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Adoption of Integrated Pest Management Tactics by Wisconsin Farmers

Published online by Cambridge University Press:  20 January 2017

Clarissa M. Hammond ,
Edward C. Luschei ,
Chris M. Boerboom  and
Pete J. Nowak
Clarissa M. Hammond
Affiliation:
Department of Agronomy, University of Wisconsin–Madison, 1575 Linden Drive, Madison, WI 53706
Edward C. Luschei*
Affiliation:
Department of Agronomy, University of Wisconsin–Madison, 1575 Linden Drive, Madison, WI 53706
Chris M. Boerboom
Affiliation:
Department of Agronomy, University of Wisconsin–Madison, 1575 Linden Drive, Madison, WI 53706
Pete J. Nowak
Affiliation:
Department of Rural Sociology, Gaylord Nelson Institute for Environmental Studies, University of Wisconsin– Madison, 1450 Linden Drive, Madison, WI 53706
*
Corresponding author's E-mail: ecluschei@wisc.edu
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Abstract

Agronomic research and extension personnel generally recognize the benefits of integrated pest management (IPM) but IPM practices have not been rapidly adopted by farmers. In order for applied research and extension programs to be as influential as possible, strategies and tactics must be evaluated in the context of the real-world constraints experienced by farmers. We investigated the linkage between farmers' pest management behaviors, attitudes, and constraints by analyzing an extensive corn pest management survey distributed throughout Wisconsin in 2002. Our objectives were to (1) create a benchmark against which future changes in pest management practices could be detected and (2) explore potential associations between practices and farm characteristics, e.g., farm size or commodity produced. A total of 213 farmers responded with descriptions of their operations; weed, insect, and disease pest management practices; crop consultant usage; interactions with their local agrichemical dealer; and attitudes regarding pest management decision-making. We compared the relative responses of cash-grain and dairy farmers as well as managers of large and small farms. Larger farm size and percentage of operation in cash-grain production were associated with an increased frequency of rotating crops, rotating herbicide families, and use of a broadcast herbicide application. Managers of large farms and/or cash-grain crops also more frequently indicated considering the level of pest control, price, carryover potential, weed resistance management, environmental safety, and risk to the applicator than did dairy or small-sized operations. Cash-grain farmers had significantly higher scores on a calculated IPM index than did dairy farmers (P < 0.0001). We also found a significant positive relationship between farm size and IPM score (P < 0.0001). Our results provide a benchmark for future comparisons of IPM adoption rates in Wisconsin and highlight the association between IPM research/extension and farmers' management behavior.

