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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. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Gado de Leite. |
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Data corrente: |
18/03/2011 |
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Data da última atualização: |
10/08/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
SILVA, M. V. G. B.; SONSTEGARD, T. S.; THALLMAN, R. M.; CONNOR, E. E.; SCHNABEL, R. D.; TASSELL, C. P. V. |
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Afiliação: |
MARCOS VINICIUS GUALBERTO B SILVA, CNPGL; Tad Stewart Sonstegard, USDA/ARS; RICHARD M. THALLMAN, USDA; ERIN E. CONNOR, USDA; ROBERT D. SCHNABEL, UNIVERSITY OF MISSOURI-COLUMBIA; CURT P. VAN TASSELL, USDA. |
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Título: |
Characterization of DGAT1 Allelic effects in a sample of north american holstein cattle. |
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Ano de publicação: |
2010 |
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Fonte/Imprenta: |
Animal Biotechnology, v. 21, p. 88-99, 2010. |
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DOI: |
https://doi.org/10.1080/10495390903504625 |
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Idioma: |
Inglês |
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Conteúdo: |
A putative causative mutation underlying a QTL was identified as a lysine to alanine non-conservative substitution at amino acid 232 of the gene encoding the acylCoA:diacylglycerol acyltransferase (DGAT1) protein. Our goal was to characterize the allelic substitution effects of this DGAT1 mutation in a large sample of Holstein bulls from North America. Statistically significant effects were identified for all of the milk production traits and somatic cell scores. Estimated average effects of substituting the lysine allele for the alanine variant on Holstein bull daughter yield deviations were −81 kg, 3.7 kg, −1.1 kg, 0.063%, 0.012%, and −0.023 units for milk yield, fat yield, protein yield, fat component, protein component, and SCS, respectively. These estimates were largely in agreement with previous studies; however, the magnitudes of the estimates were much smaller in this study. Impacts on economic indices for net merit, cheese merit, and fluid merit were modest. Because of the strong antagonism between fat and protein yield and how those traits influence economic indices, selection for DGAT1 genotypes will likely not find widespread application in the U.S. |
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Palavras-Chave: |
Substitution effect. |
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Thesaurus Nal: |
dairy cattle; milk production; quantitative trait loci. |
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Categoria do assunto: |
G Melhoramento Genético |
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Marc: |
LEADER 01943naa a2200241 a 4500
001 1881591
005 2022-08-10
008 2010 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1080/10495390903504625$2DOI
100 1 $aSILVA, M. V. G. B.
245 $aCharacterization of DGAT1 Allelic effects in a sample of north american holstein cattle.$h[electronic resource]
260 $c2010
520 $aA putative causative mutation underlying a QTL was identified as a lysine to alanine non-conservative substitution at amino acid 232 of the gene encoding the acylCoA:diacylglycerol acyltransferase (DGAT1) protein. Our goal was to characterize the allelic substitution effects of this DGAT1 mutation in a large sample of Holstein bulls from North America. Statistically significant effects were identified for all of the milk production traits and somatic cell scores. Estimated average effects of substituting the lysine allele for the alanine variant on Holstein bull daughter yield deviations were −81 kg, 3.7 kg, −1.1 kg, 0.063%, 0.012%, and −0.023 units for milk yield, fat yield, protein yield, fat component, protein component, and SCS, respectively. These estimates were largely in agreement with previous studies; however, the magnitudes of the estimates were much smaller in this study. Impacts on economic indices for net merit, cheese merit, and fluid merit were modest. Because of the strong antagonism between fat and protein yield and how those traits influence economic indices, selection for DGAT1 genotypes will likely not find widespread application in the U.S.
650 $adairy cattle
650 $amilk production
650 $aquantitative trait loci
653 $aSubstitution effect
700 1 $aSONSTEGARD, T. S.
700 1 $aTHALLMAN, R. M.
700 1 $aCONNOR, E. E.
700 1 $aSCHNABEL, R. D.
700 1 $aTASSELL, C. P. V.
773 $tAnimal Biotechnology$gv. 21, p. 88-99, 2010.
