Journal of Food Engineering 92 (2009) 339–344
Contents lists available at ScienceDirect
Journal of Food Engineering
journal homepage: www.elsevier.com/locate/jfoodeng
Comparison and modeling of microwave tempering and infrared assisted
microwave tempering of frozen potato puree
N. Seyhun a,b,c, H. Ramaswamy b, G. Sumnu a,*, S. Sahin a, J. Ahmed b
a
Dept. of Food Engineering, Middle East Technical University, 06531 Ankara, Turkey
Dept. of Food Science and Agricultural Chemistry, McGill University, Macdonald Campus, Montreal, QC, Canada H9X 3V9
c
Kocaeli Universitesi, Ihsaniye MYO, 41040 Izmit, Kocaeli, Turkey
b
a r t i c l e
i n f o
Article history:
Received 22 September 2008
Received in revised form 5 December 2008
Accepted 9 December 2008
Available online 24 December 2008
Keywords:
Microwave
Tempering
Infrared
Modeling
Frozen potato puree
a b s t r a c t
Microwave tempering and infrared assisted microwave tempering of frozen foods were simulated by
using finite difference method. The effects of microwave power and infrared power on tempering were
discussed. Three different microwave power levels (30%, 40%, and 50%) and three different infrared power
levels (10%, 20%, and 30%) were used. The increase in microwave power level and infrared power level
decreased tempering times. The change of heat capacity and the dielectric properties of frozen potato
puree with respect to time were measured. The temperature distribution inside the sample was modeled,
and the predicted results were compared with experimental results. The predicted temperatures showed
good agreement with the experimental results.
Ó 2008 Elsevier Ltd. All rights reserved.
1. Introduction
In many countries, potato puree is a common way of serving potato. Instant potato purees are produced by an industrial process of
cooking, mashing, and drying to yield a packaged product that can
be reconstituted in the home in seconds by adding hot water or
milk with very little expenditure of time and effort. Potato puree
is used mostly in catering industry, and frozen vegetable purees
have a good potential market in Europe (Alvarez et al., 2004).
Frozen food is defined as ‘tempered’ when its temperature is
raised from that of a solidly frozen condition to some higher temperature, still below the initial freezing point, at which it is still
firm but can readily be further processed (James, 1999). Thawing
is usually regarded as complete when the center of the food sample
has reached 0 °C. Lower temperatures (e.g., 5 to 2 °C) are
acceptable for food that is destined for further processing, but such
food is tempered rather than thawed (James and James, 2002).
Conventional thawing is a long process and can often compromise
the product quality. Microwave thawing is a novel method having
the advantages of fast heating rate, improved bacterial control and
low costs. Minimizing thawing times will reduce microbial growth,
chemical deterioration and excessive water loss caused by dripping
or dehydration (Taher and Farid, 2001). Dielectric properties of
food materials, which are dielectric constant and dielectric loss fac* Corresponding author. Tel.: +90 312 2105628; fax: +90 312 2101270.
E-mail address: [email protected] (G. Sumnu).
0260-8774/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved.
doi:10.1016/j.jfoodeng.2008.12.003
tor, are the electrical properties which measure the interaction of
the food with electromagnetic fields. Dielectric constant reflects
the ability of a material to store electromagnetic energy, and loss
factor measures the ability of a material to dissipate electric energy
into heat (Calay et al., 1995). It is important to know the dielectric
properties of food materials to develop effective microwave heating processes. In literature, there are a few studies on the dielectric
properties of mashed potatoes (Guan et al., 2004; Fasina et al.,
2003), but these studies did not include the freezing temperatures.
Although there was one study measuring the dielectric properties
of mashed potatoes as a function of temperature at lower temperature range (Regier et al., 2001), it is necessary to obtain more data
of dielectric properties of potato puree at a wider freezing temperature range.
Infrared (IR) radiation is the part of the electromagnetic spectrum that is predominantly responsible for the heating effect of
the sun. Infrared radiation is found between the visible light and
radio waves, and can be divided into three different categories,
namely, near-infrared radiation (NIR), mid-infrared radiation
(MIR), and far-infrared radiation (FIR) (Ranjan et al., 2002). Halogen lamp heating provides near-infrared radiation and its region
in the electromagnetic spectrum is near the visible light with higher frequency and lower penetration depth than the other infrared
radiation categories. A number of approaches have been developed
to model the microwave thawing process of frozen foods (Chamchong and Datta, 1999a,b; Taher and Farid, 2001; Basak, 2003;
Liu et al., 2005).
