THIN-LAYER INFRARED DRYING OF MINT LEAVES

Journal of Food Processing and Preservation ISSN 1745-4549 THIN-LAYER INFRARED DRYING OF MINT LEAVES CAN ERTEKIN1,3 and NURSEL HEYBELI2 1 2 Departme...
12 downloads 0 Views 832KB Size
Journal of Food Processing and Preservation ISSN 1745-4549

THIN-LAYER INFRARED DRYING OF MINT LEAVES CAN ERTEKIN1,3 and NURSEL HEYBELI2 1 2

Department of Farm Machinery, Faculty of Agriculture, Akdeniz University, 07070, Antalya, Turkey Department of Farm Machinery, Institute of Natural and Applied Sciences, Akdeniz University, Antalya, Turkey

3

Corresponding author. TEL: +902423102481; FAX: +902422274564; EMAIL: [email protected] Received for Publication September 18, 2012 Accepted for Publication March 1, 2013 doi:10.1111/jfpp.12107

ABSTRACT The effects of drying temperature on the drying time, color and thin-layer drying model were investigated. The moisture ratios changes during the drying time were compared by 38 different mathematical models and evaluated by different statistical criteria such as coefficient of determination (R2), reduced chi-square (c2), root mean square error and mean relative percentage error (P). According to the results, drying time was between 18 and 38 min at drying temperatures of 60–80C. The lightness and yellowness of the dried mint leaves were significantly increased when compared with fresh samples. The high drying temperature yielded in darker, less green and more yellow mint leaves. When the 38 models compared according to the statistical values, the rational function model (model32) for drying temperatures of 60 and 70C and Modified Henderson Pabis-II model (model-5) were superior to the others.

PRACTICAL APPLICATION Mint essential oil is extracted either from freshly harvested mint leaves or from semi dried or dried leaves through distillation process for industrial use. Therefore, mint drying by using infrared provides many advantages.

INTRODUCTION Increasing popularity of herb plants has improved their commercial importance. Since they are usually used as dried, determination of their drying characteristics are essential for their preservation and storage in longer periods (Kaya and Aydin 2009). Mint leaves (Mentha spicata L.) are a common name for members of the Labiatae (Laminaceae family; Ozbek and Dadali 2007; Kadam et al. 2011; Nayak et al. 2011). Several species are shrubby or climbing forms or, rarely, small trees. It is especially widely grown in Mediterranean region, where these plants form a dominant part of the vegetation. It has been used as a medicinal and aromatic plant since ancient times. Its leaves are used for flavoring, tea infusions and spicing. They are refreshing, antiseptic, stimulative, diaphoretic, stomachic and antispasmodic. It helps with cold, flu, fever, poor digestion, motion sickness, food poisoning, rheumatism, hiccups, stings, earaches, flatulence, and throat and sinus ailments. Its initial moisture content is about 78–82% (w.b.; Colak et al. 2008; Therdthai and Zhou 2009; Akpinar 2010; Nayak et al. 2011). Drying is one of the oldest methods of food preservation and represents a very important aspect of food processing. 1480

Infrared heating offers many advantages over conventional drying under similar drying conditions. Studies comparing infrared drying with techniques based on air convection showed that the infrared radiation (IR) method is quicker than convection methods. That is suitable if processing time is a prime factor (Hebbar and Rastogi 2001; Nowak and Lewicki 2005; Togrul 2006). Since the material is heated rapidly and more uniformly, the IR energy is transferred from the heating element to the product without heating the surrounding air (Heybeli and Ertekin 2011). The irradiated surface evaporates much more water than that of not heated until 80% of water is removed and drying time shortened by up to 50% when heating is done with infrared energy (Nowak and Lewicki 2004). IR has been applied in conjunction with several drying processes because it has advantages of increasing the drying efficiency (Das et al. 2009). Infrared drying combined with hot air pre-drying can save 20% of drying time as compared to the infrared drying alone in apple pomace drying (Sun et al. 2007). Combined with far IR, drying has recently received more attention in drying some types of fruits to produce fat-free fruit-based snacks (Nimmol et al. 2007; Swasdisevi et al. 2009). While IR is used to heat or dry moistly materials, the

Journal of Food Processing and Preservation 38 (2014) 1480–1490 © 2013 Wiley Periodicals, Inc.

C. ERTEKIN and N. HEYBELI

SUITABLE DRYING MODEL FOR INFRARED DRYING OF MINT

FIG. 1. OHAUS MB25 BASIC MOISTURE ANALYZERS; (1) PAN SUPPORT (2) HALOGEN HEATER, (3) MOISTURE SENSOR, (4) DRAFT SHIELD, (5) LOAD CELL, (6) PRINT, (7) PASSING OF BETWEEN THE LOSS WEIGHT (G), LOSS MOISTURE (%) AND DRY MATTER (%), (8) TEMPERATURE SETTING, (9) TIME SETTING, (10) TARE, (11) OPEN AND CLOSE. CAPACITY: 110 G, HEATING TECHNOLOGY: HALOGEN, TEMPERATURE RANGE: 50–160C, GRADUATION: 5C, SENSITIVITY OF BALANCE (SAMPLE = 3 G): 0.2%, POWER: 100–240 VAC, FREQUENCY: 50–60 HZ, TIME SWITCH (RANGE): 0–99 MIN

radiation penetrates inside the material and it becomes heat. The depth of penetration of radiation depends upon the characteristics of the material and wavelength of radiation. Application of IR to food processing has gained momentum due to its inherent advantages over hot air heating. Scientific studies are on infrared drying of cashew kernel (Hebbar and Rastogi 2001), parboiled rice (Das et al. 2004), apple (Togrul 2005), onion (Sharma et al. 2005; Pathare and Sharma 2006), celery (Jezek et al. 2008), red pepper (Nasiroglu and Kocabiyik 2008), olive husk (Celma et al. 2008), blueberries (Shi et al. 2008), seedless grape (Caglar et al. 2009) and carrot (Togrul 2006; Kocabiyik and Tezer 2009). The objectives of this study were (1) to observe the effect of drying temperature, (2) to determine the color changes of mint leaves and (3) to find the best suitable drying model during infrared drying of mint leaves.

