Evaluation of Thin-layer Drying Models for Jerusalem Artichoke (Helianthus tuberosus L.) Tubers in Different Drying Methods




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Evaluation of Thin-layer Drying Models for Jerusalem Artichoke (Helianthus tuberosus L.) Tubers in Different Drying Methods
Running head: Evaluation of thin-layer models for Jerusalem artichoke tubers in different drying methods
Orraya Porniammongkol, Wasan Duangkhamchan*, Sudathip Inchuen
Department of Food Technology and Nutrition, Faculty of Technology, Mahasarakham University, Kamriang, Kantarawichai, Mahasarakham 44150, Thailand. Tel. 0-4375-4085; Fax. 0-4375-4069; E-mail: wasan.d@msu.ac.th

*Corresponding author
Abstract

This paper presents the evaluation of thin-layer models for Jerusalem artichoke (Helianthus tuberosus L.) tubers in different drying methods. The slices of Jerusalem artichoke (Helianthus tuberosus L.) were dried in hot-air oven at 60C, in microwave oven with 200 W, under open-air sun and under shade until moisture content of approximately 10% (dry basis) was reached. In addition, blanching was used in order to investigate the influence of pre-treatment. The experimental data of drying kinetics was fitted to various well-known theoretical models using nonlinear regression analysis. The suitTable choice of prediction was made based on the coefficient of determination (R2), the root mean square error (RMSE), and the chi-square (2). Among several drying models tested, the Midilli et al. model gave the best fit for the convective hot-air drying and microwave drying method for both blanched and unblanched samples, while the approximation of diffusion model and the modified Page model were the best choices for the shade drying of blanched and unblanched samples, respectively. In addition, the experimental results obtained by the open-air sun drying method were suitably fitted to the Midilli et al. model and the approximation of diffusion model for blanched and unblanched samples, respectively. The effective diffusivity coefficient, Deff, for different drying methods were estimated, ranging from 0.16515x10-9 m2/s to 15.6450x10-9 m2/s. Furthermore, in order to investigate the effect of drying methods on quality of Jerusalem artichoke powders, color and browning index were determined. It was found that drying methods and pre-treatment affected color and browning index of Jerusalem artichoke powders.
Keywords: Jerusalem artichoke, drying kinetics, diffusivity coefficient, drying model, browning index

Introduction

Jerusalem artichoke (Helianthus tuberosus L.) is the perennial vegeTable plant with high sugar content (Wang et al., 2013; Matías et al., 2011). Similar to potato, it consists of tubers in which valuable nutrients are accumulated (Baltacioğlu et al., 2012). Jerusalem artichoke, originated from the North America, grows well in poor soil with high tolerance to frost and various plant diseases (Ge et al., 2010) irrespective to climate conditions (Saengthongpinit and Sajjaanantakul, 2005; Takeuchi and Nagashima, 2011; Baltacıoğlu and Esin, 2012) without any special breeding technique. Therefore its tubers can be produced worldwide (Takeuchi and Nagashima, 2011; Baltacıoğlu and Esin, 2012). Besides known as an alternative source of carbohydrate and inulin (14-15%) (Nadir et al., 2011), Jerusalem artichoke tubers contain 79.8% water, 16.6% carbohydrate, 1% protein, 16.6% crude fiber, 2.8% ash (Jilu et al., 2003), and traces of polyphenol (Baltacıoğlu and Esin, 2012). As a result of containing high amount of inulin, a non-digestible oligosaccharide, instead of starch as carbohydrate reserve, Jerusalem artichoke tubers have been increasingly used as functional food ingredients in various foods. Consequently, many attempts have been made to use the tubers to prevent diabetes and to use as anti-carcinoma, as reported in (Kaur and Gupta, 2002; Pan et al., 2009). In addition, they have been used in the diet of patients with certain diseases due to low amounts of polyamines (Righetti et al., 2008). From this point of view, consumption of Jerusalem artichoke in daily diet may support healthier life of consumers (Baltacıoğlu and Esin, 2012). However, due to changes in consumer lifestyles, the alternative forms of Jerusalem artichoke tubers, commonly eaten as vegeTable, have been processed to meet the new requirements (Gedrovica and Karklina, 2011). Among various products including powders, juices, extracted inulin, fructose and fructo-oligosaccharide (Nadir et al., 2011), Jerusalem artichoke processed in powder could be well applied as food ingredients in food applications (Gedrovica and Karklina, 2011). The Jerusalem artichoke powders are commonly prepared by drying slices at either 60 or 70C in an oven for 5 h or until expected moisture content is reached. The dried slices of Jerusalem artichoke tubers are subsequently milled to produce a fine powder with particles less than 1.0 mm in diameter (Takeuchi and Nagashima, 2011).

