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Enhancing the value of meat inspection records for broiler health and welfare surveillance: longitudinal detection of relational patterns
BACKGROUND: 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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371771/ https://www.ncbi.nlm.nih.gov/pubmed/34407823 http://dx.doi.org/10.1186/s12917-021-02970-2 |
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author | Buzdugan, S. N. Alarcon, P. Huntington, B. Rushton, J. Blake, D. P. Guitian, J. |
author_facet | Buzdugan, S. N. Alarcon, P. Huntington, B. Rushton, J. Blake, D. P. Guitian, J. |
author_sort | Buzdugan, S. N. |
collection | PubMed |
description | BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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. |
format | Online Article Text |
id | pubmed-8371771 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-83717712021-08-18 Enhancing the value of meat inspection records for broiler health and welfare surveillance: longitudinal detection of relational patterns Buzdugan, S. N. Alarcon, P. Huntington, B. Rushton, J. Blake, D. P. Guitian, J. BMC Vet Res Research BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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. BioMed Central 2021-08-18 /pmc/articles/PMC8371771/ /pubmed/34407823 http://dx.doi.org/10.1186/s12917-021-02970-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Buzdugan, S. N. Alarcon, P. Huntington, B. Rushton, J. Blake, D. P. Guitian, J. Enhancing the value of meat inspection records for broiler health and welfare surveillance: longitudinal detection of relational patterns |
title | Enhancing the value of meat inspection records for broiler health and welfare surveillance: longitudinal detection of relational patterns |
title_full | Enhancing the value of meat inspection records for broiler health and welfare surveillance: longitudinal detection of relational patterns |
title_fullStr | Enhancing the value of meat inspection records for broiler health and welfare surveillance: longitudinal detection of relational patterns |
title_full_unstemmed | Enhancing the value of meat inspection records for broiler health and welfare surveillance: longitudinal detection of relational patterns |
title_short | Enhancing the value of meat inspection records for broiler health and welfare surveillance: longitudinal detection of relational patterns |
title_sort | enhancing the value of meat inspection records for broiler health and welfare surveillance: longitudinal detection of relational patterns |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371771/ https://www.ncbi.nlm.nih.gov/pubmed/34407823 http://dx.doi.org/10.1186/s12917-021-02970-2 |
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