| |
|
|
|
Registro Completo |
|
Biblioteca(s): |
Embrapa Soja. |
|
Data corrente: |
30/03/2007 |
|
Data da última atualização: |
30/03/2007 |
|
Autoria: |
CATTELAN, A. J.; CASTRO, C. de; MORAES, J. Z.; SIBALDELLI, R. N. R.; SOUZA, M. P. de; BETTI, A. F.; LOLATA, G. B.; CARMO, K. B. do. |
|
Título: |
Ensaio de rede nacional para teste de bactérias promotoras de crescimento de plantas de soja. |
|
Ano de publicação: |
2006 |
|
Fonte/Imprenta: |
In: CENTRO TECNOLÓGICO COMIGO. Resultados do CTC 2006. Rio Verde, 2006. |
|
Páginas: |
p. 45-46. |
|
Idioma: |
Português |
|
Categoria do assunto: |
-- |
|
Marc: |
LEADER 00621naa a2200205 a 4500
001 1469931
005 2007-03-30
008 2006 bl uuuu u00u1 u #d
100 1 $aCATTELAN, A. J.
245 $aEnsaio de rede nacional para teste de bactérias promotoras de crescimento de plantas de soja.
260 $c2006
300 $ap. 45-46.
700 1 $aCASTRO, C. de
700 1 $aMORAES, J. Z.
700 1 $aSIBALDELLI, R. N. R.
700 1 $aSOUZA, M. P. de
700 1 $aBETTI, A. F.
700 1 $aLOLATA, G. B.
700 1 $aCARMO, K. B. do
773 $tIn: CENTRO TECNOLÓGICO COMIGO. Resultados do CTC 2006. Rio Verde, 2006.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Soja (CNPSO) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
|
|
|
 | 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
|
Biblioteca(s): |
Embrapa Gado de Leite. |
|
Data corrente: |
21/11/2014 |
|
Data da última atualização: |
05/02/2024 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Circulação/Nível: |
A - 2 |
|
Autoria: |
SANTOS, D. J. A.; PEIXOTO, M. G. C. D.; BORQUIS, R. R. A.; PANETTO, J. C. do C.; EL FARO, L.; TONHATI, H. |
|
Afiliação: |
D. J. A. SANTOS, UNESP; MARIA GABRIELA CAMPOLINA D PEIXOTO, CNPGL; R. R. ASPILCUETA BORQUIS, UNESP; JOAO CLAUDIO DO CARMO PANETTO, CNPGL; L. EL FARO, IZ - SP; H. TONHATI, UNESP. |
|
Título: |
Predicting breeding values for milk yield of Guzerá (Bos indicus) cows using random regression models. |
|
Ano de publicação: |
2014 |
|
Fonte/Imprenta: |
Livestock Science, v. 167, p. 41-50, 2014. |
|
DOI: |
https://doi.org/10.1016/j.livsci.2014.05.023 |
|
Idioma: |
Inglês |
|
Conteúdo: |
Given the importance of Guzerá breeding programs for milk production in the tropics, the objective of this study was to compare alternative random regression models for estimation of genetic parameters and prediction of breeding values. Test-day milk yields records (TDR) were collected monthly, in a maximum of 10 measurements. The database included 20,524 records of first lactation from 2816 Guzerá cows. TDR data were analyzed by random regression models (RRM) considering additive genetic, permanent environmental and residual effects as random and the effects of contemporary group (CG), calving age as a covariate (linear and quadratic effects) and mean lactation curve as fixed. The genetic additive and permanent environmental effects were modeled by RRM using Wilmink, Ali and Schaeffer and cubic B-spline functions as well as Legendre polynomials. Residual variances were considered as heterogeneous classes, grouped differently according to the model used. Multi-trait analysis using finite-dimensional models (FDM) for test-day milk records (TDR) and a single-trait model for 305-days milk yields (default) using the restricted maximum likelihood method were also carried out as further comparisons. Through the statistical criteria adopted, the best RRM was the one that used the cubic B-spline function with five random regression coefficients for the genetic additive and permanent environmental effects. However, the models using the Ali and Schaeffer function or Legendre polynomials with second and fifth order for, respectively, the additive genetic and permanent environmental effects can be adopted, as little variation was observed in the genetic parameter estimates compared to those estimated by models using the B-spline function. Therefore, due to the lower complexity in the (co)variance estimations, the model using Legendre polynomials represented the best option for the genetic evaluation of the Guzerá lactation records. An increase of 3.6% in the accuracy of the estimated breeding values was verified when using RRM. The ranks of animals were very close whatever the RRM for the data set used to predict breeding values. Considering P305, results indicated only small to medium difference in the animals׳ ranking based on breeding values predicted by the conventional model or by RRM. Therefore, the sum of all the RRM-predicted breeding values along the lactation period (RRM305) can be used as a selection criterion for 305-day milk production. MenosGiven the importance of Guzerá breeding programs for milk production in the tropics, the objective of this study was to compare alternative random regression models for estimation of genetic parameters and prediction