|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|107489||2018||7 صفحه PDF||سفارش دهید||4736 کلمه|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Food Control, Volume 83, January 2018, Pages 38-44
Knowing which products and hazards to monitor along the food supply chain is crucial for ensuring food safety. In this study, we developed a model to predict which types of herbs and spices products and food safety hazards should preferentially be monitored at each level of the supply chain (suppliers, border inspection points, market and consumers). A Bayesian Network method was used to develop a model based on notifications reported in the Rapid Alert System for Food and Feed and the database of the Dutch national monitoring program for chemical contaminants in food and feed over the period 2005â2014. The model was constructed by randomly selecting ca. 80% of the 3126 data records and validated using the remaining ca. 20% of the records. Model validation showed that the prediction accuracy was higher than 85%. Results showed that the sampling plan is closely related to the place where the products are checked along the supply chain, the products and the country of origin. Our approach of integrating different data sources and considering the entire supply chain can support industry and authorities at border inspection points and at all control points along the herbs and spices supply chain in setting priorities for their monitoring program.