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Registro Completo |
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Biblioteca(s): |
Embrapa Cerrados. |
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Data corrente: |
15/12/2009 |
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Data da última atualização: |
05/08/2013 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
SOUZA, K. W. de; LIMA, H. N.; SCHAEFER, C. E. G. R.; TEIXEIRA, W. G.; PULROLNIK, K.; CORRÊA, G. R. |
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Afiliação: |
KLEBERSON WORSLLEY DE SOUZA, UFV; HEDINALDO NARCISO LIMA, UFAM; CARLOS ERNESTO G. R. SCHAEFER, UFV; WENCESLAU GERALDES TEIXEIRA, CPAA; KARINA PULROLNIK, CPAC; GUILHERME RESENDE CORREA, UFV. |
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Título: |
Phosphorus forms in cultivated indian black earth (anthrosols) of varying texture in the Brazilian Amazon. |
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Ano de publicação: |
2009 |
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Fonte/Imprenta: |
Revista Brasileira de Ciência do Solo, v. 33, p. 1347 - 1355, 2009. |
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Idioma: |
Inglês |
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Conteúdo: |
Despite the agricultural importance of India Black Earth (IBE) in the Amazon region, there are few studies that report on the relation between soil texture and chemical fertility of IBE. These soils of pre-Colobian origin, with high contents of P, Ca and other nutrients are found across the Amazon valley. IBE profiles were studied to evaluate the total contents of P, its primary chemical forms and the P transformation phases in areas with IBE soils of variable texture and in adjacent reference soils. The soil texture strongly influenced soil fertility, changing in terms of transformation of the primary P forms and, consequently, predominant P forms in IBE. Soils with texture varying between clay and heavy clay had higher total P contents and primary Ca-P forms. Highest P-Al and lowest total P amounts werw observed at the site Rio Preto da Eva, where texture varies from sandy, loam to sandy clay loam. In the IBE with clay texture the amounts of soluble P, extracted with NH4CI were highest, although different from Mehlich 1-extractable amounts. |
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Palavras-Chave: |
Amazon black earth; Amazon soils; Amazônia Brasileira; Anthropogenic soils; Soil P fractionation. |
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Thesagro: |
Fósforo; Química; Solo; Textura. |
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Thesaurus Nal: |
Anthrosols; soil; soil chemistry; terra preta; upland soils. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/86984/1/souza-kwde-01-2009.pdf
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Marc: |
LEADER 02022naa a2200349 a 4500
001 1577957
005 2013-08-05
008 2009 bl uuuu u00u1 u #d
100 1 $aSOUZA, K. W. de
245 $aPhosphorus forms in cultivated indian black earth (anthrosols) of varying texture in the Brazilian Amazon.
260 $c2009
520 $aDespite the agricultural importance of India Black Earth (IBE) in the Amazon region, there are few studies that report on the relation between soil texture and chemical fertility of IBE. These soils of pre-Colobian origin, with high contents of P, Ca and other nutrients are found across the Amazon valley. IBE profiles were studied to evaluate the total contents of P, its primary chemical forms and the P transformation phases in areas with IBE soils of variable texture and in adjacent reference soils. The soil texture strongly influenced soil fertility, changing in terms of transformation of the primary P forms and, consequently, predominant P forms in IBE. Soils with texture varying between clay and heavy clay had higher total P contents and primary Ca-P forms. Highest P-Al and lowest total P amounts werw observed at the site Rio Preto da Eva, where texture varies from sandy, loam to sandy clay loam. In the IBE with clay texture the amounts of soluble P, extracted with NH4CI were highest, although different from Mehlich 1-extractable amounts.
650 $aAnthrosols
650 $asoil
650 $asoil chemistry
650 $aterra preta
650 $aupland soils
650 $aFósforo
650 $aQuímica
650 $aSolo
650 $aTextura
653 $aAmazon black earth
653 $aAmazon soils
653 $aAmazônia Brasileira
653 $aAnthropogenic soils
653 $aSoil P fractionation
700 1 $aLIMA, H. N.
700 1 $aSCHAEFER, C. E. G. R.
700 1 $aTEIXEIRA, W. G.
700 1 $aPULROLNIK, K.
700 1 $aCORRÊA, G. R.
773 $tRevista Brasileira de Ciência do Solo$gv. 33, p. 1347 - 1355, 2009.
