IDEAS home Printed from https://ideas.repec.org/a/bla/agecon/v6y1991i2p115-128.html
   My bibliography  Save this article

A stochastic dynamic programming framework for weed control decision making: an application to Avena fatua L

Author

Listed:
  • Sushil Pandey
  • R.W. Medd

Abstract

This paper develops a stochastic multi‐period decision model to analyse a continuous wheat cropping system infested by wild oats (Avena fatua L.), in southern Australia. The multi‐period solutions is obtained by employing a dynamic programming model in conjunction with a bioeconomic simulation model. An empirically estimated dose response function is used to derive the optimal herbicide rate. Uncertainties due to environmental effects on the performance of herbicide and crop yields are modelled and optimal decision rules derived. The results indicate that substantial economic gains can be realised if herbicide dose decisions are taken by considering future profit effects of current decisions, as opposed to the more common approach of only considering the current‐period effect.

Suggested Citation

  • Sushil Pandey & R.W. Medd, 1991. "A stochastic dynamic programming framework for weed control decision making: an application to Avena fatua L," Agricultural Economics, International Association of Agricultural Economists, vol. 6(2), pages 115-128, December.
    • Handle: RePEc:bla:agecon:v:6:y:1991:i:2:p:115-128
    DOI: 10.1111/j.1574-0862.1991.tb00175.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1574-0862.1991.tb00175.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1574-0862.1991.tb00175.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jones, Randall E. & Cacho, Oscar J. & Sinden, Jack A., 2003. "Modelling the Dynamics of Weed Management Technologies," 2003 Conference (47th), February 12-14, 2003, Fremantle, Australia 57902, Australian Agricultural and Resource Economics Society.
    2. Pandey, Sushil & Hardaker, J. Brian, 1995. "The role of modelling in the quest for sustainable farming systems," Agricultural Systems, Elsevier, vol. 47(4), pages 439-450.
    3. Woongchan Jeon & Kwansoo Kim, 2017. "Optimal Weed Control Strategies in Rice Production under Dynamic and Static Decision Rules in South Korea," Sustainability, MDPI, vol. 9(6), pages 1-11, June.
    4. Chalak-Haghighi, Morteza & Ruijs, Arjan & van Ierland, Ekko C., 2009. "Biological control of invasive plant species: stochastic economic analysis," 2009 Conference (53rd), February 11-13, 2009, Cairns, Australia 48153, Australian Agricultural and Resource Economics Society.
    5. Wu, JunJie, 2001. "Optimal weed control under static and dynamic decision rules," Agricultural Economics, Blackwell, vol. 25(1), pages 119-130, June.
    6. Rohan Jayasuriya & Randall Jones & Remy Ven, 2011. "A bioeconomic model for determining the optimal response strategies for a new weed incursion," Journal of Bioeconomics, Springer, vol. 13(1), pages 45-72, April.
    7. Robert, Marion & Thomas, Alban & Bergez, Jacques Eric, 2016. "Processes of adpatation in farm decision-making models. A review," TSE Working Papers 16-731, Toulouse School of Economics (TSE).
    8. Jayasuriya, Rohan T. & Jones, Randall E., 2008. "A bioeconomic model for determining the optimal response to a new weed incursion in Australian cropping systems," 2008 Conference (52nd), February 5-8, 2008, Canberra, Australia 6015, Australian Agricultural and Resource Economics Society.
    9. Finnoff, David & Tschirhart, John, 2005. "Identifying, preventing and controlling invasive plant species using their physiological traits," Ecological Economics, Elsevier, vol. 52(3), pages 397-416, February.
    10. repec:ags:aare05:137931 is not listed on IDEAS
    11. Wallinga, Jacco, 1998. "Analysis of the rational long-term herbicide use: Evidence for herbicide efficacy and critical weed kill rate as key factors," Agricultural Systems, Elsevier, vol. 56(3), pages 323-340, March.
    12. Jones, Randall E., 2005. "Sustainability and integrated weed management in Australian winter cropping systems: a bioeconomic analysis," 2005 Conference (49th), February 9-11, 2005, Coff's Harbour, Australia 137930, Australian Agricultural and Resource Economics Society.

    More about this item

    Statistics

    Access and download statistics

    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:bla:agecon:v:6:y:1991:i:2:p:115-128. See general information about how to correct material in RePEc.

    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.

    We have no bibliographic references for this item. You can help adding them by using 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/iaaeeea.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.