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Registro Completo |
Biblioteca(s): |
Embrapa Pesca e Aquicultura. |
Data corrente: |
22/03/2018 |
Data da última atualização: |
18/01/2019 |
Tipo da produção científica: |
Resumo em Anais de Congresso |
Autoria: |
FERREIRA JÚNIOR, O. J.; BORTOLON, L.; BORGHI, E.; BORTOLON, E. S. O.; CAMARGO, F. P. de; SILVA, R. R. da. |
Afiliação: |
OSVALDO JOSE FERREIRA JUNIOR, UFT, Gurupi-TO; LEANDRO BORTOLON, CNPASA; EMERSON BORGHI, CNPMS; ELISANDRA SOLANGE OLIVEIRA BORTOLON, CNPASA; FRANCELINO PETENO DE CAMARGO, CNPASA; RUBENS RIBEIRO DA SILVA, UFT, Gurupi-TO. |
Título: |
Rendimento de grãos de soja em função da correção do solo e sobressemeadura de forrageiras na soja. |
Ano de publicação: |
2018 |
Fonte/Imprenta: |
In: REUNIÃO CENTRO-OESTE DE CIÊNCIA DO SOLO, 5.; SIMPÓSIO DE NUTRIÇÃO DE PLANTAS NO CERRADO, 2., 2018, Goiânia. Uso eficiente de nutrientes e adubação de sistemas agrícolas: resumos. Goiânia: UFG, 2018. |
Páginas: |
p. 473-474. |
Idioma: |
Português |
Conteúdo: |
O objetivo desse estudo foi avaliar a influência da sobressemeadura de forrageiras na soja e a correção do solo no rendimento de grãos da soja. |
Palavras-Chave: |
Integração lavoura-pecuária. |
Thesagro: |
Cerrado; Glycine Max; Grão; Integração; Rendimento; Soja; Solo. |
Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/190908/1/CNPASA-2018-rcocs-p473.pdf
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Marc: |
LEADER 01102nam a2200277 a 4500 001 2089610 005 2019-01-18 008 2018 bl uuuu u00u1 u #d 100 1 $aFERREIRA JÚNIOR, O. J. 245 $aRendimento de grãos de soja em função da correção do solo e sobressemeadura de forrageiras na soja.$h[electronic resource] 260 $aIn: REUNIÃO CENTRO-OESTE DE CIÊNCIA DO SOLO, 5.; SIMPÓSIO DE NUTRIÇÃO DE PLANTAS NO CERRADO, 2., 2018, Goiânia. Uso eficiente de nutrientes e adubação de sistemas agrícolas: resumos. Goiânia: UFG$c2018 300 $ap. 473-474. 520 $aO objetivo desse estudo foi avaliar a influência da sobressemeadura de forrageiras na soja e a correção do solo no rendimento de grãos da soja. 650 $aCerrado 650 $aGlycine Max 650 $aGrão 650 $aIntegração 650 $aRendimento 650 $aSoja 650 $aSolo 653 $aIntegração lavoura-pecuária 700 1 $aBORTOLON, L. 700 1 $aBORGHI, E. 700 1 $aBORTOLON, E. S. O. 700 1 $aCAMARGO, F. P. de 700 1 $aSILVA, R. R. da
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Embrapa Pesca e Aquicultura (CNPASA) |
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Registro Completo
Biblioteca(s): |
Embrapa Meio Ambiente; Embrapa Semiárido. |
Data corrente: |
04/07/2022 |
Data da última atualização: |
04/07/2022 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
MELO, D. C. D.; ANACHE, J. A. A.; BORGES, V. P.; MIRALLES, D. G.; MARTENS, B.; FISHER, J. B.; NÓBREGA, R. L. B.; MORENO, A.; CABRAL, O. M. R.; RODRIGUES, T. R.; BEZERRA, B.; SILVA, C. M. S.; MEIRA NETO, A. A.; MOURA, M. S. B. de; MARQUES, T. V.; CAMPOS, S.; NOGUEIRA, J. S.; ROSOLEM, R.; SOUZA, R. M. S.; ANTONINO, A. C. D.; HOLL, D.; GALLEGUILLOS, M.; PEREZ-QUEZADA, J. F.; VERHOEF, A.; KUTZBACH, L.; LIMA, J. R. S.; SOUZA, E. S.; GASSMAN, M. I.; PEREZ, C. F.; TONTI, N.; POSSE, G.; RAINS, D.; OLIVEIRA, P. T. S.; WENDLAND, E. |
Afiliação: |
D. C. D. MELO, UFPB; J. A. A. ANACHE, UFMS; V. P. BORGES, UFPB; D. G. MIRALLES, Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium; B. MARTENS, Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium; J. B. FISHER, Schmid College of Science and Technology, Chapman University, Orange, CA; R. L. B. NÓBREGA, Department of Life Sciences, Imperial College London; A. MORENO, Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT; OSVALDO MACHADO RODRIGUES CABRAL, CNPMA; T. R. RODRIGUES, UFMS; B. BEZERRA, UFRN; C. M. S. SILVA, UFRN; A. A. MEIRA NETO, Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, AZ; MAGNA SOELMA BESERRA DE