Skip to contents

Cross-contamination of cantaloupe rind by L. monocytogenes during harvest

Source: R/caHarvestCC.R
caHarvestCC.Rd

The function caHarvestCC() simulates cross-contamination that might occur at the moment of harvesting from elements such as conveyors, crates or plastic surfaces. This function can be used for cantaloupes harvested in large farms (intended for RTE and sold as whole cantaloupe in formal retail) and in small farms (intended for traditional markets). Parameters to be changed accordingly.

Usage

caHarvestCC(
  data = list(),
  probCCH,
  trMean,
  trSd,
  nPlas,
  nLots = NULL,
  sizeLot = NULL
)

Arguments

data

a list of

N

(CFU) A matrix of size: nLots by sizeLot containing the numbers of L. monocytogenes on the rind of cantaloupes from contaminated cultivation lots

P

Prevalence of contaminated cultivation lots (scalar)

probCCH

Probability of cross-contamination during harvest

trMean

Mean of the normal distribution describing the variability in the transfer coefficient from the surface of elements to rind (scalar)

trSd

Standard deviation of the normal distribution describing the variability in the transfer coefficient from the surface of elements to rind (scalar)

nPlas

(CFU) Numbers of L. monocytogenes on food contact surfaces (conveyors or crates at harvest) touching the cantaloupes (scalar)

nLots

Number of cultivation lots

sizeLot

Number of cantaloupes cultivated and harvested in a lot

Value

A list of two elements:

N

(CFU) A matrix of size nLots by sizeLot of L. monocytogenes numbers on the rind of cantaloupes from contaminated harvested lots

P

Prevalence of harvested contaminated lots

Note

The algorithm evaluates the cross-contamination event at cantaloupe level (and not at cultivation lot level), assuming that every cantaloupe has the same probability probCCH of being contaminated from conveyors, crates or other surfaces during harvesting.

References

Team RC (2022). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.

Author

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

Examples

# Example of use in LARGE production farms
dat <- caPrimaryProduction(
nLots = 100,
  sizeLot = 100)
probCCH <- 0.005
LargeFarms <- caHarvestCC(dat,
                          probCCH = probCCH, 
                          trMean = -1.42,
                          trSd = 0.52, 
                          nPlas = 200
                          )
hist(LargeFarms$N)

probCCH <- 0.02
nPlas <- 500
SmallFarms <- caHarvestCC(dat,
                          probCCH = probCCH, trMean = -1.42,
                          trSd = 0.52, nPlas = 500,
                          nLots = 100, sizeLot = 100
                          )
                          hist(SmallFarms$N)