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Registro Completo |
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Biblioteca(s): |
Embrapa Unidades Centrais. |
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Data corrente: |
20/03/1998 |
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Data da última atualização: |
29/10/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
LANZER, E. A.; PROTAS, J. F. da S. |
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Afiliação: |
EDGAR AUGUSTO LANZER, DPE; JOSE FERNANDO DA SILVA PROTAS, CNPSA. |
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Título: |
Estratégias ótimas de descarte de matrizes em suinicultura. |
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Ano de publicação: |
1985 |
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Fonte/Imprenta: |
Pesquisa Agropecuária Brasileira, Brasília, DF, v. 20, n. 6, p. 707-715, jun. 1985. |
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Idioma: |
Português |
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Notas: |
Título em inglês: Optimum sow replacement strategies in swine production. |
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Conteúdo: |
O presente trabalho analisa o problema de elaboracao de estrategias de descarte de femeas reprodutoras, de modo a maximizar a media de leitoes desmamados por matriz por ano, na exploracao suinicola. A questao e incialmente examinada do ponto de vista teorico, revisando-se modelos aplicaveis ao caso. A seguir,estes modelos sao aplicados a um conjunto de dados empiricos de uma granja comercial de Santa Catarina. Os resultados indicam que o uso de estrategias mais elaboradas de descarte de femeas e capaz de elevar substancialmente a eficiencia do plantel reprodutor da empresa a custos virtualmente nulos. Esta eficiencia poderia ser ainda aumentada pela descoberta de metodos eficientes na selecao de matrizes para reposicao, embora o retorno a pesquisa nesta area seja limitado pela baixa repetibilidade do tamanho da leitegada. |
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Palavras-Chave: |
Economic efficiency; Eficiencia economica. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/203867/1/Estrategias-otimas-de-descarte-de-matrizes.pdf
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Marc: |
LEADER 01404naa a2200169 a 4500
001 1104554
005 2019-10-29
008 1985 bl uuuu u00u1 u #d
100 1 $aLANZER, E. A.
245 $aEstratégias ótimas de descarte de matrizes em suinicultura.
260 $c1985
500 $aTítulo em inglês: Optimum sow replacement strategies in swine production.
520 $aO presente trabalho analisa o problema de elaboracao de estrategias de descarte de femeas reprodutoras, de modo a maximizar a media de leitoes desmamados por matriz por ano, na exploracao suinicola. A questao e incialmente examinada do ponto de vista teorico, revisando-se modelos aplicaveis ao caso. A seguir,estes modelos sao aplicados a um conjunto de dados empiricos de uma granja comercial de Santa Catarina. Os resultados indicam que o uso de estrategias mais elaboradas de descarte de femeas e capaz de elevar substancialmente a eficiencia do plantel reprodutor da empresa a custos virtualmente nulos. Esta eficiencia poderia ser ainda aumentada pela descoberta de metodos eficientes na selecao de matrizes para reposicao, embora o retorno a pesquisa nesta area seja limitado pela baixa repetibilidade do tamanho da leitegada.
653 $aEconomic efficiency
653 $aEficiencia economica
700 1 $aPROTAS, J. F. da S.
773 $tPesquisa Agropecuária Brasileira, Brasília, DF$gv. 20, n. 6, p. 707-715, jun. 1985.
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Registro original: |
Embrapa Unidades Centrais (AI-SEDE) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Amazônia Oriental. Para informações adicionais entre em contato com cpatu.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Amazônia Oriental. |
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Data corrente: |
26/10/2016 |
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Data da última atualização: |
23/05/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
REIS, L. P.; SOUZA, A. L. de; MAZZEI, L.; REIS, P. C. M. dos; LEITE, H. G.; SOARES, C. P. B.; TORRES, C. M. M. E.; SILVA, L. F. da; RUSCHEL, A. R. |
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Afiliação: |
Leonardo Pequeno Reis, UFV; Agostinho Lopes de Souza, UFV; LUCAS JOSE MAZZEI DE FREITAS, CPATU; Pamella Carolline Marques dos Reis, UFV; Hélio Garcia Leite, UFV; Carlos Pedro Boechat Soares, UFV; Carlos Moreira Miquelino Eleto Torres, UFV; Liniker Fernandes da Silva, UFV; ADEMIR ROBERTO RUSCHEL, CPATU. |
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Título: |
Prognosis on the diameter of individual trees on the eastern region of the amazon using artificial neural networks. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
Forest Ecology and Management, v. 382, p. 161-167, Dec. 2016. |
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DOI: |
http://dx.doi.org.ez103.periodicos.capes.gov.br/10.1016/j.foreco.2016.10.022 |
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Idioma: |
Inglês |
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Conteúdo: |
