scholarly journals Variance Component and Breeding Value Estimation for Reproductive Traits in Laying Hens Using a Bayesian Threshold Model

2007 ◽  
Vol 86 (5) ◽  
pp. 823-828 ◽  
Author(s):  
J. Bennewitz ◽  
O. Morgades ◽  
R. Preisinger ◽  
G. Thaller ◽  
E. Kalm
Keyword(s):  
Variance Component ◽  
Laying Hens ◽  
Threshold Model ◽  
Reproductive Traits ◽  
Breeding Value ◽  
Value Estimation

scholarly journals Untersuchungen zur Mortalität von Legehennen gehalten in Einzel- und Gruppenkäfigen

2005 ◽  
Vol 48 (4) ◽  
pp. 404-411
Author(s):  
N. Mielenz ◽  
M. Schmutz ◽  
L. Schüler
Keyword(s):  
Animal Model ◽  
Genetic Parameters ◽  
Laying Hens ◽  
Laying Hen ◽  
Breeding Value ◽  
Breeding Programme ◽  
Threshold Models ◽  
Breeding Values ◽  
Value Estimation ◽  
Commercial Breeding

Abstract. Title of the paper: Mortality of laying hens housed in single and group cages This study provides genetic parameters for mortality of laying hens estimated with linear and threshold models. Records of one line from a commercial breeding programme of White Leghorns from three generations were available. Data included observations of 8636 hens from single and from 6908 hens of group cages. Mortality was defined as death in the first six months of lay with dead=1 and alive=0. The average mortality was 3.3% in single and 6.3% in group cages. The binary traits were analysed separately by linear animal (LAM), by threshold animal (TAM) and by threshold sire models. Further the two mortalities were analysed together by a linear-linear animal (LLAM) and threshold-threshold animal model (TTAM). The LLAM estimates of heritability were 1.5% for single and 3.2% for group cages. The heritability estimates of TTAM ranged from 9.6% to 9.9%. The rank correlations between breeding values of LAM and TAM were for all sires, the 10% best and the 5% best sires in the range 0.96 to 1.00. The analysis of rank correlations of the linear and threshold models showed: The LLAM provides a good (but only suboptimal) alternative for breeding value estimation of mortality in the investigated laying hen population.

scholarly journals Variance component and breeding value estimation for genetic heterogeneity of residual variance in Swedish Holstein dairy cattle

2013 ◽  
Vol 96 (4) ◽  
pp. 2627-2636 ◽  
Author(s):  
L. Rönnegård ◽  
M. Felleki ◽  
W.F. Fikse ◽  
H.A. Mulder ◽  
E. Strandberg
Keyword(s):  
Dairy Cattle ◽  
Genetic Heterogeneity ◽  
Variance Component ◽  
Breeding Value ◽  
Residual Variance ◽  
Value Estimation

scholarly journals Bayesian inference of genetic parameters for reproductive and performance traits in White Leghorn hens

2018 ◽  
Vol 63 (No. 6) ◽  
pp. 230-236 ◽  
Author(s):  
J.O. Rosa ◽  
G.C. Venturini ◽  
T.C.S. Chud ◽  
B.C. Pires ◽  
M.E. Buzanskas ◽  
...  
Keyword(s):  
Bayesian Inference ◽  
Fixed Effects ◽  
Egg Production ◽  
Genetic Parameters ◽  
Laying Hens ◽  
Reproductive Traits ◽  
A Posteriori ◽  
White Leghorn ◽  
Performance Traits ◽  
And Performance

This study estimated the genetic parameters for reproductive and performance traits and determined which ones can be used as selection criteria for egg production in laying hens using the Bayesian inference. The data of 1894 animals from three generations of White Leghorn laying hens were analyzed for fertility (FERT), hatchability (HATC), and birth rate measurements at 60 weeks of age (BIRTH), body weight at 16 and 60 weeks of age (BW16 and BW60), age at sexual maturity (ASM), egg height/width ratio, weight, and density at 28, 36, and 40 weeks of age (RHW28, RHW36, RHW40, WEGG28, WEGG36, WEGG40, DENS28, DENS36, and DENS40, respectively) traits. The genetic parameters were estimated by the Bayesian inference method of multi-trait animal model. The model included the additive and residual genetic random effects and the fixed effects of generation. The a posteriori mean distributions of the heritability estimates for reproductive traits ranged from 0.14 ± 0.003 (HATC) to 0.22 ± 0.005 (FERT) and performance from 0.07 ± 0.001 (RHW28) to 0.42 ± 0.001 (WEGG40). The a posteriori mean distributions of the genetic correlation between reproductive traits ranged from 0.18 ± 0.026 (FERT and HACT) to 0.79 ± 0.007 (FERT and BIRTH) and those related to performance ranged from –0.49 ± 0.001 (WEGG36 and DENS36) to 0.75 ± 0.003 (DENS28 and DENS36). Reproductive and performance traits showed enough additive genetic variability to respond to selection, except for RHW28. This trait alone would have little impact on the genetic gain because environmental factors would have a higher impact compared to those from the additive genetic factors. Based on the results of this study, the selection applied on the BIRTH trait can be indicated to improve FERT and HATC of eggs. Furthermore, the use of the WEGG40 could improve egg quality in this population.

