Study and mathematical description of the kinetics of microbial spoilage of
foods by thermophilic endosporeendospore-forming microorganisms
MYRSINI KAKAGIANNI (PhD candidate)
Laboratory of Food Microbiology and Hygiene, Department of Food Science and Technology, School of Agriculture,
Faculty of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, Thessaloniki, Greece
(mkakagianni@agro.auth.gr
mkakagianni@agro.auth.gr))
Food Microbiology and Hygiene (Head: K. Koutsoumanis
Koutsoumanis))
Aristotle University of Thessaloniki (1925)
Faculty of Agriculture, Forestry and Natural Environment Maria Gougouli (PostDoc Researcher), Myrsini Kakagianni (PhD candidate),
Zafeiro Aspridou (PhD candidate)
School of Agriculture (1928) (http://www.agro.auth.gr
http://www.agro.auth.gr//)
Department of Food Science and Technology (1982)
Research Interests
Quantitative (Predictive) Microbiology, Microbial Risk Assessment, Stochastic approaches
in Food Quality and Safety, Food Quality and Safety Management Systems (ISO HACCP),
Food Processing and Engineering
Decision support systems for quality and safety optimisation, Development and application
of novel methods for food preservation, Time Temperature Indicators (TTI) for monitoring
Food Chemistry and Biochemistry
food quality and safety, Microbial physiology, Microbial spoilage of foods, Single cell
http://food--science.agro.auth.gr
science.agro.auth.gr//) microbiology
Dairy Technology (http://food
Observed μmax
Predicted μmax
95% Confidence Limits (CL)
3,0
2,0
Adjustment of the models to
foods
Acid coagulation in evaporated
milk by Gs
Determination of time
time--to
to-spoilage (tts
ttsobs) based on
experimental data (Topt=62°C)
Validation under dynamic
temperature scenarios in
evaporated milk (Gs) and fruit
juices (Aac)
Gs
μmax
pH = 5.2
Gs
10
40
50
60
70
Temperature (°C)
80
Effect of pH on A. acidoterrestris
growth
Observed μmax
Predicted μmax
95% Confidence Limits (CL)
1,4
1,2
1,0
0,8
0,6
0,4
0,2
0,0
8
6,0
4
2
0
2
4
6 8 10 12 14
Time (h)
Guaiacol production in fruit juice
by Aac (Topt=48°C)
Determination of ttsobs based on
literature
2 2,5 3 3,5 4 4,5 5 5,5 6 6,5 7
pH
(T)
+ 10gt(T)
tNmax: time interval from inoculation until
population reaches Nmax
Observed spoilage: 10*gt
10 (T) after population
reaches Nmax
7
7,0
10
60
5,0
0
Aac
5,5
ttsobs
ttspred = tNmax
6,5
6
μmaxmilk(62°C) x ρ(T)
Prediction of time-to-spoilage (ttspred)
7,0
8
7
50
6,5
6
6
40
6
6,0
30
5
5,0
20
5
4,5
4
2
0
- - - pH
---- temperature
5,5
0 10 20 30 40 50 60 70 80
Time (h)
Nmax = 5-6 log10 cfu/ml
Predictive modelling approaches
TOOLS
Quantitative Microbial
Risk Assessment
@Risk
Estimation of risk of evaporated milk spoilage at the end of
the shelfshelf-life in the market of various countries
Estimation of risk of fruit juices spoilage at the end of the
shelf--life in the market of Greece
shelf
Deterministic and
Probabilistic modelling
during storage
Deterministic approach
Stochastic approach
Temperature-time storage conditions
Sources of variability
Initial population level (No)
Probability
30
Log10 CFU/ml
0,0
Bacterial growth Acid
pH
coagulation
Spoilage level
=
Log10 CFU/ml
1,0
0,5
μmax (1/h)
Prediction of bacterial growth
Nmax = 7.5 log10 cfu/ml
1,5
pH
μmax (1/h)
2,5
Relation between microbial
growth and food spoilage
pH
Effect of temperature on
Geobacillus stearothermophilus
(Gs) and Alicyclobacillus
acidoterrestris (Aac) growth
Temperature (°C)
Model development in broth
0,25
0,20
0,15
0,10
0,05
0,00
Individual behavior of bacterial spores (lag phase)
“With the support of the Erasmus+ programme of the European Union,
Project No: 2014
2014--1-MT01
MT01--KA200
KA200--000327”
Morocco
(2009-2013)
(2009-
0,0 1,4 2,7 4,1 5,4 6,8
N(t) (log10 cfu/ml)