Economics of weed management: Principles and practices

Weed Technology

Volumn 18, Issue SPEC. ISSUE 1, 2004, Pages 1403-1407

  Wiles, Lori J ^a  

^a U S DEPARTMENT OF AGRICULTURE   (United States)

Author keywords

Decision analysis; Economic analysis; Economic threshold; Risk; Value of information

Indexed keywords

EID: 38349185770     PISSN: 0890037X     EISSN: None     Source Type: Journal    
DOI: 10.1614/0890-037X(2004)018[1403:EOWMPA]2.0.CO;2     Document Type: Conference Paper

References (35)

1. Auld, B. A., K. M. Menz, and C. A. Tisdell. 1987. Weed Control Economics. London: Academic. 177 p.
2. Bauer, T. A. and D. A. Mortensen. 1992. A comparison of economic optimum thresholds for two annual weeds in soybeans. Weed Technol. 6:228-235.
3. Bennett, A. C., A. J. Price, M. C. Sturgill, G. S. Buol, and G. G. Wilkerson. 2003. HADSS™, Pocket HERB™, and WebHADSS™: decision aids for field crops. Weed Technol. 17:412-420.
4. Coble, H. D. and D. A. Mortensen. 1992. The threshold concept and its application to weed science. Weed Technol. 6:191-195.
5. Cousens, R. 1987. Theory and reality of weed control thresholds. Plant Prot. Q. 2:13-20.
6. Czapar, G. F., M. P. Curry, and L. M. Wax. 1997. Grower acceptance of economic thresholds for weed management in Illinois. Weed Technol. 11:828-831.
7. de Buck, A. J., H. B. Schoorlemmer, G.A.A. Wossink, and S.R.M. Janssens. 1999. Risks of post-emergence weed control strategies in sugar beet: development and application of a bioeconomic model. Agric. Syst. 59: 283-299.
8. Dillon, J. L. 1977. The Analysis of Response in Crop and Livestock Production. 2nd ed. New York: Pergamon. 251 p.
9. Faechner, T., K. Norrena, A. G. Thomas, and C. V. Deutsch. 2002. A riskqualified approach to calculate locally varying herbicide application rates. Weed Res. 42:476-485.
10. Hardaker, J. B., R.B.M. Huirne, and J. R. Anderson. 1997. Coping With Risk in Agriculture. New York: CABI. 274 p.
11. Hoag, D. L. and A. G. Hornsby. 1992. Coupling groundwater contamination with economic returns when applying farm pesticides. J. Environ. Qual. 21:579-586.
12. Jones, R. E. and R. Medd. 2000. Economic thresholds and the case for longer term approaches to population management of weeds. Weed Technol. 14: 337-350.
13. Jordan, D. L., G. G. Wilkerson, and D. W. Krueger. 2003. Evaluation of scouting methods in peanut (Arachis hypogaea) using theoretical net returns from HADSS®. Weed Technol. 17:358-365.
14. Jordan, N. 1992. Weed demography and population dynamics: implications for threshold management. Weed Technol. 6:184-190.
15. King, R. P., D. W. Lybecker, E. E. Schweizer, and R. Zimdahl. 1986. Bioeconomic modeling to simulate weed control strategies for continuous corn. Weed Sci. 34:972-979.
16. King, R. P., S. M. Swinton, D. W. Lybecker, and C. A. Oriade. 1998. The economics of weed control and the value of weed management information. In J. L. Hatfield, D. D. Buhler, and B. A. Stewart, eds. Integrated Weed Management. Chelsea, MI: Ann Arbor Press. Pp. 25-41.
17. Lui, S., G. A. Carlson, and D. L. Hoag. 1995. Trade-off analysis of herbicide withdrawals on agricultural production and groundwater quality. J. Agric. Appl. Econ. 27:283-300.
18. Martin, A., D. A. Mortensen, and J. L. Lindquist. 1998. Decision support models for weed management: in-field management tools. In J. L. Hatfield, D. D. Buhler, and B. A. Stewart, eds. Integrated Weed Management. Chelsea, MI: Ann Arbor Press. Pp. 361-369.
19. Monks, C. D., D. C. Bridges, J. W. Woodruff, T. R. Murphy, and D. J. Berry. 1995. Expert system evaluation and implementation for soybean (Glycine max) weed management. Weed Technol. 9:535-540.
20. Moore, J. 1996. Economic factors influencing control and management decisions for annual grasses in crops and pastures. Plant Prot. Q. 11:217-222.
21. Munier-Jolain, N. M., B. Chauvel, and J. Gasquez. 2002. Long-term modeling of weed control strategies: analysis of threshold-based options for weed species with contrasted competitive abilities. Weed Res. 42:107-122.
22. Olson, K. D. and V. R. Kidman. 1992. A farmer's choice of weed control method and the impacts of policy and risk. Rev. Agric. Econ. 14:125-137.
23. Oriade, C. A., R. P. King, F. Forcella, and J. L. Gunsolus. 1996. A bioeconomic analysis of site-specific management for weed control. Rev. Agric. Econ. 18:523-535.
24. Pannell, D. J. 1988. Weed management: a review of applied economics research. Rev. Mark. Agric. Econ. 56:255-269.
25. Pannell, D. J. 1994. The value of information in herbicide decision making for weed control in Australian wheat crops. J. Agric. Resour. Econ. 19: 366-381.
26. Schweizer, E. E., D. W. Lybecker, and L. J. Wiles. 1998. Important biological information needed for bioeconomic weed management models. In J. L. Hatfield, D. D. Buhler, and B. A. Stewart, eds. Integrated Weed Management. Chelsea, MI: Ann Arbor Press. Pp. 1-24.
27. Swinton, S. M. and R. P. King. 1994. The value of pest information in a dynamic setting: the case of weed control. Am. J. Agric. Econ. 76:34-36.
28. Swinton, S. M., D. W. Lybecker, and R. P. King. 1995. The effect of local triazine restriction policies on recommended weed management in corn. Rev. Agric. Econ. 17:351-367.
29. Swinton, S. M., K. A. Renner, and J. J. Kells. 2002. On-farm comparison of three postemergence weed management decision aids in Michigan. Weed Technol. 16:691-698.
30. U.S. Congress, Office of Technology Assessment. 1993. The application of decision making methods. In Harmful Non-Indigenous Species in the United States. Washington, DC: U.S. Government Printing Office OTAF-565.
31. Wiles, L., R. Bobbitt, B. Flynn, and P. Westra. 2003. Evaluating the Benefits of Site-Specific Weed Management. Abstracts of the American Society of Agronomy. Madison, WI: American Society of Agronomy. A08-wiles-430877-poster [CD-ROM].
32. Wiles, L. J., H. J. Gold, and G. G. Wilkerson. 1993. Modelling the uncertainty of weed density estimates to improve post-emergence herbicide control decisions. Weed Res. 33:241-252.
33. Wiles, L. J., R. P. King, E. E. Schweizer, D. W. Lybecker, and S. M. Swinton. 1996. GWM: general weed management model. Agric. Syst. 50:355-376.
34. Wiles, L. J., G. G. Wilkerson, and H. J. Gold. 1992. Value of information about weed distribution for improving post-emergence control decisions. Crop Prot. 11:547-554.
35. Wilkerson, G. G., L. J. Wiles, and A. Bennett. 2002. Weed management decision models: pitfalls, perceptions, and possibilities of the economic threshold approach. Weed Sci. 50:411-424.