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Journal of Food Engineering 107 (2011) 253–261
Contents lists available at ScienceDirect
Journal of Food Engineering
journal homepage: www.elsevier.com/locate/jfoodeng
Estimating the theoretical energy required to dry rice
Maria A. Billiris a, Terry J. Siebenmorgen a,⇑, Andy Mauromoustakos b
a
b
Department of Food Science, University of Arkansas, Fayetteville, AR 72704, USA
Agricultural Statistics Lab., University of Arkansas, Fayetteville, AR 72701, USA
a r t i c l e
i n f o
Article history:
Received 2 March 2011
Received in revised form 9 June 2011
Accepted 11 June 2011
Available online 23 June 2011
Keywords:
Heat of desorption
Desorption isotherms
Clausius–Clapeyron equation
a b s t r a c t
The total heat of desorption of rice (Qt) was determined for several rice types as a function of moisture
content (MC), and kernel temperature, using a semi-theoretical approach in which desorption isotherms
were used in conjunction with the Clausius–Clapeyron equation. Qt decreased exponentially as MC
increased, decreasing sharply for MCs above 15% and approaching the latent heat of vaporization of free
water at MCs around 20%. Qt of parboiled rice at 12.5% MC was significantly less than that of nonparboiled lots. Qt of medium-grain ‘‘Jupiter’’ was significantly greater than that of long-grains at 12.5%
MC. Equations that predict the energy required to dry a unit mass of rice from an initial MC to a final
MC were derived.
Ó 2011 Elsevier Ltd. All rights reserved.
1. Introduction
In order to maximize field yield and quality, rice is typically harvested at MCs greater than the level deemed safe for long-term
storage, which is often taken to be around 13% (Howell and
Cogburn, 2004). To preserve its quality, rice should be thus dried
to this safe level (Siebenmorgen and Meullenet, 2004).
Verma (1994) stated that the United States consumes 15 million
barrels of crude oil per year for drying grains, making grain drying
operations a major source of energy consumption. Kasmaprapruet
et al. (2009) reported that drying was the most energy-consumptive
unit operation in rice processing, accounting for 55% of the total
energy consumed for production and processing of rice.
The energy required to dry grains under ideal conditions varies
from 2500 to 2670 kJ/kg water depending on the drying temperature (T) (Fluck and Baird, 1980). However, Gunasekaran and
Thompson (1986) stated that drying of crops actually requires
from 3000 to 8000 kJ/kg water. Therefore, the efficiency of a drying
process depends on how drying is performed. Considering the
ongoing interest in reducing energy requirements and the importance of the rice crop in the United States and globally, it is timely
to investigate means of improving rice drying efficiency.
The first step in quantifying the performance of a rice drying
process is to calculate the theoretical energy required to remove
water from rice. The energy required for drying foodstuffs mainly
comprises the thermal energy required to remove water from the
food material; the mechanical energy required for conveyance or
airflow is less significant. Depending on the initial MC (MCi) of
the material and the desired final MC level (MCf), the removal of
⇑ Corresponding author. Tel.: +1 479 575 2841; fax: +1 479 575 6936.
E-mail address: tsiebenm@uark.edu (T.J. Siebenmorgen).
0260-8774/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved.
doi:10.1016/j.jfoodeng.2011.06.015
water from foodstuffs may require more energy than that required
to vaporize free water (latent heat of vaporization, hfg) (Okos et al.,
1992; Rizvi, 2005). Cenkowski et al. (1992) explained that when
the MC of a material is below 12% dry basis (d.b.), the increase in
intra-particle resistance to moisture migration increases the energy required to remove water. Okos et al. (1992) stated that the
energy required to remove water from foods increases as the binding-force between water and the food increases. Rizvi (2005) indicated that, in general, the energy requirement for drying food
materials has two main components: the energy required to evaporate free water and the energy required to remove water that is
associated with the food matrix.
The entire amount of energy required to remove water from a
food material has been referred to as the isosteric heat of sorption
(Iglesias and Chirife, 1976), the heat of sorption (Tsami et al., 1990)
and the isosteric heat of desorption (Kechaou and Maalej, 1999).
Herein, this quantity will be referred to as the total heat of desorption (Qt). The difference between Qt and hfg, which has been referred to as the net isosteric heat of sorption (Iglesias and Chirife,
1976; Tsami et al., 1990), will be called the net heat of desorption
(Qn). Aviara et al. (2004), Kechaou and Maalej (1999) and McMinn
and Magee (2003) indicated that Qn represents the energy beyond
hfg required to remove a unit mass of water from a foodstuff due to
water–solid bonds. The strength of water–solid bonds in foodstuffs
varies with MC, generally increasing as MC decreases (Okos et al.,
1992). Consequently, Qn would be expected to increase as drying
progresses. Researchers have confirmed this expectation (Aviara
et al., 2004; Cenkowski et al., 1992; Mulet et al., 1999; Toğrul
and Arslan, 2006; Tsami et al., 1990; Zuritz and Singh, 1985).
