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Registro Completo |
Biblioteca(s): |
Embrapa Recursos Genéticos e Biotecnologia. |
Data corrente: |
21/10/2009 |
Data da última atualização: |
21/10/2009 |
Tipo da produção científica: |
Artigo em Anais de Congresso / Nota Técnica |
Autoria: |
CARNEIRO, R. M. D. G.; COSTA, S. B.; SOUZA, F. R. de; MOITA, A. W.; CARNEIRO, R. G. |
Afiliação: |
REGINA MARIA DECHECHI G CARNEIRO, CENARGEN; SAMARA BELÉM COSTA; FÁBIO RODRIGUES DE SOUSA; ANTONIO WILLIAMS MOITA, CNPH; RUI GOMES CARNEIRO, IAPAR. |
Título: |
Resultados parciais sobre o manejo integrado de Meloidogyne paranaensis em cafeeiros usando rotação de cultura, controle biológico e resistência genética. |
Ano de publicação: |
2009 |
Fonte/Imprenta: |
In: SIMPÓSIO DE PESQUISA DOS CAFÉS DO BRASIL, 6., 2009, Vitória. Inovação científica, competitividade e mudanças climáticas: anais. Vitória: Consórcio Pesquisa Café, 2009. |
Descrição Física: |
1 CD-ROM. |
Idioma: |
Português |
Palavras-Chave: |
Bacterium; Cafeeiro Icatú; Coffee Icatu; Grey mucuna; Mucuna cinza; Nematóide das galhas; Oat; Peanut; Roor-knot nematode. |
Thesagro: |
Amendoim; Aveia; Bactéria. |
Thesaurus Nal: |
Pasteuria penetrans. |
Categoria do assunto: |
-- |
Marc: |
LEADER 01051nam a2200313 a 4500 001 1572839 005 2009-10-21 008 2009 bl uuuu u01u1 u #d 100 1 $aCARNEIRO, R. M. D. G. 245 $aResultados parciais sobre o manejo integrado de Meloidogyne paranaensis em cafeeiros usando rotação de cultura, controle biológico e resistência genética. 260 $aIn: SIMPÓSIO DE PESQUISA DOS CAFÉS DO BRASIL, 6., 2009, Vitória. Inovação científica, competitividade e mudanças climáticas: anais. Vitória: Consórcio Pesquisa Café$c2009 300 $c1 CD-ROM. 650 $aPasteuria penetrans 650 $aAmendoim 650 $aAveia 650 $aBactéria 653 $aBacterium 653 $aCafeeiro Icatú 653 $aCoffee Icatu 653 $aGrey mucuna 653 $aMucuna cinza 653 $aNematóide das galhas 653 $aOat 653 $aPeanut 653 $aRoor-knot nematode 700 1 $aCOSTA, S. B. 700 1 $aSOUZA, F. R. de 700 1 $aMOITA, A. W. 700 1 $aCARNEIRO, R. G.
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Embrapa Recursos Genéticos e Biotecnologia (CENARGEN) |
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Registro Completo
Biblioteca(s): |
Embrapa Amazônia Oriental. |
Data corrente: |
06/02/2018 |
Data da última atualização: |
02/05/2018 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
WU, J.; KOBAYASHI, H.; STARK, S. C.; MENG, R.; GUAN, K.; TRAN, N. N.; GAO, S.; YANG, W.; RESTREPO-COUPE, N.; MIURA, T.; OLIVEIRA JUNIOR, R. C. de; ROGERS, A.; DYE, D. G.; NELSON, B. W.; SERBIN, S. P.; HUETE, A. R.; SALESKA, S. R. |
Afiliação: |
Jin Wu, University of Arizona / Brookhaven National Laboratory; Hideki Kobayashi, Japan Agency for Marine-Earth Science and Technology; Scott C. Stark, Michigan State University; Ran Meng, Brookhaven National Laboratory; Kaiyu Guan, University of Illinois at Urbana Champaign; Ngoc Nguyen Tran, University of Technology Sydney; Sicong Gao, University of Technology Sydney; Wei Yang, Chiba University; Natalia Restrepo-Coupe, University of Arizona; Tomoaki Miura, University of Havaii; RAIMUNDO COSME DE OLIVEIRA JUNIOR, CPATU; Alistair Rogers, Brookhaven National Laboratory; Dennis G. Dye, Northern Arizona University; Bruce W. Nelson, INPA; Shawn P. Serbin, Brookhaven National Laboratory; Alfredo R. Huete, University of Technology Sydney; Scott R. Saleska, University of Arizona. |
Título: |
Biological processes dominate seasonality of remotely sensed canopy greenness in an Amazon evergreen forest. |
Ano de publicação: |
2018 |
Fonte/Imprenta: |
New Phytologist, v. 217, n. 4, p. 1507-1520, Mar. 2018. |
DOI: |
10.1111/nph.14939 |
Idioma: |
Inglês |
Conteúdo: |
Satellite observations of Amazon forests show seasonal and interannual variations, but the underlying biological processes remain debated. Here we combined radiative transfer models (RTMs) with field observations of Amazon forest leaf and canopy characteristics to test three hypotheses for satellite-observed canopy reflectance seasonality: seasonal changes in leaf area index, in canopy-surface leafless crown fraction and/or in leaf demography. Canopy RTMs (PROSAIL and FLiES), driven by these three factors combined, simulated satellite-observed seasonal patterns well, explaining c. 70% of the variability in a key reflectance-based vegetation index (MAIAC EVI, which removes artifacts that would otherwise arise from clouds/aerosols and sun?sensor geometry). Leaf area index, leafless crown fraction and leaf demography independently accounted for 1, 33 and 66% of FLiES-simulated EVI seasonality, respectively. These factors also strongly