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Embrapa Gado de Leite (CNPGL) |
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Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
11/12/2018 |
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Data da última atualização: |
08/07/2019 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
SAMUEL-ROSA, A.; DALMOLIN, R. S. D.; GUBIANI, P. I.; OLIVEIRA, S. R. de M.; TEIXEIRA, W. G.; VIANA, J. H. M.; RIBEIRO, E.; TORNQUIST, C. G.; ANJOS, L. H. C. dos; SOUZA, J. J. E. L. de; OTTONI, M. V.; MEDEIROS, P. S. C. de; GRIS, D. J.; ROSIN, N. A.; BUENO, J. M. M.; SANTOS, H. G. dos; WEBER, E. J.; FLORES, C. A.; COSTA, E. M.; OLIVEIRA, R. P. de; FILIPPINI ALBA, J. M.; PEDROSO NETO, J. C.; PEDRON, F. de A.; CAVIGLIONE, J. H.; VALLADARES, G. S.; MIRANDA, C. S. S.; DEMATTÊ, J. A. M.; MARQUES JÚNIOR, J.; SIQUEIRA, D. S.; AQUINO, R. E. de; SILVERO, N. E. Q.; GENÚ, A. M.; BROETTO, T.; CANCIAN, L. C.; MIGUEL, P.; ZALAMENA, J.; DOTTO, A. C.; ALMEIDA, J. A. de; REICHERT.; CURCIO, G. R.; COLLIER, L. S.; CARVALHO JUNIOR, W. de; FONTANA, A.; OLIVEIRA, A. P. de; VOGELMANN, E. S.; MALLMANN, F. J. K.; VASQUES, G. de M.; LEPSCH, I. F.; FINK, J. R.; KER, J. C.; SILVA, L. S. da; FREITAS, P. L. de; BIELUCZYK, B.; TIECHER, T. |
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Afiliação: |
ALESSANDRO SAMUEL-ROSA, UFSM; RICARDO SIMÃO DINIZ DALMOLIN, UFSM; PAULO IVONIR GUBIANI, UFSM; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; WENCESLAU GERALDES TEIXEIRA, CNPS; JOAO HERBERT MOREIRA VIANA, CNPMS; ELOI RIBEIRO, ISRIC World Soil Information; CARLOS GUSTAVO TORNQUIST, UFRGS; LÚCIA HELENA CUNHA DOS ANJOS, UFRRJ; JOSÉ JOÃO LELIS LEAL DE SOUZA, UFRGN; MARTA VASCONCELOS OTTONI, Serviço Geológico do Brasil; PAULA SUÉLEN CORRÊA DE MEDEIROS, IBGE; DIEGO JOSÉ GRIS, UFSM; NÍCOLAS AUGUSTO ROSIN, UFSM; JEAN MICHEL MOURA BUENO, UFSM; HUMBERTO GONCALVES DOS SANTOS, CNPS; ELISEU JOSÉ WEBER, UFRGS; CARLOS ALBERTO FLORES, CPACT; ELIAS MENDES COSTA, UFRRJ; RONALDO PEREIRA DE OLIVEIRA, CNPS; JOSE MARIA FILIPPINI ALBA, CPACT; JOÃO CHRISÓSTOMO PEDROSO NETO, Epamig; FABRÍCIO DE ARAÚJO PEDRON, UFSM; JOÃO HENRIQUE CAVIGLIONE, Iapar; GUSTAVO SOUZA VALLADARES, UFPI; CARMEM SUEZE SILVA MIRANDA, Univasf; JOSÉ ALEXANDRE MELO DEMATTÊ, USP; JOSÉ MARQUES JÚNIOR, Unesp; DIEGO SILVA SIQUEIRA, Unesp; RENATO ELEOTERIO DE AQUINO, Unesp; NELIDA ELIZABET QUIÑONEZ SILVERO, Unesp; ALINE MARQUES GENÚ, UNICENTRO; TIAGO BROETTO, Catena Planejamento Territorial; LUCIANO CAMPOS CANCIAN, UFSM; PABLO MIGUEL, UFPel; JOVANI ZALAMENA, UFSC; ANDRÉ CARNIELETTO DOTTO, USP; JAIME ANTONIO DE ALMEIDA, Udesc; JOSÉ MIGUEL REICHERT, UFSM; GUSTAVO RIBAS CURCIO, CNPF; LEONARDO SANTOS COLLIER, UFG; WALDIR DE CARVALHO JUNIOR, CNPS; ADEMIR FONTANA, CNPS; ALINE PACOBAHYBA DE OLIVEIRA, CNPS; EDUARDO SALDANHA VOGELMANN, FURG; FÁBIO JOEL KOCHEM MALLMANN, Universidade Regional Integrada do Alto Uruguai e das Missões; GUSTAVO DE MATTOS VASQUES, CNPS; IGO FERNANDO LEPSCH, USP; JESSÉ RODRIGO FINK, IFPR; JOÃO CARLOS KER, UFV; LEANDRO SOUZA DA SILVA, UFSM; PEDRO LUIZ DE FREITAS, CNPS; WANDERLEI BIELUCZYK, USP; TALES TIECHER, UFRGS. |
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Título: |
Bringing together Brazilian soil scientists to share soil data. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
In: WORLD CONGRESS OF SOIL SCIENCE, 21., 2018, Rio de Janeiro. Soil science: beyond food and fuel: proceedings... Viçosa, MG: SBCS, 2018. v. 1, p. 63-64. WCSS 2018. |
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Idioma: |
Inglês |
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Conteúdo: |
