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

Martine J. Barons (), Lael E. Walsh, Edward E. Salakpi and Linda Nichols
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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

Agriculture, 2024, vol. 14, issue 3, 1-21

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.

Keywords: Bayesian networks; integrated pest management; EU Green Deal; sustainable development goals; Integrating Decision Support Systems (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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