Post on 04-Jul-2015
description
A decision making tool to predict microbial behavior during the food processes
Sym’Previus :
Prediction of microbial behavior during the food processes
Noémie Desriacsymprevius@adria.tm.fr
A decision making tool to predict microbial behavior during the food processes
2symprevius@adria.tm.fr
Not ONLY a tool,but as well a network!
UNIR
A decision making tool to predict microbial behavior during the food processes
3
Not ONLY a tool,but as well a network!
Supported by the French food safety authorities
A decision making tool to predict microbial behavior during the food processes
symprevius@adria.tm.fr 4
1.Food process
C1284
3.Food storage2.Transport & delivery
Estimate the risk for various scenarii
during food shelf-life?
Developed with food providers, for food providers
what is the impact of adding a natural
preservative such as lactic acid?
Determine the impact of abuse
temperature condition?
A decision making tool to predict microbial behavior during the food processes
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Sym’Previus toolbox
HACCP
assistanceProbabilistic
module
Thermal destruction
simulation
Bacterial survival
simulation
B. cereus group
affiliation (I-VII) Database
Growth
interfaces
Growth
simulation
Growth curve
fitting
The Sym’Previustools
symprevius@adria.tm.fr
A decision making tool to predict microbial behavior during the food processes
6
Sym’Previus toolbox
HACCP
assistanceProbabilistic
module
Thermal destruction
simulation
Bacterial survival
simulation
B. cereus group
affiliation (I-VII) Database
Growth
interfaces
Growth
simulation
Growth curve
fitting
The Sym’Previustools
symprevius@adria.tm.fr
A decision making tool to predict microbial behavior during the food processes
7
Pathogen
microorganismsSpoilage
microorganisms
9 species:Spore-formers/non Spore-formers
13 species: Spore-formers/non Spore-formers
Sym’Previus toolbox
BiodiversityA wonderful world or… a brain teaser?!
A decision making tool to predict microbial behavior during the food processes
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Sym’Previus toolbox
…with wild strains coming from food production units … and your own data-base
Pathogenic
microorganismsSpoilage
microorganisms
9 species:Spore-formers/non Spore-formers
13 species: Spore-formers/non Spore-formers
- Microbial diversity (up to 13 strains)
- Isolated from food product/ production environment
-Standardized protocols (ring trials)
symprevius@adria.tm.fr
A decision making tool to predict microbial behavior during the food processes
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Sym’Previus applicationPractical case
Critical steps
(critical control point CCP)?
Microbial hazards of concerns ?
pH=5.2
aw=0.99
Thawing10h/8 C
Preparation2h/25 C
Cooking 2h/90 C
Cooling Until 2 C in 2h
Storage 1/3 at 4 C and
2/3 at 8 C
Packaging 1h 4 C
symprevius@adria.tm.fr
A decision making tool to predict microbial behavior during the food processes
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HACCP assistanceInput/ouput
Minimum inputs
Microorganisms (Sym’Previus possibilities)
Food properties(pH, aw)
Food processes(T, t, thawing, storage…)
Impact of each process step on microorganism
behavior (growth/inactivation)
The hazards of concerns at each process step
symprevius@adria.tm.fr
for wide range of outputs !
A decision making tool to predict microbial behavior during the food processes
11
HACCP assistance :
Sym’Previus applicationPractical case
A decision making tool to predict microbial behavior during the food processes
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Sym’Previus applicationPractical case
HACCP assistance :
A decision making tool to predict microbial behavior during the food processes
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What is the growth probability of L. moncytogenes in that
specific food product?
How to limit the growth of L. monocytogenes,
for instance what is the impact of adding a
natural preservative such as lactic acid
(0.6g/100g)?
Sym’Previus applicationPractical case
Critical steps = heat treatmentdistribution/storage step
L. monocytogenes = Of major concern during the shelf-life!
Got it!
A decision making tool to predict microbial behavior during the food processes
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Growth interfacesInput/output
Microorganisms (Sym’Previus strains
and related data,OR your own strains
and data)
Food properties(pH, aw)
Food storage (T, lactate)
Growth-no growth interfaces
symprevius@adria.tm.fr
Minimum inputs for wide range of outputs !
A decision making tool to predict microbial behavior during the food processes
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Growth interfaces :
pH 5.2aw=0.99T=8 C
Sym’Previus applicationPractical case
symprevius@adria.tm.fr
A decision making tool to predict microbial behavior during the food processes
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pH 5.2aw=0.99T=8 C
+Lactate
Sym’Previus applicationPractical case
symprevius@adria.tm.fr
Growth interfaces :
+ lactate
A decision making tool to predict microbial behavior during the food processes
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And now, what about the shelf-life?
“Hum, the marketing would like OF COURSE to
extend that shelf-life, is that realistic?”
What is the risk based regulation criteria?
Sym’Previus applicationPractical case
The probability of L. monocytogenes growth in
that specific food product exceeds 90%
Adding the appropriate concentration of lactic
acid inhibits L. moncytogenes growth
symprevius@adria.tm.fr
A decision making tool to predict microbial behavior during the food processes
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Probabilistic moduleInput/output
Microorganisms (Sym’Previus strains
and related data,OR your own strains
and data)
Food/microorganism(challenge test,
auto control data)
Food storage (T, pH profiles…)
Contamination evolution
Factor effect
Growth simulation
Sensitivity analysis
symprevius@adria.tm.fr
Minimum inputs for wide range of outputs !
A decision making tool to predict microbial behavior during the food processes
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Sym’Previus applicationPractical case
Auto control
data
Use your own data for a tailor-made approach!
Microbial hazard prevalence
Challenge test
data
Food matrix
Food product
weight
Dynamic
factors
Realistic conditions of
storage
Sales unit contamination
probability
symprevius@adria.tm.fr
A decision making tool to predict microbial behavior during the food processes
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Sym’Previus applicationPractical case
Auto control
data
Microbial hazard prevalence
Challenge test
data
Food matrix
Food product
weight
Dynamic
factors
Realistic conditions of
storage
Sales unit contamination
probability
6/247 (25g)
200 g 2
Use your own data for a tailor-made approach!
symprevius@adria.tm.fr
A decision making tool to predict microbial behavior during the food processes
a probability of 3 %
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Sym’Previus applicationPractical case
Auto control data 6/247 31% of contaminated sales unit!
9.6% of contaminated product
will exceed the criteria of 2 log
symprevius@adria.tm.fr
A decision making tool to predict microbial behavior during the food processes
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Sym’Previus applicationPractical case
symprevius@adria.tm.fr
A decision making tool to predict microbial behavior during the food processes
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The added values
symprevius@adria.tm.fr
A decision making tool to predict microbial behavior during the food processes
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Sym’Previus a constantlyevolving tool…
Risk-Benefit based probabilistic assessmentPoster presentation 83
5 10 15 20 25 30 35
3
3.5
4
4.5
5
5.5
6
6.5
7
7.5
NG
NG
NG
NG
NG
NG
G
G
G
G
G
G G G G G G G NG
G
G
G
G
NG
Temperature
pH
Mycotoxin production and Yeast interface growth / no growth
Mycoto
xin
-20
0
20
40
60
80
100
120
140
160
Growth boundaries andmycotoxin production area
Poster presentation 90
A decision making tool to predict microbial behavior during the food processes
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Sym’Previus a constantlyEvolving tool…
ICPMF8 - Paris 2013 -
See you at the friendly software-demonstration to
try Sym’Previus online
A decision making tool to predict microbial behavior during the food processes
…and enjoy your stay in Paris!
Feel free to contact our network of experts or symprevius@adria.tm.fr