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Registro Completo |
Biblioteca(s): |
Embrapa Arroz e Feijão. |
Data corrente: |
27/11/2008 |
Data da última atualização: |
21/03/2013 |
Tipo da produção científica: |
Artigo em Anais de Congresso |
Autoria: |
GONÇALVES, F. J.; NUNES, C. M. C.; FILIPPI, M. C.; SIBOV, S. T. |
Afiliação: |
FABIO JOSE GONÇALVES, UFG; CAMILA MARILLAC COSTA NUNES, UFG; MARTA CRISTINA CORSI DE FILIPPI, CNPAF; SERGIO TADEU SIBOV, UFG. |
Título: |
Isolamento de fungos micorrízicos de Cyrtopodium vernum, orquídea terrestre de campos rupestres do Estado de Goiás. |
Ano de publicação: |
2008 |
Fonte/Imprenta: |
In: CONGRESSO DE PESQUISA, ENSINO E EXTENSÃO, 5., 2008, Goiânia. Produção do conhecimento e transformação social: anais... Goiânia: Universidade Federal de Goiás, 2008. |
Descrição Física: |
1 CD-ROM. |
Idioma: |
Português |
Conteúdo: |
O objetivo deste trabalho foi isolar fungos associados a raízes de uma espécie de orquídea terrestre do gênero Cyrtopodium visando o melhor desenvolvimento de protocormos na propagação in vitro desta espécie. |
Palavras-Chave: |
Conpeex; Poletons. |
Thesagro: |
Cerrado; Orquídea; Simbiose. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/79569/1/pl-2008.101.pdf
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Marc: |
LEADER 00957nam a2200217 a 4500 001 1217545 005 2013-03-21 008 2008 bl uuuu u00u1 u #d 100 1 $aGONÇALVES, F. J. 245 $aIsolamento de fungos micorrízicos de Cyrtopodium vernum, orquídea terrestre de campos rupestres do Estado de Goiás. 260 $aIn: CONGRESSO DE PESQUISA, ENSINO E EXTENSÃO, 5., 2008, Goiânia. Produção do conhecimento e transformação social: anais... Goiânia: Universidade Federal de Goiás$c2008 300 $c1 CD-ROM. 520 $aO objetivo deste trabalho foi isolar fungos associados a raízes de uma espécie de orquídea terrestre do gênero Cyrtopodium visando o melhor desenvolvimento de protocormos na propagação in vitro desta espécie. 650 $aCerrado 650 $aOrquídea 650 $aSimbiose 653 $aConpeex 653 $aPoletons 700 1 $aNUNES, C. M. C. 700 1 $aFILIPPI, M. C. 700 1 $aSIBOV, S. T.
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Embrapa Arroz e Feijão (CNPAF) |
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Registro Completo
Biblioteca(s): |
Embrapa Meio Ambiente; Embrapa Solos. |
Data corrente: |
29/08/2017 |
Data da última atualização: |
17/01/2023 |
Tipo da produção científica: |
Artigo em Anais de Congresso |
Autoria: |
MONTIBELLER, B.; LUIZ, A. J. B.; SANCHES, I. D. A.; SILVEIRA, H. L. F. da. |
Afiliação: |
BRUNO MONTIBELLER, INPE; ALFREDO JOSE BARRETO LUIZ, CNPMA; IEDA DEL'ARCO SANCHES, INPE; HILTON LUIS FERRAZ DA SILVEIRA, CNPS. |
Título: |
Análise da variabilidade espectro-temporal intraespecífica do milho. |
Ano de publicação: |
2017 |
Fonte/Imprenta: |
In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 18.,2017, Santos. Anais... Santos: Inpe, 2017. Trabalho: 59410. |
Páginas: |
p. 2011-2018. |
Idioma: |
Português |
Conteúdo: |
Remote sensing data has been widely used worldwide to estimate crop field?s parameters such as area. For that purpose, we use automatic classification algorithms to identify different land uses and land covers (e.g. agricultural and native vegetation), groups of crops (e.g. annual and perennial crops) or crops species (e.g. maize, sugarcane or soybean). For agricultural applications, the ultimate goal is to be able to use remote sensing technology to map crops in the specie level, and then to monitor them. One essential input data used in the classifications algorithms is the spectral information of the ground targets (e.g. reflectance and vegetation indices). Therefore, it is important to know the spectral behavior of all targets. However, the ability of one classifier to distinguish between plant species is probably dependent on the amount of intraspecific variability. In other words, if a crop specie has high intraspecific spectral variation, it will be difficult to classify this specie among others. Thus, the aim of this work is to analyze the intraspecific spectral temporal variability of maize crop. To accomplish that, spectral data (OLI/Landsat-8) were acquired from first and second harvest maize plots, cultivated over distinct management systems (irrigated and non-irrigated), along two agricultural crop years, (2014/2015 and 2015/2016). We concluded that maize fields harvested in different years, sowed in different seasons, irrigated or not, have a high temporal spectral