Cenkowski et al. (1992) found that the energy required to remove
water from grain is close to hfg for MCs above 20% (d.b.). However,
Johnson and Dale (1954) reported that energy requirements to
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remove water from wheat and shelled corn at MCs above 14% (d.b.)
are close to hfg.
Since Qn is the theoretical minimum energy above hfg required
to remove a unit mass of water from a particular food (Rizvi,
2005), it is important to establish the relationship between Qn
and MC in order to quantify the theoretical energy requirements
for drying rice. In addition, it is possible that the relationship between Qn and MC changes depending on kernel properties, including kernel temperature (Truong et al., 2005). Therefore, it is also
relevant to investigate energy requirements of different rice types,
cultivars and T levels. Thus, Qt should be determined as a function
of MC and T for a given rice type/cultivar. Actual energy requirements for a specific dryer can be compared to this ideal situation,
and thus efficiencies for different commercial dryers can be
calculated.
Little research has assessed theoretical energy requirements for
drying rice, particularly for different rice types and current cultivars. Iguaz and Vírseda (2007) estimated Qn values at different
MC levels for medium-grain rough rice; Toğrul and Arslan (2006)
and Zuritz and Singh (1985) estimated Qt values at different MC
levels for long-grain and medium-grain rough rice, respectively.
Researchers have used the Clausius–Clapeyron equation, in combination with sorption isotherm data, to calculate heats of desorption for diverse foodstuffs (Aviara and Ajibola, 2002; Aviara et al.,
2004; Chen, 2006; Iglesias and Chirife, 1976; Iguaz and Vírseda,
2007; Kechaou and Maalej, 1999; Mulet et al., 1999; Tolaba
et al., 2004; Toğrul and Arslan, 2006; Tsami et al., 1990).
The fact that sorption isotherms of foodstuffs demonstrate hysteresis is an indication of irreversibility, which has posed doubts on
the reliability of the Clausius–Clapeyron equation for determining
Qn and Qt (Iglesias and Chirife, 1976; McLaughlin and Magee,
1998). However, Iglesias and Chirife (1976), after analyzing works
performed by other researchers who compared the Clausius–Clapeyron approach to calorimetric heats, concluded that the heats
of irreversible processes are small enough to be neglected when
calculating energy requirements for drying foodstuffs. Mulet
et al. (1999) obtained good agreement between calorimetric heat
measurements using a thermogravimetric analyzer (TGA) in combination with a differential scanning calorimeter (DSC) and those
obtained from the Clausius–Clapeyron method for potato starch
and cauliflower. Consequently, the application of the Clausius–Clapeyron method was deemed appropriate for estimating energy
requirements for drying rice.
The objectives of this study were (1) to calculate Qn and Qt values at various MCs and Ts for different types of rice using equilibrium moisture content (EMC) data and the Clausius–Clapeyron
equation, (2) to mathematically model Qt as a function of MC and
T for the rice types under study, (3) to develop an equation that
predicts the theoretical energy required to dry rice from varying
MCi to a desired MCf.
2.2. Heat of desorption calculation
Qt was calculated using the form of the Clausius–Clapeyron
equation developed by Othmer (1940):
lnðpv Þ ¼
Qt
lnðps Þ þ c
hfg
ð1Þ
where pv is water vapor pressure in the rice kernel associated with a
particular T, ps is vapor pressure of pure water associated with a
particular T, Qt is the total heat of desorption (kJ/kg water), hfg is
the latent heat of vaporization of pure water at a given T (kJ/kg
water), c is an integration constant.
Qt/hfg was calculated from the slope of the regression line relating ln(pv) to ln(ps) at different Ts for a specific MC; the slope of the
line equals Qt/hfg for a specific MC. The pv values were calculated
from ERH data using the following relationship:
ERH ¼
pv
ps
ð2Þ
ERH is equilibrium relative humidity in a decimal form.
It is critical to select an appropriate equation to predict ERH
using T and MC as inputs in order to calculate Qt. Research indicates that the modified Chung–Pfost equation (Chung and Pfost,
1967; Pfost et al., 1976) best describes rice isotherm data (Basunia
and Abe, 1999; Ondier et al., 2011):
ERH ¼ exp
A
expðB MCÞ
T þC
ð3Þ
where A, B and C are constants, MC is expressed in a d.b. decimal
form, T is temperature (°C) and ERH is equilibrium relative humidity
expressed in a decimal form. The values of the constants A, B and C
were obtained from Ondier et al. (2010, 2011), depending on the
temperature range and cultivar. Zuritz and Singh (1985) reported
that among the isotherm equations at that time, only the Chung–
Pfost equation was appropriate for heat of desorption calculations,
because it was the only equation in compliance with the necessary
mathematical restriction that the heat of desorption decreases with
an increase in temperature. Thus, pv values were calculated using
Eqs. (2) and (3) and ps values from the psychometric relationships
in ASAE (1998).
