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Weed Management Practice Selection Among Midwest U.S. Organic Growers

Published online by Cambridge University Press:  20 January 2017

James J. DeDecker ,
John B. Masiunas ,
Adam S. Davis  and
Courtney G. Flint
James J. DeDecker*
Affiliation:
Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801
John B. Masiunas
Affiliation:
U.S. Department of Agriculture–Agricultural Research Service Global Change and Photosynthesis Research Unit, Urbana, IL
Adam S. Davis
Affiliation:
Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801
Courtney G. Flint
Affiliation:
Department of Natural Resources and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801
*
Corresponding author's E-mail: dedecke5@msu.edu
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Abstract

Organic agricultural systems increase the complexity of weed management, leading organic farmers to cite weeds as one of the greatest barriers to organic production. Integrated Weed Management (IWM) systems have been developed to address the ecological implications of weeds and weed management in cropping systems, but adoption is minimal. Organic agriculture offers a favorable context for application of IWM, as both approaches are motivated by concern for environmental quality and agricultural sustainability. However, adoption of IWM on organic farms is poorly understood due to limited data on weed management practices used, absence of an IWM adoption metric, and insufficient consideration given to the unique farming contexts within which weed management decisions are made. Therefore, this study aimed to (1) characterize organic weed management systems; (2) identify motivations for, and barriers to, selection of weed management practices; and (3) generate guiding principles for effective targeting of weed management outreach. We surveyed Midwestern organic growers to determine how specified psychosocial, demographic, and farm structure factors influence selection of weed management practices. Cluster analysis of the data detected three disparate, yet scaled, approaches to organic weed management. Clusters were distinguished by perspective regarding weeds and the number of weed management practices used. Categorization of individual farms within the identified approaches was influenced by primary farm products as well as farmer education, years farming, and information-seeking behavior. The proposed conceptual model allows weed management educators to target outreach for enhanced compatibility of farming contexts and weed management technologies.

Keywords

Cluster analysisdecision-makingintegrated weed managementlogistic regression analysis

Information

Type
Weed Management
Information
Weed Science , Volume 62 , Issue 3 , September 2014 , pp. 520 - 531
Copyright
Copyright © Weed Science Society of America 

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References

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