Optimization of the number of cycles and intensity of selection, and population size in mass selection: Selection for single traits in outcrossing plant populations

Optimum number of cycles and rate of selection and optimum population size to give the highest cost efficiency in mass selection for allogamous crop plants were investigated. The optimum values of these variables were obtained based on the numerical calculations of a new selection efficiency index, S/C, where S stands for the probability that the desired genetic improvement is achieved in the target population, and C is the cost expended for that end. Selection procedures that maximize S/C will give the greatest opportunity of success under a certain total resource investment. The index S/C was calculated based on Monte Carlo simulations with a model in which the target population was initiated as a hybrid population of two cultivar lines that were genetically fixed for the trait concerned, and populations of a constant size were generated for subsequent selection cycles via random crossing between the plants selected with a constant rate in each cycle. The genes involved were assumed to be inherited independently and have no epistatic interaction. The calculations over practically possible ranges of the related variables led to the following conclusions. If, as would be the case in most selection projects for breeding a new commercial variety, the expenditure of time (years) rather than the resource expense for managing the selection is important, a few to several cycles of selection with a rate of around 1%, testing a few thousand plants per cycle, should be nearly if not exactly the optimum. If the desired improvement is not achieved in these cycles, the population should be discarded and a new one should be tested. By contrast, if the time expenditure is not important, as in the case of the selection for new breeding stock lines, selection with several or more cycles, a rate in the range of 10 to 20% and a population size smaller than 100 should be cost-efficient