influence of pretreatments on the dehydration characteristics during vacuum drying of water dropwort...

INFLUENCE OF PRETREATMENTS ON THE DEHYDRATIONCHARACTERISTICS DURING VACUUM DRYING OF WATER

DROPWORT (OENANTHE JAVANICA DC.)

JUN HO LEE1 and HYE-RAN KIM

Department of Food Science and EngineeringDaegu University

Gyeongsan, Gyeongbuk 712-714, Korea

Accepted for Publication August 6, 2008

ABSTRACT

The thin-layer drying behavior of water dropwort in a laboratory scalevacuum dryer was examined. Two pretreatments (blanching and 1% KMSdipping) were applied to the water dropwort, which were dried in the rangesof 50–70C of drying air temperature. The drying air temperature and pretreat-ment had significant effects on the moisture content of the water dropwortsamples. In all the drying temperature selected, the blanched samples hadshorter drying time than the control and 1% KMS treated samples. The dryingrate decreases continuously with decreasing moisture content or increasingdrying time. The models were compared based on the coefficient of determi-nation, reduced chi-square and root mean square error between the observedand predicted moisture ratios. The Page model has shown a better fit to theexperimental drying data as compared to other models. The color character-istics of dried water dropwort were also significantly influenced by thepretreatments.

PRACTICAL APPLICATIONS

The information on the drying characteristics of water dropwort as influ-enced by pretreatments may provide a practical method for the preservation ofwater dropwort and improvement on the quality of dried products. The experi-mental data are necessary to design, optimize, and control the drying processin the production of dehydrated water dropwort products.

1 Corresponding author. TEL: +82-53-850-6535; FAX: +82-53-850-6539; EMAIL: [email protected]

Journal of Food Processing and Preservation 34 (2010) 397–413.DOI: 10.1111/j.1745-4549.2008.00319.x 397© 2009 The Author(s)Journal compilation © 2009 Wiley Periodicals, Inc.

INTRODUCTION

Water dropwort (Oenanthe javanica DC.) is a perennial herb with adistinctive taste and aroma (Jeon et al. 2007), and grows wild in freshwatermarshes, swampy fields and canals in Asia and Australia (Jung et al. 2002). Itis a member of the Umbelliferae family and is a very important commercialcrop, the stems and leaves often used as a garnish in soups and stews in Korea(Jeon et al. 2007).

Drying is a common method used to preserve food stuffs. In comparisonwith a conventional atmospheric drying, vacuum drying allows for the removalof moisture under low pressure (Jaya and Das 2003). Vacuum expands air andwater vapor present in the food and creates a frothy or puffed structure,providing a large area-to-volume ratio for enhanced heat and mass transfer(Jaya and Das 2003). Consequently, with vacuum drying it is possible to havea higher drying rate, lower drying temperature and an oxygen-deficient pro-cessing environment (Wu et al. 2007).

Knowledge of the drying characteristics of the water dropwort isrequired to design, optimize and control the drying process. It is also nec-essary to evaluate the practicability of vacuum drying for improving thequality of the dried water dropwort. Although several studies have beencarried out to investigate vacuum-drying characteristics of various foodmaterials (Jaya and Das 2003; Cui et al. 2004; Methakhup et al. 2005;Arevalo-Pinedo and Murr 2006, 2007; Wu et al. 2007), no data on thevacuum-drying behavior of water dropwort are available for the engineeringdesign of drying.

The objectives of this experiment are to determine the effect of dryingtemperature and pretreatments on drying characteristics of water dropwort; toevaluate a suitable drying model for describing the drying process and toevaluate the surface color of dried samples.

MATERIALS AND METHODS

Materials

Freshwater dropwort was purchased from the local market and stored at4C before use. Prior to dehydration, the dropwort was thoroughly washed withtap water and cut into a length of about 60 mm. Samples were then subject tosalad spinner (WD23-210, Myeongmoon LC Corp., Gyeonggi, Korea) for3 min to remove excessive surface moisture. The initial moisture content of thewater dropwort samples was determined by vacuum drying at 70C for 24 h(AOAC 1995) and it ranged from 19.45–21.97 (d.b.).