Linear regressions of ln(pv) vs. ln(ps) were developed for selected MCs. Qt/hfg was estimated from the slope of each curve for
a given MC. The ratio Qt/hfg was assumed to be constant in the temperature range over which the data were collected. Thus, Qt for a
given MC and T combination was calculated using a consistent
Qt/hfg ratio for a given MC level: however, to account for varying
T levels, hfg was varied to correspond to the desired T level using
Perry and Chilton (1973). The net heat of desorption Qn was then
calculated using Eq. (4).
Q t ¼ Q n þ hfg
ð4Þ
2.3. Heat of desorption prediction
2. Materials and methods
2.1. Sorption isotherms
EMC data were obtained from two previous studies. Elevatedtemperature desorption isotherms (60, 70, 80 and 90 °C) for
long-grain ‘‘Cybonnett’’ rough rice were obtained from Ondier
et al. (2010). In addition, rough rice sorption isotherms at low temperatures (10, 20, 30, 45 and 60 °C) for long-grains ‘‘Wells’’ and ‘‘CL
XL730’’, medium-grain ‘‘Jupiter’’ and a long-grain parboiled rice of
unknown cultivar were obtained from Ondier et al. (2011). The
data from both studies were used to calculate Qt and Qn at selected
MCs and Ts.
In order to mathematically express Qt as a function of MC and T
for the different types of rice, Qt, MC and T data were used to statistically determine the constants of the relationship used by
Truong et al. (2005):
Q t ¼ A1 þ B1 T þ ðA2 þ B2 TÞ expðA3 MCÞ
ð5Þ
where A1, A2, A3, B1 and B2 are constants of the equation estimated
iteratively by fitting the non-linear model. Qt is in J/kg water, MC is
in dry basis, decimal and T is in K.
Truong et al. (2005) successfully used this model to describe Qt
data for a mixture of maltodextrin–sucrose. Non-linear least
squares regression analyses were performed on the data to obtain
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Table 1
Equilibrium relative humidities (%) of long-grain ‘‘Cybonnett’’ rough rice at the
indicated moisture contents and temperatures calculated using the modified Chung–
Pfost equation (Ondier et al., 2010).
Temperature, °C
Moisture content, % w.b.
8
60
70
80
90
26
37
46
53
10
49
60
67
72
12
70
77
82
84
14
84
88
91
92
16
92
94
95
96
18
96
97
98
98
20
98
99
99
99
22
99
99
99
99
the constants for Eq. (5). Root mean square error (RMSE) and standard error of the coefficients (SE) were used to assess the fit and
precision of the estimates.
2.4. Energy requirements per unit mass of rice and per unit mass of
water removed
Qt data was used to develop an equation that predicts the theoretical energy required per unit mass dry matter of rice (QTrice)
to dry rice from a given MCi to a MCf when drying at a given T, similar in approach to Tsami et al. (1990). To calculate QTrice, an integration of Eq. (5) was performed:
Q Trice ¼
Z
MCf
Q t dMC
ð6Þ
MCi
where QTrice is the energy required to dry rice from MCi to MCf per
unit dry mass of rice at a given T. Thus, T was considered constant
throughout the integration.
Substituting Eq. (5) into Eq. (6) and integrating:
Q Trice ¼
Z
Table 2
Net heat of desorption (Qn), total heats of desorption (Qt) and standard errors (SE) of
Qn and Qt, calculated from linear regressions using the Clausius–Clapeyron equation
at the selected moisture content levels for long-grain ‘‘Cybonnett’’ rough rice at 60 °C.
The value of hfg was 2359 kJ/kg water.
MCf
ðA1 þ B1 T þ ðA2 þ B2 TÞ expðA3 MCÞÞdMC
MCi
¼ A1 ½MCf MCi þ B1 T ½MCf MCi þ
ðexpðA3 MCf Þ expðA3 MCi ÞÞ
ðA2 þ B2 TÞ
A3
ð7Þ
Moisture content, % w.b.
Qn, kJ/kg water
Qt, kJ/kg water
SE, kJ/kg water
8
10
12
14
16
18
20
22
1381
743
359
180
81
42
18
0
3741
3102
2718
2539
2440
2401
2377
2359
166
106
57
29
9
9
10
0
Table 3
Estimated constants of Eq. (5) and associated root mean square errors (RMSEs) for
long-grains ‘‘Wells’’, ‘‘CL XL730’’ and ‘‘Cybonnett’’, medium-grain ‘‘Jupiter’’, parboiled
rice and for a general model describing all non-parboiled, long-grain rice cultivars.
Cultivar
‘‘Jupiter’’
‘‘Wells’’
‘‘Cybonnett’’
‘‘CL XL730’’
General
Parboiled
Parameter
RMSE
A1
A2
A3
B1
B2
3,150,878
3,150,927
3,200,035
3,150,916
3,189,745
3,151,394
12,725,771
11,509,211
19,950,786
10,117,409
9,742,417
8,107,920
23.2
23.4
27.1
22.7
24.2
23.0
2377
2377
2521
2377
2496
2377
9601
8683
15,719
7632
–
6117
0.22
0.23
1.15
0.23
4.0
0.72
By using Eq. (7), expressions for each type of rice were obtained,
whereby energy requirements for drying a unit mass of rice dry
matter were obtained for given MCi, MCf and T inputs. The value
of QTrice (J/kg dry matter rice) is negative but the absolute value
was reported.
