alexa Modelling the Drying Characteristics of Osmosised Coconut Strips at Constant Air Temperature | Open Access Journals
ISSN: 2157-7110
Journal of Food Processing & Technology
Like us on:
Make the best use of Scientific Research and information from our 700+ peer reviewed, Open Access Journals that operates with the help of 50,000+ Editorial Board Members and esteemed reviewers and 1000+ Scientific associations in Medical, Clinical, Pharmaceutical, Engineering, Technology and Management Fields.
Meet Inspiring Speakers and Experts at our 3000+ Global Conferenceseries Events with over 600+ Conferences, 1200+ Symposiums and 1200+ Workshops on
Medical, Pharma, Engineering, Science, Technology and Business

Modelling the Drying Characteristics of Osmosised Coconut Strips at Constant Air Temperature

Agarry SE* and Aworanti OA

Biochemical Engineering and Biotechnology Research Laboratory, Department of Chemical Engineering, Ladoke Akintola University of Technology, Ogbomoso, Nigeria

*Corresponding Author:
Dr. Agarry SE
Biochemical Engineering and Biotechnology Research Laboratory
Department of Chemical Engineering
Ladoke Akintola University of Technology, Ogbomoso, Nigeria
E-mail: [email protected]

Received date: February 24, 2012; Accepted date: March 21, 2012; Published date: March 23, 2012

Citation: Agarry SE, Aworanti OA (2012) Modelling the Drying Characteristics of Osmosised Coconut Strips at Constant Air Temperature. J Food Process Technol 3:151. doi:10.4172/2157-7110.1000151

Copyright: © 2012 Agarry SE, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Visit for more related articles at Journal of Food Processing & Technology

Abstract

Drying was performed on osmotically dehydrated coconut meat. The coconut was osmotically pre-treated using three different concentrations of sucrose solutions and immersed in a temperature water bath for 3 h at temperatures of 30, 40 and 50 º C, respectively. The osmosised and non-osmosised (control) coconut strip samples were dried in an oven at a drying temperature of 60ºC. The results showed that drying regime was characteristically in the falling rate period. A regression analysis was used to fit three thin layer drying models to the experimental drying data. The most appropriate model(s) was selected using correlation coefficient (R 2 ) and root mean square error (RMSE). The page model showed a better fit of the experimental drying data (as compared to other models) on the basis that R 2 > 0.99 and RMSE < 0.0130. The effects of the osmotic pre-treatment on the drying data of coconut samples were also explained. The effective moisture diffusivity ranged from 5.74 to 7.88 x 10 -10 m 2 /s for osmosised coconut sample and 5.44 x 10 -10 m 2 /s for non-osmosised coconut sample.

Keywords

Coconut; Osmotic dehydration; Drying; Effective diffusivity; Water content; Drying models

Introduction

Drying is one of the oldest processes used in the preservation of cultural food products. It is gaining attention as one of the emerging technology which requires innovations for research studies. Drying is dependent on two fundamental principles (i.e. heat and mass transfer). Firstly, heat has to be transferred to the product and secondly moisture has to be removed from the product [1]. Since drying is an energy driven unit operation, its efficiency can be improved if the drying rate that determines the drying period is increased. Long drying periods may lead to poor quality of final products [1,2]. Conditions which result in higher drying rates are sought for giving rise to acceptable final products that are economically and nutritionally viable [1].

It is on this basis that physical pretreatments such as osmotic pretreatment have been investigated in order to improve drying kinetics or product quality [3-6]. The beneficial effect of osmotic pretreatment includes higher quality of the final product and lower energy requirements [7,8]. Several factors affecting this treatment process include the type and concentration of the osmotic solutions, processing temperature and time, rate of agitation and raw material characteristics [9]. However, extensive studies have not been done on the effect of osmotic process variables on the drying behavior of food materials.

