© AZTI-Tecnalia

Application ofApplication of “Fish Shelf life Prediction (FSLP)Fish Shelf life Prediction (FSLP)”” software software for monitoring seafood quality in the cold chainfor monitoring seafood quality in the cold chain

Begoña Alfaro AZTI-Tecnalia, Food Research Division Spain

balfaro@suk.azti.es

3 rd International Workshop “Cold-Chain-Managment”June 2, 2008 in Bonn,Germany

© AZTI-Tecnalia

Sukarrieta (Bizkaia)

Pasaia(Gipuzkoa)

AZTI-Tecnalia

Tecnalia Corporation

Food Researchscience + innovation

• 2 + 1 Research Centers ( > 10.000 m )• 180 Personnel• 16 Millions € (income) • 30 European Projects running

2

AZTI-Tecnalia, a Technological Centre specialised in Marine and Food Research, is a private non-profit organization, whose objective is the social development and the improvement of competitiveness in its area of influence by means of technological Research and Innovation.

Derio · 2008 (Bizkaia)

www.azti.es

© AZTI-Tecnalia

““Fish Shelf Life Prediction ProgramFish Shelf Life Prediction Program”” A tool for prediction the shelf life of aquaculture products.• Introduction• Objectives of project• Our reseach: Materials and methods• Results: Software “Fish Shelf Life PredictionSoftware FSLP”• Real Life implementation• Conclusions• Plans for the future

GOODFOOD GOODFOOD EuropeanEuropean projectproject-- DemostrationDemostration projectproject• Introduction• Objectives of project• Results and conclusions

Outline of the presentation

© AZTI-Tecnalia

Introduction

Fresh fish are highly perishable products that deteriorate rapidFresh fish are highly perishable products that deteriorate rapidly if not ly if not handled and stored properlyhandled and stored properly

SHELF LIFE IN SEAFOOD PRODUCTS IS A FUCTION of several factors SHELF LIFE IN SEAFOOD PRODUCTS IS A FUCTION of several factors that influence the spoilage of fish:that influence the spoilage of fish:

••SpeciesSpecies

••Seasonal conditionSeasonal condition

••Catching methodsCatching methods

••HandlingHandling

••ProcessingProcessing

••Storage conditions (Time/Temperature)Storage conditions (Time/Temperature)

© AZTI-Tecnalia

Introduction

••Spoilage in fish products is mainly due to the action of bacteriSpoilage in fish products is mainly due to the action of bacteriaa

••Sensory evaluationSensory evaluation: is one of the most important methods for freshness : is one of the most important methods for freshness and quality evaluation in the fish sector and the fish inspectioand quality evaluation in the fish sector and the fish inspection services n services ((LutenLuten and and MartinsdMartinsdóóttirttir 1997)1997)

physical changes • colour, texture change

chemical changes• rancidity, colour change

microbiological changes• visible growth• slime • textural changes• off-odours and off-flavours

© AZTI-Tecnalia

Fish Distribution Chain

Fresh Fishing vessels

Auctions

Wholesalers- Fishmerchants

Processors

Consumers

Wholesalers, central market

AquacultureImports

Exports

Retailers

Retailers

Frozen Fishing vessels

Safety and Quality Assessment Safety and Quality Assessment Time, temperature and traceability informationTime, temperature and traceability information

© AZTI-Tecnalia

•• Objectives:Objectives:

• Develop kinetic models to predict the microbial spoilage and the sensory quality of fresh turbot at constant and fluctuating temperature conditions

• Evaluate the efficiency of a commercial time temperature integrators(TTI) label to monitor the fresh turbot shelf-life

• Develop a user-friendly software able to predict the shelf life of farmed fresh fish according to the microbial growth but also to the sensory evaluation

Objectives of the project

© AZTI-Tecnalia

•• MaterialsMaterials-- FishFish

• Turbot (Psetta maxima orScophthalmus maximus )

• Fish were chilled in ice, transferred tothe lab within 1,5 hours

• Samples were packaged in extended PVC film individually

obtained directly from aquaculture

Materials and Methods

© AZTI-Tecnalia

•• Methods:Methods:

