A review on plum drying

Renewable and Sustainable Energy Reviews 56 (2016) 362–367

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Renewable and Sustainable Energy Reviews journal homepage: www.elsevier.com/locate/rser

A review on plum drying Mahdi Hedayatizadeh a,n,1, Hossein Chaji b a b

Faculty of Agriculture, University of Birjand, Birjand, Iran Khorasan Razavi Agricultural and Natural Resources Research Center, Mashhad, Iran

art ic l e i nf o

a b s t r a c t

Article history: Received 29 July 2014 Received in revised form 22 September 2015 Accepted 30 November 2015

Plum has high consumption rates throughout the world while drying as a common way for increasing its shelf-life is inevitable. But, drying this agricultural product is highly energy-intensive since it has high moisture contents. Hence, any energy saving procedure for drying such an economic product is warmly embraced by plum drying industry. In the present review, based on perusing the plum drying-related papers, it was concluded that the conducted studies on plum drying can be generally categorized in three groups: Plum pre-treatments which highly focus on speeding the rate of drying through application of some mechanical/chemical methods mostly with energy saving perspectives; Mathematical modeling and simulation of plum drying for prognosticating the given process and also the plum drying kinetics. Fortunately, the pre-treatments used were reported to be effective in decreasing the time and the total consumed energy for plum drying. & 2015 Elsevier Ltd. All rights reserved.

Keywords: Plum Drying Pre-treatment Modeling/simulation Kinetics

Contents 1. 2.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Plum drying issues classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Pre-treatments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Mathematical modeling and simulation of plum drying . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. Drying kinetics of plum. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1. Introduction Fruits and vegetables play a very important role in our diet and nutrition and they have been mostly dried as a means of preservation for thousands of years. Hence, dehydration is probably the oldest method of preserving foodstuffs. Amongst different types of fruits, plum is one of the most important products for the drying fruit industry with 2014 production (August–September harvest, Northern hemisphere) of 88,800, 36,000, 1360 and 8700 t in USA, France, Italy and Serbia, respectively and 2015 production (February–March harvest, Southern hemisphere) of 77,000, 35,000, 1000 and 3600 t in n

Corresponding author: Tel.: þ 98 56 32254041 9; fax: þ 98 56 32254050. E-mail address: [email protected] (M. Hedayatizadeh). 1 Postal Address: Amir Abad University Campus, Birjand, Southern Khorasan Province, Iran. http://dx.doi.org/10.1016/j.rser.2015.11.087 1364-0321/& 2015 Elsevier Ltd. All rights reserved.

362 362 362 364 366 366 367

Chile, Argentina, South Africa and Australia, respectively [1]. Many studies have been conducted to study the plum drying and its changes during the process. These studies are classified mostly in three following sectors: Treatments/pre-treatments applied to plum prior to drying; Mathematical modeling and simulation of its drying process and studying the kinetics of plum drying. The authors have tried to put these findings together and prepare a review in which the researcher can get a better and sooner picture of the plum drying.

2. Plum drying issues classification 2.1. Pre-treatments The energy consumed for dehydration of plums constitutes almost a quarter of the total production cost. Hence, to enhance

