ABSTRACT
Pig production is relevant to the Brazilian economy. Different stages of the raising and slaughtering process influence the microbiological quality of pig products and by-products. Microbiological analysis and hazard analysis and critical control points (HACCPs) are tools for monitoring microbiological quality indicator microorganisms. The construction of predictive models can assist the process of monitoring the microbiological quality of pig products. This study aimed to map the slaughter stages and develop a model to predict the absence or presence of Salmonella based on the process variables (distance from the farm to the slaughterhouse and aerobic mesophilic) and analyze their influence on contamination indicator microorganisms. A total of 810 samples were collected at nine stages of the slaughter process (bleeding, scalding, dehairing, singeing, washing, evisceration, inspection, final washing, and chilling). The binary class predictive model was used as a microbiological quality predictor at the slaughter stages. Salmonella was identified at all process stages, with lower contamination levels at the scalding and chilling stages, whereas the highest levels were found at the dehairing and bleeding stages. The predictive model revealed an accuracy of about 85% for Salmonella being a tool to monitor the microbiological quality of pig slaughter.
