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S M A S

Development and application of a TTI based Safety Monitoring and Assurance System for Chilled Meat Products

QLK1-CT-2002-02545

A European Commission Research and Technology Development Project

FIFTH FRAMEWORK PROGRAMMEQuality of life and management of living resources

http://smas.chemeng.ntua.gr

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Meat Chill Chain- Need for better management

It is generally recognized by the European industry, retailers, food authorities and even consumers that the weakest link that affects directly safety and quality of chilled products is the actual chill chain. Over 44% of foodborne disease is due to temperature abuse.

Project QLK1-2002-02545

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3Meat Chill Chain- Need for better management Meat products are perishable and unless processed, packaged, distributed and stored appropriately can spoil in relatively short time. Overgrowth of incidental pathogenic bacteria like Listeria monocytogenes, Salmonella sp. and Escherichia coli followed by undercooking or inadequate preparation may pause a potential hazard for the consumer. Despite the proliferation of food safety regulations and the application of safety management systems such as HACCP, risk assessment studies show that foodborne disease has remained a main concern in the last decade.


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4Meat Chill Chain- Need for better management Application of an optimised quality and safety assurance system for chilled distribution of fresh meat and meat products requires continuous monitoring and control of storage conditions from production to consumption. The systematic management of the chill chain and the improved evaluation of safety, quality and shelf life of meat can lead to reduced safety risk and increased quality, with a significant health and economic impact to the European society and market.


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5What is SMAS?

SMAS is an integrated chill chain management system, expected to lead to an optimised handling of products in terms of both safety and quality. It is based on the ability to continuously monitor the storage conditions of each product with the use of Time Temperature Integrators (TTI). TTI are inexpensive “smart labels” that show an easily measurable, time and temperature dependent change that cumulatively reflects the time-temperature history of the food product. TTI response can be correlated to meat safety and quality status at any point of the distribution chain providing an effective decision tool. Project QLK1-2002-02545

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The SMAS project The acronym SMAS summarizes the long title of the 3 year (2003-2006) action project “Development and application of a TTI based Safety Monitoring and Assurance System for Chilled Meat Products”, co-ordinated by the National Technical University of Athens (NTUA). Funded by the EC, it is part of the key action of Food, Nutrition and Health. The project basis consists of validated predictive models of predominant meat pathogens growth and kinetics of the response of selected TTI, all applied in an expanded TTI application scheme that translates TTI response to meat microbiological and quality status. 7 Institutes/Companies are members of the SMAS project, working on its 6 main interrelating workpackages with the ultimate purpose to deliver an effective chill chain decision and management tool. Project QLK1-2002-02545

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OVERALL OBJECTIVE

State of the art ofTTI technology + Quantitative risk assessment

⇓Development of SMAS, an effective and reliable safety assurance and

quality optimization management system for meat products, extending from production to the table of consumer

Project QLK1-2002-02545 TECHNICAL ANNEX

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8PROJECT WORKPLANWorkpackages & their interrelation


Development and Application of a TTI BasedSafety Monitoring and Assurance System (SMAS)

for Chilled Meat Products

WP1MicrobialModeling

WP2Risk

Assessment

WP3TTI

DevelopmentModeling &

Optimisation

WP4SMAS

Development

PRODUCTS TTI SMAS

WP5SMAS Validation

and Application inMeat Industry

WP6ConsumerPerception& Benefit

APPLICATION

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9TTI-MEAT SAFETY SYSTEM SMASParticipant 1NTUA (LFCT)

National Technical University of Athens

School of Chemical Engineering

Laboratory Food Chemistry and Technology

Principal scientist: Dr. Petros Taoukis

COORDINATOR –Leader WP3 & WP4


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10TTI-MEAT SAFETY SYSTEM SMASParticipant 2

SIKThe Swedish Institute for Food and Biotechnology

Microbiology and Product Safety Department

Gothenburg/LUND, Sweden

Principal scientist: Dr. Elizabeth Borch

Leader WP6


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AUA Agricultural University of Athens,

Department of Food Science & Technology,

Laboratory of Microbiology & Biotechnolgy

Principal scientist: Prof. George John Nychas

Leader WP1


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NFC

Food Safety Department, Teagasc

The National Food Centre

Castleknock, Dublin, Ireland

Principal scientist: Dr. James Sheridan


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TTI-MEAT SAFETY SYSTEM SMASParticipant 5