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Registro original: |
Embrapa Cerrados (CPAC) |
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Registro Completo
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Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
28/08/2012 |
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Data da última atualização: |
05/03/2020 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
MENDONÇA-SANTOS, M. de L.; SANTOS, H. G. dos; COELHO, M. R. |
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Afiliação: |
MARIA DE LOURDES M SANTOS BREFIN, CNPS; HUMBERTO GONCALVES DOS SANTOS, CNPS; MAURICIO RIZZATO COELHO, CNPS. |
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Título: |
Modelling and digital soil mapping of the organic carbon stock in the topsoil (0-10 cm) of Rio de Janeiro State, Brazil. |
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Ano de publicação: |
2008 |
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Fonte/Imprenta: |
In: GLOBAL WORKSHOP ON DIGITAL SOIL MAPPING, 3., 2008, Logan, Utah. Bridging research, production, and environmental applications: papers. Logan, UT: University of Utah, 2008. 1 CD-ROM. |
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Idioma: |
Inglês |
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Conteúdo: |
A soil database with 431 soil profiles of Rio de Janeiro State was used in the scope of a research project entitled "Quantifying the magnitude, spatial distribution and organic carbon in soils of Rio de Janeiro State, using quantitative modeling, GIS and database technologies" (Projeto Carbono_RJ, funded by FAPERJ - Carlos Chagas Filho Foundation for Research Support in Rio de Janeiro State). Considering that these soil data were collected to other purpose, there was only a few sparse data to soil bulk density, which is essential to estimate of soil organic carbon (SOC) stock. To face this problem, pedotransfer functions (PTFs) were estimated to be used in the modeling of organic soil carbon of topsoil (0-10 cm), using s.c.o.r.p.a.n model. The following environmental correlates were used as predictor variables: satellite data, lithology and soil maps, DEM (Digital Elevation Model) and its derivatives as source of information for these variables. This dataset, that represents the best organized soil dataset in Brazil, is working as a trial for learning/teaching of Digital Soil Mapping (DSM) using a variety of methods for predicting soil classes and their properties. The "f" of the equation was modeled by means of multilinear analysis and regression-kriging. Seven different models were built and compared through statistical methods. In a general way, all models performed well to predict the SOC stock. Nevertheless, model 6 (M6) was an exceptional model, presenting the smallest AIC e RMSE, due to the use of existing soil information (polygon soil map) as predictor variable, in addition to the variables used in the other models. The result obtained in M6 was used for mapping topsoil carbon stock at spatial resolution of 90 m. MenosA soil database with 431 soil profiles of Rio de Janeiro State was used in the scope of a research project entitled "Quantifying the magnitude, spatial distribution and organic carbon in soils of Rio de Janeiro State, using quantitative modeling, GIS and database technologies" (Projeto Carbono_RJ, funded by FAPERJ - Carlos Chagas Filho Foundation for Research Support in Rio de Janeiro State). Considering that these soil data were collected to other purpose, there was only a few sparse data to soil bulk density, which is essential to estimate of soil organic carbon (SOC) stock. To face this problem, pedotransfer functions (PTFs) were estimated to be used in the modeling of organic soil carbon of topsoil (0-10 cm), using s.c.o.r.p.a.n model. The following environmental correlates were used as predictor variables: satellite data, lithology and soil maps, DEM (Digital Elevation Model) and its derivatives as source of information for these variables. This dataset, that represents the best organized soil dataset in Brazil, is working as a trial for learning/teaching of Digital Soil Mapping (DSM) using a variety of methods for predicting soil classes and their properties. The "f" of the equation was modeled by means of multilinear analysis and regression-kriging. Seven different models were built and compared through statistical methods. In a general way, all models performed well to predict the SOC stock. Nevertheless, model 6 (M6) was an exceptional model, presenting the smallest... Mostrar Tudo |
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Thesagro: |
Carbono; Estoque. |
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Thesaurus NAL: |
Soil organic carbon. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/65152/1/Mendonca-Santos-Session-6.pdf
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Marc: |
LEADER 02449nam a2200169 a 4500
001 1932483
005 2020-03-05
008 2008 bl uuuu u00u1 u #d
100 1 $aMENDONÇA-SANTOS, M. de L.
245 $aModelling and digital soil mapping of the organic carbon stock in the topsoil (0-10 cm) of Rio de Janeiro State, Brazil.$h[electronic resource]
260 $aIn: GLOBAL WORKSHOP ON DIGITAL SOIL MAPPING, 3., 2008, Logan, Utah. Bridging research, production, and environmental applications: papers. Logan, UT: University of Utah, 2008. 1 CD-ROM.$c2008
520 $aA soil database with 431 soil profiles of Rio de Janeiro State was used in the scope of a research project entitled "Quantifying the magnitude, spatial distribution and organic carbon in soils of Rio de Janeiro State, using quantitative modeling, GIS and database technologies" (Projeto Carbono_RJ, funded by FAPERJ - Carlos Chagas Filho Foundation for Research Support in Rio de Janeiro State). Considering that these soil data were collected to other purpose, there was only a few sparse data to soil bulk density, which is essential to estimate of soil organic carbon (SOC) stock. To face this problem, pedotransfer functions (PTFs) were estimated to be used in the modeling of organic soil carbon of topsoil (0-10 cm), using s.c.o.r.p.a.n model. The following environmental correlates were used as predictor variables: satellite data, lithology and soil maps, DEM (Digital Elevation Model) and its derivatives as source of information for these variables. This dataset, that represents the best organized soil dataset in Brazil, is working as a trial for learning/teaching of Digital Soil Mapping (DSM) using a variety of methods for predicting soil classes and their properties. The "f" of the equation was modeled by means of multilinear analysis and regression-kriging. Seven different models were built and compared through statistical methods. In a general way, all models performed well to predict the SOC stock. Nevertheless, model 6 (M6) was an exceptional model, presenting the smallest AIC e RMSE, due to the use of existing soil information (polygon soil map) as predictor variable, in addition to the variables used in the other models. The result obtained in M6 was used for mapping topsoil carbon stock at spatial resolution of 90 m.
650 $aSoil organic carbon
650 $aCarbono
650 $aEstoque
700 1 $aSANTOS, H. G. dos
700 1 $aCOELHO, M. R.
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