In addition to serving as a traditional method of food preservation, drying is also used for the production of special foods and food ingredients (Evin, 2012; Maroulis and Saravacos, 2003; Zhang et al., 2006). Up till now, many drying techniques have been investigated regarding energy efficiency, operating cost and effects on finished product properties (Mota et al., 2010; Tulek, 2011; Therdthai and Zhou, 2009; Doymaz, 2004; Toğrul and Pehlivan, 2004; Evin, 2012; Olawale and Omole, 2012; Mirzaee et al., 2010; Midilli et al., 2002). Open-air sun drying are an immemorial method to dry grains, vegeTablesvegetables, fruits and other agricultural products. It brings an advantage in term of low cost operation. However, this technique is not taken into consideration when large-scale production is concerned due to lack of ability to control the drying operation properly, long drying time, weather uncertainties, high labor costs, large area requirement and so on (Toğrul and Pehlivan, 2004). Hot-air drying is known as a common technique providing more energy efficiency, the ease and convenient operation compared to the former. Moreover, microwave drying is an alternative method in which drying time is greatly reduced by applying microwave energy to the drying material, resulting in remaining quality of finished product (Evin, 2012).

Mathematical modeling, recognized as the effective technique for the design and optimization of processes, has been widely used for analyzing a drying process of agricultural and food products (Cao et al., 2003). Many attempts focusing on this technique have been made to account for thin layer drying to describe the drying phenomena in a unified way, regardless of the controlling mechanism (Mota et al., 2010; Tulek, 2011; Therdthai and Zhou, 2009; Evin, 2012; Olawale and Omole, 2012; Mirzaee et al., 2010; Midilli et al., 2002). To our knowledge, little information has been reported on the drying behavior of Jerusalem artichoke (Helianthus tuberosus L.) tubers which can be served as a basis for design and process optimization. Therefore, the main objectives of this study are to: (1) investigate the drying kinetics of Jerusalem artichoke (Helianthus tuberosus L.) tubers for different drying methods, (2) model the thin layer drying of Jerusalem artichoke (Helianthus tuberosus L.) tubers by fitting well-known mathematical drying models to the experimental data obtained by different drying methods, (3) calculate the effective diffusivities of Jerusalem artichoke (Helianthus tuberosus L.) tubers for different drying methods, and (4) investigate the influences of drying method and blanching as pretreatment on physical properties of dried Jerusalem artichoke (Helianthus tuberosus L.) tubers.



Materials and Methods

Mathematical Descriptions

Thin-layer Drying Models

To account for the thin-layer drying characteristics, an one-parameter, two two-parameter, two three-parameter, and two four-parameter models used in this work are listed below (More details concerning each following model, the reader is should referred to Celma et al., 2007):



One parameter

Lewis




(1)

Two parameters

Modified Page





(2)

Henderson and Pabis



(3)

Three parameters

Logarithmic





(4)

Approximate of diffusion



(5)

Four parameters

Two term




(6)

Midilli et al.



(7)

where MR is the moisture ratio (MR = (Mt – Me)/(Mi – Me)); Mt is a moisture content at a certain time (g water/g dry solid), Me is an equilibrium moisture content (g water/g dry solid), and Mi is an initial moisture content (g water/g dry solid). t is drying time (min). a, b, c, k, k1 and k0 are equation’s constant, and n is a power constant.