Notable workers who have studied the effect of osmotic solution concentrations on the drying characteristics of food materials include Karathanos and Kostaroproulos [5], Nieto et al. [10], Madamba [6] and Garcia et al. [11]. However, no relevant information has been provided on this subject (osmotic air-drying) except that the concentrations of osmotic solution have been observed to affect the drying properties of agricultural produce [6]. Specifically, that of coconut has not been studied. Also, many studies have emphasized drying kinetics and thinlayer drying models for fruits and vegetables such as organic apple slices [12], carrots [13], rose hips [14], raw mango slices [10,15], young coconut and chopped coconut [6,16,17]. Nonetheless, the preceding thin-layer drying models provided no data for drying of osmotically pretreated coconut chips or strips.

Coconut (Cocos nucifera L.) being one of the most important crops in the tropical countries and grown in more than 80 countries of the world with a total production of 61 millions tonnes per year [18]. Nigeria produced 1088500 million tonnes of coconut palm between 2004 and 2008 [19]. Coconut can be consumed in various types of coconut derived products - coconut milk, coconut juice, coconut flour, coconut oil, and desiccated coconut [17]. The desiccated coconut with very low moisture content of about 3% dry weight basis can be use for the decoration of ice cream, cake, donuts and as flavoring agent in chocolate bars, sweets and biscuits [17,18].

Therefore, the objective of this work is to study the effect of osmotic solution concentration and its operating temperature (pretreatment variables) on the air drying properties of coconut and to fit some thinlayer drying models in which the drying rate constants and model coefficients rely on the osmotic pretreatment conditions or variables.

Materials and Methods

Materials

The coconut used for this study was obtained from a local city market of Ogbomoso in Oyo state, Nigeria. The coconut was broken up and the meat was removed, washed and cleaned after which it was cut (using vegetable shredder) into thick strips of regular rectangular shape (6.0 x 3.0 x 0.5 cm) with nearly 1.0 cm thickness. Sugar (sucrose) with trade mark ST LOUIS Sucre, France, bought from local supermarket in Ogbomoso was used as the osmotic agent (solute) for the osmotic pretreatment. The other materials that were used in this study include electric oven, temperature controlled water bath, electronic weighing balance and beakers.

Methods

Osmotic dehydration: 30 g of coconut meat chips were placed in three different 250 ml beakers containing sucrose solution of concentration 40, 50 and 60% w/w, respectively. The beakers were then placed in a temperature controlled water bath (DK-420 Glufex Medical and Scientific, England) maintained at 30ºC for 3 hours. Thereafter, the osmotic dehydrated samples (coconut samples) were removed and the excess solution on the surface of samples was removed with absorbent paper and then re-weighed. These procedures were repeated with a constant sucrose solution concentration of 40% w/w at 40 and 50°C. The weight reduction (WR), sugar gain (SG) and the water content loss (WL) of coconut meat samples was respectively calculated using Equations (1) to (3) [7]:

equation (1)

equation (2)

equation (3)

Where: M0 is initial weight of fresh coconut before osmotic treatment (g); Mf, final weight of coconut after time t of osmotic treatment (g); M0, dry weight of fresh coconut (g); Mf, final dry weight of coconut after time t of osmotic treatment (g).

Oven drying: Drying experiments were carried out in an oven dryer (Uniscope SM 9053A, England). The dimensions of the dryer are 0.693 × 0.470 × 0.486 m. The dryer consisted of a tray, electrical heater, fan and a temperature controller (50-200ºC, dry bulb temperature). The osmotically pretreated coconut meat samples were charged into the dryer and drying was performed at a dry bulb temperature of 60ºC. At regular time intervals of 60 minutes, the samples were withdrawn for weight measurement. The total drying time was obtained as the time required for the sample to attain a constant weight (or bone dry weight). Drying rates for each pretreatment condition were estimated based on weight of water removed per unit time and per kilogram of dry matter (kg kg-1h-1) [20,21]. The moisture contents of both the fresh and dried samples were determined according to AOAC [22].

