Journal of Food Engineering 83 (2007) 422 429
www.elsevier.com/locate/jfoodeng
Vacuum drying characteristics of eggplants
a a b a,*
Long Wu , Takahiro Orikasa , Yukiharu Ogawa , Akio Tagawa
a
Graduate School of Science and Technology, Chiba University, 648, Matsudo, Matsudo, Chiba 271-8510, Japan
b
Faculty of Horticulture, Chiba University, 648, Matsudo, Matsudo, Chiba 271-8510, Japan
Received 7 February 2007; received in revised form 15 March 2007; accepted 17 March 2007
Available online 28 March 2007
Abstract
The vacuum drying characteristics of eggplant were investigated. Drying experiments were carried out at vacuum chamber pressures
of 2.5, 5 and 10 kPa, and drying temperature ranging from 30 to 50 °C. The effects of drying pressure and temperature on the drying rate
and drying shrinkage of the eggplant samples were evaluated. The suitable model for describing the vacuum drying process was chosen
by fitting four commonly used drying models and a suggested polynomial model to the experimental data; the effective moisture diffu-
sivity and activation energy were calculated using an infinite series solution of Fick s diffusion equation. The results showed that increas-
ing drying temperature accelerated the vacuum drying process, while drying chamber pressure did not show significant effect on the
drying process within the temperature range investigated. Drying shrinkage of the samples was observed to be independent of drying
temperature, but increased notably with an increase in drying chamber pressure. A linear relationship between drying shrinkage ratio
and dry basis moisture content was observed. The goodness of fit tests indicated that the proposed polynomial model gave the best
fit to experimental results among the five tested drying models. The temperature dependence of the effective moisture diffusivity for
the vacuum drying of the eggplant samples was satisfactorily described by an Arrhenius-type relationship.
Ó 2007 Elsevier Ltd. All rights reserved.
Keywords: Vacuum drying; Eggplant; Drying characteristics; Drying model
1. Introduction higher drying rate, lower drying temperature and oxygen
deficient processing environment etc., these characteristics
Drying is one of the most important methods of long- may help to improve the quality and nutritive value of
term food preservation. The removal of moisture from the dried products. Presently, vacuum drying has been
the food materials prevents the growth and reproduction applied to dry various food materials, the vacuum drying
of spoilage microorganisms, slows down the action of kinetics of many fruits and vegetables has been investigated
enzymes and minimizes many of the moisture mediated and the effect of vacuum drying conditions on the drying
deteriorative reactions. Although drying processing effec- process and the qualities of dried products has been evalu-
tively extends the shelf life of agricultural products, loss ated (Arevalo-Pinedo & Murr, 2006; Arevalo-Pinedo &
of sensory and nutritive qualities is considered inevitable Murr, 2007; Bazyma et al., 2006; Cui, Xu, & Sun, 2004;
during traditional drying process due to the undesirable Jaya & Das, 2003; Methakhup, Chiewchan, & Devahastin,
textural and biochemical changes (Watson & Harper, 2005).
1988). Eggplant (Solanum melongena var. esculenta) is an
Compared with conventional atmospheric drying, vac- important market vegetable of Asian and Mediterranean
uum drying has some distinctive characteristics such as countries and has a very limited shelf life for freshness. In
order to evaluate the practicability of vacuum drying for
improving the quality of dried eggplant, it is necessary to
*
carry out research on the vacuum drying characteristics
Corresponding author. Tel./fax: [phone].
of eggplant fruit. The objectives of this study were to
E-mail address: [e-mail] (A. Tagawa).
