3.2a How can we incorporate emerging technologies, such as artificial intelligence and machine learning, into the risk analysis process for novel foods and feeds?
Background
Food innovation and bringing to market new foods and technological developments have the potential to add variety to our diets and address some of the challenges facing the food production system today. There is a need to understand the safety, and in some cases, efficacy, of these new products or technologies to ensure consumers have access to safe food innovation.
The overarching aim of this research priority is to understand the safety of these regulated food and feed products and emerging food innovations for the UK consumer.
Next steps
Get in touch: [email protected]
Source
This question was published as part of the set of ARIs in this document:
Topics
No topics assigned yet
Research fields
No research fields assigned yet
Related UKRI funded projects
-
Novel Foods Expert Network for Regulatory Challenges UK (NFX UK)
The potential for enhancing innovation in the UK economy through Novel Food's (NF) is significant, as acknowledged by the government in the Pro-innovation Regulation of Technologies Review -- Life Sciences \[1\]. NF's ar...
Funded by: Innovate UK
Lead research organisation: READING SCIENTIFIC SERVICES LIMITED
Why might this be relevant?
Addresses the incorporation of emerging technologies like AI and machine learning into risk analysis for novel foods.
-
Holistic approach for tackling food systems risks in a changing global environment
The overall objective of HOLiFOOD is to improve the integrated food safety risk analysis (RA) framework in Europe to i) meet future challenges arising from Green Deal policy driven transitions in particular in relation t...
Funded by: Horizon Europe Guarantee
Lead research organisation: NEWCASTLE UNIVERSITY
Why might this be relevant?
Focuses on improving food safety risk analysis framework but does not specifically address the incorporation of AI and machine learning.
-
Extreme Food Risk Analytics
EFRA will explore how extreme data mining, aggregation and analytics may address major scientific, economic and societal challenges associated with the safety and quality of the food that European consumers eat. EFRA’s g...
Funded by: Horizon Europe Guarantee
Lead research organisation: MOY PARK LIMITED
Why might this be relevant?
Explores extreme data mining and analytics for food risk but does not directly address the incorporation of AI and machine learning into risk analysis for novel foods.