Drying parameter estimation: Thin-layer mathematical drying models describe the drying phenomenon in a unified way regardless of the controlling mechanisms [23,24]. In thin layer drying, the moisture ratio during drying is calculated as follows:

equation (4)

Where MR is the moisture ratio, M is the moisture content at any time, M0, the initial moisture content, and Me, the equilibrium moisture content respectively, on dry weight basis.

During thin layer drying of coconut, the samples were not exposed to uniform relative humidity and temperature continuously. As a result of this, the equilibrium moisture content could not be determined and since this is usually not high for food materials [25,26], the equilibrium moisture content was assumed to be zero. Thus, the moisture ratio was simplified according to Pala et al. [27] and Kingsly et al. [24] to:

equation (5)

The recorded moisture contents for each sample were then used to plot the drying curves.

Model prediction: Drying curves were fitted to three known mathematical models given in Table 1. Regression analysis was used to select the model (based on goodness of fit) that best describes the drying data of the dehydrated coconut samples. Some of these models have been recently used by Doymaz [13,28], Demir et al. [29], Erenturk et al. [14], Friant et al. [30], Akpinar and Bicer [31], Sacilik and Elicin [12] and Vega et al. [32].

No               Model Names                         Model Equation
a.            Newton                                           MR=exp(-kt)                (6)
b.           Page                                                  MR=exp(-ktn)               (7)
c.           Two-term exponential            MR=a exp(-kt) + (1 - a) exp(-kt) (8)    

Table 1: Typical models for thin layer drying [35].

The correlation coefficient (R2) and root mean square error (RMSE) were criteria used for selecting the best model equation that describes the drying curve. In order to evaluate the goodness of fit of the simulation given by the selected models, the mean relative error, %E [33,34] and the reduced chi-square, χ2 were estimated [32-36].

equation (6)

equation (7)

Where N, total number of observations, Z, number of model parameters, MRexp i , experimental moisture ratio values and MRprei , predicted moisture ratio values. It is generally considered that %E ≤ 10% gives a good fit [34,37].

Effective moisture diffusivity: For the determination of the effective moisture diffusivity (Deff), a mathematical model was used based on Fick’s second law of diffusion which expresses a relationship between the moisture ratio and the effective moisture diffusivity, the solution for which was given by Crank [38] can be applicable for slab geometry by assuming uniform initial moisture distribution, constant diffusivity and negligible shrinkage is presented in Equation (11):

equation (8)

Where Deff is effective moisture diffusivity (m2/s), t, drying time and l, thickness (m).

Linear regression analysis was used to adjust the experimental data to Equation (11) which is the slope method [39].

Results and Discussion

Osmotic dehydration

Table 2 showed the results of the osmotic dehydration parameters. The water loss (WL) and weight reduction (WR) for the coconut chips increased as the sucrose concentration and osmotic processing temperature increased, respectively (i.e. the more concentrated osmotic dehydration solution and the higher temperature produce the higher water loss and weight reduction). Similar observations have been reported [40,41]. The water loss after the osmotic dehydration was in the order of 9-20%, indicating that the proposal made for the possibility of pre-processing is viable.

Osmotic Pretreatment
Conditions
Sample Weight (g) Moisture Content
(w/w) g/g
Weight Reduction (WR)
%
Water Loss (WL)
%
Sugar Gain
 (SG)
    %
30oC - 40% (w/w) 30 0.343 6.33 9.15    4.9
30oC - 50%(w/w) 30 0.280 12.67 16.55    6.0
30oC - 60%(w/w) 30 0.250 15.67 19.92    6.3
40oC - 40%(w/w) 30 0.300 10.67 14.20    5.4
50oC - 40%(w/w) 30 0.270 13.67 17.69    6.2
Control (Non-osmosised) 30 0.401 - -      -

Table 2: Osmotic dehydration parameters for coconut chips.

