Analysis of the variation in meat inspection of pigs using variance partitioning

Abstract

According to legal regulations, all slaughtered pigs in the European Union are subject to routine meat inspection at the slaughterhouses. The resulting post-mortem findings are valuable indicators that help improve slaughterhouse and farm management and can be used to establish a feedback system regarding animal health. A sufficiently high quality of meat inspection is therefore imperative, which implies that the results of the inspection must not depend on the person carrying out the examination. The objective of the study at hand is the estimation of the amount of variation in these post-mortem findings that can be attributed to the official meat inspectors. In order to reduce the influence of the heterogeneity in the health state of the pigs, the variation due to the farms of origin was considered in the statistical model as well. The analyzed meat inspection data were recorded by 12 official meat inspectors under real working conditions at an Austrian slaughterhouse. Logistic Multilevel Models with cross-classified random effects were applied to 20 post-mortem findings. On the basis of these models, variance partitioning coefficients (VPCs) were used to estimate the amount of variation in the probabilities of these findings due to meat inspector and farm levels. The estimated VPCs suggest that especially meat inspection of blood aspiration, scalding water lungs, skin lesions and hepatitis can be deemed as not sufficiently standardized. Hardly any variation in meat inspection could be identified for other post-mortem findings, such as pericarditis, peritonitis, arthritis and milkspots.

Keywords: Interclass correlations; Meat inspection; Post-mortem findings; Variance partitioning; Variation.