Internal contamination of fish fillets during brine injection

The function sfBriningCC() simulates the potential internal contamination of fish fillets during brining by injection of salt solution. The cross-contamination algorithm accounts for four possible scenarios:

1. cross-contamination occurring in lots already contaminated;

2. cross-contamination occurring in lots that were not contaminated;

3. no additional contamination occurring in lots already contaminated; and

4. no cross-contamination occurring in lots that were not contaminated. Probabilities of occurrence of the four events are computed.

The mean volume of brine injected per fillet (V_inj) and the mean concentration of L. monocytogenes in brine (N_brine) are allowed to vary from lot to lot; and, to this effect, their values are sampled from Pert distributions with parameters volInjMin, volInjMode, volInjMax; and concBrineMin, concBrineMode, concBrineMax, respectively. To estimate the number of cells transferred to the fish fillet, it is assumed that the cells follow a Poisson distribution in the volume of brine.

Usage

sfBriningCC(
  data = list(),
  pccBrine,
  volInjMin,
  volInjMode,
  volInjMax,
  concBrineMin,
  concBrineMode,
  concBrineMax
)

Arguments

data

a list of

N

(CFU) A matrix of size nLots lots by sizeLot units containing the numbers of L. monocytogenes in/on fish fillets;

P

Mean prevalence of contaminated lots (scalar);

ProbUnitPos

Probability of individual lots being contaminated (vector).

pccBrine

Probability that the brine solution is contaminated with L. monocytogenes (scalar).

volInjMin

(ml) minimum volume of brine solution injected in a fish fillet (scalar).

volInjMode

(ml) most likely volume of brine solution injected in a fish fillet (scalar).

volInjMax

(ml) maximum volume of brine solution injected in a fish fillet (scalar).

concBrineMin

(CFU/ml) minimum concentration of L. monocytogenes in contaminated brine solution (scalar).

concBrineMode

(CFU/ml) most likely concentration of L. monocytogenes in contaminated brine solution (scalar).

concBrineMax

(CFU/ml) maximum concentration of L. monocytogenes in contaminated brine solution (scalar).

Value

A list of three elements:

N

(CFU) A matrix of size nLots lots by sizeLot units containing the numbers of L. monocytogenes in brined fish;

ProbUnitPos

Probability of individual lots being contaminated after brining (vector);

P

Mean prevalence of contaminated lots after brining (scalar).

Note

The suggested value of \(probCCDice\_brine=0.135\) is taken from Gudmundsdóttir et al. (2005) and Gudbjörnsdóttir et al. (2004) , who analysed the presence of L. monocytogenes in brining solution, detecting 3 positive samples out of 14, and 2 positive samples out of 23, respectively. The parameters of the distributions about mean volume of brine solution injected in a fish fillet and mean concentration of L. monocytogenes in brine must be defined by the user and/or tested in scenarios.

References

Gudbjörnsdóttir B, Suihko M, Gustavsson P, Thorkelsson G, Salo S, Sjöberg A, Niclasen O, Bredholt S (2004). “The incidence of Listeria monocytogenes in meat, poultry and seafood plants in the Nordic countries.” Food Microbiology, 21(2), 217-225. doi:10.1016/S0740-0020(03)00012-1 , cited By 148. Gudmundsdóttir S, Gudbjörnsdóttir B, Lauzon HL, Einarsson H, Kristinsson KG, Kristjánsson M (2005). “Tracing Listeria monocytogenes isolates from cold-smoked salmon and its processing environment in Iceland using pulsed-field gel electrophoresis.” International journal of food microbiology, 101(1), 41-51. doi:10.1016/j.ijfoodmicro.2004.08.023 , cited By 63. Pouillot R, Delignette-Muller M (2010). “Evaluating variability and uncertainty in microbial quantitative risk assessment using two R packages.” International Journal of Food Microbiology, 142(3), 330-40. Team RC (2022). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/. FDA (2021). “FDA-iRISK 4.2 Food Safety Modeling Tool: Technical Document.” U.S. Food and Drug Administration.

Author

Ursula Gonzales-Barron ubarron@ipb.pt and Regis Pouillot rpouillot.work@gmail.com

Examples

nLots <- 100
sizeLot <- 50
pccBrine <- 5 / 37
volInjMin <- 0.5
volInjMode <- 1.2
volInjMax <- 4.5
concBrineMin <- 0
concBrineMode <- 3
concBrineMax <- 40
ProbUnitPos <- rep(0.105, nLots)

dat <- list(
  N = matrix(rpois(nLots * sizeLot, 16),
    nrow = nLots,
    ncol = sizeLot
  ),
  P = 0.22,
  ProbUnitPos = ProbUnitPos,
  nLots = 100,
  sizeLot = 50
)
Nf <- sfBriningCC(
  dat,
  pccBrine,
  volInjMin, volInjMode, volInjMax,
  concBrineMin, concBrineMode, concBrineMax
)
hist(Nf$N)