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A Comparison of Reduced Rate and Economic Threshold Approaches to Weed Management in a Corn–Soybean Rotation

Published online by Cambridge University Press:  20 January 2017

Peter Sikkema ,
Laura L. Van Eerd ,
Richard J. Vyn  and
Susan Weaver
Peter Sikkema
Affiliation:
University of Guelph Ridgetown Campus, Ridgetown, ON, N0P 2C0, Canada
Laura L. Van Eerd
Affiliation:
University of Guelph Ridgetown Campus, Ridgetown, ON, N0P 2C0, Canada
Richard J. Vyn
Affiliation:
University of Guelph Ridgetown Campus, Ridgetown, ON, N0P 2C0, Canada
Susan Weaver*
Affiliation:
Agriculture and Agri-Food Canada, Greenhouse and Processing Crops Research Centre, Harrow, ON, N0R 1G0, Canada
*
Corresponding author's E-mail: weavers@agr.gc.ca
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Abstract

A field study was conducted at two sites in southwestern Ontario, Canada, from 2002 to 2005 to assess the cumulative effects of different weed management strategies applied to the same plots over time in a corn–soybean rotation. These strategies included a POST broad-spectrum herbicide applied at recommended or reduced rates and use of a computer decision aid to select the POST herbicide having the greatest net return (economic threshold approach) based on weed populations before treatment or seed-bank estimates. Four years after study initiation, increased weed populations were observed only in the nontreated control. The reduced rate and economic threshold approaches did not lead to increased weed seed banks compared with the recommended rate of a broad-spectrum herbicide. Reductions in herbicide rate were more effective than the use of economic thresholds for reducing the risk of environmental impact in corn and soybeans. Weed populations in this study were generally above threshold levels, and herbicides selected by the computer decision aid tended to be older, less-expensive herbicides with high use rates. Recommendations by the computer decision aid were generally more effective and more profitable when based on weed populations before treatment than when based on seed-bank estimates.