To express the energy requirements to dry rice from an MCi to
an MCf on a per unit mass of water removed basis, QTrice from Eq.
(7) was divided by Dmevap the mass of water removed in the drying
process per unit rice dry matter, which can be expressed as:
Fig. 1. Natural logarithm of water vapor pressure in the rice kernel vs. the natural logarithm of vapor pressure of pure water, for long-grain ‘‘Cybonnett’’ rough rice at four
moisture content levels (w.b.) and temperatures ranging from 60 to 90 °C. The slope of each moisture content level regression line equals the total heat of desorption/latent
heat of evaporation of pure water (Qt/hfg) quotient, per Eq. (1).
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Fig. 2. Total heat of desorption (Qt) as a function of moisture content (% wet basis) for medium-grain ‘‘Jupiter’’, at 45 °C and those reported for a medium-grain rice at 40 °C by
Zuritz and Singh (1985).
Table 4
Predicted values and confidence intervals for the total heat of desorption (Qt) as
obtained from Eq. (5) at 12.5% moisture content and 60 °C and for the rice types
indicated.
Rice type
Qt, kJ/kg
water
95% Confidence interval, kJ/kg
water
Medium-grain ‘‘Jupiter’’
2705
2704–2707
Long-grain ‘‘Wells’’
Long-grain ‘‘Cybonnett’’
Long-grain ‘‘CL XL730’’
2665
2665
2656
2664–2666
2659–2672
2655–2657
Long-grain non-parboiled
(general)
2669
2656–2671
Long-grain parboiled
2590
2587–2593
Dmevap ¼ MCi MCf
same trends were observed for all rice types. Values of Qn for
long-grain ‘‘Cybonnett’’ at 60 °C are tallied in Table 2. The standard
error of Qn is equal to the SE of Qt because the difference between
these two values is a constant (hfg). Iguaz and Vírseda (2007) reported for medium-grain rough rice, Qn values from 139 to
1021 kJ/kg water for MCs ranging from 19% to 0.04% and Ts from
40 to 80 °C. The Qn values obtained in this study are greater than
those of Iguaz and Vírseda (2007) at low MCs and are lower than
those of Iguaz and Vírseda (2007) at high MCs.
3.1. Total heat of desorption prediction
ð8Þ
It is emphasized that QTrice can thus be expressed as drying energy
required per unit mass of rice dry matter, Eq. (7), or energy per unit
mass of water removed by dividing Eq. (7) by Dmevap (Eq. (8)).
All statistical analyses were performed using JMP 8.0.1 software
(SAS Institute, Inc.).
3. Results and discussion
Table 1 shows the predicted ERH values, at temperatures ranging from 60 to 90 °C, calculated from Eq. (3), for selected MCs for
long-grain ‘‘Cybonnett’’ rough rice (Ondier et al., 2010). For each
MC value, linear regressions of ln(pv) vs. ln(ps) were performed
using Eq. (1); Fig. 1 shows the corresponding linear regressions obtained for the MC levels of 8%, 10%, 12% and 18%. Qt was calculated
from the slope of each line. The same procedure was used for estimating Qt when using EMC data collected at Ts ranging from 10 to
60 °C for the four lots listed previously (data not shown). Qn was
calculated through Eq. (4). The slope of the ln(pv) vs. ln(ps) line approaches unity as MC increases (Fig. 1). Consequently, Qt approaches hfg as MC increases. This can also be interpreted to
indicate that the energy required to dry rice, in terms of energy
per unit moisture removed, increases as drying progresses. The
Heats of desorption obtained from Eq. (1), along with corresponding MCs and Ts, were used to determine the parameters of
Eq. (5) for each type of rice. Because of great differences among
the SEs of Qt across MCs (Table 2), non-linear regressions were performed using the weighting feature of JMP (SAS Institute, Inc.), in
which the SEs were weighted by using the reciprocal of SE (1/
SE). RMSE and equation constants obtained for Eq. (5) are shown
in Table 3. Eq. (5) describes the experimental data well based on
the low RMSE values for every rice type (Table 3). Additionally,
the model consistently converged with little iteration to the estimates of the parameters, which is an indication of goodness of
fit. When Iguaz and Vírseda (2007) modeled heat of desorption
data, using the modified Guggenheim Anderson De Boer (GAB) isotherm equation (Anderson, 1946; De Boer, 1953; Guggenheim,
1966; Jayas and Mazza, 1993) to predict ERH, they found that the
Kechaou and Maalej model (Kechaou and Maalej, 1999) was appropriate in describing Qn vs. MC data. Heat of desorption data for rice
reported by Zuritz and Singh (1985), who used the Chung–Pfost
equation to predict ERH, showed an exponential trend (Fig. 2),
which is in agreement with the results obtained in this study.
