Risk and indicators of condemnation of male turkey broilers in western France, February-July 2006.

A field study was conducted to estimate the sanitary condemnation proportion in male turkey broiler flocks, to describe the reasons for condemnation and the related macroscopic lesions, and to investigate whether primary production information would predict the risk of condemnation. Male turkey standard broiler flocks (117) were randomly selected in the 13 slaughterhouses located in Western France, from February to July 2006. The flocks were monitored from their arrival at the slaughterhouse until the results of the post mortem sanitary inspection. Information about rearing conditions, health history, catching and loading conditions, transportation to the slaughterhouse and slaughtering was also collected. Sampling design was considered in the calculations and the condemnation proportion was modelled using a negative binomial regression, accounting for clustering within slaughterhouse. The within-flock weighted average condemnation proportion was 1.8% (95% confidence interval, 1.3-2.3%). Emaciation, arthritis-polyarthritis and congestion were the main reported official reasons for condemnation, representing 76% of the condemned carcases. Three variables were significantly associated with increased risk of condemnation: observed locomotor disorders on the farm, high cumulative mortality 2 weeks before slaughter, and clinical signs observed by the Veterinary Services during the ante mortem inspection at the slaughterhouse. The final model explained 35% of the total variation in condemnation risk. Half of this explained variation could be attributed to locomotor disorders observed during rearing. The sensitivity and specificity of the model to predict a high flock condemnation risk were 80% and 74%, respectively, when using an optimum threshold of 0.95% to define high risk. The results of this study suggested that the variables found to be associated with condemnation proportion were markers of increased risk and could be used as indicators. These risk indicators can easily be retrieved from the pre-existing regulatory document transmitted before flock arrival at the slaughterhouse and could be used to screen flocks before slaughter, according to their expected risk of condemnation.

[1]  S. Martin,et al.  Veterinary Epidemiologic Research , 2009 .

[2]  T Blaha,et al.  Epidemiology and quality assurance application to food safety. , 1999, Preventive veterinary medicine.

[3]  A Windhaus,et al.  [Results of the evaluation of food chain information for a risk-oriented meat inspection]. , 2007, DTW. Deutsche tierarztliche Wochenschrift.

[4]  J. Rochon.  The application of the GSK method to the determination of minimum sample sizes. , 1989, Biometrics.

[5]  C Lupo,et al.  Postmortem condemnations of processed broiler chickens in western France , 2008, Veterinary Record.

[6]  A. M. Johnston,et al.  Determination of farm-level risk factors for abnormalities observed during post-mortem meat inspection of lambs: a feasibility study , 1999, Epidemiology and Infection.

[7]  John M. Lachin,et al.  Biostatistical Methods: The Assessment of Relative Risks , 2000 .

[8]  K. Stärk,et al.  [Food safety achieved through herd management]. , 2000, Schweizer Archiv fur Tierheilkunde.

[9]  Richard J Cook,et al.  Conditional analysis of mixed Poisson processes with baseline counts: implications for trial design and analysis. , 2003, Biostatistics.

[10]  A S Bremner.  Post mortem condemnation returns from poultry slaughterhouses in England and Wales , 1994, Veterinary Record.

[11]  D Meemken,et al.  [Proposals for designing the food chain information for the implementation of the risk-oriented ante- and post-mortem meat inspection]. , 2007, DTW. Deutsche tierarztliche Wochenschrift.

[12]  P. Bossuyt,et al.  Sources of Variation and Bias in Studies of Diagnostic Accuracy , 2004, Annals of Internal Medicine.

[13]  C Lupo,et al.  Feasibility of screening broiler chicken flocks for risk markers as an aid for meat inspection , 2009, Epidemiology and Infection.

[14]  T Habtemariam,et al.  A computer based decision-making model for poultry inspection. , 1983, Journal of the American Veterinary Medical Association.

[15]  J. Jarp,et al.  Factors associated with mortality in Norwegian broiler flocks. , 2002, Preventive veterinary medicine.

[16]  Risk factors for abattoir condemnation of turkey carcasses due to cyanosis in southern Ontario. , 2000, Poultry science.

[17]  S. St-Hilaire,et al.  Trends in Cellulitis Condemnations in the Ontario Chicken Industry Between April 1998 and April 2001 , 2003, Avian diseases.

[18]  J. Snijders,et al.  Predictability of post mortem abnormalities in shipments of slaughter pigs as an aid for meat inspection. , 1991, The Veterinary quarterly.

[19]  B R Berends,et al.  Suggestions for the construction, analysis and use of descriptive epidemiological models for the modernization of meat inspection. , 1996, International journal of food microbiology.

[20]  John M. Lachin.  Analysis of Count Data , 2008 .

[21]  Marcia A Ciol,et al.  Understanding the use of weights in the analysis of data from multistage surveys. , 2006, Archives of physical medicine and rehabilitation.

[22]  J M Snijders,et al.  Use of information from pig finishing herds for meat inspection purposes. , 1992, The Veterinary quarterly.

[23]  Maryam Ansari-Lari,et al.  Poultry abattoir survey of carcass condemnations in Fars province, southern Iran. , 2007, Preventive veterinary medicine.

[24]  R Kulmala,et al.  Measuring the contribution of randomness, exposure, weather, and daylight to the variation in road accident counts. , 1995, Accident; analysis and prevention.