Keywords

Corn, Zea mays L, soybean, Glycine max (L.) MerrDecision support systemeconomic thresholdenvironmental impact quotientHADSS™net returnseed bank
Type
Research
Information
Weed Technology , Volume 21 , Issue 3 , September 2007 , pp. 647 - 655
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Anonymous 2006. Guide to Weed Control. Ontario, Canada Ministry of Agriculture, Food and Rural Affairs Publ. 75. 395.Google Scholar
Bennett, A. C., Price, A. J., Sturgill, M. C., Buol, G. S., and Wilkerson, G. G. 2003. HADSS™, Pocket Herb™, and WebHADSS™: decision aids for field crops. Weed Technol. 17:412–420.Google Scholar
Blackshaw, R. E., Beckie, H. J., Molnar, L. J., Entz, T., and Moyer, J. R. 2005. Combining agronomic practices and herbicides improves weed management in wheat–canola rotations within zero-tillage production systems. Weed Sci. 53:528–535.Google Scholar
Blackshaw, R. E., O'Donovan, J. T., Harker, K. N., Clayton, G. W., and Stougaard, R. N. 2006. Reduced herbicide doses in field crops: a review. Weed Biol. Manag. 6:10–17.Google Scholar
Boström, U. and Fogelfors, H. 2002. Long-term effects of herbicide-application strategies on weeds and yield in spring-sown cereals. Weed Sci. 50:196–203.Google Scholar
Brimner, T. A., Gallivan, G. J., and Stephenson, G. R. 2005. Influence of herbicide-resistant canola on the environmental impact of weed management. Pest Manag. Sci. 61:47–52.Google Scholar
Bues, R., Dadomo, M., Lyannaz, J. P., Di Lucca, G., Macua Gonzalez, J. I., Prieto Losada, H., and Dumas, Y. 2003. Evaluation of the environmental impact of the pesticides applied in processing tomato cropping. Acta Hortic. 613:255–258.CrossRefGoogle Scholar
De Jong, F. M. W. and De Snoo, G. R. 2002. A comparison of the environmental impact of pesticide use in integrated and conventional potato cultivation in The Netherlands. Agric. Ecosyst. Environ. 91:5–13.Google Scholar
Doyle, P. and Stypa, M. 2004. Reduced herbicide rates—a Canadian perspective. Weed Technol. 18:1157–1165.Google Scholar
Dushoff, J., Caldwell, B., and Mohler, C. L. 1994. Evaluating the environmental effect of pesticides: A critique of the environmental impact quotient. Am. Entomol. 3:180–184.Google Scholar
Edwards-Jones, G. and Howells, O. 2001. The origin and hazard of inputs to crop protection in organic farming systems: are they sustainable? Agric. Syst. 67:31–47.Google Scholar
Fernandez-Cornejo, J. 1998. Environmental and economic consequences adoption: IPM in viticulture. Agric. Econ. 18:145–155.Google Scholar
Forcella, F., King, R. P., Swinton, S. M., Buhler, D. B., and Gunsolus, J. L. 1996. Multi-year validation of a decision aid for integrated weed management in row crops. Weed Sci. 44:650–661.Google Scholar
Gallivan, G. J., Surgeoner, G. A., and Kovach, J. 2001. Pesticide risk reduction on crops in the province of Ontario. J. Environ. Qual. 30:798–813.CrossRefGoogle ScholarPubMed
Hamill, A. S., Weaver, S. E., Sikkema, P. H., Swanton, C. J., Tardif, F. J., and Ferguson, G. M. 2004. Benefits and risks of economic vs. efficacious approaches to weed management in corn and soybean. Weed Technol. 18:723–732.Google Scholar
Hoffman, M. L., Buhler, D. D., and Owen, M. D. K. 1999. Weed population and crop yield response to recommendations from a weed control decision aid. Agron. J. 91:386–392.Google Scholar
Kovach, J., Petzoldt, C., Degni, J., and Tette, J. 1992. A method to measure the environmental impact of pesticides. N. Y. Food Life Sci. Bull. 139:139–146.Google Scholar
Kovach, J., Petzoldt, C., Degni, J., and Tette, J. 1999. A Method to Measure the Environmental Impact of Pesticides. Table 2. List of Pesticides. 7 p. http://www.nysipm.cornell.edu/publications/eiq/. Accessed: July 13, 2006.Google Scholar
Nzarko, O. M., Van Acker, R. C., and Entz, M. H. 2005. Strategies and tactics for herbicide use reduction in field crops in Canada: a review. Can. J. Plant Sci. 85:457–479.Google Scholar
O'Donovan, J. T., Harker, K. N., Blackshaw, R. E., and Stougaard, R. N. 2003a. Effect of variable tralkoxydim rates on wild oat (Avena fatua) seed production, wheat (Triticum aestivum) yield, and economic return. Weed Technol. 17:149–156.Google Scholar
O'Donovan, J. T., Harker, K. N., Blackshaw, R. E., and Stougaard, R. N. 2003b. Influence of variable rates of imazamethabenz and difenzoquat on wild oat (Avena fatua) seed production, and wheat (Triticum aestivum) yield and profitability. Can. J. Plant Sci. 83:977–985.Google Scholar
O'Donovan, J. T., Newman, J. C., Harker, K. N., and Clayton, G. W. 2004. Crop seeding rate influences the performance of variable herbicide rates in a canola–barley–canola rotation. Weed Technol. 18:733–741.Google Scholar
Renner, K. A., Swinton, S. M., and Kells, J. J. 1999. Adaptation and evaluation of the WEEDSIM weed management model for Michigan. Weed Sci. 47:338–348.Google Scholar
Sanchez-Bayo, F., Baskaran, S., and Kennedy, I. R. 2002. Ecological relative risk (EcoRR): another approach for risk assessment of pesticides in agriculture. Agric. Ecosyst. Environ. 91:37–57.Google Scholar
SAS 1999. SAS/STAT User's Guide, Version 8. Cary, NC SAS Institute. 3884.Google Scholar
Swanton, C. J., Shrestha, A., Clements, D. R., Booth, B. D., and Chandler, K. 2002. Evaluation of alternative weed management systems in a modified no-till corn–soybean–winter wheat rotation: weed densities, crop yield, and economics. Weed Sci. 50:504–511.Google Scholar
Upadhyah, B. M., Smith, E. G., Clayton, G. W., Harker, K. N., and Blackshaw, R. E. 2006. Economics of integrated weed management in herbicide-resistant canola. Weed Sci. 54:138–147.Google Scholar
van der Werf, H. M. G. and Zimmer, C. 1998. An indicator of pesticide environmental impact based on a fuzzy expert system. Chemosphere 36:2225–2249.Google Scholar
Vencill, W. K. 2002. Thifensulfuron. in. WSSA Herbicide Handbook. 8th ed. Lawrence, KS Weed Science Society of America. 421–422.Google Scholar
Vogue, P. A., Kerle, E. A., and Jenkins, J. J. 1994. Extension Pesticides Properties Database. http://ace.orst.edu/info/npic/ppdmove.htm. Accessed: July 13, 2006.Google Scholar
Williams, B. J. and Harvey, R. G. 2002. Influence of simulated seed rain on the seed bank of wild proso millet. Weed Sci. 50:340–343.Google Scholar
Zhang, J., Hamill, A. S., Gardiner, I. O., and Weaver, S. E. 1998. Dependence of weed flora on the active soil seedbank. Weed Res. 38:143–152.Google Scholar
Zhang, J., Weaver, S., and Hamill, A. 2000. Risks and reliability of using herbicides at below-labeled rates. Weed Technol. 14:106–115.Google Scholar
Ziegler, C. R., Donahue, D. W., Drummond, F. A., and Smith, S. N. 2002. The ecological economics of insecticide use associated with the Maine potato industry based on a producer survey. Am. J. Altern. Agric. 17:159–166.Google Scholar