398 J.H. LEE and H.-R. KIM

Drying Experiments

The control (untreated), blanched (80C for 2 min), and immersed in 1%potassium meta bisulphate (KMS) solution for 3 min water dropwort sampleswere used to conduct the drying experiments at 50, 60, and 70C in a vacuumdryer (VOS-301SD, Tokyo Rikakikai Co., Japan). Samples (ca. 20 g) wereuniformly spread in a single layer on the aluminum tray and placed in the dryerwhere the absolute pressure was set at 0.1 mPa. Moisture losses of sampleswere recorded at 30 min intervals by a digital balance of 0.01 g accuracy. Thedrying was continued until the dry product obtained an equilibrium conditionwith the atmosphere inside the drying chamber when the three consecutivereadings were not appreciably different. The moisture content at that time wasconsidered as the equilibrium moisture content. Each experiment was repli-cated three times and the average values were used for analyses.

Mathematical Modeling

The moisture ratio (MR) and the drying rate of samples during thethin-layer drying experiments were calculated by the following equations(Shafafi Zenoozian et al. 2008):

MRM M

M Me

o e

=−−

(1)

Drying rateM M

dtt dt t=

−+ (2)

where M, Mo, Me, Mt and Mt+dt are the moisture content at any time, initialmoisture content, equilibrium moisture content, moisture content at t andmoisture content at t + dt (kg water/kg dry matter), respectively, t is the dryingtime (min).

Nine well-known thin-layer drying models in Table 1 were tested toselect the best model for describing the drying curve of the water dropwortsamples. Nonlinear least square regression analysis was performed usingLevenberg-Marquardt procedure in SigmaPlot computer program. The coeffi-cient of determination (R2) was the primary criterion for selecting the bestmodel to describe the drying curve. In addition, root mean square error(RMSE) and the reduced chi-square (c2) were used to determine the goodnessof fit. These parameters can be calculated as follows:

RMSEN

MR MRpre i ii

N= −( )⎡

⎣⎢⎤⎦⎥=∑1

1

2 1 2

, exp, (3)

399VACUUM DRYING CHARACTERISTICS OF WATER DROPWORT

χ2 1

2

=−( )

−=∑ MR MR

N zpre i ii

N

, exp, (4)

where MRexp,i is the ith experimentally observed moisture ratio, MRpre,i the ithpredicted moisture ratio, N the number of observations, and z is the number ofconstant in the model. The model was considered best when RMSE and c2

were at a minimum value and R2 at a maximum value.

Color Measurement

The surface color of dried water dropwort samples were determined interms of the Commission Internationale de I’Eclairage (CIE) color character-istics (L*, a* and b*), using a Chromameter (model CR-200, Minolta Co.,Osaka, Japan) calibrated with a calibration plate using Y = 94.2, x = 0.3131and y = 0.3201. The Chromameter used xenon pulse-diffused illumination(D65 illuminant) with three response detectors set at 0° viewing angle. Inaddition, the machine was preset to use the 2° observer. The measurements ofcolor were replicated 10 times at the center location and the average andstandard deviation values were reported. Duncan’s multiple range tests(P = 0.05) were performed to determine any significant difference amongvarious treatments (SAS 1985). The total color change (DE*) was calculated asfollows (Ren et al. 2006):

Δ Δ Δ ΔE L a b* = ( ) + ( ) + ( )⎡⎣ ⎤⎦* * *2 2 2 1 2(5)

TABLE 1.THIN-LAYER DRYING MODELS USED FOR MATHEMATICAL MODELING OF VACUUM

DRYING OF WATER DROPWORT

No. Model name Model Reference

1 Newton MR = exp(-kt) O’Callaghan et al. 19712 Page MR = exp(-ktn) Page 19493 Modified page MR = exp((-kt)n) Overhults et al. 19734 Henderson and Pabis MR = a exp(-kt) Henderson and Pabis

19615 Logarithmic MR = a exp(-kt) + c Yagcioglu et al. 19996 Two term MR = a exp(-kt) + b exp(-k0t) Henderson 19747 Two-term exponential MR = a exp(-kt) + (1-a) exp(-kat) Sharaf-Eldeen et al. 19808 Approximation of

diffusionMR = a exp(-kt) + (1-a) exp(-kbt) Sharaf-Eldeen et al. 1979

9 Modified Hendersonand Pabis

MR = a exp(-kt) + b exp(-gt) + c exp(-ht) Karathanos 1999

MR, moisture ratio.


