9 - 10_ shelf-life evaluation using ALST.pptx

TPN1333 Food Packaging and Storage Technology
Food Science and Technology Department
Faculty of Agricultural Engineering and Technology, IPB
Internationally Approved Food Technology Program by IFT and IUFoST
Food Shelf-life Evaluation –
Accelerated Shelf-life Test

Internationally Recognized Undergraduate Program by IFT & IUFoST
2
Learning Outcome
Upon successful completion of this topic,
students will be able to:
 determine the shelf life of food by using
accelerated shelf life test (Arrhenius and
Labuza Equation).

3
11.1 ASLT Method with
Arrhenius
11.2 ASLT with Critical
Moisture Content
Sub Topic

Shelf-life Prediction Model (ASLT Method)
ASLT
Method
Arrhenius
Critical Moisture
Content
MSI Curve
Model
Modified MSI
Model

Data Extrapolation Method by ASLT
Storage Condition
Data
Extrapolation
Laju
kerusakan
Accelerating Factors

Arrhenius Model
To predict the shelf-life of processed foods
deterioted by chemical reaction
Temperature dependence: fat oxidation, Maillard
reaction, Vitamin C oxidation
Examples: Sterilized canned foods, UHT milk,
Snack/chips, pasteurized fruit juice, instant noodle,
frozen meat/shrimp/fish, chilli sauce, jam, pasta
product, fried peanut, etc

Experiment: Arrhenius Model

Experimental Steps
Identify product
characteristics
Identify critical
parameters
Determine anal.
method
Experiment:
Storage T, t
Data collection
Determine Qo
and Qc
Data analysis:
Determine reaction order
(0 or 1)
Determine kT
Determine kT at storage
temp. (Arrhenius model
Calculate SL
Select significant critical
parameters
Verification

Step 1: Identify product characteristics
Identify ingredients in products.
 What are the critical ingredients?
 Is there any potential component reactions or
interactions during storage?
Identify storage temperature: markets, displays, or
consumers levels

Step 2: Identify Critical Parameters Causing Product
Deterioration
 Based on experience, what are the major quality attributes
cause product rejection?
 Rancidity (fat oxidation): FFA, TBA value.
 Colour change (Maillard reaction): color measurement
 If unknown well, select several potential critical parameters.
 If any product claim, select as a critical parameters
 Exp. rich in DHA/EPA.
 Commercially sterilized canned foods: product deterioration is
not caused by microbiological factors

Step 3: Determine Analytical Methods
Analysis:
 Fat oxidation: TBA value, peroxide value
 Maillard reaction: Color measurement by
colorimeter
 Sensory evaluation: Rancid odor, color
Consider cost for analysis

Step 4:
Experiment at Accelerated Storage Temperature
Condition
Consider real storage temperature. Select min. 3
accelarated temp above real storage temperature
 Exp: Room temperature (28o
C) : 35, 45, 55
 Frozen temperature (-25o
C): -15, -10, -5o
C
Make sure that the storage temperature does not
cause change of deterioration mechanism
 Exp: microbiological growth

Example of storage temperature
and time of analysis
Real
storage
temp (o
C)
Experiments
Products
Storage
Temp (°C)
Time (day)
Canned fruits, juice,
UHT milk, instant
noodle, fried
peanut
28-30 35, 45, 55
0, 3, 7, 14,
21, 28, 35
Chilled Products 5 10, 15, 20
0, 3, 7, 14,
21, 28, 35
Frozen
meats/shrimps
-25 -15, -10, -5
1, 2, 3, 4, 5,
8, 12,

Step 5: Data Collection
 Number of samples: considered storage temp/time, types of
analysis, and replication.
Sample = T* t* rep*sample per period
of anal
 Use primary packaging
 Use calibrated incubators (at least 3)
 Control: normal storage temperature
 Collect samples per periodic and analyze

Incubator for Sample Storage

Step 5: Data Collection
Tabulate analytical data in table formats.
Use separate table for each quality parameters (Excel)
Calculate average for each data.

Contoh Format Data Hasil Pengamatan

Step 6:
Identify Initial Product Quality (Qo) and Quality
Limits (Qc)
Initial quality (Qo) for freshly processed products
(day 0).
Quality limits (Qc):
 The quality limit for product rejection by
consumers.
 Correlate the objective analysis with sensory
analysis: Qc for TBA based on rancid odor
development
 For product claim: percentage of component
los (exp. If 20% vitamin C losses, Qc 80%)

Step 7:
Determine Order Reaction abd kT
Plot graphic: Quality (Qt) vs time (t, day) according
to Order 0 and 1.
Order 0 : Qt = Qo – kTt
Order 1 : LnQt = LnQo – kTt
Determine equation model: kT (slope) and R2
.
Reaction order 0 or 1: select kT with higher R2:

