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Use of available information at a European level to construct crop nitrogen response curves for the regions of the EU

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  • Godard, C.
  • Roger-Estrade, J.
  • Jayet, P.A.
  • Brisson, N.
  • Le Bas, C.
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    Abstract

    Nowadays European agriculture is evolving in a context where policy-making and environmental concerns play a key role. To better assess agro-environmental policies, the AROPAj agricultural supply model needs to take into account the technical characteristics of crop management for different farms. A method to build up specific relationships between yield and nitrogen fertilization that takes into account agronomic techniques is proposed in this paper. The nitrogen response curve is based on an exponential function that integrates economic properties consistently from an agronomic point of view. In AROPAj, individual production systems (farm types) do not have a given location within a specified region and in databases technical information is scarce. The method involves determining technical and physical characteristics, inputs that allow the STICS crop model to assess the yield response to nitrogen of each crop on every farm type. From this information, a nitrogen response curve can be drawn up for each crop of each one of the farms. It can take into account both nitrogen from purchased fertilizer and nitrogen from animal effluents produced on farm. The method was designed to be adaptable to any European region, and tests carried out on two French regions covering a wide range of situations (crops, soils, climates and techniques) showed it was able to cope with varying prices and environments. The agronomic consistency of STICS inputs and curve shapes was also checked. When incorporated into the AROPAj economic model, the response curves can be used to render farms more sensitive to agricultural policy scenarios, by allowing their optimal fertilization level to be adjusted.

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    Bibliographic Info

    Article provided by Elsevier in its journal Agricultural Systems.

    Volume (Year): 97 (2008)
    Issue (Month): 1-2 (April)
    Pages: 68-82

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    Handle: RePEc:eee:agisys:v:97:y:2008:i:1-2:p:68-82

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    Web page: http://www.elsevier.com/locate/agsy

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    References

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    1. Janssen, Sander & van Ittersum, Martin K., 2007. "Assessing farm innovations and responses to policies: A review of bio-economic farm models," Agricultural Systems, Elsevier, Elsevier, vol. 94(3), pages 622-636, June.
    2. Bouman, B. A. M. & van Keulen, H. & van Laar, H. H. & Rabbinge, R., 1996. "The `School of de Wit' crop growth simulation models: A pedigree and historical overview," Agricultural Systems, Elsevier, Elsevier, vol. 52(2-3), pages 171-198.
    3. De Cara & Jayet, 2000. "Emissions of greenhouse gases from agriculture : the heterogeneity of abatement costs in France," Working Papers 156214, Institut National de la Recherche Agronomique, France.
    4. Arfini, Filippo, 2001. "Mathematical Programming Models Employed In The Analysis Of The Common Agriculture Policy," Working Papers, National Institute of Agricultural Economics, Italy INEA, Osservatorio Sulle Politiche Agricole dell'UE 14803, National Institute of Agricultural Economics, Italy INEA, Osservatorio Sulle Politiche Agricole dell'UE.
    5. Stéphane Cara & Martin Houzé & Pierre-Alain Jayet, 2005. "Methane and Nitrous Oxide Emissions from Agriculture in the EU: A Spatial Assessment of Sources and Abatement Costs," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 32(4), pages 551-583, December.
    6. Marsden, James R & Pingry, David E, 1986. "Engineering Production Functions and the Testing of Quantitative Economic Hypotheses," Economica, London School of Economics and Political Science, London School of Economics and Political Science, vol. 53(212), pages 533-34, November.
    7. Donaldson, A. B. & Flichman, G. & Webster, J. P. G., 1995. "Integrating agronomic and economic models for policy analysis at the farm level: The impact of CAP reform in two European regions," Agricultural Systems, Elsevier, Elsevier, vol. 48(2), pages 163-178.
    8. Llewelyn, Richard V. & Featherstone, Allen M., 1997. "A comparison of crop production functions using simulated data for irrigated corn in western Kansas," Agricultural Systems, Elsevier, Elsevier, vol. 54(4), pages 521-538, August.
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    Cited by:
    1. Lelyon, Baptiste & Chatellier, Vincent & Daniel, Karine, 2008. "Milk Quotas Abolishment And Simplification Of The Single Payment Scheme: Implications On Dairy Farmers’ Productive Strategy In The West Of France," 109th Seminar, November 20-21, 2008, Viterbo, Italy 44795, European Association of Agricultural Economists.
    2. Remble, Amber & Britz, Wolfgang & Keeney, Roman, 2013. "Farm Level Tradeoffs in the Regulation of Greenhouse Gas Emissions," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C., Agricultural and Applied Economics Association 150442, Agricultural and Applied Economics Association.
    3. Finger, Robert & Hediger, Werner, 2007. "The Application of Robust Regression to a Production Function Comparison – the Example of Swiss Corn," MPRA Paper 4740, University Library of Munich, Germany.
    4. Baptiste Lelyon & Vincent Chatellier & Karine Daniel, 2011. "Decoupling and prices: determinant of dairy farmers’ choices?," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement, INRA Department of Economics, vol. 92(1), pages 47-68.
    5. Baptiste Lelyon & Vincent Chatellier & Karine Daniel, 2011. "Decoupling and prices: determinant of dairy farmers’ choices?," Working Papers 47123, Institut National de la Recherche Agronomique, France.

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