Heritability of quantitative traits in segregating common bean families using a Bayesian approach

Genetic parameters for six quantitative traits in the early generation of segregating populations of common beans (Phaseolus vulgaris L.) were evaluated. A Bayesian approach was used for estimating the variance components, breeding values and broad sense heritability of the quantitative traits under analysis. The Markov Chain Monte Carlo method was utilized to analyze the contribution of genes affecting complex traits. Twenty-four F₃ families were evaluated in the field during 2005 in Santa Catarina, southern Brazil. With regard to the grain yield and yield components, the additive variances were relatively similar to the dominance variances. This result is confirmed by the 95% credible set from the posterior distribution. The mean estimates of broad-sense heritability (H²) varied from 11.5% to 64.2%. The heritability estimates of yield and yield components were higher than the estimates for the number of days until flowering and reproductive period. However, for grain yield, the 95% heritability credible set included the heritability estimates from point of crop duration. The predicted genetic gain reached the highest value for the number of pods per plant (10.95%). Days to flowering and reproductive period had the lowest values of genetic advance. One hundred seed-weight, grain yield and seeds per pod exhibited a similar predictable level of genetic gain: GA = 5.73%, 5.81% and 4.77%, respectively. The Bayesian framework provided information that is useful for a breeding program, since it contributes to the understanding of how quantitative traits are genetically controlled.