340
N. Seyhun et al. / Journal of Food Engineering 92 (2009) 339–344
The microwave power absorbed can be modeled by using Lambert’s law or Maxwell’s equations. In Lambert’s law, the microwave
power attenuates exponentially as a function of penetration
distance into the dielectric material (Liu et al., 2005). In several
modeling studies heat generation during microwave thawing has
been described by using Lambert’s law (Zeng and Faghri, 1994;
Chamchong and Datta, 1999a,b; Taher and Farid, 2001). On the
other hand, Maxwell’s equations can predict the absorption of energy and incorporate the reflections at front and back surfaces as
well as all internal interfaces (Liu et al., 2005). Simply, the exact
solution of Maxwell’s equations for microwave propagation is
based on both the transmitted and reflected waves, whereas Lambert’s law is based purely on transmission (Basak, 2004). There are
also significant number of studies based on Maxwell’s equations
(Basak and Ayappa, 2002; Basak and Meenakshi, 2006; Samanta
and Basak, 2008). Liu et al. (2005) and Basak (2004) compared
Lambert’s law and Maxwell’s equations for microwave heating
analysis. Liu et al. (2005) found that in regard to temperature distribution, the simulations based on Lambert’s law predicted results
similar to those predicted by using Maxwell’s equations and both
were compatible with the experimental results. Basak (2004)
concluded that Lambert’s exponential law predicts results qualitatively similar to those with the exact solution within the low
dielectric material, but the absorbed power with Lambert’s law
may be overestimated within the high dielectric material, as a result, the temperature distribution may not be evaluated accurately
if there is a strong coupling between the energy balance and electric field equations. In our study, Lambert’s law was used to represent the heat generation during microwave tempering because of
the low dielectric properties of frozen potato puree.
Microwave-infrared combination is a new technology combining near-infrared heating with microwaves. There are a few studies
on infrared assisted microwave heating (Datta and Ni, 2002;
Keskin et al., 2004; Sakiyan et al., 2007), but there is no study on
modeling of infrared assisted microwave thawing or tempering.
The purpose of this study is to model the temperature distribution inside the frozen potato puree during microwave tempering
and infrared assisted microwave tempering by finite difference
model. It was also aimed to compare temperature profiles of frozen
potato puree during microwave tempering and infrared assisted
microwave tempering. In addition, the dielectric properties and
heat capacity of the frozen potato puree were measured at different temperatures.
infrared assisted microwave tempering, and it was found that
moisture loss was not significant. Therefore, moisture loss was assumed to have negligible effect on the heat transfer during tempering and also on the physical properties of the frozen potato puree.
Chamchong and Datta (1999a) also found that average moisture
loss during microwave thawing was less than or equal to 1% and
could be assumed to be negligible during thawing. Thus, the physical properties of potato puree were taken as only temperature
dependent.
To simplify the governing equations and boundary conditions,
several assumptions have been done. First of all, the initial temperature was considered as uniform within the sample. The sides and
the bottom of the sample were insulated by aluminum foil, so the
heat transfer was assumed to be one-dimensional (Fig. 1).
The density of the potato puree sample was measured as
1395 kg/m3. The thermal conductivity of frozen potato puree was
estimated by Eq. (1) (Choi and Okos, 1986):
2. Theory
where q (kg/m3), Cp (J/kg °C), and k (W/m °C) are the density, heat
capacity, and thermal conductivity of the potato puree sample,
respectively. Qgen,mw is the internal heat generation (W/m3) caused
by microwave energy, and assumed as an exponential decay represented by Lambert’s law with varying penetration depth (Datta and
Ni, 2002), which is commonly related to the microwave surface
absorption Q0 as follows (Taher and Farid, 2001):
A mathematical model was proposed to predict the temperature profile inside the frozen potato puree sample. Average moisture loss measurements were done for microwave tempering and
kðTÞ ¼ 2:01 þ 1:39 103 T 4:33 106 T 2
ð1Þ
where T is temperature in °C, and k is thermal conductivity (W/
m °C). The heat capacity values of frozen potato puree were measured by DSC and the results are given in Section 4.1.
Penetration depth is defined as the distance from the surface of
the material at which the microwave power decreases to 1/e
(37%) of its original value, and it is also controlled by the dielectric properties. Penetration depth (Dp) was calculated by using the
following formula (2):
8"
90:5
00 2 #0:5
<
=
e
Dp ¼
1þ 0
1
0:5 :
0
;
e
2pð2e Þ
k0
ð2Þ
where k0 is the wavelength of the microwave energy in free space
(12.24 cm at 2450 MHz), e0 is dielectric constant and e00 is loss factor
(Von Hippel, 1954). The penetration depth is calculated by using Eq.
