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14163 Berlin
+49 30 838 62551 / 52790
lebensmittelhygiene@vetmed.fu-berlin.de / fleischhygiene@vetmed.fu-berlin.de
Background: In Europe, broilers are inspected after slaughter by official veterinarians or official auxiliaries. Macroscopically visible lesions and contaminations are recorded, and unfit carcasses are removed from the food chain. Information about the reason for the condemnation is valuable for
various stakeholders. However, procedures vary extensively between European countries, and the lack of uniform ways of reporting meat inspection findings makes it a challenge to analyse and compare data.
Objective: The objective was to develop a new harmonised and risk-based code set for post-mortem inspection of broilers, which would enable a detailed analysis of the data as well as implementation of computer vision systems in the future.
Materials and Methods: Information about national code sets used to registrate poultry condemnations in nine European countries was collected. Based on the most frequently recorded findings in the countries included in the study and considering harmonised epidemiological indicators for poultry meat and broiler welfare indicators, we developed a new harmonised risk-based code set for broiler carcasses.
Results: The resulting code set consists of 10 codes, which were the most frequently used reasons for condemnations in the countries included in the study, as well as three additional codes of importance for broiler welfare. These 13 codes can be assigned to the following areas of impact: health, welfare, quality and food safety.
Discussion and Conclusion
Harmonisation of the code list and the associated decision criteria would allow for conducting post-mortem inspection in the same way in all abattoirs and countries. Such a standardisation would enable a detailed analysis of the results. The next step will be to develop harmonised decision criteria de fining
the thresholds for condemnation based on lesion severity.
Perspectives: A harmonised code set, and associated decision criteria will favour implementation of computer vision systems in the future.