MOURA, CPATSA; T. V. MARQUES, UFRN; S. CAMPOS, UFRN; J. S. NOGUEIRA, UFMT; R. ROSOLEM, University of Bristol, Bristol, UK; R. M. S. SOUZA, Department of Biological and Agricultural Engineering, Texas A&M University, College Station, TX; A. C. D. ANTONINO, UFPE; D. HOLL, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany; M. GALLEGUILLOS, Department of Environmental Science and Renewable Natural Resources, University of Chile, Santiago, Chile; J. F. PEREZ-QUEZADA, Department of Environmental Science and Renewable Natural Resources, University of Chile, Santiago, Chile; A. VERHOEF, Department of Geography and Environmental Science, The University of Reading, Reading, UK; L. KUTZBACH, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany; J. R. S. LIMA, Federal University of the Agreste of Pernambuco, Garanhuns, PE; E. S. SOUZA, UFRPE, Garanhuns, PE; M. I. GASSMAN, Department of Atmospheric and Ocean Sciences, FCEN — UBA, Buenos Aires, Argentina; C. F. PEREZ, Department of Atmospheric and Ocean Sciences, FCEN ? UBA, Buenos Aires, Argentina; N. TONTI, Department of Atmospheric and Ocean Sciences, FCEN — UBA, Buenos Aires, Argentina; G. POSSE, INTA; D. RAINS, Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium; P. T. S. OLIVEIRA, UFMS; E. WENDLAND, Department of Hydraulics and Sanitary Engineering, University of São Paulo, São Carlos, SP. |
Título: |
Are remote sensing evapotranspiration models reliable across South American ecoregions? |
Ano de publicação: |
2021 |
Fonte/Imprenta: |
Water Resources Research, v. 57, n. 11, e2020WR028752, 2021. |
DOI: |
https://doi.org/10.1029/2020WR028752 |
Idioma: |
Inglês |
Conteúdo: |
Many remote sensing-based evapotranspiration (RSBET) algorithms have been proposed in the past decades and evaluated using flux tower data, mainly over North America and Europe. Model evaluation across South America has been done locally or using only a single algorithm at a time. Here, we provide the first evaluation of multiple RSBET models, at a daily scale, across a wide variety of biomes, climate zones, and land uses in South America. We used meteorological data from 25 flux towers to force four RSBET models: Priestley?Taylor Jet Propulsion Laboratory (PT-JPL), Global Land Evaporation Amsterdam Model (GLEAM), Penman?Monteith Mu model (PM-MOD), and Penman?Monteith Nagler model (PM-VI). E ET was predicted satisfactorily by all four models, with correlations consistently higher (?20.6ER) for GLEAM and PT-JPL, and PM-MOD and PM-VI presenting overall better responses in terms of percent bias (?? ?1010EPBIAS%). As for PM-VI, this outcome is expected, given that the model requires calibration with local data. Model skill seems to be unrelated to land-use but instead presented some dependency on biome and climate, with the models producing the best results for wet to moderately wet environments. Our findings show the suitability of individual models for a number of combinations of land cover types, biomes, and climates. At the same time, no model outperformed the others for all conditions, which emphasizes the need for adapting individual algorithms to take into account intrinsic characteristics of climates and ecosystems in South America. MenosMany remote sensing-based evapotranspiration (RSBET) algorithms have been proposed in the past decades and evaluated using flux tower data, mainly over North America and Europe. Model evaluation across South America has been done locally or using only a single algorithm at a time. Here, we provide the first evaluation of multiple RSBET models, at a daily scale, across a wide variety of biomes, climate zones, and land uses in South America. We used meteorological data from 25 flux towers to force four RSBET models: Priestley?Taylor Jet Propulsion Laboratory (PT-JPL), Global Land Evaporation Amsterdam Model (GLEAM), Penman?Monteith Mu model (PM-MOD), and Penman?Monteith Nagler model (PM-VI). E ET was predicted