0260-8774/$ - see front matter Ó 2007 Elsevier Ltd. All rights reserved.
doi:10.1016/j.jfoodeng.2007.03.030
L. Wu et al. / Journal of Food Engineering 83 (2007) 422 429 423
Nomenclature
A area (m2) R2 coefficient of determination
Deff effective moisture diffusivity (m2 s 1) Rd drying rate (kg m 2 h 1)
Ea activation energy (kJ kg 1) RMSE root mean square error
L sample thickness (m) t time (h)
M moisture content (d.b., decimal) T temperature (K)
M0 initial moisture content (d.b., decimal) V volume (m3)
Me equilibrium moisture content (d.b., decimal) Wd weight of dry matter (kg)
MR moisture ratio a,b coefficients in drying model
P pressure (kPa) h time (s)
P0 mean relative deviation (%) v2 reduced chi-square
R gas constant (0.462 kJ kg 1 K 1)
investigate the vacuum drying characteristics of the egg- 2.3. Experimental procedure
plant samples, to evaluate the effect of vacuum drying
conditions on the drying process, and to choose a suit- The vacuum drying chamber was preheated for 12 h
able drying model for describing the whole drying before the experiments started to obtain stable drying tem-
process. perature. Drying experiments were conducted in the drying
chamber at temperatures ranging from 30 to 50 °C, and
2. Material and methods pressures of 2.5, 5, 10 kPa as well as atmospheric pressure,
respectively. One sample was placed on the wire netting
2.1. Sample preparation basket and dried in each run, its weight was continuously
recorded at intervals of 5 min using the data acquisition
Fresh eggplants (cultivated in Kochi Prefecture Japan, system throughout the drying process. It was considered
cultivar: unknown) were purchased from a local market that the sample reached the equilibrium moisture content
and stored at 8 °C before experiments started, the storage (EMC) of drying when the reading of weight remained
time was not more than 12 h in this study. The central part the same for 1 h.
of each eggplant fruit was cut into a rectangular-shaped Fresh samples were dried under the above-mentioned
block of 45 25 20 mm for drying treatment. The initial conditions for durations ranging from 1 to 15 h individu-
moisture content of the sample blocks was determined as ally to evaluate the drying shrinkage. Approximate volume
94.00% in wet basis (N = 20, standard deviation: 0.52%) and surface area of the dried samples were calculated from
according to the vacuum oven method (i.e., drying at the measured dimensions data. According to preliminary
70 °C and 2.5 kPa for 12 h) (AOAC, 1995). tests, in which a comparison between the calculated results
and the measured volume of the dried samples using liquid
2.2. Experimental setup displacement method (Maskan, 2001; Orikasa, Tagawa,
Nakamura, & Iimoto, 2005; Zogzas, Maroulis, & Mari-
A schematic diagram of the experimental vacuum dry- nos-Kouris, 1994) was conducted, the calculated results
ing system is shown in Fig. 1. The system primarily con- were proved to be acceptable, similar results were reported
sists of an oil rotary vacuum pump (TSW-300, SATO by Ratti (1994).
VAC, Japan), a vacuum control unit (NVC-2000L, Tokyo
Rikakikai, Japan) to obtain various processing pressures 2.4. Data analysis
in the vacuum drying chamber (a glass desiccator) and
a forced convection drying oven (DO600FA, AS ONE, The average moisture content of each sample during
Japan) to maintain desired drying temperatures. A data drying was calculated from the sample weight recorded
acquisition system composed of a load cell (LTS-50GA, by the data acquisition system (moisture distribution in
KYOWA, Japan) which was fixed on a supporting frame, the sample was considered to be uniform in this study).
a wire netting sample holder suspended from the load cell, Moisture ratio (MR) of the sample was determined by
an instrumentation amplifier (WGA-710A, KYOWA, the following equation:
Japan) and a data logger (KEYENCE, NR-1000, Japan)
ðM MeÞ
MRź ð1Þ
was used to on-line monitor and record the changes in
ðM0 MeÞ
sample weight during drying. Hot air drying runs at 30
50 °C and atmospheric pressure were also conducted in where M is the average moisture content of a sample at any
the same glass desiccator with the top lid removed for time of drying, M0 and Me stand for the initial and equilib-
comparison. rium moisture content, respectively.
424 L. Wu et al. / Journal of Food Engineering 83 (2007) 422 429
Fig. 1. Schematic diagram of vacuum drying system: 1. vacuum pump, 2. cold trap, 3. vacuum control unit, 4. forced convection drying oven, 5. glass
desiccator, 6. load cell, 7. supporting frame, 8. wire netting sample holder, 9. instrumentation amplifier, and 10. data logger.