A non-linear regression analysis was initially used to determine the best fitted values of parameters for each drying condition. The quadratic functions were subsequently formulated to provide the exact fitting relationship between the drying temperature and the parameters obtained in the drying equation. The accuracy of fit was evaluated by the coefficient of determination (R2), the root mean square error (RMSE), and the reduced chi-square (2). The RMSE and 2 can be calculated as follows:





(8)



(9)

where Vobs and Vpre are the observed value and the corresponding predicted one according to the model being used, N is the number of observations, and z is the number of parameters, e.g. a, b, c, k, k1 and k0, used in each equation. In the above equations, the RMSE and 2 aim at comparing the consistency between the experimental and predicted moisture ratios, and when they approach zero it indicates that the prediction is closer to the experimental data (Mota et al., 2010; Lee and Kim, 2009; Robert et al., 2008).
Estimation of the Effective Diffusivities (Deff)

As mostly taking place for food materials, the falling-rate period plays an important role in drying as moisture transfer is dominated by internal diffusion (Tulek, 2011). Crank (1975) has expressed the diffusion according to Fick’s second law for unsteady state to describe the drying process during the falling-rate period as follow:





(10)

where Deff is the effective moisture diffusivity (m2/s) representing the conductive term of all moisture transfer mechanisms, M is the moisture content (dry basis), and t is time (s).

Assuming a uniform initial moisture content, constant effective diffusivity throughout a slab thin layer sample, and negligible shrinkage, the analytical solution of Equation (10) given by Crank (1975) is expressed by:





(11)

where L is the half thickness of the slab thin layer sample (m), and n is a positive integer. In practice, only the first term of Equation (11) is considered, yielding:



(12)

Taking natural logarithm, Equation (12) becomes a straight line of the form y = y0 + ax, as follow:



(13)

where



(14)



(15)

Thus, the effective moisture diffusivity (Deff) can be estimated for each operating condition from the slope (a) of the plot of ln (MR) as a function of time (t), Equation (15).
Drying Experiments

Samples

Freshly cultivated Jerusalem artichoke tubers (Helianthus tuberosus L.) were purchased from the farm located in the North East of Thailand. They were sorted according to uniform maturity and size. After being cleaned, Jerusalem artichoke (Helianthus tuberosus L.) tubers were peeled and subsequently sliced to 1 mm thickness to provide slabsthe thin layer samples. The prepared Jerusalem artichoke (Helianthus tuberosus L.) samples were divided into two portions. The fresh portion served as the control, while the remaining portion was blanched in order to reduce the initial microbial load and inactivate enzymes. Blanched samples were done in boiling water for 1 min and subsequently cooled under running tap water. Prior to drying processes, the average initial moistures contents of each portion were determined using the AOAC method (AOAC, 2002).


Drying Procedures

Each of prepared portions mentioned previously was dried by different drying methods including convective hot-air drying, microwave drying, open-air sun drying, and shade drying. The slices of Jerusalem artichoke (Helianthus tuberosus L.) were dried in hot-air oven at 60C, in microwave oven with 200 W, under open-air sun and under shade until moisture content of approximately 10% (dry basis) was reached. During drying processes, the moisture contents of the samples were determined at different time intervals; 10 mins, 2 mins, 120 mins, and 360 mins, for hot air drying, microwave drying, open-air sun drying, and shade drying, respectively. The dried samples obtained by all drying methods were immediately ground to provide Jerusalem artichoke (Helianthus tuberosus L.) powders for further analyses. They were subsequently packed in polyethylene bagaluminium foil and stored in cool dry placea freezer to prevent the additional moisture from the surroundings until used for various physical analyses. Both dried samples with and without pre-treatment were physically analyzed for browning index and color, as described following.

Soluble materials were extracted by incubating 1.0 g of the dried powder with 15 ml distilled water for 20 min at 80 C (Takeuchi and Nagashima, 2011). They were subsequently filtered with No.1 Whatman paper. The filtrate was diluted with an equal volume of 95% ethanol and then centrifuged at 4,000 rpm at 4 C for 15 min. The absorbance of supernatant was measured at 420 nm using a spectrophotometer. The browning index was expressed in terms of the absorbance (Abs)/g dry mater (Inchuen, 2009).