Oven drying

The moisture ratio variations with drying times for each osmotic pretreatment condition of coconut chips (Figure 1) showed that moisture ratio decreases continuously with drying time for both the osmosised and control (non-osmosised) coconut samples. The continuous decrease in moisture ratio with time indicates that the internal mass transfer for coconut chips was governed by diffusion. This corroborates Piga et al. [42] and Kingsly et al. [24] observations. The osmotically pretreated samples took less time for drying than the untreated sample. Moreover, it was observed that as the osmotic agent (sucrose) concentration and pretreatment temperature increased, the hot air-drying time consequently decreased.

food-processing-technology-moisture-ratio

Figure 1: Variation of moisture ratio with drying time for both control (nonosmosised) and pre-osmosised coconut strip samples.

The influence of the osmotic pretreatment conditions drying rates of coconut chips (Figure 2,3) showed that the initial drying rates of the samples were generally high when the moisture content was highest and decreased rapidly until all samples showed similar rate after about 3 h of drying. This was due to the free moisture near the surface of the product being removed early in the process. Also, the initial drying rates decreased as the concentration of the osmotic agent (sucrose) solution increased. The initial drying rate was highest for the control (non-osmosised) sample. The high initial drying rate probably occurred because of its higher initial moisture content which were lower in the pre-osmosised samples (Table 2). These results corroborated Nieto et al. [10] wherein it was reported that osmotic pretreatment of mango with increased glucose concentration decreased the drying rate during hot air drying, and it is variant to Madamba [6] who reported that the osmotic pretreatment of coconut with sucrose solution had no significant effect on the convective drying phase.

food-processing-technology-Drying-curves

Figure 2: Drying curves of coconut osmotically pretreated at 30oC using different sucrose concentrations and air-dried at 60oC.

Figure 3 showed the influence of osmotic pretreatment on the drying rates of coconut chips. It was observed that the initial drying rates decreased as the pretreatment temperature increased. The initial drying rate for the samples pretreated at 30°C was higher than that pretreated at 40°C and 50°C, respectively. From Figure 2 and 3, it can be seen that the drying regime of coconut is characteristics of the falling rate period. The constant rate period was obviously not observed in both the control (non-osmosised) and pre- osmosised coconut samples because of the complex nature of the internal moisture movement mechanism.

food-processing-technology-coconut-osmotically

Figure 3: Drying curves of coconut osmotically pretreated at different temperatures using 40% w/w sucrose concentration and air-dried at 60oC.

Drying models prediction

Drying data for the different pre-osmosised and control (nonosmosised) coconut samples (Figure 1) were fitted to 3 different thin layer mathematical drying models (Equations (6)-(8)) listed in Table 1.

Using regression analysis, the parameters of the different models were determined, while values of R2 and RMSE were obtained as presented in Table 3. The most appropriate model(s) capable of predicting the drying data of non-osmosised and pre-osmosised coconut samples was selected on the basis of the highest R2 and lowest RMSE values. The page model had a good fitting of data in terms of R2 > 0.99 and RMSE < 0.013 for all the tested coconut samples.

Osmotic Pretreatment conditions for c°Conut samples Model Name Model Constants R2 RMSE
a k n
30°C/40%w/w Newton - 0.3083 - 0.7921 0.0684
  Page - 0.4663 0.6476 0.9992 0.0047
  Two-term exponential 10.78 0.3083 - 0.7921 0.0762
30°C/50%w/w Newton - 0.3272 - 0.7621 0.0692
  Page - 0.4795 0.6395 0.9921 0.0145
  Two-term exponential 10.78 0.3276 - 0.7621 0.0799
30°C/60%w/w Newton - 0.3847 - 0.7238 0.0699
  Page - 0.5326 0.6273 0.9999 0.00078
  Two- term exponential 30.06 0.3847 - 0.7238 0.0855
40°C/40%w/w Newton - 0.3471 - 0.8655 0.0568
  Page - 0.4730 0.6998 0.9997 0.00309
  Two- term exponential 0.0650 0.3471 - 0.8655 0.0656
50°C/40%w/w Newton - 0.3936 - 0.8667 0.0545
  Page - 0.5071 0.7073 0.9997 0.0034
  Two-term exponential -9.935 0.3936 - 0.8667 0.0667
Control (Non- osmosised) Newton - 0.246 - 0.9166 0.0508
  Page - 0.3568 0.7594 0.9949 0.0136
  Two-term exponential -59.22 0.246 - 0.9166 0.0549

Table 3: Drying model constants and goodness of fit parameters for c°Conut samples.

