Genetic Evaluation Using Random Regression Models For Longitudinal Measurements Of Body Weight In Animals
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Genetic evaluation using random regression models for longitudinal measurements of body weight in animals
Longitudinal measurements of body weight in 3,918 boars and 1,532 bulls from test station were analysed by random-regression models. Both species were housed in groups. Boars had 6 measurements during test, and bulls approximately 9. Covariance components for random-regression coefficients wereestimated by the REML method and the VCE5 software package. Orthogonal Legendre polynomials (LG) of different order were fit to random effects. Modelfor bulls included direct additive genetic and animal permanent environmental effects, while in boars common litter environment, common pen environment, and maternal genetic effect were fitted additionally. LG with four coefficients were found sufficient in both species. Animal permanent environment accounted for 35 to 40 % of phenotypic variabilitry in boars, and between 30 and 55 % in bulls. Estimates of direct heritability in bulls were in the range 0.22 to 0.45, inm boars were around 0.40. Maternal heritability in boars decreased from 0.03 to 0.01. The proportion of common litter effect decreased over time (0.24 to 0.15), too. The eigenfunctions and corresponding eigenvalues in both species showed that around 85 to 90 % of the total geneticvariability was explained by the constant term in regression, while 10 to 15 % was genetic variability in the shape of growth curve. In bulls, a combined random regression and conventional multi-trait model for body weight (BW) and five single measured carcass traits was studied. Estimated genetic correlation over time between BW and warm carcass weight, conformation index, and ratio muscle:bone increased with time from +0.02 to +0.80 (+0.60), between BW and ratio of valuable cuts was close to zero the entire time. Changing the shape of growth curve by selection is possible, but not easy. Using the results of the combined random-regression and multiple-trait analysis in selection could be an advantage for carcass traits.
Linear Models for the Prediction of the Genetic Merit of Animals, 4th Edition
Fundamental to any livestock improvement programme by animal scientists, is the prediction of genetic merit in the offspring generation for desirable production traits such as increased growth rate, or superior meat, milk and wool production. Covering the foundational principles on the application of linear models for the prediction of genetic merit in livestock, this new edition is fully updated to incorporate recent advances in genomic prediction approaches, genomic models for multi-breed and crossbred performance, dominance and epistasis. It provides models for the analysis of main production traits as well as functional traits and includes numerous worked examples. For the first time, R codes for key examples in the textbook are provided online. Suitable for graduate and postgraduate students, researchers and lecturers of animal breeding, genetics and genomics, this established textbook provides a thorough grounding in both the basics and in new developments of linear models and animal genetics.
Book of Abstracts of the 65th Annual Meeting of the European Association for Animal Production
This Book of Abstracts is the main publication of the 65th Annual Meeting of the European Federation for Animal Science 2014 in Copenhagen, Denmark. It contains abstracts of the invited papers and contributed presentations. The meeting addressed subjects relating to science and innovation. Important problems were also discussed during the sessions of EAAP's nine Commissions: Animal Genetics, Animal Nutrition, Animal Management and Health, Animal Physiology, Cattle Production, Sheep and Goat Production, Pig Production, Horse Production and Livestock Farming Systems.