Sudut Pandang Rekayasa Proses Pangan dalam Mempelajari Fenomena Dasar pada Ilmu Pangan

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ITP703 - Ilmu Pangan Lanjut Purwiyatno Hariyadi[email protected]

Sudut Pandang Rekayasa Proses Pangan

dalam Mempelajari Fenomena Dasar pada

Ilmu Pangan

Kuantifikasi perubahan selama pengolahan/penyimpanan untuk penarikan kesimpulan.

Contoh Kasus : Penentuan Umur Simpan Produk

PURWIYATNO HARIYADI

phariyadi.staff.ipb.ac.id

REKAYASA PROSES PANGAN ?

Food process engineering

• is a broad field that is concerned with the application of engineering

principles and concepts to the

handling, manufacturing, processing and distribution of foods.

(R P Singh, R.P. And Heldman, D.R. 2008. Introduction to Food Engineering. Academic Press)

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ITP703 - Ilmu Pangan Lanjut Purwiyatno Hariyadi_{[email protected]}

REKAYASA PROSES PANGAN ?

• is concerned with feasibility and

practicality, that is, will something work and how much will it cost?

• Food engineers are educated to analyze, synthesize, design, and operate complex systems that manipulate mass, energy, and information to transform material and energy into more useful form

Valentas, K.J., Levine, L and Clark, J.P. 1991. Food Processing Operation & Scale-up. Marcel Dekker Incorporated).

Food process engineering

“MAKE”

REKAYASA PROSES PANGAN ? –

Perkembangan 25 tahun terakhir ...

Efisiensi

.

- Batch  continuous processing - Improving process reliability - Reducing waste products, and - Effective energy utilization

“better value of foods”

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“SERVICE”

“MAKE” “MAKE”

+

Melayani kebutuhan masyarakat; Convinience, food service

REKAYASA PROSES PANGAN ? –

1970 ~1980 ~1990 ~2000 ~2013

FOOD SAFETY “CARE” “SERVICE” “MAKE” “MAKE” “SERVICE” “MAKE”

+

‘Care’ food business :

Perawatan kesehatan, kebugaran Perawatan lingkungan Perawatan thd “sosial”  fair trade

REKAYASA PROSES PANGAN ? –

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Lebih personal: Perscribed food and Nutrition

“CARE” “SERVICE” “MAKE” “CARE” “SERVICE” “MAKE”

REKAYASA PROSES PANGAN ? –

…KEDEPAN ?

“MAKE”

“SERVICE”

“MAKE”

1970 ~1980 ~1990 ~2000 ~2013

FOOD SAFETY

- You have to produce (even though with imperfect information)

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- Thinking like an engineer

- You don't have to be an engineer to think like one. - Many cases where it is a definite advantage to think

like an engineer.

ITP703

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Anda sebagai Ahli Pangan

- Thinking like an engineer

- You don't have to be an engineer to think like one. - Many cases where it is a definite advantage to think

like an engineer.

- You have to examine the process(es) involved in the problem to be solved.

- You don’t only look at the symptoms of a problem but looks at the processes involved to get to the root cause of the

problem.

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- Thinking like an engineer - ……… - ………..

- ……… - ………..

- Use proven analysis methods. Find and use a set of methods that have been proven to work in analyzing problems.

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Anda sebagai Ahli Pangan

- Thinking like an engineer - ……… - ………..

- ……… - ………..

- Use proven analysis methods. Find and use a set of methods that have been proven to work in analyzing problems.

 You have to know how to apply those methods

 BUT, more importantly, you have to know which methods to apply to a given situation.

 YOU have to know about and uses appropriate tools

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Anda sebagai Ahli Pangan

- You have to produce (even though with imperfect information):

- ………

- Learns why (not just how) something is done.

(If you only know how something is done, you will eventually do it wrong. You need to understand why something is done, to make sure that you are doing it correctly).

- Must come up with an answer to the problem.

