Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-10T13:28:46.975Z Has data issue: false hasContentIssue false
  • English
  • Français

The Threshold Concept and its Application to Weed Science

Published online by Cambridge University Press:  12 June 2017

Harold D. Coble  and
David A. Mortensen
Harold D. Coble
Affiliation:
Dep. Crop Sci., N. C. State Univ., Raleigh, NC 27695
David A. Mortensen
Affiliation:
Agron. Dep., Univ. Nebr., Lincoln, NE 68583
Get access Rights & Permissions [Opens in a new window]

Abstract

The concept of thresholds has many applications in weed science, depending on the response being measured. The most common adjectives used to describe thresholds are damage, economic, period, and action. Damage threshold is the term used to define the weed population at which a negative crop yield response is detected. An economic threshold is the weed population at which the cost of control is equal to the crop value increase from control of the weeds present. Economic threshold may be used to describe short-term effects of weed interference occurring in a single growing season, or multiple-season effects including some cost associated with seed produced by uncontrolled plants. The term period threshold implies that there are times during the crop cycle in which weeds are more or less damaging than at others. Action threshold is the point at which some control action is initiated, and usually includes economic considerations along with other less tangible factors such as aesthetics, risk aversion, or sociological pressures. Regardless of the type, thresholds imply that weed effects are population dependent, and as such, allow some type of prediction to be made relative to the consequences of control decisions. One successful approach to the implementation of thresholds has been through the development of computerized decision-aid software. These programs allow users to compare economic and environmental consequences of potential control actions before committing to one particular decision.

Keywords

Weed interferenceeconomic thresholddecision aid
Type
Symposium
Information
Weed Technology , Volume 6 , Issue 1 , March 1992 , pp. 191 - 195
Copyright
Copyright © 1990 by the Weed Science Society of America 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Literature Cited