Where DL* = L*0 - L*, Da* = a*0 - a*, Db* = b*0 - b*. The L*, a* and b*values correspond to the values of water dropwort samples at different dryingconditions, whereas the values of L*0, a*0 and b*0 are related to the fresh waterdropwort.

RESULTS AND DISCUSSION

Drying Behavior of Water Dropwort

Figure 1 presents the variations in the moisture content as a function ofthe drying time at various drying temperature for the samples with differentpretreatments. It can be seen that moisture content decreases continually with

Time (min)0 100 200 300 400 500 600

Moi

stu

re c

onte

nt (

%, w

.b.)

0

20

40

60

80

100

50C60C70C

Time (min)0 100 200 300 400 500 600

Moi

stu

re c

onte

nt (

%, w

.b.)

0

20

40

60

80

100

50C60C70C

Time (min)0 100 200 300 400 500 600 700

Moi

stu

re c

onte

nt (

%, w

.b.)

0

20

40

60

80

100

50C60C70C

a

c

b

FIG. 1. EFFECT OF DRYING AIR TEMPERATURE ON MOISTURE CONTENT(A) Control, (B) blanched, and (C) 1% KMS treated samples, respectively.


drying time. The drying air temperature and pretreatment had significanteffects on the moisture content of the water dropwort samples. The increase inthe drying air temperature resulted in a decrease in the drying time. The dryingtimes required to reach same final moisture content of 0.4% (d.b.) for thecontrol were 420, 270 and 240 min at the drying air temperatures of 50, 60 and70C, respectively. Corresponding values for the blanched and 1% KMS treatedsamples were 270, 210 and 120 min and 570, 420 and 360 min, respectively atthe same respective temperature. The decrease in drying time with an increasein the drying air temperature have been reported for many food stuffs such asapricot (Togrul and Pehlivan 2003), eggplant (Ertekin and Yaldiz 2004; Wuet al. 2007), olive cake (Akgun and Doymaz 2005), apple pomace (Wang et al.2007), pumpkin slices (Doymaz 2007), red chillies (Kaleemullah and Kailap-pan 2005) and onion slices (Sarsavadia et al. 1999; Jain and Pathare 2004;Sharma et al. 2005; Kumar et al. 2006).

In all the drying temperature selected, the blanched samples had shorterdrying time than the control and 1% KMS treated samples. Similar observa-tions on the reduction of drying time by blanching have been reported byothers (Doymaz and Pala 2002; Doymaz 2004; Goyal et al. 2007). However, itis interesting to note that 1% KMS treatment significantly increased the dryingtime as compared with those with or without blanching treatments. Goyal et al.(2006) reported that combination of blanching and 1% KMS treatment on rawmango slices resulted in the shorter drying times as compared to control andblanched samples.

Changes in Drying Rate

Drying rate was calculated using Eq. (2). The changes in the drying ratesversus moisture content as influenced by drying air temperature and pretreat-ment are shown in Fig. 2. It is evident that the drying rate decreases continu-ously with decreasing moisture content or increasing drying time. It is alsonoted that the drying rate increased with the increase in drying air temperature.The drying rate was greater for water dropwort samples dried at a highertemperature than for the samples dried at a lower temperature for the sameaverage moisture content of the samples. Consequently, the drying timedecreased at a higher drying air temperature condition. Due to the fact that therelative humidity of the drying air at a higher temperature was less comparedwith that of a lower temperature, the difference in the partial vapor pressurebetween the water dropwort and their surroundings was greater for the highertemperature drying environment (Kaleemullah and Kailappan 2007). Thisresulted in a higher moisture transfer rate with the higher temperature dryingair. Such an influence of drying air temperature on the drying rate was notedin earlier researches (Akpinar et al. 2003; Lahsasni et al. 2004; Sacilik andElicin 2006; Doymaz 2007; Wang et al. 2007).


Water dropwort samples did not exhibit a constant-rate drying period andall the drying operations are seen to occur in the falling rate period. This is dueto the quick removal of moisture from the skin of water dropwort (Kaleemul-lah and Kailappan 2007) and shows the diffusion-dominant drying phenom-ena. At the beginning of the drying process, the drying rate was very high, butdecreased as the moisture content approached equilibrium. Similar resultshave been presented for aromatic plants (Belghit et al. 2000), single apricots(Togrul and Pehlivan 2003), mushrooms (Giri and Prasad 2007), red chillies(Kaleemullah and Kailappan 2007), red peppers (Akpinar et al. 2003) andonion slices (Sarsavadia et al. 1999; Pathare and Sharma 2006).