The prognosis of forest structure along the cutting cycle, using models of individual trees, is one of the alternatives to manage tropical forests aiming at sustainability. Currently, in forest management practiced in the Amazon Region, growth and production models are not used to predict the future stock of the forest. Thus, the sustainable economic and environmental aspects of this activity remain uncertain. The aim of this present work was to model the growth of individual trees in a forest managed in the Amazon Region, by using artificial neural networks (ANN) to serve as subsidy to the wielder in obtaining future stock after logging, thus reducing uncertainty on forest management sustainability. Selective harvest was carried out in 1979 with an intensity of 72.5 m3 ha−1 in a 64 ha area in the Tapajós National Forest - PA. In 1981, 36 permanent plots (50 m × 50 m) were installed at random and inventoried. There were nine successive measurements in 1982, 1983, 1985, 1987, 1992, 1997, 2007, 2010, and 2012. In the modeling of the future diameter, training and testing of ANN were carried out, including different semi-independent competition indexes (DSICI). All ANN, with and without DSICI, presented correlation above 99%, RMSE below 11%, and EF above 0.98. Based on the prognosis of tree growth, we were able to conclude that ANN can be effectively used to assist in the management of tropical forests and, thus, allow for the most suitable cutting intensity and cutting cycle per species, ensuring environmental and economic sustainability of forest management. MenosThe prognosis of forest structure along the cutting cycle, using models of individual trees, is one of the alternatives to manage tropical forests aiming at sustainability. Currently, in forest management practiced in the Amazon Region, growth and production models are not used to predict the future stock of the forest. Thus, the sustainable economic and environmental aspects of this activity remain uncertain. The aim of this present work was to model the growth of individual trees in a forest managed in the Amazon Region, by using artificial neural networks (ANN) to serve as subsidy to the wielder in obtaining future stock after logging, thus reducing uncertainty on forest management sustainability. Selective harvest was carried out in 1979 with an intensity of 72.5 m3 ha−1 in a 64 ha area in the Tapajós National Forest - PA. In 1981, 36 permanent plots (50 m × 50 m) were installed at random and inventoried. There were nine successive measurements in 1982, 1983, 1985, 1987, 1992, 1997, 2007, 2010, and 2012. In the modeling of the future diameter, training and testing of ANN were carried out, including different semi-independent competition indexes (DSICI). All ANN, with and without DSICI, presented correlation above 99%, RMSE below 11%, and EF above 0.98. Based on the prognosis of tree growth, we were able to conclude that ANN can be effectively used to assist in the management of tropical forests and, thus, allow for the most suitable cutting intensity and cutting cy... Mostrar Tudo |
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Palavras-Chave: |
Ciclo de corte; Estrutura florestal; Sustentabilidade. |
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Thesagro: |
Árvore; Diâmetro; Floresta Tropical. |
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Categoria do assunto: |
K Ciência Florestal e Produtos de Origem Vegetal |
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Marc: |
LEADER 02548naa a2200301 a 4500
001 2055417
005 2022-05-23
008 2016 bl uuuu u00u1 u #d
024 7 $ahttp://dx.doi.org.ez103.periodicos.capes.gov.br/10.1016/j.foreco.2016.10.022$2DOI
100 1 $aREIS, L. P.
245 $aPrognosis on the diameter of individual trees on the eastern region of the amazon using artificial neural networks.$h[electronic resource]
260 $c2016
520 $aThe prognosis of forest structure along the cutting cycle, using models of individual trees, is one of the alternatives to manage tropical forests aiming at sustainability. Currently, in forest management practiced in the Amazon Region, growth and production models are not used to predict the future stock of the forest. Thus, the sustainable economic and environmental aspects of this activity remain uncertain. The aim of this present work was to model the growth of individual trees in a forest managed in the Amazon Region, by using artificial neural networks (ANN) to serve as subsidy to the wielder in obtaining future stock after logging, thus reducing uncertainty on forest management sustainability. Selective harvest was carried out in 1979 with an intensity of 72.5 m3 ha−1 in a 64 ha area in the Tapajós National Forest - PA. In 1981, 36 permanent plots (50 m × 50 m) were installed at random and inventoried. There were nine successive measurements in 1982, 1983, 1985, 1987, 1992, 1997, 2007, 2010, and 2012. In the modeling of the future diameter, training and testing of ANN were carried out, including different semi-independent competition indexes (DSICI). All ANN, with and without DSICI, presented correlation above 99%, RMSE below 11%, and EF above 0.98. Based on the prognosis of tree growth, we were able to conclude that ANN can be effectively used to assist in the management of tropical forests and, thus, allow for the most suitable cutting intensity and cutting cycle per species, ensuring environmental and economic sustainability of forest management.
650 $aÁrvore
650 $aDiâmetro
650 $aFloresta Tropical
653 $aCiclo de corte
653 $aEstrutura florestal
653 $aSustentabilidade
700 1 $aSOUZA, A. L. de
700 1 $aMAZZEI, L.
700 1 $aREIS, P. C. M. dos
700 1 $aLEITE, H. G.
700 1 $aSOARES, C. P. B.
700 1 $aTORRES, C. M. M. E.
700 1 $aSILVA, L. F. da
700 1 $aRUSCHEL, A. R.
773 $tForest Ecology and Management$gv. 382, p. 161-167, Dec. 2016.
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