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 | Acesso ao texto completo restrito à biblioteca da Embrapa Solos. Para informações adicionais entre em contato com cnps.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
13/10/2008 |
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Data da última atualização: |
11/04/2024 |
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Tipo da produção científica: |
Capítulo em Livro Técnico-Científico |
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Autoria: |
MENDONÇA-SANTOS, M. de L.; SANTOS, H. G. dos; DART, R. de O.; PARES, J. G. |
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Afiliação: |
MARIA DE LOURDES MENDONÇA SANTOS BREFIN, CNPS; HUMBERTO GONCALVES DOS SANTOS, CNPS; RICARDO DE OLIVEIRA DART, CNPS; JERÔNIMO GUEDES PARÉS. |
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Título: |
Digital mapping of soil classes in Rio de Janeiro State, Brazil: data, modelling and prediction. |
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Ano de publicação: |
2008 |
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Fonte/Imprenta: |
In: HARTEMINK, A. E.; McBRATNEY, A.; MENDONÇA-SANTOS, M. de L. (ed.). Digital soil mapping with limited data. Dordrecht: Springer, 2008. cap. 34, p. 381-396. |
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DOI: |
https://doi.org/10.1007/978-1-4020-8592-5_34 |
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Idioma: |
Inglês |
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Conteúdo: |
A soil database for Rio de Janeiro State was collated in Access, for a project on quantifying the magnitude, spatial distribution and organic carbon in the soils of Rio de Janeiro State (Projeto Carbono_RJ). The main activities were the search, selection, analysis and review of the data for each soil profile already described in the study area, the georeferencing of each soil profile (when spatial coordinates were not available) and the input of new soil profiles into a new interface. The Rio de Janeiro soil dataset now contains 731 soil profiles, 2744 soil horizons, and 48 soil attributes usually described at the soil survey process. From this soil dataset, only 431 soil profiles that were adequately geo-located have been used in this application. The dataset contains limited data for bulk density and hydraulic soil properties, among others. From this dataset, quantitative modelling and digital soil mapping have been completed experimentally at 90 m resolution, using soil data and predictor variables, such as satellite images, lithology, a prior soil map and a DEM and its derivates. This dataset, which is one of the more complete soil datasets in Brazil, is being used as a testbed for learning and teaching DSM, using a variety of methods based on the scorpan model (Embrapa, 2006). In the first instance, the soil dataset was used to predict soil classes at the Order level of the Brazilian Soil Classification System ? SiBCS (Embrapa, 2006). Five models were built and their results were compared and mapped. MenosA soil database for Rio de Janeiro State was collated in Access, for a project on quantifying the magnitude, spatial distribution and organic carbon in the soils of Rio de Janeiro State (Projeto Carbono_RJ). The main activities were the search, selection, analysis and review of the data for each soil profile already described in the study area, the georeferencing of each soil profile (when spatial coordinates were not available) and the input of new soil profiles into a new interface. The Rio de Janeiro soil dataset now contains 731 soil profiles, 2744 soil horizons, and 48 soil attributes usually described at the soil survey process. From this soil dataset, only 431 soil profiles that were adequately geo-located have been used in this application. The dataset contains limited data for bulk density and hydraulic soil properties, among others. From this dataset, quantitative modelling and digital soil mapping have been completed experimentally at 90 m resolution, using soil data and predictor variables, such as satellite images, lithology, a prior soil map and a DEM and its derivates. This dataset, which is one of the more complete soil datasets in Brazil, is being used as a testbed for learning and teaching DSM, using a variety of methods based on the scorpan model (Embrapa, 2006). In the first instance, the soil dataset was used to predict soil classes at the Order level of the Brazilian Soil Classification System ? SiBCS (Embrapa, 2006). Five models were built and their re... Mostrar Tudo |
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Palavras-Chave: |
Brasil; Mapeamento digital; Rio de Janeiro. |
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Thesagro: |
Solo. |
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Thesaurus Nal: |
Soil map. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 02339naa a2200229 a 4500
001 1337609
005 2024-04-11
008 2008 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1007/978-1-4020-8592-5_34$2DOI
100 1 $aMENDONÇA-SANTOS, M. de L.