MATERIALS AND METHODS Mint was procured from a local market and cleaned by removing undesired stems and waste materials. The excess water was removed with the help of blotting paper. The

damaged and black leaves were separated manually under careful observation before putting them into dryer. In this study, infrared dryer and moisture analyzer equipment (MB25 Basic Moisture Analyzers, OHAUS, Pine Brook, NJ, USA) transmitting electromagnetic radiation in the range medium to shortwave IR (radiator) was used as drying equipment (Fig. 1). The drying temperature was set in keyboard of the equipment as 60, 70, 80C in each experiment. The amount of evaporated water during drying was determined at about 2-min intervals in each drying temperature. Drying tests were replicated three times and average weight loss was reported.

Color Changes The color of the mint leaves were measured using a CR 200 (Minolta, Tokyo, Japan) and expressed according to the Hunter color values as the lightness (L*), redness (a*) and yellowness (b*). The instrument was calibrated against a white standard. The average values of color parameters and standard deviations were calculated (L*, a*, b*, C* and H). The color value of L* have shown the brightness and it

Journal of Food Processing and Preservation 38 (2014) 1480–1490 © 2013 Wiley Periodicals, Inc.

1481

SUITABLE DRYING MODEL FOR INFRARED DRYING OF MINT

C. ERTEKIN and N. HEYBELI

ranges from 0 to 100. The color coordinates a* and b* values do not have a specific measurement range. Sample color is mean red if the a* value is positive, if it is negative, the color is expresses green. Another, if b* value is positive, the color is yellow, if it is negative, the color is described blue. Metric color chrome C* and hue H* values were calculated using the measured L*a*b* values. Evaluation of color changes of the product were done by using the total chromatic aberration (DE*), color brightness deviation (DL*), chrome aberration (DC*) and metric hue angle deviation (DH*) (Soysal et al. 2005). The changes in each color parameters were calculated as follows:

ΔE * = ( ΔL*)2 + ( Δa*)2 + ( Δb*)2

(1)

ΔL* = L*sample − L*standard

(2)

Δa* = a*sample − a*standard

(3)

Δb* = b*sample − b*standard

(4)

H * = tan −1

b* a*

(5)

C *sample = a*2 + b*2

(6)

ΔC * = C *sample − C *standard

(7)

ΔH * = ΔE *2 + ΔL*2 + ΔC *2

(8)

where Da* is red color deviation, Db* is yellow color deviation, DL* is color brightness deviation, DE* is total chromatic aberration, H* is metric hue, DH* is metric hue angle deviation, C* is metric chrome and DC* is chrome aberration.

Mathematical Model Drying curves were fitted to the experimental data using 38 different drying models (Table 1). However, the moisture ratio (MR) was simplified to M/M0 instead of (M-Me)/(M0Me) because of low values of equilibrium moisture content (Midilli and Kucuk 2003; Togrul and Pehlivan 2004; Menges and Ertekin 2006; Ertekin and Yaldiz 2011); where M is the moisture content in decimal dry basis at any time t, M0 is the initial moisture content in decimal dry basis and Me is the equilibrium moisture content in decimal dry basis. Regression analyses of these models were done by using STATISTICA routine. The determination coefficient (R2), reduced chi-square (c2), root mean square error (RMSE) and mean relative percentage error (P) were used as criteria for selecting the best model to describe the infrared drying curves of mint leaves. These statistical values can be calculated as follows: 1482

∑ ( MR = N

χ

2

i =1

exp,i

− MRpre ,i )

2

(9)

N −n 12

⎡1 N ⎤ RMSE = ⎢ ∑ MRpre ,i − MRexp,i ⎥ N ⎣ i =1 ⎦

(10)

100 N ⎧ MRexp,i − MRpre ,i ⎫ ∑ ⎨ MRexp,i ⎬ N i =1 ⎩ ⎭

(11)

P=

where MRexp,i is the ith experimental moisture ratio, MRpre,i is the ith predicted moisture ratio, N is the number of observations and n is the number of constants in the drying model (Ertekin and Yaldiz 2002; Kumar et al. 2006; Soysal et al. 2006; Celen et al. 2010; Chowdhury et al. 2011).

RESULTS AND DISCUSSION In each experiment, about 1.34 g mint leaves were used. The drying times obtained in this study were compared with the results of the previous studies given in the literature. The drying time was calculated to reach the safe moisture content of 10% (w.b) and found as 38, 27 and 18 min at drying temperatures of 60, 70 and 80C in infrared drying experiments, respectively (Fig. 2). The drying kinetics of mint is affected by drying temperature, which is the main factor in controlling the drying rate (Lebert et al. 1992; Kane et al. 2009). In convective drying, the drying time required to dry mint ranged from 5 h at drying air temperature of 30C to 5 min at 100C (Rocha et al. 1992). Changing drying air velocity from 0.2 m/s to 0.4 m/s decreased the drying time from about 600 min to about 580 min and a further increase in velocity to 0.6 m/s decreased to about 560 min. Drying air temperature changes from 35C to 45C decreased the drying time about 15% and to 55C about 26.7%. Decreasing drying air relative humidity from 70 to 55% decreased the drying time about 25% and a further decrease in relative humidity to 40% decreased the drying time to about 37.5% (Kaya and Aydin 2009). The drying time was 390 and 240 min for convective drying of mint leaves at drying air temperatures of 45 and 65C, respectively (Kadam et al. 2011). It was 9 h to reach moisture content of 14.3% (w.b.) for convective drying at drying air temperature of 46C (Soysal and Oztekin 2001). The drying time taken to reduce moisture content of mint leaves from the initial 84.7% (w.b.) to a final 10% (w.b.) was 600, 285, 180 and 105 min at 35, 45, 55 and 60C in cabinet dryer, respectively (Doymaz 2006). In microwave drying, drying time decreased considerably with increase in microwave power and with decrease in sample amount of mint leaves as well. The microwave drying process took 3.0–12.5 min depending on microwave power (Ozbek and Dadali 2007). The microwave drying process took 6.25–16.00 min depending

Journal of Food Processing and Preservation 38 (2014) 1480–1490 © 2013 Wiley Periodicals, Inc.

