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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 Ewen C. D. Todd
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 • 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
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 Conveyor Shredder Flume tank Shaker table Centrifugal dryer
Sampling for Transfer: 11 Flume Tank and 9 Shaker Table Samples
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 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 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 Transfer Transfer data expressed as a percentage (%)
Modeling Transfer Beta distribution describing transfer rates: contaminated spinachshaker
Leafy Green Processing Conveyor Shredder Flume tank Shaker table Centrifugal dryer
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 • 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-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:
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)
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 • Ho - R + I ≤ FSO • Ho = initial contamination • R = sum of reductions • I = sum of increases • FSO = Food Safety Objective
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
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 • 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 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)
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
Ho – [Rw/s + Ru + Rc] + I ≤ FSO Possible Inputs to Achieve FSO
Scenario 1:log cfu/g Ho = -1 Rw/s = 0 Ru = 0 Rc = 0 I = 1
Scenario 2:log cfu/g Ho = -1 Rw/s = 1.86 Ru = 0 Rc = 0 I = 0
Scenario 3:log cfu/g Ho = -1 Rw/s = 1.86 Ru = 0.57 Rc = 0 I = 0
Scenario 4:log cfu/g Ho = -2.52 Rw/s = 1.86 Ru = 0.57 Rc = 0 I = 0
Scenario 5:log cfu/g Ho = -2.52 Rw/s = 1.86 Ru = 0.57 Rc = 1 I = 0
Scenario 6:log cfu/g Ho = -4.09 Rw/s = 1.86 Ru = 0.57 Rc = 0 I = 0
Scenario 7:log cfu/g Ho = -4.09 Rw/s = 1.86 Ru = 0.57 Rc = 1 I = 0
Interventions: Original ContaminatedBatch FSO = -4 log cfu/g Frequency (%) E. coli O157:H7 (Log cfu/g)
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) • 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., 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., 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
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