M. Hedayatizadeh, H. Chaji / Renewable and Sustainable Energy Reviews 56 (2016) 362–367

the drying rate of plum for reduction of drying time, some physical/chemical pre-treatments have been proposed by researchers. Besides reduction of desiccation time of plum, producing a high quality final-product (with good texture and bright color) is also very significant to the whole process. Considering the two above factors, different studies have been undertaken. Wax layer on the surface of plums retard the rate of moisture loss and consequently drying. There for, Bain and Mcbean [2] studied the structure of the cuticular wax of prunes and its influence as a water barrier in relation to their drying characteristics. They estimated the amount of removed cuticular wax from 5–6 kg of prunes (250–300 fruits) and also calculated the average surface area of them while wax on the surface of prune was shown by electron microscopy. They mentioned the three following factors as the water loss retarders: the distance through which water must diffuse to the surface to evaporate; the high solid content and the cuticular wax. As an important factor, they mentioned that the lowest melting point of any component of wax is 56 °C. Hence, due to the high initial evaporative cooling at the surface of plums, drying temperatures up to 90 °C can be used in parallel-flow tunnel dryers with less heat damages to the tissues and shorter time period contrary to the counter-flow tunnel dryers through which the temperature of plum surface can reach 65 °C until 10– 12 h after the start of drying. Anyway, both tunnel dryers lead to wax melting and it was reiterated that the destruction of the natural barrier is not the only way in which quicker drying of fruit can be achieved since it has been postulated that through dipping in emulsions (as a pre-treatment), through flooding the minute spaces in the wax layer, make the wax hydrophilic instead of being hydrophobic while the original wax structure remained unimpaired [2]. Bain and Mcbean [3] also observed the development of the wax layer or bloom on prune plums throughout the growing season. They reconfirmed the effect of temperature on the wax surface with the same results as their previous research mentioned before while they also studied the effect of sodium hydroxide on the wax layer. Based on their findings, in commercial practices, prunes are sprayed with near boiling 0.2% sodium hydroxide as a pretreatment before drying causes splitting of the fruit surface, loss of half the wax layer, and decreases drying time by 10%. Examination of their sectioned replicas of fruit taken after dipping in sodium hydroxide showed that the hypodermal cells were severely damaged. They mentioned the loss of structure, together with the one caused by increasing temperature in the drying tunnel in the counter-flow system, must reduce the efficiency of the water barrier considerably, but the rate of diffusion of water through the flesh is the major limiting factor in the dehydration of these fleshy fruit [3]. Weitz et al. [4], analyzed the effect of some surface treatments on prunes under the particular process conditions imposed by the employment of indirect solar tunnel dryer. They programmed their experiments based on two temperature histories according to the data described by Cortes and Piacentini. Through their experiments, they prepared different dipping solutions ([Temperature history No. 1 with Pond's seedling variety: 2% K2CO3, 2% olive oilþ2% K2CO3 and 2% olive oilþ 4% K2CO3]; [Temperature history No. 1 with D’Agen variety: 2% olive oil þ2% K2CO3, 2% ethyl oleate, 2% methyl oleate and 4% methyl oleate] and [Temperature history NO. 2 with D’Agen variety: 2% methyl oleateþ2% K2CO3, 2% olive oil þ2% K2CO3, 2% ethyl oleate and 2% methyl oleate]) and to make sure the contact of all the fruit surfaces with the dip chemical, applied a mechanical agitation of the prunes which took 90 s. The drying process of laid prunes in trays continued until reaching moisture content of below 24% (w.b.). They concluded the effectiveness of the olive oil emulsions and the negligible advantage of potassium carbonate dip for Pond's seedling variety and