Drying curves (MR vs. time) were plotted and fitted by conditions were plotted. From Fig. 2, the drying time
four empirical drying models (i.e., proposed polynomial needed to reach the EMC was shortened notably with an
model, exponential model, Page s model and logarithmic increase in drying temperature due to a larger driving force
model), and a theoretical model based on the Fick s diffu- for heat and mass transfer at higher drying temperature.
sion law; model coefficients were calculated using Origin- Fig. 3 showed that drying chamber pressure ranging from
Pro 7.5 software (OriginLab Corp.). The goodness of fit 2.5 to 10 kPa did not affect the drying process as strongly
was evaluated by the coefficient of determination (R2), as drying temperature did. For the present vacuum drying
the root mean square error (RMSE), the reduced chi- conditions, the effect of drying chamber pressure on the dry-
square (v2) and mean relative deviation modulus (P0) ing process was not significant. According to the reports of
defined by the following equation Arevalo-Pinedo and Murr (2006) and Arevalo-Pinedo and
Murr (2007) for carrot and pumpkin, Cui et al. (2004) for
n
Y Y
100X
exp;i pre;i
carrot, Giri and Prasad (2007) for mushroom, and Metha-
P0ź ð2Þ
N Y
exp;i khup et al. (2005) for Indian gooseberry, drying pressure
iź1
had a certain effect on the drying process, the drying time
where Yexp,i is the experimental result of the investigated
was reduced by decreasing drying pressure. The differentia-
variable, Ypre,i is the predicted value from various mathe-
tion between the results of this study and the literature
matical models, N is the number of observations (Chen &
could be attributed to the different processing conditions
Morey, 1989; Jena & Das, 2007; Madamba, Driscoll, &
as well as different degrees of boiling point elevation caused
Buckle, 1996; Sacilik & Elicin, 2006).
by various plasma concentrations of the tested materials.
The best model describing the vacuum drying process of
the eggplant samples was chosen as the one with the high-
3.2. Drying shrinkage
est R2 and the least RMSE, v2 and P0.
Comparisons between means were performed in SPSS
Drying shrinkage affects not only the product quality
12.0 software (SPSS Inc.) using Duncan s multiple range
but also the drying process and rehydration capability of
tests at a significance level of 0.05.
the dried food materials (Karathanos, Anglea, & Karel,
1993; Maskan, 2001; Mcminn & Magee, 1997a, 1997b).
3. Results and discussion Ratti (1994) indicated that changes in the dimensions of
dried sample were independent of drying conditions but
3.1. Effect of vacuum drying conditions on drying process dependent on the geometric shape and type of foodstuff.
Souma, Tagawa, and Iimoto (2004) reported that the hot
After vacuum drying, the moisture content of the egg- air drying shrinkage of eggplant is very remarkable and
plant samples was reduced from a initial value of 15.67 to the reduction in sample volume was larger than the volume
less than 0.2 kg water/kg dry matter. The effects of drying of removed water due to its high porosity, similar tendency
temperature and pressure on the vacuum drying process were also observed in this study, as shown in Fig. 4.
are shown in Figs. 2 and 3a,b, in which drying curves (mois- In order to investigate the drying shrinkage of the sam-
ture content in dry basis vs. time) under different drying ples, drying experiments with different drying durations
L. Wu et al. / Journal of Food Engineering 83 (2007) 422 429 425
20 1.0
P = 2.5 kPa
50 °C Hotair drying
30 °C
15
50 °C 2.5 kPa Vacuum drying
0.8
40 °C
50 °C
10
0.6
5
0.4
0
0 5 10 15 20 25
Drying time (h)
0.2
Fig. 2. Changes in average moisture content of samples during vacuum
drying at 2.5 kPa and 30 50 °C.
0.0
0 0.2 0.4 0.6 0.8 1
(V0-V)/V0
were carried out under various drying conditions, the vol-
ume and surface area of the dried samples were calculated.
