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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.
Afiliação
  • Buzdugan SN; Veterinary Epidemiology, Economics and Public Health Group, Pathobiology and Population Sciences, Royal Veterinary College, Hawkshead Lane, Hertfordshire, AL9 7TA, North Mymms, UK. Svetlana.Buzdugan@mhra.gov.uk.
  • Alarcon P; Veterinary Epidemiology, Economics and Public Health Group, Pathobiology and Population Sciences, Royal Veterinary College, Hawkshead Lane, Hertfordshire, AL9 7TA, North Mymms, UK.
  • Huntington B; Liverpool Science Park, Innovation Centre 2, 146 Brownlow Hill, L3 5RF, Liverpool, UK.
  • Rushton J; Epidemiology and Population Health, Liverpool University, Brownlow Hill, L69 7ZX, Liverpool, UK.
  • Blake DP; Pathobiology and Population Sciences, Royal Veterinary College, North Mymms, UK.
  • Guitian J; Veterinary Epidemiology, Economics and Public Health Group, Pathobiology and Population Sciences, Royal Veterinary College, Hawkshead Lane, Hertfordshire, AL9 7TA, North Mymms, UK.
BMC Vet Res ; 17(1): 278, 2021 Aug 18.
Article em En | MEDLINE | ID: mdl-34407823
ABSTRACT

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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Contexto em Saúde: 2_ODS3 Problema de saúde: 2_quimicos_contaminacion Assunto principal: Doenças das Aves Domésticas / Bem-Estar do Animal / Registros / Inspeção de Alimentos / Matadouros / Carne Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Aspecto: Patient_preference Limite: Animals País/Região como assunto: Europa Idioma: En Revista: BMC Vet Res Assunto da revista: MEDICINA VETERINARIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Contexto em Saúde: 2_ODS3 Problema de saúde: 2_quimicos_contaminacion Assunto principal: Doenças das Aves Domésticas / Bem-Estar do Animal / Registros / Inspeção de Alimentos / Matadouros / Carne Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Aspecto: Patient_preference Limite: Animals País/Região como assunto: Europa Idioma: En Revista: BMC Vet Res Assunto da revista: MEDICINA VETERINARIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Reino Unido
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