Step 7:
Determine ReactionOrder and kT
The predicted shelf life for zero order will be shorter
than first order
t
Ln
Q
Slope = - kT
Order 1
T1
T2
T3
t
Q
Slope = - kT
Order 0
T1
T2
T3

Step 8:
Select Significant Critical Parameters
Consider :
 R2
of reaction rate constants (kT) :
Usually >
0.75
 kT increase consistently by temperature

Step 9:
Calculate kT at Real Storage Temperature (Using Arrhenius
Model)
 Plot kT versus storage temperature using Arrhenius model (in form
of logarithmic equation:
Ln kT = Ln ko - Ea/RT)
where:
kT = reaction rate constant at T
ko = Frequency factor
Ea = activation energy
T = absolute temperature (K): To
K= 273+ To
C
R = Gas constant (8.314 J/mole.K)
Ln
K
Slope (K) = - Ea/R
1/T

Step 9:
Calculate kT at Real Storage Temperature
(Using Arrhenius Model)
 Model Arrhenius dibuat dalam bentuk persamaan
logaritmik. Plot hubungan antara LnkT (sumbu y) versus
1/T (sumbu x).
LnkT = Lnko – Ea/RT
 Calculate kT at real storage temperature

Tahap 10:
Calculate Predicted Shelf-life
 Shelf-life (ts) at a storage temperature:
Order 0 : ts = (Qo-Qs)/kT
Order 1 : ts = [ln(Qo/Qs)]/kT
 kT comes from Arrhenius equation
 Plot graphics storage temp vs shelf-life
Shelf-life
(day)
Storage Temp (o
C)

Step 9:
Predicted Shelf-life
 The predicted shelf-life:
 Can be simulated at several storage
temperature
 May differ among quality parameters
 Management decision:
 Select the shortest shelf-life
 Consider storage temperature
 Consider length of product sale

Case Study
Shelf-life Determination of Instant Noodles
Product characteristics:
 Fried instant noodles
 Mushroom flavor
Quality loss factors
 Rancid odour: fat oxidation
 Color changes: Maillard reaction
 Loss of mushroom/cheese flavor

Experimental Design
Storage temperature: 45, 51, 60o
C
Periode of data collection: 0, 7, 14, 21, 27, 35 days
Controlled sample: 30o
C
Samples analyzed: noodles and spice powder
Analytical methods
 Peroxide value
 Lab colorimeter
 Sensory testing: rating difference method (8 trained
panelists)

Examples of Reaction Rate Constant (kT)
Parameter
Temp
(o
C)
Reaction order 0 Reaction order 1
Slope (kT) Intercept R2 Intercept
kT R2
Peroxide
value
45 0,0118 0,904557 0,980 0,0109 0,094 0,959
51 0,0171 0,956614 0,936 0,0144 0,039 0,890
60 0,1272 0,311312 0,835 0,0504 0,147 0,957
Lightness
(L)
45 -0,2293 71,50467 0,921 -0,0033 -4,270 0,925
51 -0,5602 70,106 0,925 -0,0089 -4,251 0,943
60 -0,9911 67,75 0,893 -0,0178 -4,219 0,926

Step 9:
Verification and Monitoring
To verify between predicted and actual shelf-life
Store and observe products at actual storage
temperature

ASLT for Reaction Kinetic
approaches:

Shelf-life Prediction Model (ASLT Method)
ASLT
Method
Arrhenius
Critical
Moisture Content
Critical Moisture
Content Model
Modified CMC
Model

Courtesy of Feri Kusnandar/ITP/Fateta/IPB November 28, 2025
Critical Moisture Content/ MSI
Method

ASLT:
Critical Moisture Content Method
Product deterioration due to water absorption. Exp:
biscuits, chips, flour
Loss of quality: agglomeration, loss of crispiness,
incresed stickiness
No chemical reaction effect is considered
Critical moisture content (Mc): level of moisture when
product is rejected sensorically
Time to reach critical moisture content (Mo-Mc):
product shelf-life

Method 1:
Critical Moisture Content Method
Factors influencing shelf life
 The difference between initial moisture content
(Mo) and critical moisture content (Mc).
 Water vapor permeability of packaging (k/x). The
lower k/x, the lower water vapor migrate into
product.
 Packaging dimension (A, m2
)

Labuza Model
t = Time to reach critical moisture content (t)
Me = Equilibrium moisture content (g H2O/g dry solid)
Mo = Initial moisture content (g H2O/g dry solid)
Mc = Critical moisture content (g H2O/g dry solid)
k/x = WVTR/Po = water vapor transmission rate (g/m2
/day) at a
certain T and RH.
A = Packaging dimension (m2
)
Ws = Initial dried weight of product (g)
Po = Absolute pressure (mmHg)
b = Slope of MSI curve
)
)(
(
*
)
/(
)
(
b
P
W
A
x
k
M
M
M
M
Ln
t
o
s
c
e
o
e 



