Dehydration kinetics of onion slices in osmotic and air convective drying process

Abstract

The effect of different pretreatments (i.e. osmotic dehydration in 10, 15 and 20ºBrix NaCl solution and drying air temperature (50, 60 and 70 ºC) on drying behaviour of onion slices were investigated. The onion slices were dried in a laboratory model tray dryer. Drying of onion slices occurred in falling rate period. Five thin-layer drying models (Exponential, Page, Henderson and Pabis, Logarithmic and Power law) were fitted to the moisture ratio data. Among the drying models investigated, the Page model satisfactory described the drying behavior of onion slices. The effective moisture diffusivity of pre-treated samples was higher than the non-treated samples.

Full text

92
Dehydration kinetics of onion slices in osmotic
and air convective drying process
V.A. R1, P.S. P2, P.B. P3, G.P. S1
1Department of Processing & Food Engineering, Maharana Pratap University
of Agriculture and Technology, Udaipur, India
2Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola, India
3Department of Process & Chemical Engineering, University College Cork, Ireland
Abstract
R V.A., P P.S., P P.B., S G.P., 2014. Dehydration kinetics of onion slices in osmotic
and air convective drying process. Res. Agr. Eng., 60: 92–99.
e effect of different pre-treatments (i.e. osmotic dehydration in 10, 15 and 20°Brix NaCl solution and drying air
temperature of 50, 60 and 70°C) on drying behaviour of onion slices were investigated. e onion slices were dried in
a laboratory model tray dryer. Drying of onion slices occurred in falling rate period. Five thin-layer drying models (Ex-
ponential, Page, Henderson and Pabis, Logarithmic and Power law) were fitted to the moisture ratio data. Among the
drying models investigated, the Page model satisfactorily described the drying behaviour of onion slices. e effective
moisture diffusivity of pre-treated samples was higher than that of non-treated samples.
Keywords: onion; drying; mathematical models; diffusivity; osmotic dehydration
Onion (Allium cepa), a very commonly used veg-
etable, ranks third in the world production of major
vegetables (M et al. 2012). In the manufacture
of processed foods such as soups, sauces, salad
dressings, sausage and meat products, packet food
and many other convenience foods, dehydrated
onion is normally used as flavour additive, being
preferred to the fresh product, because it has bet-
ter storage properties and is easy to use (R,
D 1995; K-E, G 2005).
Onion is an important vegetable to serve as ingre-
dients in dishes, as toppings on burgers, in season-
ings, as chip coatings etc. (S et al. 2005a).
Conventional air-drying is a simultaneous heat
and mass transfer process, accompanied by phase
change (B et al. 1994) being a high cost
process. However, water removal using high tem-
peratures and long drying times may cause seri-
ous decreases in nutritive and sensorial values,
damaging mainly the flavour, colour and nutrients
of dried products (L 1996; L et al. 1998).
Osmotic dehydration was used as pre-treatment
to reduce air drying time and improve the product
quality (T 1993; J, G
1995; K et al. 1995; S et al. 2001;
R et al. 2007). Other advantages include
limited heat damage, improved textural quality, vi-
tamin retention, flavour enhancement and colour
stabilization (A-O et al. 2003).
Osmotic dehydration is the most reported pre-
treatment used prior to air-drying (L et al.
2008; M et al. 2010). It removes water from
the fruit or vegetable up to a certain level, which
is still high for food preservation so that this pro-
cess must be followed by another process in order
to lower even more the fruit water content. It is a
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93
useful technique that involves the immersion of the
fruit in a hypertonic aqueous solution leading to the
loss of water through the cell wall membranes of the
fruit and subsequent flow along the inter-cellular
space before diffusing into the solution (S et
al. 2001). As a partial dehydration process, osmosis
may be regarded as a simultaneous water and sol-
ute diffusion operation, wherein the sample incurs
a gain of solids and a simultaneous loss of moisture
(MM, M 1999b). e shelf life quality of
the final product is better than without such treat-
ment due to the increase in sugar/acid ratio, the im-
provement in texture and the stability of the colour
pigment during storage (L et al. 2008).
