02085naa a2200265 a 450000100080000000500110000800800410001902400350006010000190009524501040011426000090021852013100022765000260153765300230156365300090158665300270159565300260162265300170164865300170166565300090168270000200169170000170171170000250172877300660175319693042013-10-24       2013    bl uuuu     u00u1 u    #d7 a10.1007/s00122-013-2089-62DOI1 aSILVA, F. F. e  aBayesian inference of mixed models in quantitative genetics of crop species.h[electronic resource]  c2013  aThe objectives of this study were to implement a Bayesian framework for mixed models analysis in crop species breeding and to exploit alternatives for informative prior elicitation. Bayesian inference for genetic evaluation in annual crop breeding was illustrated with the first two half-sib selection cycles in a popcorn population. The Bayesian framework was based on the Just Another Gibbs Sampler software and the R2jags package. For the first cycle, a non-informative prior for the inverse of the variance components and an informative prior based on meta-analysis were used. For the second cycle, a noninformative prior and an informative prior defined as the posterior from the non-informative and informative analyses of the first cycle were used. Regarding the first cycle, the use of an informative prior from the meta-analysis provided clearly distinct results relative to the analysis with a non-informative prior only for the grain yield. Regarding the second cycle, the results for the expansion volume and grain yield showed differences among the three analyses. The differences between the non-informative and informative prior analyses were restricted to variance components and heritability. The correlations between the predicted breeding values from these analyses were almost perfect.  aquantitative genetics  aBayesian inference  aBLUP  aGenética quantitativa  aInferência Bayesiana  aMixed models  aModelo mixto  aREML1 aVIANA, J. M. S.1 aFARIA, V. R.1 aRESENDE, M. D. V. de  tTheoretical and Applied Geneticsgv. 126, p. 1749-1761, 2013.