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United States Department of Agriculture

Agricultural Research Service

Title: Analyses of Cow Weight in Beef Cattle with Random Regression Models

Authors
item Arango, Jesus - UNIV. OF NEBRASKA-LINCOLN
item Cundiff, Larry
item Van Vleck, Lloyd

Submitted to: Journal of Animal Science Supplement
Publication Type: Abstract Only
Publication Acceptance Date: May 30, 2000
Publication Date: N/A

Technical Abstract: Data from the first four cycles of the Germplasm Evaluation Program were used to evaluate weights of Angus, Hereford, and F1 cows produced by crosses of 22 sire and two dam (Angus and Hereford) breeds. Four weights per cow-yr were available from two through eight yr of age (AY) with age coded in months (AM). Weights (n=61798) were analyzed with REML fitting a random regression model (RRM). Models included fixed regression on AM and effects of cow line, AY, season and their interactions, year of birth and status codes. The random part of the models fitted Legendre polynomials of AM for additive (a) and permanent environmental (c) effects. The resulting covariance functions were used to estimate covariances for all ages in the data. Temporary environmental effects were modeled to account for heterogeneity of variance for the AY. Quadratic fixed regression was sufficient to model population trajectory. Different models varied order of ffit of a and c coefficients. The best model included linear and quartic regression coefficients for a and c respectively. Coefficients for c were highly correlated, so estimation with cubic order did not reduce likelihood significantly. Additive and phenotypic variances increased with cow age. The surface of the plots of permanent environmental and phenotypic covariances was not smooth. Heritabilities for AM were in the range of .38 (36 mo) to .78 (94 mo) with some fluctuation especially for extreme ages. Genetic correlations were high for most age combinations. The smallest (.70) was between extreme ages (19, 103 mo). Permanent environmental correlations were more erratic. Results show that cow weights do not fit a repeatability model with constant variances.

Last Modified: 10/24/2014
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