Osmotic dehydration combined with drying tech-
nologies provides an opportunity to produce novel
shelf stable types of high quality product. e dry-
ing kinetics of food is a complex phenomenon and
requires simple representations to predict the dry-
ing behaviour, and to optimize the drying param-
eters. Recently, studies were done on drying kinetics
of fruits and vegetables (T, P 2002;
D 2004; J, P 2004; A, B
2005; S et al. 2005a; G et al. 2006; M-
 et al. 2010). However, very limited studies
were found in the literature which relate to the influ-
ence of pre-treatments, i.e. osmotic dehydration, on
drying kinetics of onion. e objective of this study
was (i) to investigate the influence of pre-treatments
and drying air temperature on the drying behaviour
of onion, (ii) to evaluate a suitable thin-layer drying
model for describing the drying process, and (iii) to
calculate the effective moisture diffusivity.
MATERIALS AND METHODS
Raw material. e fresh white onion bulbs (cv.
V-12) were used in the present study. e white
onion bulbs were stored in storage chamber main-
tained at a temperature of 4 ± 1°C and 70% air rela-
tive humidity until experiments were completed.
Onions were taken from the storage and were al-
lowed to equilibrate with ambient conditions for
about 2 h followed by hand peeling. e peeled
onions were cut into circular slices of thickness
equal to 4 ± 0.1 mm using a manual stainless steel
cutter. A sample size of about 200 g was used in
each drying experiment. Initial moisture content of
each sample was determined using the oven dry-
ing method which ranged between 4.56 and 5.45 g
H2O/g dry matter (DM).
Osmotic dehydration. e onion slices were par-
tially dehydrated using osmotic drying technique.
e slices were placed in different containers hold-
ing 10, 15 and 20°Brix of NaCl solution at ambi-
ent temperature (30°C) for 1 h; and stirring of the
solution was done at regular intervals of 15 min-
utes. Solution to sample ratio was kept as 2.5:1 in
each experiment. After a period of 1 h, slices were
removed quickly and blotted gently using a tissue
paper to remove the surface moisture.
Hot air drying. Samples non-treated and pre-
treated in osmotic solution (10, 15 and 20°Brix NaCl
solution) were dried in a laboratory tray dryer. e
dryer consisted of a drying chamber, electric heat-
er, fan and a temperature controller. Experiments
were conducted at 50, 60 and 70°C air tempera-
ture and at a constant airflow velocity of 1.5 m/s.
Slices of raw onion samples were uniformly spread
in each trays and kept in dryer. Moisture loss was
recorded in 5 min interval for an hour, then the
weighing interval was increased to 10 min for next
one hour; further readings were taken at 15min in-
terval by a digital balance of 0.01 g accuracy. e
drying continued till the final moisture content of
about 0.07 g water per g dry matter was reached
in the dried product. Experiments were replicated
three times. In total, 12 treatments combination as
described in Table 1 were conducted.
Mathematical modelling. Mathematical model-
ling is essential to predict and simulate the drying
behaviour. It is also an important tool in dryer’s
design, contributing to a better understanding of
the drying mechanism. To select a suitable model
for describing the drying process of onion slices,
drying curves were fitted with five thin-layer dry-
ing equations (Eqs 1–5), (T, P 2002;
D 2004; A, B 2005).
Exponential MR = exp(–kt) (1)
Page MR = exp(–ktn) (2)
Henderson-Pabis MR = aexp(–kt) (3)
Logarithmic MR = a + bln(t) (4)
Power law MR = AtB (5)
where:
MR – moisture ratio (–)
t – time (s)
k, a, b, A – coefficients specific to each model
n, B – exponent specific to each model
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94
e acceptability of the model was determined
by the coefficient of determination R². In addition
to the coefficient of determination, the goodness
of fit was determined by various statistical param-
eters such as reduced mean square of the deviation
χ², mean bias error EMB and root mean square er-
ror ERMS. For quality fit, R² value should be higher,
close to one, and χ², EMB and ERMS values should be
lower (S et al. 1999; T, P
2002; Dr et al. 2004; E et al. 2004).
Moisture diffusivity. In drying, diffusivity is used
to indicate the flow of moisture out of material. In
falling rate period of drying, moisture transfer
within the food is mainly by molecular diffusion.
