USING BEST LINEAR UNBIASED PREDICTIONS TO ENHANCE BREEDING FOR YIELD IN SOYBEAN .1. CHOOSING PARENTS

In self-pollinated crops, choosing parents typically is accomplished b y calculating parental performance from historical data and then calcu lating the midparent value (MPV) for potential crosses. When limited o r no data exist for parents of interest, precise predictions are diffi cult or impossible to obtain. Best linear unbiased prediction (BLUP), has been used to determine paired matings in dairy cattle under condit ions described above. The objectives of this study were to compare the efficiencies of two methods of parental selection, MPV and BLUP, for identifying superior soybean [Glycine mar (L.) Merr.] cross combinatio ns when (i) equal and unequal amounts of yield data on all potential p arents were available, and (ii) unequal amounts of yield data were ava ilable for some parents and no data were available for others. F-4-F-6 bulks and F-5:6 lines from 24 soybean crosses were evaluated to estim ate the mean yield performance of each cross. Historical yield records on the parents of each cross were used to predict the performance of the 24 crosses. Numbers of records on the parents were restricted to p rovide simulated situations of balanced and unbalanced parent data ava ilability. The performance of each cross was predicted with MPV and BL UP for each situation. Standard errors of the predicted differences (S E) and rank correlations between the actual and the predicted performa nces were calculated to determine the relative efficiencies of MPV and BLUB. In every case, predictions from BLUP provided higher rank corre lations, lower SE, and identified higher percentages of the superior c rosses than MPV.