Keywords

cornZea mays L.Integrated weed managementsurveyCPMS, corn pest management surveyHRC, herbicide-resistant cropsMP, most productiveUSDA, United States Department of Agriculture
Type
Research Article
Information
Weed Technology , Volume 20 , Issue 3 , September 2006 , pp. 756 - 767
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Agresti, A. 2002. Categorical Data Analysis. 2nd ed. Hoboken, NJ: J. Wiley. Pp. 1–114.Google Scholar
Boerngen, M. A. and Bullock, D. S. 2003. Farmers' time investment in human capital: a comparison between conventional and reduced-chemical growers. Renew. Agr. Food Syst. 19:100–109.Google Scholar
Browner, C. M., Rominger, R., and Kessler, D. A. 1993. Testimony before U.S. House Subcommittee on Department of Operations and Nutrition, Committee on Agriculture, September 22, 1993. Washington, DC.Google Scholar
Buhler, D. D., Liebman, M., and Obrycki, J. J. 2000. Theoretical and practical challenges to an IPM approach to weed management. Weed Sci. 48:274–280.Google Scholar
Busck, A. G. 2002. Farmers' landscape decisions: relationships between farmers' values and landscape practices. Soc. Ruralis. 42:233–249.Google Scholar
Czapar, G. F., Curry, M. P., and Gray, M. E. 1995. Survey on integrated pest management practices in Central Illinois. J. Prod. Agric. 8:483–486.Google Scholar
Czapar, G. F., Curry, M. P., and Wax, L. M. 1997. Grower acceptance of economic thresholds for weed management in Illinois. Weed Technol. 11:828–831.CrossRefGoogle Scholar
Dhaliwal, G. S., Koul, O., and Arora, R. 2004. Integrated pest management: retrospect and prospect. Pages 1–20 in Koul, O., Dhaliwal, G. S., and Cuperus, G. W. eds. Integrated Pest Management: Potential, Constraints and Challenges. Cambridge, MA: CAB International.Google Scholar
D'Souza, G. and Ikerd, J. 1996. Small farms and sustainable development: is small more sustainable? J. Agr. Appl. Econ. 28:73–83.Google Scholar
Fishbein, M. and Ajzen, I. 1975. Belief, attitude, intention, and behavior: an introduction to theory and research. Cambridge, MA: Addison-Wesley Publishing Company. 578 p.Google Scholar
Forte-Gardner, O., Young, F. L., Dillman, D. A., and Carroll, M. S. 2004. Increasing the effectiveness of technology transfer for conservation cropping systems through research and field design. Renew. Agr. Food Syst. 19:199–209.CrossRefGoogle Scholar
Greene, A. and Breisch, N. L. 2002. Measuring integrated pest management programs for public buildings. J. Econ. Entomol. 95:1–13.Google Scholar
Hollingsworth, C. S. and Coli, W. M. 2001. IPM adoption in northeastern U.S.: an examination of the IPM continuum. Am. J. Alternative Agr. 16:177–183.CrossRefGoogle Scholar
Jackson-Smith, D. B. and Buttel, F. H. 2003. Social and ecological dimensions of the alternative–conventional agricultural paradigm scale. Rural Soc. 68:513–530.CrossRefGoogle Scholar
Jacobsen, B. J. 1997. Role of plant pathology in integrated pest management. Ann. Rev. Phytopath. 35:373–391.CrossRefGoogle ScholarPubMed
Kessler, D. A. 1993. Testimony before U.S. House Subcommittee on Department of Operations and Nutrition, Committee on Agriculture, September 22, 1993. Washington, DC.Google Scholar
Luschei, E. C. and Jackson, R. D. 2005. Research methodologies and statistical approaches for multitactic systems. Weed Sci. 53:393–403.Google Scholar
Luschei, E. C., Van Wychen, L., Maxwell, B., Bussan, A., Buschena, D., and Goodman, D. 2001. Implementing and conducting on-farm weed research with the use of GPS. Weed Sci. 49:536–542.Google Scholar
Lyson, T. A. and Welsh, R. 1993. The production function, crop diversity, and the debate between conventional and sustainable agriculture. Rural Soc. 58:424–439.CrossRefGoogle Scholar
Malone, S., Herbert, D. A. Jr., and Pheasant, S. 2004. Determining adoption of integrated pest management practices by grains farmers in Virginia. J. Exten. 42:4.Google Scholar
Owen, M. D. K. 1998. Producer attitudes and weed management. in Hatfield, J. L., Buhler, D. D., and Stewart, B. A., eds. Integrated Weed Management. Chelsea, MI: Ann Arbor Press. Pp. 43–59.Google Scholar
Proost, R. T., Jensen, B. M., Heider, D. J., and Boerboom, C. M. 2002. Using a self assessment tool to promote and educate integrated pest management to farmers. North Central Weed Sci. Soc. Abstr. 57. [CD-ROM computer file]. Champaign, IL: North Central Weed Sci. Soc. December 2002.Google Scholar
[SAS] Statistical Analysis Systems. 2003. SAS 9.1.3 Help and Documentation, Cary, NC: SAS Institute Inc. Google Scholar
Smith, R. F. and van den Bosch, R. 1967. Integrated control. in Kilgore, W. and Doutt, R., eds. Pest Control: Biological, Physical, and Selected Chemical Methods. New York: Academic. Pp. 295–340.Google Scholar
Stern, V. M., Smith, R. F., van den Bosch, R., and Hagen, K. S. 1959. The integrated control concept. Hilgardia 29:81–101.Google Scholar
Stokes, M. E., Davis, C. S., and Koch, G. G. 2000. Categorical data analysis using the SAS® system. 2nd edition. Cary, NC: Statistical Analysis Systems Institute. 648 p.Google Scholar
Tavernier, E. M. and Tolomeo, V. 2004. Farm typology and sustainable agriculture: does size matter? J. Sustain. Agr. 24:33–46.Google Scholar
Upadhyay, B. M., Young, D. L., Wang, H. H., and Wandschneider, P. 2003. How do farmers who adopt multiple conservation practices differ from their neighbors? Am. J. Alternative Agr. 18:27–36.Google Scholar
USDA. 1998. Pest management practices: 1997 summary. SpCr 1(98). Washington, DC: USDA, National Agricultural Statistics Service, Agricultural Statistics Board.Google Scholar
USDA. 2002. 2002 Census of Agriculture. Washington, DC: USDA, National Agricultural Statistics Service, Agricultural Statistics Board. http://www.nass.usda.gov/Data_and_Statistics/.Google Scholar
Wallace, A. 1994. Evolution of the low income per acre—large number of acres per farm—highly mechanized—monoculture—not too sustainable agriculture. Commun. Soil Sci. Plant Anal. 25:61–66.CrossRefGoogle Scholar
Warland, R. H. and Sample, J. 1973. Response certainty as a moderator variable in attitude measurement. Rural Soc. 38:174–186.Google Scholar
Wilson, C. and Tisdell, C. 2001. Why farmers continue to use pesticides despite environmental, health and sustainability costs. Ecol. Econ. 39:449–462.Google Scholar