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Anda sebagai Ahli Pangan

- You have to produce (even though with imperfect information):

- ……… - ………

- Keep your skills updated.

(Applying an out-of-date solution is almost as bad as not providing any solution. You have to constantly looks to see if new, better solutions to a problem exist).

You must fully understand the

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ITP703

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Anda sebagai Ahli Pangan

Back to basics:

• Understand the “physical, chemical, biological + engineering

phenomena” behind the problem you are facing (“object or problem of your study”)

ITP703

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Anda sebagai Ahli Pangan

Back to basics:

phenomena” behind the problem you are facing (“object or

problem of your study”)

"To measure is to know."

"If you can not measure it, you can not improve it."

"In physical science the first essential step in the direction of learning any subject is to find principles of numerical reckoning and practicable methods for measuring some quality connected with it. I often say that when you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind; it may be Quotations of

LORDKELVIN

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ITP703

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Anda sebagai Ahli Pangan

Back to basics:

phenomena” behind the problem you are facing (“object or problem of your study”)

BEWARE: Syndrome “the latest version“ software

garbage in garbage out

I have one good news and one bad news. The good news is that statistical analysis in now easy to perform. The bad news is that statistical analysis in now easy to perform

(Sastroasmoro, 2000) A C B D V_o Vo Rule of thumbs:

ITP703

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Anda sebagai Ahli Pangan

Perhatikan: "minimal experimental design" yang diperlukan, dll Back to basics:

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ITP703 - Ilmu Pangan Lanjut Purwiyatno Hariyadi[email protected] 100 80 60 40 20 0 0 2 4 6 8 10 t

Storage Time (months)

Obsrev ed V alue T2 T3 T1 < T2 < T3 T1

ITP703

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Anda sebagai Ahli Pangan

Perhatikan: "Number & frequency of sampling” yang diperlukan T25 T30 T35 T40

t

₁ t₁ t₁ t₁ t₁

t

2 t2 t2 t2 t2

t

3 t3 t3 t3 t3

t

4

t

4

t

4

t

4

t

4 Perhatikan: "Number & frequency of sampling” yang

ITP703



Anda sebagai Ahli Pangan

Menghasilkan 1 data: k,

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ITP703 - Ilmu Pangan Lanjut Purwiyatno Hariyadi_{[email protected]} Perhatikan: "Number & frequency of sampling” yang diperlukan

ITP703

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Anda sebagai Ahli Pangan

Menghasilkan 1 data: k, _T25C

Minimal Experimental Design?

Hati-hati dengan well established model : kinetika,

reologi, dll

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Anda sebagai Ahli Pangan

Back to basics:

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A B

Linier?

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Anda sebagai Ahli Pangan

Back to basics:

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Anda sebagai Ahli Pangan

Back to basics:

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Anda sebagai Ahli Pangan

Back to basics:

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Anda sebagai Ahli Pangan

Check!

• Theoretical background • Assumptions

• Your data?

– Unit and dimensions – Mass balance – Energy balance – Momentum balance – ETC

Back to basics:

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ITP703 - Ilmu Pangan Lanjut Purwiyatno HariyadiPurwiyatno Hariyadi_{[email protected]}_{[email protected]}

Case 1.

Kinetic of food quality changes

during processing and storage

-

Understanding Shelf Life of Foods

Purwiyatno Hariyadi

Department Food Science & Technology, Faculty of Agricultural Technology

and

Southeast Asian Food & Agricultural Science & Technology (SEAFAST) Center,

Bogor Agricultural University

Main References :

Labuza,T. 2007. Lecture Note

(http://www.ardilla.umn.edu/tplabuza.html)

Kilcast, D and Subramaniam, P. (Eds). 2000. The stability and shelf-life of food. Woodhead Publishing Limited, Abington Hall, Abington, Cambridge CB1 6AH, England

Hariyadi, P. 2006. Handouts and Modules of Shelf Life Determination (in Bahasa Indonesia). Seafast

Center/Department of Food Science and Technology, Faculty of Agriculture Technology, Bogor Agricultural University.