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also effectiveness of fatty acid ester dips for D’Agen. The authors also reported that in spite of the smaller reduction in drying time, olive oil emulsion dips were greater commercial interest in their country (Argentina) due to its availability and cost in comparison to methyl oleate or ethyl oleate [4]. Di Matteo et al. [5] studied the effect of superficial abrasion of the plums peel as a physical pre-treatment through using an inert abrasive material to help removing the cuticular waxy layer, surrounding the fruit, being taken into account as the limiting factor for moisture loss. It was also taken into consideration by the researchers to achieve light abrasion (not peel break-ups.) on peel to avoid loss of liquid during drying. Moreover, the researchers also pre-treated the Angeleno cultivar samples of plum chemically through dipping samples into ethyl oleate and eventually compared the results with the untreated ones being used as the reference. The results of their study revealed that the abrasive pretreatment most considerably reduced the dehydration time and the chemical pre-treatment also seemed effective in reducing the time duration of plum drying in comparison with the reference case [5]. The drying process has undoubtedly effects on quality of fruits and it is a significant objective to have it in such a way that leads to minimization of the adverse effects such as decrease in nutritional value and color changes. Parallel with the above mentioned goal, Cinquanta et al. [6] studied the effect of physical pre-treatment of superficial abrasion of the plums peel and also the chemical one (immersion into alkaline solution) (Part2 of the previous research) on the quality characteristics-skin color, sugars, Phenols etc. – of three plum cultivars namely Stanley, Angeleno and Empress. They found that both physical and chemical pre-treatments have positive effects on the final contents of glucose and fructose in Stanley and Empress prune cultivars while their proposed physical pretreatment most importantly brought about a smaller loss of sugar in Empress and Angeleno [6]. Doymaz [7] also investigated the effect of dipping solution (alkali emulsion of ethyl oleate) on the drying kinetics of plum. He started the drying experiments using a cabinet type dryer until the moisture content of plum samples reached 20% (w/w). He reported that the treated and untreated samples both followed a similar trend of drying up to moisture ratio of 0.6 while passing 0.6, the treated samples started to dry faster (treated samples had 29.4% shorter effective time in comparison with the untreated samples). His research also emphasized on increase of diffusion coefficients of treated plum samples than those of untreated plums which is attributed to the partial chemical breakdown of the sample skins [7]. Tarhan [8] also studied the combined effect of chemical and thermal pre-treatments on plum drying. Through his research, he selected eight different pre-treatments (three chemical solutions (Ethyl oleate, Potassium hydroxide and Sodium hydroxide) plus water combined with two dipping temperatures (23 and 60 °C)). These all eight pre-treatments were applied onto plums dried through three different ways of drying i.e. laboratory tray dryer (artificial drying), greenhouse dryer (solar drying) and open sun drying (in all three methods of drying, the air temperature was below 55 °C). To make a comparison between the above mentioned combinations of pretreatments, he measured the weight loss percentage (WLP) of plum dried as the criteria through the process of drying and also applied the two-way analysis of variance and multiway factorial analysis to find the combined effects. He concluded that the temperature of chemical solution as the dipping medium is a key step for drying of plum and reported the 1% KOH with 60 °C dipping temperature as the best recommended combination of pre-treatments for all the three methods of drying while 1% NaOH took the second position. It is also worth mentioning that based on his research about color changes occurred during the process of drying, no drastic changes in color values

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(L, a, b2) were observed with all drying trials. Moreover, the duration of drying for reaching the final weight loss percentage of 75% was also another important issue being observed through his research that in the case of solar drying and open sun drying it was around 177 h and 250 h, respectively being too much longer than 54 h of laboratory tray drying [8]. Goyal et al. [9] also studied the pre-treatment effects on kinetics of thin layer drying of plum. Hence, they commenced their drying experiments on control (untreated), blanched (50 °C for 20 min) and blanched with 1% potassium metabisulfite solution (KMS) plum slices through a tunnel dryer till there was no large variation of moisture loss observed. They mentioned that drying time is reduced by increase in drying air temperature and also the pre-treatment has had positive effect on reducing the drying duration. Moreover, it is reported that KMS pre-treatment leads to highest moisture diffusivity coefficient of plum slices. The authors also fitted some drying models to their experimental data and found the logarithmic model the best [9]. Jazini and Hatamipour [10] also pierced their plum samples to study its effect as a physical pre-treatment on drying rate of plums while compared the results with a chemically applied pretreatment which included plum dipping into boiling NaOH solution. Hence, they pierced the approximately uniform size samples of plum with a needle trying to achieve a uniform number of holes per surface area. To fulfill the comparison, the researchers measured the moisture content of samples during the drying time and calculated the MR3 being fitted by well-known drying mathematical models to find the best. They expressed the physical pretreatment of needle piercing as a more effective way of reducing drying time in comparison with the chemical one and also found that the moisture diffusivity of their chemically pre-treated samples was less than the values reported by those researchers who had applied ethyl oleate solution or pure water as the chemical pre-treatment since dipping in boiling solution can better remove the waxy layer compared with the low temperature solution [10]. 2.2. Mathematical modeling and simulation of plum drying Bertin et al. [11] focused on estimation of drying functions instead of constant unknown coefficients. Based on their claim, in different drying models using average values of water content or diffusion model unknown functions must be estimated. Their study was carried out using optimization techniques through minimization of a least square criterion between model values through simulation and experimental values. Their estimation of the optimum function consisted in giving from a first step an initial guess of that unknown function in discretized points through the optimization process mentioned above. Moreover, for finding the minimum fast the conjugate gradient algorithm and an analytic form of the gradient were used. To show their method, two examples of drying were carried out. The first one concerned a simple model like “characteristic drying curve” in the case of plum to find the unknown function f(ϕ) while the second one was about the diffusion model in the case of shelled corn drying for finding the diffusion coefficients. Their study showed acceptable results [11]. Weitz et al. [12] studied the drying of thin layered-prunes through a multi-shelf type solar dryer and investigated the influence of shelf spacing and length of dryer on the final product characteristics. Their model employed was a simplified model since it only included moisture transfer based on Luikov’s theory of drying and on a particular shrinkage hypothesis. They found the 2 L, a and b are the chromatric scales showing the brightness, redness and yellowness within specified values, respectively. 3 Moisture ratio.