The color of fresh and dry-powdered Jerusalem artichoke was measured using a Minolta CR 300 colorimeter (Konica-Minolta, Japan). The color system used was Hunter L*a* b* (considering standard illumination D65 and observer 2). The color brightness coordinate L* measured the whiteness value, ranging from black at 0 to white at 100. The chromaticity coordinate a* measured red when positive and green when negative, chromaticity coordinate b* measured yellow when positive and blue when negative (Inchuen, 2009).


Results and Discussion

Evaluation of Thin-layer Drying Models

Thin-layer drying experiments of blanched and unblanched Jerusalem artichoke (Helianthus tuberosus L.) samples were performed by means of different methods including the convective hot-air drying, the microwave drying, the shade drying, and the open-air sun drying. The initial moisture contents of blanched and unblanched samples, approximately 600-740 % (dry basis), decreased until a certain moisture content less than 10% (dry basis) or the equilibrium moisture content were reached for each drying condition, as shown in Figure 1(a-d). It was found from these Figures that with various drying methods, obvious difference in drying time was observed. Among drying methods tested, microwave drying took shortest time to reach the desired moisture content, followed by hot air, open-air sun, and shade drying. It could be explained by the larger driving force for heat transfer. This finding was also found by Karacabey et al. (2011). Similar results were observed for blanched Jerusalem artichoke slices. However, it was found from Figure 1(a-d) that blanching affected the drying kinetics of samples, lower drying rate at the period before reaching the equilibrium for all drying methods. This trend was an opposite behavior found in literature (Leeratanarak et al., 2006; Kuitche et al., 2007; Olawale and Omole, 2012) in which the blanched samples were observed to dry faster than the unblanched ones. The excessive blanching time decreasing the rate of moisture removal could be the possible explanation. Leeratanarak et al. (2006) investigated the effect of blanching time on the drying rate of potato chips in different drying methods. They found that suiTablesuitable blanching time could facilitate the moisture movement, otherwise excess water content absorbed during longer blanching was found, resulting in lower drying rate.

In order to assess the suiTablesuitable choice of using the thin-layer drying models for Jerusalem artichoke (Helianthus tuberosus L.) tubers, the highest R2 values, and the lowest RMSE and 2 values were used as a criterion. The goodness-of-fit values for each drying conditions obtained from the thin-layer drying models proposed in the literature (Equations 1-7) are presented in Tables 1-4. The results showed that the model expressed by Midilli et al. (2002), containing four parameters gave the best consistency with the experimental data for the convective hot-air drying and the microwave drying methods for both treated and untreated samples. It obtained the highest R2 and the lowest RMSE. However, when comparing the 2, the coefficient of performance based on both a number of data and parameters being used in a model, the modified Page model gave the value closer to zero, meaning that this model was more suitable when the complexity of model parameters was concerned. From this, it could be confirmed that besides the Page, modified Page and logarithmic models found to be the best in many instances (Falade and Solademi, 2010; Doymaz, 2011), the Midilli et al. model was useful for practical proposes. This finding is in agreement with other results reported for microwave drying of Jerusalem artichoke (Helianthus tuberosus L.) tubers (Karacabey et al., 2011) and other products such as apricot and ginger reported by (Mirzaee et al., (2010) ;and Loha et al., ( 2012), respectively. However, factors such as types of samples, drying conditions, and drying methods are known as the influence on drying kinetics, resulting in different drying models used (Olawale and Omole, 2012). It was evident in this work that not only the Midillie et al. model was a good fit to experimental data, but the others such as the approximation of diffusion model and the modified Page model were also a good choice, especially for the shade drying, for blanched and unblanched samples, respectively (Table 3). In addition, Table 4 shows that the model proposed by Midilli et al. (2002) and the approximation of diffusion model were considered to be the most suitable ones for treated and untreated samples dried by the open-air sun drying method, respectively. The model parameters of the selected thin-layer drying models for each drying methods and both blanched and unbleached Jerusalem artichoke samples are presented in Table 5.
Estimation of diffusivity coefficient (Deff)