Experimental Steps
Identify product
characteristics
Identify method of
analysis
Determine Mo and
Ws
Determine Mc
Develop MSI
experimentally
Determine MSI
slope (b)
Determine k/x
Calculate SL
(Labuza model)
Verification

Step 1:
Identify Product Characteristics
Identify product characteristics: usually dried
products
Identify product deterioration
 Exp: loss of crispiness, agglomeration, sticky

Critical Parameter
Example: survey to consumer for biscuits
Critical parameter: Texture
0
5
10
15
20
25
30
35
Tekstur Rasa Aroma Warna
Texture Taste Aroma Color

Step 2
Select Analytical Method: Moisture Content
Consider product characteristics
Methods
 Oven (105o
C, 3 hours): heat stable foods
 Vaccum Oven (60-70o
C, 3 hours): heat sensitive
foods
 Karl Fischer: low moisture foods (exp: hard
candy)

Step 3:
Determine Mo and Ws
 Freshly processed products
 Mo: Avarage of Initial Moisture contents (db), minimal
10 times measurement
 Ws : weight of product corrected by its Mo
1 -
Mo
1 + Mo
x 100
% Solid =
Ws = m (weight basis) x % solid (g)

Step 4:
Determine Critical Moisture Content (Mc)
Store product at high RH (91% or 96%) with
packaging or at open air (without packaging).
Develop sensory sheet of quality parameters
Observe periodically (per hour) by trained panelists
(5-7) until product starts to loss of quality.
Measure moisture content when product started to
be rejected: Mc

Step 5:
Develop MSI Curve Experimentally
 Prepare series of saturated salt solutions (10-90% RH)
LiCl KCH3CO2 MgCl2 K2CO3 Mg(NO2)2 NaNO2 NaCl KCl

Chamber for Saturated Salt Solutions

Step 5:
Develop MSI Curve Experimentally
 Place samples (known initial weight and initial moisture (Mo))
into chambers containing different saturated salt solutions (10-
96% RH)
 Store chamber in incubator (usually set at 30o
C).
 Weigh samples periodically (exp. every 5 hr) until constant
weight is reached (the increase of sample weight < 2%).
 Measure moisture content: Equilibrium moisture content (Me)
at different RHs
 Develop plot of RH (x axis) vs Me (y axis).
 Determine slope (b) of the liniear MSI curve: passing Mo, Mc
and MeRH.
 Mo < Mc < MeRH

Step 5:
Develop MSI Curve
Curve of moisture content vs time at different RH

Example MSI Curve
0
5
10
15
20
25
30
0 20 40 60 80 100
Equilibrium
Me
(%)
RH (%)

Step 6:
Determine Me at Storage RH
 Determine Me from the liniear equation of MSI
curve.
 Various storage RHs can be simulated

Step 7:
Water Vapor Permability and
Surface Area of Packaging
k/x : check packaging specification/certificate of
analysis
When WVTR at RH at T known:
 k/x = WVTR/Po; Po at T
A is two side surface area of primary packaging

Tahap 8:
Calculate Shelf-life
 Input the experimental data into Labuza model
)
)(
(
*
)
/(
)
(
b
P
W
A
x
k
M
M
M
M
Ln
t
o
s
c
e
o
e 



Case Study:
Shelf life Determination of Biscuits
 Product: Biscuit A & B
 Initial moisture content (Mo)
 Biscuit A: 0.0183 g H2O/g solid
 Biscuit B: 0.0249 g H2O/g solid
 Packaging materials:
 Metalized
 PP
 Critical quality parameter : texture (firmness, crispiness)
 MC analytical method: Gravimetry (AOAC)
 Determine Shelf-life at different RH: 75%, 80%, 85% at 30o
C

Data experiment:
Equlibrium MC at different Aw
Aw (Saturated
Salt Solution)
Equilibrium Moisture Content
(g H2O/g solid weight)
Biscuit A Biscuit B
0.3240 0.0490 0.0410
0.5600 0.0774 0.0890
0.7510 0.1239 0.1643
0.8360 0.2089 0.2342
0.9230 0.2791 0.3073

Determine the Slope of the Curve
0
5
10
15
20
25
30
0 20 40 60 80 100
Equilibrium
Me
(%)
RH (%)

Experimental Data
No Parameter Unit Biscuit A Biscuit B
1.
Initial Moisture
content (Mo)
g H2O/g solid 0.0183 0.0249
2. Slope MSI curve (b) - 0.1180 0.1743
3.
Permeability (k/x):
Metallized
packaging
PP packaging
g H2O/m2
.day.mmHg
g H2O/m2
.day.mmHg
0.0136
0.0739
0.0180
0.0739
4.
Solid weight of
sample (Ws)
gram 216.0017 122.6230
5.
Surface area of
packaging (A)
m2
0.0588 0.0359

