ORIGINAL PAPER

Microwave Frying Compared with ConventionalFrying via Numerical Simulation

Ilkay Sensoy & Serpil Sahin & Gulum Sumnu

Received: 25 October 2011 /Accepted: 6 February 2012# Springer Science+Business Media, LLC 2012

Abstract Microwave heating can be combined with othermeans of heating to yield a unique heating profile. In thestudy, microwave frying, a combination of convective andmicrowave heating, was compared with conventional fry-ing. Frying experiments were performed by inserting asingle food sample (chicken breast meat) in the hot oil at180±1°C for both frying methods. Center temperature of thesample and the oil temperature were recorded during bothfrying methods. Simulations were performed to predict heattransfer coefficients. Processing time was shorter with mi-crowave frying. Simulations revealed a varying convectiveheat transfer coefficient, which was in the range of 160–490 W/m2 K, during conventional frying. Higher convectiveheat transfer coefficient, 500 W/m2 K, compared to conven-tional frying was observed during microwave frying withthe simulations. This is suggested to be due to higher tur-bulence in microwave frying.

Keywords Frying .Microwave .Modeling . Temperatureprofile

NomenclatureA Area perpendicular to heat transfer in square meterc Speed of light in meters per secondCp Specific heat capacity in joules per kilogram per kelvinDp Penetration depth in metersf Frequency in hertz

h Convective heat transfer coefficient in watts per squaremeter per kelvin

k Thermal conductivity (watts per meter per kelvin)m Evaporated moisture in kilogramsq�

Microwave heat absorption in watts per cubic meterq Heat flux in watts per square meterq0 Microwave surface heat absorption in watts per cubic

meterT Temperature in degree Celsiust Time in secondsx Distance from the surface in the x direction for the

chicken meat sample in meters

Greek lettersε′ Relative dielectric constant dimensionlessε″ Relative dielectric loss factor dimensionlessρ Density in kilograms per cubic meterλ Latent heat of vaporization in joules per kilogram

Subscriptsc Centeri Initialoil Frying oils Surface

Introduction

Deep fat frying is a popular and therefore important foodprocess (Ahromrit and Nema 2010; Gharachorloo et al.2010; Halder et al. 2007). The frying process can be definedas a cooking and drying process by immersing a food productin edible oil or fat at a higher temperature than the boilingpoint of water (Barutcu et al. 2009; Erdogdu and Dejmek2010; Halder et al. 2007). Simultaneous heat andmass transfer

I. Sensoy (*) : S. Sahin :G. SumnuDepartment of Food Engineering, Middle East TechnicalUniversity,Universiteler Mahallesi, Dumlupinar Bulvari, No:1,06800 Ankara, Turkeye-mail: isensoy@metu.edu.tr

Food Bioprocess TechnolDOI 10.1007/s11947-012-0805-x

occur during frying (Alvis et al. 2009; Farid and Kizilel 2009;Oztop et al. 2007a; Sahin et al. 1999). Immersing frying canbe defined by four stages (Farkas et al. 1996). During the firststage, heat transfer is by convection and food surface heats upto the boiling point of water. In the second stage, surface waterstarts to boil and evaporate. Therefore, heat transfer betweenthe oil and the food changes from natural convection to forcedconvection due to turbulence in the oil. This enhances the heattransfer coefficient. Dehydration of surface and high temper-ature cause crust layer formation in this stage. In the thirdstage, temperature in the internal region of the food increasesslowly to boiling point of water. Physicochemical changes likestarch gelatinization and protein denaturation happen in thisstage. In addition, crust layer thickness increases and watervapor transfer at the surface diminishes. At the final stage,surface evaporation ceases and no bubbles are observed at thesurface of the food (Alvis et al. 2009).

During frying, food is immersed into oil at a temperatureof 180–190°C which leads to intense vaporization of thewater in the food and transport out through the surface (Niand Datta 1999). As the water moves out, frying oil canmove in to the material. During frying food absorbs sub-stantial amount of oil which is affected by process condi-tions such as duration and temperature of the process,pretreatment of the food, and physicochemical character-istics of food and oil (Oztop et al. 2007b). Most of the oiluptake happens during cooling process because drop ofsteam pressure inside the pores forces oil at the surface tothe inside (Alvis et al. 2009; Moreira et al. 1997).

