Safety based shelf life for ready to eat
pre-packaged refrigerated foods
Cold Chain Management III
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QuickTime™ and a
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Bonn Germany June 2-3, 2008
QuickTime™ and a
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Dr. Ted Labuza & Dr. Francisco Diez & Dr. Amit Pal
University of Minnesota St Paul MN 55108
Slide # 1
Greetings from Minnesota, USA
We are 4.4 million
15,129 lakes
Two ocean going seaport ports
State bird is a mosquito
Rated one of best places to
live in USA but climate goes from
-35°C to +37°C
Slide # 3
What do we want to know ?
• Get the location of a case-lot of food in the cold
distribution chain in case of an adverse event
(eg. recall)
– ISO 9000-2000 Clause 3.5.4 Traceability is the ability to trace the
history or location of what is under consideration
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
• What is the shelf life left of the product at each
point in the distribution? “Quality”
• Is the food safe when we eat it, determined either
by sensors or by modeling the time-temperature
history in the cold chain?
Slide # 4
Expiration Dating of foods & Safety
The last package of
of hotdogs you sold
me was no good !!!
Did the
date expire ?
Mike’s
Hotdog
Stand
No, but the dog I gave it to
did !
Mike’s
Hotdog
Stand
Question of safety vs food quality
US regulatory Value of life = $6.5 MM
Slide # 5
U.S. Regulatory Stance on Shelf Life
• Federal Laws
– Required for drugs, OTC and infant formula
– Drugs 10% loss below label value on lower 95% CL line
– All other food products voluntary
• State laws
– 30 states regulate some dates (dairy, meat)
– Minnesota ≤ 90 days
– None based on safety , more for commerce
• GMA v Mass. Dept. Public Health
– 393 NE2nd 881 (1981)
– Court rules state can require dating based on public
health concerns re US Constitution
Slide # 6
EU Food Dating Rules
Directive 97/4/EEC Article 9 of 79/112/EEC
1.The date of minimum durability of a foodstuff shall be the
date until which the foodstuff retains its specific properties
when properly stored. It shall be indicated in accordance with
the provisions of this article.
2.The date shall be preceded by the words:
--“Best before…” when the date includes an indication of
the day,
--“Best before end…” in other cases
3. In the case of foodstuffs which, from the
microbiological point of view, are highly perishable and
are therefore likely after a short period to constitute an
immediate danger to human health, the date of minimum
durability shall be replaced by the “use by” date.
Slide # 7
Types of food dating
Code date
Born on date
Sell by date
Better if used by
Freeze by
Best when purchased by
Best if used by - minimum durability
Death date - use by (expiration)
Slide # 8
Temperature Abuse
• Szybist and Labuza 2001
– 100 homes
42°F = 5.6°C
Slide # 9
Taoukis study Greece
20
20
9
11
temperature ( C)
0
3
7
5
3
0
7
5
17
5
15
10
13
10
11
15
9
15
5
% of cases
te m pe r atur e ( oC)
Left: Temperature distribution in commercial chilled storage.
(Measurements in 150 supermarkets in the metropolitan area of Athens).
Right: Temperature distribution in domestic refrigerators. (Based on
measurements at 40 households).(Adapted from Taoukis et al., 1998.)