more spacing exists between the adjacent shelves, the lower moisture content of the final product will be reached within a specified time period while it was not that significant. Moreover, within a specified time period of drying and fixed shelf spacing, a longer dryer showed a higher average of moisture content of fruits. Finally, the authors who had tried to determine the values of both parameters bringing about the best yield for the minimum dryer volume, proposed the moisture content heterogeneity (Δ̅W r ) of the final product as a criterion. Their results depicted that with a less shelf spacing, the moisture content heterogeneity rises with length of dryer. They also figured the moisture content evolution of prunes for different weather conditions (different inlet air temperature due to varied amount of solar incident on collector) and reported a 3.4–4.5 days period change between the favorable to less favorable weather conditions. Finally, they evaluated the performance of their solar drying system based on drying capacity and emphasized on feasibility of solar drying as a cheap and efficient way of food preservation [12]. Techaena et al. [13] simulated the plum drying in a deep bed. Hence, they selected the equation, X ¼ a∙expð b∙t Þ þ Xe where X, a, b and Xe are product moisture content at time t (kg water/kg dry matter), coefficients and limiting product moisture content (kg water/kg dry matter), respectively,among different empirical equations representing thin layer experimental as well as the equations of law of energy accumulation, heat/mass balances of air and product through some assumptions to model the thin layer of plum drying. This modeling paved the way for deep bed modeling of plum. The dehydrator they used were batch and continuous. They also validated their model against the experimental results and found good agreements [13]. Sabarez et al. [14] performed drying experiments on d’Agen plum samples and studied the effects of temperature and drying air relative humidity on the rate of moisture loss. Their data were also tested against a two-stage drying model. They applied four different temperature levels with three (low, medium and high) relative humidity conditions for the plum samples inside the tunnel dryer. They found that two regimes were necessary to describe the drying process of plums. It was found that after a short pre-heating, the plums experienced a constant rate of mass loss which the dominant factor controlling the rate of water loss was the maximum evaporation rate from the fruit surface. At later stages, the falling rate period started being interpreted as the ratecontrolling step which includes the migration of moisture from flesh to the surface. The model they used was the so-called gen¼ K ðW e W Þn where W, K, We and n are eralized order kinetics: dW dt 1 the weight loss at any time (kg), generalized rate constant (h ), final weight loss at equilibrium (kg), order of reaction, respectively, assuming two distinct periods (constant and falling) of drying for description of total drying curve. Based on literature, they applied dW ¼ hAðTHa v T s Þ for the constant and dW ¼ K ðW e W Þ for the falling dt c dt rates of drying where h, A, Ta, Ts and Hv are the heat transfer coefficient (W∙m2 ∙K 1 ), area of heat transfer (m2 ), dry bulb temperature of drying air (K), stable fruit temperature during constant 1 period (K) and latent heat of vaporization of water (J∙kg ), respectively. The authors verified their new model against the experiments of other researchers and mentioned that their newly proposed two-phase model is a simple one being clearly an improvement on the Newman single stage model which can follow the drying phenomena more realistically [14]. Sabarez and Price [15] also aimed at obtaining high quality drying data for the dehydration of d’Agen plums as a function of temperature. They applied three levels of temperature to plum samples spread uniformly on a mesh in a single layer through the drying chamber while trying to maintain the relative humidity at 37 0.5%. Their model constituted a numerical solution to the Fick's


