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 | Acesso ao texto completo restrito à biblioteca da Embrapa Arroz e Feijão. Para informações adicionais entre em contato com cnpaf.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
21/09/2018 |
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Data da última atualização: |
21/09/2018 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
REZENDE, B. A.; ABREU, A. de F. B.; RAMALHO, M. A. P.; SOUZA, E. A. de. |
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Afiliação: |
BRENO A. REZENDE, UFLA; ANGELA DE FATIMA BARBOSA ABREU, CNPAF; MAGNO ANTONIO PATTO RAMALHO, UFLA; ELAINE A. DE SOUZA, UFLA. |
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Título: |
Severity evaluation methods in common bean recurrent selection programme for resistance to angular leaf spot. |
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Ano de publicação: |
2014 |
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Fonte/Imprenta: |
Journal of Phytopathology, v. 162, n. 10, p. 643-649, Oct. 2014. |
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ISSN: |
1439-0434 |
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DOI: |
10.1111/jph.12238 |
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Idioma: |
Inglês |
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Conteúdo: |
The objectives of this study were to identify which method and period of evaluation of angular leaf spot (ALS) of common bean, caused by the fungal pathogen Pseudocercospora griseola, allow better discrimination among common bean lines derived from seven cycles of recurrent selection for resistance to this pathogen. For that reason, 35 lines of the first seven cycles of the programme were assessed for disease severity on leaves and pods using a rating scale. For leaves, the methods used were severity in field plots (SF), severity in sampled leaflets (SS) and percentage of the sampled leaf area with symptoms (%LAS). Leaf assessments were performed at 7, 14, 21, 28, 33 and 41 days after flowering (DAF), and area under the disease progress curve (AUDPC) was calculated. On pods, severity was evaluated at 41 DAF. It was observed that the SF using a rating scale is the most efficient method for selection of resistant lines, and the best time period for evaluating the disease is around 33 DAF |
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Thesagro: |
Doença de Planta; Feijão; Mancha Angular; Melhoramento Genético Vegetal; Phaseolus Vulgaris; Resistência Genética; Seleção Recorrente. |
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Thesaurus Nal: |
Beans; Disease resistance; Leaf spot; Plant breeding; Pseudocercospora; Recurrent selection. |
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Categoria do assunto: |
G Melhoramento Genético |
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Marc: |
LEADER 02017naa a2200337 a 4500
001 2096124
005 2018-09-21
008 2014 bl uuuu u00u1 u #d
022 $a1439-0434
024 7 $a10.1111/jph.12238$2DOI
100 1 $aREZENDE, B. A.
245 $aSeverity evaluation methods in common bean recurrent selection programme for resistance to angular leaf spot.$h[electronic resource]
260 $c2014
520 $aThe objectives of this study were to identify which method and period of evaluation of angular leaf spot (ALS) of common bean, caused by the fungal pathogen Pseudocercospora griseola, allow better discrimination among common bean lines derived from seven cycles of recurrent selection for resistance to this pathogen. For that reason, 35 lines of the first seven cycles of the programme were assessed for disease severity on leaves and pods using a rating scale. For leaves, the methods used were severity in field plots (SF), severity in sampled leaflets (SS) and percentage of the sampled leaf area with symptoms (%LAS). Leaf assessments were performed at 7, 14, 21, 28, 33 and 41 days after flowering (DAF), and area under the disease progress curve (AUDPC) was calculated. On pods, severity was evaluated at 41 DAF. It was observed that the SF using a rating scale is the most efficient method for selection of resistant lines, and the best time period for evaluating the disease is around 33 DAF
650 $aBeans
650 $aDisease resistance
650 $aLeaf spot
650 $aPlant breeding
650 $aPseudocercospora
650 $aRecurrent selection
650 $aDoença de Planta
650 $aFeijão
650 $aMancha Angular
650 $aMelhoramento Genético Vegetal
650 $aPhaseolus Vulgaris
650 $aResistência Genética
650 $aSeleção Recorrente
700 1 $aABREU, A. de F. B.
700 1 $aRAMALHO, M. A. P.
