Study Title
Artificial Intelligence in Food Safety: A Decade Review and Bibliometric Analysis
Principal Investigator
Zhe Liu, Shuzhe Wang, Yudong Zhang, Yichen Feng, Jiajia Liu, Hengde Zhu
Affiliation
Henan University of Technology, China; University of Leicester, UK
Start Date
Not specified
End Date
Not specified
Study Objective
To explore the historical development, current trends, and future directions of artificial intelligence (AI) applications in food safety, focusing on machine learning and deep learning technologies applied across food quality, safety, and nutrition.
Short Abstract
This bibliometric review investigates AI's role in food safety from 2012 to 2022 using a combination of performance analysis, science mapping, and network analysis. By analyzing 1855 articles from global research databases, the study identifies AI trends in food safety, including applications in foodborne illness prediction, food quality control, and agricultural sustainability.
Study Design
Bibliometric analysis
Population
Global studies on AI applications in food safety
Sample Size
1855 articles
Inclusion Criteria
Articles from 2012 to 2022 related to AI applications in food safety
Exclusion Criteria
Studies not focused on AI in food safety, non-peer-reviewed articles
Intervention/Exposure
AI and machine learning technologies in food safety
Outcome Measures
- Evolution of AI applications in food safety
- Hotspots and future trends in AI for food quality, safety, and nutrition
Funding Source
Not specified
Collaborating Institutions
Henan University of Technology, University of Leicester
Ethics Approval
Not specified
Publication Status
Published in Foods (2023)
Keywords
Artificial intelligence, food safety, bibliometric analysis, machine learning, deep learning, food quality, foodborne illness
Data Collection Methods
Bibliometric analysis using CiteSpace from Web of Science (WoS) database
Primary Data Availability
Not applicable
Contact Information
Zhe Liu:
Yudong Zhang: