Open Access

Using Fitness Value for Monitoring Kiwifruit’s Variant Seedling in Tissue Culture

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Cybernetics and Information Technologies
Issue Title: Special Issue on Application of Advanced Computing and Simulation in Information Systems


Based on Genetic Algorithm, a pattern recognition approach using fitness to dynamically monitor the sub cultured seeding of kiwifruit is proposed in order to decrease the loss of variant seedlings in tissue culture. By coding, selection, mutation and cross-overing the selected primer pairs of the sub cultured seeding, we simulate the process of optimizing the kiwifruit’s genomic DNA polymorphism. The corresponding fitness values of the primer pairs are evaluated with fitness function for monitor the variation of kiwi’s DNA. The result shows that kiwi’s plantlets can better maintain their genes’ genetic stability for the first to the ninth generation. But from the tenth generation, the fitness values become variation. The results are based on experimentation, which uses optimized AFLP system for analyzing genetic diversity of 75 samples of seventh to eleventh 5 generations of kiwi.

Publication timeframe:
4 times per year
Journal Subjects:
Computer Sciences, Information Technology