Law with moving boundaries accounting for shrinkage due to the mass loss while considering plum as a composite spherical body having two concentric materials. To model, the authors considered the flesh of plum divided into N concentric spherical shells of equal thickness surrounding a spherical core. During the shrinkage, the thickness of the shells was considered equally reduced. To establish the moisture content distribution in the space time domain across the domain, a microscopic mass balance was performed in each shell for every time step. The authors solved the equations iteratively to find the moisture content distribution within the flesh and the average moisture content of the whole plum as a function of time and also considered the change in volume during drying equivalent to the amount of moisture removed. Their obtained effective moisture diffusion coefficient 2 lied in the range of 4:3 7:610 10 ms . They also concluded that their model works better at higher temperature ranges. Hence such a diffusion model is more applicable to parallel-flow (air and fruit inlet are at the same end of dryer) commercial dehydrators [15]. Stencl et al. [16], tried to determine the effect of temperature on the adsorption and desorption isotherms of prunes in the temperature range of 15–45 °C. To do the sorption test, they developed a fully computerized laboratory drying device equipped with special control software. They prepared their samples mentioned in the literature and commenced their tests. They used four equations i.e. Chung-Pfost, Halsey, Henderson and Oswin, describing the relation between EMC4 and equilibrium relative humidity to evaluate their ability to fit data for prune. Based on their findings, modified Halsey’ model was the best one predicting the adsorption and desorption EMC of dried prunes for known levels of temperature and relative humidity and it was also concluded that sorption isotherms of dried fruit can be measured by an indirect gravimetric dynamic method with sufficient accuracy for practical purposes [16]. Karathanos and Belessiotis [17] examined two types of drying processes and fitted a modified equation to their data. Hence, they did a series of experiments to find the drying constants of the Page equation applied to various high-sugar containing agricultural products such as plums. They also wanted to test whether Page equation is appropriate only for specific moisture content range or can be extended to the drying of relatively dried products. It is worth mentioning that they calculate the equilibrium moisture content through using a modified Hayakawa’s method. Their achievements showed that the Page equation can successfully predict the drying process of high-water containing fruits mentioned above while it is not able to fit the data of drying relatively dried high-sugar-containing fruits. This was attributed to the fact that besides the water evaporation, a second weight reduction mechanism has occurred. Hence, Page equation may be applied exclusively for relatively wet products [17]. Contrary to the previous diffusion based mathematical models predicting the moisture diffusion through the plum being less successful at lower temperatures [15,18] attempted to develop a mathematical model being able to predict the drying kinetics of prunes more successfully and particularly at lower temperature. His model constituted PDEs5 considering simultaneous heat and mass transfer and also shrinkage and surface evaporation. They considered the flesh of plum divided into N concentric spherical nodes of equal thickness except for the surface segment. Their mass balance equation equated the moisture stored in a node with the difference between the moisture diffused in and out of the spherical walls of node and it was the same for heat balance 4 5

Equilibrium Moisture Content. Partial Differential Equations.