Therefore, the page model is proposed as the best model describing the drying behaviour of non-osmosised and osmosised coconut samples dried at 60°C. Similar observations have been reported for drying of red pepper [32,34,43]; tomato [36] and parsley leaves [44]. The estimated values for the page model parameters are summarized in Table 4. The results shown in Table 4 shows that the osmotic variables (sucrose concentration and process temperature) used in the preprocessing of osmotic dehydration on prior to drying had a positive influence on the drying behaviour of coconut as described by the page model.

Osmotic Pretreatment k n %E RMSE χ2 R2
30oC/40%w/w 0.4663 0.6476 11.4 0.0415 0.00259 0.95
30oC/50%w/w 0.4795 0.6395 1.82 0.0138 0.00032 0.98
30oC/60%w/w 0.5326 0.6273 1.02 0.0038 0.00003 0.99
40oC/40%w/w 0.4730 0.6998 0.70 0.0041 0.000027 0.99
50oC/40%w/w 0.5071 0.7073 0.36 0.0032 0.000021 0.99
Control(Non-osmosised) 0.3568 0.7594 2.99 0.0163 0.000355 0.97

Table 4: Summary of the values of page model parameters together with the mean relative error (%E) reduced chi-square (χ2), root mean square error (RMSE) and correlation coefficient (R2) for the drying of coconut.

It is observed that the drying constant ‘k’ generally increased with increase in both the osmotic agent (sucrose) concentration and process temperature, respectively. While the empirical constant ‘n’ marginally decreased with increase in the osmotic agent concentration and marginally increase with increase in process temperature. The dependence of these model parameters on the osmotic variables can be represented through a linear regression relationship as given in the equations (12) and (13):

k = 0.2467+0.3493x1+0.0023x2 (R2 = 0.98)                             (12)

n = 0.6199-0.1392x1+0.0030x2 (R2 = 0.98)                              (13)

It was also observed that the drying constant ‘k’ value for the osmosised samples were higher than of the non-osmosised sample. Thus, osmotic pretreatment increases the drying constant ‘k’ values during thermal air drying phase. The higher the ‘k’ value, lower is the drying time.

In order to mathematically evaluate the simulation, the mean relative error (%E), correlation coefficient (R2), root mean square error (RMSE) and reduced chi-square (χ2) were calculated from comparing the experimental moisture ratio and those given by the proposed model for the non-osmosised and pre-osmosised coconut samples dried at 60ºC. These results are shown in Table 4. By using Equations (12) and (13) (page model), the moisture ratio variation during drying has been estimated. From Table 4, the %E values were equal or below 10%, the R2 value very high, RMSE and the reduced chi-square value (χ2) were low for all osmosised and non-osmosised samples. Thus, the page model allowed an accurate simulation of the thermal drying curves of coconut for the whole range of osmotic process variables studied, exhibiting a high agreement between experimental and estimated (predicted) moisture ratio (Table 4).

Effective moisture diffusivity

The transport of water (or moisture transfer mechanism) during drying can be described by the Fick’s diffusion model. The experimental drying curves obtained at drying temperature of 60ºC for non-osmosised and pre-osmosised samples were adjusted to the Fick’s diffusion equation (Equation (11)). The excellent linear adjustment to this equation with correlation coefficient of 99% show that drying of coconut slices is well represented by the diffusion model proposed by Fick, and this enable the calculation of the effective moisture diffusivity (Deff) for both the non-osmosised and pre-osmosised samples. The results showed that the effective moisture diffusivity of pre-osmosised coconut slices ranged from 5.74 to 7.88x10-10 m2/s, while that for non-osmosised coconut sample is 5.44x10-10 m2/s. These values were found to be within the general range 10-11-10-9 m2/s for drying of food materials [6,12,20,36,45-47].

