2011 International Conference on Alternative Energy in Developing Countries and Emerging Economies
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Fig. 1. Comparisons between experimental data and predict data from
equilibrium moisture content models.
0
10
20
30
40
0 20 40 60 80 100
Relative humidity (%)
Equilibrium moisture content
(% dry-basis)
Experimental data
Halsey's model
BET's model
Oswin's model
Henderson's model
GAB's model
The whiteness of milled rice samples was measured
with a commercial whiteness meter (Model C-300, Kett
Electronic Co., Japan). This meter measures the
whiteness of rice kernels as whiteness (W) in the linear
range of 0 to 100, where 0 corresponds to perfect black
surface and the 100 corresponds to the whiteness of the
magnesium oxide fumes. The equipment was calibrated
with a ceramic plate having whiteness value of 85.8
provided by equipment.
4. Cooking time
Cooking time is duration time to partial starch
gelatinize of 90% of the total starch kernels based on
visual observation. Ten grams of mature rice kernel were
boiled in 250 ml of distilled water; after 20 min of
cooking, 10 grains were removed from water and placed
over a Petri dish and compressed with a spatula in order
to visualize and count the grains that no longer had the
opaque core (fully gelatinized kernels). The same
procedure was repeated every minute until all the 10
kernels reached the complete gelatinization for two
successive cooking times.
5. Physicochemical property
The rice kernel samples were used for determination
of physicochemical properties, namely, gel consistency
(GC), alkali spreading value (AS) and water absorption.
Gel consistency and alkali spreading value were
determined following methodologies suggested by
Cagampang
et al.
, 1973 [4], and Little
et al.
, 1958 [11],
respectively. Water absorption was determined by
Juliano, 1971 [10].
6. Chemical property
Amylose content (AMC) was determined by iodine
colorimetric method as recommended by Juliano, 1971
[10]. Protein content (PC) was determined by Micro
Kjeldahl apparatus. Lipid content (LC) was determined
by AOAC, 1996 [1].
F. Thermal property
The thermal properties of rice flour were determined
with differential scanning calorimeter (DSC) Model 821
(Mettler-Toledo Ltd., Australia). Rice flour (3.5 mg) was
weighed into an aluminum pan and distilled water was
added using a micro syringe to give 70% of total mass.
The sealed sample was equilibrated for 1 h and then
heated from 25 to 120 °C at a heating rate of 10 °C/min
to determine the gelatinization enthalpy and temperatures.
G. Morphological study
The structure of dried parboiled rice kernels
characterized with a field emission scanning electron
microscope SEM-Quanta. Before scanning, the samples
were cut in cross section. Then, the samples were glued
on the metal cylinder stubs for the stable supporting and
were coated with gold (~30 nm thick) with plasma
sputtering to become the electrical conductor for electron
attachment during scanning.
H. Texture property of cooked rice
Hardness, stickiness and adhesiveness value of
cooked parboiled rice was determined by a bench-top
texture analyzer model TA-XT
2i
(Stable Micro Systems
Ltd., USA). A 30 g portion of each milled head rice
sample was place in an aluminum cylindrical cup. The
sample was cooked with distilled water at rice-to-water
weight ratios of 1:2. The compression probe was set at
the pretest speed, test speed and post speed of probe were
1.5, 0.5 and 10 mm/s, respectively. The maximum force
required for compressing cooked rice to 90% of the initial
height of 20 mm was indicated as the hardness of cooked
rice. The hardness value was represented by mean of five
replications and was also expressed in kg.
I. Specific energy consumption (SEM)
Specific energy consumption was defined as the
energy required for removing a unit mass of water in
drying the parboiled rice from its initial moisture content
of 54±1%d.b. to the final moisture content of 16%d.b.
The specific energy consumption was calculated as
follows:
d W)fM- in (M
3.6P
SEC
(2)
All experimental results were shown in average
value by using one-way ANOVA (p 0.05) while the
model suitability was judged by the highest value of
coefficient of determination value(R
2
) and the lowest root
mean square error value (RMSE), which was defined as
follows:
RMSE =
N
1
(∑(X
predicted,i
-X
observed,i
)
2
)
1/2
(3)
IV. RESULT AND DISCUSSIONS
A. Equilibrium moisture content and mathematic
modeling
Comparisons of equilibrium moisture content data
with the experimental data are shown in Fig. 1. Results
showed that for the temperature ranges of 40 to 60
q
C and
relative humidity from 11 to 87%, GAB’s model yielded