Moisture diffusivity is influenced by shrinkage,
case hardening during drying, moisture content
and temperature of material. e falling rate pe-
riod of biological materials is best described by
Fick’s second law of diffusion (C 1975). Uni-
form initial moisture distribution throughout the
sample, negligible external resistance to movement
and onion slices releasing the moisture from top as
well as from bottom surface are assumed. e solu-
tion of the above mentioned equation as proposed
by C (1975) for plane sheet of half thickness
(S et al. 2005b) is:
M−Me
M
0
−M
e
=8
π2∑
n=1
∞
1
(2n−1)2exp −(2n−1)2π2Dt
L2
⎡
⎣
⎢⎤
⎦
⎥ (6)
Simplifying this by considering only first term of
the series, the equation reduced to:
MR =M−Me
M0−M
=8
π2exp −π2Dt
L2
⎡
⎣
⎢⎤
⎦
⎥ (7)
where:
MR – moisture ratio (–)
Me – equilibrium moisture content (g H2O/g DM)
M0 – initial moisture content (g H2O/g DM)
M – moisture content at time t (g H2O/g DM)
L – half thickness of slab (0.002 m)
t – time (s)
D – diffusivity coefficient (m2/s)
Rearranging the above mentioned Eq. (7):
ln(MR) =ln 8
π2
⎛
⎝
⎜⎞
⎠
⎟− π2Dt
L
2
⎛
⎝
⎜⎞
⎠
⎟ (8)
e ln(MR) versus drying time (t) was plotted
which would result in straight line and slope of the
line would be used to estimate moisture diffusivity
during the drying process.
RESULTS AND DISCUSSION
Effect of pre-treatments
on drying behaviour of onion slices
Final moisture content of samples dried under
different conditions ranged from 5 to 7% dry basis
(d.b.). e effect of treatment and drying tempera-
ture on time taken to reach the final moisture con-
Table 1. Drying time and effective moisture diffusivity for onion slices
Treatment
No.
Temperature (°C) NaCl concentra-
tion (°Bx)
Drying time
(min)
Diffusivity
(m²/s) R2
osmotic solution drying
1 – 50 –390 0.78 × 10–10 0.8827
2 – 60 –360 0.87 × 10–10 0.9325
3 – 70 –315 1.21 × 10–10 0.9626
430 50 10 280 0.83 × 10–10 0.9662
530 50 15 270 0.86 × 10–10 0.838
630 50 20 255 0.91 × 10–10 0.9374
730 60 10 265 0.98 × 10–10 0.9556
830 60 15 255 0.92 × 10–10 0.9576
930 60 20 220 1.09 × 10–10 0.894
10 30 70 10 250 0.98 × 10–10 0.9299
11 30 70 15 240 1.14 × 10–10 0.9265
12 30 70 20 210 1.30 × 10–10 0.894
R2 – coefficient of determination
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95
tent is presented in Table 1. Drying air temperature
has an important effect on drying. At higher tem-
perature, due to the quick removal of moisture, the
drying time was shorter. Similar observations were
reported for drying of garlic slices (M et
al. 1996), onion slices (S et al. 1999),
and egg plants (A, B 2005). In case of
onion slices pre-treated with osmotic solution, dry-
ing time at all air drying temperatures decreased
with the increase in the concentration of NaCl in
osmotic solution. e reason of it is that the treat-
ment with the higher NaCl concentration resulted
into removal of substantial amount of moisture
from the onion slices.
Fig. 1 shows the experimental data (moisture ra-
tio versus drying time) obtained for air at tempera-
tures ranging from 50 to 70°C, and a constant flow
rate of 1.5 m/s. As it would be expected, during the
initial stages of drying there was a rapid moisture
removal from the product, which later decreased
with an increase in drying time. From these figures
it can be seen that the moisture ratio decreases
continually with drying time. As expected, drying
air temperatures had much stronger effect on the
drying moisture content of onion. e temperature
influence was higher at 70°C air temperature. e
absence of a constant drying rate period may be
due to the thin layer of product that did not pro-
vide a constant supply of water for an applied pe-
riod of time. Continuous decrease in moisture ratio
indicates that diffusion has governed the internal
mass transfer. is is in agreement with the results
of study on onions (M, L 1980), let-
tuce and cauliflower leaves (L et al. 2000) and
figs (P et al. 2004). Onion slices did not exhibit a
constant rate period of drying. e drying occurred
Fig. 1. Effect of pre-treatments
on drying time at different drying
air temperature (a) 50°C, (b) 60°C
and (c) 70°C
0.0
0.2
0.4
0.6
0.8
1.0
0 50 100 150 200 250 300 350 400 450
Moisture ratio
Drying time (min)
Non-treated
10%
15%
20%
0.0
0.2
0.4
0.6
0.8
1.0
0 50 100 150 200 250 300 350 400
Moisture ratio
Drying time (min)
0.0
0.2
0.4
0.6
0.8
1.0
0 50 100 150 200 250 300 350
Moisture ratio
Drying time (min)
(a)
(b)
(c)
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96
Table 2. Values of model constants and statistical param-
eters
Treat-
ment No.
