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Optimal contribution selection was an effective tool to optimally allocate different combinations of reproductive technologies.
Optimal contribution selection was an effective tool in optimizing the allocations of combined reproductive technologies.
This study demonstrates the benefits of optimizing the allocation of females to reproductive technologies through the use of optimal contribution selection, which resulted in increased rates of genetic gain under sustainable rates of inbreeding.
Optimal contribution of improved models in overall estimation is computed by mean of the BA method.
ICA is employed to obtain the optimal contribution of ANN for a better water saturation prediction.
In the weighted averaging method a genetic algorithm (GA) was employed to obtain the optimal contribution of each algorithm in construction of the CMIS.
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This could cause a setback in the genetic diversity gained for both equal contribution- as well as optimal contribution-schemes.
Therefore, optimal contributions based on pedigrees with MPI can perform less well than equal contributions.
If WSI is over 35%, on average, optimal contributions preserve less genetic diversity than equal contributions.
Optimal contributions are extremely sensitive to differences in kinship between candidates.
However, policies like mean kinship and optimal contributions, might be impractical.
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