satisfactorily by all four models, with correlations consistently higher (?20.6ER) for GLEAM and PT-JPL, and PM-MOD and PM-VI presenting overall better responses in terms of percent bias (?? ?1010EPBIAS%). As for PM-VI, this outcome is expected, given that the model requires calibration with local data. Model skill seems to be unrelated to land-use but instead presented some dependency on biome and climate, with the models producing the best results for wet to moderately wet environments. Our findings show the suitability of individual models for a number of combinations of land cover types, biomes, and climates. At the same time, no model outperformed the others for all conditions, which emphasizes the need for adapting individual algorithms to take into account int... Mostrar Tudo |
Palavras-Chave: |
MODIS; Penman-Monteith; Priestley-Taylor. |
Thesagro: |
Evapotranspiração; Sensoriamento Remoto; Vegetação. |
Thesaurus NAL: |
Remote sensing. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
Marc: |
LEADER 03247naa a2200613 a 4500 001 2144450 005 2022-07-04 008 2021 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.1029/2020WR028752$2DOI 100 1 $aMELO, D. C. D. 245 $aAre remote sensing evapotranspiration models reliable across South American ecoregions?$h[electronic resource] 260 $c2021 520 $aMany remote sensing-based evapotranspiration (RSBET) algorithms have been proposed in the past decades and evaluated using flux tower data, mainly over North America and Europe. Model evaluation across South America has been done locally or using only a single algorithm at a time. Here, we provide the first evaluation of multiple RSBET models, at a daily scale, across a wide variety of biomes, climate zones, and land uses in South America. We used meteorological data from 25 flux towers to force four RSBET models: Priestley?Taylor Jet Propulsion Laboratory (PT-JPL), Global Land Evaporation Amsterdam Model (GLEAM), Penman?Monteith Mu model (PM-MOD), and Penman?Monteith Nagler model (PM-VI). E ET was predicted satisfactorily by all four models, with correlations consistently higher (?20.6ER) for GLEAM and PT-JPL, and PM-MOD and PM-VI presenting overall better responses in terms of percent bias (?? ?1010EPBIAS%). As for PM-VI, this outcome is expected, given that the model requires calibration with local data. Model skill seems to be unrelated to land-use but instead presented some dependency on biome and climate, with the models producing the best results for wet to moderately wet environments. Our findings show the suitability of individual models for a number of combinations of land cover types, biomes, and climates. At the same time, no model outperformed the others for all conditions, which emphasizes the need for adapting individual algorithms to take into account intrinsic characteristics of climates and ecosystems in South America. 650 $aRemote sensing 650 $aEvapotranspiração 650 $aSensoriamento Remoto 650 $aVegetação 653 $aMODIS 653 $aPenman-Monteith 653 $aPriestley-Taylor 700 1 $aANACHE, J. A. A. 700 1 $aBORGES, V. P. 700 1 $aMIRALLES, D. G. 700 1 $aMARTENS, B. 700 1 $aFISHER, J. B. 700 1 $aNÓBREGA, R. L. B. 700 1 $aMORENO, A. 700 1 $aCABRAL, O. M. R. 700 1 $aRODRIGUES, T. R. 700 1 $aBEZERRA, B. 700 1 $aSILVA, C. M. S. 700 1 $aMEIRA NETO, A. A. 700 1 $aMOURA, M. S. B. de 700 1 $aMARQUES, T. V. 700 1 $aCAMPOS, S. 700 1 $aNOGUEIRA, J. S. 700 1 $aROSOLEM, R. 700 1 $aSOUZA, R. M. S. 700 1 $aANTONINO, A. C. D. 700 1 $aHOLL, D. 700 1 $aGALLEGUILLOS, M. 700 1 $aPEREZ-QUEZADA, J. F. 700 1 $aVERHOEF, A. 700 1 $aKUTZBACH, L. 700 1 $aLIMA, J. R. S. 700 1 $aSOUZA, E. S. 700 1 $aGASSMAN, M. I. 700 1 $aPEREZ, C. F. 700 1 $aTONTI, N. 700 1 $aPOSSE, G. 700 1 $aRAINS, D. 700 1 $aOLIVEIRA, P. T. S. 700 1 $aWENDLAND, E. 773 $tWater Resources Research$gv. 57, n. 11, e2020WR028752, 2021.
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