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What is Shelf life

?

Everything has a shelf life

The period between manufacture and retail

purchase of a food product during which the

product is of satisfactory quality

(IFT; 1974).

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The time during which the food product will :

1. remain safe;

2. be certain to retain desired sensory, chemical, physical and microbiological characteristics;

3. comply with any label declaration of nutritional data,

when stored under the recommended

conditions.

(IFST Guidelines, 1993)

What is Shelf life

?

Shelf-life as the period during which a food product

maintains its microbiological safety and suitability at

a specified storage temperature and, where

appropriate, specified storage and handling

conditions

(Codex Alimentarius, CAC/RCP-46; 1999) .

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Open Dating?

Yahoo/Google ?

Open shelf-life dating

Open dating is the use of dates

(means the use of legible terms such

as a day, month, and year; NOT a

code, or a symbol)

on a can or package

of food that gives the consumer

(including distributors, wholeseller or

retailers)

an indication of when the food

was packaged or by when it should be

sold or used.

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Open shelf-life dating

Why?

1. Encourages better handling practices

by wholesalers, retailers, and

consumers by expediting the sale or

use of food near the end of shelf life.

2. Increase consumer confidence in the

freshness of food purchased.

3. Better handling practices attributed to

open dating could minimize nutrient

loss.

Can be expressed as :

1. date of pack or manufacture,

2. pull date or sell-by date,

3. best-if-used-by date,

4. expiration date or use-by date, or

5. combination of two of the above.

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Expressed as Expiration date

• Date that indicates that before that

date food products is still in

“satisfactory quality” or “desired”

condition”

(provided that product

stored under the recommended

conditions)

• END of shelf life

Open shelf-life dating

Expressed as Expiration date

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Expressed as Expiration date

Open shelf-life dating

What is “satisfactory quality“ ?

What is “desired” ?

Except in situations in which

microbiological safety is an issue, the

definition of shelf-life is related to the

positioning of the product in the

market in terms of quality and

customer perceptions of that quality.

END of SHELF LIFE?

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END of SHELF LIFE?

• What is specific quality properties ?

• What is “desired” quality? What is “satisfactory quality”? • Who determined “desired”/”satisfactory quality”?

• At what condition food product is not in ”satisfactory quality” condition?

• How “satisfactory quality” changes during

distribution, storage, display ???

• Kinetic of quality changes

What is “critical factor” for

customer perceptions of quality ?

What is “critical factor” for

customer perceptions of quality ?

Kilcast, D and Subramaniam, P.

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What is “critical factor” for

customer perceptions of quality ?

(Eds). 2000.

What is “critical factor” for

customer perceptions of quality ?

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What is “critical factor” for

customer perceptions of quality ?

(Eds). 2000.

What is “critical factor” for

customer perceptions of quality ?

“critical Factor”

Which

one?

a. (Micro)biological factors : bacteria, mold, yeast b. Chemical factors : vit C., thiamin, riboflavin, etc c. Nutritional factors : protein, fats, digestion quality, etc d. Fucntionality factors : enzyme activity, probiotic acitivity,

antioxidant activity, etc

e. Physical factors: Viscosity, texture, color, emulsion stability, etc

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What is “critical factor” for

customer perceptions of quality ?

“critical Factor”

Which

one?

FACTORS INFLUENCING SHELF-LIFE OF FOODS

A. intrinsic (properties of the final product) :

• Water activity (aw) (available water). • pH value and total acidity; type of acid. • Available oxygen.

• Nutrients.

• Natural microflora and surviving microbiological counts.

• Natural biochemistry of the product formulation (enzymes, chemical reactants).

• Use of preservatives in product formulation (e.g. salt).

What is “critical factor” for

customer perceptions of quality ?

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What is “critical factor” for

customer perceptions of quality ?

