Modeling the Optimal Strategies for Mitigating Genetically Modified (GM) Wheat Contamination Risks
| dc.creator | Ge, Houtian | |
| dc.creator | Goetz, Stephan | |
| dc.creator | Gray, Richard | |
| dc.creator | Nolan, James | |
| dc.date | 2017-04-01T20:12:07Z | |
| dc.date.accessioned | 2026-07-09T10:33:24Z | |
| dc.description | Wheat contamination issues of recent years harmed the reputation and customer trust of U.S. production and threatened U.S. exports. There would appear to be a need for research designed to identify and validate novel reactive strategies designed to maintain sustainable and competitive grain supply chains. This research attempts to identify cost-effective handling strategies to mitigate the genetically modified (GM) wheat contamination risks. We explicitly model the U.S. wheat supply chain in a realistic manner to embrace complexity inherent in the system. The specification of appropriate wheat handling strategies in the supply chain is formulated as system optimization problems and solved by using simulation. Once solved for a base scenario, sensitivity analysis is conducted on key variables that influence wheat quality testing strategies. | |
| dc.identifier | doi:10.22004/ag.econ.235939 | |
| dc.identifier | https://ageconsearch.umn.edu/record/235939/files/AAEA%20wheat%20paper%20may%2025.pdf | |
| dc.identifier | http://ageconsearch.umn.edu/record/235939 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/619827 | |
| dc.language | eng | |
| dc.publisher | ||
| dc.source | http://ageconsearch.umn.edu/record/235939 | |
| dc.title | Modeling the Optimal Strategies for Mitigating Genetically Modified (GM) Wheat Contamination Risks | |
| dc.type | Text |