1Slide #

Safety based shelf life for ready to eatpre-packaged refrigerated foods

Cold Chain Management III

Bonn Germany June 2-3, 2008

Dr. Ted Labuza & Dr. Francisco Diez & Dr. Amit Pal

University of Minnesota St Paul MN 55108

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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

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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

• 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?

QuickTime™ and aTIFF (Uncompressed) decompressor

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5Slide #

Expiration Dating of foods & Safety

The last package of of hotdogs you sold me was no good !!!

Did the date expire ?

No, but the dog I gave it to did !

Mike’s Hotdog Stand

Mike’s Hotdog Stand

Question of safety vs food quality

US regulatory Value of life = $6.5 MM

6Slide #

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

7Slide #

EU Food Dating RulesDirective 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.

8Slide #

Types of food datingCode 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)

9Slide #

Temperature Abuse• Szybist and Labuza 2001

– 100 homes

42°F = 5.6°C

10Slide #

Taoukis study Greece

0

5

10

15

203 5 7 9 11 13 15 17

temperature (�C)

% of cases

0

5

10

15

20

3 5 7 9 11

tem perature (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.)

11Slide #

So dates by themselves ignore t-T history in refrigerated distribution

Thus to ensure safety need t-T integration

12Slide #

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

k = koe−Ea

RT lnk = lnko −Ea

RTlogτ = τ r − bT

k = A + bT3.73.63.53.43.33.2

1

10

100

ARRHENIUS PLOT TTI I

1/Tx10 (K )3

-1

k

Or

TTD

13Slide #

0 2 4 6 8 10 12 1410

50

100200500

Hours

Temperature °C

Sensory Shelf Life Plot of Skim Milkmarker problem

2x102CFU/mL 3x102

CFU/mL

2x104CFU/mL

4x107CFU/mL

8x104CFU/mL

Q10 ~ 5

MN-SD Dairy Research Center

14Slide #

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

15Slide #

Using kinetics

% fcon=100(1/90) x 3.320/10 =10.7%

fcon =100 (20/90) x 3.31/10 = 25%

Hot dog Q10 = 3.3 ts 0°C = 90 days

%fconsumed =100 (t/ ts0°C ) x Q10ΔT/10

16Slide #

Sensory of Skim MilkAmount 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

17Slide #

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

time

T °CΔt

18Slide #

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).

19Slide #

Shelf Life plots food or drug vs tag

TTIshelf life

Temperature

shelf life

Temperature

shelf life

Temperature

shelf life

Temperature

Log time

Log time TTITTI

TTI

Illustration of proper and improper TTI design

20Slide #

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

21Slide #

• 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 Taoukis@orfeas.chemeng.ntua.gr

22Slide #

% Life Consumed

Field Test : Monitoring seabream exported from Greece to Italy

Note test showed if use LSFO increase profit by 15%

TTI Center Box TTI Top Box

Time (h) out Inside box

Center of box

out Inside box

Center of box

4860% 40% 20% 70% 45% 25%

7885% 50% 25% >100% 75% 40%

120>100% 90% 45% >100% >100% 60%

23Slide #

-0.10

0.00

0.10

0.20

0.30

0.40

0.50

-16 -14 -12 -10 -8 -6 -4 -2 0

Log probability of illness

Pro

babi

lity

FIFOSMAS

Theoretical Probability of Reduction in illness using LSFO

To prove it need data for growth of pathogens or toxin production

Pro

babi

lity

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25Slide #

1. What are the scientific parameters for establishing safety-based ‘‘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

26Slide #

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.

27Slide #

TimeTime--toto--Detect (TTD) ConceptDetect (TTD) ConceptGrowth from initial counts below detection since if present is adulterated (TTD)or growth to 100 CFU/gOr time to + toxin

Vital to satisfy FSO (food safety objective)

Baranyi and Pin, 1999

Limit time = TTD (conservative) or

Limit time = TTD + λ + [ln(N/No)]/μ

Or just assume growth rate below detection is same as above starting at some probable level for No

TTDDispatch Shelf life →

28Slide #

Days to detect botulinum toxin in CAP/MAP partially cooked fish

Baker & Genigeorgis 1990

0.1

1.0

10

100

Days

0 10 20 30 40Temperature °C

Safety Line

Q10 ~ 4

Ea ~ 21.3 Kcal/mole

29Slide #

Shelf Life and Storage ConditionsShelf Life and Storage ConditionsShelf life of frankfurters and other deli meats: ≤ 90 days at X°C At 5 °C, mean generation time of Lm from math modeling program

1.77 days in frankfurters or 12 days to reach 100 CFU/g @ 5°C2.45 days in deli meats or 16 days (US FDA/CFSAN, USDA/FSIS & CDC, 2003)

The risks from Lm could be considered minimal ifInitial contamination No with Lm is at very low levels (≤10-5 CFU/g)No temperature/time abuse during storageIf 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 andat No = 10-6 it is 35 daysSeems too short or likely growth rate much less

69-78% of consumers store opened packages of deli meats for a week 10-13% for 1-3 weeks in their refrigerators so vacuum lost (USDA-FSIS, 2006)

USDA-FSIS noted in BilMar outbreak that contaminated hotdogs were consumed near or beyond end of shelf life labeled on package

R E A L I T Y

30Slide #

Shelf Life Evaluation of ReadyShelf Life Evaluation of Ready--toto--Eat Eat Meat and Poultry Products based on Meat and Poultry Products based on Listeria monocytogenesListeria monocytogenes growthgrowth

Dan Belina MS & Amit Pal Ph.D.

