Investigation of infrared drying of pomegranate by-products

Abstract

Keywords: Infrared Drying; Pomegranate By-Product; Modelling; Effective Moisture Diffusivity; Activation Energy

Introduction

The pomegranate, botanical name Punica granatum, is a fruit-bearing deciduous shrub or small tree in the family Lythraceae that grows between 5 and 8 m tall. Pomegranates are used in baking, cooking, juice blends, meal garnishes, smoothies, and alcoholic beverages, such as cocktails and wine. The pomegranate originated in the region of modern-day Iran, and has been cultivated since ancient times throughout the Mediterranean region and northern India. Today, it is widely cultivated throughout the Middle East and Caucasus region, north and tropical Africa, the Indian subcontinent, Central Asia, the drier parts of southeast Asia, and parts of the Mediterranean Basin. It is also cultivated in parts of Arizona and California. In recent years, it has become more common in the commercial markets of Europe and the Western Hemisphere [1-3]. During the industrial processing of pomegranate, large volumes of industrial wastes are produced, which have a wide range of nutritional values. Therefore, in the recent years, the attention has been focused on the industrial by-products of pomegranate that have a high potential of antioxidant and antifungal properties [4, 5]. Furthermore, the presence of abundant effective compounds has been reported in many parts of this plant such as leaves, barks, roots, peels, juice and seeds that cause high antimicrobial and antioxidant activity of them [5, 6]. Fruit by-products generally present high moisture content, which makes them perishable. One may to facilitate their subsequent use is to dry them [7]. Drying process has been used for decades in food processing industries for efficient long-term preservation of final products. The basic objective in drying food products is the removal of water from fresh product reaching a level at which microbial spoilage is avoided [8]. Hot air dying has many disadvantages such as; lower energy efficiency, long drying times, but on the other hand it has been used widely [9, 10]. Infrared (IR) heating has so many advantages compared to the widely used hot air drying. Also the equipment of IR can be compact with controllable parameters in order to control the overheating and fast heating [11]. Various agricultural and animal products have been successfully dried by the infrared application and/or by a combined infrared-assisted convection process [12-15]. However, there is no information available about infrared drying of pomegranate by-products. In this study, the thin-layer drying behaviour of pomegranate byproducts in an infrared dryer was investigated, and mathematical modelling by using three thin-layer drying models available in the literature was performed. Also, the values of effective moisture diffusivity and activation energy were calculated. This paper was recommended for publication in revised form by Regional Editor Bekir Yılbaş 1Department of Chemical Engineering, Yildiz Technical University, Istanbul, TURKEY *E-mail address: skipcak@yildiz.edu.tr Manuscript Received 30 May 2017, Accepted 11 October 2017

Journal of Thermal Engineering, Research Article, Vol. 4, No. 2, Special Issue 7, pp. 1821-1827, February, 2018

Materials And Methods

Materials Pomegranade by-products, were provided by Döhler Natural Food & Beverage Ingredients factory located in Denizli. By-products were collected just after the pressing operation and immediately packaged and stored at 4°C. The average thickness of a pomegranate by-products were 1 cm. The initial moisture content of the pomegranate by-product was determined using the AOAC method [16] and found to be 1.729  0.005 kg water/kg dry matter (d.b.). Drying experiments were carried out in a moisture analyzer with one 250 W halogen lamp (Snijders Moisture Balance, Snijders b.v., Tilburg, Holland). The infrared drying process, the sample should be separated evenly and homogeneously over the entire pan. The drying experiments were performed at infrared power level varying from 88 to 167 W. The samples of pomegranate by-products were removed of dryer at time intervals of 15 min during the drying process and weighted with a BB3000 model digital balance (Mettler-Toledo AG, Grefensee, Switzerland), which has an an accuracy of 0.1 g. Drying was finished when the moisture content of samples were approximately 0.005  0.001 kg water /kg dry matter (d.b.). The experiments done three times and average values of the moisture contents were used. The moisture content (M), drying rates (DR) and moisture ratio (MR) of pomegranate by-product were calculated using (1), (2) and (3) [17]:

where M is the moisture content (kg water / kg dry matter), mw is the water content (g), md is the dry matter content (g), DR is the drying rate (kg water / kg dry matter × min), Mt+dt is the moisture content at t + dt (kg water / kg dry matter), t is the drying time (min), MR is the moisture ratio (dimensionless), Mt, Me and Mi are the moisture content at selected time, at equilibrium and the initial value in kg water / kg dry matter. The drying curves were fitted to three thin-layer drying models, which are widely used in the literature for food products (Table 1). Table 1. Models used for fitting the experimental data Model Aghbashlo et al.