Also, it could be observed from Table 5, that the effective moisture diffusivity increased with increase in the osmotic predrying process variables (sucrose concentration and pretreatment temperature) used in pre-processing of osmotic dehydration prior to drying. The values for the pre-osmosised samples are higher than that of non-osmosised sample. Thus, osmotic pretreatment increased the effective moisture diffusivity. This is in contrast to the observation of Nieto et al. [10]. These workers reported that osmotic pretreatment strongly decreased the effective moisture diffusivity of mango dried at 60ºC. They adduced glucose uptake during the impregnation step and starch gelatinization as possible reasons for this observation.

Osmotic Pretreatment Deff X10-10(m2/s) R2
30°C/40% w/w 5.74 0.9932
30°C/50% w/w 6.26 0.9997
30°C/60% w/w 6.91 0.9952
40°C/40% w/w 6.88 0.9943
50°C/40% w/w 7.88 0.9955
Control (Non-osmosised) 5.44 0.9920

Table 5: Values of the effective moisture diffusivity of c°Conut dried at 60°C.

Conclusion

Osmotic dehydration reduces considerably the drying rate and drying time of coconut samples due to loss of the initial water content. The osmotic dehydration is a pre condition which had a significant influence on the thermal air drying behaviour of coconut. The proposed thin layer drying model of page provides an adequate preliminary description stage for the drying behaviour of coconut and this could represent a significant tool for engineering purposes. The Fick’s diffusion model showed a better adjustment to the experimental drying data which allowed the determination of the effective moisture diffusivity. Osmotic pretreatment increased the effective moisture diffusivity.

References

Select your language of interest to view the total content in your interested language
Post your comment

Share This Article

Relevant Topics

Recommended Conferences

Article Usage

  • Total views: 11788
  • [From(publication date):
    April-2012 - Sep 24, 2017]
  • Breakdown by view type
  • HTML page views : 7978
  • PDF downloads :3810
 

Post your comment

captcha   Reload  Can't read the image? click here to refresh

Peer Reviewed Journals
 
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
 
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

Agri, Food, Aqua and Veterinary Science Journals

Dr. Krish

[email protected]

1-702-714-7001 Extn: 9040

Clinical and Biochemistry Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Business & Management Journals

Ronald

[email protected]

1-702-714-7001Extn: 9042

Chemical Engineering and Chemistry Journals

Gabriel Shaw

[email protected]

1-702-714-7001 Extn: 9040

Earth & Environmental Sciences

Katie Wilson

[email protected]

1-702-714-7001Extn: 9042

Engineering Journals

James Franklin

[email protected]

1-702-714-7001Extn: 9042

General Science and Health care Journals

Andrea Jason

[email protected]

1-702-714-7001Extn: 9043

Genetics and Molecular Biology Journals

Anna Melissa

[email protected]

1-702-714-7001 Extn: 9006

Immunology & Microbiology Journals

David Gorantl

[email protected]

1-702-714-7001Extn: 9014

Informatics Journals

Stephanie Skinner

[email protected]

1-702-714-7001Extn: 9039

Material Sciences Journals

Rachle Green

[email protected]

1-702-714-7001Extn: 9039

Mathematics and Physics Journals

Jim Willison

[email protected]

1-702-714-7001 Extn: 9042

Medical Journals

Nimmi Anna

[email protected]

1-702-714-7001 Extn: 9038

Neuroscience & Psychology Journals

Nathan T

[email protected]

1-702-714-7001Extn: 9041

Pharmaceutical Sciences Journals

John Behannon

[email protected]

1-702-714-7001Extn: 9007

Social & Political Science Journals

Steve Harry

[email protected]

1-702-714-7001 Extn: 9042

 
© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version
adwords