Slide # 10
So dates by themselves ignore t-T history in
refrigerated distribution
Thus to ensure safety
need t-T integration
Slide # 11
Degradation Kinetic parameters
• Rate of degradation as f(T)
• Arrhenius function ln rate vs 1/T in K --> Ea
• simple Ln time to X (or rate) vs temperature --> Q10
• Olley square root of rate vs T
100
ARRHENIUS PLOT TTI I
−E a
Ea
k = ko e
ln k = ln ko −
RT
logτ = τ r − bT
RT
k = A + bT
k
Or
10
TTD
1
3.2
3.3
3.4
3.5
3.6
3.7
3
1/Tx10 (K -1
)
Slide # 12
Sensory Shelf Life Plot of Skim Milk
500
marker problem
2x104
2x102
200
CFU/mL
CFU/mL
3x102
CFU/mL
4x107
CFU/mL
100
Hours
8x104
CFU/mL
50
Q10 ~ 5
10
0
2
4
6
8
10
Temperature °C
12
14
MN-SD Dairy Research Center
Slide # 13
Area under T vs t curve
Shelf life depends on the rate and temperature sensitivity
Ea or Q10, ie how much faster for a 10 °C increase in T
Slide # 14
Using kinetics
Hot dog Q10 = 3.3
ts 0°C = 90 days
%fconsumed =100 (t/ ts0°C ) x Q10 ΔT/10
% fcon=100(1/90) x 3.320/10 =10.7%
fcon =100 (20/90) x 3.31/10 = 25%
Slide # 15
Sensory of Skim Milk
Amount of Change for Q10 = 5 t 0°C=28 days
• for 1 day @ 20°C
• %fconsumed =100 (1/ 28 )x 6 20/10 =128% (long dead)
• for 20 days at 1°C
• %fconsumed = 100 (20/28) x 6 1/10
= 85% or 4 days left @1°C
Slide # 16
Time Temperature Integration
• Combine T vs t, k and Ea or Q10 functions in
algorithm
– Temperature vs time measurement
– Algorithm for Reaction extent as f(t,T)
– Use an integrating tag TTI
T °C
Δt
time
Slide # 17
USDA -FSIS 1998
Guidance for Beef Grinders to Better Protect
Public Health
Guidance for Minimizing Impact Associated with a
Food Safety Hazard in Raw Ground
Meat and Other FSIS Regulated Products
Install a time-temperature indicator on the package to
indicate adequate temperature of storage, distribution,
and display (in grocery and other retail establishments).
Slide # 18
Shelf Life plots food or drug vs tag
shelf life
shelf life
Log time
TTI
TTI
Temperature
Temperature
shelf life
Log time
TTI
TTI
shelf life
Temperature
Temperature
Illustration of proper and improper TTI design
Slide # 19
Shelf Life Dating Warnings
• August 1998 Prevention Magazine - NBC survey
– 61% feel sell by is last date to safely sell
– 34% feel use by is last date to safely use
• 1999 US IFT document to RCs related to safety through
label date
• 1999 National Enquirer
– Use by date is a stern warning on meats, poultry, fish and other
perishables. Pay close attention and do not use once date is
passed
• Food Technology July 1999 “Playing the Open Dating
Game” Ted Labuza and Lynn Szybist
Slide # 20
• FIFO vs LSFO system Taoukis et al
– ≥15% savings (EU programs including SMAS)
– Taoukis, P.S., Bili M., Giannakourou M. (1998). “Application of shelf life
modelling of chilled salad products to a TTI based distribution and stock
rotation system.“ Proceedings of the International Symposium on Applications
of Modelling as an Innovative Technology in the Agri-Food-Chain Ed. L.M.M.
Tijskens, Wageningen, Netherlands, p. 131-140.
– Case study with fish in Greece to Italy chain store
– Basis for formation of SMAS
•
•
http://www.vitsab.com/htdocs/default.htm
Contact [email protected]
Slide # 21
% Life Consumed
TTI Center Box
Time (h)
TTI Top Box
out
Inside
box
Center
of box
out
Inside
box
Center
of box
60%
40%
20%
70%
45%
25%
85%
50%
25%
>100%
75%
40%
>100%
90%
45%
>100%
>100%
60%
48
78
120
Field Test : Monitoring seabream exported from Greece to Italy
Note test showed if use LSFO increase profit by 15%
Slide # 22
Theoretical Probability of Reduction in illness using LSFO
0.50
FIFO
Probability
Probability
0.40
SMAS
0.30
0.20
0.10
0.00
-16
-14
-12
-10
-8
-6
-4
-2
0
-0.10
Log probability of illness
To prove it need data for growth of pathogens or
toxin production
Slide # 23
Slide # 24
1. What are the scientific parameters for establishing safetybased ‘‘use-by’’ date labels for refrigerated RTE foods?
2. What effect do the multiple factors that influence the
growth and survival of L. monocytogenes, i.e., strain
differences, food matrices, production and distribution
systems, consumer susceptibility, etc., have on the
establishment of safety based ‘‘use-by’’ date labels for
refrigerated RTE foods?
3. What data need to be acquired to scientifically validate and
verify the adequacy of a proposed safety-based ‘‘use-by’’
date label for a refrigerated RTE food?
Note sushi/sashimi are RTE consumed as raw
products as are oysters
Slide # 25
4. Should safety-based ‘‘use-by’’ date labels for refrigerated
RTE foods be established using mathematical modeling
techniques? If so, what modeling approaches are best suited
to the development of labels for refrigerated RTE foods?
