Table 5 Combinations of years in the candidate and test sets in which the different training set optimization methods were tested. For each test set year, the candidate set is initially composed of the previous year, and older years are progressively included, e.g. 5-3 indicates that the candidate set contains all data from years 3, 4, and 5. For a given combination of years in the candidate set, optimization can be used to find an optimal subset of all hybrids tested in said years. This subset then becomes the training set. The optimized training sets are subsequently used to calibrate genomic selection models. Finally, the predictive ability of the model in the test set is used to evaluate the performance of the optimization of its training set

From: Maximizing efficiency in sunflower breeding through historical data optimization