In the Amazon region, types of soil known as Archaeological Black Lands (ABL) present anthropic horizon A and are associated with prolonged human occupation by indigenous societies from the pre-Columbian period, where chemical and physical attributes have better quality than other types of soil in the Amazon, setting a large organic carbon reservoir. However, the conversion of these natural ecosystems into cultivated environments make emerge changes in soil carbon dynamics, often leading to a decline in soil organic carbon content. Therefore, our aim was to use data mining techniques to generate predictive models for the effect of soil use on carbon stock in natural and transformed areas of Archaeological Black Lands. We carried out our experiment in Manicoré and Apuí, Amazonas State, Brazil. After field data collection and laboratory analysis, we obtained a set of data consisting of 21 attributes, 20 predictive attributes consisting of 13 soil physical attributes, 6 soil chemical attributes, 1 soil use related attribute, and 1 response variable, referring to soil carbon stock (SCS), which is the classification target. Due to the large number of attributes, we performed a selection procedure to eliminate attributes of low correlation to the response variable. For data classification, we used the binary induction technique of the decision tree through software Weka 3.8. The results obtained showed that for the depth of 0.00-0.05 and 0.05-0.10 m, the best selected subset was determined using the Wrapper method for attribute selection. In the depth of 0.00-0.05 m, we generated a model of 79% accuracy containing only six rules, including, as the most important classification attribute was soil use. For the depth of 0.05-0.10 m, we generated an eight-rule decision tree of 74% accuracy including sand as the most important attribute. In this context, we highlight the Wrapper method efficiency to select subsets of predictive attributes, capable to generate more understandable decision trees, using a smaller number of attributes in the classification process, making it faster and with a lower computational cost. In addition, data mining techniques were efficient at providing predictive models capable to assist the decision-making process on possible management practices with the potential to conserve or increase soil carbon stock in archeological black lands. MenosIn the Amazon region, types of soil known as Archaeological Black Lands (ABL) present anthropic horizon A and are associated with prolonged human occupation by indigenous societies from the pre-Columbian period, where chemical and physical attributes have better quality than other types of soil in the Amazon, setting a large organic carbon reservoir. However, the conversion of these natural ecosystems into cultivated environments make emerge changes in soil carbon dynamics, often leading to a decline in soil organic carbon content. Therefore, our aim was to use data mining techniques to generate predictive models for the effect of soil use on carbon stock in natural and transformed areas of Archaeological Black Lands. We carried out our experiment in Manicoré and Apuí, Amazonas State, Brazil. After field data collection and laboratory analysis, we obtained a set of data consisting of 21 attributes, 20 predictive attributes consisting of 13 soil physical attributes, 6 soil chemical attributes, 1 soil use related attribute, and 1 response variable, referring to soil carbon stock (SCS), which is the classification target. Due to the large number of attributes, we performed a selection procedure to eliminate attributes of low correlation to the response variable. For data classification, we used the binary induction technique of the decision tree through software Weka 3.8. The results obtained showed that for the depth of 0.00-0.05 and 0.05-0.10 m, the best selected subset was d... Mostrar Tudo |
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Palavras-Chave: |
Anthropic soils; Árvore de decisão; Data mining techniques; Decision tree; Estoque de carbono; Mineração de dados; Soil management system. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 04807nam a2200829 a 4500
001 2101195
005 2019-07-08
008 2018 bl uuuu u01u1 u #d
100 1 $aSAMUEL-ROSA, A.
