In the pedigree method of conducting an autogamous population of segregating plants, the genealogy of the progenies is registered. Although labor-intensive, these data are rarely used. One possibility of exploiting this information is to improve selection efficiency using BLUP (Best Linear Unbiased Prediction). In this study BLUP with genealogy inclusion was compared to the mean in the progenies evaluation conducted by the pedigree method. Progenies of crosses of the common bean lines BRS MG Talismã and BRS Valente in F4:6 and F4:7 were used. The 256 F4:6 progenies were sown in February 2005, in southeast of Brazil, in a 16 <FONT FACE=Symbol>´</FONT> 16 simple lattice design. The grain yield data were subjected to BLUP analysis with inclusion of genealogy. Based on this analysis and the mean, the 30 progenies with best and worst performance were selected. These 60 F4:7 progenies were classified in relation to the origin, i.e., selected by BLUP, mean, or BLUP and mean and coincident results were obtained. In the selection for best performance, the efficiency of BLUP was 2.4% higher than the mean. In the selection for the opposite extreme, BLUP analysis was however not advantageous. The progenies <FONT FACE=Symbol>´</FONT> environments interaction indicates the need for an evaluation of the progenies in different environments before beginning selection.
BLUP; selection method; bean improvement; heritability; quantitative genetics
