ABSTRACT

The first step in quantitative microbial risk assessment (QMRA) is to determine the distribution of pathogen contamination among servings of the food in question at some point in the farm-to-table chain. In the present study, the distribution of Salmonella contamination among servings of chicken liver for use in the QMRA was determined at meal preparation. Salmonella prevalence (P), most probable number (MPN, N), and serotype for different serving sizes were determined by use of a combination of five methods: (i) whole sample enrichment; (ii) quantitative PCR; (iii) culture isolation; (iv) serotyping; and (v) Monte Carlo simulation. Epidemiological data also were used to convert serotype data to virulence (V) values for use in the QMRA. A Monte Carlo simulation model based in Excel and simulated with @Risk predicted Salmonella P, N, serotype, and V as a function of a serving size of one (58 g) to eight (464 g) chicken livers. Salmonella P of chicken livers was 72.5% (58 of 80) per 58 g. Four Salmonella serotypes were isolated from chicken livers: (i) Infantis (P = 28%, V = 4.5); (ii) Enteritidis (P = 15%, V = 5); (iii) Typhimurium (P = 15%, V = 4.8); and (iv) Kentucky (P = 15%, V = 0.8). Salmonella N was 1.76 log MPN/58 g (median) with a range of 0 to 4.67 log MPN/58 g, and the median Salmonella N was not affected (P > 0.05) by serotype. The model predicted a nonlinear increase (P ≤ 0.05) of Salmonella P from 72.5%/58 g to 100%/464 g, a minimum N of 0 log MPN/58 g to 1.28 log MPN/464 g, and a median N from 1.76 log MPN/58 g to 3.22 log MPN/464 g. Regardless of serving size, predicted maximum N was 4.74 log MPN per serving, mean V was 3.9 per serving, and total N was 6.65 log MPN per lot (10,000 chicken livers). The data acquired and modeled in this study address an important data gap in the QMRA for Salmonella and whole chicken liver.

HIGHLIGHTS
  • Quantitative data for Salmonella contamination of chicken liver were collected.

  • A model for Salmonella contamination of chicken liver servings was developed.

  • Salmonella prevalence should be expressed as a function of sample size.

  • Salmonella serotype data should be collected for risk assessment.

  • A dap gap in risk assessment for Salmonella and chicken liver was addressed.

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