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equation. The author presented the balance equations and found the model parameters i.e. convective heat transfer coefficient, thermal conductivity, specific heat of prunes, latent heat of vaporization of water etc. Through writing a computer program in C þ þ , the set of equations were solved iteratively and the simultaneous estimation of temperature and moisture distribution in the space-time domain across the fruit became possible. Based on Sabarez claim, such an analysis enables us to monitor the moisture content of different points of the product at the end of drying and detect the possible points in which the safe level of moisture is exceeded which paves the way for microbial deterioration [18]. Di Matteo et al. [19] evaluated the effectiveness of a physical pre-treatment (superficial abrasion of the plum skin) through analytically solved mathematical modeling considering dimension variations with time and the different geometry. To gain such a goal, they considered whole the drying process controlled by mass transfer only as the length of the thermal transient was considered far less than the length of drying process and to commence the modeling, the authors initially derived the analytically solved mathematical model for drying process of fruit having a large stone under the constant dimension hypothesis and to find the general model, the hypothesis was then removed. Their mathematical model of plum drying reduced to that of a mass diffusion from a spherical body surrounding an impermeable stone was solved through initial and boundary conditions considered for pulp, pulp/skin interface, skin and skin/gaseous film interface. They also applied their model to the peeled plum. In the next step, the authors took into account the changes in radius through plum dehydration. Hence, the fixed considered radius derived equations were used for computing the changes in water concentration only for a small enough time intervals as the radius can be considered fixed and the entire drying process model constituted many of these successive time intervals and finally, to identify the model parameters, the experimental data were fitted [19]. Toğrul and Pehlivan [20] studied the drying kinetics of some fruits under open-air sun drying and fitted the models to find the best describing ones. Plum was one of those fruits being pretreated with NaOH solution. Through their experiments on top of a three-floor building, they measured the temperatures of the fruit bed on the tray, air temperature, relative humidity just above the fruit bed surface and so on at 15 min intervals. The drying rates of the selected fruits were graphed against time of drying and moisture content while a decreasing trend of drying rate was reported against time and moisture content loss. Based on their findings, the drying process of all the selected fruits occurred during the falling-rate period showing the internal mass transfer as the predominant mechanism of mass transfer through those fruits. The time duration of plum drying was also reported 5 days. Finally, they obtained their drying curves and through regression work tried to find the most convenient model expressing the moisture ratio as the best fitted one to plum data was found to be the modified Henderson and Pabis model. It is also worth mentioning that authors regressed the constants of the models against fruit surface temperature and relative humidity just above the fruit surface using multiple regression analysis to find a better match between the experimental and predicted results [20]. Gabas et al. [21], tried to find the thermophysical properties i.e. density, specific heat, effective thermal conductivity and thermal diffusivity of prunes as a function of moisture content through presentation of some equations. Hence, they planned some experiments including bulk and apparent density estimation through weighing the sample occupying a container of known volume and application of an apparatus using the liquid displacement method, respectively. Moreover, the bulk porosity and effective bulk thermal conductivity of the sample were evaluated through adopting a relation and using the experimental apparatus

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consisted of a cylindrical cell made of chromium-plated brass, respectively. The effective bulk thermal diffusivity of prunes was also obtained using the method of Dickerson in an apparatus consisted of an agitated water bath. The obtained effective thermal conductivity, bulk density and effective thermal diffusivity all led to estimation of specific heat using a relation. Due to complexity of theoretical models, they selected 5 empirical models to predict the above mentioned properties through finding the best fit. Finally, they found the best-fitted empirical models for estimation of thermophysical properties of plum [21]. Menges and Ertekin [22] studied the applicability of 14 thin layer drying models to find the best model describing the thin layer drying behavior of treated (2% NaOH solution) and untreated Stanley plums. They accepted Midilli et al. model (MR ¼ a∙expð kt n Þ þ bt), where MR, k, t and a, b, n are Moisture Ratio (dimensionless), the 1 drying rate constant (h ), time (h) and the experimental constants, respectively, due to the lowest values of RMSE6 and chi-square and the highest values of EF7 for the untreated/treated plums. They also found the relations between the Midilli et al. model constants i.e. “a” and “n” with air temperature (T), “k” as a function of air flowing velocity (V) and “b” without any functionality as a constant for both treated and untreated samples of plums [22]. Ioannou et al. [23], studied the drying kinetics and performed modeling of the mirabelle plum drying. They initially modeled the sorption isotherms of this fruit at 20 and 60 °C and calculated the net sorption heat. Before starting the drying experiments, their plum samples were cut into two halves, stored and frozen and to avoid oxidation, the frozen plums were instantaneously dipped into a sucrose-saturated solution as a pre-treatment. Through their modeling, each unpeeled half of plum was approximated a thin slab of rectangular dimensions and shrinkage and external resistance were both neglected. Through their study, only a falling rate period was reported without any hardening phenomenon seen and also their applied protective pre-treatment, limiting the browning reactions, significantly slowed down the drying kinetics particularly at lower temperatures which was attributed to the formation of an additional film limiting the moisture transfer. They also found that temperature and air velocity have slight effects on effective diffusivity while it increases with temperature and decreases with air velocity. The condition giving the highest drying rate for mirabelle plum was reported 85 °C with 0.6 m/s. To model the kinetics of mirabelle plum drying, empirical models such as Newton, Page and modified page, logarithmic and approximation of diffusion were fitted to data while approximation of diffusion model was chosen as the best fit [23]. As empirical and semi-empirical models describing the thin layer drying process of plums are based on simplifying hypotheses, do not take into account the changing operating conditions during the drying process, either considering only the internal or external resistance to mass transfer in isothermal process and also do not consider the shrinkage, Sabarez [24] developed a 2-dimensional axis-symmetric mathematical model including the heat, mass and momentum processes which occur in convective drying of prunes. He performed his experiments with a computer-controlled drying system being detailed fully in his paper through 8 treatments. He presented the equations of energy balance in the food material and drying air while modeled the transient moisture transport within the food matrix considering water mass balance in the drying air. To solve the governing PDEs, the calculation of thermophysical and transport properties of the product, considering the proximate composition of prunes, air and also the heat and mass transfer coefficients was necessary. Finding all the model 6 7

