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Registro Completo |
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Biblioteca(s): |
Embrapa Meio-Norte. |
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Data corrente: |
27/07/2010 |
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Data da última atualização: |
19/12/2023 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
DANTAS, I. M. S.; MENDES, R. F. de M.; NASCIMENTO, M. P. S. C. B. do; LIMA, P. S. da C. |
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Afiliação: |
IONNE MARTINS SOARES DANTAS, NOVAFAPI; RAUL FERREIRA DE MIRANDA MENDES, UESPI; MARIA PERPETUO SOCORRO CORTEZ BONA DO NASCIMENTO, CPAMN; PAULO SARMANHO DA COSTA LIMA, CPAMN. |
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Título: |
Otimização e seleção de Primers RAPD para caracterização molecular de acessos de Angico de Bezerro (Piptadenia moniliformis Benth.). |
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Ano de publicação: |
2010 |
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Fonte/Imprenta: |
In: CONGRESSO BRASILEIRO DE RECURSOS GENÉTICOS; WORKSHOP EM BIOPROSPECÇÃO E CONSERVAÇÃO DE PLANTAS NATIVAS DO SEMI-ÁRIDO, 3.; WORKSHOP INTERNACIONAL SOBRE BIOENERGIA E MEIO AMBIENTE, 2010, Salvador. Bancos de germoplasma: descobrir a riqueza, garantir o futuro: anais. Brasília, DF: Embrapa Recursos Genéticos e Biotecnologia, 2010. |
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Descrição Física: |
1 CD-ROM. |
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Idioma: |
Português |
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Conteúdo: |
Objetivou-se otimizar a reação de amplificação e selecionar primers RAPD (Random Amplified Polimorfic DNA) para análises de variabilidade genética em 10 acessos de angico de bezerro que compõem o Banco Ativo de Germoplasma de Forrageiras Nativas da Embrapa Meio-Norte. |
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Palavras-Chave: |
PCR; Poliformismo; Reação. |
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Thesagro: |
Banco de Germoplasma; Marcador Molecular. |
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Categoria do assunto: |
--
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://www.alice.cnptia.embrapa.br/alice/bitstream/doc/880763/1/418SELECAoDEPRIMERS.pdf
https://www.alice.cnptia.embrapa.br/alice/bitstream/doc/858639/1/OtimizacaoSelecao-24396.pdf
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Marc: |
LEADER 01269nam a2200217 a 4500
001 1880763
005 2023-12-19
008 2010 bl uuuu u00u1 u #d
100 1 $aDANTAS, I. M. S.
245 $aOtimização e seleção de Primers RAPD para caracterização molecular de acessos de Angico de Bezerro (Piptadenia moniliformis Benth.).$h[electronic resource]
260 $aIn: CONGRESSO BRASILEIRO DE RECURSOS GENÉTICOS; WORKSHOP EM BIOPROSPECÇÃO E CONSERVAÇÃO DE PLANTAS NATIVAS DO SEMI-ÁRIDO, 3.; WORKSHOP INTERNACIONAL SOBRE BIOENERGIA E MEIO AMBIENTE, 2010, Salvador. Bancos de germoplasma: descobrir a riqueza, garantir o futuro: anais. Brasília, DF: Embrapa Recursos Genéticos e Biotecnologia$c2010
300 $c1 CD-ROM.
520 $aObjetivou-se otimizar a reação de amplificação e selecionar primers RAPD (Random Amplified Polimorfic DNA) para análises de variabilidade genética em 10 acessos de angico de bezerro que compõem o Banco Ativo de Germoplasma de Forrageiras Nativas da Embrapa Meio-Norte.
650 $aBanco de Germoplasma
650 $aMarcador Molecular
653 $aPCR
653 $aPoliformismo
653 $aReação
700 1 $aMENDES, R. F. de M.
700 1 $aNASCIMENTO, M. P. S. C. B. do
700 1 $aLIMA, P. S. da C.
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Registro original: |
Embrapa Meio-Norte (CPAMN) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Semiárido. Para informações adicionais entre em contato com cpatsa.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Meio Ambiente; Embrapa Semiárido. |
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Data corrente: |
04/07/2022 |
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Data da última atualização: |
04/07/2022 |
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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: |
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. |
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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. |
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Título: |
Are remote sensing evapotranspiration models reliable across South American ecoregions? |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Water Resources Research, v. 57, n. 11, e2020WR028752, 2021. |
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DOI: |
https://doi.org/10.1029/2020WR028752 |
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Idioma: |
Inglês |
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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 |
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Palavras-Chave: |
MODIS; Penman-Monteith; Priestley-Taylor. |
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Thesagro: |
Evapotranspiração; Sensoriamento Remoto; Vegetação. |
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Thesaurus NAL: |
Remote sensing. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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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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