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Optimising nitrogen fertiliser in high yielding irrigated cotton: A benefit-cost analysis and the feasibility of participation in the ERF

Author

Listed:
  • Welsh, Jon
  • Powell, Janine
  • Scott, Fiona

Abstract

Maximising nutrient use efficiency and minimising emissions of the powerful greenhouse gas nitrous oxide, could enable Australian producers of high yielding irrigated cotton to participate in the Emissions Reduction Fund. This paper reviews nitrogen (N) use in the cotton industry in Australia to date and the challenges of achieving optimal N use in commercial growing practices. The study quantifies both the social and economic parameters in a benefit-cost analysis using two scenarios: an optimal use of N fertiliser and an overuse of N fertiliser in irrigated cotton production. Results of sensitivity analysis for social and economic costs have implications for policy makers focusing on improved N management and an industry supplying an increasingly environmentally aware global market. The study also contains preliminary modelling using industry research of a cotton-N emissions abatement project under the Australian Government’s Emissions Reduction Fund.

Suggested Citation

  • Welsh, Jon & Powell, Janine & Scott, Fiona, 2015. "Optimising nitrogen fertiliser in high yielding irrigated cotton: A benefit-cost analysis and the feasibility of participation in the ERF," AFBM Journal, Australasian Farm Business Management Network, vol. 12, December.
    • Handle: RePEc:ags:afbmau:284944
    DOI: 10.22004/ag.econ.284944
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    Cited by:

    1. Rathnayake, Chinthani & Malcolm, Bill & Griffith, Garry & Sinnett, Alex & Deane, Paul, 2023. "Using Nitrogen Fertilizer to Grow Irrigated Cotton in Australia: Marginal Benefits and Costs of Nitrogen and Nitrous Oxide Emissions," AFBM Journal, Australasian Farm Business Management Network, vol. 20(4), October.
    2. Powell, J.W. & Welsh, J.M. & Eckard, R.J., 2017. "An irrigated cotton farm emissions case study in NSW, Australia," Agricultural Systems, Elsevier, vol. 158(C), pages 61-67.
    3. Leo, Stephen & De Antoni Migliorati, Massimiliano & Nguyen, Trung H. & Grace, Peter R., 2023. "Combining remote sensing-derived management zones and an auto-calibrated crop simulation model to determine optimal nitrogen fertilizer rates," Agricultural Systems, Elsevier, vol. 205(C).

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