Data-Mining Poultry Processing Bio-Mapping Counts of Pathogens and Indicator Organisms for Food Safety Management Decision Making

Abstract

Bio-mapping studies play an important role, as the data collected can be managed and analyzed in multiple ways to look at process trends, find explanations about the effect of process changes, activate a root cause analysis for events, and even compile performance data to demonstrate to inspection authorities or auditors the effect of certain decisions made on a daily basis and their effects over time in commercial settings not only from the food safety perspective but also from the production side. This study presents an alternative analysis of bio-mapping data collected throughout several months in a commercial poultry processing operation as described in the article “Bio-Mapping Indicators and Pathogen Loads in a Commercial Broiler Processing Facility Operating with High and Low Antimicrobial Interventions”. The conducted analysis identifies the processing shift effect on microbial loads, attempts to find correlation between microbial indicators data and pathogens loads, and identifies novel visualization approaches and conducts distribution analysis for microbial indicators and pathogens in a commercial poultry processing facility. From the data analyzed, a greater number of locations were statistically different between shifts under reduced levels of chemical interventions with higher means at the second shift for both indicators and pathogens levels. Minimal to negligible correlation was found when comparing aerobic counts and Enterobacteriaceae counts with Salmonella levels, with significant variability between sampling locations. Distribution analysis and visualization as a bio-map of the process resulted in a clear bimodality in reduced chemical conditions for multiple locations mostly explained by shift effect. The development and use of bio-mapping data, including proper data visualization, improves the tools needed for ongoing decision making in food safety systems.

Bio-Mapping of Microbial Indicators and Pathogen Quantitative Loads in Commercial Broiler Processing Facilities in South America

“…In order to be able to perform an analysis that includes both the quantification and prevalence results, some adjustments were made to the data (Table 1). BAX ® -System-SalQuant ® and BAX ® -System-CampyQuant ™ counts can be extrapolated below the LOQ as counts are obtained from a regression equation provided by methodology, the reason why a new LOQ was established as 1% of the real LOQ (0.01 CFU/mL or 0.6 Log CFU/sample) [10,[20][21][22]. Counts below 0.6 Log CFU/sample were reported as 50% of the new LOQ (0.3 Log CFU/sample), as well as samples that were not quantifiable but observed positive for prevalence analysis.…”

“…For both indicator organisms, a similar trend was observed in microbial levels with a minimal reduction from the live receiving area to the post-evisceration step, followed by an important reduction at post-chiller and then a significant increase in parts (wings). The increase in microbial loads on parts has been observed in multiple studies, and it has been associated with the extensive manipulation intrinsic to the process (cutting, processing, and packaging) that increases the potential for cross-contamination [10,21,24]. However, the existing sampling method can significantly influence the results because the contact surface during parts rinsing is larger compared to whole chicken carcass rinsing, which affects the final counts.…”

Modernization Data Analysis and Visualization for Food Safety Research Outcomes

“…Furthermore, in cases when indicator data are used as a measure of pathogen control, then indicator results from bio-mapping are beneficial for food safety management decisions. Although a few process mapping studies have been conducted in the past [85,86], there has been a recent increased interest in bio-mapping due to regulatory changes, new Salmonella quantification methodologies, intervention assessment, and riskbased decision making, resulting in poultry [47,87], beef [56,62,88,89], pork [46], and leafy green [50] bio-mapping studies.…”