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Registro Completo |
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Biblioteca(s): |
Embrapa Acre. |
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Data corrente: |
09/12/2021 |
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Data da última atualização: |
09/12/2021 |
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Tipo da produção científica: |
Folder/Folheto/Cartilha |
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Autoria: |
COSTA, F. de S.; MORAIS, J. C. de N.; ARAÚJO, M. C.; BROWN, V. R. |
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Afiliação: |
FALBERNI DE SOUZA COSTA, CPAF-AC; JÚLIO CESAR DE NEGREIROS MORAIS, SEMAPI; MÔNICA COSTA DE ARAÚJO, SESACRE; VERA REIS BROWN, SEMAPI. |
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Título: |
Plano de controle da poluição veicular do Estado do Acre - PCPV/AC. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Rio Branco, AC: Secretaria de Estado de Meio Ambiente e Políticas Indígenas, 2021. |
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Páginas: |
45 p. |
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Idioma: |
Português |
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Conteúdo: |
Esta publicação apresenta o Plano de Controle da Poluição Veicular – PCPV que, enquanto instrumento de gestão da qualidade do ar, aponta a melhor alternativa de controle da poluição atmosférica, das fontes móveis e/ou das fontes naturais (queimadas), sinalizando a busca pelo monitoramento menos oneroso, porém eficaz, através da rede de monitoramento da qualidade do ar. |
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Palavras-Chave: |
Acre; Air pollution control; Amazonia Occidental; Amazônia Ocidental; Automóviles; Control de la contaminación atmosférica; Western Amazon. |
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Thesagro: |
Controle Ambiental; Políticas Públicas; Poluição do Ar; Veiculo. |
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Thesaurus Nal: |
Automobiles; Public policy. |
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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/228811/1/27239.pdf
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Marc: |
LEADER 01318nam a2200313 a 4500
001 2137391
005 2021-12-09
008 2021 bl uuuu u0uu1 u #d
100 1 $aCOSTA, F. de S.
245 $aPlano de controle da poluição veicular do Estado do Acre - PCPV/AC.$h[electronic resource]
260 $aRio Branco, AC: Secretaria de Estado de Meio Ambiente e Políticas Indígenas$c2021
300 $a45 p.
520 $aEsta publicação apresenta o Plano de Controle da Poluição Veicular – PCPV que, enquanto instrumento de gestão da qualidade do ar, aponta a melhor alternativa de controle da poluição atmosférica, das fontes móveis e/ou das fontes naturais (queimadas), sinalizando a busca pelo monitoramento menos oneroso, porém eficaz, através da rede de monitoramento da qualidade do ar.
650 $aAutomobiles
650 $aPublic policy
650 $aControle Ambiental
650 $aPolíticas Públicas
650 $aPoluição do Ar
650 $aVeiculo
653 $aAcre
653 $aAir pollution control
653 $aAmazonia Occidental
653 $aAmazônia Ocidental
653 $aAutomóviles
653 $aControl de la contaminación atmosférica
653 $aWestern Amazon
700 1 $aMORAIS, J. C. de N.
700 1 $aARAÚJO, M. C.
700 1 $aBROWN, V. R.
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Registro original: |
Embrapa Acre (CPAF-AC) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Gado de Leite. Para informações adicionais entre em contato com cnpgl.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Gado de Leite; Embrapa Recursos Genéticos e Biotecnologia. |
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Data corrente: |
06/11/2019 |
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Data da última atualização: |
06/02/2024 |
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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: |
SILVA, A. A.; SILVA, D. A.; SILVA, F. F.; COSTA, C. N.; LOPES, P. S.; CAETANO, A. R.; THOMPSON, G.; CARVALHEIRA, J. |
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Afiliação: |
A. A. SILVA, UFV; D. A. SILVA, UFV; F. F. SILVA, UFV; CLAUDIO NAPOLIS COSTA, CNPGL; P. S. LOPES, UFV; ALEXANDRE RODRIGUES CAETANO, Cenargen; G. THOMPSON, CIBIO-INBIO, UNIVERSITY OF PORTO, PORTUGAL; J. CARVALHEIRA, CIBIO-INBIO, UNIVERSITY OF PORTO, PORTUGAL. |
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Título: |
Autoregressive single-step test-day model for genomic evaluations of Portuguese Holstein cattle. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
Journal of Dairy Science, v. 102, n. 7, p. 6330-6339, 2019. |
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DOI: |
10.3168/jds.2018-15191 |
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Idioma: |
Inglês |
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Conteúdo: |
The multiple-lactation autoregressive test-day (AR) model is the adopted model for the national genetic evaluation of dairy cattle in Portugal. Under this model, animals' permanent environment effects are assumed to follow a first-order autoregressive process over the long (auto-correlations between parities) and short (auto-correlations between test-days within lactation) terms. Given the relevance of genomic prediction in dairy cattle, it is essential to include marker information in national genetic evaluations. In this context, we aimed to evaluate the feasibility of applying the single-step genomic (G)BLUP to analyze milk yield using the AR model in Portuguese Holstein cattle. In total, 11,434,294 test-day records from the first 3 lactations collected between 1994 and 2017 and 1,071 genotyped bulls were used in this study. Rank correlations and differences in reliability among bulls were used to compare the performance of the traditional (A-AR) and single-step (H-AR) models. These 2 modeling approaches were also applied to reduced data sets with records truncated after 2012 (deleting daughters of tested bulls) to evaluate the predictive ability of the H-AR. Validation scenarios were proposed, taking into account young and proven bulls. Average EBV reliabilities, empirical reliabilities, and genetic trends predicted from the complete and reduced data sets were used to validate the genomic evaluation. Average EBV reliabilities for H-AR (A-AR) using the complete data set were 0.52 (0.16) and 0.72 (0.62) for genotyped bulls with no daughters and bulls with 1 to 9 daughters, respectively. These results showed an increase in EBV reliabilities of 0.10 to 0.36 when genomic information was included, corresponding to a reduction of up to 43% in prediction error variance. Considering the 3 validation scenarios, the inclusion of genomic information improved the average EBV reliability in the reduced data set, which ranged, on average, from 0.16 to 0.26, indicating an increase in the predictive ability. Similarly, empirical reliability increased by up to 0.08 between validation tests. The H-AR outperformed A-AR in terms of genetic trends when unproven genotyped bulls were included. The results suggest that the single-step GBLUP AR model is feasible and may be applied to national Portuguese genetic evaluations for milk yield. MenosThe multiple-lactation autoregressive test-day (AR) model is the adopted model for the national genetic evaluation of dairy cattle in Portugal. Under this model, animals' permanent environment effects are assumed to follow a first-order autoregressive process over the long (auto-correlations between parities) and short (auto-correlations between test-days within lactation) terms. Given the relevance of genomic prediction in dairy cattle, it is essential to include marker information in national genetic evaluations. In this context, we aimed to evaluate the feasibility of applying the single-step genomic (G)BLUP to analyze milk yield using the AR model in Portuguese Holstein cattle. In total, 11,434,294 test-day records from the first 3 lactations collected between 1994 and 2017 and 1,071 genotyped bulls were used in this study. Rank correlations and differences in reliability among bulls were used to compare the performance of the traditional (A-AR) and single-step (H-AR) models. These 2 modeling approaches were also applied to reduced data sets with records truncated after 2012 (deleting daughters of tested bulls) to evaluate the predictive ability of the H-AR. Validation scenarios were proposed, taking into account young and proven bulls. Average EBV reliabilities, empirical reliabilities, and genetic trends predicted from the complete and reduced data sets were used to validate the genomic evaluation. Average EBV reliabilities for H-AR (A-AR) using the complete data set w... Mostrar Tudo |
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Palavras-Chave: |
Autoregressive test-day model; Holstein cattle; Single-step genomic BLUP. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 03130naa a2200253 a 4500
001 2129209
005 2024-02-06
008 2019 bl uuuu u00u1 u #d
024 7 $a10.3168/jds.2018-15191$2DOI
100 1 $aSILVA, A. A.
245 $aAutoregressive single-step test-day model for genomic evaluations of Portuguese Holstein cattle.$h[electronic resource]
260 $c2019
520 $aThe multiple-lactation autoregressive test-day (AR) model is the adopted model for the national genetic evaluation of dairy cattle in Portugal. Under this model, animals' permanent environment effects are assumed to follow a first-order autoregressive process over the long (auto-correlations between parities) and short (auto-correlations between test-days within lactation) terms. Given the relevance of genomic prediction in dairy cattle, it is essential to include marker information in national genetic evaluations. In this context, we aimed to evaluate the feasibility of applying the single-step genomic (G)BLUP to analyze milk yield using the AR model in Portuguese Holstein cattle. In total, 11,434,294 test-day records from the first 3 lactations collected between 1994 and 2017 and 1,071 genotyped bulls were used in this study. Rank correlations and differences in reliability among bulls were used to compare the performance of the traditional (A-AR) and single-step (H-AR) models. These 2 modeling approaches were also applied to reduced data sets with records truncated after 2012 (deleting daughters of tested bulls) to evaluate the predictive ability of the H-AR. Validation scenarios were proposed, taking into account young and proven bulls. Average EBV reliabilities, empirical reliabilities, and genetic trends predicted from the complete and reduced data sets were used to validate the genomic evaluation. Average EBV reliabilities for H-AR (A-AR) using the complete data set were 0.52 (0.16) and 0.72 (0.62) for genotyped bulls with no daughters and bulls with 1 to 9 daughters, respectively. These results showed an increase in EBV reliabilities of 0.10 to 0.36 when genomic information was included, corresponding to a reduction of up to 43% in prediction error variance. Considering the 3 validation scenarios, the inclusion of genomic information improved the average EBV reliability in the reduced data set, which ranged, on average, from 0.16 to 0.26, indicating an increase in the predictive ability. Similarly, empirical reliability increased by up to 0.08 between validation tests. The H-AR outperformed A-AR in terms of genetic trends when unproven genotyped bulls were included. The results suggest that the single-step GBLUP AR model is feasible and may be applied to national Portuguese genetic evaluations for milk yield.
653 $aAutoregressive test-day model
653 $aHolstein cattle
653 $aSingle-step genomic BLUP
700 1 $aSILVA, D. A.
700 1 $aSILVA, F. F.
700 1 $aCOSTA, C. N.
700 1 $aLOPES, P. S.
700 1 $aCAETANO, A. R.
700 1 $aTHOMPSON, G.
700 1 $aCARVALHEIRA, J.
773 $tJournal of Dairy Science$gv. 102, n. 7, p. 6330-6339, 2019.
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