Table 6 presents the results of the fitting to Equation (13), which allowed calculating the values of the diffusivity coefficients, Deff, for different drying methods by Equations (14) and (15). The values of the correlation coefficients varied from 0.91848 for the microwave drying of blanched samples to 0.98773 for the shade drying of blanched samples. It could be also observed from Table 6 that the effective diffusivity coefficients were different with the various drying methods used for both blanched and unblanched samples. The microwave drying gave the maximum Deff of 15.6450x10-9 m2/s and 15.6399 x10-9 m2/s for blanched and unblanched samples, respectively, followed by the hot-air, open-air sun, and shade drying for both treated and untreated samples. It could be explained by the fact that in microwave drying, thermal energy used for heat transfer was higher compared with other drying methods investigated in this work, resulting in larger driving force and higher moisture diffusivity.


Color and Browning Index

Table 7 illustrates the color values and the browning index of Jerusalem artichoke (Helianthus tuberosus L.)powder obtained from sliced tubers dried by different methods under pre-treatment conditions. In a case of lightness (L*), drying method significantly affected the lightness of both blanched and unblaned samples. The L* value of dried samples obtained by the hot-air drying was highest, followed by the open-air sun drying, the shade drying, and the microwave drying. In microwave drying, the dried blanched and unblanched Jerusalem artichoke tuber slices were darkest probably due to heat damage resulting from inappropriate microwave output power (200 W) used. When compared to the faster hot-air drying, the shade and open-air sun drying utilizing lower thermal energy obtained darker dried samples, resulting from the browning effect.

Regarding the redness of dried Jerusalem artichoke tuber slices, drying method significantly affected a* value for blanched samples, ranging from 1.2670.115 to 2.9670.058. Different trend could be observed for unblanched samples. The redness of Jerusalem artichoke tuber slices dried by the microwave and shade drying method were similar and highest compared with those obtained by other two methods. The effect of browning reaction could be possible explanation for the shade drying, while burning may cause the redder microwave-dried samples. For the effect of pre-treatment, the redness of blanched Jerusalem artichoke tuber slices highly decreased in the microwave drying. This influence was probably due to the excessive water absorbed during blanching which was not affected by heat damage resulting in redder dried samples, compared with unblanched ones at the same microwave power and drying time. The decrease in a* value was also found for the shade drying of blanched Jerusalem artichoke tuber slices. In a case of shade drying, the effect of blanching on the redness could be explained by the browning reaction taking place during the long period of drying. In contrast, the unexpected redder samples were observed for blanched samples in the open-air sun drying. However, the influence of blanching was not observed when regarding the hot-air drying.

For the effect of drying method and blanching of Jerusalem artichoke tuber on yellowness, the obvious trend was not observed. The different b* values were significant with different drying methods under blanching condition, while dried samples obtained by the hot-air drying and open-air sun drying were insignificant. Taking the effect of blanching into consideration, the yellowness of samples dried by the hot-air method increased, while a decrease in this value was observed when the shade drying used. The insignificant influence of blanching was not found for the microwave and open-air sun drying.

The effects of blanching and drying method on the browning index of Jerusalem artichoke (Helianthus tuberosus L.) tuber slices are also presented in Table 7. The results showed significant decreasing browning index for all drying methods, when regarding the influence of blanching. From this, it could be concluded that blanching in boiling water for 1 min could be sufficient to inactivate enzymes which are the cause of browning reaction. However, when the effect of drying on browning index was concerned, the trend could not be obviously captured. Surprisingly, the browning indices of both blanched and unblanched Jerusalem artichoke (Helianthus tuberosus L.) tuber slices dried by the open-air sun drying were lower than those of the microwave-dried and hot-air-dried samples. This might be due to the higher degree of non-enzymatic browning (Mailard reaction) occurring during microwave and hot-air drying. Since Jerusalem artichoke (Helianthus tuberosus L.) tubers contain high essential amino acid and reducing sugar (Aleknaviciene et al., 2009), the Mailard reaction resulting from a reaction between those two chemicals takes place, usually requiring heat.
Conclusions

