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Registro Completo |
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Biblioteca(s): |
Embrapa Milho e Sorgo. |
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Data corrente: |
28/10/2015 |
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Data da última atualização: |
14/04/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
GOMES, E. A.; OLIVEIRA-PAIVA, C. A.; LANA, U. G. P.; NODA, R. W.; MARRIEL, I. E.; SOUZA, F. A. de. |
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Afiliação: |
ELIANE APARECIDA GOMES, CNPMS; CHRISTIANE ABREU DE OLIVEIRA PAIVA, CNPMS; UBIRACI GOMES DE PAULA LANA, CNPMS; ROBERTO WILLIANS NODA, CNPMS; IVANILDO EVODIO MARRIEL, CNPMS; FRANCISCO ADRIANO DE SOUZA, CNPMS. |
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Título: |
Arbuscular mycorrhizal fungal communities in the roots of maize lines contrasting for al tolerance grown in limed and non-limed Brazilian Oxisoil. |
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Ano de publicação: |
2015 |
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Fonte/Imprenta: |
Journal of Microbiology and Biotechnology, Seoul, v. 25, n. 7, p. 978-987, 2015. |
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DOI: |
http://dx.doi.org/10.4014/jmb.1408.08002 |
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Idioma: |
Inglês |
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Conteúdo: |
Aluminum (Al) toxicity is one of the greatest limitations to agriculture in acid soils, particularly in tropical regions. Arbuscular mycorrhizal fungi (AMF) can supply plants with nutrients and give protection against Al toxicity. The aim of this work was to evaluate the effects of soil liming (i.e., reducing Al saturation) on the AMF community composition and structure in the roots of maize lines contrasting for Al tolerance. To this end, we constructed four 18S rDNA cloning libraries from L3 (Al tolerant) and L22 (Al sensitive) maize lines grown in limed and non-limed soils. A total of 790 clones were sequenced, 69% belonging to the Glomeromycota phylum. The remaining sequences were from Ascomycota, which were more prominent in the limed soil, mainly in the L3 line. The most abundant AM fungal clones were related to the family Glomeraceae represented by the genera uncultured Glomus followed by Rhizophagus and Funneliformis. However, the most abundant operational taxonomic units with 27% of the Glomeromycota clones was affiliated to genus Racocetra. This genus was present in all the four libraries, but it was predominant in the non-limed soils, suggesting that Racocetra is tolerant to Al toxicity. Similarly, Acaulospora and Rhizophagus were also present mostly in both lines in non-limed soils. The community richness of AMF in the non-limed soils was higher than the limed soil for both lines. The results suggest that the soil Al saturation was the parameter that mostly influences the AMF species composition in the soils in this study. MenosAluminum (Al) toxicity is one of the greatest limitations to agriculture in acid soils, particularly in tropical regions. Arbuscular mycorrhizal fungi (AMF) can supply plants with nutrients and give protection against Al toxicity. The aim of this work was to evaluate the effects of soil liming (i.e., reducing Al saturation) on the AMF community composition and structure in the roots of maize lines contrasting for Al tolerance. To this end, we constructed four 18S rDNA cloning libraries from L3 (Al tolerant) and L22 (Al sensitive) maize lines grown in limed and non-limed soils. A total of 790 clones were sequenced, 69% belonging to the Glomeromycota phylum. The remaining sequences were from Ascomycota, which were more prominent in the limed soil, mainly in the L3 line. The most abundant AM fungal clones were related to the family Glomeraceae represented by the genera uncultured Glomus followed by Rhizophagus and Funneliformis. However, the most abundant operational taxonomic units with 27% of the Glomeromycota clones was affiliated to genus Racocetra. This genus was present in all the four libraries, but it was predominant in the non-limed soils, suggesting that Racocetra is tolerant to Al toxicity. Similarly, Acaulospora and Rhizophagus were also present mostly in both lines in non-limed soils. The community richness of AMF in the non-limed soils was higher than the limed soil for both lines. The results suggest that the soil Al saturation was the parameter that mostly influ... Mostrar Tudo |
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Thesagro: |
Fungo; Micorriza; Milho. |
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Categoria do assunto: |
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Marc: |
LEADER 02324naa a2200229 a 4500
001 2027475
005 2021-04-14
008 2015 bl uuuu u00u1 u #d
024 7 $ahttp://dx.doi.org/10.4014/jmb.1408.08002$2DOI
100 1 $aGOMES, E. A.
245 $aArbuscular mycorrhizal fungal communities in the roots of maize lines contrasting for al tolerance grown in limed and non-limed Brazilian Oxisoil.$h[electronic resource]
260 $c2015
520 $aAluminum (Al) toxicity is one of the greatest limitations to agriculture in acid soils, particularly in tropical regions. Arbuscular mycorrhizal fungi (AMF) can supply plants with nutrients and give protection against Al toxicity. The aim of this work was to evaluate the effects of soil liming (i.e., reducing Al saturation) on the AMF community composition and structure in the roots of maize lines contrasting for Al tolerance. To this end, we constructed four 18S rDNA cloning libraries from L3 (Al tolerant) and L22 (Al sensitive) maize lines grown in limed and non-limed soils. A total of 790 clones were sequenced, 69% belonging to the Glomeromycota phylum. The remaining sequences were from Ascomycota, which were more prominent in the limed soil, mainly in the L3 line. The most abundant AM fungal clones were related to the family Glomeraceae represented by the genera uncultured Glomus followed by Rhizophagus and Funneliformis. However, the most abundant operational taxonomic units with 27% of the Glomeromycota clones was affiliated to genus Racocetra. This genus was present in all the four libraries, but it was predominant in the non-limed soils, suggesting that Racocetra is tolerant to Al toxicity. Similarly, Acaulospora and Rhizophagus were also present mostly in both lines in non-limed soils. The community richness of AMF in the non-limed soils was higher than the limed soil for both lines. The results suggest that the soil Al saturation was the parameter that mostly influences the AMF species composition in the soils in this study.