C. ERTEKIN and N. HEYBELI

SUITABLE DRYING MODEL FOR INFRARED DRYING OF MINT

TABLE 1. MATHEMATICAL MODELS GIVEN BY VARIOUS AUTHORS FOR DRYING CURVES No

Model name

Model

Reference

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Newton Page Henderson and Pabis Modified Henderson and Pabis-I Modified Henderson and Pabis-II Modified Page-I Modified Page-II Modified Page-III Logarithmic Two-term Mod. two-term-I Mod. two-term-II Mod. two-term-III Two-term exponential Verma et al. Diffusion approximation Wang and Singh Midilli et al. Modified Midilli et al.-I Modified Midilli et al.-II Mod. Midilli et al.-III Hii et al. Weibull distribution-I Weibull distribution-II Vega-Galvez-I Vega-Galvez-II Vega-Lemus Jena-Das One term Two-term Three-term

Senadeera et al. 2003; Sacilik et al. 2006 Doymaz, 2007; Cihan et al. 2007 Aktas and Polat 2007 Arslan and Ozcan 2011 Corzo et al. 2011 Babalis et al. 2006 Jazini and Hatamipour 2010 Kurozawa et al. 2011 Sacilik et al. 2006 Togrul and Pehlivan 2003 Dadali et al. 2007 Baini and Langrish 2007 Tirawanichakul et al. 2008 Naghavi et al. 2010 Togrul and Pehlivan 2003 Artnaseaw et al.2010 Purkayastha et al. 2011 Soysal et al. 2006 Ghazanfari et al. 2006 Erbay and Icier 2010 Erbay and Icier 2010 Hii et al. 2009 Babalis et al. 2006 Mundada et al. 2010 Lemus-Mondaca et al. 2009 Lemus-Mondaca et al. 2009 Vega-Galvez et al. 2009 Jena and Das 2007 Wang et al. 2004 Wang et al. 2004 Wang et al. 2004

32

Rational function

33 34 35 36

Sripinyowanich and Noomhorn Noomhorn and Verma Hasibuan and Daud Sharaf-Eldeen et al.

37

Henderson and Henderson-I

38

Henderson and Henderson-II

MR = exp(-kt) MR = exp(-ktn) MR = a exp(-kt) MR = a exp(-k0t) + b exp(-k1t) + c exp(-k2t) MR = a exp(-ktn) + b exp(-gt) + c exp(-ht) MR = a exp[-(ktn)] MR = exp[-(ktn)] MR = exp-(ktn) MR = a exp(-kt) + c MR = a exp(-k0t) + b exp(-k1t) MR = a exp(-k0t) + (1 - a) exp(k1t) MR = a exp(-k0t) + a exp(-k1t) MR = a exp(-k0tn) + b exp(-k1t) MR = a exp(-kt) + (1 - a)exp(-kat) MR = a exp(-kt) + (1 - a)exp(-gt) MR = a exp(-kt) + (1 - a)exp(-kbt) MR = 1 + at + bt2 MR = a exp(-ktn) + bt MR = exp(-ktn) + bt MR = exp(-kt) + bt MR = a exp(-kt) + bt MR = a exp(-ktn) + c exp(-gtn) MR = a - b exp[-(ktn)] MR = a - b exp[-ktn] MR = n + k t MR = exp(n + kt) MR = (a + bt)2 MR = aexp − kt + b t + c MR = a exp(bkt) + (1 - a) MR = (1 - a) exp(bkt) + a exp(ckt) MR = (1 - a - b) exp(ckt) + a exp(dkt) + b exp(fkt) a + bt MR = 1+ ct + dt 2 MR = exp(-ktn) + bt + c MR = a exp(-kt) + b exp(-gt) + c MR = 1 - atn exp(-ktn) MR = a exp(kt) + [1 - a exp(-bkt)] 1 MR = c ⎡⎢exp ( − kt ) + exp ( −9kt )⎤⎥ 9 ⎣ ⎦ 1 MR = c exp ( − kt ) + exp ( −9kt ) 9

(

on the drying conditions. The lower microwave power density, the longer the drying time of mint leaves (Soysal 2005). It was ranged between 11 and 16 min in other study (Fathima et al. 2001); this drying time was 10–13 min in microwave vacuum drying (Therdthai and Zhou 2009). It was also ranged between 64 and 180 min for different drying air velocities at constant IR density of 1,080 W/m2 in convective infrared drying (Kocabiyik and Demirturk 2008). This drying process took 21 h in a hybrid photovoltaic thermal-based greenhouse dryer (Nayak et al. 2011), 7 h in humidity-controlled solar dryer (Gurel et al. 2010) and 12 h in domestic solar dryer (Saleh and Badran 2009). It took 6 h for natural sun drying (Akpinar 2006). In contact

)

Haghi and Angiz 2007 Sripinyowanich and Noomhorm 2011 Kaleta and Gornicki 2010 Daud et al. 2007 Wang et al. 2004 Barrazo et al. 2004 Cordeiro and Oliveira 2006

dryer, the shortest drying time obtained was 15 h for peppermint (Tarhan et al. 2011). This drying time was 7.5 h for heat pump-assisted dryer (Fatouh et al. 2006), 12–14 h in freeze dryer (Antal et al. 2011) and 12–18 h for rotary drum dyer (Tarhan et al. 2010) for peppermint. Lightness (L*), greenness (negative a*) and yellowness (positive b*) of fresh mint leaves were 40.79 ⫾ 3.55, 15.56 ⫾ 1.45 and 21.01 ⫾ 1.39, respectively. As shown in Fig. 3, the lightness and yellowness of the dried mint leaves were significantly increased, possibly because of chlorophyll degradation. The degree of color change was dependent on drying temperature, drying time and oxygen level. High temperature could lead to the replacement of magnesium in

Journal of Food Processing and Preservation 38 (2014) 1480–1490 © 2013 Wiley Periodicals, Inc.