However, it is noted that Zuritz and Singh (1985) did not test
any model to describe heat of desorption vs. MC. Discrepancies
in findings can be explained by Souza et al. (2006), in that regardless of the crop, Qn, and thus Qt, behavior varies, depending on the
equation that is used to predict ERH from sorption isotherm data.
Rice was among the crops studied by Souza et al. (2006) who
observed that when the modified Chung–Pfost equation was used
to predict ERH, the heat of desorption curve followed an
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Fig. 3. Total heat of desorption (Qt) at different moisture content levels for long-grain ‘‘CL XL730’’, long-grain ‘‘Wells’’, medium-grain ‘‘Jupiter’’ and parboiled rice at 60 °C. The
value of hfg is indicated and was 2359 kJ/kg water.
Table 5
Equations based on Eq. (7) and Table 3 to predict the energy required to dry rice from an MCi to a desired MCf (QTrice) in J/kg dry matter, for the indicated rice types.a
Equation
Medium-grain/non-parboiled
Q Trice ¼ ð3; 150; 878 2377TÞðMCf MCi Þ þ e23:2MCf e23:2MCi
23:2
Q Trice ¼ ð3; 189; 745 2496TÞðMCf MCi Þ þ e24:2MCf e24:2MCi ð9;742;417Þ
24:2
Q Trice ¼ ð3; 151; 394 2377TÞðMCf MCi Þ þ e23:0MCf e23:0MCi ð8;107;9206117TÞ
23:0
Long-grain/non-parboiled
Long-grain/parboiled
a
b
Temp. range,b °C
Rice type
ð12;725;7719601TÞ
10–60
10–90
10–60
MCi and MCf are inputs on a dry basis.
Temperature range over which EMC data were collected.
Fig. 4. Total energy required to dry rice (QTrice) to 12.5%, 13.5% and 14.5% w.b. moisture content, expressed on a per unit mass of wet or dry matter of rice, as a function of the
initial moisture content of the rice for long-grain, non-parboiled rice at 60 °C.
exponential trend. In the case of other ERH equations, such as the
modified Henderson equation (Thompson et al., 1968), the Qn
curve was linear.
To assess differences in drying energy requirements among rice
cultivars, a final, target MC of 12.5% was chosen based on the fact
that 12.5% is a typical, desired final MC in the rice industry. Since Qt
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Fig. 5. Energy required to dry rice (QTrice) to 12.5%, 13.5% and 14.5% w.b. moisture content, expressed on a per unit mass of water removed, basis as a function of the initial
moisture content of rice for long-grain non-parboiled rice at 60 °C.
Fig. 6. Energy required to dry rice (QTrice) to 12.5% w.b. moisture content, expressed on a per unit mass of water removed, basis as a function of the initial moisture content of
the rice for long-grain non-parboiled, long-grain parboiled and medium-grain non-parboiled rice at 60 °C.
increases as MC decreases, Qt is greatest at the end of drying and
consequently it was relevant to evaluate if the differences in energy requirements among rice types were significant at this MC level. In addition, a T of 60 °C was selected to compare energy
requirements among rice cultivars.
Table 4 shows Qt values predicted using Eq. (5), and the 95%
confidence intervals (CIs) obtained for each predicted Qt value for
the different rice types. The Qt predicted for medium-grain ‘‘Jupiter’’ was significantly greater than the other rice types since the
CI of ‘‘Jupiter’’ does not overlap with the other CIs; thus, the energy
required to remove a unit mass of water from medium-grain rough
rice with 12.5% MC at 60 °C is estimated to be significantly greater
than that required for the other rice types (Table 4). Long-grain
parboiled rice required significantly less energy to remove a unit
mass of water from rough rice with 12.5% MC at 60 °C than that required for non-parboiled rice. The Qt CIs of long-grains ‘‘Wells’’ and
‘‘Cybonnett’’ do overlap. This indicated that the difference in Qt between these two cultivars at 12.5% MC and 60 °C was not necessarily significant. While Qt values for long-grain ‘‘CLXL 730’’ were
significantly lower than those of long-grains Wells and ‘‘Cybonnet’’, the general level was similar among long-grains.
As the differences in Qt between ‘‘Wells’’ and ‘‘Cybonnett’’ were
not significant and as Qt of ‘‘CL XL730’’ was similar to those of
‘‘Wells’’ and ‘‘Cybonnett’’, one general model for long-grain,
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259
Fig. 7. Energy required to dry rice (QTrice) to 12.5% w.b. moisture content expressed on a per unit mass of water removed basis as a function of the initial moisture content of
the rice for long-grain non-parboiled rice.
non-parboiled rice was developed. The predicted range of Qt for
general, long-grain cultivars at 12.5% MC and 60 °C is shown in Table 4, while the RMSE for this general model is shown in Table 3.
It is noted that the term B2 was not significant when fitting the
general model. A possible explanation for this could be that the effect of cultivar on Qt was greater than that of T in affecting the
exponential term of Eq. (5). Therefore, when considering all the
cultivars separately, the B2 coefficient was significant but when
all long-grain cultivars were used to develop the general model,
the B2 coefficient was not significant.