Fig. 4. Comparison between volumetric shrinkage of eggplant and volume
Fig. 5 presents the relationship between the volume shrink- of removed water during drying at 50 °C and atmospheric pressure.
age ratio (V/V0) and the moisture content of the samples
plant tissue during drying. In contrast with atmospheric
dried at 2.5 kPa and various drying temperatures, the
drying, the pressure unbalance during vacuum drying is
results indicated that drying temperature had insignificant
substantially reduced due to the reduction in air pressure,
effect on the drying shrinkage of the eggplant samples for
consequently the drying shrinkage could be inhibited.
the investigated temperature range. Fig. 6 shows the effect
Until now, many theoretical and empirical models for
of drying chamber pressure on the drying shrinkage of the
describing drying shrinkage have been proposed (Mayor
samples at 50 °C, it can be seen that the shrinkage became
& Sereno, 2004). Among them, linear equation:
more severe at higher vacuum chamber pressures. This
phenomenon could be explained as follows: when water
V
źaMþb ð3Þ
is removed from the material during drying, a pressure
V
0
unbalance is generated between the interior of the dried
where V is the volume of a sample at any time of drying
material and the external environment, and induces the
(m3), M is the average moisture content of the sample at
contracting stresses that lead to drying shrinkage. The dry-
ing shrinkage of eggplant is particularly severe because of
the collapse of the unconsolidated porous structure of egg-
P = 2.5 kPa
1
0.8
20
a
T = 30 °C
0.6
2.5 kPa 30 °C
15
0.4
5 kPa 40 °C
10 kpa 50 °C
0.2
10
0
0 4 8 12 16
5
Moisture content (d.b. decimal)
0
Fig. 5. Volume shrinkage ratio (V/V0) as a function of moisture content
0 5 10 15 20 25
of samples at 2.5 kPa and different drying temperatures.
Drying time (h)
b
20 T = 50 °C
1
T = 50°C
2.5 kPa
15 0.8
5 kPa
0.6
10 kPa
2.5 kPa
10
0.4 5 kPa
5 10 kPa
0.2
Atmospheric pressure
0
0
0 0.2 0.4 0.6 0.8 1
0 5 10 15 20
M/M0
Drying time (h)
Fig. 3. Changes in average moisture content of samples during vacuum Fig. 6. Volume shrinkage ratio (V/V0) as a function of moisture content
drying at different drying chamber pressures: (a) 30 °C and (b) 50 °C. of samples at 50 °C and different drying chamber pressures.
/V
(d.b.decimal)
Moisture content
removed water
0
V
0
V/V
(d.b.decimal)
Moisture content
0
V/V
(d.b.decimal)
Moisture content
426 L. Wu et al. / Journal of Food Engineering 83 (2007) 422 429
the same time, V0 is the sample s initial volume (2.25
0.006
30°C 2.5 kPa Experimental
10 5 m3 (initial moisture content: 15.67) in this study),
0.005
has been successfully used for describing the drying shrink-
0.004
age of a wide range of foodstuffs under various drying con-
ditions (Baini & Langrish, 2007; Lozano, Rotstein, &
0.003
y = 0.0001x + 0.0027
Urbicain, 1980; Lozano, Rotstein, & Urbicain, 1983; Ratti,
0.002
R2 = 0.9802
1994; Suzuki, Kubota, Tsutomu, & Hosaka, 1976; Zogzas
P' = 8%
0.001
et al., 1994).
0
Eq. (3) was fitted to the experimental data under differ-
0 4 8 12 16
ent drying conditions, goodness of fit of the equation was
Moisture content (d.b. decimal)
evaluated by R2 and P0. The statistical results indicated that
Fig. 7. Variation in surface area with respect to moisture content of
under present conditions, linear model was adequate to
samples during drying at 2.5 kPa and 30 °C.
predict the drying shrinkage of the eggplant samples, the
R2 of the linear regression reached about 0.99, and P0
was less than 7%, as shown in Table 1. The results also
3.3. Rate of vacuum drying
proved that the drying shrinkage caused by vacuum drying
was obviously less than that caused by atmospheric drying
According to Toei (1975), drying rate (Rd) is defined as
at the same drying temperature.
