The Use of Adaptive Genetic Algorithm for Detecting Kiwifruit’s Variant Subculture Seedling
In order to reduce the possible economic loss brought by variant seedlings in tissue culture, we propose a pattern recognition approach using fitness to dynamically monitor subculture seedlings of kiwifruit based on adaptive Genetic Algorithm. By coding, selection, mutation and crossover the selecte...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Bulgarian Academy of Sciences
2017-12-01
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| Series: | International Journal Bioautomation |
| Subjects: | |
| Online Access: | http://www.biomed.bas.bg/bioautomation/2017/vol_21.4/files/21.4_08.pdf |
| Summary: | In order to reduce the possible economic loss brought by variant seedlings in tissue culture, we propose a pattern recognition approach using fitness to dynamically monitor subculture seedlings of kiwifruit based on adaptive Genetic Algorithm. By coding, selection, mutation and crossover the selected primer pairs of the subculture seedlings, we simulate the process of optimizing the kiwifruit’s genomic DNA polymorphism. The result shows that fitness values of kiwifruit’s subculture seedlings can better maintain their genetic stability from the first to the ninth generation in the simulation. But from the tenth generation, the rapid change of the fitness values of subculture seedlings happen. It is in accord with the experimentation, which uses optimized AFLP system for analyzing genetic diversity of 75 samples of seventh to eleventh 5 generations of kiwifruit subculture seedlings. |
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| ISSN: | 1314-1902 1314-2321 |