245 $aBringing together Brazilian soil scientists to share soil data.$h[electronic resource]
260 $aIn: WORLD CONGRESS OF SOIL SCIENCE, 21., 2018, Rio de Janeiro. Soil science: beyond food and fuel: proceedings... Viçosa, MG: SBCS, 2018. v. 1, p. 63-64. WCSS 2018.$c2018
520 $aIn the Amazon region, types of soil known as Archaeological Black Lands (ABL) present anthropic horizon A and are associated with prolonged human occupation by indigenous societies from the pre-Columbian period, where chemical and physical attributes have better quality than other types of soil in the Amazon, setting a large organic carbon reservoir. However, the conversion of these natural ecosystems into cultivated environments make emerge changes in soil carbon dynamics, often leading to a decline in soil organic carbon content. Therefore, our aim was to use data mining techniques to generate predictive models for the effect of soil use on carbon stock in natural and transformed areas of Archaeological Black Lands. We carried out our experiment in Manicoré and Apuí, Amazonas State, Brazil. After field data collection and laboratory analysis, we obtained a set of data consisting of 21 attributes, 20 predictive attributes consisting of 13 soil physical attributes, 6 soil chemical attributes, 1 soil use related attribute, and 1 response variable, referring to soil carbon stock (SCS), which is the classification target. Due to the large number of attributes, we performed a selection procedure to eliminate attributes of low correlation to the response variable. For data classification, we used the binary induction technique of the decision tree through software Weka 3.8. The results obtained showed that for the depth of 0.00-0.05 and 0.05-0.10 m, the best selected subset was determined using the Wrapper method for attribute selection. In the depth of 0.00-0.05 m, we generated a model of 79% accuracy containing only six rules, including, as the most important classification attribute was soil use. For the depth of 0.05-0.10 m, we generated an eight-rule decision tree of 74% accuracy including sand as the most important attribute. In this context, we highlight the Wrapper method efficiency to select subsets of predictive attributes, capable to generate more understandable decision trees, using a smaller number of attributes in the classification process, making it faster and with a lower computational cost. In addition, data mining techniques were efficient at providing predictive models capable to assist the decision-making process on possible management practices with the potential to conserve or increase soil carbon stock in archeological black lands.
653 $aAnthropic soils
653 $aÁrvore de decisão
653 $aData mining techniques
653 $aDecision tree
653 $aEstoque de carbono
653 $aMineração de dados
653 $aSoil management system
700 1 $aDALMOLIN, R. S. D.
700 1 $aGUBIANI, P. I.
700 1 $aOLIVEIRA, S. R. de M.
700 1 $aTEIXEIRA, W. G.
700 1 $aVIANA, J. H. M.
700 1 $aRIBEIRO, E.
700 1 $aTORNQUIST, C. G.
700 1 $aANJOS, L. H. C. dos
700 1 $aSOUZA, J. J. E. L. de
700 1 $aOTTONI, M. V.
700 1 $aMEDEIROS, P. S. C. de
700 1 $aGRIS, D. J.
700 1 $aROSIN, N. A.
700 1 $aBUENO, J. M. M.
700 1 $aSANTOS, H. G. dos
700 1 $aWEBER, E. J.
700 1 $aFLORES, C. A.
700 1 $aCOSTA, E. M.
700 1 $aOLIVEIRA, R. P. de
700 1 $aFILIPPINI ALBA, J. M.
700 1 $aPEDROSO NETO, J. C.
700 1 $aPEDRON, F. de A.
700 1 $aCAVIGLIONE, J. H.
700 1 $aVALLADARES, G. S.
700 1 $aMIRANDA, C. S. S.
700 1 $aDEMATTÊ, J. A. M.
700 1 $aMARQUES JÚNIOR, J.
700 1 $aSIQUEIRA, D. S.
700 1 $aAQUINO, R. E. de
700 1 $aSILVERO, N. E. Q.
700 1 $aGENÚ, A. M.
700 1 $aBROETTO, T.
700 1 $aCANCIAN, L. C.
700 1 $aMIGUEL, P.
700 1 $aZALAMENA, J.
700 1 $aDOTTO, A. C.
700 1 $aALMEIDA, J. A. de
700 1 $aREICHERT.
700 1 $aCURCIO, G. R.
700 1 $aCOLLIER, L. S.
700 1 $aCARVALHO JUNIOR, W. de
700 1 $aFONTANA, A.
700 1 $aOLIVEIRA, A. P. de
700 1 $aVOGELMANN, E. S.
700 1 $aMALLMANN, F. J. K.
700 1 $aVASQUES, G. de M.
700 1 $aLEPSCH, I. F.
700 1 $aFINK, J. R.
700 1 $aKER, J. C.
700 1 $aSILVA, L. S. da
700 1 $aFREITAS, P. L. de
700 1 $aBIELUCZYK, B.
700 1 $aTIECHER, T.
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