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Shelf life prediction of packaged cassava-flour-based baked product

by using empirical models and activation energy for water vapor

permeability of polyolefin films

Ratchaneewan Kulchan a, Waraporn Boonsupthip b, Panuwat Suppakul c,*

a Thai Packaging Centre, Thailand Institute of Scientific and Technological Research, 196 Phaholyothin Rd., Ladyao, Chatuchak, Bangkok 10900, Thailandb Department of Food Science and Technology (Food Engineering Major), Faculty of Agro-Industry, Kasetsart University, 50 Phaholyothin Rd., Ladyao,

Chatuchak, Bangkok 10900, Thailandc Department of Packaging and Materials Technology, Faculty of Agro-Industry, Kasetsart University, 50 Phaholyothin Rd., Ladyao, Chatuchak, Bangkok 10900, Thailand

a r t i c l e i n f o

Article history:

Received 14 February 2010

Received in revised form 18 April 2010

Accepted 20 April 2010

Available online xxxx

Keywords:

Cassava-flour-based baked product

Moisture sorption

Empirical model

Activation energy

Shelf life

Packaging

a b s t r a c t

Moisture sorption kinetics and isotherms of cassava-flour-based baked product were investigated. Empir-

ical models were testedto fit the experimental data. Texturalchanges of the product were investigated. In

addition, activation energies (Ep) for water vapor permeability (WVP) of polyolefin films were deter-

mined. Finally, the product was packaged in low-density polyethylene (LDPE) or oriented polypropylene

(OPP) pouches, and stored at 30 1 C and 50 2% RH to simulate actual storage conditions and to deter-

mine shelf life. This actual shelf life was compared to the predicted shelf life by using empirical models

and Epfor WVP. Moisture sorption kinetics was more rapid during the initial stage, while a lesser amount

of moisture was adsorbed as adsorption time increased. The higher the relative humidity used, the more

pronounced the effect. Thesigmoidal moisturesorption isotherms of this product canbe classified as type

II. The GAB model was found to be the best-fit model for this product. Once the product hardness or work

reached the maximum and began to reduce at moisture content (MC) 6%, the product texture began to

be detectedas becomingslightly soft. This implies that hardness andwork at themaximumlevel could beused to identify the critical MC which causes a loss of crispness to an unacceptable degree. The predicted

shelf lives estimated by employingEpfor WVP of LDPE and OPP, and the GAB model were close to the

actual shelf lives. Therefore, the estimation by empirical models and activation energy was found to be

applicable for rapid and accurate shelf life prediction.

2010 Elsevier Ltd. All rights reserved.

1. Introduction

Cassava (Manihot esculentaCrantz) flour is used as a key ingre-

dient in several dry crisp products such as potato chips and puffed

curls. In addition, Asian and Latin American peoples are interested

in its use as a partial substitute for wheat flour (Lopez et al., 2004;

Mohamed et al., 2006). To consumers, high crispness of such prod-

ucts indicates not only good quality but also freshness (Rohm,

1990). Unfortunately, few study results have been reported on

the creation and preservation of crispness for cassava-based flour

products (Chang et al., 2000). Such research has been especially

rare for multi-component systems.

Sorption characteristics of cassava-flour-based baked products

are crucial for the design, modeling and optimization of their

drying, packaging, storage and transport. Knowledge of sorption

isotherms is also important for predicting moisture sorption

properties of highly sensitive food products via empirical models.

These isotherms provide information on the moisture-binding

capacity of products at a determined relative humidity, and are a

useful means for analyzing the moisture plasticizing effect and

the effect on textural properties (Bell and Labuza, 2000; Al-Muh-

taseb et al., 2002). Chirife and Iglesias (1978) reviewed 23 isotherm

models and their use for fitting sorption isotherms of foods and

food products. None of these models accurately described the sorp-

tion isotherm over the entire range of relative humidity, since

water is related to the food matrix by different mechanisms in dif-

ferent activity regions. However, these kinetic models are still

important for use in the prediction of moisture sorption properties

of foodstuffs.

