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A Decision Support System for Sustainable Agriculture and Food Loss Reduction under Uncertain Agricultural Policy Frameworks

Author

Listed:
  • Martine J. Barons

    (Department of Statistics, The University of Warwick, Coventry CV4 7AL, UK)

  • Lael E. Walsh

    (Horticulture Development Department, Teagasc Ashtown Food Research Centre, D15 DY05 Dublin, Ireland)

  • Edward E. Salakpi

    (Biological and Environmental Sciences, University of Stirling, Stirling FK9 4LA, UK)

  • Linda Nichols

    (Department of Statistics, The University of Warwick, Coventry CV4 7AL, UK)

Abstract

The EU Green Deal requires the reduction in pesticides and fertilisers in food crop production, whilst the sustainable development goals require reductions in food loss and food waste. In a complex and interacting system like the food system, these goals are difficult to coordinate. Here, we show an approach using Bayesian network modelling for decision support. Bayesian networks are important tools for modelling complex systems which may develop emergent behaviour and for providing quantitative comparisons for different candidate policies, approaches or interventions under the Integrating Decision Support System paradigm. Using lettuce as an exemplar crop, we demonstrate that expected food loss changes under different agricultural input reduction and integrated pest management combinations can be quantified to aid decision making for growers.

Suggested Citation

  • Martine J. Barons & Lael E. Walsh & Edward E. Salakpi & Linda Nichols, 2024. "A Decision Support System for Sustainable Agriculture and Food Loss Reduction under Uncertain Agricultural Policy Frameworks," Agriculture, MDPI, vol. 14(3), pages 1-21, March.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:3:p:458-:d:1355340
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    References listed on IDEAS

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