5. What impact would safety-based ‘‘use-by’’ date labels
created for one psychrotrophic pathogen, e.g., L.
monocytogenes, likely have on the control of other
foodborne pathogens in refrigerated RTE foods?
Note that in US under FDA, Listeria is an adulterant so if you detect it (1
CFU/25 g) then the food is considered adulterated while EU & Canada rules
allow up to 100 CFU/g or 2500 per 25 g in a food as long as it does not allow
growth above that.
Slide # 26
Time-to-Detect (TTD) Concept
™ Growth from initial counts
below detection since if
present is adulterated
(TTD)
™ or growth to 100 CFU/g
™ Or time to + toxin
¾ Vital to satisfy FSO
(food safety objective)
Limit time = TTD (conservative) or
Limit time = TTD + λ
Dispatch
Shelf life →
TTD
+ [ln(N/No)]/μ
Or just assume growth rate below
detection is same as above starting at
some probable level for No
Baranyi and Pin, 1999
Slide # 27
Days to detect botulinum toxin in CAP/MAP
partially cooked fish
Days
Baker & Genigeorgis 1990
100
Safety Line
10
Q10 ~ 4
Ea ~ 21.3 Kcal/mole
1.0
0.1
0
10
20
30
Temperature °C
40
Slide # 28
Shelf Life and Storage Conditions
™ Shelf life of frankfurters and other deli meats: ≤ 90 days at X°C
™ At 5 °C, mean generation time of Lm from math modeling program
¾ 1.77 days in frankfurters or 12 days to reach 100 CFU/g @ 5°C
¾ 2.45 days in deli meats or 16 days
(US FDA/CFSAN, USDA/FSIS & CDC, 2003)
™ The risks from Lm could be considered minimal if
Initial contamination No with Lm is at very low levels (≤10-5 CFU/g)
No temperature/time abuse during storage
If assume same growth rate at below detection then at No = 10-5
TTD = [ ln (1/No)] x G/0.693 or for hotdogs TTD is 29 days @ 5°C and
at No = 10-6 it is 35 days
¾ Seems too short or likely growth rate much less
REALITY
¾
¾
¾
¾
™ 69-78% of consumers store opened packages of deli meats for a week
¾ 10-13% for 1-3 weeks in their refrigerators so vacuum lost
(USDA-FSIS, 2006)
¾ USDA-FSIS noted in BilMar outbreak that contaminated hotdogs were consumed
near or beyond end of shelf life labeled on package
Slide # 29
Shelf Life Evaluation of Ready-to-Eat
Meat and Poultry Products based on
Listeria monocytogenes growth
Dan Belina MS & Amit Pal Ph.D.
Slide # 30
RTE Meat Processing
Trimming
Cooler &
Peeler
Blender
Stuffer
Smoking/
Cooking
Weighing &
Sorting
Vacuum
Packing
CONSUMER
Source: http://www.hotdogcartsdirect.com/how_hot_dogs_are_made.htm
Slide # 31
Safety-Based Shelf life Dating (SBDL)
• Strain differences
• Food matrices
• Competing microflora and packaging
• Production, distribution, and handling practices
• Consumer susceptibility
• Initial level
• Growth kinetics
™Lm contamination levels in RTE meats are mostly <10 CFU/g
(Gombas et al., 2003; Draughon et al., 2006)
Slide # 32
So what temperature should date be based on?
™ Audits International, 1999
Lunch Meat Temperature (°F)
Home (%)
Retail (%)
< 32
9
4
33 – 35
10
3
36 – 38
25
10
39 – 41
29
23
42 – 44
18
22
45 – 47
5
12
48 – 50
3
15
51 – 53
0.4
4
54 – 56
0.5
3
57 – 59
0.4
2
60 – 63
0.1
1.3
™ 13% door and 4% bottom of the household refrigerators >45°F
Godwin et al, 2007
(>7.2 °C)
Slide # 33
Inoculum Size and TTD
TTD (hours)
Robinson et al., 2001
TSB
1.2 M NaCl in TSB
Inoculum size Log (cells/mL)
™ Fuqua et al., 1994; Robinson et al., 2001
™ Note Ln(1/No) = [0.693/G] x time
™ This data suggests the model works with constant G and thus could model to level at
below detection.
Slide # 34
PRELIMINARY STUDY
™ Francisco Diez-Gonzalez, Daniel Belina, Theodore P. Labuza and Amit Pal.