1483

SUITABLE DRYING MODEL FOR INFRARED DRYING OF MINT

FIG. 2. MOISTURE CONTENT CHANGES DURING THE DRYING PROCESS

FIG. 3. COLOR DEGRADATION

the chlorophyll by hydrogen, thereby converting chlorophylls to pheophytins (Therdthai and Zhou 2009). The a* values were ranged between -5.46 and -0.78 and b* values between 12.16 and 17.19 for dried mint leaves. The total chromatic aberration (DE*) and the chrome aberration (DC*) indices are not good indicators for determining the color difference (Camelo and Gomez 2004). Hue angle is defined as a color circle of red-purple color values of 0–360° angle to take, and the yellow color to take 90° angle and bluish green color 180–270° angle values. Chrome value indicates the saturation of color. When chrome values decreased at mat colors, the chrome value rises at vivid colors (Mutlu and Ergunes 2008). Table 2 shows that the color of dried mint leaves were changed when the drying temperature changed. The high temperature yielded in darker, less green and more yellow mint leaves. As a result, DE* values of the dried samples were significantly higher at drying temperature of 70C. The lightness values were also affected from the drying air temperature. It can be observed from analysis of variance test that drying temperature is not a significant variable 1484

C. ERTEKIN and N. HEYBELI

for color change at P < 0.05 in infrared drying of mint leaves. In convective infrared drying of mint leaves, the total color change (DE*) ranged between 14.5 at drying air velocity of 0.5 m/s and 23.7 at 1.5 m/s (Kocabiyik and Demirturk 2008). The a* value changed from an initial value of -8.74 in fresh samples to -7.68 after blanching and to -2.13 after natural sun drying. There is a decrease in greenness with blanching and drying process. The L* value was 30.06 in fresh mint and decreased to 23.58 after blanching, to 18.41 after cabinet drying and 20.62 after natural sun drying. DE* value for fresh mint was 33.74 and decreased to 26.17 after blanching. After cabinet drying and natural sun drying of mint, DE* value was decreased to 19.36 and 21.48, respectively. Thus, DE* value was the maximum for fresh samples and decreased after blanching and drying (Kaur et al. 2008). In rotary drum dryer, the drying process caused considerable color changes. It resulted in darkened color, especially, relatively long drying times were the main factors in color change (Tarhan et al. 2010). In order to modeling, the experimental moisture content data were used on the dry weight basis. These moisture content data at any time of drying process obtained at different drying air temperatures were converted to the MR values and fitted against the drying time. Forty thin-layer drying models were compared according to their statistical results such as R2, reduced c2, RMSE and mean relative percentage error. In thin-layer infrared drying of mint leaves, R2 is ranged between 0.826517 and 0.999204, RMSE between 0.008334 and 0.378977, c2 between 0.000087 and 0.159582 and P between 2.270349 and 88.103370 for drying temperature of 60C. For drying temperature of 70C, c2 was between 0.000055 and 0.121687, P between 1.592870 and 86.244212, RMSE between 0.006351 and 0.324750 and R2 between 0.818192 and 0.999545. The thin-layer drying of mint leaves at drying temperature of 80C, the R2 were varied between 0.868028 and 0.999816, RMSE between 0.004150 and 0.111188, c2 ranged between 0.000057 and 0.018610 and P between 1.000824 and 30.033557. The results indicated that the lowest values of c2, RMSE and P and the

TABLE 2. CHANGE COLOR OF DRIED SAMPLES Drying temperature (C)

DL*

Da*

60 70 80

8.369 10.909 9.036

-13.571 -12.209 -11.574

C*

DC*

60 70 80

14.223 14.076 15.231

11.920 12.067 10.911

Db* 6.951 7.356 6.361

DE* 17.405 18.009 16.359

H*

DH*

-82.064 -76.399 -76.3992

22.696 24.268 21.641

Journal of Food Processing and Preservation 38 (2014) 1480–1490 © 2013 Wiley Periodicals, Inc.

C. ERTEKIN and N. HEYBELI

SUITABLE DRYING MODEL FOR INFRARED DRYING OF MINT

MR =

0.9846227 − 0.0004022 t 1 − 0.0003395 t + 0.0000001 t 2

for 60C

MR =

0.9903057 − 0.0005371 t 1 − 0.0003644 t + 0.0000002 t 2

for 70C.

FIG. 4. STATISTICAL RESULT FOR DRYING TEMPERATURE OF 60C

highest values of R2 were obtained at rational function model (model-32) for drying temperature of 60 and 70C and Modified Henderson Pabis-II model (model-5) for drying temperature of 80C (Figs. 4–6). These model constants and coefficients were given below:

FIG. 5. STATISTICAL RESULT FOR DRYING TEMPERATURE OF 70C

Journal of Food Processing and Preservation 38 (2014) 1480–1490 © 2013 Wiley Periodicals, Inc.

