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| Main Authors: | , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.13802 |
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| _version_ | 1866914237054451712 |
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| author | Kizililsoley, Nehir van Meer, Floor Mutlu, Osman Hoenderdaal, Wouter F Hobé, Rosan G. Mu, Wenjuan Gerssen, Arjen van der Fels-Klerx, H. J. Jóźwiak, Ákos Manikas, Ioannis Hürriyetoǧlu, Ali van der Velden, Bas H. M. |
| author_facet | Kizililsoley, Nehir van Meer, Floor Mutlu, Osman Hoenderdaal, Wouter F Hobé, Rosan G. Mu, Wenjuan Gerssen, Arjen van der Fels-Klerx, H. J. Jóźwiak, Ákos Manikas, Ioannis Hürriyetoǧlu, Ali van der Velden, Bas H. M. |
| contents | In the European Union, official food safety monitoring data collected by member states are submitted to the European Food Safety Authority (EFSA) and published on Zenodo. This data includes 392 million analytical results derived from over 15.2 million samples covering more than 4,000 different types of food products, offering great opportunities for artificial intelligence to analyze trends, predict hazards, and support early warning systems. However, the current format with data distributed across approximately 1000 files totaling several hundred gigabytes hinders accessibility and analysis. To address this, we introduce the CompreHensive European Food Safety (CHEFS) database, which consolidates EFSA monitoring data on pesticide residues, veterinary medicinal product residues, and chemical contaminants into a unified and structured dataset. We describe the creation and structure of the CHEFS database and demonstrate its potential by analyzing trends in European food safety monitoring data from 2000 to 2024. Our analyses explore changes in monitoring activities, the most frequently tested products, which products were most often non-compliant and which contaminants were most often found, and differences across countries. These findings highlight the CHEFS database as both a centralized data source and a strategic tool for guiding food safety policy, research, and regulation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_13802 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Food safety trends across Europe: insights from the 392-million-entry CompreHensive European Food Safety (CHEFS) database Kizililsoley, Nehir van Meer, Floor Mutlu, Osman Hoenderdaal, Wouter F Hobé, Rosan G. Mu, Wenjuan Gerssen, Arjen van der Fels-Klerx, H. J. Jóźwiak, Ákos Manikas, Ioannis Hürriyetoǧlu, Ali van der Velden, Bas H. M. Computers and Society Artificial Intelligence Computer Vision and Pattern Recognition In the European Union, official food safety monitoring data collected by member states are submitted to the European Food Safety Authority (EFSA) and published on Zenodo. This data includes 392 million analytical results derived from over 15.2 million samples covering more than 4,000 different types of food products, offering great opportunities for artificial intelligence to analyze trends, predict hazards, and support early warning systems. However, the current format with data distributed across approximately 1000 files totaling several hundred gigabytes hinders accessibility and analysis. To address this, we introduce the CompreHensive European Food Safety (CHEFS) database, which consolidates EFSA monitoring data on pesticide residues, veterinary medicinal product residues, and chemical contaminants into a unified and structured dataset. We describe the creation and structure of the CHEFS database and demonstrate its potential by analyzing trends in European food safety monitoring data from 2000 to 2024. Our analyses explore changes in monitoring activities, the most frequently tested products, which products were most often non-compliant and which contaminants were most often found, and differences across countries. These findings highlight the CHEFS database as both a centralized data source and a strategic tool for guiding food safety policy, research, and regulation. |
| title | Food safety trends across Europe: insights from the 392-million-entry CompreHensive European Food Safety (CHEFS) database |
| topic | Computers and Society Artificial Intelligence Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2507.13802 |