cold chain evaluation and management using ...ccm.ytally.com/fileadmin/user_upload/downloads/...cold...

Petros Taoukis*1, George Katsaros1, Theofania Tsironi1,

Efimia Dermesonluoglu1, Eleni Gogou1, Graciela Alvarez2, Evelyne Derens2

1 National Technical University of Athens, School of Chemical Engineering. Laboratory of Food Chemistry and Technology

*[email protected]

2 IRSTEA, FRANCE

COLD CHAIN EVALUATION AND MANAGEMENT USING FRISBEE PROJECT PREDICTION TOOLS

5th International Workshop Cold Chain Management June 10 – 11, 2013 Bonn

Laboratory of Food Chemistry & Technology School of Chemical Engineering

National Technical University of Athens

Current philosophy

Development and application of structured quality management systems based on prevention by monitoring, controlling and recording of critical parameters through product’s entire life cycle

Food Quality Assurance

5th International Workshop, Cold Chain Management June 10-11, 2013 Bonn

Laboratory of Food Chemistry & Technology School of Chemical Engineering – National Technical University of Athens

It is generally recognized by the European industry, retailers, food authorities

and even consumers that the cold chain affects directly safety and quality of

chilled and frozen products.

Cold Chain – Need for better management

The systematic management of the cold chain and the improved evaluation

of safety, quality and shelf life of the products can lead to reduced safety risk

and increased quality, with a significant health and economic impact to the

society and the market.

Cold Chain Management



Temperature variations in distribution and storage conditions

Need for Real Time-Temperature Profiles along the cold chain




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Time (min)

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Temperature variation between 3 profiles of

same product distribution and storage

Distribution and retail display of same product at 3 different dates



Differences between 3 profiles

of same product distribution and

storage -2

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Time (min)

Time min

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Distribution and retail display of same product at 3 different dates



4 data loggers were distributed randomly to potential consumers to monitor variations

INSIDE the refrigerator

1

2

3

4

1: upper shelf 2: middle shelf 3: lower shelf 4: door



Variations WITHIN the domestic refrigerator

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UPMIDDLEDOWNDOOR

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Temperature conditions IN the domestic refrigerator

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-0.8

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2.7

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upper shelf middle shelf

lower shelf door

Temperature ( C)

% o

f d

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esti

c re

frig

erat

ors



Temperature conditions IN the domestic refrigerator

Food products are exposed, throughout the distribution, including retail and domestic

storage, to effective temperatures that deviated significantly from the recommended range.

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T (°C)

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Average storage temperatures measured in different types of retail freezers

in several stores of a large supermarket chain. (Temperature data from

recent surveys conducted by NTUA in collaboration with a leading

supermarket chain).

Temperature conditions within retail display freezers



Electronic Data Loggers

Data loggers were sealed in packages of products and monitored from processing through distribution to delivery and storage in Super Markets all over Greece.

Examples of data collection in the cold chain



Sharp (but short) increases of temperature (during transport)

Cases of retail storage at temperatures >7°C

Significant temperature fluctuations

Quality of optimally processed food products depends on the

temperature conditions of storage, handling and distribution. Monitoring and control of these conditions would allow cold chain optimization and reliable product shelf life prediction.

Temperature conditions FROM production TO the retail outlet



ESTIMATION OF THE DEVIATION OF DISTRIBUTION AND

STORAGE TEMPERATURE FROM RECOMMENDED

FRISBEE PROJECT

TOOLS FOR COLD CHAIN MANAGEMENT

COLD CHAIN DATABASE

COLD CHAIN PREDICTOR SOFTWARE




Food Refrigeration Innovations for Safety, Consumers’

Benefit, Environmental Impact and Energy Optimisation

Along the Cold Chain in Europe

EC 7th Framework RTD Project Grant agreement no.: 245288



FRISBEE Project

Collection of existing data on cold chain

Data from all stages of the cold chain (from production to consumption) is being

collected, and weak links for different types of products identified. The consortium already

has a core of survey data of product temperature evolution along the supply chain for

products such as yoghurt, meat and fish products in different European regions. Other

available data, i.e., published data, data from the industry and cold chain parties

(distributors, retailers), from associations and research projects is included.

Systematic analysis of these data will allow identification of the weak links of the cold

chain and serve as a tool for cold chain management with regards product quality and

shelf life.



Development of comprehensive database on cold chain in Europe

How can I contribute my data?

