IDEAS home Printed from https://ideas.repec.org/a/eee/agisys/v142y2016icp33-40.html
   My bibliography  Save this article

The Harrington Seed Destructor: Its role and value in farming systems facing the challenge of herbicide-resistant weeds

Author

Listed:
  • Jacobs, A.
  • Kingwell, R.

Abstract

Herbicide-resistant weeds are an increasing global problem in crop production systems. To lessen the incidence of herbicide resistance and to prevent the spread of herbicide-resistant weeds many farmers in Australia have adopted weed seed control measures at grain harvest. One new option is known as the Harrington Seed Destructor (HSD). It is a machine that intercepts crop residue from the harvester and then mechanically destroys embedded weed seeds. In this study, the RIM (Ryegrass Integrated Management) model was used to investigate the economic worth of the HSD within integrated weed management strategies applicable to different weed environments, rotations, sizes of cropping programmes and crop yields. Use of the HSD generated increased returns compared to many other weed management strategies in several scenarios, but especially when non-selective herbicide resistance occurred and large areas of high-yielding crops were grown. Emerging trends in grain farming that include larger areas sown to crops, a greater incidence of herbicide-resistant weeds and higher crop yields, when combined with further manufacturing improvement of the HSD, will only further favour the use of the HSD as a key component of integrated weed management.

Suggested Citation

  • Jacobs, A. & Kingwell, R., 2016. "The Harrington Seed Destructor: Its role and value in farming systems facing the challenge of herbicide-resistant weeds," Agricultural Systems, Elsevier, vol. 142(C), pages 33-40.
  • Handle: RePEc:eee:agisys:v:142:y:2016:i:c:p:33-40
    DOI: 10.1016/j.agsy.2015.11.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308521X15300433
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. Graeme J. Doole & David J. Pannell & Clinton K. Revell, 2009. "Economic contribution of French serradella (Ornithopus sativus Brot.) pasture to integrated weed management in Western Australian mixed-farming systems: an application of compressed annealing ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 53(2), pages 193-212, April.
    3. David J. Pannell, 2006. "Flat Earth Economics: The Far-reaching Consequences of Flat Payoff Functions in Economic Decision Making," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 28(4), pages 553-566.
    4. Pannell, David J. & Stewart, Vanessa & Bennett, Anne & Monjardino, Marta & Schmidt, Carmel & Powles, Stephen B., 2004. "RIM: a bioeconomic model for integrated weed management of Lolium rigidum in Western Australia," Agricultural Systems, Elsevier, vol. 79(3), pages 305-325, March.
    5. Randall Jones & Oscar Cacho & Jack Sinden, 2006. "The importance of seasonal variability and tactical responses to risk on estimating the economic benefits of integrated weed management," Agricultural Economics, International Association of Agricultural Economists, vol. 35(3), pages 245-256, November.
    6. Graeme J. Doole & David J. Pannell, 2008. "Optimisation of a Large, Constrained Simulation Model using Compressed Annealing," Journal of Agricultural Economics, Wiley Blackwell, vol. 59(1), pages 188-206, February.
    7. Schmidt, Carmel P & Pannell, David J, 1996. "Economic Issues in Management of Herbicide-Resistant Weeds," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 64(03), pages 1-8, December.
    8. Livingston, Michael & Fernandez-Cornejo, Jorge & Unger, Jesse & Osteen, Craig & Schimmelpfennig, David & Park, Tim & Lambert, Dayton, 2015. "The Economics of Glyphosate Resistance Management in Corn and Soybean Production," Economic Research Report 205083, United States Department of Agriculture, Economic Research Service.
    Full references (including those not matched with items on IDEAS)

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agisys:v:142:y:2016:i:c:p:33-40. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Haili He). General contact details of provider: http://www.elsevier.com/locate/agsy .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.