31Slide #

RTE Meat ProcessingRTE Meat Processing

Blender

Trimming

Stuffer

Smoking/Cooking

Cooler & Peeler

Weighing &Sorting

Vacuum Packing

Source: http://www.hotdogcartsdirect.com/how_hot_dogs_are_made.htm

CONSUMER

32Slide #

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)

33Slide #

So what temperature shouldSo what temperature should date be based on?date be based on?

1.3234

151222231034

Retail (%)

0.160 – 630.457 – 590.554 – 560.451 – 53348 – 50545 – 471842 – 442939 – 412536 – 381033 – 359< 32

Home (%)Lunch Meat Temperature (°F) Audits International, 1999

13% door and 4% bottom of the household refrigerators >45°F (>7.2 °C) Godwin et al, 2007

34Slide #

Inoculum Size and TTDInoculum Size and TTD

TSB 1.2 M NaCl in TSB

Fuqua et al., 1994; Robinson et al., 2001

Note Ln(1/No) = [0.693/G] x timeThis data suggests the model works with constant G and thus could model to level at below detection.

Robinson et al., 2001

Inoculum size Log (cells/mL)

TTD

(hou

rs)

35Slide #

PRELIMINARY STUDYPRELIMINARY STUDYFrancisco 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 H7776Implicated in hotdog outbreakGrowth part No = 5 CFU/gTTD part No= 0.01 CFU/g or 0.25 CFU/25 g ie less than detectionSix temperatures 4 to 36°CTwo media

TSB brothHPP processed hotdogs

36Slide #

L. mono Time to DetectionR2 = 0.9324

1

10

100

1000

0 10 20 30 40Temp (C)

Hou

rs

Q10 ~ 3.5

Phase 1 preliminary evaluation in TSB broth shows can work

37Slide #

Phase 1 TTD in hot dogsPhase 1 TTD in hot dogs

Ln Q10 =(Ea x 10)/[R T1T2]

Q10 = 3.45

38Slide #

Arrhenius plots of TTDArrhenius plots of TTD

TSB R2 ~ 0.91 hotdogs R2 ~ 0.96

39Slide #

18°C Growth CurveTSB

so time to 100 ~1 day

0

1

2

3

4

5

6

7

8

9

10

0 20 40 60 80 100 120

Hours

Log

CFU

/mL Log phase

7.9 hours per logk =0.293 hr-1

Lag = 13 hr

Stationary phase

time to 102 = 25 hrLog

CFU

/mL

40Slide #

Summary of growth dataSummary of growth data

Note at 4°C (39.2°F) G is ~ 33 hr much longer than USDA model of 1.77 hr

29 days

9 days

41Slide #

Summary ofSummary of temperature effecttemperature effect

Note that this means just can’t use one Q10 or use largest one which would mean throwing away good food

Q10 4.39 3.35 4.01

Q10 3.32 7.2 9.68

42Slide #

Phase 2 Finding fastest growersPhase 2 Finding fastest growers

Total 19 Lm ribotypes (ID by DUP-XXXX) with 2 reps

4 °C

109 CFU/ml

8 °C 12 °C

Plate Counting

on PALCAM

103-4 CFU/ml

+

1 part frank ORturkey breast 3 part PW

30 ml slurry

× 2

× 2

With orwithoutPL/SD

Stomached to slurry

43Slide #

Growth ModelsGrowth Models

exp A.= ][-exp1]t)-(

A.e[ +λμ

yGompertz

Transformation → y = (N/No)

t>λ

1= y t<λLinear

exp= )]-t([ λμy

]2)(4exp[1

A= +−+ t

A

yλμ

)ln(e1t= )( )(t λμμλμ

μ+−− −++ teetA

Logistic

Baranyi )e

1eln(1-A(t)y= )(y

A(t)

o max oyy −

+++

μ

μ

Growth curve

TimeLag time

y = µt + cNo

λ = [Ln(No) – c] / µ

44Slide #

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

45Slide #

Phase 2 FindingsPhase 2 FindingsNo significant difference between model performances (P > 0.05)So use the simplest ln N/No vs timeVariability 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

fastest strains selected were: DUP-1044A, 1039C, 1030A, and 1042B No definitive link between serotype and fastest strainsAverage lag Q10 = 7.6 and Average Log phase Q10 = 7Time to 102 Q10 = 7.4Pal, 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 SlurriesJ. Food Microbiology 25:460-470; 2008