245 $aDigital mapping of soil classes in Rio de Janeiro State, Brazil$bdata, modelling and prediction.$h[electronic resource]
260 $c2008
520 $aA soil database for Rio de Janeiro State was collated in Access, for a project on quantifying the magnitude, spatial distribution and organic carbon in the soils of Rio de Janeiro State (Projeto Carbono_RJ). The main activities were the search, selection, analysis and review of the data for each soil profile already described in the study area, the georeferencing of each soil profile (when spatial coordinates were not available) and the input of new soil profiles into a new interface. The Rio de Janeiro soil dataset now contains 731 soil profiles, 2744 soil horizons, and 48 soil attributes usually described at the soil survey process. From this soil dataset, only 431 soil profiles that were adequately geo-located have been used in this application. The dataset contains limited data for bulk density and hydraulic soil properties, among others. From this dataset, quantitative modelling and digital soil mapping have been completed experimentally at 90 m resolution, using soil data and predictor variables, such as satellite images, lithology, a prior soil map and a DEM and its derivates. This dataset, which is one of the more complete soil datasets in Brazil, is being used as a testbed for learning and teaching DSM, using a variety of methods based on the scorpan model (Embrapa, 2006). In the first instance, the soil dataset was used to predict soil classes at the Order level of the Brazilian Soil Classification System ? SiBCS (Embrapa, 2006). Five models were built and their results were compared and mapped.
650 $aSoil map
650 $aSolo
653 $aBrasil
653 $aMapeamento digital
653 $aRio de Janeiro
700 1 $aSANTOS, H. G. dos
700 1 $aDART, R. de O.
700 1 $aPARES, J. G.
773 $tIn: HARTEMINK, A. E.; McBRATNEY, A.; MENDONÇA-SANTOS, M. de L. (ed.). Digital soil mapping with limited data. Dordrecht: Springer, 2008. cap. 34, p. 381-396.
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Registro original: |
Embrapa Solos (CNPS) |
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| Acesso ao texto completo restrito à biblioteca da Embrapa Unidades Centrais. Para informações adicionais entre em contato com biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Unidades Centrais. |
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Data corrente: |
19/07/2002 |
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Data da última atualização: |
19/07/2002 |
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Autoria: |
ZAMBOLIM, L.; RODRIGUES, C. H.; MARTINS, M. C. del P. |
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Título: |
Controle Químico da Ferrugem-do-Feijoeiro |
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Ano de publicação: |
1987 |
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Fonte/Imprenta: |
Pesquisa Agropecuária Brasileira, Brasília, v.22, n.2, p.179-186, fev.1987 |
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Idioma: |
Português |
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Conteúdo: |
0 presente estudo, realizado em casa de vegetação, mostrou que os fungicidas, com o princípio ativo dosado em ppm - clorotalonil (1.125), mancozeb (1.200), bitertanol (125), tiofanato metílico mais tiram (400), triadimefon (125), triforine (100) e oxicarboxin (375) -,apresentaram capacidade de proteção quando aplicados até quinze dias antes da inoculação por Uromyces phaseoli var. typica. Oxicarboxin e triforine apresentaram ação curativa quando são aplicados até seis dias após a moculação, e bitertanol e triadimefon, quando aplicados até três dias após. Os ensaios de campo mostraram que os fungicidas mais eficientes no controle da ferrugem-do-feijoeiro foram: oxicarboxin (0,5 kg/ha do p.c.), bitertanol (0,5 kg/ha do p.c.) e triforine (0,5 I/ha do p.c.),
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Palavras-Chave: |
ação curativa; capacidade de proteção; fungicidas; phaseoli var; typica; U. |
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Thesagro: |
Phaseolus Vulgaris. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 01400naa a2200229 a 4500
001 1107497
005 2002-07-19
008 1987 bl uuuu u00u1 u #d
100 1 $aZAMBOLIM, L.
245 $aControle Químico da Ferrugem-do-Feijoeiro
260 $c1987
520 $a0 presente estudo, realizado em casa de vegetação, mostrou que os fungicidas, com o princípio ativo dosado em ppm - clorotalonil (1.125), mancozeb (1.200), bitertanol (125), tiofanato metílico mais tiram (400), triadimefon (125), triforine (100) e oxicarboxin (375) -,apresentaram capacidade de proteção quando aplicados até quinze dias antes da inoculação por Uromyces phaseoli var. typica. Oxicarboxin e triforine apresentaram ação curativa quando são aplicados até seis dias após a moculação, e bitertanol e triadimefon, quando aplicados até três dias após. Os ensaios de campo mostraram que os fungicidas mais eficientes no controle da ferrugem-do-feijoeiro foram: oxicarboxin (0,5 kg/ha do p.c.), bitertanol (0,5 kg/ha do p.c.) e triforine (0,5 I/ha do p.c.),
650 $aPhaseolus Vulgaris
653 $aação curativa
653 $acapacidade de proteção
653 $afungicidas
653 $aphaseoli var
653 $atypica
653 $aU
700 1 $aRODRIGUES, C. H.
700 1 $aMARTINS, M. C. del P.
773 $tPesquisa Agropecuária Brasileira, Brasília$gv.22, n.2, p.179-186, fev.1987
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