Visit FRISBEE website

http://www.frisbee-project.eu/






Database development on cold chain

htpp://www.frisbee-project.eu/coldchaindb.html

WP2 - Cold Chain Data Collection

Please Enter Username and Password and press "Login"

Username :

Password :

Login

If you do not have a username you can create a new account

, or contact us at [email protected] to receive your account details

Visit FRISBEE Cold Chain Data Collection Platform



Collection of existing data on cold chain


Cold chain database




Add Cold Chain Data 0

Stage/step of cold chain Required Field Production stage - food chilling operation

Production stage - food freezing operation

Production warehouse

Transportation

Distribution warehouse

Retail warehouse

Hypermarket

Supermarket

Hard discounter

Grocery

Retail display

Consumer domestic refrigerator

Transportation by consumer - Retail to home

Complete cold chain

Other

Country of origin Required Field

Please select an item

Destination country Please select an item

Sample Date 03/03/2011

Time data logger started collecting data (hrs:min)

Please select an item



Cold chain database htpp://www.frisbee-project.eu/coldchaindb.html



Cold chain database


View data uploaded by the user After the completion of your upload you can see all the files that have been uploaded by the user in a list.

If you click one set e.g.

, you will see two options:

Click

where you can download the uploaded .xls file

or click

where you can see all the descriptive information of the selected file.



Cold chain database


Large number of temperature profiles FROM production UPTO the consumer

Representative t-T profile



Cold chain database





Representative t-T profile



FRISBEE European Cold Chain Database

On the left panel the user can see the list of records matching the selected search criteria. In order to see the data of a specific record click on the record name (e.g. 6410mins, 1.1 to 10.2 C).





Meta-data of each t-T profile


Cold Chain Data collection

More than 9000 files have been contributed,

130 accounts created

Chilled and frozen food products t-T profiles contributed

Dynamically growing

Data Collection

Saving data on server

Reviewing contributed data

Reviewing meta-data

Data screening




10/2011 04/2012 07/2012

3230 profiles

4430 profiles

4940 profiles

On going…

5040 profiles

*12/2011

3250 profiles

09/2012

9000 profiles

11/2012

5560 profiles

05/2013

! Dynamically growing




Total number of Records: 9000

Type of Data Food storage temperature range

0,00

10,00

20,00

30,00

40,00

50,00

60,00

chilled superchilled

frozen other

51,88

0,03

41,18

6,91

Set of T values for a time period

69%

Single T

measurement

31%




0,00

5,00

10,00

15,00

20,00

25,00

30,00

35,00

40,00

45,00

Me

at and

M

eat p

rod

uct

Fish an

d Fish

p

rod

uct

Fruit an

d

Fruit p

rod

uct

Ve

getab

les

Milk an

d M

ilk p

rod

uct

Mixe

d

Oth

er

28,72

0,18 0,24 1,77

27,65

1,07

40,37





Country of origin

0,95

56,50

0,04

21,81

0,11 1,86

0,02

9,61

6,77

2,33

0,00

10,00

20,00

30,00

40,00

50,00

60,00

Belgium France Germany Greece Hungary Netherlands Spain UK North America

Other



Total number of Records:


9000


0,00

10,00

20,00

30,00

40,00

0,08 0,11 2,97

12,40

5,49 2,85 6,45

3,92

19,37

2,57

38,85

3,57

19,36

10,43

3,34 2,72

Stage/step of cold chain





Gain access to Cold

Chain Database platform

Predict quality and shelf

life of products

Determine food product

quality along the cold

chain

Manage your own time-

Temperature data

CONTRIBUTE

YOUR DATA:



Why should I contribute my data?

Retrieve time-temperature

profiles according to user defined criteria

Build a representative time temperature profile

Access to files &

Descriptive statistics

Quality & Shelf life data

Technology energy

requirements

Product quality status Shelf life at different stages

From production to consumption

What is ColdBase?




Cold Chain Predictor Software

Determination of the product quality status and shelf life at the different stages of the cold chain

Determination of product quality status and shelf life at the different stages of the cold chain

Cold Chain Database

Quality & Shelf Life Data

Representative t-T Profile along the

Cold chain

Food Quality Modeling

Monte Carlo simulation




Step 1: Build Cold Chain using the Cold Chain Database

Cold Chain Database

Quality & Shelf Life Data

Representative t-T Profile along the

Cold chain

Safety & Quality Modeling

Step 3: Use the Representative t-T profile and predictive kinetic models

Step 4: Estimate the Shelf Life Remaining at the end of the cold chain

Step 2: Build Representative t-T profile

Determining the product quality status and shelf life at the different stages of the cold chain

Cold Chain Database & FRISBEE CCP Software Cooked ham case study


http://frisbee-wp2.chemeng.ntua.gr/coldchaindb

Determining the product quality status and shelf life at the different stages of the cold chain:

Milk products case study





Cold Chain Predictor

Shelf Life Remaining at the end of the cold chain: 43.3 days









Taking into account the isothermal steps of representative t-T profile…


Tem

pe

ratu

re

Transportation (0.3 days)


(3 days)


Distribution warehouse (2.2 days)


