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A decision making tool
to predict microbial behavior
during the food processes
Sym’Previus :
Prediction of microbial behavior
during the food processes
Noémie Desriac
symprevius@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
C
12
8
4
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
5
Sym’Previus
toolbox
HACCP
assistance
Probabilistic
module
Thermal destruction
simulation
Bacterial survival
simulation
B. cereus group
affiliation (I-VII)
Database
Growth
interfaces
Growth
simulation
Growth curve
fitting
The Sym’Previus
tools
symprevius@adria.tm.fr
A decision making tool
to predict microbial behavior
during the food processes
6
Sym’Previus
toolbox
HACCP
assistance
Probabilistic
module
Thermal destruction
simulation
Bacterial survival
simulation
B. cereus group
affiliation (I-VII)
Database
Growth
interfaces
Growth
simulation
Growth curve
fitting
The Sym’Previus
tools
symprevius@adria.tm.fr
A decision making tool
to predict microbial behavior
during the food processes
7
Pathogen
microorganisms
Spoilage
microorganisms
9 species:
Spore-formers/non Spore-formers
13 species:
Spore-formers/non Spore-formers
Sym’Previus
toolbox
Biodiversity
A wonderful world or… a brain teaser?!
A decision making tool
to predict microbial behavior
during the food processes
8
Sym’Previus
toolbox
…with wild strains coming from food production
units … and your own data-base
Pathogenic
microorganisms
Spoilage
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
9
Sym’Previus application
Practical case
 Critical steps
(critical control point CCP)?
 Microbial hazards of concerns ?
pH=5.2
aw=0.99
Thawing
10h/8 C
Preparation
2h/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
10
HACCP assistance
Input/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 application
Practical case
A decision making tool
to predict microbial behavior
during the food processes
12
Sym’Previus application
Practical case
HACCP assistance :
A decision making tool
to predict microbial behavior
during the food processes
13
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 application
Practical case
Critical steps = heat treatment
distribution/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
14
Growth interfaces
Input/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
15
Growth interfaces :
pH 5.2
aw=0.99
T=8 C
Sym’Previus application
Practical case
symprevius@adria.tm.fr
A decision making tool
to predict microbial behavior
during the food processes
16
pH 5.2
aw=0.99
T=8 C
+Lactate
Sym’Previus application
Practical case
symprevius@adria.tm.fr
Growth interfaces :
+
lactate
A decision making tool
to predict microbial behavior
during the food processes
17
 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 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 
symprevius@adria.tm.fr
A decision making tool
to predict microbial behavior
during the food processes
18
Probabilistic module
Input/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
19
Sym’Previus application
Practical 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
20
Sym’Previus application
Practical 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 %
21
Sym’Previus application
Practical 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
22
Sym’Previus application
Practical case
symprevius@adria.tm.fr
A decision making tool
to predict microbial behavior
during the food processes
23
The added values
symprevius@adria.tm.fr
A decision making tool
to predict microbial behavior
during the food processes
24
Sym’Previus a constantly
evolving tool…
Risk-Benefit based
probabilistic assessment
Poster 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
Mycotoxin
-20
0
20
40
60
80
100
120
140
160
Growth boundaries and
mycotoxin production area
Poster presentation 90
A decision making tool
to predict microbial behavior
during the food processes
25
Sym’Previus a constantly
Evolving 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

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Sym'previus predictive microbiology software

  • 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 symprevius@adria.tm.fr
  • 2. 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
  • 3. 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
  • 4. A decision making tool to predict microbial behavior during the food processes symprevius@adria.tm.fr 4 1.Food process C 12 8 4 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?
  • 5. A decision making tool to predict microbial behavior during the food processes 5 Sym’Previus toolbox HACCP assistance Probabilistic module Thermal destruction simulation Bacterial survival simulation B. cereus group affiliation (I-VII) Database Growth interfaces Growth simulation Growth curve fitting The Sym’Previus tools symprevius@adria.tm.fr
  • 6. A decision making tool to predict microbial behavior during the food processes 6 Sym’Previus toolbox HACCP assistance Probabilistic module Thermal destruction simulation Bacterial survival simulation B. cereus group affiliation (I-VII) Database Growth interfaces Growth simulation Growth curve fitting The Sym’Previus tools symprevius@adria.tm.fr
  • 7. A decision making tool to predict microbial behavior during the food processes 7 Pathogen microorganisms Spoilage microorganisms 9 species: Spore-formers/non Spore-formers 13 species: Spore-formers/non Spore-formers Sym’Previus toolbox Biodiversity A wonderful world or… a brain teaser?!
  • 8. A decision making tool to predict microbial behavior during the food processes 8 Sym’Previus toolbox …with wild strains coming from food production units … and your own data-base Pathogenic microorganisms Spoilage 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
  • 9. A decision making tool to predict microbial behavior during the food processes 9 Sym’Previus application Practical case  Critical steps (critical control point CCP)?  Microbial hazards of concerns ? pH=5.2 aw=0.99 Thawing 10h/8 C Preparation 2h/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
  • 10. A decision making tool to predict microbial behavior during the food processes 10 HACCP assistance Input/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 !
  • 11. A decision making tool to predict microbial behavior during the food processes 11 HACCP assistance : Sym’Previus application Practical case
  • 12. A decision making tool to predict microbial behavior during the food processes 12 Sym’Previus application Practical case HACCP assistance :
  • 13. A decision making tool to predict microbial behavior during the food processes 13 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 application Practical case Critical steps = heat treatment distribution/storage step L. monocytogenes = Of major concern during the shelf-life! Got it!
  • 14. A decision making tool to predict microbial behavior during the food processes 14 Growth interfaces Input/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 !
  • 15. A decision making tool to predict microbial behavior during the food processes 15 Growth interfaces : pH 5.2 aw=0.99 T=8 C Sym’Previus application Practical case symprevius@adria.tm.fr
  • 16. A decision making tool to predict microbial behavior during the food processes 16 pH 5.2 aw=0.99 T=8 C +Lactate Sym’Previus application Practical case symprevius@adria.tm.fr Growth interfaces : + lactate
  • 17. A decision making tool to predict microbial behavior during the food processes 17  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 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  symprevius@adria.tm.fr
  • 18. A decision making tool to predict microbial behavior during the food processes 18 Probabilistic module Input/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 !
  • 19. A decision making tool to predict microbial behavior during the food processes 19 Sym’Previus application Practical 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
  • 20. A decision making tool to predict microbial behavior during the food processes 20 Sym’Previus application Practical 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
  • 21. A decision making tool to predict microbial behavior during the food processes a probability of 3 % 21 Sym’Previus application Practical 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
  • 22. A decision making tool to predict microbial behavior during the food processes 22 Sym’Previus application Practical case symprevius@adria.tm.fr
  • 23. A decision making tool to predict microbial behavior during the food processes 23 The added values symprevius@adria.tm.fr
  • 24. A decision making tool to predict microbial behavior during the food processes 24 Sym’Previus a constantly evolving tool… Risk-Benefit based probabilistic assessment Poster 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 Mycotoxin -20 0 20 40 60 80 100 120 140 160 Growth boundaries and mycotoxin production area Poster presentation 90
  • 25. A decision making tool to predict microbial behavior during the food processes 25 Sym’Previus a constantly Evolving tool… ICPMF8 - Paris 2013 - See you at the friendly software-demonstration to try Sym’Previus online
  • 26. 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