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Optimal Weed Control Strategies in Rice Production under Dynamic and Static Decision Rules in South Korea

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  • Woongchan Jeon

    (Department of Agricultural Economics and Rural Development, Seoul National University, Seoul 08826, Republic of Korea)

  • Kwansoo Kim

    (Department of Agricultural Economics and Rural Development, Seoul National University, Seoul 08826, Republic of Korea
    Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea)

Abstract

This paper analyzes optimal weed control management strategies under static and dynamic decision rules. Seed bank is taken into account to introduce dynamics into the model. We present a numerical example of controlling Sheathed Monochoria ( Monochoria Vaginalis ) in Korean rice paddy fields. Our results show that producers benefit from dynamic decision rules; higher income and more control of weed density can be obtained with the same amount of herbicide. In order to illustrate the magnitude of differences between static and dynamic models, a numerical example is presented using a data set from Korean rice production. When it comes to controlling weed density, Korean rice farmers are found to be better off under the dynamic model, and the magnitude of advantages are found to be more sensitive to herbicide efficacy and less sensitive to initial seed banks and germination rates in terms of weed density.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:6:p:956-:d:101271
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    References listed on IDEAS

    as
    1. David J. Pannell, 1991. "Pests and pesticides, risk and risk aversion," Agricultural Economics, International Association of Agricultural Economists, vol. 5(4), pages 361-383, August.
    2. Gershon Feder, 1979. "Pesticides, Information, and Pest Management under Uncertainty," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 61(1), pages 97-103.
    3. 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.
    4. Odom, Doreen I. S. & Cacho, Oscar J. & Sinden, J. A. & Griffith, Garry R., 2003. "Policies for the management of weeds in natural ecosystems: the case of scotch broom (Cytisus scoparius, L.) in an Australian national park," Ecological Economics, Elsevier, vol. 44(1), pages 119-135, February.
    5. Scott M. Swinton & Robert P. King, 1994. "The Value of Pest Information in a Dynamic Setting: The Case of Weed Control," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 76(1), pages 36-46.
    6. Wu, JunJie, 2001. "Optimal weed control under static and dynamic decision rules," Agricultural Economics, Blackwell, vol. 25(1), pages 119-130, June.
    7. Pandey, Sushil & Medd, R. W., 1991. "A stochastic dynamic programming framework for weed control decision making: an application to Avena fatua L," Agricultural Economics, Blackwell, vol. 6(2), pages 115-128, December.
    8. Carlson, Gerald A., 1984. "Risk Reducing Inputs Related to Agricultural Pests," Regional Research Projects >1984: S-180 Annual Meeting, March 25-28, 1984, New Orleans, Louisiana 307236, Regional Research Projects > S-180: An Economic Analysis of Risk Management Strategies for Agricultural Production Firms.
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