1485

SUITABLE DRYING MODEL FOR INFRARED DRYING OF MINT

C. ERTEKIN and N. HEYBELI

with predicted values at any particular drying condition for validation of the established model, these values laid around the straight line (Fig. 7). This means that these models are valid at drying temperatures of 60–80C for infrared drying of mint leaves. Park et al. (2002) evaluated Page and Fick’s model and found that Page’s model was show a better fit to experimental mint drying data except for convective drying at drying air temperature of 50C and velocity of 1.0 m/s. Akpinar (2010) used 10 models as Newton, Page, Modified Page I, Henderson and Pabis, logarithmic, two-term, two-term exponential, Verma et al., Wang and Singh and Thompson and concluded Wang and Singh model was the best descriptive model for the convective solar drying and natural sun drying of mint leaves. It is possible to predict MR by this model with R = 0.99918, c2 = 0.00024726, RMSE = 0.01361781 for convective solar drying and with R = 0.99883, c2 = 0.000355057, RMSE = 0.01744519 for natural sun drying. Doymaz (2006) examined four different thin-layer drying models (Lewis, Henderson and Pabis, Modified Page and logarithmic) and used determination coefficient, reduced c2 and RMSEs for comparison. According to the results, logarithmic model showed a good fit than the other models. Akpinar (2006) fitted 12 different thinlayer drying models (Newton, Page, another type of Modified Page I and another type of Modified Page, Henderson and Pabis, logarithmic, two-term, two-term exponential, Wang and Singh, diffusion approximation, Verma et al., Modified Henderson and Pabis II) on their experimental data and decided that the another type of Modified Page model was the best descriptive model for solar drying of mint leaves with the statistical results of R = 0.99739, c2 = 0.00065, RMSE = 0.02363. Kadam et al. (2011) examined seven thin-layer drying models as Newton, Henderson and Pabis, logarithmic, two-term exponential, another type

FIG. 6. STATISTICAL RESULT FOR DRYING TEMPERATURE OF 80C

MR = −2.7763819 exp ( −0.0018597 t 1.0877487 ) − 2.5775130 exp ( −0.0010111 t ) + 6.3543640 exp ( −0.0016754 t ) for 80C. These models represented the experimental MR values satisfactorily. After comparing the experimental MR values 1486

FIG. 7. EXPERIMENTAL VERSUS PREDICTED MOISTURE RATIO FOR DESCRIBED BEST MODELS

Journal of Food Processing and Preservation 38 (2014) 1480–1490 © 2013 Wiley Periodicals, Inc.

C. ERTEKIN and N. HEYBELI

of Wang and Singh and diffusion approximation. The established R2 values for the models were greater than 0.80 at all temperatures and the Verma et al. model was superior with lowest values of c2, MBE and RMSE. The Modified Verma et al. model with highest R2 value of 0.998 adequately represented thin-layer drying behavior of mint leaves in convective tunnel dryer. Kane et al. (2009) evaluated 13 mathematical models (Newton, Page, Modified Page I, another type of Modified Page, Henderson and Pabis, logarithmic, two-term, two-term exponential, Wang and Singh, diffusion approximation, Modified Henderson and Pabis I, Verma et al. and Midilli-Kucuk) and found that logarithmic model showed the best agreement with the experimental data for convective solar drying with R2 of 0.9999 and c2 of 1.8 ¥ 10-5. Soysal (2005) used 11 models (Newton, Page, Henderson and Pabis, logarithmic, Midilli et al., Wang and Singh, logistic, two-term, Verma et al., two-term exponential and diffusion approximation) to describe drying behavior of mint under microwave and found that Midilli et al. model gave the best fit for all the experimental data points with values for the modeling efficiency of greater than 0.99821 and RMSE of lower than 0.00037. Arslan et al. (2010) evaluated 12 models (Lewis, Page, another type of Modified Page, Henderson and Pabis, logarithmic, two-term model, Midilli and Kucuk, Mod. Henderson and Pabis I, two-term exponential, diffusion approximation, Wang– Singh and Verma et al.) in drying of peppermint leaves by natural sun, oven and microwave drying methods. According to the results, Page, another type of Modified Page, Midilli and Kucuk models adequately described the oven, sun and microwave drying behaviors of peppermint leaves.

CONCLUSIONS Thin-layer infrared drying experiments were conducted with infrared dryer at constant drying temperatures of 60, 70 and 80C. According to the results, drying time decreased when compared with convective, freeze, heat pump, solar and natural sun drying. The color change occurred after drying process, but drying temperature did not significantly affect the color change. Thirty-eight different thin-layer drying models were compared to find the drying behaviour of mint leaves according to R2, RMSE, reduced c2 and P. The rational function model (model-32) for drying temperature of 60 and 70C and Modified Henderson Pabis-II model (model-5) could be used to describe drying behavior of mint leaves with high capability.

ACKNOWLEDGMENT This research was partly supported by the Scientific Research Administration Unit of Akdeniz University, Antalya-Turkey.