W dM
d
Theoretically, the surface area of the sample during dry-
Rdź ð6Þ
A dt
ing can be predicted by the following equation (Orikasa
where Rd is the drying rate (kg m 2 h 1), Wd is the weight
et al., 2005; Pabis, 1999; Pabis & Jaros, 2002; Suzuki
of dry matter of the sample (kg), A is the drying area of the
et al., 1976):
sample (m2), M is the volume-averaged moisture content, t
2
l
3
2
A V
is the drying time (h).
3
źk źkðaMþbÞl ð4Þ
A0 V
0 Substituting Eq. (5) into Eq. (6) gives
where A is the surface area of a sample at any time (m2), A0 W dM
Rdź 0 d ð7Þ
is initial surface area of the sample. Due to the complexity
a Mþb0 dt
of drying process of food materials, Eq. (4) lost its accuracy
The drying rate of the samples under various drying condi-
in some cases. According to the results reported by
tions was calculated using Eq. (7) and plotted with respect
Nakamura, Tagawa, Orikasa, and Iimoto (2005) Orikasa,
to the moisture content in dry basis. Fig. 8 shows the
Tagawa, Soma, Iimoto, and Ogawa (2005), the relationship
changes in drying rate as a function of moisture content
between surface area and moisture content in dry basis of
at 2.5 kPa and various drying temperatures, similar trends
the sample could be approximately expressed by a linear
were observed at other drying chamber pressures. From the
equation:
figure, the drying temperature affected the drying rate
Aźa0Mþb0 ð5Þ
significantly, drying at higher temperature was apparently
faster than that at lower temperatures. The results also
Eq. (5) was fitted to the experimental data of surface area
indicated that the drying rates of the samples decreased
and moisture content, the model coefficients and the
with decreasing moisture content throughout the drying
indexes of goodness of fit (R2 and P0) were calculated.
processes, that is to say, vacuum drying of the eggplant
The results showed that the linear equation was adequate
samples under the investigated drying conditions took
to describe the changes in surface area with respect to the
place in the falling rate period only.
moisture content of the samples during drying. The exper-
imental data at 30 °C and 2.5 kPa and the results of linear
regression are shown in Fig. 7.
0.8 P= 2.5 kPa
Table 1
Results of linear regression for modelling drying shrinkage with respect to
30 ºC 40 ºC 50 ºC
0.6
moisture content
Drying condition Linear equation R2 P0(%)
0.4
coefficient
Vacuum drying (2.5 kPa, 50 °C) a = 0.6124, 0.9864 3.3819
0.2
b = 0.3961
Vacuum drying (5 kPa, 50 °C) a = 0.6773, 0.9929 3.0343
0
b = 0.3657
01020
5 15
Vacuum drying (10 kPa, 50 °C) a = 0.7238, 0.9919 3.5381
Moisture content (d.b. decimal)
b = 0.307
Hot air drying (atmospheric a = 0.8438, 0.9897 6.0831
Fig. 8. variation in drying rate with respect to moisture content of samples
pressure, 50 °C) b = 0.2471
at 2.5 kPa and different drying temperatures.
2
Surface area (m )
-2
-1
"
"
(kg m
h )
Drying rate
L. Wu et al. / Journal of Food Engineering 83 (2007) 422 429 427
As can be seen in Fig. 9a,b, the warming-up and con-
3.0
P = 2.5 kPa
stant rate period (from initial moisture content to about
2.5
5 kg water/kg dry matter) as existed in the hot air drying
process were not observed in the vacuum drying at 30 30°C
2.0
50 °C. For the investigated drying temperature range, the 40°C
1.5
vacuum drying was apparently faster than the hot air dry- 50°C
ing at atmospheric pressure and the same temperature, but
1.0
the difference between the drying rate of the vacuum and
0.5
hot air drying diminished quickly with increasing drying
temperature.