Modeling the Growth of Listeria monocytogenes Based on the Time-to-Detect in
Culture Media and Frankfurters Intl. J. Food Microbiology 113:277-283; 2007
™
™
™
™
™
™
Listeria monocytogenes H7776
Implicated in hotdog outbreak
Growth part No = 5 CFU/g
TTD part No= 0.01 CFU/g or 0.25 CFU/25 g ie less than detection
Six temperatures 4 to 36°C
Two media
¾ TSB broth
¾ HPP processed hotdogs
Slide # 35
Phase 1 preliminary evaluation in TSB broth shows can work
L. mono Time to Detection
2
R = 0.9324
1000
Q10 ~ 3.5
Hours
100
10
1
0
10
20
30
40
Temp (C)
Slide # 36
Phase 1
TTD in hot dogs
Ln Q10 =(Ea x 10)/[R T1T2]
Q10 = 3.45
Slide # 37
Arrhenius plots of TTD
TSB
R2 ~ 0.91
hotdogs R2 ~ 0.96
Slide # 38
18°C Growth Curve
TSB
so time to 100 ~1 day
Stationary phase
10
9
Log Log
CFU/m
L
CFU /mL
8
7
6
5
Log phase
7.9 hours per log
k =0.293 hr-1
Lag = 13 hr
4
3
time to 102 = 25 hr
2
1
0
0
20
40
60
80
100
120
Hours
Slide # 39
Summary of growth data
9 days
29 days
Note at 4°C (39.2°F) G is ~ 33 hr much longer than USDA
model of 1.77 hr
Slide # 40
Summary of temperature effect
Q10
4.39
3.35
Q10
3.32
7.2
4.01
9.68
™ Note that this means just can’t use one Q10 or use largest
one which would mean throwing away good food
Slide # 41
Phase 2 Finding fastest growers
™ Total 19 Lm ribotypes (ID by DUP-XXXX) with 2 reps
109 CFU/ml
+
1 part frank OR
turkey breast
×2
3 part PW
103-4 CFU/ml
With or
without
PL/SD
Plate
Counting
on PALCAM
4 °C
Stomached to slurry
8 °C
12 °C
30 ml slurry × 2
Slide # 42
Growth Models
Transformation → y = (N/No)
[ μ ( t -λ )]
Linear
y = exp
t>λ
y =1
t<λ
Growth curve
y = µt + c
No
Lag time
Time
λ = [Ln(No) – c] / µ
Gompertz
Logistic
y = A. exp
[-exp
μ .e
A
( λ -t)+1]
]
A
y=
1 + exp[
Baranyi
[
4μ
(λ − t ) + 2]
A
e μA(t) + 1
y = yo + μA(t)- ln(1+ (ymax − yo ) )
e
A(t ) = t +
1
μ
ln(eμt + e−μλ − e−μ (t +λ ) )
Slide # 43
Listeria monocytogenes Strains
• Three strains used
− Provided by Dr. M. Weidman’s ILSI Listeria database, Cornell
University
− Selected based on their manifesting the fastest growth characteristics
on culture media and a frankfurter slurry
• DUP-1044A
− 1998-99, multistate outbreak, frankfurter, 4b
• DUP-1042B
− 2000, epidemic, Mexican style cheese, 4b
• DUP-1039C
− 1998, sporadic, human, 3a
Slide # 44
Phase 2 Findings
™ No significant difference between model performances (P > 0.05)
™ So use the simplest ln N/No vs time
™ Variability in lag times and maximum growth rates was not similar
among strains –
™ No single strain consistently had the fastest growth at all growth
conditions on broth or meat slurries
¾ fastest strains selected were: DUP-1044A, 1039C, 1030A, and 1042B
™ No definitive link between serotype and fastest strains
™ Average lag Q10 = 7.6 and Average Log phase Q10 = 7
™ Time to 102 Q10 = 7.4
Pal, A, Labuza, T.P. and Diez-Gonzalez. F. Comparison of Primary Predictive Models
Study the Growth of Listeria monocytogenes at Low-Temperatures in Liquid Cultures and
Selection of Fastest Growing Ribotypes in Meat and Turkey Product Slurries
J. Food Microbiology 25:460-470; 2008
Slide # 45
Phase 3 Growth on Frankfurters
~52.44 g and 121.9 cm2
109
CFU/ml
0.1 ml rinse or 1 ml in 4 plates
4 °C
8 °C
102 CFU
12 °C
×2
×2
20 ml PW
40 sec rinse
×2
Lm
Psychrotrophs
Counting
Counting
on PALCAM
on PCA
Using the 3 fastest growers in air vs vacuum, w/wo
antimicrobial, & each w/wo competition with psychrotrops
at 39.2, 46.4 & 53.6 °F
Initial No at < 2 CFU/g (0.3 Log) ie less than 100 CFU/gSlide # 46
DUP-1044A at 4 °C (Vacuum packaged)
Control (V)
HPP (V)
PL/SD + HPP (V)
PL/SD (V)
8
2
log10(CFU/cm )
10
6
Sig. Diff.
