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Registro Completo |
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Biblioteca(s): |
Embrapa Territorial. |
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Data corrente: |
14/08/2017 |
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Data da última atualização: |
14/08/2017 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
TEIXEIRA, A. H. de C.; LEIVAS, J. F.; HERNANDEZ, F. B. T.; FRANCO, R. A. M. |
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Afiliação: |
ANTONIO HERIBERTO DE C TEIXEIRA, CPATSA; JANICE FREITAS LEIVAS, CNPM; FERNANDO BRAZ TANGERINO HERNANDEZ, UNESP; RENATO ALBERTO MOMESSO FRANCO, UNESP. |
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Título: |
Large-scale radiation and energy balances with Landsat 8 images and agrometeorological data in the Brazilian semiarid region. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Journal of Applied Remote Sensing, v. 11, n. 1, jan./mar. 2017. |
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Páginas: |
p. 016030-1-016030-15. |
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DOI: |
10.1117/1.JRS.11.016030. |
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Idioma: |
Inglês |
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Conteúdo: |
Aiming to subsidize the rational water resources management, four Landsat 8 (L8) images along different conditions of the year 2014 were used for modeling the radiation and energy balances in the mixed agroecosystems inside a Brazilian reference semiarid area. The SAFER algorithm was applied to calculate the latent heat flux (λE); net radiation (Rn) was acquired by the Slob equation; ground heat flux (G) was considered a fraction of Rn; and the sensible heat flux (H) was retrieved by residue in the energy balance equation. For classifying the vegetation, the surface resistance algorithm (SUREAL) was used to estimate the surface resistance to the water fluxes (rs) with threshold values for rs. Clearly, one could see higher λE values from irrigated crops (ICs) than those for natural vegetation (NV) with some situations of heat horizontal advection. The respective λE, H, and G average ratios to Rn for the ICs ecosystem were 64% to 79%, 18% to 28%, and 3%, respectively. For the NV ecosystem, the corresponding fractions were 4% to 37%, 60% to 94%, and 4%, respectively. The algorithms proved to have strong sensibility to quantifying the large-scale energy and mass exchanges by applying L8 images in mixed agroecosystems of semiarid environments. |
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Palavras-Chave: |
Energy partition; Latent heat flux; Net radiation; Sensible heat flux; Soil heat flux. |
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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/162671/1/4838.pdf
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Marc: |
LEADER 02062naa a2200241 a 4500
001 2073988
005 2017-08-14
008 2017 bl uuuu u00u1 u #d
024 7 $a10.1117/1.JRS.11.016030.$2DOI
100 1 $aTEIXEIRA, A. H. de C.
245 $aLarge-scale radiation and energy balances with Landsat 8 images and agrometeorological data in the Brazilian semiarid region.$h[electronic resource]
260 $c2017
300 $ap. 016030-1-016030-15.
520 $aAiming to subsidize the rational water resources management, four Landsat 8 (L8) images along different conditions of the year 2014 were used for modeling the radiation and energy balances in the mixed agroecosystems inside a Brazilian reference semiarid area. The SAFER algorithm was applied to calculate the latent heat flux (λE); net radiation (Rn) was acquired by the Slob equation; ground heat flux (G) was considered a fraction of Rn; and the sensible heat flux (H) was retrieved by residue in the energy balance equation. For classifying the vegetation, the surface resistance algorithm (SUREAL) was used to estimate the surface resistance to the water fluxes (rs) with threshold values for rs. Clearly, one could see higher λE values from irrigated crops (ICs) than those for natural vegetation (NV) with some situations of heat horizontal advection. The respective λE, H, and G average ratios to Rn for the ICs ecosystem were 64% to 79%, 18% to 28%, and 3%, respectively. For the NV ecosystem, the corresponding fractions were 4% to 37%, 60% to 94%, and 4%, respectively. The algorithms proved to have strong sensibility to quantifying the large-scale energy and mass exchanges by applying L8 images in mixed agroecosystems of semiarid environments.
653 $aEnergy partition
653 $aLatent heat flux
653 $aNet radiation
653 $aSensible heat flux
653 $aSoil heat flux
700 1 $aLEIVAS, J. F.
700 1 $aHERNANDEZ, F. B. T.
700 1 $aFRANCO, R. A. M.
773 $tJournal of Applied Remote Sensing$gv. 11, n. 1, jan./mar. 2017.