Preservation studies were carried out under normal and abusive Preservation studies were carried out under normal and abusive conditionsconditions:

• 0 , 5 , 10 and 15 ºC.• Two dynamic storage experiments: non-isothermal

Microbiological measurements:Microbiological measurements:• Total aerobic viable counts (TVC)• Enterobacteriaceae• SSO (specific spoilage organisms: Pseudomonas spp.• Shewanella putrefaciens, B. thermosphacta

Sensory evaluationSensory evaluation by trained panel (ISO 1993):

• Cooked fish : odour, flavour and texture• Raw fish: Using a 6 point descriptive scale (ISO 41:21:1987)

Materials and Methods

© AZTI-Tecnalia

•• DefinitionDefinition ofof timetime--temperaturetemperature indicatorsindicators TTI:TTI:A simple, inexpensive device that shows an easily measurable, time-temperature dependent change that reflects the full or partial temperature history and quality status of the food product to which it is attached to. (Taoukis and Labuza, 1989)

Monitor Mark (3M)

Fresh Check® (LLT)

Check Point®

(Vitsab)

Response of Response of TTIsTTIs: Colorimeter (Minolta CR-200)

Materials and Methods

© AZTI-Tecnalia

Evaluate the performance of the models by comparison predictions with observations

Model the effect of temperature on bacterial growth sensory assessment and rate of change, of TTIs

Models of Baranyi and Robert (1994)

PCA (Principal Components Analysis)

Rate of change of colour (empirical models)

Bacterial growth curves

Sensory score

Response of TTIs

Validation ofmodels

Secondarymodelling

Primary ModellingData generation

Methodology

© AZTI-Tecnalia

Fig 1 Total aerobic flora in turbot. Model (red line)ROD0AM

(Ta, -0.00999, 0, 0.058631, 1.340874, 3.209296, 0.043586, 5.453841, 5.552621, True, True, IN: TURB)

-1

0

1

2

3

4

5

6

7

8

9

0 200 400 600

ROD5AM(Ta, -0.00999, 5, 6.485831, 5.104144,

9.330892, 8.547162, 6.690711, 5.552621, True, True, IN: TURB)

-2

0

2

4

6

8

10

12

0 200 400 600

ROD10AM(Ta, 1, 10, 0.109205, 2.140779, 0.186438, 0.163667, 0.128599, 0.220160, True, True, IN: TURB)

0

1

2

3

4

5

6

7

8

9

0 100 200 300

ROD15AM(Ta, 1, 15, 0.370710, 8.570531, 0.311481, 0.306411, 0.387263, 0.602239, True, True, IN: TURB)

0

1

2

3

4

56

7

8

9

10

0 50 100 150 200

Fig 2 Pseudomonas in turbot. Model (red line)ROD0PS

(Ps, 1, 0, 5.009801, 8.361341, 3.742901, 0.04272, 5.552621, True,

True, IN: TURB)

0

1

2

3

4

5

6

7

8

0 200 400 600

ROD5PS(Ps, 1, 5, 6.975071, 0.014473,

8.350123, 7.718181, 9.945997, True, True, IN: TURB)

0

2

4

6

8

10

12

0 200 400 600

ROD10PS(Ps, 1, 10, 0.120696, 1.725890,

0.147813, 0.136559, 0.220160, True, True, IN: TURB)

0

1

2

3

4

56

7

8

9

10

0 100 200 300

ROD15PS(Ps, 1, 15, 0.251292, 5.611238,

0.230367, 0.236877, 0.602239, True, True, IN: TURB)

0

1

2

3

4

56

7

8

9

10

0 50 100 150 200

RESULTS: Finding the spoilage rate: Model of Baranyi and Roberts (1994)

In: Maider Nuin, Begoña Alfaro, Ziortza Cruz, Nerea Argarate, Susie George, Yvan Le Marc, June Olley and Carmen Pin* Modelling spoilage of fresh turbot and evaluation of a time-temperature integrator (TTI) label under fluctuating temperature.Int J Food Microbiol, (in press).