Moisture content (g water/g solid)

0 2 4 6 8 10 12 14 16 180.00

0.05

0.10

0.15

0.20

0.25

0.3050C

60C

70C

0 2 4 6 8 10 12 14 16 180.00

0.05

0.10

0.15

0.20

0.25

0.3050C

60C

70C


0 2 4 6 8 10 12 14 16 180.00

0.05

0.10

0.15

0.20

0.25

0.3050C

60C

70C

0 2 4 6 8 10 12 14 16 18

Dry

ing

ra

te (

g w

ate

r/g

dry

so

lid

. m

in)

0.00

0.05

0.10

0.15

0.20

0.25

0.3050C

60C

70C


0 2 4 6 8 10 12 14 16 18D

ryin

g r

ate

(g w

ate

r/g d

ry s

oli

d. m

in)

0.00

0.05

0.10

0.15

0.20

0.25

0.3050C

60C

70C

0 2 4 6 8 10 12 14 16 18

Dry

ing

ra

te (

g w

ate

r/g

dry

so

lid

. m

in)

0.00

0.05

0.10

0.15

0.20

0.25

0.3050C

60C

70C

a

c

b

FIG. 2. EFFECT OF DRYING AIR TEMPERATURE ON DRYING RATE(A) Control, (B) blanched, and (C) 1% KMS treated samples, respectively.


Vacuum Drying Modeling

The moisture content data from the drying experiment were convertedinto the MR and then fitted to the selected thin-layer drying models listed inTable 1. The statistical results of the different models, including the compari-son criteria used to evaluate goodness of the fit, viz., the values of the coeffi-cient of determination (R2), reduced chi-square (c2) and RMSE with estimatedparameters for proposed models are presented in Tables 2–4. Based on thecriteria of the highest R2 and the lowest RMSE, the best model describing the

TABLE 2.ESTIMATED VALUES OF PARAMETERS OF SELECTED MODELS USED FOR THIN-LAYER

DRYING OF THE CONTROL SAMPLES AT DIFFERENT TEMPERATURE

ModelNo.

Temp.(C)

Model constants R2 c2 RMSE

1 50 k = 0.0142 0.9985 0.00015 0.0000760 k = 0.0165 0.9908 0.00104 0.0004970 k = 0.0188 0.9945 0.00065 0.00030

2 50 k = 0.0096, n = 1.0885 0.9993 0.00007 0.0000360 k = 0.0041, n = 1.3222 0.9984 0.00018 0.0000870 k = 0.0067, n = 1.2456 0.9989 0.00013 0.00006

3 50 k = 0.0137, n = 1.0409 0.9985 0.00018 0.0000860 k = 0.0150, n = 1.1052 0.9908 0.00134 0.0006370 k = 0.0173, n = 1.0898 0.9945 0.00065 0.00030

4 50 k = 0.0144, a = 1.0105 0.9986 0.00014 0.0000760 k = 0.0170, a = 1.0332 0.9916 0.00095 0.0004470 k = 0.0192, a = 1.0222 0.9949 0.00061 0.00028

5 50 k = 0.0141, a = 1.0148, c = -0.0064 0.9988 0.00012 0.0000660 k = 0.0163, a = 1.0447, c = -0.0150 0.9927 0.00082 0.0003870 k = 0.0184, a = 1.0326, c = -0.0136 0.9957 0.00051 0.00023

6 50 k = 0.0144, k0 = 0.0144, a = 0.5111, b = 0.4994 0.9986 0.00014 0.0000760 k = 0.0170, k0 = 0.0170, a = 0.5361, b = 0.4971 0.9916 0.00095 0.0004470 k = 0.0192, k0 = 0.0192, a = 0.5256, b = 0.4966 0.9949 0.00061 0.00028

7 50 k = 0.0142, a = 1.0000 0.9985 0.00015 0.0000760 k = 0.0234, a = 1.8571 0.9978 0.00025 0.0001270 k = 0.0188, a = 1.0000 0.9945 0.00065 0.00030