FACTORS INFLUENCING SHELF-LIFE OF FOODS

B. Extrinsic factors (factors the final product encounters as it moves through the food chain) :

• Time–temperature profile during processing. • Temperature.

• Relative humidity (RH). • Exposure to light (UV and IR). • Environmental microbial counts.

• Composition of atmosphere within packaging. • Subsequent heat treatment (e.g.

Reheating/cooking before consumption). • Consumer handling.

• Experiments

& Analysis

• Emperical

Analysis

SHELF LIFE Informations needed :

• Quality critical factor(s)? • Value of critical factor(s)

• Maximum value (quality at the factory gate)

• Minimum value of critical factor(s) : minimum quality at the end of shelf-life

• Kinetic parameters for quality

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Measure either loss of A, desirable quality marker,

or production of B, undesirable quality marker

A = quality

t = time

k = rate constant

n = reaction order

PRINCIPLES OF SHELF LIFE DETERMINATION

KINETIC OF QUALITY CHANGES

A  B

-dA/dt = kA

n

Zero order (n=0) quality changes



-dA/dt = kA

n

PRINCIPLES OF SHELF LIFE DETERMINATION

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Zero order (n=0) quality changes

-dA/dt = k

_z

or

A = A

₀

- k

_z

t

PRINCIPLES OF SHELF LIFE DETERMINATION

KINETIC OF QUALITY CHANGES

If Q

_s

is quality level at the end of shelf life, then

A

_s

= A

₀

- k

_z

t

_s

or

t

_s

= (A

₀

-A

_s

)/ k

_z

at which

PRINCIPLES OF SHELF LIFE DETERMINATION

KINETIC OF QUALITY CHANGES

Zero order (n=0) quality changes

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ITP703 - Ilmu Pangan Lanjut Purwiyatno Hariyadi[email protected] Just Illustration:

A_o= 100 units at time zero A = 60 units at 20 weeks

What is k_zif quality change follow zero order ? Remember, k_zis a slope ∆Y/∆X

= (100-60)/(20-0)= 40/20 = 2 units per day Thus 2 units per day x 20 days is loss of 40 units (with 60 units of quality left)

PRINCIPLES OF SHELF LIFE DETERMINATION

KINETIC OF QUALITY CHANGES

Zero order (n=0) quality changes

-dA/dt = k

_z

or

A

_t

= A

₀

- k

_z

t

100 80 60 40 20 0 Quality V alue

Firts order (n=1) kinetic of quality changes

-dA/dt = kA

1

_

_{-dA/dt = k}

f

A

PRINCIPLES OF SHELF LIFE DETERMINATION

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Firts order (n=1) kinetic of quality changes

-dA/dt = kA

1

_

_{-dA/dt = k}

f

A

PRINCIPLES OF SHELF LIFE DETERMINATION

KINETIC OF QUALITY CHANGES

or

ln (A/A

₀

) = - kt

Firts order (n=1) kinetic of quality changes

-dA/dt = k A

1

PRINCIPLES OF SHELF LIFE DETERMINATION

KINETIC OF QUALITY CHANGES

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Firts order (n=1) kinetic of quality changes

-dA/dt = k A

1

PRINCIPLES OF SHELF LIFE DETERMINATION

KINETIC OF QUALITY CHANGES

or

log (A/A

₀

) = - (k

_f

/2.3)t

If A

_s

is A at the end of shelf life, then

ln (A

_s

/A

₀

) = - k

_f

t

_s

Or

t

_s

= [ln(A

₀

/A

_s

)]/k

_f

Or

t

_1/2

= 0,693/ k

_f

PRINCIPLES OF SHELF LIFE DETERMINATION

Firts order (n=1) kinetic of quality changes

-dA/dt = kA

or

ln (A/A

₀

) = - k

_f

t

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ITP703 - Ilmu Pangan Lanjut Purwiyatno Hariyadi[email protected] Just Illustration :

Ao = 100 units at time zero A = 60 units at 20 weeks

What is k_f if quality changes follows first order? Remember slope is ∆Y/∆X but on Ln scale so