Retail Display (1.9 days)

Transportation by consumer

(1 hour)

Consumer refrigerator (3 days)





Taking into account the isothermal steps of representative t-T profile…


Taking into account the actual

distribution of effective average

temperature per stage throughout the cold chain…



(3 days)


Distribution warehouse (2.2 days)


Retail Display (1.9 days)


(1 hour)

Consumer refrigerator (3 days)

Tem

pe

ratu

re





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60

70

41,60 41,88 42,17 42,45 42,74 43,02 43,30 43,59

Shelf Life Remaining (days)

Fre

qu

en

cy

[%

]

Cold Chain

Management Tools

Search within almost 9000 profiles of

the European Food Cold Chain Database




effectively manage and improve cold chain weak links. offer concepts and solutions for improving refrigeration and food product shelf life

management along the European food cold chain. allow one to run simulations and distribution scenarios based on real cold chain data. information from the Cold Chain Database may be retrieved and used to determine the

behaviour of food products along the cold chain avoiding costly and time-consuming field tests

FRISBEE Tools

European Cold Chain Database

Cold Chain Predictor Software




Further Data Collection - Expansion of Cold Chain Database

Validation of the FRISBEE developed tools – Field survey

studies in four European countries



Next Steps

Field tests conducted in 4 European countries

Greece, France, Belgium, UK

Production/Production Warehouse

Distribution Warehouse 2 distribution centers

Supermarket Warehouse and Display 24 supermarkets stores in 12 Greek cities

Consumer Transport


Validation of comprehensive database on cold chain in Europe - Field test in cold chain in

European markets



FOOD PRODUCT Product: Smoked turkey slices Packaging: An outside plastic transparent container within which the slices are placed vacuum packed (skin packed) in a second film Shelf life: 2 months

DATALOGGER Mini Nomad RFID temperature logger Omega Engineering Inc.

FIELD TEST DESIGN

Conducted in two time periods: June & October 2012

24 supermarket stores, 12 cities in Greece

Dataloggers retrieval has been completed

145 dataloggers were successfully retrieved




European markets

Field Test Cold Chain Stages


European markets



Production/Production Warehouse

Distribution Warehouse 2 distribution centers

Supermarket Warehouse and Display 24 supermarkets stores in 12 Greek cities

Consumer Transport


Production/ Production Warehouse

Distribution platform for supermarket

Distribution platform for hypermarket

Supermarket Hypermarket

Transport by consumer

Domestic refrigerator

Transport by consumer

Domestic refrigerator

2

2

6

4

5

11

2 11

12

4

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5

4


European markets



Production Warehouse

Supermarket Warehouse

Supermarket Outlet (open fridge)


Transportation to Distribution Center

Distribution Center

Transportation to supermarket


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Time (days)

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C)Field test time temperature profiles: Complete Cold Chain-Retrieved profile



Validation Experiments Cold chain simulation

Selection of time-temperature profiles Reproduced in time-temperature controlled cabinets 2 scenarios Representative t-T profile built by CCP software Worst case scenario

Sampling at predetermined times Simulated to different cold chain stages Parameters to be measured Total viable counts Lactic acid bacteria counts Sensory evaluation

Remaining shelf life determination Tools: Kinetic models FRISBEE Cold Chain Predictor Software

Time (days)

0 2 4 6 8

Te

mp

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ture

(o

C)

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20AB Éëéóéá

Time (days)

0 2 4 6 8

Te

mp

era

ture

(o

C)

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20AB Çñáêëåéï

Time (days)

0 2 4 6 8 10

Te

mp

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(o

C)

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20AB ×ï ëáñãï ò

Taking into account Retrieved t-T profiles from the conducted field tests




European markets

Data from all stages of the cold chain (from production to consumption) was

collected. Systematic analysis of these data allows identification of the weak links

of the cold chain and serves as a tool for cold chain management with regards

product quality and shelf life.

The Cold Chain Predictor software uses t-T profiles from the Cold Chain Database

to develop “representative” (statistically most probable) description of the cold

chain stages of different foods and estimate remaining shelf-life of different food

products based on user defined quality models or selected from a library.



CONCLUSIONS

Petros Taoukis [email protected]

http://www.frisbee-project.eu

COLD CHAIN EVALUATION AND MANAGEMENT USING FRISBEE PROJECT PREDICTION TOOLS

5th International Workshop Cold Chain Management June 10 – 11, 2013 Bonn

Laboratory of Food Chemistry & Technology School of Chemical Engineering

National Technical University of Athens

The research leading to these results has received funding from the European Community‘s Seventh Framework Programme (FP7/2007-2013) FRISBEE under grant agreement No245288




cold chain evaluation and management using ...ccm.ytally.com/fileadmin/user_upload/downloads/...cold...

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