SUITABLE DRYING MODEL FOR INFRARED DRYING OF MINT

REFERENCES AKPINAR, E.K. 2006. Mathematical modelling of thin layer drying process under open sun of some aromatic plants. J. Food Eng. 77, 864–870. AKPINAR, E.K. 2010. Drying of mint leaves in a solar dryer and under open sun: Modelling, performance analyses. Energ. Convers. Manage. 51, 2407–2418. AKTAS, T. and POLAT, R. 2007. Changes in the drying characteristics and water activity values of selected pistachio cultivars during hot air drying. J. Food Process Eng. 30, 607–624. ANTAL, T., KEREKES, B. and SIKOLYA, L. 2011. Influence of drying on the volatile compounds of spearmint (Mentha spicata L.). Proceedings of the III European Drying Conference EuroDrying’ 2011. http://www.uibcongres. org/imgdb/archivo_dpo11058.pdf (accessed June 18, 2013). ARSLAN, D. and OZCAN, M.M. 2011. Evaluation of drying methods with respect to drying kinetics, mineral content, and color characteristics of savory leaves. Food Bioprocess. Technol. 5, 983–991. ARSLAN, D., OZCAN, M.M. and MENGES, H.O. 2010. Evaluation of drying methods with respect to drying parameters, some nutritional and colour characteristics of peppermint (Mentha x piperita L.). Energ. Convers. Manage. 51, 2769–2775. ARTNASEAW, A., THEERAKULPISUT, S. and BENJAPIYAPON, C. 2010. Development of a vacuum heat pump dryer for drying chilli. Biosyst. Eng. 105, 130–138. BABALIS, S.J., PAPANICOLAOU, E., KYRIAKIS, N. and BELESSIOTIS, V.G. 2006. Evaluation of thin-layer drying models for describing drying kinetics of figs (Ficus Carica). J. Food Eng. 75, 205–214. BAINI, R. and LANGRISH, T.A.G. 2007. Choosing an appropriate drying model for intermittent and continuous drying of bananas. J. Food Eng. 79, 330–343. BARRAZO, M.A.S., SARTORI, D.J.M. and FREIRE, J.T. 2004. A study of the statistical discrimination of the drying kinetics equations. Food Bioprod. Process. 82, 219–225. CAGLAR, A., TOGRUL, I.T. and TOGRUL, H. 2009. Moisture and thermal diffusivity of seedless grape under infrared drying. Food Bioprod. Process. 87, 292–300. CAMELO, A.F.L. and GOMEZ, P.A. 2004. Comparison of color indexes for tomato ripening. Hortic. Bras. 22, 534–537. CELEN, S., KAHVECI, K., AKYOL, U. and HAKSEVER, A. 2010. Drying behavior of cultured mushrooms. J. Food Process. Pres. 34, 27–42. CELMA, A.R., ROJAS, S. and LOPEZ-RODRIGUEZ, F. 2008. Mathematical modelling of thin-layer infrared drying of wet olive husk. Chem. Eng. Process 47, 1810–1818. CHOWDHURY, M.M.I., BALA, B.K. and HAQUE, M.A. 2011. Mathematical modeling of thin-layer drying of jackfruit leather. J. Food Process. Pres. 35(6), 797–805.

Journal of Food Processing and Preservation 38 (2014) 1480–1490 © 2013 Wiley Periodicals, Inc.

1487

SUITABLE DRYING MODEL FOR INFRARED DRYING OF MINT

CIHAN, A., KAHVECI, K. and HACIHAFIZOGLU, O. 2007. Modelling of intermittent drying of thin layer rough rice. J. Food Eng. 79, 293–298. COLAK, N., KUZGUNKAYA, E. and HEPBASLI, A. 2008. Exergetic assessment of drying of mint leaves in a heat pump dryer. J. Food Process Eng. 31, 281–298. CORDEIRO, D.S. and OLIVEIRA, W.P. 2006. Thin layer drying of Maytenus ilicifolia leaves: Dehydration kinetics and product quality. In Proceedings of the 15th International Drying Symposium, Budapest, Hungary. pp. 1591–1604. CORZO, O., BRACHO, N. and ALVAREZ, C. 2011. Determination of suitable thin layer model for air drying of mango slices at different air temperatures and velocities. J. Food Process Eng. 34, 332–350. DADALI, G., DEMIRHAN, E. and OZBEK, B. 2007. Microwave heat treatment of spinach: Drying kinetics and effective moisture diffusivity. Dry Technol. 25, 1703–1712. DAS, I., DAS, S.K. and BAL, S. 2004. Specific energy and quality aspects of infrared (IR) dried parboiled rice. J. Food Eng. 62, 9–14. DAS, I., DAS, S.K. and BAL, S. 2009. Drying kinetics of high moisture paddy undergoing vibration-assisted infrared (IR) drying. J. Food Eng. 95, 166–171. DAUD, W.R.W., TALIB, M.Z.M. and HOOI, O.C. 2007. Characteristics of superheated steam through drying of kenaf fibers. In Proceedings of the 5th Asia-Pasific Drying Conference, Hong Kong. pp.144–149. DOYMAZ, I. 2006. Thin-layer drying behaviour of mint leaves. J. Food Eng. 74, 370–375. DOYMAZ, I. 2007. Air-drying characteristics of tomatoes. J. Food Eng. 78, 1291–1297. ERBAY, Z. and ICIER, F.A. 2010. A review of thin layer drying of foods: Theory, modeling, and experimental results. Crit. Rev. Food Sci. Nutr. 50, 441–464. ERTEKIN, C. and YALDIZ, O. 2002. A research on the drying of fig by a solar dryer and determination of drying behaviour. In Proceedings of the 8th International Congress on Mechanization and Energy in Agriculture, October 15–17, Kusadasi, Turkey, pp. 210–215. ERTEKIN, C. and YALDIZ, O. 2011. Thin layer convective air drying of onion. In Proceedings of the XXXIV CIOSTA CIGR V Conference 2011, Efficient and Safe Production Processes in Sustainable Agriculture and Forestry, June 29–July 1, Vienna, Austria. FATHIMA, A., BEGUM, K. and RAJALAKSHMI, D. 2001. Microwave drying of selected greens and their sensory characteristics. Plant. Food Hum. Nutr. 56, 303–311. FATOUH, M., METULLY, M.N., HELALI, A.B. and SHEDID, M.H. 2006. Herbs drying using a heat pump dryer. Energ. Convers. Manage. 47, 2629–2643. GHAZANFARI, A., EMAMI, S., TABIL, L.G. and PANIGRAHI, S. 2006. Thin-layer drying of flax fiber: II. Modeling drying process using semi-theoretical and empirical models. Dry. Technol. 24, 1637–1642.

