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Economic evaluation of a weed-activated sprayer for herbicide application to patchy weed populations


  • Bennett, Anne L.
  • Pannell, David J.


Spatial distribution of weeds in a crop is patchy. Traditional boom sprayers waste herbicide by applying it to areas where weed density is already low. A new technology, Weed Activated Spray Process (WASP), uses sensors to detect the presence of weeds and control spray nozzles accordingly. The economic benefits of this technology to extensive crop farmers in Western Australia are investigated using a model based on the economics of information. Existing technology is likely to reduce profits because the weed density at which it switches off spraying is too high. Even if sensitivity to low densities could be improved, likely benefits of pre‐crop usage would still be very low or negative.

Suggested Citation

  • Bennett, Anne L. & Pannell, David J., 1998. "Economic evaluation of a weed-activated sprayer for herbicide application to patchy weed populations," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 42(4), pages 1-20.
  • Handle: RePEc:ags:aareaj:117284
    DOI: 10.22004/ag.econ.117284

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    References listed on IDEAS

    1. Russell J. Gorddard & David J. Pannell & Greg Hertzler, 1995. "An Optimal Control Model For Integrated Weed Management Under Herbicide Resistance," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 39(1), pages 71-87, April.
    2. David J. Pannell, 1997. "Sensitivity analysis of normative economic models: theoretical framework and practical strategies," Agricultural Economics, International Association of Agricultural Economists, vol. 16(2), pages 139-152, May.
    3. David J. Pannell, 1990. "An Economic Response Model Of Herbicide Application For Weed Control," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 34(3), pages 223-241, December.
    4. D. J. Pannell, 1991. "Responses To Risk In Weed Control Decisions Under Expected Profit Maximisation: Reply," Journal of Agricultural Economics, Wiley Blackwell, vol. 42(3), pages 407-408, September.
    5. Anderson, Jock R. & Dillon, John L. & Hardaker, Brian, 1977. "Agricultural Decision Analysis," Monographs: Applied Economics, AgEcon Search, number 288652, September.
    6. Pannell, David J., 1994. "The Value Of Information In Herbicide Decision Making For Weed Control In Australian Wheat Crops," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 19(2), pages 1-16, December.
    7. Anderson, Jock R. & Feder, Gershon, 2007. "Agricultural Extension," Handbook of Agricultural Economics, in: Robert Evenson & Prabhu Pingali (ed.),Handbook of Agricultural Economics, edition 1, volume 3, chapter 44, pages 2343-2378, Elsevier.
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    Cited by:

    1. Swinton, Scott M. & Day, Esther, 2000. "Economics In The Design, Assessment, Adoption, And Policy Analysis Of I.P.M," Staff Paper Series 11789, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    2. Marra, Michele & Pannell, David J. & Abadi Ghadim, Amir, 2003. "The economics of risk, uncertainty and learning in the adoption of new agricultural technologies: where are we on the learning curve?," Agricultural Systems, Elsevier, vol. 75(2-3), pages 215-234.
    3. Mooney, Daniel F. & Larson, James & Roberts, Roland & English, Burton, 2009. "When Does Variable Rate Technology for Agricultural Sprayers Pay? A Case Study for Cotton Production in Tennessee," Journal of the ASFMRA, American Society of Farm Managers and Rural Appraisers, vol. 2009, pages 1-11.
    4. Mooney, Daniel F. & Larson, James A. & Roberts, Roland K. & English, Burton C., 2009. "Economics of the Variable Rate Technology Investment Decision for Agricultural Sprayers," 2009 Annual Meeting, January 31-February 3, 2009, Atlanta, Georgia 46860, Southern Agricultural Economics Association.

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