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ARTICLE |
1 Department of Genetics, University Campus of Rabanales, University of Córdoba. Carretera Madrid - Córdoba Km. 396-a. C.P. 14071. Córdoba, Spain
2 Institute National de la Recherche Agronomique (INRA), Unité de Recherches Zootechniques, Guadeloupe, French West Indies
3 Department of Agroforest Sciences, E.U.I.T.A., University of Seville, Seville, Spain
4 Department of Animal Production, University Campus of Rabanales, University of Córdoba, Córdoba, Spain
* To whom correspondence should be addressed. E-mail: ge1moala{at}uco.es.
| Abstract |
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A total of 88,727 individual live weight records of Spanish Merino lambs, obtained from 30,214 animals between 2 and 92 days of age, were analyzed using a random regression model (RRM). These animals were progeny of 546 rams and 15,586 ewes raised in 30 flocks, between 1992 and 2002, with a total of 45,941 animals in the pedigree. The contemporary groups (CG are animals of the same flock, year, and season; CG with 452 levels), the lambing number (11 levels), the combination sex of lambs with type of litter (4 levels) and a fixed regression coefficient of age on live weight were included as fixed effects. A total of 7 different RRM were compared and the best fit was obtained for a model of order 3 for the direct and maternal genetic effects and for the individual permanent environmental effect. For the maternal permanent environmental effect the best model had an order 2. The residual variance was assumed to be heterogeneous with ten age classes; the covariance between both genetic effects was included. According to the results of the selected RRM, the heritability for both genetic effects (h2a and h2m) increased with age, with estimates of 0.123 to 0.186 for h2a and of 0.059 to 0.108 for h2m. The correlations between direct and genetic maternal effects were -0.619 to -0.387 during the first 45 days of age decreasing as age increased, until reaching values from -0.366 to -0.275 between 45 to 75 days of age. Important changes in ranking the animals were found based on the breeding value estimation by the current method and by the random regression procedure. The use of RRM to analyze the genetic trajectory of growth in this population of Merino sheep is highly recommended.
Key Words: genetic parameters, growth, Merino sheep, random regression models
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