Hostname: page-component-8448b6f56d-c47g7 Total loading time: 0 Render date: 2024-04-25T01:14:19.894Z Has data issue: false hasContentIssue false
  • English
  • Français

Decision Rules for Postemergence Control of Pigweed (Amaranthus spp.) in Soybean (Glycine max)

Published online by Cambridge University Press:  12 June 2017

Anita Dieleman ,
Allan S. Hamill ,
Glenn C. Fox  and
Clarence J. Swanton
Anita Dieleman
Affiliation:
Crop Sci. Dep. Univ. of Guelph, Guelph, ON N1G 2W1
Allan S. Hamill
Affiliation:
Agric. Can. Res. Stn., Harrow, ON N0R 1G0
Glenn C. Fox
Affiliation:
Ag. Econ. and Bus. Dep., Univ. of Guelph, Guelph, ON
Clarence J. Swanton
Affiliation:
Crop Sci. Dep., Univ. of Guelph, Guelph, ON N1G 2W1
Get access Rights & Permissions [Opens in a new window]

Abstract

Weed control decision rules were derived for the application of postemergence herbicides to control pigweed species in soybean. Field experiments were conducted at two locations in 1992 and 1993 to evaluate soybean-pigweed interference. A damage function was determined that related yield loss to time of pigweed emergence, density, and soybean weed-free yield. A control function described pigweed species response to variable doses of imazethapyr and thifensulfuron. The integration of these two functions formed the basis of an economic model used to derive two weed control decision rules, the biologist's “threshold weed density” and the economist's “optimal dose.” Time of weed emergence had a more significant role than weed density in the economic model. Later-emerging pigweed caused less yield loss and therefore, decision rules lead to overuse of herbicides if emergence time is not considered. The selected herbicide dose influenced the outcome of the control function. Depending on the desired level of weed control, a herbicide could be chosen to either eradicate the escaped weed species (label or biologically-effective doses) or reduce the growth of the weed species and thereby offset interference (optimal dose). The development of a biologically-effective dose by weed species matrix was recommended. Decision rules should not be utilized as an exclusive weed management strategy but rather as a component of an integrated weed management program.