In the texture study, crispness was perceived as a combination

of the sound generated and the fracture of the product as it was

bitten completely through with the back molars (Duizer et al.,

1998). Different instrumental and sensory approaches have been

applied to study this quality attribute, and have generated a large

amount of experimental data (Roudaut et al., 2002). Unfortunately,

0260-8774/$ - see front matter 2010 Elsevier Ltd. All rights reserved.doi:10.1016/j.jfoodeng.2010.04.031

* Corresponding author. Tel.: +66 2 562 5058; fax: +66 2 562 5047.

E-mail address: [email protected](P. Suppakul).

Journal of Food Engineering xxx (2010) xxxxxx

Contents lists available at ScienceDirect

Journal of Food Engineering

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / j f o o d e n g

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Please cite this article in press as: Kulchan, R., et al. Shelf life prediction of packaged cassava-flour-based baked product by using empirical models and

activation energy for water vapor permeability of polyolefin films. Journal of Food Engineering (2010), doi: 10.1016/j.jfoodeng.2010.04.031
http://dx.doi.org/10.1016/j.jfoodeng.2010.04.031mailto:[email protected]://www.sciencedirect.com/science/journal/02608774http://www.elsevier.com/locate/jfoodenghttp://dx.doi.org/10.1016/j.jfoodeng.2010.04.031http://dx.doi.org/10.1016/j.jfoodeng.2010.04.031http://www.elsevier.com/locate/jfoodenghttp://www.sciencedirect.com/science/journal/02608774mailto:[email protected]://dx.doi.org/10.1016/j.jfoodeng.2010.04.031


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no conclusion can be soundly drawn for the relationship between

instrumental and sensory results. This is due to the fact that many

definitions of crisp were applied (Roudaut et al., 2002), and only

a few studies of sensory data have been reported to the public

(Hecke et al., 1995; Roudaut et al., 2002). The crispness of dry crisp

products is controlled by product composition and structure

(Roudaut et al., 2002). Process conditions affect the final moisture

content which governs crispness of the finished product ( Roudaut

et al., 2002). During storage, water adsorption from the atmo-

sphere or by mass diffusion from neighboring components can also

cause a loss of crispness (Nicholls et al., 1995).

Moisture-sensitive products may absorb moisture during long-

term storage, as the commonly used packaging materials are per-

meable to moisture. Moisture content can be used as the critical

data for judging the quality of products that have been degraded

by moisture. Water vapor permeability of packaging materials is

one of the important criteria for predicting the rate of moisture up-

take (Chen and Li, 2003). Recently there has been increased inter-

est in the development of a mathematical model for optimization

of flexible film packaging of moisture-sensitive foods (Del Nobile

et al., 2003; Azanha and Faria, 2005; Araromi et al., 2008; Siripatr-

awan, 2009).

This study is aimed at: (1) investigating the moisture sorption

kinetics and empirically modeling the moisture sorption isotherm

of cassava-flour-based baked product; (2) determining a critical

water activity of cassava-flour-based baked product based on

mechanical and sensory approaches; and (3) determining the acti-

vation energy for water vapor permeability of polyolefin films, and

applying this to the predicted shelf life of moisture-sensitive food

products.

2. Materials and methods

2.1. Sample preparation

A cassava-flour-based baked sample was prepared using cas-

sava flour (55.2%) (Cho Heng Rice Vermicelli Co., Ltd., Nakhon

Pathom, Thailand); coconut milk (18.4%); egg yolk (1.1%); and su-

crose (23%), obtained from various commercial retailers. Firstly, a

mixture of coconut milk and sucrose was heated at 90 C until

40% sample weight loss was reached. The obtained mixture, with

egg yolk and cassava flour then added, was kneaded into dough

using a domestic mixer (KM 410, Kenwood Limited, UK) at a min-

imum speed. The dough was stored in a tightly sealed container at

room temperature overnight. Then the dough, after adding water

(2.3%), was kneaded to obtain homogeneous distribution beforebeing divided roll dough into small balls (1 cmdia) using a

1 cm plain biscuit cutter. The balls were placed on a greased pan

and baked at 150 C for 20 min. After baking, they became porous

and expanded to 1.5 cm dia. The baked products were left to cool,

and kept in a tightly sealed container for further use.

2.2. Proximate analysis

The sample was analyzed for moisture, protein, carbohydrate,

starch, fat, ash and fiber using AOAC methods (Lane, 1998). All

determinations were carried out in triplicate.