1. Anonymous. 1980. Webster's New World Dictionary of the American Language. Second college edition. Simon and Schuster Publ. New York, N.Y. Google Scholar
2. Auld, B. A., and Tisdell, C. A. 1987. Economic thresholds and response to uncertainty in weed control. Agric. Syst. 25:219–227.Google Scholar
3. Ball, D. A., and Miller, S. D. 1989. A comparison of techniques for estimation of arable soil seedbanks and their relationship to weed flora. Weed Res. 29:365–373.Google Scholar
4. Bauer, T. A., Mortensen, D. A., and Wicks, G. A. 1990. Environmental variability and economic thresholds for soybeans. Abstr. Weed Sci. Soc. Am. 30:53.Google Scholar
5. Bauer, T. A., and Mortensen, D. A. 1992. A comparison of economic and economic optimum thresholds for two annual weeds in soybeans. Weed Technol. 6:228–235.Google Scholar
6. Burnside, O. C., Fenster, C. R., Evetts, L. L., and Mumm, R. F. 1981. Germination of exhumed weed seed in Nebraska. Weed Sci. 29:577–586.Google Scholar
7. Chisaka, H. 1977. Weed damage to crops: Yield loss due to weed competition. p. 1–16 in Integrated Control of Weeds, Fryer, J. D., and Matsunaka, S., eds. Univ. of Tokyo Press, Tokyo.Google Scholar
8. Coble, H. D. 1985. Development and implementation of economic thresholds for soybean. p. 295–307 in Frisbee, R. E., and Adkisson, P. L., eds. Integrated Pest Management of Major Agricultural Systems, Texas A&M University, College Station, Tex. Google Scholar
9. Coble, H. D., Williams, F. M., and Ritter, R. L. 1981. Common ragweed interference in soybeans. Weed Sci. 29:339–342.Google Scholar
10. Cousens, R. 1987. Theory and reality of weed control thresholds. Plant Prot. Q. 2:13–20.Google Scholar
11. Cousens, R. 1985. A simple model relating yield loss to weed density. Ann. Appl. Biol. 107:239–252.CrossRefGoogle Scholar
12. Cousens, R., Wilson, B. J., and Cussans, G. W. 1985. To spray or not to spray: the theory behind the practice. Proc. 1985 Brit. Crop Prot. Conf.–Weeds. p. 671–678.Google Scholar
13. Cousens, R., Doyle, C. J., Wilson, B. J., and Cussans, G. W. 1986. Modelling the economics of controlling Avena fatua in winter wheat. Pestic. Sci. 17:1–12.Google Scholar
14. Dawson, J. H. 1986. The concept of period thresholds. Proc. Eur. Weed Res. Soc. Symposium 1986, Economic Weed Control. p. 327–331.Google Scholar
15. Doyle, C. J., Cousens, R., Moss, S. R. 1986. A model of the economics of controlling Alopecuris myosuroides in winter wheat. Crop Prot. 5:143–150.Google Scholar
16. Eaton, B. J., Russ, O. G., and Feltner, K. C. 1973. Venice mallow competition in soybeans. Weed Sci. 21:89–94.Google Scholar
17. Egley, G. H., and Chandler, J. M. 1983. Longevity of weed seeds after 5.5 years in the Stoneville 50-year buried-seed study. Weed Sci. 31:264–270.Google Scholar
18. Forcella, F. 1990. Breeding soybeans tolerant to weed competition. Abstr. Weed Sci. Soc. Am. 30:51.Google Scholar
19. Légère, A., and Schreiber, M. M. 1989. Competition and canopy architecture as affected by soybean (Glycine max) row width and density of redroot pigweed (Amaranthus retroflexus). Weed Sci. 37:84–92.CrossRefGoogle Scholar
20. Lueschen, W. E., and Anderson, R. L. 1980. Longevity of velvetleaf (Abutilon theophrasti) seeds in soil under agricultural practices. Weed Sci. 28:341–346.CrossRefGoogle Scholar
21. Martin, M.P.L.D., and Field, R. J. 1988. Influence of time of emergence of wild oat on competition with wheat. Weed Res. 28:111–116.Google Scholar
22. McWhorter, C. G., and Anderson, J. M. 1979. Hemp sesbania (Sesbania exaltata) competition in soybeans (Glycine max). Weed Sci. 27:58–63.Google Scholar
23. Mortensen, D. A., and Coble, H. D. 1989. The influence of soil water content on common cocklebur (Xanthium strumarium) interference in soybeans (Glycine max). Weed Sci. 37:76–83.CrossRefGoogle Scholar
24. Norris, R. F. 1984. Weed thresholds in relation to long-term population dynamics. Proc. West Weed Sci. Soc. 25:38–44.Google Scholar
25. Oliver, L. R. 1979. Influence of soybean (Glycine max) planting date on velvetleaf (Abutilon theophrasti) competition. Weed Sci. 27:183–188.Google Scholar
26. Reichelderfer, K. H. 1980. Economics of integrated pest management: Discussion. Am. J. Agric. Econ. 62:1012–1013.Google Scholar
27. Stoller, E. W., Harrison, S. K., Wax, L. M., Regnier, E. E., and Nafziger, E. D. 1987. Weed interference in soybeans (Glycine max). Rev. Weed Sci. 3:155–181.Google Scholar
28. Weaver, S. E. 1986. Factors affecting threshold levels and seed production of jimsonweed (Datura stramonium L.) in soyabeans [Glycine max (L.) Merr.]. Weed Res. 26:215–223.Google Scholar
29. Wilkerson, G. G., Modena, S. A., and Coble, H. D. 1988. HERB v2.0: Herbicide decision model for postemergence weed control in soybeans, Users manual. Bull. No. 113, Crop Sci. Dep., N. C. State Univ., Raleigh, N.C. Google Scholar
30. Wilson, R. G., Kerr, E. D., and Nelson, L. A. 1985. Potential for using weed seed content in the soil to predict future weed problems. Weed Sci. 33:171–175.Google Scholar