*k is the drying rate constant or coefficient (1/s) and a,b and c are the constants (dimensionless) Regression analysis was conducted using the Statistica 8.0 computer programme (StatSoft Inc., Tulsa, USA). Model parameters were estimated using a non-linear regression procedure based on the LavenbergMarquardt algorithm. In the literature, higher R2 values were accepted as better results [16]. R2 equation is given in (4):

Journal of Thermal Engineering, Research Article, Vol. 4, No. 2, Special Issue 7, pp. 1821-1827, February, 2018

  1 N  MRexp,i    MRexp,i   n   i 1  i 1 

where MRexp and MRpre represent experimental and predicted values of moisture ratios, respectively. Fick’s second law of unsteady state diffusion can be used to determine the moisture ratio. For longer drying periods, the equation can be given as in (5): 2  8    Deff  ln MR   ln 2    t 2      4 L 

where Deff is the effective moisture diffusivity (m2/s), t is the time (s), L is the half-thickness of samples (m) and n is a positive integer. The effective moisture diffusivity is typically obtained by plotting ln (MR) versus drying time in equation 5. Temperature is not directly measurable quantity in the infrared power level during drying process in this study. For the calculation of activation energy equation 6 is used [16]:

Where D0 is the pre-exponential factor of Arrhenius equation (m2/s), Ea is the activation energy (W/kg), P is the infrared power (W), and m is the sample weight (kg).

Results And Discussion

The effect of infrared power on drying curves of pomegranate by-product during drying is shown in Figure 1. The drying curves are typical to ones for similar fruits, vegetables, by-products and pomaces. It is obvious that the moisture content decreased with drying time and infrared power. The drying time required reaching the final moisture content of samples were 270, 150, 105, 90 and 60 min at the infrared powers of 88, 104, 125, 146, and 167 W, respectively. As expected at higher infrared power level the higher heat absorption resulted in higher product temperature, higher mass transfer driving force, faster drying rate and consequently lesser drying time [14, 17, 21].

Figure 1. Moisture contents of the pomegranate by-products dried with different infrared power levels 1823

Journal of Thermal Engineering, Research Article, Vol. 4, No. 2, Special Issue 7, pp. 1821-1827, February, 2018 It has been explained in the literature that the drying of food products generally follows the falling-rate period, meaning that the the last part of drying corresponds to a falling drying rate and the moisture transfer from the solid matter is explained using the Fick’s second law [14, 17, 21]. In Figure 2, the drying rate vs moisture content is given for different infrared power levels. From Figure 2 it is seen that the falling-rate period proved to be the main stage of infrared drying. In Table 1 three thin layer models created by Aghbashlo et al., Jena & Das and Midilli & Kucuk were fitted to the experimental MR with respect to drying times. The best model was selected based on the highest R 2. The results of the estimated coefficients and statistical data obtained from Aghbashlo et al., Jena & Das and Midilli & Kucuk were given in the Tables 2, 3 and 4, respectively.

Figure 2. Drying rate curves of pomegranate by-products dried with different infrared power levels Table 2. Estimated coefficients and statistical data obtained from Aghbashlo et al. model Power (W)

In Aghbashlo et al. model the lowest and the highest R2 values were found as 0.999104 at 88 W and 0.999778 at 167 W, respectively. Table 3. Estimated coefficients and statistical data obtained from Jena & Das model Power (W)

Journal of Thermal Engineering, Research Article, Vol. 4, No. 2, Special Issue 7, pp. 1821-1827, February, 2018 In Jena & Das model the lowest and the highest R2 values were found as 0.988834 at 125 W and 0.993563 at 88 W, respectively. In Midilli & Kucuk model the lowest and the highest R2 values were found as 0.949948 at 146 W and 0.999631 at 104 W, respectively. Among the three models, considering the average R2 values, Aghbashlo et al. best fits the experimental data. Table 4. Estimated coefficients and statistical data obtained from Midilli & Kucuk model Power (W)

The plot of ln(MR) vs. drying time (min) is shown in Figure 3.

Figure 3. The plot of ln(MR) vs. drying time (min) From the equations, the slope Deff values are calculated as 3.296 × 10-09, 6.609 × 10-09, 7.573 × 10-09, 1.259 × 10 and 1.413 × 10-08 m2/s for the infrared power levels of 88, 104, 125, 146 and 167 W, respectively. It is seen that Deff values increased with increasing infrared power level. This phenomenon can be explained as the increase in infrared power causes a rapid temperature rise of a food product [14]. Using the obtained Deff values, the plot of Deff vs. infrared power level is drawn and given in Figure 4. -08

Journal of Thermal Engineering, Research Article, Vol. 4, No. 2, Special Issue 7, pp. 1821-1827, February, 2018 From the plot of ln(Deff) vs. m/P, which is shown in Figure 5, Ea can be calculated and the estimated value of Ea are found as 4.424 kW/kg.

Conclusion

Using different drying methods, the shelf life and storage of food products can be extended In this study, the drying characteristics of pomegranate by-products is investigated using the infrared method at five different infrared power levels. The last part of drying took place in the falling-rate period. The drying time decreased with the increase in infrared power level. The Aghbashlo et al. model best fits the experimental results. The Deff values are calculated to be between 3.296×10−9 to 1.431×10−8 m2/s and the activation energy was estimated as 4.424 kW/kg.

Share and Cite