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Registro Completo |
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Biblioteca(s): |
Embrapa Milho e Sorgo. |
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Data corrente: |
25/08/2021 |
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Data da última atualização: |
02/10/2021 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
DUARTE, J. de O.; SANTOS, C. M.; NOCE, M. A.; MIRANDA, R. A. de; ALVARENGA, R. C.; SANTANA, D. P. |
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Afiliação: |
JASON DE OLIVEIRA DUARTE, CNPMS; CHRISTIENE MARA SANTOS, UNIFEMM; MARCO AURELIO NOCE, CNPMS; RUBENS AUGUSTO DE MIRANDA, CNPMS; RAMON COSTA ALVARENGA, CNPMS; DERLI PRUDENTE SANTANA, CNPMS. |
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Título: |
Analysis of the economic, social and environmental impacts of URT/ILPF: corn and sorghun in the central region of Minas Gerais. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
In: WORLD CONGRESS ON INTEGRATED CROP-LIVESTOCK-FORESTRY SYSTEMS, 2., 2021. Proceedings reference. Brasília, DF: Embrapa, 2021. |
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Páginas: |
p. 847-852. |
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ISBN: |
978-65-994135-4-4 |
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Idioma: |
Inglês |
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Notas: |
WCCLF.
Evento online. |
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Conteúdo: |
The objective of this work is to make an analysis of the environmental, social and economic impacts of the ILPF Strategy for agriculture in the central region of Minas Gerais and neighboring areas. The method of analysis of information was based on secondary data. The data were provided by Santos (2020) and by Noce (2017), from two different research for doctoral theses. All the analysis of this work was based on the experience of the project of installation of a URT of the ILPF System in the farm of Embrapa in Sete Lagoas - Brazil. The results analyzed showed that the economic, social and environmental impacts of the Systems implemented in the Central Region of Minas Gerais were positive resulting in farmers seeking to increase their areas with the ILPF system and adding new producers, in a spillover effect of the technology. |
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Thesagro: |
Agricultura Sustentável; Economia; Impacto Econômico; Pequeno Produtor. |
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Thesaurus Nal: |
Economic sustainability; Economics; Small farms. |
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Categoria do assunto: |
A Sistemas de Cultivo |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/226600/1/Analysis-economic.pdf
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Marc: |
LEADER 01806nam a2200289 a 4500
001 2133843
005 2021-10-02
008 2021 bl uuuu u00u1 u #d
020 $a978-65-994135-4-4
100 1 $aDUARTE, J. de O.
245 $aAnalysis of the economic, social and environmental impacts of URT/ILPF$bcorn and sorghun in the central region of Minas Gerais.$h[electronic resource]
260 $aIn: WORLD CONGRESS ON INTEGRATED CROP-LIVESTOCK-FORESTRY SYSTEMS, 2., 2021. Proceedings reference. Brasília, DF: Embrapa$c2021
300 $ap. 847-852.
500 $aWCCLF. Evento online.
520 $aThe objective of this work is to make an analysis of the environmental, social and economic impacts of the ILPF Strategy for agriculture in the central region of Minas Gerais and neighboring areas. The method of analysis of information was based on secondary data. The data were provided by Santos (2020) and by Noce (2017), from two different research for doctoral theses. All the analysis of this work was based on the experience of the project of installation of a URT of the ILPF System in the farm of Embrapa in Sete Lagoas - Brazil. The results analyzed showed that the economic, social and environmental impacts of the Systems implemented in the Central Region of Minas Gerais were positive resulting in farmers seeking to increase their areas with the ILPF system and adding new producers, in a spillover effect of the technology.
650 $aEconomic sustainability
650 $aEconomics
650 $aSmall farms
650 $aAgricultura Sustentável
650 $aEconomia
650 $aImpacto Econômico
650 $aPequeno Produtor
700 1 $aSANTOS, C. M.
700 1 $aNOCE, M. A.
700 1 $aMIRANDA, R. A. de
700 1 $aALVARENGA, R. C.
700 1 $aSANTANA, D. P.