between
HPP and
control
4
2
Survived
but
no growth
0
-2
0
20
40
60
Time (days)
80
100
V vacuum packed
HPP slices treated in package at 400 MPa (15 min) for 106 reduction, then inoculated
PL/SD 2%Potassium acetate + 0.2% Na-Lactate in meat formula
Slide # 47
DUP-1044A at 12 °C (Vacuum packaged)
Control (V)
HPP (V)
PL/SD + HPP (V)
PL/SD (V)
2
log10(CFU/cm )
10
8
6
>3
log(CFU/cm2)
4
2
0
25 days vs label of 90 days but
started at above detection
-2
0
20
Time (days)
40
60
Slide # 48
Lm vs PPC – Comparison at 8°C
10
8°C-vacuum
8
(□) HPP
(○) Control
Listeria monocytogenes
growth - Safety Indicator
6
4
2
(♦) PL/SD + HPP
0
(▲) PL/SD
-2
0
20
40
60
80
10
(□) HPP
8°C-vacuum
8
Psychotrophs growth Spoilage Indicator
Q10 ~ 6
(○) Control
6
(▲) PL/SD
4
(♦) PL/SD + HPP
2
0
-2
(♦) PL/SD + HPP
(▲) PL/SD
(□) HPP
(○) Control
0
20
40
60
80
Slide # 49
Phase 3 Results Summary
Time to 100-fold Listeria population
With
Without
‘P Lact. + Sod. Diac.’
‘P Lact. + Sod. Diac.’
Franks
oC
4
8
12
4
Psy 45 day
8
Psy 18 day
12
Psy 6 day
Q10 = 6
DUP1044A
NG
NG
18-25
22-44*
3-5*
2-3*
DUP1042B
NG
DUP1039C
NG
Strain
Q10 = 4.7
NG-65 (air
packaging)
NG-21 (air
packaging)
19-49*
NG
NG
18-45*
5-12*
3-6*
Q10 = 4.7
8-10*
4-7*
Q10 = 4.7
NG: No Growth ≤ 1 log growth in >90 days psy = 106psychrotrops
Slide # 50
Phase 3 Findings
™ Lm growth strain dependent so which one do we use for standard ?
™ Even with PL/SD, Lm DUP-1044 was able to grow to 102 CFU/g but longer
than quality-based shelf life of 6 days at 12 °C
™ Without the PL/SD, pathogen level to 100 CFU/g occurs before spoilageat
all temps whereas in fish@ < 10°C, bot toxin slower than spoilage Reddy
et al 1999
™ Results could be used to create a safety based tag but would need to
account for initial levels below the detection limit
Pal, A, Labuza, T.P. and Diez-Gonzalez. F. Evaluating the growth of
Listeria monocytogenes in refrigerated ready-to-eat frankfurters –
Influence of strain, temperature, packaging, lactate and diacetate, and
background microflora. (J. Food Protection accepted – in press) 2008
Slide # 51
Phase 4 TTD Modeling
Assumption 100 lb = 1000 g
25 g = 0.55 g
~10 CFU (DUP-1044A)
Size
(g)
0.55 g × 3
No
(CFU/25g)
100
2.5
250
1
1000
0.25
1500
0.18
37 °C for 48 h
+
+
5 ml PDX-LIB
MOX
agar
™ True positive = when at least two out of the three replicates showed
confirmed presence
™ Sampling frequency: 3 days (4 °C), 2 days (8 °C), and 1 day (12 °C)
™ TTD = first out of three consecutive positive samples
Slide # 52
TTD (days) vs. Inoculum size (Ln No)
60.0
a
a
TTD = -3.95 ln(No) + 32.09
2
R = 0.97
50.0
b
40.0
10.0
a
a
8.0
TTD = -1.24 ln(No) + 1.92
2
R = 0.89
a
6.0
b
4 °C
4.0
2.0
30.0
b
8 °C
0.0
-5.50
-4.50
0.007
0.01
-3.50
-2.50
0.04
-5.50
-4.50
-3.50
-2.50
0.1 CFU/g
6.0
Observed TTD
Expected TTD (Phase 2 data)
Safe growth limit
TTDs with common letter are not significantly
different (P > 0.05) from pair-wise t-test
4.0
a
TTD = -0.62 ln(No) + 0.56
2
R = 0.95
a
ab
2.0
b
12 °C
0.0
-5.50
-4.50
-3.50
-2.50
Slide # 53
Shelf Life Model (TTD vs Temp.)