influenced modeled near-infrared (NIR) reflectance, explaining why both modeled and observed EVI, which is especially sensitive to NIR, captures canopy seasonal dynamics well. Our improved analysis of canopy-scale biophysics rules out satellite artifacts as significant causes of satellite-observed seasonal patterns at this site, implying that aggregated phenology explains the larger scale remotely observed patterns. This work significantly reconciles current controversies about satellite-detected Amazon phenology, and improves our use of satellite observations to study climate?phenology relationships in the tropics. MenosSatellite observations of Amazon forests show seasonal and interannual variations, but the underlying biological processes remain debated. Here we combined radiative transfer models (RTMs) with field observations of Amazon forest leaf and canopy characteristics to test three hypotheses for satellite-observed canopy reflectance seasonality: seasonal changes in leaf area index, in canopy-surface leafless crown fraction and/or in leaf demography. Canopy RTMs (PROSAIL and FLiES), driven by these three factors combined, simulated satellite-observed seasonal patterns well, explaining c. 70% of the variability in a key reflectance-based vegetation index (MAIAC EVI, which removes artifacts that would otherwise arise from clouds/aerosols and sun?sensor geometry). Leaf area index, leafless crown fraction and leaf demography independently accounted for 1, 33 and 66% of FLiES-simulated EVI seasonality, respectively. These factors also strongly influenced modeled near-infrared (NIR) reflectance, explaining why both modeled and observed EVI, which is especially sensitive to NIR, captures canopy seasonal dynamics well. Our improved analysis of canopy-scale biophysics rules out satellite artifacts as significant causes of satellite-observed seasonal patterns at this site, implying that aggregated phenology explains the larger scale remotely observed patterns. This work significantly reconciles current controversies about satellite-detected Amazon phenology, and improves our use of satellite... Mostrar Tudo |
Palavras-Chave: |
Sazonalidade. |
Thesagro: |
Fenologia; Floresta tropical. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
Marc: |
LEADER 02563naa a2200361 a 4500 001 2087194 005 2018-05-02 008 2018 bl uuuu u00u1 u #d 024 7 $a10.1111/nph.14939$2DOI 100 1 $aWU, J. 245 $aBiological processes dominate seasonality of remotely sensed canopy greenness in an Amazon evergreen forest.$h[electronic resource] 260 $c2018 520 $aSatellite observations of Amazon forests show seasonal and interannual variations, but the underlying biological processes remain debated. Here we combined radiative transfer models (RTMs) with field observations of Amazon forest leaf and canopy characteristics to test three hypotheses for satellite-observed canopy reflectance seasonality: seasonal changes in leaf area index, in canopy-surface leafless crown fraction and/or in leaf demography. Canopy RTMs (PROSAIL and FLiES), driven by these three factors combined, simulated satellite-observed seasonal patterns well, explaining c. 70% of the variability in a key reflectance-based vegetation index (MAIAC EVI, which removes artifacts that would otherwise arise from clouds/aerosols and sun?sensor geometry). Leaf area index, leafless crown fraction and leaf demography independently accounted for 1, 33 and 66% of FLiES-simulated EVI seasonality, respectively. These factors also strongly influenced modeled near-infrared (NIR) reflectance, explaining why both modeled and observed EVI, which is especially sensitive to NIR, captures canopy seasonal dynamics well. Our improved analysis of canopy-scale biophysics rules out satellite artifacts as significant causes of satellite-observed seasonal patterns at this site, implying that aggregated phenology explains the larger scale remotely observed patterns. This work significantly reconciles current controversies about satellite-detected Amazon phenology, and improves our use of satellite observations to study climate?phenology relationships in the tropics. 650 $aFenologia 650 $aFloresta tropical 653 $aSazonalidade 700 1 $aKOBAYASHI, H. 700 1 $aSTARK, S. C. 700 1 $aMENG, R. 700 1 $aGUAN, K. 700 1 $aTRAN, N. N. 700 1 $aGAO, S. 700 1 $aYANG, W. 700 1 $aRESTREPO-COUPE, N. 700 1 $aMIURA, T. 700 1 $aOLIVEIRA JUNIOR, R. C. de 700 1 $aROGERS, A. 700 1 $aDYE, D. G. 700 1 $aNELSON, B. W. 700 1 $aSERBIN, S. P. 700 1 $aHUETE, A. R. 700 1 $aSALESKA, S. R. 773 $tNew Phytologist$gv. 217, n. 4, p. 1507-1520, Mar. 2018.
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