0.0
0 5 10 15 20
3.4. Modelling vacuum drying process of eggplant sample Drying time (h)
Fig. 10. dM/dt as a function of drying time at 2.5 kPa and different drying
In this study, perfect linear relationships between dM/dt
temperatures.
and drying time t were observed for all the investigated
vacuum drying conditions, as shown in Fig. 10. Accord-
ingly, the relationship between dM/dt and t can be
Table 2
expressed as
Model coefficients and goodness of fit of the proposed drying model fitted
to experimental data of 2.5 kPa and 30 °C
dM
źa0tþb0 ð8Þ
Equation Model coefficient R2 RMSE v2 P0
dt
(%)
By integrating Eq. (8) with respect to time (t) Using the ini-
MR = at2 + bt +1 a = 0.00298, 0.999 0.008 0.00006 5.31
tial condition M = M0 at t = 0, Eq. (9) can be obtained:
b = 0.10801
a0
Mź t2þb0tþM0 ð9Þ
2
Eq. (10) described the changes in MR of the eggplant
Eq. (9) may be further transformed into a more general
samples during vacuum drying process. Same equation
form as follows:
was proposed by Wang and Singh (1978) for modelling
M Me
the drying process of rough rice.
MRź źat2þbtþ1 ð10Þ
M0 Me
Drying curves (MR vs. time) under various drying con-
where a and b are coefficients to be determined empirically. ditions were plotted and fitted with Eq. (10) and other four
commonly-used drying models. The results indicated that
among the five drying models, the suggested polynomial
model Eq. (10) had the best goodness of fit indexes (i.e.,
0.8
a
highest R2 and lowest RMSE, v2 and P0, as shown in Table
2.5 kPa
T=30°C 2). A comparison between the drying curves (MR vs. t) at
Atmospheric pressure
0.6
2.5 kPa and various drying temperatures and the data pre-
dicted by Eq. (10) is shown in Fig. 11. The polynomial
0.4
model equation (10) was proved to be adequate to model
the whole vacuum drying process of the eggplant samples.
0.2
0
0 5 10 15 20
1.2
P = 2.5 kPa
Moisture content (d.b. decimal)
1 30 °C Predicted
0.8
2.5 kPa 40 °C Predicted
b
0.8
T = 50°C
50 °C Predicted
Atomospheric pressure
0.6
30 °C Experimental
0.6
40 °C Experimental
0.4
0.4
50 °C Experimental
0.2
0.2
0
0 5 10 15 20
0
0 4 8 12 16 20 24
Moisture content (d.b. decimal)
Drying time (h)
Fig. 9. Comparison of drying rate between vacuum drying (2.5 kPa) and
hot air drying of eggplant sample at same drying temperature: (a) 30 °C Fig. 11. Comparison of drying curves (MR vs. t) at 2.5 kPa and various
and (b) 50 °C. drying temperatures and data predicted by drying model equation (10).
dM/dt
-2
-1
(kg
"
m
"
h )
Drying rate
-2
-1
Moisture ratio
(kg
"
m
"
h )
Drying rate
428 L. Wu et al. / Journal of Food Engineering 83 (2007) 422 429
3.5. Calculation of basic drying parameters
1.00E-08
Drying models based on the diffusion theory sometimes
failed to accurately predict the drying process of some
foodstuffs due to the complexity of food drying kinetics
as well as the incompliance with the basic assumptions
1.00E-09
for using the model. however, the diffusion equation is still
2.5 kPa
extensively used for the evaluation of the fundamental
Atmospheric pressure
parameters of drying process.