3.2. Total heat of desorption results
The values of Qt and their corresponding SE for long-grain
‘‘Cybonnett’’ are shown in Table 2. The total heat of desorption increases exponentially as MC decreases for all rice types (Fig. 3).
There was a sharp increase in Qt for MCs below 15% and Qt approached hfg at MCs around 20%. The increase in Qt as MC decreases
indicates that water is increasingly bound to the rice matrix as MC
decreases. This is of interest to the rice industry as rice is dried
within the range in which Qt increases considerably. Qt varied for
long-grain ‘‘Wells’’ from 2371 to 3488, for long-grain ‘‘CL XL730’’
from 2371 to 3413, for medium-grain ‘‘Jupiter’’ from 2372 to
3624 and for parboiled rice from 2368 to 3194 kJ/kg water, for
MCs from 8% to 22% at 60 °C. Zuritz and Singh (1985) reported Qt
values for medium-grain rough rice from 2438 to 4015 kJ/kg water,
for MCs from 4.8% to 23%, at 40 °C.
Based on the trends shown in Fig. 3, parboiled rice requires less
energy to be dried than non-parboiled rice lots at MCs below 15%.
A possible explanation for this would be that during the parboiling
process, part of the hull typically cracks, reducing the resistance to
moisture transfer. Another possibility is that since starch gelatinizes during the parboiling process, the change in starch structure
could increase the diffusivity of the endosperm, producing less
resistance to moisture flow.
Fig. 3 also shows the general effect of kernel dimensions and
shape on the energy requirements to dry rice. Boyce (1965) referred to an unspecified study stating that kernels with similar
dimensions would have similar energy requirements. Fig. 3 shows
that the energy requirements for long-grain, pureline ‘‘Wells’’ and
for long-grain, hybrid CLXL730 are equivalent, reinforcing the
Boyce (1965) statement. Nevertheless, more cultivars should be
studied to confirm this hypothesis.
Another observation regarding kernel dimensions is shown in
Fig. 3 in that the energy requirements for drying the medium-grain
cultivar are slightly greater than that of the long-grains for MCs below 15%. Since medium-grain kernels are thicker, wider and shorter than long-grains, moisture has to migrate through a longer
pathway, producing an internal resistance that is greater in
medium-grain than long-grain rice. Therefore, the energy required
to remove water from medium-grain rice would be expected to be
greater than that of long-grain rice. Cnossen et al. (2002) found
that the effect of drying air conditions on the drying rate of a medium-grain cultivar was less significant than for a long-grain, presumably due to the fact that internal resistance to moisture
transport is greater in the first case. The Qt-results obtained for
medium-grain ‘‘Jupiter’’ at 45 °C in this study and those for a medium-grain rice at 40 °C reported by Zuritz and Singh (1985) are
shown in Fig. 2. The results are in general agreement, although a
slight difference exists at the lowest MC level reported by Zuritz
and Singh (1985).
3.3. Energy requirements to dry rice from an MCi to an MCf
Based on Eq. (7), mathematical expressions that predict the energy required to dry rice from an MCi to a desired MCf (QTrice) at a
given drying T were developed. These equations were developed
using the appropriate A1, A2, A3, B1 and B2 values from Table 3.
The resulting equations are shown in Table 5. Eq. (7) can be adjusted to predict energy requirements to dry rice from an MCi to
an MCf on a per unit mass of water removed basis by dividing by
the mass of water removed (Eq. (8)).
Fig. 4 shows the variation of QTrice (drying energy required per
unit mass wet rice and per unit dry matter) with MCi for longgrain, non-parboiled rice for three MCf levels at 60 °C. QTrice per
unit mass wet rice was obtained by dividing QTrice (Eq. (7)) by
the amount of wet rice corresponding to a unit mass dry matter
at the MCi. The trends indicated in Fig. 4 are practically linear.
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An explanation for this would be that the linear terms of the equations shown in Table 5, representing the energy required to vaporize free water, are considerably greater than the exponential terms
and therefore, the linear terms contribute considerably more to
QTrice. Nevertheless, in order to obtain accurate theoretical energy
requirements, including both terms in the equation is necessary
because as MC decreases, the contribution of Table 5 exponential
term becomes more important. For instance, the exponential term
is 4.2% of the QTrice value when drying from 22% to 12.5% MC at
60 °C but is 10.0% of QTrice when drying from 14% to 12.5% at
60 °C for long-grain, non-parboiled rice.
A conventional way of quantifying drying energy requirements
in the grains industry is to express energy requirements on a per
unit mass of water removed. Fig. 5 shows the energy required to
dry rice from an MCi to a desired MCf of 12.5%, 13.5% and 14.5%
on a per unit mass of water removed at 60 °C. QTrice decreased
exponentially as MCi increases, when expressed on a per unit mass
of water removed. In addition, QTrice increases as MCf decreases.