46Slide #

PhasePhase 3 Growth on Frankfurters3 Growth on Frankfurters

4 °C109 CFU/ml

8 °C

12 °C102 CFU

~52.44 g and 121.9 cm2

LmCounting

on PALCAM

× 2

× 2 PsychrotrophsCountingon PCA

× 2

20 ml PW40 sec rinse

0.1 ml rinse or 1 ml in 4 plates

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/g

47Slide #

DUPDUP--1044A at 4 1044A at 4 °°C (Vacuum packaged)C (Vacuum packaged)

-2

0

2

4

6

8

10

0 20 40 60 80 100Time (days)

log1

0 (C

FU/c

m2 )

Control (V)HPP (V)PL/SD + HPP (V)PL/SD (V)

Sig. Diff. between HPP and control

Survivedbut

no growth

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

48Slide #

DUPDUP--1044A at 12 1044A at 12 °°C (Vacuum packaged)C (Vacuum packaged)

-202468

10

0 20 40 60Time (days)

log1

0 (C

FU/c

m2 )

Control (V)HPP (V)PL/SD + HPP (V)PL/SD (V)

>3 log(CFU/cm2)

25 days vs label of 90 days but started at above detection

49Slide #

Lm vs PPC – Comparison at 8°C8°C-vacuum

-2

0

2

4

6

8

10

0 20 40 60 80

8°C-vacuum

-2

0

2

4

6

8

10

0 20 40 60 80

Psychotrophs growth -Spoilage Indicator

Q10 ~ 6

Listeria monocytogenes growth - Safety Indicator

(♦) PL/SD + HPP (▲) PL/SD (□) HPP (○) Control

(○) Control

(○) Control

(□) HPP

(♦) PL/SD + HPP

(□) HPP

(▲) PL/SD

(▲) PL/SD

(♦) PL/SD + HPP

50Slide #

3-6*

Q10 = 4.7

5-12*19-49*NG-21 (air packaging)

NG-65 (air packaging)

NGDUP-1042B

oC

4-7*

Q10 = 4.7

8-10*18-45*NGNGNGDUP-1039C

2-3*

Q10 = 4.7

3-5*22-44*18-25NGNGDUP-1044A

12Psy 6 day Q10 = 6

8Psy 18 day

4 Psy 45 day

1284

Strain

Without‘P Lact. + Sod. Diac.’

With‘P Lact. + Sod. Diac.’

Franks

NG: No Growth ≤ 1 log growth in >90 days psy = 106psychrotrops

Phase 3 Results Summary Time to 100Time to 100--fold fold ListeriaListeria populationpopulation

51Slide #

Phase 3 FindingsPhase 3 FindingsLm 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 °CWithout 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

52Slide #

Phase 4 TTD ModelingPhase 4 TTD Modeling

5 ml PDX-LIB

(CFU/25g)(g)

0.1815000.251000

12502.5100

No Size

0.55 g × 3

37 °C for 48 h

MOXagar

True positive = when at least two out of the three replicates showed confirmed presenceSampling frequency: 3 days (4 °C), 2 days (8 °C), and 1 day (12 °C) TTD = first out of three consecutive positive samples

~10 CFU (DUP-1044A)

Assumption 100 lb = 1000 g25 g = 0.55 g

+ + -

53Slide #

TTD (days) vs. Inoculum size (Ln NTTD (days) vs. Inoculum size (Ln Noo))

TTD = -3.95 ln(No) + 32.09R2 = 0.97

30.0

40.0

50.0

60.0

-5.50 -4.50 -3.50 -2.50

a

a

bb

TTD = -1.24 ln(No) + 1.92R2 = 0.89

0.0

2.0

4.0

6.0

8.0

10.0

-5.50 -4.50 -3.50 -2.50

aa

a

b

TTD = -0.62 ln(No) + 0.56R2 = 0.95

0.0

2.0

4.0

6.0

-5.50 -4.50 -3.50 -2.50

a a

abb

Observed TTDExpected TTD (Phase 2 data)Safe growth limit

4 °C 8 °C

12 °C

0.007 0.01 0.04 0.1 CFU/g

TTDs with common letter are not significantly different (P > 0.05) from pair-wise t-test

54Slide #

Shelf Life Model (TTD vs Temp.)Shelf Life Model (TTD vs Temp.)

TTD1 = 185.17e-0.34T

R2 = 0.96

TTD2 = 151.84e-0.38T

R2 = 0.93

1.0

10.0

100.0

2 4 6 8 10 12 14

Temperature (°C)

TTD

(day

s)0.1 CFU/g 0.04 CFU/g 0.01 CFU/g 0.007 CFU/g

)exp( bTShelfLifeShelfLife oT −=

)10exp(10 bTQ =

Guadagni, 1968; Labuza, 1972

47 days

23 days

6 days

3.4 days

Q10= 31

Q10= 24

55Slide #

PhasePhase 5 Findings5 FindingsSignificant 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!

56Slide #

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

57Slide #

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.

58Slide #

ContactDr. Theodore LabuzaDepartment of Food Science and NutritionUniversity of Minnesotatplabuza@umn.edu 612-624-9701 fax 651-483-3302 cell 651-307-2985http://www.ardilla.umn.edu/Ted_Labuza