The thin-layer drying models for different drying methods and pre-treatment were evaluated in this study. The drying methods and blanching were found to have difference in suiTablesuitable selection of the theoretical models. The Midilli et al. model gave the best fit for the hot-air drying and microwave drying method for both blanched and unblanched samples, while the approximation of diffusion model and the modified Page model were good choices for the shade drying of blanched and unblanched samples, respectively. In a case of open-air sun drying, the Midilli et al. model and the approximation of diffusion model were suiTablesuitable for blanched and unbalanced samples, respectively. The effective diffusivity coefficients for different drying methods were also estimated in this work. These values were different with the various drying methods and pre-treatment, ranging from 0.16515x10-9 m2/s to 15.6450x10-9 m2/s. Color and browning index of Jerusalem artichoke powders were examined in order to investigate the effects of drying methods and pre-treatment. In terms of lightness (L*) and browning index, drying methods and blanching were found to have obvious effects. The L* value of dried samples obtained by hot-air drying was highest, followed by open-air sun drying, shade drying and microwave drying for both blanched and unblanched samples, while the decrease in browning index with the use of pre-treatment was observed for all drying methods.


Acknowledgements

The authors gratefully acknowledge Mahsarakham University for financial support of this research.


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Figure 1. Drying kinetics of Jerusalem artichoke tubers in (a) microwave drying (b) hot-air drying (c) shade drying and (d) open-air sun drying; blanching (triangle) and unblanching (square)
Table 1. The goodness-of-fit values for the convective hot-air drying

Model name

Blanched

Unblanched

R2

RMSE

2

R2

RMSE

2

Lewis

Modified Page

Henderson&Pabis

Logarithmic

Approximation of diffusion

Two-term


Midilli et al.

0.971061

0.982192


0.972158

0.97601


0.982195

0.972158


0.98301

0.054131

0.042461


0.053230

0.0498911

0.042426

0.053230


0.041154

0.0032174

0.0021131

0.0033349

0.0031110

0.0023340

0.0041093



0.0024446

0.995477

0.99804


0.995489

0.99703


0.998788

0.998788


0.99823

0.020685

0.012314


0.0199893

0.0152156

0.012814

0.012814


0.011716

0.0005464

0.0002179

0.0005468

0.0003299

0.000213

0.000237


0.0002198


In every table, please use bpld font for the best model and please consider to reduce the decimal points. For example, for R2, it should not be more than 3 decimal points.

Table 2. The goodness-of-fit values for the microwave drying

Model name

Blanched

Unblanched

R2

RMSE

2

R2

RMSE

2

Lewis

Modified Page

Henderson&Pabis

Logarithmic

Approximation of diffusion

Two-term


Midilli et al.

0.98549

0.99137


0.98640

0.998781


0.99208

0.98640


0.99822

0.036321

0.028009


0.0352168

0.014102


0.026833

0.0352168



0.012723

0.001421

0.000915


0.001443

0.000253


0.000916

0.001732


0.000227

0.97559

0.97809


0.976562

0.98918


0.978993

0.976562


0.991068

0.046142

0.043711


0.046109

0.030715


0.041837

0.046109


0.028505

0.0023293

0.002229


0.0025480

0.001201


0.002228

0.00302976



0.001138


Table 3. The goodness-of-fit values for the shade drying

Model name

Blanched

Unblanched

R2

RMSE

2

R2

RMSE

2

Lewis

Modified Page

Henderson&Pabis

Logarithmic

Approximation of diffusion

Two-term


Midilli et al.

0.98717

0.99615


0.988782

0.79359


0.99647

0.99647


0.65654

0.0314365

0.0172180

0.030559

0.125813


0.0165460

0.0165459

0.1623293


0.0011073

0.000354


0.001121

0.021105


0.0004361

0.000406


0.039509

0.98233

0.997668

0.983284


0.84800

0.99647


0.99647

0.758785


0.0361084

0.015650

0.035555


0.105824

0.016127


0.016127

0.1336566



0.001420

0.0003294

0.001517


0.014932

0.000347


0.0004390

0.0268760




Table 4. The goodness-of-fit values for the open-air sun drying

Model name

Blanched

Unblanched

R2

RMSE

2

R2

RMSE

2

Lewis

Modified Page

Henderson&Pabis

Logarithmic



Approximation of diffusion

Two-term


Midilli et al.