Keywords

Imazethapyr, 2-[4,5-dihydro-4-methyl-4-(1-methylethyl)-5-oxo-1 H-imidazol-2-yl]-5-ethyl-3-pyridinecarboxylic acidthifensulfuron, 3-[[[[(4-methoxy-6-methyl-1,3,5-triazin-2-yl)amino]carbonyI]amino]sulfonyl]-2-thiophenecarboxylic acidgreen pigweed, Amaranthus powellii S. Wats. ♯ AMAPOredroot pigweed, Amaranthus retroflexus L. ♯ AMAREsoybean, Glycine max (L.) Merr. ‘Maple Glen’ and ‘KG 60.’Economicsintegrated weed managementtime of emergenceweed densityAMAPOAMARE
Type
Weed Management
Information
Weed Science , Volume 44 , Issue 1 , March 1996 , pp. 126 - 132
Copyright
Copyright © 1996 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. Adcock, T. E. and Banks, P. A. 1991. Effects of preemergence herbicides on the competitiveness of selected weeds. Weed Sci. 39: 54–56.CrossRefGoogle Scholar
2. Anonymous. 1989. Grain and forage crops: estimated production costs Ontario, 1989. Economics Information Rept. No. 89-05. Ont. Min. Agric. Fd., Toronto, ON. 26 pp.Google Scholar
3. Auld, B. A., Menz, K. M., and Tisdell, C. A. 1987. Weed Control Economics. Academic Press Inc. Ltd, London, UK. p. 47–62.Google Scholar
4. 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.CrossRefGoogle Scholar
5. Bauer, T. A., Mortensen, D. A., Wicks, G. A., Hayden, T. A., and Martin, A. R. 1991. Environmental variability associated with economic thresholds for soybeans. Weed Sci. 39: 564–569.CrossRefGoogle Scholar
6. Brown, D. M. 1978. Heat units for corn in southern Ontario. Factsheet, Agdex 111/31, Ont. Min. Agric. Fd., Toronto, ON. 4 pp.Google Scholar
7. Brown, H. M., Wittenbach, V. A., Forney, D. R., and Strachan, S. D. 1990. Basis for soybean tolerance to thifensulfuron methyl. Pest. Biochem. Phys. 37: 303–313.CrossRefGoogle Scholar
8. Cantwell, J. R., Liebl, R. A., and Slife, F. W. 1989. Imazethapyr for weed control in soybean (Glycine max). Weed Technol. 3: 596–601.CrossRefGoogle Scholar
9. Chism, W. J., Birch, J. B., and Bingham, S. W. 1992. Nonlinear regressions for analyzing growth stage and quinclorac interactions. Weed Technol. 6: 898–903.CrossRefGoogle Scholar
10. Cousens, R. 1985. A simple model relating yield loss to weed density. Ann. App. Biol. 107: 239–252.CrossRefGoogle Scholar
11. Cousens, R. 1987. Theory and reality of weed control thresholds. Plant Prot. Q. 2: 13–20.Google Scholar
12. Cousens, R., Brain, P., O'Donovan, J. T., and O'Sullivan, P. A. 1987. The use of biologically realistic equations to describe the effects of weed density and relative time of emergence on crop yield. Weed Sci. 35: 720–725.CrossRefGoogle Scholar
13. Deen, W., Weersink, A., Turvey, C. G., and Weaver, S. E. 1993. Weed control decision rules under uncertainty. Rev. Agric. Econ. 15: 39–50.CrossRefGoogle Scholar
14. Devlin, D. L., Long, J. H., and Maddux, L. D. 1991. Using reduced rates of postemergence herbicides in soybeans (Glycine max). Weed Technol. 5: 834–840.CrossRefGoogle Scholar
15. Dieleman, A., Hamill, A. S., Weise, S. F., and Swanton, C. J. 1995. Empirical models of pigweed (Amaranthus spp.) interference in soybean (Glycine max). Weed Sci. (In press).CrossRefGoogle Scholar
16. Draper, N. R. and Smith, H. 1981. Applied Regression Analysis. John Wiley and Sons, Inc., New York, NY. p 490–521.Google Scholar
17. Fehr, W. R. and Caviness, C. E. 1977. Stages of soybean development. Spec. Rep. 80. Cooperative Ext. Serv., Iowa State Univ., Ames, IA. 12 pp.Google Scholar
18. Forcella, F., Westgate, M. E., and Warnes, D. D. 1992. Effect of row width on herbicide and cultivation requirements in row crops. Am. J. Alt. Agric. 7: 161–167.CrossRefGoogle Scholar
19. Frick, B. and Thomas, A. G. 1992. Weed surveys in different tillage systems in southwestern Ontario field crops. Can. J. Plant Sci. 72: 1337–1347.CrossRefGoogle Scholar
20. Knezevic, S. Z., Weise, S. F., and Swanton, C. J. 1994. Interference of redroot pigweed (Amaranthus retroflexus) in corn (Zea mays). Weed Sci. 42: 568–573.CrossRefGoogle Scholar
