Computer aided selection in breeding programs using genetic algorithm in MATLAB program

In plant and animal breeding, the best individuals are selected for the next breeding cycle based on the selection index computed from observed phenotypic values of several traits. However, in calculating the selection index, large amounts of data must be analyzed which is still performed by a calculator. This can cause imperfections in the breeding procedures. In this paper an automatic method for simulating a population under natural selection is proposed based on the selection operator of the genetic algorithms. The fitness function of the algorithm is a linear combination of the individual traits imported by the user. The algorithm generates both general and detailed scores of each trait for each labeled individual. The individuals are sorted with respect to their general scores and it is possible to extract individuals whose general scores are greater than a threshold defined by the user. The outlier individuals can also be eliminated. Moreover, for improved illustration and comparison, the individuals are displayed in a graph based on their index values. The proposed algorithm was applied to two distinct dataset and shown that results of the two methods coincide. The proposed method is automatic, fast, and free of human mistakes. Therefore, it is expected to improve the breeding procedures, especially when the numbers of individuals and traits are huge.