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Designing Cost-effective Monitoring Schemes for Chemical Hazards in Feed Using Machine Learning

出版	Wageningen University, 2022
ISBN	94644750059789464475005
URL	http://books.google.com.hk/books?id=GTiXzwEACAAJ&hl=&source=gbs_api

註釋Chemical hazards, like mycotoxins, dioxins and polychlorinated biphenyls (PCBs), and heavy metals in feed can affect animal and human health. Maximum allowable concentrations of these food safety hazards in animal feed and their ingredients are established in EU Directive 2002/32/EC to control their presence in feed. Feed containing such food safety hazards above the maximum levels may be unsafe for animals and humans and must be withdrawn from the supply chain. Therefore, the presence of such food safety hazards in feed can result in economic damage due to the recall of the contaminated feed as well as food of animal origin. Also, economic damage occurs through higher disease prevalence in case the contaminations are not detected. Monitoring programs to control the presence of chemical hazards in feed have been designed and implemented by both the industry and governmental agencies. Since the checking the presence of all food safety hazards in the endless number of feed ingredients is resource demanding, such monitoring programs are ideally carried out with a risk-based approach to monitor the hazards that pose the highest risk to animal and human health. In addition, monitoring plans could be conducted in a cost-effective way, meaning the plan provides the highest effectiveness of food safety monitoring given available resources.