© AZTI-Tecnalia

MM10_1(TTI, Monitor , exp((X-X, 10)

0

0.2

0.4

0.6

0.8

11.2

1.4

1.6

1.8

2

0 20 40 60

MM5_1(TTI, Monitor , exp((X-X, 5)

0

0.2

0.4

0.6

0.8

11.2

1.4

1.6

1.8

2

0 20 40 60 80

MM5_9(TTI, Monitor , exp((X-X, 5)

0

0.2

0.4

0.6

0.8

11.2

1.4

1.6

1.8

2

0 50 100

Monitor Mark0

0( ) 1m

x xx xF x e−−= −

FC0_1(TTI, Fresh Ch, ln(X0/X), 0)

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

00 200 400 600FC5_8

(TTI, Fresh Ch, ln(X0/X), 5)

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

00 100 200 300 400

FC10_3(TTI, Fresh Ch, ln(X0/X), 10)

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

00 20 40 60 80

FC15_4(TTI, Fresh Ch, ln(X0/X), 15)

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

00 50 100

CP0_1(TTI, Check Po, sqrt(ln(, 0)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 200 400 600

CP5_5(TTI, Check Po, sqrt(ln(, 5)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 50 100 150 200

CP10_3(TTI, Check Po, sqrt(ln(, 10)

0

0.1

0.2

0.3

0.4

0.5

0.6

0 20 40 60 80

CP15_10(TTI, Check Po, sqrt(ln(, 15)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 20 40 60 80

Fresh Check

Check Point

0( ) ln xF xx

⎛ ⎞= ⎜ ⎟⎝ ⎠

0

0

( ) ln 1m

x xF xx x

⎛ ⎞−= +⎜ ⎟−⎝ ⎠

RESULTS: Finding the rate of change of TTIs: Primary models

© AZTI-Tecnalia

SOFTWARE SOFTWARE ““FISH SHELF LIFE PREDICITON PROGRAM FISH SHELF LIFE PREDICITON PROGRAM (FSLP)(FSLP)”” ((AZTI_InstituteAZTI_Institute ofof FoodFood ResearchResearch--UK ):UK ):

• The models have been implemented in a Visual Basic add-in for Excel ““FishFishShelfShelf LifeLife PredictionPrediction (FSLP) (FSLP) programprogram””

• This program predicts the shefshef lifelife ofof freshfresh turbotturbot at contants andfluctuating temperature conditions according:

Sensory acceptability: rejection time (hours)Growth of spoilage bacteria ( log 10 cfu/g) (log

• Response of twotwo commercialcommercial timetime--temperaturetemperatureintegratorsintegrators (hours): Monitor Mark ® and

Fresh Check®

RESULTS

© AZTI-Tecnalia

Implementation of an online online TTªª monitoring system for the fresh fishlogistic chain

To enable a future generation of producers and logistic groups to trace fish at any time.

To protect consumers from the consumption of unsafe fish.

Fishing

AQUACULTURE LOGISTICS RETAILERSWHOLESALERS

Transport Distribution DistributionTransport

Real life implementation

““Monitoring time/TMonitoring time/Tªª data for the fresh turbot logistic chain from data for the fresh turbot logistic chain from fish farmed (Spain) to distribution (Italy)fish farmed (Spain) to distribution (Italy)

© AZTI-Tecnalia

The chain starts when the turbot is captured in the fish farmer (San Sebastian-Spain)and transport to Irun (Spain) food perishable centre in refrigerated truck…

Fresh Turbot Logistic Chain

Data-loggers were placed inside a polystyrene box with the fish

© AZTI-Tecnalia

Fresh Turbot Logistic Chain

From Irun (Spain) Zaragoza (Spain) Barcelona (Spain) Ghioggia(Italy) in refrigerated trucks…

Real life implementation

The whole logistic chain can take around 3 days from the capture to the consumer.

© AZTI-Tecnalia

Results Real life implementation•Measured by 3 data-loggers Tª was kept below 2ºC along the complete journey of 72 hours• Correlation of Tª peaks with events along the truck transport

Fish boxes wereloaded into the

truck

© AZTI-Tecnalia

Results Real life implementation

Figure: Sreenshot from “Fish Shelf Life Prediction Program (FSLP)” for the fresh turbot transportedfrom Spain to Italy (70 hours) showing the predicted total bacteria and sensory score. In addition, showing the scores for the TTIs.