1488

C. ERTEKIN and N. HEYBELI

GUREL, A.E., YILMAZ, S. and CEYLAN, I. 2010. Experimental analysis of solar dryer and humidity controlled. e-J. N. World Sci. Acad. Technol. Appl. Sci. 5, 178–187. HAGHI, A.K. and ANGIZ, F.Z. 2007. Heat and mass transfer in thermal drying of wool: A theoretical approach. In Proceedings of the 5th Asia-Pasific Drying Conference, Hong Kong, pp. 443–448. HEBBAR, H.U. and RASTOGI, N.K. 2001. Mass transfer during infrared drying of cashew kernel. J. Food Eng. 47, 1–5. HEYBELI, N. and ERTEKIN, C. 2011. Effects of different drying techniques on apple drying process: A review. In Proceedings of the VI. International CIGR Technical Symposium on Towards a Sustainable Food Chain-Food Process, Bioprocessing and Food Quality Management, April, Nantes, France (CD). HII, C.L., LAW, C.L. and CLOKE, M. 2009. Modeling using a new thin layer drying model and product quality of cocoa. J. Food Eng. 90, 191–198. JAZINI, M.H. and HATAMIPOUR, M.S. 2010. A new physical pretreatment of plum for drying. Food Bioprod. Process. 88, 133–137. JENA, S. and DAS, H. 2007. Modelling for vacuum drying characteristics of coconut presscake. J. Food Eng. 79, 92–99. JEZEK, D., TRIPALO, B., BRNCIC, M., KARLOVIC, D., BRNCIC, S.R., VIKIC-TOPIC, D. and KARLOVIC, S. 2008. Dehydration of celery by infrared drying. Croatica Chem. Acta. CCACAA 81, 325–331. KADAM, D.M., GOYAL, R.K., SINGH, K.K. and GUPTA, M.K. 2011. Thin layer convective drying of mint leaves. J. Med. Plants Res. 5, 164–170. KALETA, A. and GORNICKI, K. 2010. Some remarks on evaluation of drying models of red beet particles. Energ. Convers. Manage. 51, 2967–2978. KANE, C.S.E., SID’AHMED, M.A.O. and KOUHILA, M. 2009. Evaluation of drying parameters and sorption isotherms of mint leaves (M. pulegium). Rev. Energ. Renouvel. 12, 449–470. KAUR, A., KAUR, D., OBEROI, D.P.S., GILL, B.S. and SOGI, D.S. 2008. Effect of dehydration on physicochemical properties of mustard, mint and spinach. J. Food Process. Pres. 32, 103–116. KAYA, A. and AYDIN, O. 2009. An experimental study on drying kinetics of some herbal leaves. Energ. Convers. Manage. 50, 118–124. KOCABIYIK, H. and DEMIRTURK, B.S. 2008. Infrared radiation drying of mint leaves. J. Tekirdag Agric. Fac. 5, 239–246. KOCABIYIK, H. and TEZER, D. 2009. Drying of carrot slices using infrared radiation. Int J. Food Sci. Technol. 44, 953–959. KUMAR, D.G.P., HEBBAR, H.U. and RAMESH, M.N. 2006. Suitability of thin layer models for infrared–hot air-drying of onion slices. LWT 39, 700–705. KUROZAWA, L.E., AZOUBEL, P.M., MURR, F.E.X. and PARK, K.J. 2011. Drying kinetic of fresh and osmotically dehydrated mushroom (Agaricus blazei). J. Food Process Eng. 35(2), 295–313.

Journal of Food Processing and Preservation 38 (2014) 1480–1490 © 2013 Wiley Periodicals, Inc.

C. ERTEKIN and N. HEYBELI

LEBERT, A., THARRAU, H., ROCHA, T. and MARTYAUDOUIN, C. 1992. The drying kinetics of mint. J. Food Eng. 17, 15–28. LEMUS-MONDACA, R., BETORET, N., VEGA-GALVEZ, A. and LARA-ARAVENA, E. 2009. Dehydration characteristics of papaya (Carica pubenscens): Determination of equilibrium moisture content and diffusion coefficient. J. Food Eng. 32, 645–663. MENGES, H.O. and ERTEKIN, C. 2006. Modelling of air drying Hacihaliloglu-type apricots. J. Sci. Food Agric. 86, 279–291. MIDILLI, A. and KUCUK, H. 2003. Mathematical modeling of thin layer drying of pistachio by using solar energy. Energ. Convers. Manage. 44, 1111–1122. MUNDADA, M., HATHAN, B.S. and MASKE, S. 2010. Convective dehydration kinetics of osmotically pretreated pomegranate arils. Biosyst. Eng. 107, 307–316. MUTLU, A. and ERGUNES, G. 2008. Tomato drying by shelfed solar dryer. Tarim Bilim Derg. 1, 61–68. (in Turkish). NAGHAVI, Z., MOHEB, A. and ZIAEI-RAD, S. 2010. Numerical simulation of rough rice drying in a deep-bed dryer using non-equilibrium model. Energ. Convers. Manage. 51, 258–264. NASIROGLU, S. and KOCABIYIK, H. 2008. Thin-layer infrared radiation drying of red pepper slices. J. Food Process Eng. 32, 1–16. NAYAK, S., KUMAR, A., MISHRA, J. and TIWARI, G.N. 2011. Drying and testing of mint (Mentha piperita) by a hybrid photovoltaic-thermal (PVT)-based greenhouse dryer. Dry. Technol. 29, 1002–1009. NIMMOL, C., DEVAHASTIN, S., SWASDISEVI, T. and SOPONRONNARIT, S. 2007. Drying of banana slices using combined low-pressure superheated steam and far-infrared radiation. J. Food Eng. 81, 624–633. NOWAK, D. and LEWICKI, P.P. 2004. Infrared drying of apple slices. Innov. Food Sci. Emerg. 5, 353–360. NOWAK, D. and LEWICKI, P.P. 2005. Quality of infrared dried apple slices. Dry. Technol. 23, 831–846. OZBEK, B. and DADALI, G. 2007. Thin-layer drying characteristics and modelling of mint leaves undergoing microwave treatment. J. Food Eng. 83, 541–549. PARK, K.J., VOHNIKOVA, Z. and BROD, F.P.R. 2002. Evaluation of drying parameters and desorption isotherms of garden mint leaves (Mentha crispa L.). J. Food Eng. 51, 193–199. PATHARE, P.B. and SHARMA, G.P. 2006. Effective moisture diffusivity of onion slices undergoing infrared convective drying. Biosyst. Eng. 93, 285–291. PURKAYASTHA, M.D., NATH, A., DEKA, B.C. and MAHANTA, C.L. 2011. Thin layer drying of tomato slices. J. Food Sci. Technol. 50, 642–653. ROCHA, T., LEBERT, A. and AUDOUIN, C.M. 1992. Effect of drying conditions and of blanching on drying kinetics of mint (Mentha spicata Huds.) and basil (Ocimum basilicum). In Proceedings of the Drying’92. pp. 1360–1368.

