Artificial Intelligence and Big Data in food safety
The majority of Big Data applications requires dealing with large volumes, diverse sources and forms of data, ranging from highly structured to unstructured data, which is due to the rise in the sharing and availability of data. To deal with this complexity, new tools are needed to automatically extract process, integrate, visualize and organize this data into both human and machine readable summaries. Wageningen Food Safety Research is exploring the application of Artificial intelligence (AI) and Big Data technologies in food safety to keep and make food safe. Progress in these areas will allow us to greatly improve our knowledge in AI and Big Data, and will help us to utilise better the available data for the generation of knowledge.
Applications
Publicaties
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Artificial intelligence to detect unknown stimulants from scientific literature and media reports
Food Control 130 (2021). - ISSN 0956-7135 -
Role of analytical testing for food fraud risk mitigation – A commentary on implementation of analytical fraud testing : Role of analytical testing for food fraud mitigation
Current Research in Food Science 4 (2021). - ISSN 2665-9271 - p. 301 - 307. -
Identification of potential vulnerable points and paths of contamination in the Dutch broiler meat trade network
PLoS ONE 15 (2020)5. - ISSN 1932-6203 -
A system approach towards prediction of food safety hazards : Impact of climate and agrichemical use on the occurrence of food safety hazards
Agricultural Systems 178 (2020). - ISSN 0308-521X -
Application of Bayesian Networks in the development of herbs and spices sampling monitoring system
Food Control 83 (2018). - ISSN 0956-7135 - p. 38 - 44. -
Development of food fraud media monitoring system based on text mining
Food Control 93 (2018). - ISSN 0956-7135 - p. 283 - 296. -
Application of Bayesian networks for hazard ranking of nanomaterials to support human health risk assessment
: Wageningen University & Research -
Big data in food safety; an overview
Critical Reviews in Food Science and Nutrition 57 (2017)11. - ISSN 1040-8398 - p. 2286 - 2295. -
Big Data in food safety- A review
Current Opinion in Food Science 36 (2020). - ISSN 2214-7993 - p. 24 - 32. -
Prediction of food fraud type using data from Rapid Alert System for Food and Feed (RASFF) and Bayesian network modelling
Food Control 61 (2016). - ISSN 0956-7135 - p. 180 - 187.