2.3. Moisture sorption kinetics and isotherm

A standard gravimetric methodology (weighing samples equili-

brated in thermally stabilized desiccators) was used for determina-

tion of the adsorption kinetics. The baked product was crushed,

and completely dried in a vacuum oven at 70 C and 76 mm Hg

for 48 h, and then in a desiccator over P2O5 for 2 weeks. The driedsamples (in triplicate) were placed into desiccators with saturated

salt solutions at 30 C. The salt solutions included LiCl, MgCl2,

Mg(NO3)2, NaCl, and K2NO3 of known relative humidity (% RH):

11.3, 32.4, 51.4, 75.1, and 92.5% RH, respectively (Greenspan,

1977). Weights of samples as a function of time were measured;

moisture content was then measured by drying in an oven at

105 C for 3 h (Lane, 1998). Set of experiments was performed in

two replications. This was expressed on a dry-weight basis as g

H2O/100 g dry sample. Water activity (aw) was determined using

a water activity instrument (Testo 650, Testo, Inc., Germany). Mois-

ture adsorption curves of the samples were fitted to a mathemat-

ical model suggested byPeleg (1988):

Mt M0 t=k1k2t; 1

where,Mt= moisture after timet;M0= initial moisture; andk1 and

k2= parameters.

A standard gravimetric methodology was used for determina-

tion of the adsorption isotherms. The baked product was prepared

and conditioned, as described in Section2.3. The dried samples in

triplicate were equilibrated over saturated salt solutions inside

desiccators at 30 C for 4 weeks. The salt solutions included LiCl,

CH3COOK, MgCl2, K2CO3, Mg(NO3)2, KI, NaCl, KCl and K2NO3 of

known relative humidity (% RH): 11.3, 21.6, 32.4, 43.2, 51.4, 67.9,

75.1, 83.6 and 92.5, respectively (Greenspan, 1977). Moisture con-

tent was then measured by drying in an oven at 105 C for 3 h

(Lane, 1998). Set of experiments was performed in 4 replications.

This was expressed on a dry-weight basis as g H2O/100 g dry

sample. Water activity was determined using a water activityinstrument.

Nomenclature

A test area (m2)aw water activitya, b, c, d constants of the Peleg modelCB

constant of the BET modelCG,k constants of the GAB model

Ep apparent activation energy of water vapor permeabilityF, G,Hconstants of the Lewicki modelG

weight change (g)k, c constants of the Oswin modelk1, k2 parameters of Peleg kinetic modell thickness (mil)M0 initial moisture content

Mc critical moisture contentMt moisture after time (t)P water vapor permeability coefficient (g mil m2 d1

mmHg1)psat saturated vapor pressure at constant temperature,

mmHgDp vapor pressure difference (mmHg)RH0 relative humidity in test dishRH relative humidity in desiccatorT temperature (K)Tg,m mid-point glass transition temperature (C)t time (d)

2 R. Kulchan et al. / Journal of Food Engineering xxx (2010) xxxxxx

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activation energy for water vapor permeability of polyolefin films. Journal of Food Engineering (2010), doi:10.1016/j.jfoodeng.2010.04.031
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2.4. Moisture sorption isotherm modeling

Isotherm models from the literature (Berg and Bruin, 1981; To-

ledo, 1991) were selected for modeling the experimental data of

adsorption isotherms of cassava-flour-based baked samples. Those

models are expressed and rearranged as given in Table 1. The

parameters of the equations were estimated using Kyplot 2.0 for

Windows (Kyence Inc., Japan). The value of the root mean square

percentage error (%RMS) represents the fitting ability of a model

in association with the number of data points.

2.5. Determination of critical water activity of cassava-flour-based

baked product based on mechanical and sensory approaches

2.5.1. Sensory evaluation

Twelve panelists were trained to ensure the same perception of

crispness attribute, as defined by Duizer et al. (1998). Crispness

was rated on a nine-point category scale (1 = not crisp/soggy,

9 = very crisp). The panelists evaluated the samples in a random or-

der, three times over three sessions. A three-way variance analysis

products, panelists and replications (block factor) ensured no

interaction between products and panelists. This ensured a greater

understandability and homogeneity of panelists results regarding

the crispness evaluation.