= (Ln( 60/100))/(20-0) = 0.51/20 = 0.02554 day-1

A= A_oe-k

ft  A= 100 x e-0.02554x20 = 100 x e-0.511 = 60

PRINCIPLES OF SHELF LIFE DETERMINATION

Firts order (n=1) kinetic of quality changes

-dA/dt = kA

or

ln (A/A

₀

) = - k

_f

t

KINETIC OF QUALITY CHANGES

Examples of kinetic of quality change of slecetd

product during storage/processing

Zero Order

• Overall quality of frozen food • Non-enzimatic browning

First Order

• Vitamin loss/degradation • Mikcorbial inactivation

• Oxidatif deterioration of color • Thermal degradation of texture

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ITP703 - Ilmu Pangan Lanjut Purwiyatno Hariyadi_{[email protected]} Quality degradation during

storage : Difference between zero and first order kinetics

Zero or First

Order

Kinetics?

Quality degradation during

Zero or First

Order

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Zero or First

Order

Kinetics?

Zero or First

Order

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Zero or First

Order

Kinetics?

x

Zone of data that may distinguish between zero and first orfer kinetics

Zero or First

Order

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Zero or First

Order

Kinetics?

To be able to distinguish easily wwther quality changes is following zero or first order; perform experiment until the extent of quality loss is more than 50%

Published values

(27.7o_C)

Recommendation (Labuza, T. 2007)

• If few data points with time and

• End Quality level is less than 50%

change from initial



Then KISS : Use zero order

Zero or First

Order

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Case 2:

Predicting Shelf life of Food by

Accelerated Shelf-life Testing (ASLT)

method  Using Arrhenius model

Purwiyatno Hariyadi

Department Food Science & Technology, Faculty of Agricultural Technology

and

Southeast Asian Food & Agricultural Science & Technology (SEAFAST) Center,

Bogor Agricultural University

Main References :

Labuza,T. 2007. Lecture Note

(http://www.ardilla.umn.edu/tplabuza.html)

Kilcast, D and Subramaniam, P. (Eds). 2000. The stability and shelf-life of food. Woodhead Publishing Limited, Abington Hall, Abington, Cambridge CB1 6AH, England

Hariyadi, P. 2006. Handouts and Modules of Shelf Life Determination (in Bahasa Indonesia). Seafast

Center/Department of Food Science and Technology, Faculty of Agriculture Technology, Bogor Agricultural University.

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Accelerated Shelf Life Test

Arrhenius Method

Principles : accelerate rate of quality loss by increasing temperature of storage

Quality loss  -dA/dt = kAn

Rate constant (k) depends on Temperature :

k = k₀.exp-Ea/RT k = rate constant

k₀= frequency factor (NOT as function of T) Ea = Activation Energy

T = Absolute Temperature (K)

R = Gas constant; 1,986 kal/mol (8.314 J/mol.K)

k (1/T) T R a E e o k k =

-Accelerated Shelf Life Test

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ITP703 - Ilmu Pangan Lanjut Purwiyatno Hariyadi[email protected] Slope - Ea/R Ln k = Ln ko - (Ea/R)(1/T) Ln k (1/T)

Arrhenius Plot

Ln k_o

Accelerated Shelf Life Test

Arrhenius Method

Example : Carbohydrate at amorphous condition may undergoes crystalization at low temperature

.

Know your product WELL!

Retrogradation • Texture hardening • Release of water • Bread staling

Accelerated Shelf Life Test

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ITP703 - Ilmu Pangan Lanjut Purwiyatno Hariyadi_{[email protected]} • Rate of “bread staling” incease as temperature of storage decrease (4°C - 40°C) • Maximum “staling” rate : 4°C.

Example : Carbohydrate at amorphous condition may undergoes crystalization at low temperature

.

