to cooling of cooked meat and poultry products Vijay K. Juneja, DVM, - PowerPoint PPT Presentation

Hazards associated with Clostridium perfringens in particular reference to predictive models applicable to cooling of cooked meat and poultry products Vijay K. Juneja, DVM, MS, Ph.D. Eastern Regional Research Center ARS - USDA 600 East Mermaid Lane Wyndmoor, Pennsylvania 19038 Phone: 215-233-6500 Fax: 215-233-6697 e-mail: vjuneja@arserrc.gov

Clostridium perfringens • Anaerobic • Gram-positive • Spore-forming • Rod-shaped • Non-motile bacterium

Clostridium perfringens • Implicated in 248,520 cases of foodborne illnesses every year in the United States with 41 hospitalizations and 7 deaths (Mead et al. 2000). • Illnesses estimated at $123 million in North America (Anonymous, 1995). • Inadequate cooling practices.

Nature of Problem • Clostridium perfringens is a spore- forming bacterium • It grows under anaerobic conditions • It is distributed widely in the environment – Exits in the intestines of humans and animals – Persists in soil, sediments, and areas where fecal contamination can occur • It survives well in the world

Perfringens Food Poisoning • It is usually caused by consumption of large number of vegetative cells (> 10 8 ) • It is associated with production of C. perfringens toxins – Cells producing toxins in the intestine – Foods containing toxins • It can cause intense abdominal cramps and diarrhea with 8 - 22 h • It is usually over in less than 24 h

Why Is It So Important? • Spores – normal cooking temperatures cannot kill them • During cooking – spores activated by heat and then germinate, outgrow and multiply rapidly if cooling rate is slow • Note: Growth is rapid when temperature is between 30 – 50°C.

Temperature Abuse D t 1 Temperature D T Danger Zone D t 2 time

What Types of Foods? • Foods are cooked, but not canned • Allowed to cool slowly • Kept warm – Large pieces of cooked meats – A big pot of soup

Who, When, Where, and How? • Institutional feeding - school cafeteria, hospitals, prisons, and nursing homes where large quantities of foods are prepared • Malfunctioned cooling systems during manufacturing of cooked meats • The young and elderly are always victims

For Prepared Food Manufacturers Cooling! Cooling! Cooling!

Federal Regulation USDA Food Safety and Inspection Services Guideline 130 – 80°F (54.4 – 26.6°C) ≤ 1.5 h 80 – 40 ° F (26.6 – 4.4 ° C) ≤ 5 h In the event of process deviation or temperature abuse, manufacturers must prove that growth of C. perfringens < 1 log

Federal Register, Vol. 64, No. 3; Jan 6, 1999

Option I Internal temperature should not remain between 130 and 80 F for > 1.5 h nor between 80 and 40 for > 5 h

Option II • Cooling should begin 90 min from the end of cooking cycle • Product chilled from 120 to 55 F in < 6 h; Chilling should continue until the product reaches 40 F; • Product shall not be shipped until it reaches 40 F

Option III • Product chilled from 130 to 80 F in 5 h; and 80 to 45 F in 10 h RTE meat and poultry cured with nitrite (min 100 ppm)

Option III… Narrow margin of safety In case of cooling deviation, assume the process has exceeded performance standard for C. perfringens Therefore, Use PMP

Stabilization Performance Standards • All RTE products must be processed so as to prevent multiplication of toxigenic microorganisms such as C. botulinum and allow no more than 1-log 10 multiplication of C. perfringens within the product (USDA-FSIS, 2001). • Determined using our PMP

Cooling Deviations…. – If computer modeling suggests > 1 log CFU/g increase in C. perfringens, there is a hazard – Therefore, re-cook the product

Cooling Requirements • USDA/FSIS: Compliance Guidelines for Cooling Heat- Treated Meat and Poultry Products (Stabilization) – “ In the event that a cooling deviation does occur, the product may often be salvaged if the results of computer modeling and/or sampling can ensure product safety. Because of a lack of information concerning the distribution of C. perfringens in product, sampling may not be the best recourse for determining the disposition of product following cooling deviations. However, computer modeling can be a useful tool in assessing the severity of a cooling deviation. While computer modeling cannot provide an exact determination of the possible amount clostridial growth, it can provide a useful estimate. “

Safe cooling rates for cooked products (Objectives) Develop models to predict the relative growth of Clostridium perfringens from spores at temperatures applicable to the cooling of cooked beef, pork and chicken.

