Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-10T10:07:00.882Z Has data issue: false hasContentIssue false
  • English
  • Français

Bioeconomic Weed Management Models for Sugarbeet (Beta vulgaris) Production

Published online by Cambridge University Press:  12 June 2017

John M. Shribbs ,
Donald W. Lybecker  and
Edward E. Schweizer
John M. Shribbs
Affiliation:
ICI Americas, Inc., P.O. Box 760, Mt. View, CA 94042
Donald W. Lybecker
Affiliation:
Dep. Agric. and Res. Econ., Colorado State Univ., Fort Collins, CO 80523
Edward E. Schweizer
Affiliation:
Agric. Res. Serv., U.S. Dep. Agric., Crops Res. Lab., 1701 Center Ave., Fort Collins, CO 80526
Get access Rights & Permissions [Opens in a new window]

Abstract

Bioeconomic sugarbeet weed management models for preplant, postemergence, and layby herbicides, and late-season handweeding decisions are presented. The personal computer/spreadsheet models are based on number of weed seed in soil, field survey of weed populations, growth stages of weeds and sugarbeets, expected yield loss from weeds, herbicide weed control, weed control cost, and sugarbeet price. The models incorporate two producer risk levels. Several weed scenarios were used to verify the models for reasonable recommendations.

Keywords

SugarbeetBeta vulgaris L. ‘Monohikari’Computer modelseconomicsweed controlinterdisciplinary research
Type
Special Topics
Information
Weed Science , Volume 38 , Issue 4-5 , September 1990 , pp. 436 - 444
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. Cousens, R. 1985. A simple model relating yield loss to weed density. Ann. Appl. Biol. 107:239–252.CrossRefGoogle Scholar
2. Cussans, G. W., Cousens, R. D., and Wilson, B. J. 1986. Thresholds for weed control–the concepts and their interpretation. Proc. EWRS Symp., Economic Weed Control, Pages 253–260.Google Scholar
3. Dawson, J. H. 1974. Full-season weed control in sugarbeets. Weed Sci. 22:330–335.Google Scholar
4. Dawson, J. H. 1977. Competition of late-emerging weeds with sugarbeets. Weed Sci. 25:168–170.Google Scholar
5. Dawson, J. H. 1986. The concept of period thresholds. Proc. EWRS Symp., Economic Weed Control. Pages 327–331.Google Scholar
6. Doyle, C. J., Cousens, R. D., and Moss, S. R. 1986. A model of the economics of controlling Alopercurus myosuroides Huds. in winter wheat Crop Prot. 5:143–150.Google Scholar
7. Eshel, Y., Schweizer, E. E., and Zimdahl, R. L. 1976. Sugarbeet tolerance of post-emergence applications of desmedipham and ethofumesate. Weed Res. 16:249–254.CrossRefGoogle Scholar
8. King, R. P., Lybecker, D. W., Schweizer, E. E., and Zimdahl, R. L. 1986. Bioeconomic modeling to simulate weed control strategies for continuous com (Zea mays). Weed Sci. 34:972–979.Google Scholar
9. Mara, M. C. and Carlson, G. A. 1983. An economic threshold model for weeds in soybeans (Glycine max). Weed Sci. 31:604–609.Google Scholar
10. Schweizer, E. E. 1981. Broadleaf weed interference in sugarbeets (Beta vulgaris). Weed Sci. 29:128–133.CrossRefGoogle Scholar
11. Schweizer, E. E. and Dexter, A. G. 1987. Weed control in sugarbeets (Beta vulgaris) in North America. Rev. Weed Sci. 3:113–133.Google Scholar
12. Schweizer, E. E. and Weatherspoon, D. M. 1971. Response of sugarbeets and weeds to phenmedipham and two analogues. Weed Sci. 19:635–639.Google Scholar
13. Scott, R. K. and Wilcockson, S. J. 1976. Weed biology and the growth of sugarbeet. Ann. Appl. Biol. 83:331–335.CrossRefGoogle Scholar
14. Scott, R. K., Wilcockson, S. J., and Moisey, F. R. 1979. The effects of time of weed removal on growth and yield of sugarbeet J. Agric. Sci., Cambridge. 93:693–709.CrossRefGoogle Scholar
15. Shribbs, J. M., Schweizer, E. E., Hergert, L., and Lybecker, D. W. 1990. Validation of four bioeconomic weed management models for sugarbeet (Beta vulgaris) production. Weed Sci. 38:445–451.Google Scholar
16. Storer, K. R., Schmehl, W. R., and Hecker, R. J. 1973. Growth analysis studies of sugarbeet. Colorado State Univ. Exp. Stn. Tech. Bull. No. 118. 69 pp.Google Scholar
17. Wicks, G. A., Anderson, F. N., and Robison, L. R. 1970. Weed control in sugarbeets. Univ. Nebraska Ext. Circ. 204, 18 pp.Google Scholar
18. Wicks, G. A. and Wilson, R. G. 1983. Control of weeds in sugarbeets (Beta vulgaris) with handhoeing and herbicides. Weed Sci. 31:493–499.Google Scholar
19. Wilkerson, G. G., Modena, S. A., and Coble, H. D. 1988. HERB V2.0: Herbicide decision model for postemergence weed control in soybeans–User's Manual. Bull. No. 113. Crop Sci. Dep., North Carolina State Univ. 98 pp.Google Scholar
20. 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
21. Winter, S. R. and Wiese, A. F. 1982. Economical control of weeds in sugarbeets (Beta vulgaris). Weed Sci. 30:620–623.Google Scholar