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Registro original: |
Embrapa Territorial (CNPM) |
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Biblioteca |
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Origem |
Tipo/Formato |
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Registro |
Volume |
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URL |
Voltar
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Registro Completo
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Biblioteca(s): |
Embrapa Pecuária Sudeste. |
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Data corrente: |
17/12/2019 |
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Data da última atualização: |
13/03/2023 |
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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: |
BERNARDO, A. P. da S.; SILVA, A. C. M. da; FRANCISCO, V. C.; RIBEIRO, F. A.; NASSU, R. T.; CALKINS, C. R.; NASCIMENTO, M. da S.; PFLANZER, S. B. |
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Afiliação: |
Ana Paula da Silva Bernardo, UNICAMP; Astrid Caroline Muniz da Silva, UNICAMP; Vanessa Cristina Francisco, UNESP; Felipe A. Ribeiro, University of Nebraska; RENATA TIEKO NASSU, CPPSE; Chris R. Calkins, University of Nebraska; Maristela da Silva do Nascimento, UNICAMP; Sérgio Bertelli Pflanzer, UNICAMP. |
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Título: |
Effects of freezing and thawing on microbiological and physical-chemical properties of dry-aged beef. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Meat Science, v. 161, 108003, mar. 2020. |
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Páginas: |
9 p. |
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DOI: |
https://doi.org/10.1016/j.meatsci.2019.108003 |
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Idioma: |
Inglês |
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Conteúdo: |
This study evaluated the effects of freezing, prior to and after dry aging, on the microbiological and physical-chemical quality of beef. Strip loins (n = 24) from 12 carcasses were assigned to four treatments: non-frozen dry aging (Dry); dry aging, steak fabrication, freezing and slow thawing (Dry + ST); freezing, fast thawing (FT; 20 °C/15 h) and dry aging (FT + Dry); freezing, slow thawing (ST; 4°C / 48h) and dry aging (ST + Dry). Freezing conditions were - 20°C/28 days and dry aging conditions were 2°C/70% relative humidity, for 28 days. Freezing prior to dry aging did not affect the microbial counts compared to Dry. However, FT + Dry and ST + Dry increased (16%) total process loss (P < .05) compared to Dry and Dry+ST. Moreover, freezing changed volatile compounds profile. Thus, freezing prior to dry aging was not a feasible process due to increased process loss, while freezing after dry aging was considered a viable alternative to preserve the steaks without compromising beef physical-chemical traits. |
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Palavras-Chave: |
Dry-aged beef; Microbiological beef quality. |
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Thesaurus NAL: |
Freezing; Thawing; Volatile compounds. |
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Categoria do assunto: |
Q Alimentos e Nutrição Humana |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/213573/1/EffectsFreezingThawing-OK.pdf
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Marc: |
LEADER 01898naa a2200289 a 4500
001 2117101
005 2023-03-13
008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.meatsci.2019.108003$2DOI
100 1 $aBERNARDO, A. P. da S.
245 $aEffects of freezing and thawing on microbiological and physical-chemical properties of dry-aged beef.$h[electronic resource]
260 $c2020
300 $a9 p.
520 $aThis study evaluated the effects of freezing, prior to and after dry aging, on the microbiological and physical-chemical quality of beef. Strip loins (n = 24) from 12 carcasses were assigned to four treatments: non-frozen dry aging (Dry); dry aging, steak fabrication, freezing and slow thawing (Dry + ST); freezing, fast thawing (FT; 20 °C/15 h) and dry aging (FT + Dry); freezing, slow thawing (ST; 4°C / 48h) and dry aging (ST + Dry). Freezing conditions were - 20°C/28 days and dry aging conditions were 2°C/70% relative humidity, for 28 days. Freezing prior to dry aging did not affect the microbial counts compared to Dry. However, FT + Dry and ST + Dry increased (16%) total process loss (P < .05) compared to Dry and Dry+ST. Moreover, freezing changed volatile compounds profile. Thus, freezing prior to dry aging was not a feasible process due to increased process loss, while freezing after dry aging was considered a viable alternative to preserve the steaks without compromising beef physical-chemical traits.
650 $aFreezing
650 $aThawing
650 $aVolatile compounds
653 $aDry-aged beef
653 $aMicrobiological beef quality
700 1 $aSILVA, A. C. M. da
700 1 $aFRANCISCO, V. C.
700 1 $aRIBEIRO, F. A.
700 1 $aNASSU, R. T.
700 1 $aCALKINS, C. R.
700 1 $aNASCIMENTO, M. da S.
700 1 $aPFLANZER, S. B.
773 $tMeat Science$gv. 161, 108003, mar. 2020.
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Registro original: |
Embrapa Pecuária Sudeste (CPPSE) |
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