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Book (series)Joint FAO-IOC-IAEA technical guidance for the implementation of early warning systems for harmful algal blooms 2023
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No results found.Globally, there are 3 400 to 4 000 described species of marine microalgae but only 1 to 2 percent are considered to be harmful. Harmful algal blooms (HABs) have significant impacts on food safety and security through contamination or mass mortalities of aquatic organisms. The impacts and mass mortalities of marine species caused by harmful algae are not new and have been recorded for decades. However, there is growing concern that these events will increase due to accelerating global warming, climate change and anthropogenic activities. Indeed, if not properly controlled, aquatic products contaminated with HAB biotoxins are responsible for potentially deadly foodborne diseases and when rapidly growing, HAB consequences include reduced dissolved oxygen in the ocean, dead zones, and mass mortalities of aquatic organisms. Improving HAB forecasting is an opportunity to develop early warning systems for HAB events such as food contamination, mass mortalities, or foodborne diseases. Surveillance systems have been developed to monitor HABs in many countries; however, the lead-time or the type of data (i.e. identification at the species-level, determination of toxicity) may not be sufficient to take effective action for food safety management measures or other reasons, such as transfer of aquaculture products to other areas. Having early warning systems could help mitigate the impact of HABs and reduce the occurrence of HAB events. The Joint FAO-IOC-IAEA technical guidance for the implementation of early warning systems (EWS) for HABs will guide competent authorities and relevant institutions involved in consumer protection or environmental monitoring to implement early warning systems for HABs present in their areas (marine and brackish waters), specifically those affecting food safety or food security (benthic HABs, fish-killing HABs, pelagic toxic HABs, and cyanobacteria HABs). The guidance provides a roadmap for stakeholders on how to improve or implement an EWS for HABs and biotoxins, where appropriate. It is important to note that not all countries and institutions can implement the same level of EWS for HABs, and this guidance is intended mainly for those who seek to broaden existing early warning systems, or who are just beginning to consider putting a system in place. -
PresentationThe impact of climate change on food safety, 17 November 2020 2020
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No results found.The presentation highlights the key messages from the FAO publication, Climate change: Unpacking the burden on food safety. Climate change is associated with rising temperatures, droughts, wildfires as well as the amplification and increased frequency of extreme weather events like hurricanes. These changes have implications for food safety and food security. However, while climate change impacts on food security are well-known, the implications for food safety have received less attention. To address this, a document, Climate change: Unpacking the burden on food safety, was recently published by FAO which identified some anticipated and current food safety issues that are associated with various climate change-related environmental factors. Apart from raising awareness of the issue, the objective of the publication was also to help foster better international cooperation in reducing the global burden of these concerns. -
ArticleMaking food systems more resilient to food safety risks by including artificial intelligence, big data, and internet of things into food safety early warning and emerging risk identification tools 2024
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No results found.To enhance the resilience of food systems to food safety risks, it is vitally important for national authorities and international organizations to be able to identify early signals of emerging food safety risks and to provide early warning in a timely manner. This review provides an overview of existing and experimental applications of artificial intelligence (AI), big data, and internet of things tools and methods as part of early warning and emerging risk identification in the food safety domain. There is an ongoing rapid development of systems fed by numerous, real-time, and diverse data with the aim of early warning and identification of emerging food safety risks. The suitability of big data and AI to support such systems is illustrated by two cases in which climate change drives the emergence of risks, namely, harmful algal blooms affecting seafood and fungal growth and mycotoxin formation in crops. Automation and machine learning are crucial for the development of future real-time food safety risk early warning systems. Although these developments and tools increase the feasibility and effectiveness of prospective early warning and emerging risk identification, their implementation may prove challenging, particularly for low- and middle-income countries due to low connectivity and data availability. It is advocated to overcome these challenges by improving the capability and capacity of national authorities, as well as by enhancing their collaboration with the private sector and international organizations.
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