Transcript Diapositive 1

A decision making tool
to predict microbial behavior
during the food processes
Sym’Previus :
Prediction of microbial behavior
during the food processes
Noémie Desriac
[email protected]
A decision making tool
to predict microbial behavior
during the food processes
Not ONLY a tool,
but as well a network!
UNIR
[email protected]
2
A decision making tool
to predict microbial behavior
during the food processes
Not ONLY a tool,
but as well a network!
Supported by the French food safety authorities
3
A decision making tool
to predict microbial behavior
during the food processes
Developed with food providers,
for food providers
°C
12
8
4
what is the impact of
adding a natural
preservative such as
lactic acid?
1.Food process
Determine the
impact of abuse
temperature
condition?
2.Transport &
delivery
[email protected]
Estimate the risk for
various scenarii
during food shelflife?
3.Food storage
4
A decision making tool
to predict microbial behavior
during the food processes
HACCP
assistance
Sym’Previus
toolbox
The Sym’Previus
tools
Probabilistic
module
Growth
interfaces
Thermal destruction
Growth
Bacterial survival
simulation
simulation
Growth curve
fitting
simulation
B. cereus group
affiliation (I-VII)
[email protected]
Database
5
A decision making tool
to predict microbial behavior
during the food processes
HACCP
assistance
Sym’Previus
toolbox
The Sym’Previus
tools
Probabilistic
module
Growth
interfaces
Thermal destruction
Growth
Bacterial survival
simulation
simulation
Growth curve
fitting
simulation
B. cereus group
affiliation (I-VII)
[email protected]
Database
6
A decision making tool
to predict microbial behavior
during the food processes
Sym’Previus
toolbox
Pathogen
microorganisms
Spoilage
microorganisms
9 species:
13 species:
Spore-formers/non Spore-formers
Spore-formers/non Spore-formers
Biodiversity
A wonderful world or… a brain teaser?!
7
A decision making tool
to predict microbial behavior
during the food processes
Sym’Previus
toolbox
Pathogenic
microorganisms
Spoilage
microorganisms
9 species:
13 species:
Spore-formers/non Spore-formers
Spore-formers/non Spore-formers
- Microbial diversity (up to 13 strains)
- Isolated from food product/ production environment
-Standardized protocols (ring trials)
…with wild strains coming from food production
units … and your own data-base
[email protected]
8
A decision making tool
to predict microbial behavior
during the food processes
Sym’Previus application
Practical case
Thawing
Preparation
Cooking
Cooling
Packaging
10h/8°C
2h/25°C
2h/90°C
Until 2°C in 2h
1h 4°C
pH=5.2
aw=0.99
Storage
1/3 at 4°C and
2/3 at 8°C
 Critical steps
(critical control point CCP)?
 Microbial hazards of concerns ?
[email protected]
9
A decision making tool
to predict microbial behavior
during the food processes
HACCP assistance
Input/ouput
Minimum inputs for wide range of outputs !
Microorganisms
(Sym’Previus possibilities)
Impact of each process
step on microorganism
Food properties
behavior
(growth/inactivation)
(pH, aw)
Food processes
The hazards of concerns
at each process step
(T, t, thawing, storage…)
[email protected]
10
A decision making tool
to predict microbial behavior
during the food processes
Sym’Previus application
Practical case
HACCP assistance :
11
A decision making tool
to predict microbial behavior
during the food processes
Sym’Previus application
Practical case
HACCP assistance :
12
A decision making tool
to predict microbial behavior
during the food processes
Sym’Previus application
Practical case
Critical steps = heat treatment
distribution/storage step
Got it!
L. monocytogenes = Of major concern during
shelf-life!
the
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)?
13
A decision making tool
to predict microbial behavior
during the food processes
Growth interfaces
Input/output
Minimum inputs for wide range of outputs !
Microorganisms
(Sym’Previus strains
and related data,
OR your own strains
and data)
Growth-no growth
interfaces
Food properties
(pH, aw)
Food storage
(T, lactate)
[email protected]
14
A decision making tool
to predict microbial behavior
during the food processes
Sym’Previus application
Practical case
Growth interfaces :
pH 5.2
aw=0.99
T=8°C
[email protected]
15
A decision making tool
to predict microbial behavior
during the food processes
Sym’Previus application
Practical case
Growth interfaces :
+
lactate
pH 5.2
aw=0.99
T=8°C
+Lactate
[email protected]
16
A decision making tool
to predict microbial behavior
during the food processes
Sym’Previus application
Practical 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

 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?
[email protected]
17
A decision making tool
to predict microbial behavior
during the food processes
Probabilistic module
Input/output
Minimum inputs for wide range of outputs !
Microorganisms
(Sym’Previus strains
and related data,
OR your own strains
and data)
Contamination evolution
Food/microorganism
Growth simulation
(challenge test,
auto control data)
Sensitivity analysis
Factor effect
Food storage
(T, pH profiles…)
[email protected]
18
A decision making tool
to predict microbial behavior
during the food processes
Sym’Previus application
Practical case
Use your own data for a
tailor-made approach!
Auto control
data
Challenge test
data
Realistic
conditions of
storage
Food matrix
Microbial hazard
prevalence
Dynamic
factors
Food product
weight
Sales unit
contamination
probability
[email protected]
19
A decision making tool
to predict microbial behavior
during the food processes
Sym’Previus application
Practical case
Use your own data for a
tailor-made approach!
Auto control
data
6/247
(25g)
Microbial hazard
prevalence
Challenge test
data
Food product
weight
200 g ± 2
Food matrix
Dynamic
factors
Realistic
conditions of
storage
Sales unit
contamination
probability
[email protected]
20
A decision making tool
to predict microbial behavior
during the food processes
Auto control data 6/247
Sym’Previus application
Practical case
31% of contaminated sales unit!
9.6%
of contaminated product
will exceed
the criteria of 2 log
a probability
of 3 %
[email protected]
21
A decision making tool
to predict microbial behavior
during the food processes
Sym’Previus application
Practical case
[email protected]
22
A decision making tool
to predict microbial behavior
during the food processes
The added values
[email protected]
23
A decision making tool
to predict microbial behavior
during the food processes
Growth boundaries and
mycotoxin production area
Poster presentation 90
Sym’Previus a constantly
evolving tool…
Risk-Benefit based
probabilistic assessment
Poster presentation 83
Mycotoxin production and Yeast interface growth / no growth
160
7.5
140
7 NG G
G
120
6.5
100
G
pH
80
5.5
60
5 NG
NG G
G NG
Mycotoxin
6 NG G
40
4.5
4 NG G
G
20
0
3.5
3 NG G G G G
5
10
G
15
G
G
20
25
Temperature
30
G NG
-20
35
24
A decision making tool
to predict microbial behavior
during the food processes
Sym’Previus a constantly
Evolving tool…
See you at the friendly
software-demonstration to
try Sym’Previus online
ICPMF8 - Paris 2013 -
25
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 [email protected]