Root Mean Square Error. Modeling Efficiency.

parameters, Sabarez applied a numerical approach to solve the set of time-dependent PDEs and verified his proposed model against his experimental data and reported a very good agreement. Through his research, he also did a parametric analysis on influencing parameters such as fruit size, initial moisture content, air temperature, air velocity and mode of operation (parallel/counter T flow) which seems very useful to plum dehydrator designers [24]. 2.3. Drying kinetics of plum Newman et al. [25] investigated the drying kinetics of prunes through looking at the processing parameters that affect the rate of moisture loss from the product surface including temperature, relative humidity and air-flow characteristics. In addition, the authors tried to identify the major factors influencing the rate of drying. Their drying data were fitted to a first-order equation while excellent correlations were obtained. They found a clearly marked increase in the rate of water loss above 70 °C being attributed to the poor efficiency of cell wall rupture at this temperature and also mentioned that the process of water loss is a hindered one with a tortuous path within the food matrix. The two-phase temperature regime was also investigated whether it could decrease the drying time which seemed beneficial [25]. Karathanos and Belessiotis [26] also performed drying experiments to study the drying kinetics of some agricultural products (specifically grapes) including plum. Based on their experiments through an artificial air dryer, a first falling close to constant rate and a much steeper second falling drying rate period was observed [26]. Sacilik et al. [27] studied the kinetics of Üryani plum through a convective hot-air dryer to determine the effect of air temperature and pre-treatment (being dipped in hot-water) on drying behavior of the Üryani plum, calculate the effective diffusivity and activation energy of samples and find the best-fit drying model for better description of thin-layer drying of product. They reported that the air temperature and pre-treatment have both positive effects on reducing the drying time required for drying samples from initial moisture content to a desired one. To calculate the effective diffusivity, Fick’s second law (considering simplifying assumptions) had been applied and the great effect of air temperature and pretreatment was observed. The activation energy of samples was calculated through plotting and it was found that the pre-treated samples show a lower energy of activation indicating lower energy needed for water removal from the plum. Finally, they concluded that the Two-term model is best fitted to their experimental data within the experimental range of study [27].

3. Conclusion To prolong the shelf-life of plum, decrease the shipment costs etc., it is necessary to decrease its water contents (dehydration) through drying techniques. Mean while, it was concluded that application of pre-treatments to the plum product is highly promising for reducing the time of drying, though, keeping the quality high and also consuming less energy. Moreover, in the present review, the simulation and mathematical models presented for plum drying process are also studied comprehensively and summarized which help to find critical temperature points and also foretell the processes with high precisions. Besides, studying the kinetics of plum drying through presenting some model fittings also revealed that the trend of moisture loss and drying process being widely used which also has been a matter of significance for plum and brought here.


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