Estimation of variance components of threshold characters by marginal posterior modes and means via Gibbs sampling

Records of Large White breed animals were used to estimate variance components, genetic parameters and trends for the character total number of born piglets (TNBP) as measure of litter size. For obtaining variance components and genetic parameters, it was used the Restricted Maximum Likelihood Method using MTDFREML software. Two mixed models (additive and repeatability) were evaluated. The additive model contained fixed effect of the contemporary group and the following random effects: direct additive genetic and residual effect for the first parturition. Repeatability model had the same effects of the additive model plus parturition order fixed effect and non-correlated animal permanent environment random effect for the second, third and forth parturition. Direct additive heritability estimates for TNBP were 0.15 and 0.20 for the additive and repeatability models, respectively. The estimate of the ration among variance of the non-correlated effect of animal permanent environment effect and the phenotypic variance, expressed as total variance proportion (c2) was 0.09. The estimates of yearly genetic trends obtained in the additive and repeatability models have similar behaviors (0.02 piglets/sow/year).

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Estimation of variance components of milk, fat, and protein yields of Tunisian Holstein dairy cattle using Bayesian and REML methods

Archives Animal Breeding ◽

10.5194/aab-59-243-2016 ◽

2016 ◽

Vol 59 (2) ◽

pp. 243-248 ◽

Cited By ~ 3

Author(s):

Hafedh Ben Zaabza ◽

Abderrahmen Ben Gara ◽

Hedi Hammami ◽

Mohamed Amine Ferchichi ◽

Boulbaba Rekik

Keyword(s):

Dairy Cattle ◽

Bayesian Methods ◽

Milk Fat ◽

Variance Components ◽

Genetic Parameters ◽

Genetic Correlations ◽

Bayesian Procedure ◽

Milk Traits ◽

Residual Variances ◽

Estimation Of Variance

Abstract. A multi-trait repeatability animal model under restricted maximum likelihood (REML) and Bayesian methods was used to estimate genetic parameters of milk, fat, and protein yields in Tunisian Holstein cows. The estimates of heritability for milk, fat, and protein yields from the REML procedure were 0.21 ± 0.05, 0.159 ± 0.04, and 0.158 ± 0.04, respectively. The corresponding results from the Bayesian procedure were 0.273 ± 0.02, 0.198 ± 0.01, and 0.187 ± 0.01. Heritability estimates tended to be larger via the Bayesian than those obtained by the REML method. Genetic and permanent environmental variances estimated by REML were smaller than those obtained by the Bayesian analysis. Inversely, REML estimates of the residual variances were larger than Bayesian estimates. Genetic and permanent correlation estimates were on the other hand comparable by both REML and Bayesian methods with permanent environmental being larger than genetic correlations. Results from this study confirm previous reports on genetic parameters for milk traits in Tunisian Holsteins and suggest that a multi-trait approach can be an alternative for implementing a routine genetic evaluation of the Tunisian dairy cattle population.

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ESTIMATION OF VARIANCE COMPONENTS RELATED TO MILK YIELD OF JERSEY CATTLE BY DIFFERENT METHODS

ANADOLU JOURNAL OF AGRICULTURAL SCIENCES ◽

10.7161/anajas.2012.v27n1.4147 ◽

2012 ◽

Vol 27 (1) ◽

pp. 41-47

Author(s):

Adnan ÜNALAN

Keyword(s):

Milk Yield ◽

Variance Components ◽

Jersey Cattle ◽

Estimation Of Variance

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Selection on lean growth in a nucleus of Landrace pigs: an analysis using Gibbs sampling

Animal Science ◽

10.1017/s1357729800014806 ◽

1996 ◽

Vol 63 (2) ◽

pp. 243-253 ◽

Cited By ~ 8

Author(s):

M. C. Rodriguez ◽

M. Toro ◽

L. Silió

Keyword(s):

Gibbs Sampling ◽

Variance Components ◽

Fixed Effects ◽

Prediction Method ◽

Environmental Parameters ◽

Linear Unbiased Prediction ◽

Normal Distributions ◽

Lean Growth ◽

Best Linear Unbiased ◽

Selection For

AbstractData from 4150 Landrace pigs tested during the period 1989-94 for backfat thickness and age at 100 kg in an open selection nucleus were analysed with the standard restricted maximum likelihood/best linear unbiased prediction method and with a Bayesian approach based on the marginal posterior distributions of parameters of interest achieved via Gibbs sampling. Breeding values and fixed effects were sampled from normal distributions and (co)variance components from inverted Wishart distributions. The Bayesian analysis indicated that the selection was effective for both traits. Assuming flat priors for the (co)variance components, the posterior means of the annual rates of response to selection for both traits were −0·473 days and −0·212 mm. The influence of informative priors constructed from (co)variances estimated in the French Landrace breed on inferences about genetic and common environmental parameters, genetic group effects and total and annual responses was also examined.

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