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Registro Completo |
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Biblioteca(s): |
Embrapa Uva e Vinho. |
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Data corrente: |
10/10/2006 |
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Data da última atualização: |
23/01/2018 |
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Tipo da produção científica: |
Sistema de Produção |
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Autoria: |
HICKEL, E.; CALEGARIO, F. F.; MELO, G. W. B. de; KUNH, G. B.; NACHTIGAL, J. C.; MAIA, J. D. G.; PROTAS, J. F. da S.; MELLO, L. M. R. de; GARRIDO, L. da R.; CONCEIÇÃO, M. A. F.; BOTTON, M.; SÔNEGO, O. R.; NAVES, R. de L.; SORIA, S. de J.; FAJARDO, T. V. M.; CAMARDO, U. A. |
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Afiliação: |
GEORGE WELLINGTON BASTOS DE MELO, CNPUV; JAIR COSTA NACHTIGAL, CPACT; JOAO DIMAS GARCIA MAIA, CNPUV; JOSE FERNANDO DA SILVA PROTAS, CNPUV; LOIVA MARIA RIBEIRO DE MELLO, CNPUV; LUCAS DA RESSURREICAO GARRIDO, CNPUV; MARCO ANTONIO FONSECA CONCEICAO, CNPUV; MARCOS BOTTON, CNPUV; ROSEMEIRE DE LELLIS NAVES, CNPUV; THOR VINICIUS MARTINS FAJARDO, CNPUV. |
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Título: |
UVAS sem sementes: cultivares BRS Morena, BRS Clara e BRS Linda. |
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Ano de publicação: |
2005 |
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Fonte/Imprenta: |
Bento Gonçalves: Embrapa Uva e Vinho, 2005. |
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Série: |
(Embrapa Uva e Vinho. Sistemas de Produção, 8). |
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Idioma: |
Português |
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Palavras-Chave: |
BRS Clara; BRS Linda; BRS Morena; Embrapa Uva e Vinho; Propagação; Trato cultural; Uva sem semente; Uvas do Brasil. |
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Thesagro: |
Adubação; Colheita; Doença de Planta; Irrigação; Manejo; Praga; Solo; Variedade; Viticultura. |
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Categoria do assunto: |
-- |
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URL: |
https://sistemasdeproducao.cnptia.embrapa.br/FontesHTML/Uva/UvasSemSementes/index.htm
https://www.cnpuv.embrapa.br/publica/sprod/UvasSemSementes/
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Marc: |
LEADER 01317nam a2200493 a 4500
001 1541456
005 2018-01-23
008 2005 bl uuuu 00u1 u #d
100 1 $aHICKEL, E.
245 $aUVAS sem sementes$bcultivares BRS Morena, BRS Clara e BRS Linda.
260 $aBento Gonçalves: Embrapa Uva e Vinho$c2005
490 $a(Embrapa Uva e Vinho. Sistemas de Produção, 8).
650 $aAdubação
650 $aColheita
650 $aDoença de Planta
650 $aIrrigação
650 $aManejo
650 $aPraga
650 $aSolo
650 $aVariedade
650 $aViticultura
653 $aBRS Clara
653 $aBRS Linda
653 $aBRS Morena
653 $aEmbrapa Uva e Vinho
653 $aPropagação
653 $aTrato cultural
653 $aUva sem semente
653 $aUvas do Brasil
700 1 $aCALEGARIO, F. F.
700 1 $aMELO, G. W. B. de
700 1 $aKUNH, G. B.
700 1 $aNACHTIGAL, J. C.
700 1 $aMAIA, J. D. G.
700 1 $aPROTAS, J. F. da S.
700 1 $aMELLO, L. M. R. de
700 1 $aGARRIDO, L. da R.
700 1 $aCONCEIÇÃO, M. A. F.
700 1 $aBOTTON, M.
700 1 $aSÔNEGO, O. R.
700 1 $aNAVES, R. de L.
700 1 $aSORIA, S. de J.
700 1 $aFAJARDO, T. V. M.
700 1 $aCAMARDO, U. A.
