|
|
Registro Completo |
Biblioteca(s): |
Embrapa Gado de Leite. |
Data corrente: |
14/11/2016 |
Data da última atualização: |
12/12/2022 |
Tipo da produção científica: |
Documentos |
Autoria: |
ARCURI, P. B.; OTENIO, M. H.; CARNEIRO, J. da C.; MACHADO, J. C.; GOMIDE, E. V. de A.; FILGUEIRAS, J. da S. |
Afiliação: |
PEDRO BRAGA ARCURI, CNPGL; MARCELO HENRIQUE OTENIO, CNPGL; JAILTON DA COSTA CARNEIRO, CNPGL; JUAREZ CAMPOLINA MACHADO, CNPGL; ESTER VILELA DE ANDRADE GOMIDE, CNPGL; JUCELIA DA SILVA FILGUEIRAS, CNPGL. |
Título: |
Gestão de P&D na Embrapa Gado de Leite: compêndio 2016/2017. |
Ano de publicação: |
2016 |
Fonte/Imprenta: |
Juiz de Fora: Embrapa Gado de Leite, 2016. |
Páginas: |
40 p. |
Série: |
(Embrapa Gado de Leite. Documentos, 196). |
Idioma: |
Português |
Conteúdo: |
Este documento traz uma compilação da estrutura de gestão de P&D na Embrapa Gado de Leite, das normas, documentos e orientações referentes aos trâmites de propostas. |
Palavras-Chave: |
Gestão e desenvolvimento; Núcleos temáticos. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/149992/1/DOC-196-Gestao-PD-completo.pdf
|
Marc: |
LEADER 00804nam a2200217 a 4500 001 2056360 005 2022-12-12 008 2016 bl uuuu u0uu1 u #d 100 1 $aARCURI, P. B. 245 $aGestão de P&D na Embrapa Gado de Leite$bcompêndio 2016/2017. 260 $aJuiz de Fora: Embrapa Gado de Leite$c2016 300 $a40 p. 490 $a(Embrapa Gado de Leite. Documentos, 196). 520 $aEste documento traz uma compilação da estrutura de gestão de P&D na Embrapa Gado de Leite, das normas, documentos e orientações referentes aos trâmites de propostas. 653 $aGestão e desenvolvimento 653 $aNúcleos temáticos 700 1 $aOTENIO, M. H. 700 1 $aCARNEIRO, J. da C. 700 1 $aMACHADO, J. C. 700 1 $aGOMIDE, E. V. de A. 700 1 $aFILGUEIRAS, J. da S.
Download
Esconder MarcMostrar Marc Completo |
Registro original: |
Embrapa Gado de Leite (CNPGL) |
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
|
|
Registro Completo
Biblioteca(s): |
Embrapa Solos. |
Data corrente: |
26/06/2020 |
Data da última atualização: |
26/06/2020 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 2 |
Autoria: |
CORDEIRO, F. R.; CESÁRIO, F. V.; FONTANA, A.; ANJOS, L. H. C. dos; CANTO, A. C. B. do; TEIXEIRA, W. G. |
Afiliação: |
FERNANDA REIS CORDEIRO, UFRRJ; FERNANDO VIEIRA CESÁRIO, UFF; ADEMIR FONTANA, CNPS; LÚCIA HELENA CUNHA DOS ANJOS, UFRRJ; ANA CAROLINA BARBOSA DO CANTO, UFF; WENCESLAU GERALDES TEIXEIRA, CNPS. |
Título: |
Pedotransfer functions: the role of soil chemical properties units coversion for soil classification. |
Ano de publicação: |
2020 |
Fonte/Imprenta: |
Revista Brasileira de Ciência do Solo, v. 44, e0190086, 2020. |
DOI: |
https://doi.org/10.36783/18069657rbcs20190 |
Idioma: |
Inglês |
Conteúdo: |
Chemical soil analysis data can be expressed by weight (i.e., gravimetric basis) or volume (i.e., volumetric basis) of the fine earth (sieved >=2 mm), resulting in different units, cmolc kg-1 and cmolc dm-3, respectively. The research problem is that the difference between methods to express the same soil properties hinders the comparison of results and database or dataset standardization. This paper aims to develop pedotransfer functions (PTF) to obtain the density of fine earth, which will then be used for conversion data expressed in volumetric to gravimetric basis, or vice versa, that will be applied to compare results and to standardize databases with different units. Soils samples, including profiles of the main soil orders in Brazil such as Latossolos (Ferralsols or Oxisols)and Argissolos (Acrisols or Ultisols), from the states of Rondônia, Roraima, and Mato Grosso do Sul (132 horizons) were selected and weighed (in triplicate) to obtain the fine earth mass contained in a volume of 10 cm3. The mass values were used to calculate the fine earth density. Spearman's correlation analysis was used between the density and nine soil properties (coarse sand, fine sand, total sand, silt, clay, clay dispersed in water, clay dispersion, particle density, and organic carbon). The total sand, clay, and organic carbon showed the best correlations, therefore they were selected to construct the pedotransfer functions. Nonlinear regression techniques were used to obtain the models (PTFs) to predict density, which was used for unit conversion. As a result, the residual standard error (RSE) statistics of the models were: 0.0920, 0.1231, and 0.1633 g cm-3, respectively for PTF1 (using total sand as a predictor), PTF2 (using clay), and PTF3 (using organic carbon). Independent data was used to evaluate the accuracy of the models by residue analysis and the RSE. For the validation, the lowest RSE obtained was from the PTF1, so the best performance. Thus, to convert values of the chemical properties from a volumetric to gravimetric basis, the value must be divided by the predicted density. While, the conversion from gravimetric to volumetric basis requires that the value be multiplied by the predicted density. The PTFs using the properties total sand, clay, and organic carbon as predictor variables, allowed conversion of analytical data of soil samples expressed in the volumetric basis to gravimetric and vice versa, which can be used for dataset or database standardization. MenosChemical