ABSTRACT

The goal of this work was to estimate stability and adaptability parameters using a Bayesian approach to Eberhart and Russel's method and to assess the efficiency of using an a priori distribution. The information from assessing the popping expansion and grain yield of 16 popcorn genotypes was used in randomized block experiments implemented in five environments in the North and Northeast regions of the State of Rio de Janeiro, Brazil. The Bayesian methodology was implemented using the free software package R with the MCMCregress function of the MCMCpack package. Eberhart and Russel's method using a Bayesian technique was found to be efficient in recommending cultivars to more or less favorable environments. The incorporation of a priori information provided greater accuracy in estimating the stability and adaptability parameters. In the comparison of a priori distributions, the BayesFactor function indicated the informative a priori as the most effective for obtaining reliable estimates.

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