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• W2897811020 abstract "Abstract The presence and development of many food safety risks are driven by factors within and outside the food supply chain, such as climate, economy and human behaviour. The interactions between these factors and the supply chain are complex and a system or holistic approach is needed to reveal cause-effect relationships and to be able to perform effective mitigation actions to minimise food safety risks. In this study, we demonstrate the potential of the Bayesian Network (BN) approach to identify and quantify the strength of relationships and interactions between the presence of food safety hazards as reported in Rapid Alert System for Food and Feed (RASFF) for fruits and vegetables on one hand, and climatic factors, economic and agronomic data on the other. To this end, all food safety notifications in RASFF (i.e. 3781 notifications) on fruits and vegetables originating from India, Turkey and the Netherlands were collected for the period 2005–2015. In addition, climatic factors (e.g. temperature, precipitation), agricultural factors (e.g. pesticide use, fertilizer use) and economic factors (e.g. price, production volumes) were collected for the countries of origin of the product concurrent with the period of food safety notification in RASFF. A BN was constructed with 80% of the collected data using a machine-learning algorithm and optimised for each specific hazard category. The performance of the developed BN was determined in terms of accuracy of prediction of the hazard category in the evaluation set comprising 20% of the total data. The accuracy was high (95%) and the following factors contributed most: product category, notifying country, yearly production, number of notification, maximal residue level (MRL) ratio, country of origin, and the annual agricultural budget of a country. The assessment of the impact of interactions within the BN showed a significant interaction between the presence and level of a hazard as reported in RASFF and several drivers of change but at present, no definite conclusions can be drawn regarding the climatic factors and food safety hazards." @default.
• W2897811020 created "2018-10-26" @default.
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• W2897811020 date "2019-03-01" @default.
• W2897811020 modified "2023-10-16" @default.
• W2897811020 title "Impact of drivers of change, including climatic factors, on the occurrence of chemical food safety hazards in fruits and vegetables: A Bayesian Network approach" @default.
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• W2897811020 doi "https://doi.org/10.1016/j.foodcont.2018.10.021" @default.
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