Prediction of Corn Hybrids Using the Total Effects of Associated Markers Approach.

The objective of a corn breeding program is to find the best combinations between the inbred lines. However, the number of potential crosses grows rapidly as more inbred lines are generated, and is known that the field evaluation of hybrid performance requires extremely large resources. Hybrid prediction is expected to increase genetic gains by increasing selection intensity and accelerating the breeding cycle. The present study aimed to predict the performance of corn hybrids and evaluate if the total effects of associated markers (TEAM) method can correctly predict hybrids using cross validation and regional trials. The training population was performed in 7 locations of Southern Brazil during the 2010 season. The regional trials were conducted in 6 different locations in the South of Brazil during the 2011 season. In the training trial, 51 inbred lines from different backgrounds were used and 58 single cross hybrids were created. Seventy-nine microsatellite markers were used to genotype the 51 inbred lines and to construct the matrices of additive and dominance effects. The predictive accuracy, using the cross validation method, ranged from 0.10 to 0.96, depending on the sample size. The accuracy was 0.30 when the hybrids values that were not used in the training population (152) were predicted for the regional trials. Considering selective loss, the TEAM method correctly predicted 50% of the hybrids selected in the regional trials, which is considered to be a satisfactory value because the prediction and assessment were performed in completely different environments. There was also loss in only 33% of cases; that is, only 33% of the materials predicted to be good were considered to be bad, according to the results from the regional assays. Overall, the results of this study show that the predictive validation of different crop conditions is possible and the cross-validation results represented the field performance.