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Systematic design for trait introgression projects
Theoretical and Applied Genetics
  • John N. Cameron, Iowa State University
  • Ye Han, Iowa State University
  • Lizhi Wang, Iowa State University
  • William D. Beavis, Iowa State University
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We demonstrate an innovative approach for designing Trait Introgression (TI) projects based on optimization principles from Operations Research. If the designs of TI projects are based on clear and measurable objectives, they can be translated into mathematical models with decision variables and constraints that can be translated into Pareto optimality plots associated with any arbitrary selection strategy. The Pareto plots can be used to make rational decisions concerning the trade-offs between maximizing the probability of success while minimizing costs and time. The systematic rigor associated with a cost, time and probability of success (CTP) framework is well suited to designing TI projects that require dynamic decision making. The CTP framework also revealed that previously identified ‘best’ strategies can be improved to be at least twice as effective without increasing time or expenses.

This article is published as Cameron, J.N., Han, Y., Wang, L. et al. Theor Appl Genet (2017). doi:10.1007/s00122-017-2938-9. Posted with permission.

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John N. Cameron, Ye Han, Lizhi Wang and William D. Beavis. "Systematic design for trait introgression projects" Theoretical and Applied Genetics (2017) p. 1 - 12
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