Both of these observations reflect the increasing importance of
Qn at the lower MC levels. Therefore, the energy required to remove a unit mass of water from rice should not be considered constant across MCi.
Fig. 6 shows that QTrice decreases exponentially as MCi increases
for the different rice types, when expressed on a per unit mass of
water removed. Further, Fig. 6 confirms the findings discussed in Table 4 in that medium-grain rice required more energy than longgrains and that non-parboiled rice requires more energy than parboiled rice, when expressed on a per unit mass of water removed.
The effect of temperature on energy requirements to dry rice
from MCi to 12.5% is shown in Fig. 7. The energy required to dry
rice from MCi to 12.5% decreases as drying T increases. For instance, the energy required to dry rice from 20% to 12.5% at 40 °C
was of 2517 kJ/kg water removed, at 60 °C was of 2467 kJ/kg water
removed and at 80 °C was of 2417 kJ/kg water removed (Fig. 7).
4. Conclusions
The net heat of desorption (Qn) and total heat of desorption (Qt)
decreased exponentially as MC increased for all types of rice in the
range of 10–90 °C and 8–22% MC. Mathematical models were
developed to predict the Qt (the amount of energy required to remove a unit mass of water from rice with a specific MC) for rough
rice of long-grains ‘‘Wells’’, ‘‘Cybonnett’’ and ‘‘CLXL730’’, mediumgrain ‘‘Jupiter’’ and long-grain, parboiled rice. The Qt of parboiled
rice at 12.5% MC and 60 °C was significantly less than that of
non-parboiled lots, and the net heat of desorption of medium-grain
rough rice was significantly greater than that of long-grains at
12.5% MC and 60 °C. Equations that predict the energy required
to dry a unit mass of rice from an MCi to a desired MCf at a given
T were obtained for long-grain non-parboiled, medium-grain
non-parboiled, and parboiled rice. The energy required to remove
a unit mass of water when drying from a given MCi to a desired
MCf decreased exponentially as MCi increased at a given T. These
equations provide a more accurate estimate of the energy required
to dry rice than the approach of simply using the latent heat of
vaporization when assessing energy efficiency of a drying process.
References
Anderson, R.B., 1946. Modifications of the B.E.T. equation. Journal of American
Chemical Society 68, 686–691.
Aviara, N.A., Ajibola, O.O., 2002. Thermodynamics of moisture sorption in melon
seed and cassava. Journal of Food Engineering 55, 107–113.
Aviara, N.A., Ajibola, O.O., Oni, S.A., 2004. Sorption equilibrium and thermodynamic
characteristics of soya bean. Biosystems Engineering 87 (2), 179–190.
ASAE, 1998. Standard D271.2 DEC94. Psychrometric Data, St. Joseph.
Basunia, M.A., Abe, T., 1999. Moisture adsorption isotherms of rough rice. Journal of
Food Engineering 42 (4), 235–242, MI, USA.
Boyce, D.S., 1965. Grain moisture and temperature changes with position and time
during through drying. Journal of Agricultural Engineering Research 10 (4),
333–341.
Cenkowski, S., Jayas, D.S., Hao, D., 1992. Latent heat of vaporization for selected
foods and crops. Canadian Agricultural Engineering 34, 281–286.
Chen, C., 2006. Obtaining the isosteric sorption heat directly by sorption isotherm
equations. Journal of Food Engineering 74 (2), 178–185.
Chung, D.S., Pfost, H.B., 1967. Adsorption and desorption of water vapor by cereal
grains and their products: Part 2. Development of the general isotherm
equation. Transactions of the ASAE 10, 549–555.
Cnossen, A.G., Siebenmorgen, T.J., Yang, W., 2002. The glass transition temperature
concept in rice drying and tempering: effect on drying rate. Transactions of the
ASAE 45 (3), 759–766.
De Boer, J.H., 1953. The Dynamical Character of Adsorption. Clarendon Press,
Oxford.
Fluck, R.C., Baird, C.D., 1980. Energy requirements for agricultural inputs. In:
Agricultural Energetics. AVI Publishing Company, Inc., Westport, Connecticut, p.
87.
Guggenheim, E.A., 1966. Application of Statistical Mechanics. Clarendon Press,
Oxford.
Gunasekaran, S., Thompson, T.L., 1986. Optimal energy management in grain
drying. Critical Reviews in Food Science and Nutrition 25 (1), 1.
Howell Jr., T.A., Cogburn, R.R., 2004. Rough-rice storage. In: Champagne, E.T. (Ed.),
Rice Chemistry and Technology, vol. 3. American Association of Cereal
Chemists, Inc., St. Paul, Minnesota, USA, p. 269.
Iglesias, H.A., Chirife, J., 1976. Isosteric heat of water vapour sorption on dehydrated
foods: Part 1. Analysis of the differential heat curves. Lebensmittel-Wissenchaft
& Technologie 9, 116.
Iguaz, A., Vírseda, P., 2007. Moisture desorption isotherms of rough rice at high
temperatures. Journal of Food Engineering 79 (3), 794–802.