Clostridium perfringens (Accomplishments) • Cooling models: »Beef Gravy »cured and uncured beef »cured and uncured chicken »cured and uncured pork • Model for growth of C. perfringens : Temperature, sodium chloride and sodium pyrophosphate, sodium nitrite

Mathematical Models • Modified Gompertz Model Primary • Logistic Model models • Baranyi Model

Growth Equation based on Baranyi Model μ = specific exponential growth rate. q affects the lag phase duration. m = ln of maximum population density, M.   ( ) A t 1 e        ( ) (0) ( ) ln(1 ) ( ) n t n A t t  ( (0)) m n e   ut e q     1 ( ) ln( ) A t t  1 q

Modeling Growth of C. perfringens In Cooked Beef Under Isothermal Conditions 9 8 7 25°C 9 6 1 7° C log(CFU/g) 8 30°C 7 36°C 5 6 log(CFU/g) 45°C 5 4 47°C 4 3 50°C 2 3 1 0 0 20 40 60 80 100 120 140 160 180 200 2 t (h) 1 0 10 20 30 40 50 t (h)

Secondary model T is temperature in C. a, b, Tmin, Tmax are parameter values EGR 1/2 = a (T-Tmin)[1-exp( b (T-Tmax))] 1/2 ( Ratowsky Equation) EGR times Lag is a function of q – reflecting the physiological state of the cells (Baranyi). Often assumed constant for modeling. Consider quantity. ζ = ln(EGR x LAG)

Plot of estimated EGR versus temperature, for uncured chicken 2.5 All Rep = 1 Rep = 2 2.0 Deleted 1.5 EGR 1.0 0.5 0.0 10 20 30 40 50 Temp C

Differential equations describing dynamic growth, m o (t) = cells in lag phase • m D (t) = cells in exponential phase h(t) = λ (t) = the hazard function for lag to exponential phase ( ) dm t   O ( ) ( ) h t m t O dt  ( ) ( ) ( ) dm t m t m t     D O D ( ) ( ) ( ) ( )( 1 ) h t m t t m t O D dt M

Clostridium perfringens Growth in Beef (Dynamic Cooling Scenarios) Time (h) Time (h) Initial Observed Predicted log 10 increase between between level log 10 Logistic Baranyi Linear 54.4 and 27 27 and 4 C log 10 increase model model model C 1.5 0.0 2.87 0.66 1.11 1.07 1.11 1.5 0.0 1.07 -0.24 1.11 1.07 1.11 3.0 0.0 2.97 2.45 3.66 3.56 3.54 3.0 0.0 0.81 1.44 3.66 3.58 3.56 4.5 0.0 3.03 4.37 6.02 4.94 4.94 4.5 0.0 0.82 4.03 6.02 6.07 6.00 6.0 0.0 2.84 6.20 6.95 5.16 5.16 6.0 0.0 0.73 5.35 6.95 7.26 7.25

Clostridium perfringens Growth in Beef (Dynamic Cooling Scenarios) Time (h) Time (h) Initial Observed Predicted log 10 increase between between level log 10 Logistic Baranyi Linear 54.4 and 27 27 and log 10 increase model model model C 4 C 1.5 12.5 2.64 2.73 3.24 3.24 3.21 1.5 15.0 2.77 3.62 3.74 3.67 3.63 3.0 12.5 2.98 4.30 5.77 4.94 4.93 3.0 12.5 0.85 1.72 5.77 5.75 5.67 3.0 15.0 0.47 0.86 6.06 6.20 6.10

Clostridium perfringens Growth in Beef (Dynamic Cooling Scenarios) Hours Hours Log 10 relative growth from 54.4 from 27 Observed Predicted log10 relative growth for to 27 ° C to 4 ° C exponential model Δ = 0 h Δ = 0.25 h Δ = 0.5 h Function 1.5 0 0.66 (0.33) 1.11 0.95 0.80 1.00 1.5 12.5 2.73 (0.24) 3.21 3.09 2.98 3.31 1.5 15 3.62 (0.04) 3.63 3.51 3.41 3.73 3.0 0 2.45 (0.09) 3.54 3.40 3.25 3.37 * Δ = 1 - EGR/(8ln(10)), so that Δ ranged from 0.26 to 1.

Conclusions The Traditional Method : May lead to slight overestimation of C. perfringens growth in uncured chicken and beef meats during dynamic cooling. Use of Memory : The predicted values improved to within ± 0.5 log10 of the mean of the observed values for the cooling scenarios.

Predictive Microbiology Information Portal Regulations Models Useful Links • Final Rule on Listeria monocytogenes in RTE Meat and Poultry Products • “Zero Tolerance” Policy

USDA Pathogen Modeling Program Download at www.ars.usda.gov/naa/errc/mfsru/pmp

Pathogen Modeling Program (PMP) 7.0 The PMP is a repository of models that estimate the behavior of bacterial pathogens in specific environments. Through a user interface, information is provided about the effects of environmental factors on: - growth - inactivation (thermal and non-thermal) - toxin production

PMP • The PMP 7.0 currently contains: - 40 models - 15 food and 25 broth models - static and dynamic temperature models • Used by ~50% of FSIS-inspected companies • >7,000 downloads per year