8 50 k = 0.0240, a = 2.1896, b = 0.5921 0.9985 0.03325 0.0157560 k = 0.0244, a = 6.2371, b = 0.6782 0.9908 0.16452 0.0771270 k = 0.0291, a = 4.9017, b = 0.6473 0.9945 0.12530 0.05817

9 50 k = 0.0144, a = 0.3371, b = 0.3427,c = 0.3306, g = 0.0144, h = 0.0144

0.9986 0.00014 0.00007

60 k = 0.0170, a = 0.3544, b = 0.3494,c = 0.3294, g = 0.0170, h = 0.0170

0.9916 0.37340 0.17503

70 k = 0.0192, a = 0.3478, b = 0.3455,c = 0.3289, g = 0.0192, h = 0.0192

0.9949 0.00061 0.00028


thin-layer drying characteristics of water dropwort was selected. For allexperiments, the R2, c2 and RMSE values for models changed between 0.9841and 0.9995, 0.5 ¥ 10-4, and 3.7 ¥ 10-1, 0.2 ¥ 10-4 and 1.7 ¥ 10-1, respectively.From Tables 3–5, the highest R2 values and the lowest values of c2, and RMSEvalues were obtained from the Page model. The R2, c2 and RMSE values ofPage model vary between 0.9937–0.9995, 0.5–7.0 ¥ 10-4 and 0.2–3.3 ¥ 10-4,respectively. According to these results, the Page model was selected asthe suitable model to represent the thin-layer drying behavior of waterdropwort.


DRYING OF THE BLANCHED SAMPLES AT DIFFERENT TEMPERATURES

ModelNo.

Temp.(C)


1 50 k = 0.0119 0.9927 0.00093 0.0004460 k = 0.0139 0.9885 0.00166 0.0007770 k = 0.0238 0.9899 0.00139 0.00063

2 50 k = 0.0048, n = 1.1946 0.9967 0.00043 0.0002060 k = 0.0035, n = 1.3068 0.9966 0.00050 0.0002370 k = 0.0052, n = 1.3800 0.9977 0.00032 0.00014

3 50 k = 0.0110, n = 1.0779 0.9927 0.00093 0.0004460 k = 0.0126, n = 1.1041 0.9885 0.00166 0.0007770 k = 0.0216, n = 1.1026 0.9899 0.00139 0.00063

4 50 k = 0.0122, a = 1.0248 0.9932 0.00087 0.0004160 k = 0.0143, a = 1.0366 0.9895 0.00153 0.0007170 k = 0.0242, a = 1.0221 0.9903 0.00133 0.00061

5 50 k = 0.0114, a = 1.0403, c = -0.0225 0.9949 0.00065 0.0003160 k = 0.0131, a = 1.0602, c = -0.0319 0.9923 0.00112 0.0005270 k = 0.0229, a = 1.0394, c = -0.0203 0.9920 0.00111 0.00050

6 50 k = 0.0122, k0 = 0.0122, a = 0.5263, b = 0.4985 0.9932 0.00087 0.0004160 k = 0.0143, k0 = 0.0143, a = 0.0583, b = 0.4984 0.9895 0.03221 0.0149670 k = 0.0242, k0 = 0.0242, a = 0.5255, b = 0.4966 0.9903 0.00133 0.00061

7 50 k = 0.0155, a = 1.6952 0.9965 0.00044 0.0002160 k = 0.0137, a = 1.0000 0.9885 0.00167 0.0007870 k = 0.0348, a = 1.9443 0.9969 0.00043 0.00019

8 50 k = 0.0188, a = 4.7246E-011, b = 0.6325 0.9927 0.00093 0.0004460 k = 0.0205, a = 2.9416E-011, b = 0.6781 0.9885 0.00166 0.0007770 k = 0.0354, a = 6.8893E-011, b = 0.6740 0.9899 0.00139 0.00063

9 50 k = 0.0122, a = 0.3478, b = 0.3471,c = 0.3300, g = 0.0122, h = 0.0122

0.9932 0.00087 0.00041

60 k = 0.0143, a = 0.3560, b = 0.3507,c = 0.3300, g = 0.0143, h = 0.0143

0.9895 0.00153 0.00071

70 k = 0.0242, a = 0.3478, b = 0.3455,c = 0.3288, g = 0.0242, h = 0.0242

0.9903 0.00133 0.00061


Figure 3 compares the experimental and the predicted moisture ratioswith the Page model versus the drying time for dried water dropwort at 50, 60and 70C for the control, blanched and 1% KMS treated samples, respectively.As can be seen, the proposed model provided conformity between experimen-tal and predicted moisture ratios. Figure 4 indicates the comparison of thepredicted and the experimental moisture ratio values for various drying airtemperatures for the control, blanched and 1% KMS treated samples, respec-tively. It can be seen that there was a very good agreement between the


DRYING OF THE 1% KMS TREATED SAMPLES AT DIFFERENT TEMPERATURES

ModelNo.

