Buzdugan, SN, Alarcon, P, Huntington, B, Rushton, J 
ORCID: 0000-0001-5450-4202, Blake, DP and Guitian, J
(2021)
Enhancing the value of meat inspection records for broiler health and welfare surveillance: longitudinal detection of relational patterns.
BMC VETERINARY RESEARCH, 17 (1).
278-.
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Enhancing the value of meat inspection records for broiler health and welfare surveillance longitudinal detection of relatio.pdf - Published version Download (2MB) | Preview |
Abstract
<h4>Background</h4>Abattoir data are under-used for surveillance. Nationwide surveillance could benefit from using data on meat inspection findings, but several limitations need to be overcome. At the producer level, interpretation of meat inspection findings is a notable opportunity for surveillance with relevance to animal health and welfare. In this study, we propose that discovery and monitoring of relational patterns between condemnation conditions co-present in broiler batches at meat inspection can provide valuable information for surveillance of farmed animal health and welfare.<h4>Results</h4>Great Britain (GB)-based integrator meat inspection records for 14,045 broiler batches slaughtered in nine, four monthly intervals were assessed for the presence of surveillance indicators relevant to broiler health and welfare. K-means and correlation-based hierarchical clustering, and association rules analyses were performed to identify relational patterns in the data. Incidence of condemnation showed seasonal and temporal variation, which was detected by association rules analysis. Syndrome-related and non-specific relational patterns were detected in some months of meat inspection records. A potentially syndromic cluster was identified in May 2016 consisting of infection-related conditions: pericarditis, perihepatitis, peritonitis, and abnormal colour. Non-specific trends were identified in some months as an unusual combination of condemnation reasons in broiler batches.<h4>Conclusions</h4>We conclude that the detection of relational patterns in meat inspection records could provide producer-level surveillance indicators with relevance to broiler chicken health and welfare.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Meat inspection data, Machine learning, Relational patterns, Monitoring, Surveillance, Broiler chickens |
| Divisions: | Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Infection, Veterinary and Ecological Sciences |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 07 Feb 2022 16:15 |
| Last Modified: | 18 Jan 2023 21:13 |
| DOI: | 10.1186/s12917-021-02970-2 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3148440 |
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