SUITABLE DRYING MODEL FOR INFRARED DRYING OF MINT

SACILIK, K., KESKIN, R. and ELICIN, A.K. 2006. Mathematical modeling of solar tunnel drying of thin layer organic tomato. J. Food Eng. 73, 231–238. SALEH, A. and BADRAN, I. 2009. Modeling and experimental studies on a domestic solar dryer. Renew Energ. 34, 2239–2245. SENADEERA, W., BHANDARI, B.R., YOUNG, G. and WIJESINGHE, B. 2003. Influence of shapes of selected vegetable materials on drying kinetics during fluidized bed drying. J. Food Eng. 58, 277–283. SHARMA, G.P., VERMA, R.C. and PATHARE, P. 2005. Mathematical modeling of infrared radiation thin layer drying of onion slices. J. Food Eng. 71, 282–286. SHI, J., PAN, Z., MCHUGH, T.H., WOOD, D., ZHU, Y., AVENA-BUSTILLOS, R.J. and HIRSCHBERG, E. 2008. Effect of berry size and sodium hydroxide pretreatment on the drying characteristics of blueberries under infrared radiation heating. J. Food Sci. 73, 237–245. SOYSAL, Y. 2005. Mathematical modeling and evaluation of microwave drying kinetics of mint. J. Appl. Sci. 5, 1266–1274. SOYSAL, Y. and OZTEKIN, S. 2001. Technical and economic performance of a tray dryer for medicinal and aromatic plants. J. Agric. Eng. Res. 79, 73–79. SOYSAL, Y., OZTEKIN, S., ISIKBER, A.A., DUMAN, A.D. and DAYISOGLU, K.S. 2005. Kurutulmus kirmizi biberde rengin bir kalite parametresi olarak onemi. In Proceedings of the III. Tarımsal Urunleri Kurutma Teknigi Calistayi, 2–4 Mayıs, Antalya (in Turkish). SOYSAL, Y., OZTEKIN, S. and EREN, O. 2006. Microwave drying of parsley: Modelling, kinetics, and energy aspects. Biosyst. Eng. 93, 403–413. SRIPINYOWANICH, J. and NOOMHORM, A. 2011. A new model and quality of unfrozen and frozen cooked rice dried in a microwave vibro-fluidized bed dryer. Dry. Technol. 29, 735–748. SUN, J., HU, X., ZHAO, G., WU, J., WANG, Z., CHEN, F. and LIAO, X. 2007. Characteristics of thin-layer infrared drying of apple pomace with and without hot air pre-drying. Food Sci. Technol. Int. 13, 91–97. SWASDISEVI, T., DEVAHASTIN, S., SA-ADCHOM, P. and SOPONRONNARIT, S. 2009. Mathematical modeling of combined far-infrared and vacuum drying banana slice. J. Food Eng. 92, 100–106. TARHAN, S., TELCI, I., TUNCAY, M.T. and POLATCI, H. 2010. Product quality and energy consumption when drying peppermint by rotary drum dryer. Ind. Crop. Prod. 32, 420–427. TARHAN, S., TELCI, I., TUNCAY, M.T. and POLATCI, H. 2011. Peppermint drying performance of contact dryer in terms of product quality, energy consumption, and drying duration. Dry. Technol. 29, 642–651. THERDTHAI, N. and ZHOU, W. 2009. Characterization of microwave vacuum drying and hot air drying of mint leaves (Mentha cordifolia Opiz ex Fresen). J. Food Eng. 91, 482–489.

Journal of Food Processing and Preservation 38 (2014) 1480–1490 © 2013 Wiley Periodicals, Inc.

1489

SUITABLE DRYING MODEL FOR INFRARED DRYING OF MINT

TIRAWANICHAKUL, S., TIRAWANICHAKUL, Y. and SNISO, E. 2008. Paddy dehydration by adsorption: Thermo-physical properties and diffusion model of agriculture residues. Biosyst. Eng. 99, 249–255. TOGRUL, H. 2005. Simple modeling of infrared drying of fresh apple slices. J. Food Eng. 71, 311–323. TOGRUL, H. 2006. Suitable drying model for infrared drying of carrot. J. Food Eng. 77, 610–619. TOGRUL, I.T. and PEHLIVAN, D. 2003. Modelling of drying kinetics of single apricot. J. Food Eng. 58, 23–32. TOGRUL, I.T. and PEHLIVAN, D. 2004. Modelling of thin layer drying kinetics of some fruit under open-air sun drying process. J. Food Eng. 65, 413–425.

1490

C. ERTEKIN and N. HEYBELI

VEGA-GALVEZ, A., ANDRES, A., GONZALEZ, E., NOTTE-CUELLO, E., CHACANA, M. and LEMUS-MONDACA, R. 2009. Mathematical modelling on the drying process of yellow squat lobster (Cervimunida jhoni) fishery waste for animal feed. Anim. Feed Sci. Technol. 151, 268–279. WANG, D.C., FON, D.S., FANG, W. and SOKHANSANJ, S. 2004. Development of a visual method to test the range of applicability of thin layer drying equations using MATLAB tools. Dry. Technol. 22, 1921–1948.

Journal of Food Processing and Preservation 38 (2014) 1480–1490 © 2013 Wiley Periodicals, Inc.

Suggest Documents