Artificial Intelligence in Food Safety: A Decade Review and Bibliometric Analysis

Area of Science:

• Food Science
• Agricultural Science
• Computer Science

Background:

• Artificial Intelligence (AI) offers solutions for food yield, quality, nutrition, safety, traceability, resource efficiency, and waste reduction.
• Existing reviews on AI in food safety are qualitative; a quantitative, systematic approach is needed.
• Understanding the historical trajectory and future trends of AI in food safety is crucial.

Purpose of the Study:

• To conduct an in-depth quantitative and systematic review of AI technologies in food safety literature from 2012 to 2022.
• To identify the historical development, current landscape, and future research trends of AI in food safety.
• To provide a comprehensive overview for researchers, practitioners, and policymakers.

Main Methods:

• Bibliometric analysis of 1855 articles from the Web of Science Core Collection database (2012-2022).
• Utilized CiteSpace software for performance analysis, science mapping, and network analysis.
• Focused on literature concerning artificial intelligence technologies applied to food safety.

Main Results:

• China and the United States are leading contributors to AI in food safety research.
• The Chinese Academy of Sciences published the most articles; PLoS ONE and Computers and Electronics in Agriculture are top journals.
• Identified key research areas, hot spots, and emerging trends in AI for food safety.

Conclusions:

• The review provides a comprehensive bibliometric analysis of AI in food safety, covering precision agriculture to nutrition.
• Highlights major contributors, leading publications, and research hotspots.
• Offers insights into the evolution and future directions of AI applications in ensuring food safety.