variation, which cannot be associated with these known characteristics. MenosRemote sensing data has been widely used worldwide to estimate crop field?s parameters such as area. For that purpose, we use automatic classification algorithms to identify different land uses and land covers (e.g. agricultural and native vegetation), groups of crops (e.g. annual and perennial crops) or crops species (e.g. maize, sugarcane or soybean). For agricultural applications, the ultimate goal is to be able to use remote sensing technology to map crops in the specie level, and then to monitor them. One essential input data used in the classifications algorithms is the spectral information of the ground targets (e.g. reflectance and vegetation indices). Therefore, it is important to know the spectral behavior of all targets. However, the ability of one classifier to distinguish between plant species is probably dependent on the amount of intraspecific variability. In other words, if a crop specie has high intraspecific spectral variation, it will be difficult to classify this specie among others. Thus, the aim of this work is to analyze the intraspecific spectral temporal variability of maize crop. To accomplish that, spectral data (OLI/Landsat-8) were acquired from first and second harvest maize plots, cultivated over distinct management systems (irrigated and non-irrigated), along two agricultural crop years, (2014/2015 and 2015/2016). We concluded that maize fields harvested in different years, sowed in different seasons, irrigated or not, have a high temporal spec... Mostrar Tudo |
Palavras-Chave: |
Agricultural monitoring; Dado multitemporal; Monitoramento agrícola; Multitemporal data; OLI-Landsat-8; Reflectância de superfície; Surface reflectance. |
Thesagro: |
Milho; Sensoriamento remoto. |
Thesaurus NAL: |
Remote sensing. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra X Pesquisa, Tecnologia e Engenharia |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/170682/1/2017AA32.pdf
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/163104/1/2017-021.pdf
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Marc: |
LEADER 02476nam a2200277 a 4500 001 2084705 005 2023-01-17 008 2017 bl uuuu u00u1 u #d 100 1 $aMONTIBELLER, B. 245 $aAnálise da variabilidade espectro-temporal intraespecífica do milho.$h[electronic resource] 260 $aIn: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 18.,2017, Santos. Anais... Santos: Inpe, 2017. Trabalho: 59410.$c2017 300 $ap. 2011-2018. 520 $aRemote sensing data has been widely used worldwide to estimate crop field?s parameters such as area. For that purpose, we use automatic classification algorithms to identify different land uses and land covers (e.g. agricultural and native vegetation), groups of crops (e.g. annual and perennial crops) or crops species (e.g. maize, sugarcane or soybean). For agricultural applications, the ultimate goal is to be able to use remote sensing technology to map crops in the specie level, and then to monitor them. One essential input data used in the classifications algorithms is the spectral information of the ground targets (e.g. reflectance and vegetation indices). Therefore, it is important to know the spectral behavior of all targets. However, the ability of one classifier to distinguish between plant species is probably dependent on the amount of intraspecific variability. In other words, if a crop specie has high intraspecific spectral variation, it will be difficult to classify this specie among others. Thus, the aim of this work is to analyze the intraspecific spectral temporal variability of maize crop. To accomplish that, spectral data (OLI/Landsat-8) were acquired from first and second harvest maize plots, cultivated over distinct management systems (irrigated and non-irrigated), along two agricultural crop years, (2014/2015 and 2015/2016). We concluded that maize fields harvested in different years, sowed in different seasons, irrigated or not, have a high temporal spectral variation, which cannot be associated with these known characteristics. 650 $aRemote sensing 650 $aMilho 650 $aSensoriamento remoto 653 $aAgricultural monitoring 653 $aDado multitemporal 653 $aMonitoramento agrícola 653 $aMultitemporal data 653 $aOLI-Landsat-8 653 $aReflectância de superfície 653 $aSurface reflectance 700 1 $aLUIZ, A. J. B. 700 1 $aSANCHES, I. D. A. 700 1 $aSILVEIRA, H. L. F. da
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