modeling the survival and growth of salmonella on chicken skin stored at 4 to 12 c
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Modeling the Survival and Growth of Salmonella on Chicken Skin Stored at 4 to 12 C. Thomas P. Oscar, Ph.D. U.S. Department of Agriculture Agricultural Research Service Princess Anne, MD. Introduction. Salmonella & poultry 1 - 2 cases per 100,000 Initial contamination - PowerPoint PPT PresentationTRANSCRIPT
Modeling the Survival and Growth of Modeling the Survival and Growth of SalmonellaSalmonella on Chicken Skin Stored on Chicken Skin Stored
at 4 to 12at 4 to 12CC
Thomas P. Oscar, Ph.D.Thomas P. Oscar, Ph.D.U.S. Department of AgricultureU.S. Department of AgricultureAgricultural Research ServiceAgricultural Research Service
Princess Anne, MDPrincess Anne, MD
IntroductionIntroduction
SalmonellaSalmonella & poultry & poultry
1 - 2 cases per 100,0001 - 2 cases per 100,000
Initial contaminationInitial contamination
< 30 CFU per chicken carcass< 30 CFU per chicken carcass
Illness doseIllness dose
101055 to 10 to 1077 CFU CFU
Int. J. Food Microbiol. 2004. 93:231-247.
IntroductionIntroduction
Risk AssessmentRisk Assessment Hazard IdentificationHazard Identification
Hazard CharacterizationHazard Characterization
Exposure AssessmentExposure Assessment
Risk CharacterizationRisk Characterization
PackagingContamination
Cold StorageTemp. Abuse
Meal Prep.Temp. Abuse
CookingUnder-cooking
ConsumptionExposure
Meal Prep.Cross-contamination
Risk Pathway
IntroductionIntroduction
Predictive microbiologyPredictive microbiology
Support risk assessmentsSupport risk assessments
Data gapsData gaps
Low initial doseLow initial dose
Microbial competitionMicrobial competition
Low temperaturesLow temperatures
IntroductionIntroduction
Another data gapAnother data gap
Variation among Variation among
serotypesserotypes
Autoclaved chicken meat at 25C
J. Food Safety. 2000. 20:225-236.
ObjectiveObjective
Develop a predictive modelDevelop a predictive model Survival & growthSurvival & growth
SalmonellaSalmonella Typhimurium & Typhimurium &
KentuckyKentucky
Low initial dose (0.9 log)Low initial dose (0.9 log)
Chicken thigh skin (2.14 cmChicken thigh skin (2.14 cm22) )
with microbial competitionwith microbial competition
Low temperature (4 to 12Low temperature (4 to 12C)C)
Materials & MethodsMaterials & Methods
Experimental designExperimental design
Model development Model development ((SalmonellaSalmonella serotype Typhimurium serotype Typhimurium
DT104)DT104)
5 x 5 full factorial5 x 5 full factorial
Temperature (4, 6, 8, 10, 12Temperature (4, 6, 8, 10, 12C)C)
Time (0, 1, 3, 6, 10 days)Time (0, 1, 3, 6, 10 days)
4 replicates4 replicates
Materials & MethodsMaterials & Methods
Experimental designExperimental design
Model validation Model validation ((SalmonellaSalmonella serotype Typhimurium serotype Typhimurium
DT104)DT104)
4 x 5 full factorial4 x 5 full factorial
Temperature (5, 7, 9, 11Temperature (5, 7, 9, 11C)C)
Time (0, 1, 3, 6, 10 days)Time (0, 1, 3, 6, 10 days)
2 replicates2 replicates
Materials & MethodsMaterials & Methods
Experimental designExperimental design
Model validation (Model validation (SalmonellaSalmonella serotype serotype
Kentucky)Kentucky)
4 x 5 full factorial4 x 5 full factorial
Temperature (5, 7, 9, 11Temperature (5, 7, 9, 11C)C)
Time (0, 1, 3, 6, 10 days)Time (0, 1, 3, 6, 10 days)
2 replicates2 replicates
Materials & MethodsMaterials & Methods
SalmonellaSalmonella enumeration enumeration
Combined MPN & CFU methodCombined MPN & CFU method
D) Typhimurium; 35 C
0 2 4 6 80
2
4
6
8PredictedObserved
Time (h)