Accelerated Shelf Life Test

Arrhenius Method

• Arrhenius anomali. Effect of temperature on “bread staling” • Negative Ea 3.2 3.3 3.4 3.5 3.6 1/T x 103 Ln (staling rate)

Accelerated Shelf Life Test

Arrhenius Method

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ITP703 - Ilmu Pangan Lanjut Purwiyatno Hariyadi[email protected] 100 80 60 40 20 0 0 2 4 6 8 10

Storage Time (months)

V alue of Quality Marker T1 T2 T3 T1 < T2 < T3 Number & frequency of sampling

!

Accelerated Shelf Life Test

Arrhenius Method -- in Practices

Do experiment and measurement of quality loss –at least-at

3 different temperatures of storage  Statistical problems • Can’t do predictions with one temperature

Accelerated Shelf Life Test

Arrhenius Method -- in Practices (1a)

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• Two points always give a straight line

Accelerated Shelf Life Test

Arrhenius Method -- in Practices (1a)

ln k

1/T

• Two points always give a straight line • Three points give poor statistics

Accelerated Shelf Life Test

Arrhenius Method -- in Practices (1a)

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• Choose temperature of storage higher that normal T of storage

• Temperature od storage will not cause changes in mechanism of quality loss

• Again; know your product WELL hub Arrhenius:

A B

ln k

1/T

Range Of Storage Temp Range of ASLT Temperature Maximum ASLT Temperature

Accelerated Shelf Life Test

Arrhenius Method -- in Practices (1b)

Type of Product Temperature of

ASLT (°C) Temperature Control (°C)

Canned foods 30, 35, 40, 45 4

Dried foods 30, 35, 40, 45 -18

Chilled Products 5, 10, 15, 20 0

Frozen products -5, -10, -15 < -40 So, which three (3) different temperatures of storage? Know your product WELL

Accelerated Shelf Life Test

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Accelerated Shelf Life Test

Arrhenius Method -- in Practices (3a)

• Frequency of sampling 



Know your product WELL

Shelf life at 5o_{C= 12 months}

If Q₁₀=2  ASLT (at 25o_{C) : 3 months}

If Q₁₀=3  ASLT (at 25o_{C) : 1.3 months}

If Q₁₀=4  ASLT (at 25o_{C) : 23 days}

Number of samples?Statistical problems

• Can’t do predictions with one temperature • Two points always give a straight line

Accelerated Shelf Life Test

Arrhenius Method -- in Practices (3a)

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Value of k at normal storage condition  May be predicted/calculated using Arrhenius Equation :

k = k_o.exp-Ea/RT ln k = ln k_o– Ea/R (1/T) Ta (normal T of storage) Ln k 1/T Zone of experiment -accelerated T1 T2 T3 And, extrapolate value of k at normal T of storage:

Accelerated Shelf Life Test

Arrhenius Method -- in Practices (4)

k1 k2

k3

Determinn A_s(quality value at end of shelf life). • Standard of identity, SNI, etc

• Sensory properties

Shelf life may be predicted using :

t_s= (A₀-A_s)/k_z; if quality changes follow zero order kinetics ts= [ln(A0/As)]/kf; if quality changes follow first order kinetics

Accelerated Shelf Life Test

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Accelerated Shelf Life Test

Arrhenius Method -- in Practices (6)

Accelerated Shelf Life Test

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Accelerated

Shelf Life Test

Arrhenius

Method

--in Practices (8)

Accelerated Shelf Life Test

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Accelerated Shelf Life Test

Arrhenius Method -- in Practices (10)

Accelerated Shelf Life Test

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Accelerated Shelf Life Test

Arrhenius Method -- in Practices (12)

Degree of losses of selected vitamin predicted using Arrhenius model as compared to its actual losses

Losses (%) after

6 months of storage , 20o_{C, RH 75%}

Vitamin

Predicted by Result of Arrhenius Model Analysis Vitamin C

(ascorbic acid) 24,0 23,0

Vitamin A 15,0 10,0

Folic Acid 8,1 7,4

Accelerated Shelf Life Test

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