TNOTNO Nutrition and Food Research

AJ Zeits, The Netherlands

Principal scientist: Dr. ir. Servè Notermans

Leader WP2


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IFRInstitute of Food Research

Food Safety Division Norwich Research Park

Norwich, United Kingdom

Principal scientist: Dr. József Baranyi


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TTI-MEAT SAFETY SYSTEM SMASParticipant 7CRETA FARM

Creta Farm SA, Latzimas

Crete, Greece

Principal scientist: Dr. Constantin Genigeorgis

Leader WP5


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16 The major expected achievements of the project will be: • Accurate, validated mathematical models for safety and quality related

microorganisms of ready to cook meat products. They will provide the meat industry with a tool for product development and safety assurance and the European authorities with a quantitative means for meat product risk evaluation.

• The development and study of an assortment of Time Temperature Integrators (TTI) suitable for meat safety monitoring. These TTI will provide the meat industry and retail business with effective tools to monitor the chill chain.

• Improved distribution logistics and management of the meat chill chain from the application the Safety Monitoring and Assurance System (SMAS). SMAS could replace the current “First In First Out” (FIFO) practice and lead to risk minimization and quality optimization.

• Increased ability of the meat sector to control its weak link, the chill chain

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17• Fulfilment of consumer expectations that extra efforts and state of the art

technology, represented by the use of TTI active labels and SMAS, have been employed to guarantee him low risk-high quality meat products.

• Wide availability of state of the art information, from the project and other reliable sources (i.e validated mathematical models for pathogen growth, data for pathogen prevalence and concentration, distribution temperature profiles, dose response data, inactivation models, TTI and SMAS application) for Risk Assessment of specific meat products, through the establishment of an effective Internet site (http://smas.chemeng.ntua.gr)

TThhee ccoonnttrriibbuuttiioonn ooff SSMMAASS iinn tthhee cchhiillll cchhaaiinn mmaannaaggeemmeenntt ccaann bbee vviissuuaalliizzeedd aass aa mmiinniimmiizzaattiioonn ooff rriisskk ffoorr iillllnneessss aanndd ooppttiimmiissaattiioonn ooff tthhee mmeeaatt pprroodduucctt qquuaalliittyy aatt tthhee ttiimmee ooff ccoonnssuummppttiioonn

http://smas.chemeng.ntua.gr

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Product quality at consumption

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SMAS BROCHURE

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SMAS BROCHURE

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APPLICABILITY OF TTI FOR MONITORING

THECHILL CHAIN

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27TTI: main principles

Time Temperature Indicators (TTI) are simple, inexpensive devices that can show an easily measurable, time and temperature dependent change that cumulatively indicates the time-temperature history of the product from the point of manufacture to the consumer, allowing the location and the improvement of the critical points of the chill chain

PRINCIPLES OF TTI

TYPES OF TTI

ENZYMATICPolymer based

Diffusion based

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TTI

ΤΤΙ Τype ΙII

Time Temperature Indicators

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Principle of function:Principle of function:

The indicator starts with two liquid-filled pouches heat sealed into plastic

The contents are mixed by bursting the seal between the pouches by pressure

After exposure to time and temperature, the contents turn from green to yellow

Visual Indicator Tag Systems, AB Malmö, SwedenΤΤΙ Type ΙI


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All green at activation.

Dot 3 changes color last. At that point, all three dots are yellow. This is an “end of shelf life” condition, or 0% of shelf life remaining.

Dot 1 changes color first. This color change is usually to indicate 75% of shelf life remaining.

Dot 2 changes color next, after dot 1 has changed. This color change is usually to indicate 50% of shelf life remaining.