(2), and the results are given in Section 4.2.
2.1. Modeling of microwave tempering
The one-dimensional unsteady state heat conduction equation
with heat generation is used to describe microwave heating of
material undergoing tempering:
@ @
@T
qC p T ¼
kðTÞ
þ Q gen;mw
@t
@z
@z
ð3Þ
Q gen;mw ¼ Q 0;mw eðz=Dp;mw Þ
ð4Þ
3
where Dp is the penetration depth in m. Q0,mw (W/m ) was estimated by trial and error to fit the experimental data as Zeng and
Faghri (1994) did since a reliable way to measure it directly was
not available.
The following initial and boundary conditions are used for
microwave tempering:
Fig. 1. View of the frozen potato puree sample.
@ t ¼ 0 0 < z < L T ¼ T0
@T
¼ hðT T 1 Þ
@ t > 0 z ¼ 0 kðTÞ
@z
@T
@t>0 z¼L
¼0
@z
ð5Þ
ð6Þ
ð7Þ
N. Seyhun et al. / Journal of Food Engineering 92 (2009) 339–344
where L is the thickness of the sample, T1 is the surrounding temperature, and h is the convective heat transfer coefficient of air. In
literature, the heat transfer coefficient values used in a microwave
oven ranged from 2 to 39.44 (Chamchong and Datta, 1999a). In this
study, it was chosen as 20 W/m2 °C for microwave tempering, and
30 W/m2 °C for infrared assisted microwave tempering.
341
where i denotes the node position, n is the time interval, and Dz and
Dt are the axial and time increments, respectively.
A MATLAB program was written to solve the resulting set of
equations. Time increment was chosen as 0.0005 and spatial increment was 0.001.
3. Materials and methods
2.2. Modeling of near-infrared assisted microwave tempering
3.1. Preparation of the sample
The same one-dimensional unsteady state heat conduction
equation is used to describe near-infrared assisted microwave
tempering with a different generation term:
@ @
@T
qC p T ¼
kðTÞ
þ Q gen
@t
@z
@z
ð8Þ
where Qgen (the total heat generation term) is defined as:
Q gen ¼ Q gen;mw þ Q gen; inf
ð9Þ
3
where Qgen,mw is the internal heat generation (W/m ) caused by
microwave energy, and Qgen,inf is the internal heat generation (W/
m3) caused by infrared energy.
The infrared power flux was also modeled as an exponential decay similar to microwave power (Datta and Ni, 2002) which is expressed by:
Q gen; inf ¼ Q 0;inf eðz=Dp; inf Þ
ð10Þ
where Q0,inf is infrared surface flux, and Dp,inf is infrared penetration
depth which is defined exactly as microwave penetration depth. For
this study, Dp,inf is taken as 3.5 mm for potato tissues from Almeida
et al. (2006). Q0,inf was estimated by trial and error to fit the experimental data.
In near-infrared assisted microwave heating, on–off cycling of
infrared heating depending on the halogen lamp power is important. Such cycling is generally done by turning infrared source on
for some of the time during the cycle and turning it off during
the rest of the cycle. The fraction of time the power is on is called
as Duty cycle and defined as (Chamchong and Datta, 1999):
Duty cycle ¼
t on
:
ton þ t off
ð11Þ
The time values ton and toff changes with changing halogen lamp
power. When the halogen lamp power is increased, ton also increases and toff decreases.
To solve near-infrared assisted microwave tempering equations, the same boundary conditions are used with microwave
tempering.
2.3. Solution of the mathematical model
To predict the temperature profile inside the sample, the mathematical model was solved numerically by using the initial and
boundary conditions. Explicit finite difference method was used
to solve the governing equations. Heat capacity, thermal conductivity, and the penetration depth were taken as dependent on
temperature.