Jayas, D.S., Mazza, G., 1993. Comparison of three-parameter equations for the
description of adsorption data of oats. Transactions of the ASAE 36, 119–
125.
Johnson, H.K., Dale, A.C., 1954. Heat required to vaporize moisture. Agricultural
Engineering 35, 705–714.
Kasmaprapruet, S., Paengjuntuek, W., Saikhwan, P., Phungrassami, H., 2009. Life
cycle assessment of milled rice production: case study in Thailand. European
Journal of Scientific Research 30 (2), 195–203.
Kechaou, N., Maalej, M., 1999. Desorption isotherms of imported banana.
Application of the GAB theory. Drying Technology 17 (6), 1201–1213.
McLaughlin, C.P., Magee, T.R.A., 1998. The determination of sorption isotherm and
the isosteric heats of sorption for potatoes. Journal of Food Engineering 35 (3),
267–280.
McMinn, W.A.M., Magee, T.R.A., 2003. Thermodynamic properties of moisture
sorption of potato. Journal of Food Engineering 60 (2), 157–165.
Mulet, A., García-Reverter, J., Sanjuán, R., Bon, J., 1999. Sorption isosteric heat
determination by thermal analysis and sorption isotherms. Journal of Food
Science 64 (1), 64–68.
Okos, M.R., Narsimhan, G., Singh, R.K., Weitnauer, A.C., 1992. Food Dehydration
Handbook of Food Engineering. Marcel Dekker, New York.
Ondier, G.O., Siebenmorgen, T.J., Mauromoustakos, A., 2010. Equilibrium moisture
contents of rough rice dried using high temperature, fluidized-bed conditions.
Transactions of the ASABE 53 (1), 1667–1672.
Ondier, G.O., Siebenmorgen, T.J., Bautista, R.C., Mauromoustakos, A., 2011.
Equilibrium moisture contents of pureline, hybrid and parboiled rice.
Transactions of ASABE 53 (3), 1007–1013.
Othmer, D.F., 1940. Correlating vapor pressure and latent heat data. Industrial and
Engineering Chemistry 32 (6), 841–856.
Perry, R.H., Chilton, C.H., 1973. Chemical Engineers’ Handbook, fifth ed. McGrawHill, Inc., USA.
Pfost, H.B., Maurer, S.G., Chung, D.S., Milliken, G.A., 1976. Summarizing and
reporting equilibrium moisture data for grains. ASAE Paper No. 76-3520, St.
Joseph, Michigan, USA.
Rizvi, S.S.H., 2005. Thermodynamic properties of foods in dehydration. In: Rao, M.A.,
Rizvi, S.S.H., Datta, A.K. (Eds.), Engineering Properties of Foods, third ed. CRC
Press, Boca Raton, FL, p. 239.
Siebenmorgen, T.J., Meullenet, J., 2004. Impact of drying, storage, and milling on rice
quality and functionality. In: Champagne, E.T. (Ed.), Rice Chemistry and
Technology, third ed. American Association of Cereal Chemists, St. Paul, MN,
p. 301.
Souza, C.M. Alves de, Tertuliano, P.C., Rafull, L.Z.L., Prat, M.I.H., Robaina, A.D., 2006.
Comparación de modelos matemáticos para descripción de las curvas de
entalpia de vaporización de agua de diferentes productos agrícolas. In:
Conferencia Científica de Ingenieria Agrícola de La Habana, 2006, Habana. 2ª
Conferencia Científica de Ingenieria Agrícola de La Habana, vol. 1, 2006, pp. 1–
14.
Thompson, T.L., Peart, R.M., Foster, G.H., 1968. Mathematical simulation of corn
drying. Transactions of the ASAE 24 (3), 582–586.
Tolaba, M.P., Peltzer, M., Enriquez, N., Pollio, M.L., 2004. Grain sorption equilibria of
quinoa grains. Journal of Food Engineering 6, 365–371.
Toğrul, H., Arslan, N., 2006. Moisture sorption behaviour and thermodynamic
characteristics of rice stored in a chamber under controlled humidity.
Biosystems Engineering 95 (2), 181–195.
Author's personal copy
M.A. Billiris et al. / Journal of Food Engineering 107 (2011) 253–261
Tsami, E., Maroulis, Z.B., Marinos-Kouris, D., Saravacos, G.D., 1990. Heat of sorption
of water in dried fruits. International Journal of Food Science and Technology
25, 350.
Truong, V., Bhandari, T.H., Howes, T., 2005. Optimization of co-current spray drying
process of sugar-rich foods: Part 1. Moisture and glass transition temperature
profile during drying. Journal of Food Engineering 71, 55–65.
261
Verma, L.R., 1994. New methods for on-the-farm rice drying: solar and biomass. In:
Wayne, E.M., Wadsworth, J.I. (Eds.), Rice Science and Technology. Marcel
Dekker, Inc., 270 Madison Avenue, New York, USA.
Zuritz, C.A., Singh, R.P., 1985. An equation to compute the heat of evaporation of
water for rough rice during drying. Drying Technology 3 (3), 421–435.