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Data-Driven Analysis of Risk-Assessment Methods for Cold Food Chains.
Qian Wang1,2, Zhiyao Zhao1,2, Zhaoyang Wang1,2
1College of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, China.
Foods (Basel, Switzerland)
|April 28, 2023
Summary
Ensuring cold-chain food safety relies on effective risk assessment. This study maps research trends and evaluates methods to improve cold food chain safety and regulatory decision-making.
Area of Science:
- Food Science
- Risk Management
- Information Science
Background:
- Cold-chain food safety is a growing concern globally.
- Effective risk assessment is crucial for maintaining food safety throughout the cold chain.
Purpose of the Study:
- To analyze research hotspots in cold-chain food safety over 18 years.
- To summarize and evaluate cold food chain risk assessment methods.
- To identify challenges and provide recommendations for improving cold chain risk assessment.
Main Methods:
- Knowledge mapping using CiteSpace software.
- Analysis of research keywords, centrality, and cluster values.
- Review and categorization of risk assessment methodologies (qualitative, quantitative, comprehensive).
Main Results:
- Identified key research trends and hotspots in cold-chain food safety.
- Summarized advantages and disadvantages of different risk assessment approaches.
- Highlighted challenges including data credibility, audit methods, and non-traditional risks.
Conclusions:
- The study provides a data-driven overview of cold chain risk assessment research.
- Recommendations are offered to enhance risk assessment systems for better food safety control.
- Findings support regulatory authorities in implementing effective risk prevention measures.
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