2.5.2. Mechanical measurement

Mechanical measurement was performed with a texture ana-

lyzer (LLOYD Instrument TM LRX S/N 10313, Lloyd Instruments

Ltd., UK). A sample was placed on top of the lower hollow cylinder.

A flat cylindrical plunger (4.77 mm dia) was set to a crosshead

speed of 10 cm/min and a load of 50 kgf. Force and deformation

data were recorded. Each sample was measured in 1520 repli-

cates. Hardness (kgf) was defined as the maximum force at the

breaking point of the product, and work (kgf.mm) as the integral

area under the force and deformation curve (Li et al., 1998).

2.6. Determination of activation energy for water vapor permeability

of LDPE and OPP films

Water vapor permeability (WVP) was measured gravimetri-

cally, according to ASTM Standard Method E 9519. The test dish

was filled with desiccant within 6 mm of the specimen. The spec-

imen was then attached to the dish, and the edges of the specimen

sealed with melted paraffin wax to prevent the passage of vapor

into, out of, or around the specimen edges. Three test dishes were

used per sample. Each was weighed at once, placed in a separate

desiccator over saturated salt solution having known relative

humidity of 90 2% RH and conditioned in a temperature-

controlled chamber at 5 different temperatures (20 1 C,

2 5 1 C, 30 1 C, 35 1 C a n d 3 8 1 C). Test dishes were

weighed periodically. The relationship of gain weight and time

were plotted, with WVTR calculated as follows:

WVTR G

t

1

A 2

The water vapor permeability coefficient (P) can be expressed

as:

PWVTR

Dp l; 3

where:G = weight change (from the straight line), g; t= time, d;G/

t= slope of the straight line, g d1; A = test area (cup mouth area),

m2; WVTR = rate of water vapor transmission, g d1 m2;P= water

vapor permeability, g mil d1 m2 mmHg1; l = thickness, mil; and

Dp= vapor pressure difference, mmHg.

Plotting ln P versus 1/T gives a straight line. The slope of the

straight line representsEp/R. TheEpof the reaction can now be cal-

culated by multiplying the slope by the gas constant (R).

2.7. Shelf life simulation of moisture-sensitive products

The shelf life simulation of moisture-sensitive products was

developed based on Eq. (10):

t Gl

APDp; 4

where: t= time, d; G= mass of products (dry) [critical moisture

(Mc) initial moisture (M0)], g; A= area, m2; l= thickness, mil;

P= permeability coefficient, g mil d1 m2 mmHg1;

Dp psatRH0RH

100 ;mmHg:

Shelf life simulation was rendered into two cases. In the first

case, the water vapor permeability coefficient was in accordancewith a standard condition of storage at 38 C, as a worst-case sce-

nario. In the second case, the water vapor permeability coefficient

was in accordance with the actual condition of storage at 30 C.

This coefficient can be calculated by employing the activation en-

ergy for WVP.

2.8. Shelf life determination of moisture-sensitive products

The shelf life of cassava-flour-based baked products can be

determined experimentally. About 50 g of samples were packed

in 0.103 0.156 m of 50lm LDPE and 50 lm OPP pouches. Stor-

age conditions were 30 1 C and 50%RH. The pouches containing

the products were evaluated for moisture content, sensory hard-

ness, and work every 34 days, until products reached their criticalmoisture content. The results obtained from analytical and exper-

imental shelf life predictions were compared.

3. Results and discussion

3.1. Food properties

The chemical composition of the cassava-flour-based baked

sample was 84.78% 0.09% carbohydrate (approximately 60.08%

starch), 0.63% 0.07% protein, 10.24% 0.09% fat, 3.74% 0.05%

water, 0.32% 0.01% ash and 0.29% 0.03% fiber, on a wet basis.

This dry crisp sample was high in starch and fat contents. After

baking and cooling down, the sample was analyzed for aw and

moisture content. It was found that the sample properties were0.38 and 3.9%, respectively.

Table 1

Models describing the moisture sorption isotherms of cassava-flour-based baked

product.

Model Mathematical expression

BET (BrunauerEmmettTeller)

Brunauer et al. (1938)

me moCBaw=1 aw1 CB 1aw

GAB (GuggenheimAndersonde

Boer)Berg and Bruin (1981)

me moCGkaw=1 aw1 CG 1kaw

LewickiLewicki (1998) me F=1 awG F=1 aHw

OswinOswin (1946) me kaw=1 awc

PelegPeleg (1993) me aabw cadw

me, Equilibrium moisture content;mo, monolayer moisture content;a,b,c,CB,CG,d,F, G, H, k, constants specific to individual mathematical expression.

R. Kulchan et al. / Journal of Food Engineering xxx (2010) xxxxxx 3

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3.2. Moisture sorption kinetics and isotherm

Moisture sorption kinetic curves of cassava-flour-based baked

product are depicted in Fig. 1. Moisture adsorption was more rapid

in the initial stages, and declined with increasing time. Then, mois-

ture content of the product reached a plateau, indicating that it be-

came equilibrated with relative humidity in each condition. At

relative humidity of 11.3%, 32.4%, 51.4%, 75.1% and 92.5%, the re-

quired times to reach each equilibrium were 34, 60, 76, 100 and

384 h, respectively. Baucour and Daudin (2000) reported that, at

high relative humidity, the mass transfer is very slow, making it

difficult to reach equilibrium in the range 0.91.0 aw. Measured

sorption kinetic curve data were fitted to Eq. (1). The constants

k1 andk2, which were derived from the linear fit, are shown in

Table 2. The coefficients of determination were found to be high

in all cases (r2 > 0.90); this is an indication of a good fit to the

experimental data. Generally, food products stored at a higher

relative humidity tended to have lower k1 and k2 values, and vice

versa. As constants associated with mass transfer and maximum

moisture adsorption capacity, the lower the k1, the higher the ini-

tial moisture adsorption rate, and the lower the k2, the higher the

moisture adsorption capacity (Turhan et al., 2002). However in this

case, at 92.5% RH,k1 showed a higher value, which means a lower

degree of initial moisture adsorption rate. This is due to a slow

mass transfer at high relative humidity.

The moisture sorption isotherm curve of cassava-flour-based

baked product, represented in Fig. 2, can be classified as a type II

sigmoidal isotherm, which is obtained for soluble materials and

shows an asymptotic trend as water activity tends toward 1 ( Bell

and Labuza, 2000). Moisture sorption was more rapid in the initial

stages, and a lesser amount of moisture was adsorbed as adsorp-

tion time increased. The higher the relative humidity used, the

more pronounced the effect. The equilibrium moisture content of

the product dramatically soared above aw= 0.73.

Calculated model constants, coefficient of determination (r2),

and %RMS for each model for the product are represented in

Table 3. The GAB model is a semi-theoretical multilayer sorption

model with a physical meaning for each constant. In general, it isthe most accepted model for foods or edible materials. The product

presented a monolayer moisture content of 2.46% (dry basis). This

value indicates the maximum amount of water that can be ad-

sorbed in a single layer of the dry product, and is a measure of

the number of sorbing sites. This monolayer moisture content de-

fines the physical and chemical stability of foods. It has an effect on

lipid oxidation, enzyme activity, non-enzymatic browning, flavor

preservation, and product structure (Menkov, 2000). This value is

in the range of acceptability because the maximum monolayer

moisture content should not be more than 10% dry basis for food

products (Labuza et al., 1985).Araromi et al. (2008)also reported

that monolayer moisture content decreases with increasing tem-

perature. This is due to a decrease in the number of active sites

for water binding, which may be caused by changes in physical

or chemical structures in the food products as a result of changes

in temperature (Geankoplis, 1993). The trends are in line for

high-carbohydrate foods, as reported byLabuza (1968).

The BET model can be also used to determine the monolayer

water content of a product (2.39%, dry basis). However, this model

is applicable only betweenawvalues of 0 and 0.5 (Bell and Labuza,

2000). The Lewicki model was developed for applicability to a high

range of aw. It fits well with the moisture sorption data at high

humidity, and predicts that water content tends to infinity when

aw reaches 1.0. The Oswin model provides good descriptions of

the moisture isotherms throughout the entire range of water

Fig. 1. Moisture sorption curves of cassava-flour-based baked product at various

relative humidity as a function of time.