Visual Indicator Tag Systems, AB Malmö, SwedenΤΤΙ Type ΙI


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Enzymatic TTI RESPONSE

• L*a*b* measurements chroma value:

normalized chroma:

Response function

• F(Xc) vs time• Arrhenius plots (lnk=f(1/T))

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XCC Cmin

Cmax Cmin=

−

−

F(XC) ln1

1 Xkt

C=

−

=

kEa

ΤΤΙ – Type II response kinetics

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ΤΤΙ – Type II response kinetics at CONSTANT temperatures

TTI - TYPE Μ2-3510 - WINDOW 1

0

0.2

0.4

0.6

0.8

1

0 50 100 150 200 250 300t (h)

X(b)

X(c)

TTI - TYPE M2-3510 - WINDOW 1

0

0.5

1

1.5

2

2.5

0 50 100 150 200 250 300

t (h)

F(Xb)F(Xc)Linear (F(Xb))Linear (F(Xc))

XCC Cmin

Cmax Cmin=

−

−

F(XC) ln1

1 Xkt

C=

−

=

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> Degradation of quality index Α:

> Quality deteriorartion for variable temperature distribution:

Τeff : constant temperature that results in the same quality change as the variable temperature distribution over the same time period

( ) ktAf =

( ) ( )[ ] tdTTR

EexpkdttTkAft

ref

aA

t

t ref ∫∫

−

−==

00

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( ) tTTR

EexpkAfrefeff

aAt ref

−

−=

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KINETICS OF FOOD QUALITY DETERIORATION

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( ) t 11

−

−==

ref

aI TTR

EexpkktXF I

ref

Χ: measurable change of ΤΤΙΧ: measurable change of ΤΤΙ

Response functionResponse function:

?? Using effective Using effective temperaturetemperature::

( ) ( )[ ] tdTTR

EexpkdttTkXF

t

ref

aI

t

tI

ref ∫∫

−

−==

00

11

( ) tTTR

EexpkXF

refeff

aIt

I

ref

−

−=

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?? For variable temperature distributionFor variable temperature distribution::

TTI RESPONSE KINETICS

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ΤΤΙ APPLICATION SCHEME

Measurement of ΤΤΙ response

F(X)

Teff

Teff

f (A)

AtQuality at time t

Response function:

Quality function

( ) tTTR

EexpkAfrefeff

aAt ref

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−

−=

( )

I

ref

a

I

t

1ref

1eff E

kXF lnR

TT

−= −−

Iref aI E ,kaA E ,k

refΕa (ΤΤΙ) ≅ Εa (food)

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36TTI reliabilityThe error in the Teff calculation is due to three sources:1. The variability in the value of the response function, F(X), between

indicators of the same model, at same time and temperature. It can expressed as an average coefficient of variation for a large number of different conditions.

2. The uncertainty in the Arrhenius equation, modelling the TTI temperature behaviour, statistically expressed by the confidence limits of the regression values of EA and kI.

3. The third error in Teff is due to the difference in activation energies of the food and the TTI. This error is systematic and not random. Calculations with assumed variable temperatures showed that if the activation energies of the food and the TTI differ by less than 40 kJ/mol, i.e. EATTI - EAfood < 40 kJ/mol, then in general the two Teff differ by 0.4 to 1.8° C.

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Overview of TTI applications1. Continuous temperature monitoring of the chill chain &

elucidation of the “problematic” links

2. Correlation to food quality deterioration kinetics-prediction of

the remaining shelf life at ANY point of the distribution chain

3. Improvement of the management and stock rotation

system (FIFO) ⇒ introduction of Least Shelf life Out

(LSFO)/ Shelf Life Decision system (SLDS)

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TTI applications

NEXT STEP: From SLDS to SMAS

Introduction of a Safety Monitoring and Assurance System

(SMAS)

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Development of a Safety Monitoring and Assurance Development of a Safety Monitoring and Assurance System (SMAS) for chilled food productsSystem (SMAS) for chilled food products

Pathogen kinetic model

Variation of food characteristics

(aw, pH etc)

Time-temperature history

(TTI, data loggers)

SMAS building blocks

SMAS principles

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Example of SMAS application

Decision points Decision points in the chill chain:in the chill chain:

1. Distribution Center2. Stock display (retail level)

Method: Comparison of listeriosis risk and remaining shelf life at the time of consumptionin products managed with FIFO and SMAS system using Monte Carlo simulation

Product: Cooked meat (ham)

Tools: • Microbiological data from literature• Temperature data collected in the chill chain• validated kinetic models of microbial growth • validated kinetic models of TTI response

Safety and quality assessment

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47Main goals of SMAS The aim of this research project is to study reliable and practical Time Temperature Integrator (TTI) systems and establish their applicability as safety monitors of meat products from manufacture to consumption. The project will capitalize and expand on the scientific state of the art approach of mathematical modelling of dominating meat pathogens and translate this knowledge to TTI.

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