ShelfLife T = ShelfLife o exp( − bT )
0.1 CFU/g
0.04 CFU/g
0.01 CFU/g
Guadagni, 1968; Labuza, 1972
0.007 CFU/g
100.0
47 days
TTD (days)
23 days
TTD1 = 185.17e-0.34T
R2 = 0.96
10.0
6 days
Q10= 31
TTD2 = 151.84e-0.38T
3.4 days
R2 = 0.93
Q10= 24
1.0
2
4
6
8
10
12
14
Temperature (°C)
Q10 = exp(10bT )
Slide # 54
Phase 5 Findings
™ Significant difference between TTDs existed when the inoculum
sizes differed by at least 2-log (P < 0.05) but followed expected
pattern of log No vs time
™ The Q10 values for the TTD of Listeria shelf life plot ranged from 24
to 31 while lag and growth phase was about 7 in slurry and 4.6 on
hotdog
™ Q10 values change with process, composition, matrix and packaging
™ We cannot design the proper safety tag without agreement on the
right input data and would need a dual tag for safety & shelf life!
Slide # 55
Micro-electronic TTI tag
• Infratab (US) (www.infratab.com)
– Micro-electronic TTI integrator
• RFID capability for traceability
• US Patent # 5,442,669
• ePC global compatible
– Possible to program for all 3 growth
phases which one cannot do with
chemical tag
Slide # 56
References
• Audits International/FDA. 2006. U.S. food temperature evaluation. Available at:
http://www.foodrisk.org/Audits-FDA_temp_study.htm. Accessed 12 June 2007.
• Center for Food Safety and Applied Nutrition, Food Safety and Inspection Service, Centers for Disease
Control and Prevention. 2003. Quantitative assessment of the relative risk to public health from
foodborne Listeria monocytogenes among selected categories of ready-to-eat foods. Washington, D.C.:
U.S. Department of Health and Human Services and U.S. Department of Agriculture. Available at:
http://www.foodsafety.gov/~dms/lmr2-toc.html. Accessed 12 June 2007.
• Mead, P. S., L. Slutsker, V. Dietz, L. F. McCaig, J. S. Bresee, C. Shapiro, P. M. Griffin, and R. V. Tauxe.
1999. Food-related illness and death in the United States. Emerg. Infect. Dis. 5:607-625.
• NACMSF. 2005. Considerations for establishing safety-based consume-by date labels for refrigerated
ready-to-eat foods. J. Food Prot. 68:1761-1775.
• Pleasant, A.B., Soboleva, T.K., Dykes, G.A., Jones, R.J., and Filippov, A.E. 2001. Modelling of the
growth of Listeria monocytogenes and a bacteriocin-producing strain of Lactobacillus in pure and mixed
cultures. Food Microbiol. 18:605-615.
• Reddy, N. R., H. M. Solomon, and E. J. Rhodehamel. 1999. Comparison of margin of safety between
sensory spoilage and onset of Clostridium botulinum toxin development during storage of modified
atmosphere(MA)-packaged fresh marine cod fillets with MA-packaged aquacultured fish fillets. J. Food
Saf. 19:171-183.
• USDA-FSIS. 2006. Consumer attitudes and behaviors regarding ready-to-eat foods. Available at:
http://www.fsis.usda.gov/OPPDE/rdad/FRPubs/02-041N/conley_lm.htm. Accessed 12 June 2007.
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Contact
Dr. Theodore Labuza
Department of Food Science and Nutrition
University of Minnesota
[email protected]
612-624-9701 fax 651-483-3302 cell 651-307-2985
http://www.ardilla.umn.edu/Ted_Labuza
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