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Cross Contamination. Ewen C. D. Todd. H 0. ΣR. ΣI. FSO. A Systems Approach to Minimize Escherichia coli O157:H7 Food Safety Hazards Associated With Fresh- and Fresh-cut Leafy Greens. Production & Primary Handling. Processing & Packaging. Distribution & Shelf-life. Minimizing

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Cross contamination

Cross Contamination

Ewen C. D. Todd


Cross contamination

H0

ΣR

ΣI

FSO

A Systems Approach to Minimize Escherichia coli O157:H7 Food Safety Hazards Associated With Fresh- and Fresh-cut Leafy Greens

Production & Primary Handling

Processing & Packaging

Distribution & Shelf-life

Minimizing

an increase

in levels

  • Minimizing

  • initial levels

  • Composting (1)

  • Internalization (2)

  • Cross contamination (3)

  • Processing water (4)

Reducing

levels

Food Safety

Objective (8)

  • Physical & Chemical

  • Treatments (5)

  • Survival & Growth (6)

-

+

Risk Analysis Model (7)


Risk assessment and management of leafy greens

Risk Assessment and Management of Leafy Greens

  • Fernando Pérez-Rodríguez, Food Science and Technology, University of Córdoba, Córdoba, Spain.

  • Martin Cole and Alvin Lee, National Center for Food Safety and Technology, Summit Argo, IL

  • Tom Ross, Tasmanian Institute of Agricultural Research School of Agricultural Science University of Tasmania, Hobart, Australia

  • Ewen Todd, Ewen Todd Consulting, Okemos, MI


Cross contamination

Raw material storage at 4-6 C

Manual trimming and preliminary washing

Shredding

Wash in chlorinated water

Rinsing

Moisture removal by centrifugation

Packaging

Storage at 4-6 C

QRA Scheme of Production of Minimally Processed Vegetables


Leafy green processing shredding and washing

Leafy Green Processing – Shredding and Washing

Conveyor

Shredder

Flume tank

Shaker table

Centrifugal dryer


Sampling for transfer 11 flume tank and 9 shaker table samples

Sampling for Transfer: 11 Flume Tank and 9 Shaker Table Samples


Leafy green processing lettuce and spinach

Leafy Green Processing (Lettuce and Spinach)

  • Number of batches processed in a day = 22 ( ≈ 3 batches/h) – contamination may occur at any stage

  • Batch size = 1000 kg

  • Number of bags per batch: 10,000

  • Bag size: 100 g


Modeling transfer

Modeling Transfer

  • Modeling cross contamination by E. coli O157:H7 during processing of leafy greens (spinach):

    • Probabilistic model

    • Two-dimensional model:

      • Uncertainty

      • Variability

    • Probability distributions describing transfer experimental data:

      • Contaminated product to Equipment

      • Equipment to Non-contaminated product


Cross contamination simulations

Cross ContaminationSimulations

  • The model was simulated by applying Latin Hypercube Sampling technique implemented with @Risk

  • The simulation consisted in 10 uncertainty realizations and 1000 variability iterations

  • The outputs were prevalence and concentration of E. coli O157:H7 at the end of the processing line (bags)


Modeling transfer1

Modeling Transfer

Transfer data expressed as a percentage (%)


Modeling transfer2

Modeling Transfer

Beta distribution describing transfer rates:

contaminated spinachshaker


Leafy green processing

Leafy Green Processing

Conveyor

Shredder

Flume tank

Shaker table

Centrifugal dryer


Modeling cross contamination

Modeling Cross-contamination

ESTIMATING TRANSFER USING DISTRIBUTIONS

Monte Carlo Simulation

Risk

Tr(%)EB

Tr(%)AE

Product A (cfu/g)

Product B

(cfu/g)

Transfer rate from Product A to Equipment= Tr(%)AE

Transfer rate from Equipment Product B= Tr(%)EB


Modeling assumptions

Modeling Assumptions

  • As contamination by E. coli O157:H7 is sporadic event (Doyle & Eriksson, 2007), it is assumed that only one contaminated batch would be in the processing line, and this variable was modeled as a stochastic process being an uncertainty source