Temp.(C)


1 50 k = 0.0094 0.9931 0.00076 0.0003660 k = 0.0145 0.9920 0.00087 0.0004170 k = 0.0139 0.9841 0.00207 0.00097

2 50 k = 0.0068, n = 1.0653 0.9937 0.00070 0.0003360 k = 0.0037, n = 1.3057 0.9995 0.00005 0.0000270 k = 0.0015, n = 1.4934 0.9992 0.00014 0.00006

3 50 k = 0.0110, n = 1.0702 0.9927 0.00076 0.0003660 k = 0.0126, n = 1.1041 0.9885 0.00087 0.0004170 k = 0.0216, n = 1.1026 0.9899 0.00207 0.00097

4 50 k = 0.0094, a = 0.9957 0.9932 0.00076 0.0003660 k = 0.0150, a = 1.0392 0.9930 0.00075 0.0003670 k = 0.0146, a = 1.0603 0.9865 0.00176 0.00083

5 50 k = 0.0090, a = 1.0036, c = -0.0134 0.9939 0.00066 0.0003260 k = 0.0144, a = 1.0491, c = -0.0134 0.9940 0.00063 0.0003070 k = 0.0139, a = 1.0753, c = -0.0199 0.9880 0.00318 0.00149

6 50 k = 0.0094, k0 = 0.0094, a = 0.5040, b = 0.4918 0.9932 0.00076 0.0003660 k = 0.0150, k0 = 0.0150, a = 0.5383, b = 0.5010 0.9930 0.00075 0.0003670 k = 0.0146, k0 = 0.0146, a = 0.5576, b = 0.5027 0.9865 0.00176 0.00083

7 50 k = 0.0111, a = 1.5075 0.9941 0.00065 0.0003160 k = 0.0206, a = 1.8558 0.9992 0.00009 0.0000470 k = 0.0216, a = 2.0295 0.9986 0.00018 0.00009

8 50 k = 0.0152, a = 7.8902E-011, b = 0.6186 0.9931 0.00076 0.0003660 k = 0.0221, a = 5.9880E-011, b = 0.6569 0.9920 0.00087 0.0004170 k = 0.0197, a = 1.7863E-010, b = 0.7069 0.9841 0.00207 0.00097

9 50 k = 0.0094, a = 0.3319, b = 0.3387,c = 0.3252, g = 0.0094, h = 0.0094

0.9932 0.00076 0.00036

60 k = 0.0150, a = 0.3559, b = 0.3514,c = 0.3319, g = 0.0150, h = 0.0150

0.9930 0.00075 0.00036

70 k = 0.0146, a = 0.3693, b = 0.3581,c = 0.3330, g = 0.0146, h = 0.0146

0.9865 0.00176 0.00083


experimental and calculated moisture ratio values, which are closely bandingaround at a 45° straight line. Accordingly, this indicates the suitability of thePage model in describing drying behavior of water dropwort. The Page modelhas also been suggested by others to describe thin-layer drying of raw mangoslices (Goyal et al. 2006), pomegranate arils (Kingsly and Singh 2007) andaloe vera (Vega et al. 2007).

Surface Color

Effects of drying temperature and pretreatment on surface color of waterdropwort as CIE color values are shown in Table 5. The surface color of thedried water dropwort appeared to be more influenced by pretreatment condi-tions than drying air temperature. In general, 1% KMS treated samples showlower L* and b* values and higher a* values than those of control andblanched samples. There were significant decreases in L* values after dryingregardless of the pretreatments (P < 0.05). The dried samples were hencedarkened compared to the fresh samples as expected. Drying also resulted ina significantly higher a* values but lower b* values than those of fresh samples(P < 0.05). Decrease in greenness after blanching and drying was alsoobserved for mustard, mint and spinach (Kaur et al. 2008). Total color changevalues (DE*) for control and blanched sample ranged from 17.19–21.12 and17.18–19.88, respectively, whereas those for 1% KMS treated samples were24.52–31.04. Significant changes in the color characteristics with an increasein the drying air temperature were found in some conditions (P < 0.05) but nodirect relationship with drying air temperature was found.