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Registro original: |
Embrapa Milho e Sorgo (CNPMS) |
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Registro Completo
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
18/09/2013 |
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Data da última atualização: |
03/01/2018 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
MOTA, R. R.; MARQUES, L. F. A.; LOPES, P. S.; SILVA, L. P. da; RESENDE, M. D. V. de; TORRES, R. A. |
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Afiliação: |
UFV; UNIVERSIDADE FEDERAL DO ESPIRITO SANTO; UFV; UFV; MARCOS DEON VILELA DE RESENDE, CNPF; UFV. |
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Título: |
Genetic evaluation using multi-trait and random regression models in Simmental beef cattle. |
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Ano de publicação: |
2013 |
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Fonte/Imprenta: |
Genetics and Molecular Research, v. 12, n. 3, p. 2465-2480, 2013. |
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Idioma: |
Inglês |
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Conteúdo: |
The Brazilian Association of Simmental and Simbrasil Cattle Farmers provided 29,510 records from 10,659 Simmental beef cattle; these were used to estimate (co)variance components and genetic parameters for weights in the growth trajectory, based on multi-trait (MTM) and random regression models (RRM). The (co)variance components and genetic parameters were estimated by restricted maximum likelihood. In the MTM analysis, the likelihood ratio test was used to determine the significance of random effects included in the model and to define the most appropriate model. All random effects were significant and included in the final model. In the RRM analysis, different adjustments of polynomial orders were compared for 5 different criteria to choose the best fit model. An RRM of third order for the direct additive genetic, direct permanent environmental, maternal additive genetic, and maternal permanent environment effects was sufficient to model variance structures in the growth trajectory of the animals. The (co)variance components were generally similar in MTM and RRM. Direct heritabilities of MTM were slightly lower than RRM and varied from 0.04 to 0.42 and 0.16 to 0.45, respectively. Additive direct correlations were mostly positive and of high magnitude, being highest at closest ages. Considering the results and that pre-adjustment of the weights to standard ages is not required, RRM is recommended for genetic evaluation of Simmental beef cattle in Brazil. |
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Palavras-Chave: |
Componente de variância; Simental; Tragetória de crescimento. |
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Thesagro: |
Gado de Corte; Peso. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/89678/1/Deon-GMR-Genetic.pdf
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Marc: |
LEADER 02202naa a2200241 a 4500
001 1966526
005 2018-01-03
008 2013 bl uuuu u00u1 u #d
100 1 $aMOTA, R. R.
245 $aGenetic evaluation using multi-trait and random regression models in Simmental beef cattle.$h[electronic resource]
260 $c2013
520 $aThe Brazilian Association of Simmental and Simbrasil Cattle Farmers provided 29,510 records from 10,659 Simmental beef cattle; these were used to estimate (co)variance components and genetic parameters for weights in the growth trajectory, based on multi-trait (MTM) and random regression models (RRM). The (co)variance components and genetic parameters were estimated by restricted maximum likelihood. In the MTM analysis, the likelihood ratio test was used to determine the significance of random effects included in the model and to define the most appropriate model. All random effects were significant and included in the final model. In the RRM analysis, different adjustments of polynomial orders were compared for 5 different criteria to choose the best fit model. An RRM of third order for the direct additive genetic, direct permanent environmental, maternal additive genetic, and maternal permanent environment effects was sufficient to model variance structures in the growth trajectory of the animals. The (co)variance components were generally similar in MTM and RRM. Direct heritabilities of MTM were slightly lower than RRM and varied from 0.04 to 0.42 and 0.16 to 0.45, respectively. Additive direct correlations were mostly positive and of high magnitude, being highest at closest ages. Considering the results and that pre-adjustment of the weights to standard ages is not required, RRM is recommended for genetic evaluation of Simmental beef cattle in Brazil.
650 $aGado de Corte
650 $aPeso
653 $aComponente de variância
653 $aSimental
653 $aTragetória de crescimento
700 1 $aMARQUES, L. F. A.
700 1 $aLOPES, P. S.
700 1 $aSILVA, L. P. da
700 1 $aRESENDE, M. D. V. de
700 1 $aTORRES, R. A.
773 $tGenetics and Molecular Research$gv. 12, n. 3, p. 2465-2480, 2013.
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Embrapa Florestas (CNPF) |
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