Table 2

Sorption kinetic model constants and coefficient of determination for cassava-flour-

based baked product at selected relative humidity.

Relative humidity (%) Cassava-flour-based baked product

k1 k2 r2

11.3 3.32 0.76 0.9286

32.4 1.86 0.30 0.9429

51.4 1.09 0.16 0.9391

75.7 0.64 0.09 0.9634

92.5 1.79 0.02 0.9650

Fig. 2. Moisture sorption isotherm of cassava-flour-based baked product.

Table 3

Sorption isotherm model constants, coefficient of determination and percentage of

root mean square error for cassava-flour-based baked product.

Sorption isotherm model Constant r2 %RMS

BET m0= 2.3867 0.9481 6.6812

CB= 4.6705

GAB m0= 2.4598 0.9976 3.1309

CG= 49.0599

k= 1.0904

Lewicki F= 1.6765 0.9888 4.7429

G= 1.5727

H= 3.9982

Oswin k= 4.3764 0.9668 13.9072

c= 1.1409

Peleg a= 335.0922 0.9991 3.6487

b= 16.6709

c= 13.6947

d= 1.1218


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activity. However in this case, the maximum %RMS value was ob-

tained for the Oswin model. The Peleg model can predict both sig-

moid and non-sigmoid isotherms. This model might be fitted as

well or better than the GAB model, but unfortunately its constants

had no physical meaning. In the case of the Peleg model, the value

ofr2 was highest and was similar to the GAB model. Nevertheless,

the %RMS value from the Peleg model produced a higher result

than that of the GAB model. Thus, the GAB model was found to

be the best estimator for predicting the equilibrium moisture con-

tent of the product, followed by the Peleg and Lewicki models. This

is in agreement withRohvein et al. (2004) and Siripatrawan and

Jantawat (2006)who reported that the GAB model is considered

to be the most versatile sorption model available in the literature,

since it has been shown to fit the experimental sorption data for

nearly all products and over the whole water activity range.

Fig. 3 reveals the experimental vs. predicted moisture content of

the product. The obtained points lie on the diagonal for low and

intermediate awlevels, indicating low interaction between compo-

nents in accordance with their separation in independent phases,

as observed during the product baking. At a high level of water

activity, it can also be observed that points fall on the diagonal,

as a result of the interaction between water molecules and the po-

lar groups of the product.

3.3. Relationship between texture and water activity

Crispness of the baked samples was determined using a sensoryapproach. Fresh samples were highly crispy, with a score of 7.8,

and were very moisture-sensitive. As the samples adsorbed more

water, the crispness acceptance sharply declined in a linear man-

ner with an increase in water activity (Fig. 4). It was noticed that

the product crispness was preserved to a satisfactory degree

(scoreP 5) when containing a small amount of water (aw< 0.54)

or moisture content (dry basis < 6%). These specific values of awand moisture content (0.54 or 6%) could be considered as critical

points of crispness loss. These critical water activity values corre-

sponded to those of other dry crisp starchprotein-matrix prod-

ucts, reported as approximately 0.5 (Roos et al., 1998; Hough

et al., 2001). The cassava baked sample also contained protein

and starch, which would be anticipated to form such a crispy ma-

trix during baking. This matrix was significantly softened by the

plasticization effect of water adsorbed above the critical level

(Martinez-Navarrete et al., 2004). It is interesting to point out that

the water activity at the critical level (0.54) is much higher than

that at the monolayer water content (2.5% dry basis or

aw 0.12). As demonstrated in previous work, at the critical water

activity the product was still in a glassy stage (Tg,m 132.8 C)

(Kulchan et al., 2010).

The product texture was also examined using a mechanical ap-

proach. The results showed that product hardness and work were

changed in a concave manner with increasing water activity

(Fig. 4). Each of them increased to a maximum point at

aw 0.54. As pointed out above, awat this value is the critical point

of crispness loss (score = 5). This suggested that the mechanical

hardness and work data at the maximum level could be used to

identify the critical aw of crispness loss in sensory data. The same

incidence was also reported for extruded flat bread (Roudaut

et al., 1998).