0.961081

0.99283


0.962180

0.963274


0.99356

0.962180


0.997672

0.0593275

0.024350


0.058520

0.0578797

0.024033

0.058520


0.0165482

0.003514

0.000701


0.003736

0.004009


0.0007693

0.0046566



0.0004392

0.979862

0.98958


0.979884

0.98239


0.99039

0.979884


0.92904

0.0418760

0.028012


0.041550

0.037903


0.02807999

0.041550


0.0761082

0.001744

0.000927


0.0019883

0.001724


0.000941

0.002302


0.007718


Table 5. The parameters of the selected models for different drying methods


Drying methods

Pre-treatment

Model

Parameters

Hot air


blanched

unblanched




Midilli et al.

Midilli et al.




a = 0.960443

k = 0.007894

n = 1.400880

b = 0.000046

a = 0.998983

k = 0.077100

n = 0.881481

b = 0.000076



Microwave


blanched

unblanched



Midilli et al.

Midilli et al.




a = 0.999493

k = 0.094409

n = 0.927417

b = -0.005727

a = 0.986608

k = 0.119185

n = 0.793363

b = 0.008575



Shade

blanched

unblanched



Approximation of diffusion

Modified Page



a =0.278727

k = 0.038315

b = 0.035445

k = 0.002587

n = 0.668000


Open-air sun

blanched

unblanched



Midillie et al.

Approximation of diffusion



a = 1.009899

k = 0.000045

n = 1.971890

b = 0.000024

a = -1.68387

k = 0.168116



b = 0.085320


Table 6. Estimated effective diffusivity coefficients for different drying methods


Method

Blanched

Unblanched

R2

y0

a

Deff

(x10-9m2/s)

R2

y0

a

Deff

(x10-9m2/s)

Hot air

0.95910

0.00462

-0.040108

4.06095

0.96411

-0.39232

-0.03590

3.63743

Microwave

0.91848

0.41181

-0.15441

15.6450

0.932198

0.37195

-0.154436

15.6399

Shade

0.988773

-0.09080

-0.00163

0.16515

0.97439

-0.242439

-0.001656

0.158106

Open-air sun

0.94907

0.19872

-0.009988

1.00105

0.94324

0.06175

-0.00935

0.94735


Table 7. Browning Index and color in terms of L* a* b* values of dried Jerusalem artichoke (Helianthus tuberosus L.) tuberpowder in different drying methods

Pre-treatment

Drying method

L*

a*

b*

Browning Index

unblanched

Fresh

-

-

-


A0.119±(0.001)c




Microwave drying

A51.533±(0.231)d

A5.100±(0.173)a

ns17.067±(0.473)b


A0.128±(0.001)b




Hot-air drying

A87.267±(0.058)a

ns1.233±(0.153)c

B11.667±(0.321)d


A0.123±(0.001)bc




Open-air sun drying

A83.200±(0.100)b

B1.833±(0.058)b

ns13.333±(0.252)c


A0.119±(0.002)c




Shade drying

B67.700±(0.173)c

A5.333±(0.321)a

A21.967±(0.231)a


A0.345±(0.008)a

blanched

Fresh

-

-

-


B0.063±(0.002)c




Microwave drying

B49.267±(0.115)d

B1.900±(0.173)c

ns16.467±(0.058)b


B0.096±(0.002)b




Hot-air drying

B79.500±(0.173)a

ns1.267±(0.115)d

A13.767±(0.153)c


B0.077±(0.006)c




Open-air sun drying

B78.133±(0.058)b

A2.267±(0.153)b

ns13.467±(0.351)c


B0.062±(0.001)c

 

Shade drying

A69.233±(0.208)c

B2.967±(0.058)a

B19.600±(0.346)a


B0.204±(0.020)a


A,B denote the effect of blanching, significant difference (p<0.05) when using different letter.

a,b,c,d denote the effect of drying method, significant difference (p<0.05) when using different letter.

ns denotes insignificant value.

± Standard derivation


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