  • Transfer was expressed as transfer percentage (%): proportion of cells transferred from donor surface (food, water or equipment) to receptor surface (food, water or equipment) expressed in %

    • Transfer rate (%) = (cfu receptor surface/ cfu donor surface)*100

  • Transfer rates for the modeling were estimated using experimental data obtained at low contamination levels

  • Growth rate was determined as under some refrigeration after processing


Cross contamination model

Cross-contaminationModel

The analysis of iterations showed that E. coli O157:H7 was transferred to the product at very low levels, average being ≈ 1-6 cfu/bag:


Cross contamination

Managing Risk from Risk Assessment outputs


Cross contamination

H0

ΣR

ΣI

FSO

A Systems Approach to Minimize Escherichia coli O157:H7 Food Safety Hazards Associated With Fresh- and Fresh-cut Leafy Greens

Production & Primary Handling

Processing & Packaging

Distribution & Shelf-life

Minimizing

an increase

in levels

  • Minimizing

  • initial levels

  • Composting (1)

  • Internalization (2)

  • Cross contamination (3)

  • Processing water (4)

Reducing

levels

Food Safety

Objective

  • Physical & Chemical

  • Treatments (5)

  • Survival & Growth (6)

-

+

Risk Analysis Model (7)


Cross contamination

Generic Process Risk Assessment Model (Whiting, 2009)

Performance Objectives

Microbiological Criteria

Raw

ingredients

Heating

Storage &

Trans.

Periods

Consumption

Illness

Acceptable Level Of

Protection

Performance Criteria

(logs inactivation)

Process Criteria

(°C - min)

Product Criteria

(pH, salt)

Food Safety Objective


Food safety objectives

Food Safety Objectives

  • Ho - R + I ≤ FSO

  • Ho = initial contamination

  • R = sum of reductions

  • I = sum of increases

  • FSO = Food Safety Objective


Setting the fso

Setting the FSO

  • Food safety objective (FSO): the maximum frequency and/or concentration of a hazard in a food at the time of consumption that provides or contributes to the Appropriate Level of Protection (ALOP)

  • There is no one way to set a FSO by an assessor because it is a decision made by managers in the context of scientific and other parameters

  • A possible FSO for E. coli O157:H7 is 10-4/g based on the FDA Juice HACCP regulation = 1 cfu in 10 kg


Cross contamination

Flow Chart for Production of Leafy Greens

Farms

Harvest

Clear cut

Initial Number

Ho

Transport

In Bins

Reduction

of Hazard

∑R

Sanitizer

Tank

Rinse

Tank

Dump

tank

Shredder

Potential

Increase

∑I

Food Safety

Objective

FSO

De-watering

Centrifuge

Irradiation/testing/

Ultrasound/chilling

Consumption

Distribution,Retail

Storage in Home

Packaging


Possible decontamination strategies

Possible Decontamination Strategies

  • Testing. Increased testing and removal of possible contaminated product – the more samples tested, the more the contaminated product is likely to be discovered and removed

  • Chilling. Regardless of atmosphere and E. coli O157 inoculation level, populations of the pathogen decreased only when the temperature was ≤ 7°C

  • Ultrasound with chlorine. High power ultrasound (HPU) for 120 sec in the presence of 200 ppm chlorine at 10 or 20°C inactivated 1.3 or 0.5 log E. coli O157/g, respectively, more than 200 ppm chlorine without HPU

  • X-ray irradiation. A 5-log reduction likely achievable at a dose of 0.2 kGy with a X-Ray irradiator


Example of achieving a fso in leafy greens

Example of Achieving a FSO in Leafy Greens

Ho - R + I ≤ FSO

< 1/10kg

14 Days Shelf-Life

12oC 1 log Increase

5oC 1 Log Decrease

3.0 – 9.2 MPN/g

generic E.coli

(Valentin-Bon et al, 2008)

Worst case 10/g

Testing to eliminate

highly contaminated lots

15 x 25 g samples

-2.63 1 cfu/400g (S.D.=0.8)

200 ppm chlorine

plus high power ultrasound

2.43 Log reduction (S.D.=0.67)


H o r i fso

Ho - R + I ≤ FSO

  • R = sum of reductions

  • in leafy green processing/distribution, reductions through:

  • washing and sanitizer (W/S)

  • ultrasound (U)

  • chill storage (C)

  • R = Rw/s + Ru + Rc

  • I = I Growth at 12ºC


H o r w s r u r c i fso

Ho – [Rw/s + Ru + Rc] + I ≤ FSO

Possible Inputs to Achieve FSO


Scenario 1 log cfu g

Scenario 1:log cfu/g

Ho = -1

Rw/s = 0

Ru = 0

Rc = 0

I = 1


Scenario 2 log cfu g

Scenario 2:log cfu/g

Ho = -1

Rw/s = 1.86

Ru = 0

Rc = 0

I = 0


Scenario 3 log cfu g

Scenario 3:log cfu/g

Ho = -1

Rw/s = 1.86

Ru = 0.57

Rc = 0

I = 0


Scenario 4 log cfu g

Scenario 4:log cfu/g

Ho = -2.52

Rw/s = 1.86

Ru = 0.57

Rc = 0

I = 0


Scenario 5 log cfu g

Scenario 5:log cfu/g

Ho = -2.52

Rw/s = 1.86

Ru = 0.57

Rc = 1

I = 0


Scenario 6 log cfu g

Scenario 6:log cfu/g

Ho = -4.09

Rw/s = 1.86

Ru = 0.57

Rc = 0

I = 0


Scenario 7 log cfu g

Scenario 7:log cfu/g

Ho = -4.09

Rw/s = 1.86

Ru = 0.57

Rc = 1

I = 0


Interventions original contaminated batch

Interventions: Original ContaminatedBatch

FSO = -4 log cfu/g

Frequency (%)

E. coli O157:H7 (Log cfu/g)


Interventions effect cross contaminated batch

InterventionsEffect: Cross-contaminatedBatch

FSO = -4 log cfu/g

0 log (1 cfu/g)

Frequency (%)

E. coli O157:H7 (Log cfu/g)


Fsos and pos van schothorst et al 2009

FSOs and POs (van Schothorst et al., 2009)

  • ALOP: “expression of the level of protection in relation to food safety that is currently achieved

    • It is not an expression of a future or desirable level of protection

  • FSO: the maximum permissible level of a microbiological hazard in a food at the moment of consumption

    • Maximum hazard levels at other points along the food chain are called Performance Objectives (POs)

  • PO: the maximum frequency and / or concentration of a hazard in a food at a specified step in the food chain before consumption that provides or contributes to an FSO or ALOP, as applicable


Fsos and pos van schothorst et al 20091

FSOs and POs (van Schothorst et al., 2009)

  • Industries may have to validate that their food safety system is capable of controlling the hazard of concern, i.e., to provide evidence that control measures can meet the targets

  • In addition, industry must periodically verify that their measures are functioning as intended

  • To assess compliance with FSOs and POs, control authorities rely on inspection procedures (e.g., physical examination of manufacturing facilities, review of HACCP monitoring and verification records, analysis of samples) to verify the adequacy of control measures adopted by industry


Fsos and pos van schothorst et al 20092

FSOs and POs (van Schothorst et al., 2009)

  • Safe food is produced by adhering to GHPs, GMPs, GAPs, etc., and implementation of food safety risk management systems such as HACCP, but the level of safety that these food safety systems are expected to deliver is usually not in quantitative terms

  • Establishment of FSOs and POs provides the industry with quantitative targets to be met

  • Although FSOs and POs are expressed in quantitative terms, they are not Microbiological Criteria (MCs)which are defined as the acceptability of a product or a food lot, based on the absence/presence or number of microorganisms including parasites, and/or quantity of their toxins/metabolites, per unit(s) of mass, volume, area or lot

  • MCs are designed to determine adherence to GHPs and HACCP (i.e., verification) when more effective and efficient means are not available


Cross contamination

Generic Process Risk Assessment Model

Performance Objectives

Microbiological Criteria

Raw

ingredients

Heating

Storage &

Trans.

Periods

Consumption

Illness

Acceptable Level Of

Protection

Performance Criteria

(logs inactivation)

Process Criteria

(°C - min)

Product Criteria

(pH, salt)

Food Safety Objective


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