Statistical parameters
R2χ² × 10–3 EMB × 10–3 ERMS
Exponential model
10.8827 0.02184 0.02125 0.01458
20.9325 0.00824 0.00800 0.00894
30.9626 0.01518 0.01469 0.01212
40.9662 0.02580 0.02485 0.01576
50.838 0.07616 0.07353 0.02712
60.9374 0.01661 0.01604 0.01267
70.9501 0.04556 0.04381 0.02093
80.9528 0.01565 0.01509 0.01229
90.8031 0.07184 0.06918 0.02630
10 0.9259 0.04012 0.03845 0.01961
11 0.9211 0.01735 0.01666 0.01291
12 0.8882 0.03769 0.03612 0.01901
Page model
10.9825 0.00338 0.00319 0.00565
20.9897 0.00465 0.00438 0.00662
30.9939 0.00494 0.00462 0.00679
40.9936 0.00558 0.00517 0.00719
50.9869 0.00356 0.00330 0.00575
60.9892 0.00686 0.00637 0.00798
70.9928 0.00651 0.00601 0.00775
80.9915 0.00633 0.00588 0.00767
90.9798 0.00619 0.00573 0.00757
10 0.9902 0.00824 0.00756 0.00869
11 0.9899 0.00894 0.00823 0.00907
12 0.9879 0.01026 0.00941 0.00970
Henderson & Pabis model
10.8827 0.05813 0.05499 0.02345
20.9325 0.01252 0.01179 0.01086
30.9626 0.01936 0.01811 0.01346
40.9609 0.05808 0.05378 0.02319
50.8294 0.01719 0.16003 0.04000
60.9305 0.06567 0.06114 0.02473
70.9501 0.02512 0.02318 0.01523
Treat-
ment No.
Statistical parameters
R2χ² × 10–3 EMB × 10–3 ERMS
80.9528 0.00956 0.00888 0.00942
90.8031 0.09337 0.08646 0.02940
10 0.9259 0.05999 0.05499 0.02345
11 0.9804 0.00558 0.00514 0.00717
12 0.8882 0.07930 0.07269 0.02696
Logarithmic model
10.968 0.04626 0.04376 0.02092
20.9642 0.05590 0.05262 0.02294
30.9655 0.06857 0.06415 0.02533
40.9588 0.01554 0.01439 0.01200
50.9355 0.02458 0.02288 0.01513
60.9761 0.00831 0.00774 0.00880
70.9514 0.01871 0.01727 0.01314
80.9699 0.01044 0.00970 0.00985
90.9668 0.01233 0.01141 0.01068
10 0.9577 0.01770 0.01623 0.01274
11 0.971 0.01149 0.01057 0.01028
12 0.9747 0.01072 0.00982 0.00991
Power law model
10.6009 24.2081 22.8996 0.15133
20.6806 9.44003 8.88473 0.09425
30.707 15.3818 14.3894 0.11996
40.6949 12.2613 11.3530 0.10655
50.5502 22.0841 20.5610 0.14339
60.668 19.3163 17.9841 0.13410
70.6843 9.28092 8.56700 0.09256
80.7115 8.58460 7.97141 0.08928
90.5387 23.9666 22.1913 0.14897
10 0.6455 14.9387 13.6938 0.11702
11 0.6619 14.2182 13.0808 0.11437
12 0.6179 27.7766 25.4619 0.15957
R2 – coefficient of determination; χ² – reduced mean square
of the deviation; EMB – mean bias error; ERMS – root mean
square error
Table 2 to be continued
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97
under falling rate of drying period. Similar results
were also reported for the drying studies on plum
(I et al. 2008) and apricots (D 2004).