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Registro original: |
Embrapa Uva e Vinho (CNPUV) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Pecuária Sudeste. Para informações adicionais entre em contato com cppse.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Pecuária Sudeste; Embrapa Pecuária Sul. |
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Data corrente: |
17/11/2020 |
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Data da última atualização: |
18/11/2020 |
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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: |
CAVANI, L.; LOPES, F. B.; GIGLIOTI, R.; BRESOLIN, T.; CAMPOS, G. S.; OKINO, C. H.; GULIAS-GOMES, C. C.; CAETANO, A. R.; OLIVEIRA, M. C. de S.; CARDOSO, F. F.; ROSA, G. J. de M.; OLIVEIRA, H. N. de. |
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Afiliação: |
LIGIA CAVANI, UNESP; FERNANDO BRITO LOPES, UNIVERSITY OF WISCONSIN-MADISON, USA; RODRIGO GIGLIOTI, INSTITUTO DE ZOOTECNIA; TIAGO BRESOLIN, UNESP; GABRIEL SOARES CAMPOS, UFRGS; CINTIA HIROMI OKINO, CPPSE; CLAUDIA CRISTINA GULIAS GOMES, CPPSUL; ALEXANDRE RODRIGUES CAETANO, Cenargen; MARCIA CRISTINA DE SENA OLIVEIRA, CPPSE; FERNANDO FLORES CARDOSO, CPPSUL; GUILHERME JORDÃO DE MAGALHÃES ROSA, UNIVERSITY OF WISCONSIN MADISON, USA; HENRIQUE NUNES DE OLIVEIRA, Unesp. |
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Título: |
Inferring phenotypic causal networks for tick infestation, Babesia bovis infection, and weight gain in Hereford and Braford cattle using structural equation models. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Livestock Science, v. 238, aug. 2020, 104032. |
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Páginas: |
8 p. |
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DOI: |
https://doi.org/10.1016/j.livsci.2020.104032 |
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Idioma: |
Inglês |
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Conteúdo: |
Tick infestation and associated diseases (i.e., babesiosis) constitute major drawbacks for improvement of beef cattle productivity in the tropics, mainly when purebred and crossbred taurine animals are used. Host-parasitepathogen interactions form complex biological systems that are poorly understood and which significantly affect production and quality traits in ways yet to be dissected and described. This research was carried out to investigate potential causal relationships, through the use of structural equation modeling (SEM), among tick counts (TC), Babesia bovis infection level (IB) and the gains in weight: from birth to adjusted weaning age (WG), and from weaning to yearling (YG). Statistical analyses were conducted in three steps: 1) Partition of (co) variances into genetic and residual components using Bayesian multiple-trait modeling (MTM); of 2) Search for plausible causal structures by applying the inductive causation (IC) algorithm to the residual (co)variances obtained in the first step; and 3) Final analysis using SEM, which was based on the causal network learned from the IC algorithm. The most plausible results comprised three direct links between traits: WG→YG, TC→WG, and WG→IB with structural coefficients posterior means equal to -0.3026, 6.3620, and 0.0004, respectively. The final inferred directed acyclic graph (DAG) suggests that interventions on TC would directly affect WG, which would then affected YG; moreover, WG could also present a small positive effect on IB. MenosTick infestation and associated diseases (i.e., babesiosis) constitute major drawbacks for improvement of beef cattle productivity in the tropics, mainly when purebred and crossbred taurine animals are used. Host-parasitepathogen interactions form complex biological systems that are poorly understood and which significantly affect production and quality traits in ways yet to be dissected and described. This research was carried out to investigate potential causal relationships, through the use of structural equation modeling (SEM), among tick counts (TC), Babesia bovis infection level (IB) and the gains in weight: from birth to adjusted weaning age (WG), and from weaning to yearling (YG). Statistical analyses were conducted in three steps: 1) Partition of (co) variances into genetic and residual components using Bayesian multiple-trait modeling (MTM); of 2) Search for plausible causal structures by applying the inductive causation (IC) algorithm to the residual (co)variances obtained in the first step; and 3) Final analysis using SEM, which was based on the causal network learned from the IC algorithm. The most plausible results comprised three direct links between traits: WG→YG, TC→WG, and WG→IB with structural coefficients posterior means equal to -0.3026, 6.3620, and 0.0004, respectively. The final inferred directed acyclic graph (DAG) suggests that interventions on TC would directly affect WG, which would then affected YG; moreover, WG could also presen... Mostrar Tudo |
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Palavras-Chave: |
Causality; Genetic parameter; Inductive causation; Tick resistance. |
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Thesaurus NAL: |
Babesiosis. |
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Categoria do assunto: |
H Saúde e Patologia |
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Marc: |
LEADER 02577naa a2200337 a 4500
001 2126667
005 2020-11-18
008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.livsci.2020.104032$2DOI
100 1 $aCAVANI, L.
245 $aInferring phenotypic causal networks for tick infestation, Babesia bovis infection, and weight gain in Hereford and Braford cattle using structural equation models.$h[electronic resource]
260 $c2020
300 $a8 p.
520 $aTick infestation and associated diseases (i.e., babesiosis) constitute major drawbacks for improvement of beef cattle productivity in the tropics, mainly when purebred and crossbred taurine animals are used. Host-parasitepathogen interactions form complex biological systems that are poorly understood and which significantly affect production and quality traits in ways yet to be dissected and described. This research was carried out to investigate potential causal relationships, through the use of structural equation modeling (SEM), among tick counts (TC), Babesia bovis infection level (IB) and the gains in weight: from birth to adjusted weaning age (WG), and from weaning to yearling (YG). Statistical analyses were conducted in three steps: 1) Partition of (co) variances into genetic and residual components using Bayesian multiple-trait modeling (MTM); of 2) Search for plausible causal structures by applying the inductive causation (IC) algorithm to the residual (co)variances obtained in the first step; and 3) Final analysis using SEM, which was based on the causal network learned from the IC algorithm. The most plausible results comprised three direct links between traits: WG→YG, TC→WG, and WG→IB with structural coefficients posterior means equal to -0.3026, 6.3620, and 0.0004, respectively. The final inferred directed acyclic graph (DAG) suggests that interventions on TC would directly affect WG, which would then affected YG; moreover, WG could also present a small positive effect on IB.
650 $aBabesiosis
653 $aCausality
653 $aGenetic parameter
653 $aInductive causation
653 $aTick resistance
700 1 $aLOPES, F. B.
700 1 $aGIGLIOTI, R.
700 1 $aBRESOLIN, T.
700 1 $aCAMPOS, G. S.
700 1 $aOKINO, C. H.
700 1 $aGULIAS-GOMES, C. C.
700 1 $aCAETANO, A. R.
700 1 $aOLIVEIRA, M. C. de S.
700 1 $aCARDOSO, F. F.
700 1 $aROSA, G. J. de M.
700 1 $aOLIVEIRA, H. N. de
773 $tLivestock Science$gv. 238, aug. 2020, 104032.
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Embrapa Pecuária Sudeste (CPPSE) |
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