Lo
g n
um
ber
MPN CFU
J. Food Prot. 2006. 69:2048-2057.
Materials & MethodsMaterials & Methods
Plating mediaPlating media
SalmonellaSalmonella serotype Typhimurium DT104 serotype Typhimurium DT104
XLH-CATSXLH-CATS
SalmonellaSalmonella serotype Kentucky serotype Kentucky
XLH-NATSXLH-NATS
J. Food Prot. 2006. 69:2048-2057.
Materials & MethodsMaterials & Methods General Regression Neural Network ModelGeneral Regression Neural Network Model
T t
… …-0.71 4.13
N(x) D(x)
ŷ
Input Layer
Pattern Layer
Summation Layer
Output (Δ)
Temp. time
Distance Function
Predicted Value
IEEE Trans. Neural. Netw. 1991. 2:568-576
Materials & MethodsMaterials & Methods
Model performanceModel performance
ResidualResidual
Observed - predictedObserved - predicted
Acceptable prediction zone (APZ)Acceptable prediction zone (APZ)
-1 log (fail-safe) to 0.5 log (fail-dangerous)-1 log (fail-safe) to 0.5 log (fail-dangerous)
Acceptable performanceAcceptable performance
70% of residuals in APZ70% of residuals in APZ
Prediction bias & accuracy
J. Food Sci. 2005. 70:M129-M137.
ResultsResults
SalmonellaSalmonella serotype Typhimurium DT104 serotype Typhimurium DT104
Model development (Model development (nn = 163) = 163)
4 C
0 2 4 6 8 10-1
0
1
2
3
4ObservedPredicted
Time (d)
(l
og)
10 C
0 2 4 6 8 10-1
0
1
2
3
4ObservedPredicted
Time (d)
(lo
g)
8 C
0 2 4 6 8 10-1
0
1
2
3
4ObservedPredicted
Time (d)
(lo
g)
6 C
0 2 4 6 8 10-1
0
1
2
3
4ObservedPredicted
Time (d)
(lo
g)
12 C
0 2 4 6 8 10-1012345
ObservedPredicted
Time (d)
(lo
g)
ResultsResults
SalmonellaSalmonella serotype Typhimurium DT104 serotype Typhimurium DT104
Model validation for interpolation (Model validation for interpolation (nn = 77) = 77)
5 C
0 2 4 6 8 10-1
0
1
2
3
4ObservedPredicted
Time (d)
(l
og)
7 C
0 2 4 6 8 10-1
0
1
2
3
4ObservedPredicted
Time (d)
(log
)9 C
0 2 4 6 8 10-1
0
1
2
3
4ObservedPredicted
Time (d)
(l
og)
11 C
0 2 4 6 8 10-1
0
1
2
3
4ObservedPredicted
Time (d)
(l
og)
DiscussionDiscussion
SalmonellaSalmonella serotype Typhimurium DT104 serotype Typhimurium DT104
Growth on sterile chicken breast meat at 10Growth on sterile chicken breast meat at 10CC
0 5 10 15 200
2
4
6
8
10
Time (d)
log
CFU
/g
Oscar (unpublished)
ResultsResults
SalmonellaSalmonella serotype Kentucky serotype Kentucky
Model validation for extrapolation (Model validation for extrapolation (nn = 70) = 70)
5 C
0 2 4 6 8 10-1
0
1
2
3
4ObservedPredicted
Time (d)
(l
og)
7 C
0 2 4 6 8 10-1
0
1
2
3
4ObservedPredicted
Time (d)
(log
)9 C
0 2 4 6 8 10-1
0
1
2
3
4ObservedPredicted
Time (d)
(l
og)
11 C
0 2 4 6 8 10-1
0
1
2
3
4ObservedPredicted
Time (d)
(l
og)
DiscussionDiscussion
Variation among serotypesVariation among serotypes
Kentucky grows slower on chicken skin at Kentucky grows slower on chicken skin at
3535CCTyphimurium DT104
0 2 4 6 80
2
4
6
8PredictedObserved
Time (h)
Log
num
ber
Kentucky
0 2 4 6 80
2
4
6
8PredictedObserved
Time (h)
Log
num
ber
J. Food Prot. 2009. 72:2078-2087.
Results & DiscussionResults & Discussion
Model Performance (Development)Model Performance (Development)
-3
-2
-1
0
1
2
3 A) Dependent
0 1 3 6 10
APZ = 85.3%
0 1 3 6 10 0 1 3 6 10 0 1 3 6 10 0 1 3 6 10
4C 6C 8C 10C 12C
Time (d)
Res
idu
al (
log
)
Results & DiscussionResults & Discussion
Model Performance (Interpolation)Model Performance (Interpolation)
-3
-2
-1
0
1
2
3 B) Interpolation
0 1 3 6 10
APZ = 84.4%
0 1 3 6 10 0 1 3 6 10 0 1 3 6 10
5C 7C 9C 11C
Time (d)
Re
sid
ua
l (lo
g)
Results & DiscussionResults & Discussion
Model Performance (Extrapolation)Model Performance (Extrapolation)
-3
-2
-1
0
1
2
3 C) Extrapolation
0 1 3 6 10
APZ = 87.1%
0 1 3 6 10 0 1 3 6 10 0 1 3 6 10
5C 7C 9C 11C
Time (d)
Res
idu
al (
log
)
Results & DiscussionResults & Discussion
ConclusionsConclusions
Model was validatedModel was validated
Microbial competition suppresses growthMicrobial competition suppresses growth
MPD = 1 log vs 8 log @ 10MPD = 1 log vs 8 log @ 10CC
Kentucky grows slowerKentucky grows slower
Compatible with @RiskCompatible with @Risk