The following equations were used:
@T T nþ1
T ni
¼ i
@t
Dt
n
n
@T T iþ1 T i1
¼
@z
2 Dz
2
@
@T
@k @T
@2T
¼
þ kðTÞ 2
kðTÞ
@z
@z
@T
@z
@z
n
n
n
2
T
2T
þ
T
@ T
i
i1
¼ iþ1
@z2
ðDzÞ2
ð12Þ
ð13Þ
ð14Þ
ð15Þ
A commercial potato puree powder (Knorr, Turkey) having a
moisture content of 6% was used as the sample. The chemical
composition of the commercial potato puree powder was 72% carbohydrate, 8% protein, and 1% fat. It contained potato, emulsifier
(mono- and diglyceride), stabilizator (disodium diphosphate), food
preservative (sodium Meta bisulphite), spice extract, and antioxidant (ascorbyl palmitate). Hot water was used to prepare potato
puree containing 15% potato puree powder. The potato puree was
shaped as a cylindrical slab with 25 cm diameter and 2.5 cm height.
3.2. Tempering
A halogen lamp–microwave combination oven (Advantium
oven , General Electric Company, Louisville, KY, USA) was used
for both microwave tempering and infrared assisted microwave
tempering. The power of microwave oven has been determined
as 706 W by using IMPI 2-l test (Buffler, 1993). Three different
microwave power levels (30%, 40%, and 50%) were used for microwave tempering. For infrared assisted microwave tempering, lower
halogen lamp was not used, and three different upper halogen
lamp power levels (10%, 20%, and 30%) were used in combination
with the microwave power levels.
TM
3.3. Measurement of temperature
Temperature was measured with a fiber optic temperature
probe (FOT-L/2M, FISO, Canada) at three different points (0.5 cm,
1.5 cm, and 2.5 cm far from the surface). The temperature data
was collected every 10 s.
3.4. Measurement of density
The volume of the potato puree with a known weight was measured, and the density was calculated by the following density
formula:
q¼
m
:
V
ð16Þ
3.5. Measurement of heat capacity
Step scan alternating differential scanning calorimeter (DSC)
(Perkin–Elmer Diamond DSC, Perkin–Elmer, USA) was used to
measure the heat capacity of the sample. Hermetically sealed aluminum pans were used to avoid any moisture loss during the test.
In the experiment, unfrozen potato puree samples (10–15 mg)
were put into the pan, and the pans were sealed. They were cooled
to 30 °C, held at that temperature for 15 min, and then warmed at
heating rate of 10 °C/min from 30 °C to 10 °C. The equation is
then extrapolated to 2 °C.
3.6. Measurement of dielectric properties
A vector network analyzer (Model: Agilent 8722ES, Agilent
Technology, Palo Alto, CA) with an open–ended coaxial cable
(Nos. 8120-6192, Hewlett Packard) connected to a probe
N. Seyhun et al. / Journal of Food Engineering 92 (2009) 339–344
60
40
20
0
-40
3.7. Data analysis
Microsoft Excel software package (Microsoft Corporation, USA)
was used to carry out the statistical analysis and linear regressions
of experimental data. MATLAB was used for finite difference
modeling.
-30
-20
-10
0
10
20
Temperature (ºC)
Fig. 2. Variation of dielectric constant (e0 ) of frozen potato puree with respect to
temperature.
20
15
ε''
(85070C, Agilent Technology, Palo Alto, CA) was used to measure
dielectric properties of potato puree. The built-in S-parameter test
set provided a full range of magnitude and phase measurements in
both the forward and reverse directions. The instrument was calibrated by measuring the properties of air, short-circuit block, and
water at 25 °C. To obtain uniform readings, the instrument was
turned on at least 2 h before the calibration and measurements
were made. The network analyzer probe and the cable were fixed
together so that there could be no movement during sample measurement and data acquisition. The dielectric properties of the potato puree were measured in the temperature range of 30 °C to
10 °C for every 2 °C intervals. A thermocouple temperature sensor
(BK Precision 390A, Taiwan) was used to monitor the temperature
during the study and the temperature variation within the sample
was minimal, ±0.5 °C. The dielectric properties of the potato puree
were measured at 2450 MHz. The dielectric spectra of the samples
(dielectric constant e0 , and dielectric loss factor e00 ) were automatically computed and recorded with the manufacturer supplied
computer software (Version 85070 D1.00, Agilent Technologies,
Palo Alto, CA).
ε'
342
10
5
0
-40
-30
-20
-10
0
10
20
Temperature (ºC)
4. Results and discussion
Fig. 3. Variation of loss factor (e00 ) of frozen potato puree with respect to
temperature.
