Simulation modeling in plant breeding : Principles and applications
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Permanent link to cite or share this item: http://hdl.handle.net/10568/44100
Conventional plant breeding largely depends on phenotypic selection and breeder's experience, therefore the breeding efficiency is low and the predictions are inaccurate. Along with the fast development in molecular biology and biotechnology, a large amount of biological data is available for genetic studies of important breeding traits in plants, which in turn allows the conduction of genotypic selection in the breeding process. However, gene information has not been effectively used in crop improvement because of the lack of appropriate tools. The simulation approach can utilize the vast and diverse genetic information, predict the cross performance, and compare different selection methods. Thus, the best performing crosses and effective breeding strategies can be identified. QuLine is a computer tool capable of defining a range, from simple to complex genetic models, and simulating breeding processes for developing final advanced lines. On the basis of the results from simulation experiments, breeders can optimize their breeding methodology and greatly improve the breeding efficiency. In this article, the underlying principles of simulation modeling in crop enhancement is initially introduced, following which several applications of QuLine are summarized, by comparing the different selection strategies, the precision parental selection, using known gene information, and the design approach in breeding. Breeding simulation allows the definition of complicated genetic models consisting of multiple alleles, pleiotropy, epistasis, and genes, by environment interaction, and provides a useful tool for breeders, to efficiently use the wide spectrum of genetic data and information available.
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