An increase in water content in the product resulted in a de-

crease of the glass transition temperature (Kulchan et al., 2010)

as well as crispness over the whole range ofaw, but for hardness

and work it occurred only ataw higher than 0.54. Such reductions

are caused by molecular mobility which is facilitated by water

Fig. 3. Comparison between experimental moisture content and those predicted by

various sorption isotherm models for cassava-flour-based baked product.

Fig. 4. Relationships between water activity and texture properties and moisture content of the cassava-flour-based baked product.


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molecules (Roudaut et al., 2002). However at lower water activity

(from 0.23 to 0.54), hardness and work, on the contrary, sharply in-

creased with an increase in water activity. This is due to the fact

that at such low water activity (such as 0.23, which is close to

0.12 of the monolayer water) the product had only a small number

of water molecules. An addition of water could be just enough to

fill the free volume (at a microscopic level), leading to an increase

in product density (Benczedi 1999; Seow et al., 1999) and interac-

tions among water and other component molecules (Roudaut et al.,

2002). These phenomena cause strong increases in hardness and

work (a stronger puncture force was required). However, such an

increase in water had only a slight impact on glass transition tem-

perature, corresponding to a slight increase in molecular mobility

(Kulchan et al., 2010).

3.4. Activation energy of water vapor permeability of LDPE and OPP

films

Arrhenius plots of WVPs of LDPE and OPP films are depicted in

Fig. 5. It was found that WVPs of LDPE and OPP films are not highly

temperature-dependent. This resulted in low values of activation

energies for WVPs of LDPE and OPP films: 22.33 and

21.26 kJ mol1, respectively. This low Ep implies that temperature

fluctuation during storage does not have a significant impact on

WVP, and in turn shelf life estimation (and vice versa). Xiong

(2002) reported that activation energy of WVP of LDPE was

22.86 kJ mol1. In addition,George et al. (1997)reported that acti-

vation energies for WVPs of LDPE composite films reinforced with

20% (w/w) untreated and treated dicumyl peroxide (05% by

weight of polymer) pineapple-leaf fiber were 23.64 and

22.23 kJ mol1, respectively.

3.5. Shelf life simulation of moisture-sensitive products

Predicted shelf life by the GAB model was simulated using the

WVPs of LDPE and OPP films at a standard condition (38 C), which

were 0.2785 and 0.0861g mil d1 m2 mmHg1, respectively.

Predicted shelf life by the GAB model andEp for WVP were simu-

lated using the WVPs of LDPE and OPP films at an actual storage

condition (30 C), which were 0.2288 and 0.0687g mil d1

m2 mmHg1, respectively. The simulated shelf life values of cas-

sava-flour-based baked products in all packages are shown in Table

4. It was found that predicted shelf life by the GAB model and Epfor

WVP yields better shelf life estimation, closer to the actual shelf life

as predicted by the GAB model. The differences between the exper-

imental and the predicted shelf life of the product are minute,

especially in the case of the predicted shelf life by the GAB model

andEpfor WVP, which is based solely on the relationship between

moisture content of the product and the barrier property of the

packaging material, as well as the storage condition. However,

Roca et al. (2006)stated that shelf life of a moisture-sensitive food

product is affected not merely by moisture adsorption but also by

moisture migration in the food product, which is greatly affected

by the complexity of the food structure.

4. Conclusion

The moisture sorption kinetics of cassava-flour-based baked

products was more rapid in the initial stages; a lesser amount of

moisture was adsorbed as the adsorption time increased. GAB, Pe-

leg and Lewicki models were useful to fit moisture sorption iso-

therm data of the products. The product hardness or work

reached the maximum and began to reduce at moisture content

(MC) 6%, when the product texture began to be detected as

becoming slightly soft. The predicted shelf lives estimated by

employing Epfor WVP of LDPE and OPP, and the GAB model were

close to the actual shelf lives. Therefore, the estimation by empir-

ical models and activation energy was found to be applicable for

rapid and accurate shelf life prediction.

Acknowledgments

This work was fully supported by a fund for the promotion of

research at the Center of Advanced Studies for Agriculture and

Food (CASAF), Kasetsart University. The authors express their

thanks and appreciation for this support.

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