21. Kropff, M. J. and Spitters, C.J.T. 1991. A simple model of crop loss by weed competition from early observations on relative leaf area of the weeds. Weed Res. 31: 97–105.CrossRefGoogle Scholar
22. Légerè, 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
23. Marra, M. C. and Carlson, G. A. 1983. An economic threshold model for weeds in soybeans (Glycine max). Weed Sci. 31: 604–609.CrossRefGoogle Scholar
24. McLachlan, S. M., Swanton, C. J., Weise, S. F., and Tollenaar, M. 1993. Effect of corn-induced shading and temperature on rate of leaf appearance in redroot pigweed (Amaranthus retroflexus L.). Weed Sci. 41: 590–593.CrossRefGoogle Scholar
25. Moffitt, L. J. 1988. Incorporating environmental considerations in pest control advice for farmers. Am. J. Agric. Econ. 70: 628–634.CrossRefGoogle Scholar
26. Monks, D. W. and Oliver, L. R. 1988. Interactions between soybean (Glycine max) cultivars and selected weeds. Weed Sci. 36: 770–774.CrossRefGoogle Scholar
27. Moolani, M. K., Knake, E. L., and Slife, F. W. 1964. Competition of smooth pigweed with corn and soybean. Weeds 12: 126–128.CrossRefGoogle Scholar
28. Orwick, P. L. and Schreiber, M. M. 1979. Interference of redroot pigweed (Amaranthus retroflexus) and robust foxtail (Setaria viridis var. rohustaalba or var. robusta-purpurea) in soybeans (Glycine max). Weed Sci. 27: 665–674.Google Scholar
29. Pannell, D. J. 1990. An economic response model of herbicide application for weed control. Aus. J. Agric. Econ. 34: 223–241.Google Scholar
30. Pannell, D. J. 1990. Model of wheat yield response to application of diclofop-methyl to control ryegrass (Lolium rigidum). Crop Prot. 9: 422–28.CrossRefGoogle Scholar
31. Poston, D. H., Murdock, E. C., and Toler, J. E. 1992. Cost-efficient weed control in soybean (Glycine max) with cultivation and banded herbicide applications. Weed Technol. 6: 990–995.CrossRefGoogle Scholar
32. Shurtleff, J. L. and Coble, H. D. 1985. Interference of certain broadleaf weed species in soybeans (Glycine max). Weed Sci. 33: 654–657.CrossRefGoogle Scholar
33. Swanton, C. J. and Weise, S. F. 1991. Integrated weed management: the rationale and approach. Weed Technol. 5: 657–663.CrossRefGoogle Scholar
34. Swanton, C. J., Harker, K. N., and Anderson, R. L. 1993. Crop losses due to weeds in Canada. Weed Technol. 7: 537–542.CrossRefGoogle Scholar
35. Weaver, S. E. 1991. Size-dependent economic thresholds for three broadleaf weed species in soybeans. Weed Technol. 5: 674–679.CrossRefGoogle Scholar
36. Weaver, S. E. and McWilliams, E. L. 1980. The biology of Canadian weeds. 44. Amaranthus retroflexus L., A. powellii S. Wats. and A. hybridus L. Can. J. Plant Sci. 60: 1215–1234.CrossRefGoogle Scholar
37. Weersink, A., Deen, W., and Weaver, S. 1991. Defining and measuring economic threshold levels. Can. J. Agric. Econ. 39: 619–625.CrossRefGoogle Scholar
38. Weersink, A., Deen, W., and Weaver, S. 1992. Evaluation of alternative decision rules for postemergence herbicide treatments in soybeans. J. Prod. Agric. 5: 298–303.CrossRefGoogle Scholar
39. Wiles, L. J., Oliver, G. W., York, A. C., Gold, H. J., and Wilkerson, G. G. 1992. Spatial distribution of broadleaf weeds in North Carolina soybean (Glycine max) fields. Weed Sci. 40: 554–557.CrossRefGoogle Scholar
40. Wiles, L. J., Wilkerson, G. G., Gold, H. J., and Coble, H. D. 1992. Modeling weed distribution for improved postemergence control decisions. Weed Sci. 40: 546–553.CrossRefGoogle Scholar
41. Yelverton, F. H. and Coble, H. D. 1991. Narrow row spacing and canopy formation reduces weed resurgence in soybeans (Glycine max). Weed Technol. 5: 169–174.CrossRefGoogle Scholar
42. Zanin, G., Berti, A., and Toniolo, L. 1993. Estimation of economic thresholds for weed control in winter wheat. Weed Res. 33: 459–467.CrossRefGoogle Scholar