700 1 $aSOUZA, E. A. de
773 $tJournal of Phytopathology$gv. 162, n. 10, p. 643-649, Oct. 2014.
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Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
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URL |
Voltar
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Registro Completo
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Biblioteca(s): |
Embrapa Cerrados. |
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Data corrente: |
11/05/2009 |
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Data da última atualização: |
20/03/2023 |
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Tipo da produção científica: |
Artigo em Anais de Congresso / Nota Técnica |
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Autoria: |
TEIXEIRA, C. V.; SANO, E. E. |
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Afiliação: |
CÉSAR VALDENIR TEIXEIRA, INSTITUTO BRASILEIRO DO MEIO AMBIENTE E DOS RECURSOS NATURAIS RENOVÁVEIS; EDSON EYJI SANO, CPAC. |
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Título: |
Metodologias de fusão de imagens ópticas e de radar para identificar alvos representativos na várzea Amazônica. |
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Ano de publicação: |
2009 |
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Fonte/Imprenta: |
In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 14., 2009, Natal. Anais... São José dos Campos: INPE, 2009. |
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Páginas: |
P. 7211-7217 |
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Idioma: |
Português |
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Conteúdo: |
ABSTRACT - At the Amazonian basin, the strong amplitude of variation of water level draining generates systematic floodings in vast zones called “varzea” (floodplain). This work aims to develop a methodological approach to analyze patterns and techniques to discriminate representative areas of Amazon floodplains using combined, optical (Landsat sensor) and radar (R99B Brasilian Air Force), remotely sensed data providing the delimitation and the identification of representative targets of these areas. Two study areas, selected based on data availability, were located in the regions of the cities of Manaus and Iranduba – AM. For the identification of representative targets in the varzea, we used two image fusion techniques - principal components and IHS transform. The result of this process were hybrid images that have joined a good spatial and spectral resolutions, so we can identify with precision the targets selected. The results were compared with field data. The study had an important support of ProVárzea/Ibama (The Floodplain “Várzea” Natural Resources Management Project), specifically from the group dealing with GIS-based data management for floodplain monitoring. |
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Palavras-Chave: |
Planície de inundação. |
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Thesagro: |
Ecossistema; Radar; Sensoriamento Remoto; Sinergismo; Várzea. |
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Thesaurus NAL: |
Floodplains; Landsat; Remote sensing; Synergism. |
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Categoria do assunto: |
-- |
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URL: |
https://www.alice.cnptia.embrapa.br/alice/bitstream/doc/557322/1/Metodologias-fusao-imagens-2009.pdf
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Marc: |
LEADER 01974nam a2200253 a 4500
001 1557322
005 2023-03-20
008 2009 bl uuuu u00u1 u #d
100 1 $aTEIXEIRA, C. V.
245 $aMetodologias de fusão de imagens ópticas e de radar para identificar alvos representativos na várzea Amazônica.
260 $aIn: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 14., 2009, Natal. Anais... São José dos Campos: INPE$c2009
300 $aP. 7211-7217
520 $aABSTRACT - At the Amazonian basin, the strong amplitude of variation of water level draining generates systematic floodings in vast zones called “varzea” (floodplain). This work aims to develop a methodological approach to analyze patterns and techniques to discriminate representative areas of Amazon floodplains using combined, optical (Landsat sensor) and radar (R99B Brasilian Air Force), remotely sensed data providing the delimitation and the identification of representative targets of these areas. Two study areas, selected based on data availability, were located in the regions of the cities of Manaus and Iranduba – AM. For the identification of representative targets in the varzea, we used two image fusion techniques - principal components and IHS transform. The result of this process were hybrid images that have joined a good spatial and spectral resolutions, so we can identify with precision the targets selected. The results were compared with field data. The study had an important support of ProVárzea/Ibama (The Floodplain “Várzea” Natural Resources Management Project), specifically from the group dealing with GIS-based data management for floodplain monitoring.
650 $aFloodplains
650 $aLandsat
650 $aRemote sensing
650 $aSynergism
650 $aEcossistema
650 $aRadar
650 $aSensoriamento Remoto
650 $aSinergismo
650 $aVárzea
653 $aPlanície de inundação
700 1 $aSANO, E. E.
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