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Theoretical and Applied Genetics

pp 1–12

First Online: 24 June 2017Received: 29 March 2017Accepted: 15 June 2017DOI: 10.1007-s00122-017-2938-9

Cite this article as: Cameron, J.N., Han, Y., Wang, L. et al. Theor Appl Genet 2017. doi:10.1007-s00122-017-2938-9

Abstract

Key messageUsing an Operations Research approach, we demonstrate design of optimal trait introgression projects with respect to competing objectives.

AbstractWe 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.

Communicated by Matthias Frisch.

Electronic supplementary materialThe online version of this article doi:10.1007-s00122-017-2938-9 contains supplementary material, which is available to authorized users.





Autor: John N. Cameron - Ye Han - Lizhi Wang - William D. Beavis

Fuente: https://link.springer.com/







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