Goplen, Jared2017-07-182017-07-182017-03https://hdl.handle.net/11299/188831University of Minnesota Ph.D. dissertation. March 2017. Major: Applied Plant Sciences. Advisor: Jeffrey Gunsolus. 1 computer file (PDF); v, 73 pages.Herbicide-resistant biotypes of giant ragweed are becoming widespread, making control with herbicides increasingly difficult. To improve control of giant ragweed and prevent the proliferation of resistant biotypes, it is necessary to use integrated methods of weed control. This research evaluated the economic performance and weed control potential of several crop rotations and spring pre-plant tillage dates. The prediction accuracy of previously developed giant ragweed emergence models was evaluated in various crop rotations and spring tillage dates to determine the giant ragweed emergence model most effective at predicting emergence. Total and temporal patterns of giant ragweed emergence were evaluated in various spring tillage dates to determine the best timing of spring tillage for giant ragweed control. Finally, the economic performance of various crop rotations was determined in the presence of herbicide-resistant giant ragweed. This research provides a valuable assessment of the crop rotations, tillage dates, and emergence models that are most effective in improving herbicide-resistant giant ragweed control.enEmergence ModelingHerbicide ResistanceIntegrated Weed ManagementThesis or Dissertation