4.1. Heat capacity
The specific heat capacity is the amount of heat required to
change a unit mass of a substance by 1° in temperature. Heat
capacity of food is important for heat transfer since it determines
how fast a food can be heated. The heat capacity of potato puree
was observed to increase with increasing temperature. Predictive
equation for the heat capacity obtained from this result
(r2 = 0.99) and used for the modeling is given as follows:
C p ðTÞ ¼ 2087:8 þ 21:058 T þ 0:2224 T 2 :
ð17Þ
4.2. Dielectric properties
Figs. 2 and 3 show the change of dielectric constant (e0 ) and loss
factor (e00 ) of the frozen potato puree with respect to temperature,
respectively. Results indicated that the dielectric constant and loss
factor of potato puree samples increased exponentially as the temperature increased. Both dielectric parameters were found to be
very low (3–10 for dielectric constant and 0–3 for loss factor) up
to 10 °C and level off at above 2 °C. During thawing, both dielectric constant and loss factor show large increases with temperature. After thawing, dielectric properties of foods are known to
decrease with increasing temperature (Sahin and Sumnu, 2006).
Free and bound moisture content affect the rate of change of
dielectric constant and loss factor with temperature. If the water
is in bound form, the increase in temperature increases the dielectric properties. However, in the presence of free water, dielectric
properties of free water decrease as temperature increases. At high
temperatures, hydrogen bonds become rare. Less energy is required to overcome intermolecular bond at higher temperatures
that results in lower dielectric properties. Therefore, the rate of
variation of dielectric properties depends on the ratio of bound
to free moisture content (Sahin and Sumnu, 2006). The values of
both dielectric constant and loss factor were found to be rather
small for mashed potatoes at 2450 MHz (Regier et al., 2001). Ice
has a low dielectric constant and loss factor when compared to that
of water (Schiffmann, 1986). The dielectric constant and loss factor
of ice is 3.2 and 0.0029, and the dielectric constant and loss factor
of water is 78 and 12.48 at 2450 MHz.
The dielectric constant decreased slightly whereas loss factor
increased significantly as the frequency was increased (Fig. 3.1
and 3.2). The same trend was observed for frozen tylose samples
in literature (Chamchong, 1997). These results are important for
microwave thawing and tempering of frozen potato puree studies
and can be used for modeling purposes to estimate the thawing or
tempering time and temperature distribution during microwave
heating.
The penetration depth of frozen potato puree was calculated by
using Eq. (2). As microwaves move through the slab at any point,
the rate of heat generated per unit volume decreases. For materials
having high loss factor, the rate of heat generated decreases rapidly
and microwave energy does not penetrate deeply. A parameter
called penetration depth indicates the distance that microwaves
will penetrate into the material before it is reduced to 1/e of its initial value (Sahin and Sumnu, 2006). The penetration depth (Dp) of
the frozen samples decreased as a function of temperature. The decrease was more significant at lower temperatures and the penetration depth became almost constant after 6 °C. An equation
was fitted to penetration depth data to use in modeling and given
as:
Dp ¼ 0:0137 þ 0:0032 T þ 0:0004 T 2
r 2 ¼ 0:99:
ð18Þ
4.3. Modeling
In this study, tempering time is defined as the time needed for
the surface temperature of frozen potato puree sample to reach
343
N. Seyhun et al. / Journal of Food Engineering 92 (2009) 339–344
0
0
100
200
300
400
500
Temperature (ºC)
-5
-10
-15
-20
-25
-30
Time (s)
Fig. 4. Comparison of experimental and model prediction data for microwave
tempering frozen potato puree with 40% microwave power. () Experimental data
at 0.5 cm, (N) experimental data at 1.5 cm, () experimental data at 2.5 cm, (—)
model.
0
0
50
100
150
200
250
Temperature (ºC)
-5
-10
-15
-20
-25
-30
Time (s)
Fig. 5. Comparison of experimental and model prediction data for infrared assisted
microwave tempering with 30% microwave power and 20% halogen power. ()
Experimental data at 0.5 cm, (N)experimental data at 1.5 cm, () experimental data
at 2.5 cm, (—) model.
0
0
100
200
300
400
500
-5
Temperature (ºC)
2 °C. The microwave tempering times of frozen potato puree are
given in Table 1. When the microwave power was increased, the
tempering time got shorter as expected.
The temperature distribution within the frozen potato puree
during tempering is modeled by using finite difference method.
Fig. 4 shows the variation of temperature at different positions as
a function of time for 40% microwave power. Different markers
indicate different thermocouple positions inside the frozen potato
puree sample. The predicted temperatures show good agreement
with the experimental results. The r2 values ranged between
0.989 and 0.998. The bottom of the sample was heated slower
(Fig. 4) since microwave power flux decreases as an exponential
decay. The temperature distribution was more uniform at lower
microwave powers since tempering time was longer at lower
microwave powers allowing also conduction to take place.