of breeding values. Test-day milk yields records (TDR) were collected monthly, in a maximum of 10 measurements. The database included 20,524 records of first lactation from 2816 Guzerá cows. TDR data were analyzed by random regression models (RRM) considering additive genetic, permanent environmental and residual effects as random and the effects of contemporary group (CG), calving age as a covariate (linear and quadratic effects) and mean lactation curve as fixed. The genetic additive and permanent environmental effects were modeled by RRM using Wilmink, Ali and Schaeffer and cubic B-spline functions as well as Legendre polynomials. Residual variances were considered as heterogeneous classes, grouped differently according to the model used. Multi-trait analysis using finite-dimensional models (FDM) for test-day milk records (TDR) and a single-trait model for 305-days milk yields (default) using the restricted maximum likelihood method were also carried out as further comparisons. Through the statistical criteria adopted, the best RRM was the one that used the cubic B-spline function with five random regression coefficients for the genetic additive and permanent environmental effects. However, the models using the Ali and Schaeffer function or Legendre polynomia... Mostrar Tudo |
|
Palavras-Chave: |
B-spline function; Covariance function; Legendre polynomials; Parametric function. |
|
Thesaurus NAL: |
lactation curve. |
|
Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
|
Marc: |
LEADER 03285naa a2200253 a 4500
001 2000770
005 2024-02-05
008 2014 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.livsci.2014.05.023$2DOI
100 1 $aSANTOS, D. J. A.
245 $aPredicting breeding values for milk yield of Guzerá (Bos indicus) cows using random regression models.$h[electronic resource]
260 $c2014
520 $aGiven the importance of Guzerá breeding programs for milk production in the tropics, the objective of this study was to compare alternative random regression models for estimation of genetic parameters and prediction of breeding values. Test-day milk yields records (TDR) were collected monthly, in a maximum of 10 measurements. The database included 20,524 records of first lactation from 2816 Guzerá cows. TDR data were analyzed by random regression models (RRM) considering additive genetic, permanent environmental and residual effects as random and the effects of contemporary group (CG), calving age as a covariate (linear and quadratic effects) and mean lactation curve as fixed. The genetic additive and permanent environmental effects were modeled by RRM using Wilmink, Ali and Schaeffer and cubic B-spline functions as well as Legendre polynomials. Residual variances were considered as heterogeneous classes, grouped differently according to the model used. Multi-trait analysis using finite-dimensional models (FDM) for test-day milk records (TDR) and a single-trait model for 305-days milk yields (default) using the restricted maximum likelihood method were also carried out as further comparisons. Through the statistical criteria adopted, the best RRM was the one that used the cubic B-spline function with five random regression coefficients for the genetic additive and permanent environmental effects. However, the models using the Ali and Schaeffer function or Legendre polynomials with second and fifth order for, respectively, the additive genetic and permanent environmental effects can be adopted, as little variation was observed in the genetic parameter estimates compared to those estimated by models using the B-spline function. Therefore, due to the lower complexity in the (co)variance estimations, the model using Legendre polynomials represented the best option for the genetic evaluation of the Guzerá lactation records. An increase of 3.6% in the accuracy of the estimated breeding values was verified when using RRM. The ranks of animals were very close whatever the RRM for the data set used to predict breeding values. Considering P305, results indicated only small to medium difference in the animals׳ ranking based on breeding values predicted by the conventional model or by RRM. Therefore, the sum of all the RRM-predicted breeding values along the lactation period (RRM305) can be used as a selection criterion for 305-day milk production.
650 $alactation curve
653 $aB-spline function
653 $aCovariance function
653 $aLegendre polynomials
653 $aParametric function
700 1 $aPEIXOTO, M. G. C. D.
700 1 $aBORQUIS, R. R. A.
700 1 $aPANETTO, J. C. do C.
700 1 $aEL FARO, L.
700 1 $aTONHATI, H.
773 $tLivestock Science$gv. 167, p. 41-50, 2014.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Gado de Leite (CNPGL) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
| Expressão de busca inválida. Verifique!!! |
|
|