Calculated Shelf-life
Umur simpan Biskuit A Biskuit B
Metallized packaging (months)
RH 75% 17.4 12.4
RH 80% 13.3 9.9
RH 85% 9.9 8.0
PP packaging (months)
RH 75% 5.1 5.6
RH 80% 4.6 4.9
RH 85% 4.2 4.4

Courtesy of Feri Kusnandar/ITP/Fateta/IPB November 28, 2025
Modified Critical Moisture Content
Method

Method 2:
Modified Critical Moisture Content Method
Product characteristics:
 Very higroscopic product.
 Difficult to reach equilibrium moisture content
(Me) at high RH
 Usually high sugar content. Exp. Hard candy
MSI curve is not sigmoidal. Liniear curve and slope b
cannot be determined
Conventional Labuza model is not applicable

Modified Labuza equation
Principle: water migration is due to air pressure
difference between inside and outside packaging
P
A
x
k
W
M
M
t s
o
c



)
(
)
(
P = Pressure difference betwee Pout and Pin
(mmHg)
Mc-Mo = Difference initial moisture content and critical
moisture content
Method 2:
Modified Critical Moisture Content Method

Water migration due to air pressure difference
 If Pout > Pin, water vapor migrates from outside to
inside. Moisture content of product will increase
 If Pout < Pin, water vapor migrates from inside to
outside (product will dry, less moisture content).
In shelf-life model: Pout>Pin
If it is assumed that RH inside packaging = aw*100,
So: Pin = aw*Po
Time for water migration to reach Mc : product shelf
life
Principle of Modified Critical Moisture Content Method

Experimental Steps
Identify product
characteristics
Identify method of
analysis
Determine Mo and
Ws
Determine Mc
Measure initial Aw
of product
Calculate P
Determine k/x
Calculate SL
(Labuza model)
Verification

Step 6:
Determine Air Pressure Difference (P)
Pout = Po* RH
Pin = Po* Aw
Po : water pressure at certain temperature (water
vapor table; Labuza, 1982).

Step 7:
Predict Shelf-life at certain RH
Predicted shelf-life: at different RH and temperature.
Use water vapor table to determine Po at different
storage temperature (at a limited range)
Calculated shelf-life: The higher storage temperature,
the shorter shelf-life.

Tahap 7:
Predict Shelf-life at Certain RH
The determinant of product shelf-life:
Type of packaging
Storage temperature and RH
Initial moisture content
Initial aw

Case Study:
Shelf life Determination of Hard Candy
Product: Hard candy A & B
Initial moisture content: 2.20 g H2O/100 g solid
Initial Aw: 0.62
Packaging :
 Product A: Metalized PP
 Product B: PP
Critical quality parameter : hardness, stickiness
MC analytical method: Karl Fischer
Determine Shelf-life at different storage RH and temp.:
RH (70%, 75%, 80%); T (25o
C, 30o
C)

Sensory Parameter to determine Critical MC (Factory Standar)
 Sensory attributes
 Contact clarity
 Wrapper sticking
 Deformity
 Surface appearance (dullness)
 Colour
 Hand stickiness
 Grain (depth
 Total flavour intensity
 Flavour change (off notes)
 Mouthfeel roughness
 Tooth stickiness.
 Score scale: 1 (best) dan 5 (worst)
 Employ 7 trained panelists

Experimental Data
No Parameter Unit
Hard
Candy A
Hard
Candy B
1.
Initial Moisture
content (Mo)
g H2O/100 g solid 0.0183 0.0249
2. Initial Aw - 0.62 0.62
3.
Permeability (k/x):
Metalized PP (A)
PP (B)
g H2O/m2
.day.mmHg
g H2O/m2
.day.mmHg
0.0105
0.0016
4.
Solid weight of
sample (Ws)
gram 3.100 3.130
5.
Surface area of
packaging (A)
m2
0.00175 0.00175

Determine P
Temp
(o
C)
Po (mmHg) RH
(%)
Aw (sample
A&B)
Pout
(Po*RH)
Pin
(Po* Aw)
P
(mmHg)
25 23.76 70 0.62 15.63 14.73 1.90
75 17.82 14.73 3.09
80 19.00 14.73 4.28
30 31.82 70 0.62 32.95 19.73 2.55
75 35.50 19.73 4.14
80 37.76 19.73 5.73
P
A
x
k
W
M
M
t s
o
c



)
(
)
(

Data Analysis and Calculated Self-life of Hard
Candy

70
ありがとうございました
谢谢
ขอขอบคุณ
‫شكرا‬ ‫شكرا‬
‫شكرا‬

9 - 10_ shelf-life evaluation using ALST.pptx

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