Times necessary to temper frozen potato puree in infrared assisted microwave oven are also given in Table 1. As can be seen
from the table, using infrared heating in combination with microwaves decreased the tempering time. In addition, increasing halogen power level resulted in lower tempering times.
Finite difference method was used to model the temperature
distribution during infrared assisted microwave tempering. Fig. 5
compares the measured and simulated temperature distribution
during infrared assisted microwave tempering with 30% microwave power and 20% infrared power combination. Different markers indicate different thermocouple positions inside the frozen
potato puree sample. As can be observed from the figure below,
the heating pattern seems to be different from microwave tempering (Figs. 4 and 5). The stepwise changes seen in temperature profile are due to on–off cycling of infrared heating depending on the
halogen lamp power. Actually, microwave heating also has on–off
cycling, but due to very low dielectric properties of frozen sample
the effect of cycling cannot be observed on temperature profile of
frozen potato puree during microwave tempering.
Fig. 6 represents the effect of halogen power on variation of
temperature during microwave tempering and infrared assisted
microwave tempering. Infrared heating provided an additional flux
as illustrated in Fig. 6. Using infrared heating in combination with
microwave heating decreased the tempering time and changed the
heating pattern. It can also be seen that increasing the halogen
power decreased the tempering time. Considering the experimental data and the model, the match between the two is very good.
The r2 values ranged between 0.985 and 0.998. It is worth to note
that how the model well predicted the onset and the offset of the
heating profile.
The effect of microwave power during infrared assisted microwave tempering is shown in Fig. 7. As the microwave power increases, tempering time also decreases in infrared assisted
microwave tempering (Fig. 7). It was observed that at the same
microwave power level, increasing the infrared power increases
the height of the steps in stepwise changes on the temperature
profile, resulting in a more non-uniform temperature distribution
since when the infrared power increased, the halogen lamp (the
source of infrared heating) is on for a longer time, i.e., the sample
is exposed to infrared heating more. Also, at the same infrared
power level, increasing the microwave power level increased the
non-uniformity in the temperature distribution during tempering.
At 30% microwave plus 10% infrared level, the temperature profile
is the most uniform one. The effect of infrared heating is observed
-10
-15
-20
-25
-30
Time (s)
Fig. 6. Effect of halogen power on variation of temperature during tempering of
frozen potato puree at 1.5 cm depth with 40% microwave power. (}) Experimental
data at 0% halogen power, (h) experimental data at 10% halogen power, (D)
experimental data at 20% halogen power, () experimental data at 30% halogen
power, (—) model.
as more dominant at the lowest microwave power level, but
infrared heating adds non-uniformity to the temperature
distribution.
Table 1
Tempering times for microwave and infrared assisted microwave tempering.
Microwave power
30%
Infrared power
Tempering time (s)
0%
630
40%
10%
320
20%
240
30%
200
0%
440
50%
10%
250
20%
210
30%
170
0%
330
10%
210
20%
170
30%
150
344
N. Seyhun et al. / Journal of Food Engineering 92 (2009) 339–344
0
0
50
100
150
200
250
300
Temperature (ºC)
-5
-10
-15
-20
-25
-30
Time (s)
Fig. 7. Effect of microwave power on variation of temperature during tempering of
frozen potato puree at 1.5 cm depth with 20% halogen power. (}) Experimental
data at 30% microwave power, (h) experimental data at 40% microwave power, (D)
experimental data at 50% microwave power, (—) model.
5. Conclusion
The temperature distribution and the heating patterns were observed to be different in microwave tempering and infrared assisted microwave tempering. An increase in either microwave
power or halogen lamp power resulted in a decrease the tempering
time. A finite difference model was developed to help to predict the
temperature profile of frozen potato puree during microwave tempering and infrared assisted microwave tempering. The models for
both microwave tempering and infrared assisted microwave tempering fitted the experimental data well. These models can be used
to design microwave tempering and infrared assisted microwave
tempering experiments for other frozen foods. These models eliminate the need for preliminary testing, which saves time, money,
and resources. A novel tempering technology is introduced by this
research. This study will be helpful for further thawing and tempering studies performed with different food samples.
Acknowledgement
This research was supported by the Middle East Technical University (BAP-08-11-DPT2002K120510-GT-2).
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