Application of Fish Shelf life Prediction Program for Application of Fish Shelf life Prediction Program for monitoring fresh turbot quality in the cold chain. monitoring fresh turbot quality in the cold chain.

© AZTI-Tecnalia

Results Real life implementationComparison of growth of total bacteria:Comparison of growth of total bacteria:

observed and predicted dataobserved and predicted data

© AZTI-Tecnalia

Modelling shelf life and quality on real fresh fish products is difficultbut possible

To predict shelf life it is important to have information about rawmaterials, to have the time-temperature profiles of the product

We have developed a software able to predict the shelf life of farmedfish (turbot) products taken into account microbial and sensoryparameters (at constant or fluctuating temperatures)

Prediction softwares: useful tools for cold chain management.

CONCLUSIONS

© AZTI-Tecnalia

•Available free version of the software ““FishFish ShelfShelf LifeLife PredictionPrediction ProgramProgramFSLPFSLP”” in internet for industry, food inspection services, teaching, researchand consumer organisations)

http://www.azti.es/muestracontenido.asp?idcontenido=980&content=15&nodo1=30&nodo2=0

(Spanish version)

http://www.azti.es/muestracontenido.asp?idcontenido=981&content=15&nodo1=30&nodo2=0(English Version)

•http://www.azti.es/

CONCLUSIONS

© AZTI-Tecnalia

•• Validate the software with more fish species and products (fresh andlightly preserved seafood)

•Software: combination of shelf-life models and traceability tools (e.g. data logger or radio frequency identification tags _RFID)

PLANS FOR THE FUTURE

© AZTI-Tecnalia

“FOOD SAFETY AND QUALITY WITH MICROSYSTEMS” (FP6-IT-1-508774-IP)

Objective (WP6): Development of a flexible tag for food monitoring during thelogistic chain, integrating:

- physical sensors (Tª, rH and light) - chemical sensors- RFID communication capabilities

GOODFOOD project

Demostration project: Objective: Implementation of an online online TTªª andand rHrHmonitoring system for the fresh fish logistic chain(based on the RFID tag developed)

© AZTI-Tecnalia

MethodologyMethodology: Real-life implementation of the smartsmart RFID RFID tagtag alonginternational fresh fish logistic chain . Field tests:from South-Africa

to Spain by airplane and from Frankfurt (Germany) to Vitoria (Spain)

ConclusionsConclusions: RFID smart tag system developed has been demostrated andvalidated along an international fresh fish.

Traceability and cold chain data are stored in the Smart Tag memory

Fishing Processing

FISHERMEN INDUSTRIALS

Airport (origin)

Airport (destination)

LOGISTICS RETAILERSWHOLESALERS

Transport Distribution DistributionTransport

GOODFOOD:Demonstration project

© AZTI-Tecnalia

FSLP_SoftwareFSLP_Software: AZTI: AZTI--TECNALIA, TECNALIA, SpainSpainFoodFood ResearchResearch DivisionDivision

Maider NuinNerea ArgarateZiortza CruzBego Alfaro

InstituteInstitute ofof FoodFood ResearchResearch,,ComputationalComputational MicrobiologyMicrobiologyNorwichNorwich, UK, UK

Carmen PinJozsef BaranyiYvan Le Marc

THANK YOU !!

Agriculture and Fisheries Department of the Basque Government for providing financial support for this research.

© AZTI-Tecnalia

Txatxarramendi ugartea z/g.

48395 SUKARRIETA (Bizkaia)

Tel.: +34 946029400 / Fax: +34 946870006

Txatxarramendi ugartea z/g.

48395 SUKARRIETA (Bizkaia)

Tel.: +34 946029400 / Fax: +34 946870006

Herrera Kaia, Portu aldea z/g.

20110 PASAIA (Gipuzkoa)

Tel.: +34 943004800 / Fax: +34 943004801

Herrera Kaia, Portu aldea z/g.

20110 PASAIA (Gipuzkoa)

Tel.: +34 943004800 / Fax: +34 943004801

www.azti.esThank you for your attention!!!

www.azti.esinfo@azti.es