scholarly journals MoBPSweb: A web-based framework to simulate and compare breeding programs

2020 ◽  
Author(s):  
T. Pook ◽  
L. Büttgen ◽  
A. Ganesan ◽  
N.T. Ha ◽  
H. Simianer
Keyword(s):  
Selection Index ◽  
Relevant Information ◽  
Simulation Software ◽  
Breeding Program ◽  
Breeding Value ◽  
Long Term Effects ◽  
General Applicability ◽  
Breeding Programs ◽  
Web Based ◽  
Value Estimation

ABSTRACTSelective breeding is a continued element of both crop and livestock breeding since early prehistory. In this work, we are proposing a new web-based simulation framework (“MoBPSweb”) that is combining a unified language to describe breeding programs with the simulation software MoBPS, standing for ‘Modular Breeding Program Simulator’. Thereby, MoBPSweb is providing a flexible environment to enter, simulate, evaluate and compare breeding programs. Inputs can be provided via modules ranging from a Vis.js-based flash environment for “drawing” the breeding program to a variety of modules to provide phenotype information, economic parameters and other relevant information. Similarly, results of the simulation study can be extracted and compared to other scenarios via output modules (e.g. observed phenotypes, accuracy of breeding value estimation, inbreeding rates). Usability of the framework is showcased along a toy example of a dairy cattle breeding program on farm level, with comparing scenarios differing in implemented breeding value estimation, selection index and selection intensity being considered. Comparisons are made considering both short and long-term effects of the different scenarios in terms of genomic gains, rates of inbreeding and the accuracy of the breeding value estimation. Lastly, general applicability of the MoBPSweb framework and the general potential for simulation studies for genetics and in particular in breeding are discussed.

scholarly journals Analysis of prolificacy in sows of hyperprolific lines of Large White breed

2011 ◽  
Vol 50 (No. 4) ◽  
pp. 155-162
Author(s):  
V. Matoušek ◽  
A. Čermáková ◽  
N. Kernerová ◽  
P. Králová
Keyword(s):  
Candidate Genes ◽  
Reproductive Performance ◽  
Reproductive Traits ◽  
Breeding Value ◽  
Large White ◽  
Large White Breed ◽  
Lifetime Performance ◽  
White Breed ◽  
Positive Effect ◽  
Esr Gene

The objective of the paper was to evaluate the results of reproductive performance of sows in some elite breeding herds of the Large White breed included in experimental herds for the production of hyperprolific lines of dam breeds. The set consisted of 98 sows with the known genotypes of ESR, FSHâ and PRLR genes. The dendrogram shows that on the basis of their genetic outfit the sows can be divided into two clusters. The first cluster can be described as a cluster with marked dominance of HPL sows and the second cluster with marked dominance of the sows of basic herd. The first cluster consisted of individuals in which the preferred genotype AA of PRLR gene was not detected. As for FSHâ gene, the beneficial genotype BB was found out in 74.10% of sows. In ESR gene the beneficial genotype DD was recorded only in 11.10% of individuals. On average for the lifetime performance they delivered by 2.08 piglets more in all born piglets and by 1.96 piglets more in live-born piglets per litter. Differences in the reproductive traits between HPL sows and the sows of basic herd in the first cluster were statistically highly significant. On the contrary, genotype AA of PRLR gene was identified in all sows of the second cluster, 61.36% of animals possessed beneficial genotype BB of FSHâ gene. As for ESR gene, beneficial genotype DD was identified within the whole cluster in 31.82% of sows. In lifetime performance the HPL sows had on average by 1.10 individuals more in all born piglets and by 1.01 more in live-born piglets (statistically significantly higher values). The unambiguous expression of a positive effect of preferred genotypes of selected candidate genes failed to be confirmed by the results of statistical analyses testing the associations of candidate genes for pig reproduction with selected parameters of breeding value and prolificacy of sows.  

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