Since the drying of the eggplant samples took place in
the falling rate period only, the following infinite series
1.00E-10
0.003 0.0031 0.0032 0.0033 0.0034
solution of Fick s second law of diffusion, which was devel-
oped for particles with slab geometry assuming unidirec-
1/T (K-1)
tional moisture movement without volume change,
Fig. 13. Temperature dependence of effective moisture diffusivity.
constant diffusivity and temperature, uniform initial mois-
ture distribution, was used for the calculation of the effec-
tive moisture diffusivity of the samples during drying: Under the investigated experimental conditions, the dry-
!
ing chamber pressure showed no significant effect on the
1
X
8 1 ð2nþ1Þ2p2Deffh
Deff of the samples, while increasing drying temperature
MRź exp ð11Þ
p2 ð2nþ1Þ2
4L2
led to an apparent increase in the effective moisture diffu-
nź0
sivity. The temperature dependence of Deff was examined
where MR is the moisture ratio, Deff is the effective mois-
by the following Arrhenius-type equation (Madamba
ture diffusivity (m2/s), L is the slab thickness (m), the half
et al., 1996; Pińaga, Carbonell, Peńa, & Miquel, 1984; Tag-
slab thickness is used when evaporation occurs on both
awa et al., 2003):
sides of the slab, and h is the drying time (s) (Crank,
Ea
1975; Tutuncu & Labuza, 1996).
DeffźD0 exp ð12Þ
In this study, notable deviations from the experimental
RT
results were observed when using the drying model based
where Ea is referred to as activation energy for moisture
on the diffusion theory to describe the latter part
diffusion (kJ), T is the absolute temperature (K). A typical
(MR < 0.35) of the drying process. Consequently, the effec-
Arrhenius-type relationship between the Deff and drying
tive moisture diffusivity of the eggplant samples for the MR
temperature could be observed by plotting Deff with respect
range from 1 to 0.35 was calculated by fitting Eq. (11) to
to the reciprocal of absolute temperature in a semi-loga-
the MR data between 1 and 0.35 under various drying con-
rithmic graph (Fig. 13), the activation energy for moisture
ditions. Fig. 12 showed that the infinite series solution of
diffusion, which was obtained from the slopes of the lines
Fick s second law of diffusion Equation (11) agreed fairly
fitted to the data in Fig. 13, was found to be 1640 and
satisfactorily with the experimental results. For the tested
1652 kJ/kg for the vacuum drying and hot air drying under
MR range, the values of the Deff of the samples dried at
atmospheric pressure, respectively. The temperature depen-
2.5 kPa and 30, 40 and 50 °C were calculated to be
dence of the effective moisture diffusivity for the vacuum
1.653 10 9, 2.353 10 9 and 3.417 10 9 m2/s, respec-
drying of the eggplant samples could be described by the
tively, which was significantly higher than those of the
following equation:
hot air dried samples (varying from 1.005 10 9 to
3550:1
2.086 10 9) at the same temperature, as shown in Fig. 13.
Deffź2:012 10 4 exp ð13Þ
T
10
4. Conclusion
30 °C 2.5 kPa Experimental
Pedicted by Eq. (11)
Vacuum drying of the eggplant samples under the inves-
tigated drying conditions took place in the falling rate per-
1
iod. Drying chamber pressure had statistically insignificant
effect on the vacuum drying process, increasing drying tem-
perature shortened the drying process notably. The drying
shrinkage of the samples was independent of the drying
0.1
temperature, but intensified significantly with an increasing
0 5 10 15 20 25 30
in the drying chamber pressure. The relationship between
Drying time (×103s)
the vacuum drying shrinkage ratio and moisture content
during vacuum drying could be expressed by a linear equa-
Fig. 12. Comparison of experimental results (30 °C and 2.5 kPa) within
MR range from 1 to 0.35 and predicted data using diffusion Eq. (11). tion. The suggested polynomial model showed the best fit
eff
D
MR
L. Wu et al. / Journal of Food Engineering 83 (2007) 422 429 429
Mayor, L., & Sereno, A. M. (2004). Modelling shrinkage during
to the experimental results among the examined drying
convective drying of food materials: A review. Journal of Food
models, and can be used to describe the vacuum drying
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Mcminn, W. A. M., & Magee, T. R. A. (1997a). Physical characteristics of
gated vacuum drying conditions. The effective moisture dif-
dehydrated potatoes  Part I. Journal of Food Engineering, 33(1-2),
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