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Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học thế giới đề tài: A Bayesian analysis of the effect of selection for growth rate on growth curves in rabbits | 21 Genet Sei. Evol. 35 2003 21-41 INRA EDP Sciences 2003 DOI 10.1051 gse 2002034 Original article a BaYesian analysis of the effect of selection for growth rate on growth curves in rabbits Agustin Blascoa Miriam Pilesa Luis Varonab a Departamento de Ciencia Animal Universidad Politécnica de Valencia PG Box 22012 Valencia 46071 Spain b UdL-IRTA. Rovira Roure 177 Lleida Spain Received 15 November 2001 accepted 24 September 2002 Abstract - Gompertz growth curves were fitted to the data of 137 rabbits from control C and selected S lines. The animals came from a synthetic rabbit line selected for an increased growth rate. The embryos from generations 3 and 4 were frozen and thawed to be contemporary of rabbits born in generation 10. Group c was the offspring of generations 3 and 4 and group s was the contemporary offspring of generation 10. The animals were weighed individually twice a week during the first four weeks of life and once a week thereafter until 20 weeks of age. Subsequently the males were weighed weekly until 40 weeks of age. The random samples of the posterior distributions of the growth curve parameters were drawn by using Markov Chain Monte Carlo MCMC methods. As a consequence of selection the selected animals were heavier than the c animals throughout the entire growth curve. Adult body weight estimated as a parameter of the Gompertz curve was 7 higher in the selected line. The other parameters of the Gompertz curve were scarcely affected by selection. When selected and control growth curves are represented in a metabolic scale all differences disappear. growth curves selection rabbits Bayesian analysis 1. introduction Growth curves can describe the entire growth process in terms of a few parameters having a biological interpretation. Selection for growth rate can modify these parameters but there are some technical difficulties for comparing curves before and after selection. Typically growth curves are htted by nonlinear regression or by linear .