soil analysis data can be expressed by weight (i.e., gravimetric basis) or volume (i.e., volumetric basis) of the fine earth (sieved >=2 mm), resulting in different units, cmolc kg-1 and cmolc dm-3, respectively. The research problem is that the difference between methods to express the same soil properties hinders the comparison of results and database or dataset standardization. This paper aims to develop pedotransfer functions (PTF) to obtain the density of fine earth, which will then be used for conversion data expressed in volumetric to gravimetric basis, or vice versa, that will be applied to compare results and to standardize databases with different units. Soils samples, including profiles of the main soil orders in Brazil such as Latossolos (Ferralsols or Oxisols)and Argissolos (Acrisols or Ultisols), from the states of Rondônia, Roraima, and Mato Grosso do Sul (132 horizons) were selected and weighed (in triplicate) to obtain the fine earth mass contained in a volume of 10 cm3. The mass values were used to calculate the fine earth density. Spearman's correlation analysis was used between the density and nine soil properties (coarse sand, fine sand, total sand, silt, clay, clay dispersed in water, clay dispersion, particle density, and organic carbon). The total sand, clay, and organic carbon showed the best correlations, therefore they were selected to construct the pedotransfer functions. Nonlinear regression techniques were used to obtain the models (PTF... Mostrar Tudo |
Palavras-Chave: |
Data standardization; Nonlinear regression; Padronização de dados; Regressão não linear. |
Thesagro: |
Análise do Solo. |
Thesaurus NAL: |
Soil analysis. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/214225/1/Pedotransfer-functions-the-role-of-soil-chemical-properties-units-coversion-for-soil-classification-2020.pdf
|
Marc: |
LEADER 03358naa a2200265 a 4500 001 2123471 005 2020-06-26 008 2020 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.36783/18069657rbcs20190$2DOI 100 1 $aCORDEIRO, F. R. 245 $aPedotransfer functions$bthe role of soil chemical properties units coversion for soil classification.$h[electronic resource] 260 $c2020 520 $aChemical soil analysis data can be expressed by weight (i.e., gravimetric basis) or volume (i.e., volumetric basis) of the fine earth (sieved >=2 mm), resulting in different units, cmolc kg-1 and cmolc dm-3, respectively. The research problem is that the difference between methods to express the same soil properties hinders the comparison of results and database or dataset standardization. This paper aims to develop pedotransfer functions (PTF) to obtain the density of fine earth, which will then be used for conversion data expressed in volumetric to gravimetric basis, or vice versa, that will be applied to compare results and to standardize databases with different units. Soils samples, including profiles of the main soil orders in Brazil such as Latossolos (Ferralsols or Oxisols)and Argissolos (Acrisols or Ultisols), from the states of Rondônia, Roraima, and Mato Grosso do Sul (132 horizons) were selected and weighed (in triplicate) to obtain the fine earth mass contained in a volume of 10 cm3. The mass values were used to calculate the fine earth density. Spearman's correlation analysis was used between the density and nine soil properties (coarse sand, fine sand, total sand, silt, clay, clay dispersed in water, clay dispersion, particle density, and organic carbon). The total sand, clay, and organic carbon showed the best correlations, therefore they were selected to construct the pedotransfer functions. Nonlinear regression techniques were used to obtain the models (PTFs) to predict density, which was used for unit conversion. As a result, the residual standard error (RSE) statistics of the models were: 0.0920, 0.1231, and 0.1633 g cm-3, respectively for PTF1 (using total sand as a predictor), PTF2 (using clay), and PTF3 (using organic carbon). Independent data was used to evaluate the accuracy of the models by residue analysis and the RSE. For the validation, the lowest RSE obtained was from the PTF1, so the best performance. Thus, to convert values of the chemical properties from a volumetric to gravimetric basis, the value must be divided by the predicted density. While, the conversion from gravimetric to volumetric basis requires that the value be multiplied by the predicted density. The PTFs using the properties total sand, clay, and organic carbon as predictor variables, allowed conversion of analytical data of soil samples expressed in the volumetric basis to gravimetric and vice versa, which can be used for dataset or database standardization. 650 $aSoil analysis 650 $aAnálise do Solo 653 $aData standardization 653 $aNonlinear regression 653 $aPadronização de dados 653 $aRegressão não linear 700 1 $aCESÁRIO, F. V. 700 1 $aFONTANA, A. 700 1 $aANJOS, L. H. C. dos 700 1 $aCANTO, A. C. B. do 700 1 $aTEIXEIRA, W. G. 773 $tRevista Brasileira de Ciência do Solo$gv. 44, e0190086, 2020.
Download
Esconder MarcMostrar Marc Completo |
Registro original: |
Embrapa Solos (CNPS) |
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
Expressão de busca inválida. Verifique!!! |
|
|