAI models by using ground-based measurements and satellite (Landsat) data. The objective of this study was to create and test new empirical models using a multi-year and multi-source of reflectance data. The study was based on measurements of photosynthetic photon flux density (PPFD) from above and below the canopy during the periods of 2011?2012 and 2016?2018. Through iterative processing, we obtained more than a million candidate models for estimating PAI and LAI. To clean up the small discrepancies in the extremes of each interpolated series, we smoothed out the dataset by fitting a logarithmic equation with the PAI data and the inverse contribution of WAI (Wood Area Index) to PAI, that is the portion of PAI that is actually LAI (LAIC). LAIC can be calculated as follows: LAIC = 1 (WAI/PAI)). We subtracted the WAI values from the PAI to develop our in situ LAI dataset that was used for further analysis. Our in situ dataset was also used as a reference to compare our models with four other models used for the Caatinga, as well as the MODIS-derived LAI products (MCD15A3H/A2H). Our main findings were as follows: (i) Six models use NDVI (Normalized Difference Vegetation Index), SAVI (Soil-Adjusted Vegetation Index) and EVI (Enhanced Vegetation Index) as input, and performed well, with r2 ranging from 0.77 to 0.79 (PAI) and 0.76 to 0.81 (LAI), and RMSE with a minimum of 0.41m2m?2 (PAI) and 0.40m2m?2 (LAI). The SAVI models showed values 20% and 32% (PAI), and 21% and 15% (LAI) smaller than those found for the models that use EVI and NDVI, respectively; (ii) the other models (ten) use only two bands, and in contrast to the first six models, these new models may abstract other physical processes and components, such as leaves etiolation and increasing protochlorophyll. The developed models used the near-infrared band, and they varied only in relation to the inclusion of the red, green, and blue bands. (iii) All previously published models and MODIS-LAI underperformed against our calibrated models. Our study was able to provide several PAI and LAI models that realistically represent the phenology of the Caatinga. MenosLeaf Area Index (LAI) models that consider all phenological stages have not been developed for the Caatinga, the largest seasonally dry tropical forest in South America. LAI models that are currently used show moderate to high covariance when compared to in situ data, but they often lack accuracy in the whole spectra of possible values and do not consider the impact that the stems and branches have over LAI estimates, which is of great influence in the Caatinga. In this study, we develop and assess PAI (Plant Area Index) and LAI models by using ground-based measurements and satellite (Landsat) data. The objective of this study was to create and test new empirical models using a multi-year and multi-source of reflectance data. The study was based on measurements of photosynthetic photon flux density (PPFD) from above and below the canopy during the periods of 2011?2012 and 2016?2018. Through iterative processing, we obtained more than a million candidate models for estimating PAI and LAI. To clean up the small discrepancies in the extremes of each interpolated series, we smoothed out the dataset by fitting a logarithmic equation with the PAI data and the inverse contribution of WAI (Wood Area Index) to PAI, that is the portion of PAI that is actually LAI (LAIC). LAIC can be calculated as follows: LAIC = 1 (WAI/PAI)). We subtracted the WAI values from the PAI to develop our in situ LAI dataset that was used for further analysis. Our in situ dataset was also used as a reference... Mostrar Tudo |
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Palavras-Chave: |
Índice de área arborizada; Índice de área foliar; Plant Area Index; Semiárido. |
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Thesagro: |
Caatinga; Fenologia; Floresta Tropical. |
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Thesaurus NAL: |
Landsat; Phenology; Tropical forests. |
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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/204857/1/Realistic-and-simplified-models-of-plant-2019.pdf
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Marc: |
LEADER 03602naa a2200301 a 4500
001 2114427
005 2021-10-01
008 2020 bl uuuu u00u1 u #d
024 7 $a10.1016/j.jag.2019.101992$2DOI
100 1 $aMIRANDA, R. de Q.
245 $aRealistic and simplified models of plant and leaf area indices for a seasonally dry tropical forest.$h[electronic resource]
260 $c2020
520 $aLeaf Area Index (LAI) models that consider all phenological stages have not been developed for the Caatinga, the largest seasonally dry tropical forest in South America. LAI models that are currently used show moderate to high covariance when compared to in situ data, but they often lack accuracy in the whole spectra of possible values and do not consider the impact that the stems and branches have over LAI estimates, which is of great influence in the Caatinga. In this study, we develop and assess PAI (Plant Area Index) and LAI models by using ground-based measurements and satellite (Landsat) data. The objective of this study was to create and test new empirical models using a multi-year and multi-source of reflectance data. The study was based on measurements of photosynthetic photon flux density (PPFD) from above and below the canopy during the periods of 2011?2012 and 2016?2018. Through iterative processing, we obtained more than a million candidate models for estimating PAI and LAI. To clean up the small discrepancies in the extremes of each interpolated series, we smoothed out the dataset by fitting a logarithmic equation with the PAI data and the inverse contribution of WAI (Wood Area Index) to PAI, that is the portion of PAI that is actually LAI (LAIC). LAIC can be calculated as follows: LAIC = 1 (WAI/PAI)). We subtracted the WAI values from the PAI to develop our in situ LAI dataset that was used for further analysis. Our in situ dataset was also used as a reference to compare our models with four other models used for the Caatinga, as well as the MODIS-derived LAI products (MCD15A3H/A2H). Our main findings were as follows: (i) Six models use NDVI (Normalized Difference Vegetation Index), SAVI (Soil-Adjusted Vegetation Index) and EVI (Enhanced Vegetation Index) as input, and performed well, with r2 ranging from 0.77 to 0.79 (PAI) and 0.76 to 0.81 (LAI), and RMSE with a minimum of 0.41m2m?2 (PAI) and 0.40m2m?2 (LAI). The SAVI models showed values 20% and 32% (PAI), and 21% and 15% (LAI) smaller than those found for the models that use EVI and NDVI, respectively; (ii) the other models (ten) use only two bands, and in contrast to the first six models, these new models may abstract other physical processes and components, such as leaves etiolation and increasing protochlorophyll. The developed models used the near-infrared band, and they varied only in relation to the inclusion of the red, green, and blue bands. (iii) All previously published models and MODIS-LAI underperformed against our calibrated models. Our study was able to provide several PAI and LAI models that realistically represent the phenology of the Caatinga.
650 $aLandsat
650 $aPhenology
650 $aTropical forests
650 $aCaatinga
650 $aFenologia
650 $aFloresta Tropical
653 $aÍndice de área arborizada
653 $aÍndice de área foliar
653 $aPlant Area Index
653 $aSemiárido
700 1 $aNÓBREGA, R. L. B.
700 1 $aMOURA, M. S. B. de
700 1 $aRAGHAVANE, S.
700 1 $aGALVÍNCIO, J. D.
773 $tInternational Journal of Applied Earth Observation and Geoinformation$gv. 85, 2020.
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Embrapa Semiárido (CPATSA) |
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