Mathematical modelling of drying curves
e moisture ratio data of pre-treated and non-
treated onion slices dried at various temperatures
were fitted into the different thin-layer drying
models listed above section and the values of (R2),
χ², EMB and ERMS, are summarized in Table 2.
It was observed that in all cases, the values of R²
were greater than 0.90, indicating a good fit (M-
 et al. 1996; E et al. 2004) except
for power law model. However, the Page model
gave comparatively higher R² values in all the dry-
ing treatments (0.9825–0.9939) and also the χ²
(0.0033–0.01026 × 10–3), EMB (0.00319–0.00941 ×
10–3) and ERMS (0.00565–0.00970) values were
lower. Hence, the Page model may be assumed to
represent the thin-layer drying behaviour of onion
slices. D et al. (2004) and G et al. (2006)
reported a similar result for air-drying of bay leaves
and raw mango slices, respectively.
Fig. 2 suggests the experimental moisture ratios
fitted with the page model at various air tempera-
tures for onion samples, also Fig. 3 shows a com-
parison between both observed and predicted
moisture values obtained using the Page model,
which gave the best fit for the entire onion drying
process. is means that the model has very high
performance for describing the characteristics of
drying curves.
Effective moisture diffusivity
e effective moisture diffusivity, Deff, was cal-
culated using the slopes method (D 2004;
P, S 2006) and its results are given
in Table 1. e moisture diffusivity value of food
material was affected by moisture content as well as
temperature. At lower level of moisture content the
diffusivity is less than that of high moisture con-
tent. Also it was observed that moisture diffusivity
increased with drying air temperature in both non-
treated and pre-treated samples (R, L
1991; P, P 1998). e moisture
diffusivity varied in the range of 0.78 to 1.21 × 10–10
m²/s and 0.83 to 1.30 × 10–10 m²/s for non-treated
and pre-treated onion samples depending on the
drying air temperature, respectively. ese values
are within the general range of 10–8 to 10–12m²/s
Fig. 3. Comparison of observed and
predicted dimensionless moisture
ratio values by Page model
Fig. 2. Experimental moisture ratio
versus drying time fitted with the
Page model at drying air tempera-
ture of 60°C
0.0
0.2
0.4
0.6
0.8
1.0
0 50 100 150 200 250 300 350 400
Moisture ratio
Drying time (min)
Non-treated
10°Bx
15°Bx
20°Bx
Page model
0.0
0.2
0.4
0.6
0.8
1.0
1.2
0.0 0.2 0.4 0.6 0.8 1.0 1.2
Predicted moisture ratio
Observed moisture ratio
Page model
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98
for drying of food materials (MM, M
1999a). e pre-treatment affected the internal
mass transfer during drying. Table 1 also indi-
cates that the effective moisture diffusivity during
convective dehydration of osmosed samples was
higher than untreated samples. Effective moisture
diffusivity with osmotic pre-treatment can increase
due to loosening of the surface cellular structure
and leaching of some soluble components of the
external cell layers of onion slices during soaking in
osmotic solution. Similar results were reported in
apricot cubes (R et al. 2005), in melons (R-
, F 2007) and in pomegranate arils
(M et al. 2010).
CONCLUSIONS
e effect of temperature and pre-treatment
on drying behaviour of onion slices in tray dryer
was investigated in this study. An increase in dry-
ing air temperature decreased drying time. Pre-
treated onion slices have shorter drying time than
the untreated samples. e entire drying process
occurred in falling rate period and constant rate
period was not observed. Five thin-layer drying
equations were investigated for their suitability to
describe the drying behaviour of onion slices. e
Page model shows the best fit with high values for
the coefficient of determination and low χ², EMB
and ERMS values. e effective moisture diffusivity
varied in the range of 0.78 to 1.21 × 10–10 m²/s and
0.83 to 1.30 × 10–10 m²/s for non-treated and pre-
treated onion samples depending on the drying air
temperature, respectively.
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Received for publication May 1, 2012
Accepted after corrections October 2, 2012
Corresponding author:
Dr. P B. P, Stellenbosch University, Faculty of AgriSciences, South African
Research Chair in Postharvest Technology, South Africa 7602
phone: + 27 21808 9280, e-mail: pbpathare@yahoo.co.in
Res. Agr. Eng. Vol. 60, 2014, No. 3: 92–99