Genetic parameters and selection gain in tropical wheat populations via Bayesian inference

The development process of a new wheat cultivar requires time between obtaining the base population and selecting the most promising line. Estimating genetic parameters more accurately in early generations with a view to anticipating selection means important advances for wheat breeding programs. Thus, the present study estimated the genetic parameters of F-2 populations of tropical wheat and the genetic gain from selection via the Bayesian approach. To this end, the authors assessed the grain yield per plot of 34 F-2 populations of tropical wheat. The Bayesian approach provided an adequate fit to the model, estimating genetic parameters within the parametric space. Heritability (h(2)) was 0.51. Among those selected, 11 F-2 populations performed better than the control cultivars, with genetic gain of 7.80%. The following populations were the most promising: Tbio Sossego/CD 1303, CD 1303/Tbio Ponteiro, BRS 254/CD 1303, Tbio Duque/Tbio Aton, and Tbio Aton/CD 1303. Bayesian inference can be used to significantly improve tropical wheat breeding programs.