TABLE 5.EFFECT OF DRYING TEMPERATURE AND PRETREATMENTS ON SURFACE COLOR OF

WATER DROPWORT

Processing condition L* value a* value b* value DE*

Fresh 53.19 � 2.77a -19.96 � 1.24e 33.62 � 2.44a 00.00Control

50C 37.63 � 2.94cd -15.04 � 1.68cd 23.06 � 2.92bc 19.4460C 36.22 � 3.82cd -15.00 � 1.26cd 22.06 � 2.40bcd 21.1270C 38.82 � 4.02bc -16.17 � 1.40cd 24.76 � 2.96b 17.19

Blanching50C 37.71 � 1.55cd -16.37 � 1.25d 22.83 � 1.96bc 19.2160C 41.44 � 5.23b -15.80 � 1.73cd 21.79 � 3.23bcd 17.1870C 39.58 � 3.92bc -12.69 � 1.55b 21.09 � 4.04cd 19.88

1% KMS50C 26.10 � 3.13f -10.32 � 2.33a 13.60 � 3.58e 35.0460C 34.51 � 5.16de -14.33 � 2.99bc 18.77 � 5.50d 24.5270C 31.69 � 4.27e -9.96 � 2.88a 13.59 � 4.98e 31.04

Samples in the same column with different superscripts differ significantly at P < 0.05.


CONCLUSIONS

The drying characteristics of water dropwort with and without pretreat-ments were investigated in a vacuum dryer as a single layer at the drying airtemperatures of 50, 60 and 70C. Constant drying rate period was not observed,the water dropwort drying occurred in the falling rate period. The moisturecontent and drying rate were influenced by the drying air temperature. Increas-ing in the drying air temperature caused a decrease in the drying time and anincrease in the drying rate. Based on nonlinear regression analysis, the Page

Time (min)

0 100 200 300 400 500 600

Mois

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rati

o

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1.2

50C

60C

70C

Page

Time (min)

0 100 200 300 400 500 600

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re r

ati

o

0.0

0.2

0.4

0.6

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60C

70C

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Time (min)

0 100 200 300 400 500 600 700 800

Mo

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ati

o

0.0

0.2

0.4

0.6

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50C

60C

70C

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c

a b

FIG. 3. EXPERIMENTAL AND COMPUTED MOISTURE RATIO OBTAINEDUSING THE PAGE MODEL

(A) Control, (B) blanched, and (C) 1% KMS treated samples, respectively.


model was considered adequate to describe the thin-layer drying behavior ofwater dropwort. The color changes among samples with and without pretreat-ments were significantly different.

Based on the experimental data, the most adequate drying condition ofwater dropwort using a vacuum dryer would be blanching pretreatment anddrying at 60C, which led to the minimum total color difference value. Withrespect to drying efficiency, the total drying time based on the same finalmoisture content for samples with blanching pretreatment and drying at 50 or70C was significantly reduced as compared to that of control. Blanching is

Experimental moisture ratio

0.0 0.2 0.4 0.6 0.8 1.0

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60 C

70 C


0.0 0.2 0.4 0.6 0.8 1.0

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0.2

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60 C

70 C


0.0 0.2 0.4 0.6 0.8 1.0

Pre

dic

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ture

rati

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0.0

0.2

0.4

0.6

0.8

1.050 C

60 C

70 C

a b

c

FIG. 4. COMPARISON OF EXPERIMENTAL AND PREDICTED MOISTURE RATIOBY THE PAGE MODEL

(A) Control, (B) blanched, and (C) 1% KMS treated samples, respectively.


strongly recommended although selection of temperature would depend onwhether the drying efficiency or color quality parameter is important inprocess evaluation criteria.

ACKNOWLEDGMENTS

This research was supported by the Daegu University Research Grant,2007.

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influence of pretreatments on the dehydration characteristics during vacuum drying of water dropwort...

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