650 $aFungo
650 $aMicorriza
650 $aMilho
700 1 $aOLIVEIRA-PAIVA, C. A.
700 1 $aLANA, U. G. P.
700 1 $aNODA, R. W.
700 1 $aMARRIEL, I. E.
700 1 $aSOUZA, F. A. de
773 $tJournal of Microbiology and Biotechnology, Seoul$gv. 25, n. 7, p. 978-987, 2015.
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Embrapa Milho e Sorgo (CNPMS) |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
06/05/2019 |
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Data da última atualização: |
21/01/2020 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
CAON, I. L.; BECKER, W. R.; GANASCINI, D.; CATTANI, C. E. V.; MENDES, I. de S.; PRUDENTE, V. H. R.; OLDONI, L. V.; ANTUNES, J. F. G.; MERCANTE, E. |
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Afiliação: |
IVÃ LUIS CAON, Unioeste; WILLYAN RONALDO BECKER, Unioeste; DIANDRA GANASCINI, Unioeste; CARLOS EDUARDO VIZZOTTO CATTANI, Unioeste; ISAQUE DE SOUZA MENDES, Unioeste; VICTOR HUGO ROHDEN PRUDENTE, Inpe; LUCAS VOLOCHEN OLDONI, Inpe; JOAO FRANCISCO GONCALVES ANTUNES, CNPTIA; ERIVELTO MERCANTE, Unioeste. |
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Título: |
Comparativo entre os classificadores RF e MAXVER, para classificação de uso e cobertura da terra, em diferentes densidades temporais. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 19., 2019, Santos. Anais... São José dos Campos: INPE, 2019. |
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Páginas: |
4 p. |
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ISBN: |
978-85-17-00097-3 |
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Idioma: |
Português |
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Notas: |
Editores: Douglas Francisco Marcolino Gherardi, Ieda Del?Arco Sanches, Luiz Eduardo Oliveira e Cruz de Aragão. SBSR 2019. |
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Conteúdo: |
RESUMO. O uso combinado de sensores com melhor resolução temporal com sensores de melhor resolução espacial, têm permitido o mapeamento detalhado da superfície terrestre. Desse modo destacam-se os algoritmos de predição, que são capazes de unir a melhor resolução espacial de um sensor a melhor resolução temporal de outro. Além das resoluções das imagens, o uso de algoritmos de classificação eficientes é decisivo para se obter elevada acurácia nos mapeamentos. Assim, o objetivo desse trabalho foi comparar os classificadores Random Forest e Máxima Verossimilhança, com diferentes modos de entrada de dados, a fim de definir qual o melhor classificador. Os resultados apontaram que o algoritmo Random Forest apresentou as maiores métricas de acurácia. |
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Palavras-Chave: |
Algoritmo Random Forest; Classificação de imagens; Cobertura da terra; Fusão de imagens; Image classification; Image fusion; STARFM. |
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Thesagro: |
Uso da Terra. |
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Thesaurus NAL: |
Land cover; Land use. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/196958/1/PL-Comparativo-SBSR-2019.pdf
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Marc: |
LEADER 02019nam a2200361 a 4500
001 2108719
005 2020-01-21
008 2019 bl uuuu u00u1 u #d
020 $a978-85-17-00097-3
100 1 $aCAON, I. L.
245 $aComparativo entre os classificadores RF e MAXVER, para classificação de uso e cobertura da terra, em diferentes densidades temporais.$h[electronic resource]
260 $aIn: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 19., 2019, Santos. Anais... São José dos Campos: INPE$c2019
300 $a4 p.
500 $aEditores: Douglas Francisco Marcolino Gherardi, Ieda Del?Arco Sanches, Luiz Eduardo Oliveira e Cruz de Aragão. SBSR 2019.
520 $aRESUMO. O uso combinado de sensores com melhor resolução temporal com sensores de melhor resolução espacial, têm permitido o mapeamento detalhado da superfície terrestre. Desse modo destacam-se os algoritmos de predição, que são capazes de unir a melhor resolução espacial de um sensor a melhor resolução temporal de outro. Além das resoluções das imagens, o uso de algoritmos de classificação eficientes é decisivo para se obter elevada acurácia nos mapeamentos. Assim, o objetivo desse trabalho foi comparar os classificadores Random Forest e Máxima Verossimilhança, com diferentes modos de entrada de dados, a fim de definir qual o melhor classificador. Os resultados apontaram que o algoritmo Random Forest apresentou as maiores métricas de acurácia.
650 $aLand cover
650 $aLand use
650 $aUso da Terra
653 $aAlgoritmo Random Forest
653 $aClassificação de imagens
653 $aCobertura da terra
653 $aFusão de imagens
653 $aImage classification
653 $aImage fusion
653 $aSTARFM
700 1 $aBECKER, W. R.
700 1 $aGANASCINI, D.
700 1 $aCATTANI, C. E. V.
700 1 $aMENDES, I. de S.
700 1 $aPRUDENTE, V. H. R.
700 1 $aOLDONI, L. V.
700 1 $aANTUNES, J. F. G.
700 1 $aMERCANTE, E.
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