Improvement of the processing methods or exploringnew processing methods is essential for the food industry.There are alternative frying methods such as vacuum fryingand high pressure frying. Vacuum frying is carried in aclosed system where the pressure below the atmosphericlevel results in reduced frying temperature due to waterboiling point depression (Dueik and Bouchon 2011). Inhigh-pressure frying, the vapor released from the productsnaturally generates adequate pressure and known to takeless time and results in longer lasting oil or fat with lessenergy use (Erdogdu and Dejmek 2010). Microwave fryingis also considered as an alternative method to conventionalfrying due to shorter time, lower temperature of processing,and convenience of use (Gharachorloo et al. 2010). Shortertime and lower temperature of microwave heating comparedto conventional frying yield less degradation of oil(Gharachorloo et al. 2010). In addition, microwave fryinghave shown to reduce the oil uptake (Oztop et al. 2007a).

Microwave heating was simulated by several authors(Barringer et al. 1995; Campanone and Zaritzky 2010;Chen et al. 2007; Geedipalli et al. 2007; Gunasekaran andYang 2007; Knoerzer et al. 2008; Rakesh et al. 2009;Rakesh et al. 2010; Salvi et al. 2011). Modeling the fryingprocess with fundamental equations or explanations remains

a challenge due to complexity of the process, particularlythe presence of rapid evaporation and bubbles (Alvis et al.2009; Erdogdu and Dejmek 2010; Halder et al. 2007;Hubbard and Farkas 1999). Difficulties are due to both informulation of the physical problem into mathematicalequations as well as in numerical complexities of solvingthese equations (Halder et al. 2007). In microwave frying,additional complexity arises due to the calculation of elec-tromagnetic field distribution inside the oven cavity.

Number of heating methods are used to prepare foods(Rakesh et al. 2010). Customized heating profiles suitablefor a particular process can be designed by combiningdifferent heating modes (Rakesh et al. 2010). Combiningmicrowave with convection and radiation heating are exam-ples which found to be effective technique (Rakesh et al.2010). Microwave frying combines microwave and convec-tion heating. This manuscript compares microwave fryingwith conventional frying via experimental data and numer-ical simulation, which lacks in literature.

Materials and Methods

Raw Material

Sunflower oil was used as frying medium and chickenbreast meat as a food sample. Sunflower oil and chickenbreast meat were bought from a local market. Meat was keptin the freezer (−18°C) until use and thawed in the refriger-ator (4°C) before use.

Experimental Procedure

Chicken breast meats were cut in 1.7×7.5-cm dimensionswith a custom-made cutter. Then 1.1-cm slices were cut by aknife to obtain a rectangular prism with the dimensions of1.1×1.7×7.5 cm. Sample weights were checked to haveuniform range of 11.5±1 g.

Conventional frying was done on a Bunsen burner andtemperature of the oil kept constant during frying by adjust-ing the flame level manually. A domestic microwave oven(BOSH HMT 9820, BSH Ev Aletleri Sanayi ve Ticaret A.Ş.,Istanbul, Turkey) was used for microwave frying. Microwaveoven was used at 296-W power level. IMPI 2-L test was usedto determine the power level of microwave (Buffler 1993).Conventional frying was performed by using a steel containercontaining 750 mL oil. Microwave frying was performed byusing a glass container containing 750 mL oil. Oil was dis-carded after a maximum of 4-h use.

Oil was heated until the temperature of 180±1°Cbefore insertion of the single food sample for both fryingmethods. Experiments were specifically designed to be asclose as possible to real cases. Therefore, the turn table

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was used to enhance uniformity during microwave fryingand samples let float freely in the frying oil for bothfrying methods. The temperature of both chicken sliceand oil temperature were recorded by insertion of fiberoptic temperature probes (FISO Technologies Inc.,Quebec, Canada) in to the geometric center of chickensample and oil for both microwave and conventionalfrying. Position of the fiber optic probes were checkedafter each frying process to ensure the probes were notdisplaced. Data were recorded with a signal conditioner(FTI-10, FISO Technologies Inc., Quebec, Canada).

Drying rates (dm/dt) of the samples, which were used insimulations, were determined by frying the samples fordifferent time intervals: 0, 0.5, 1, 1.5, and 2 min for micro-wave frying and 0, 1, 2, 4, and 5 min for commercial frying.Moisture content of the samples was determined by dryingthe samples at 105°C oven for 48 h. All experiments wereconducted in triplicate.

Numerical Simulation

Numeric simulation was conducted on the one fourth of thesample due to symmetry. Size of the sample was assumedconstant during frying.

Governing Equations and Boundary Conditions for Con-ventional Frying Temperature distribution was obtained bya solution of energy balance equation for conventional fry-ing in three dimensions:

ρCp@T

@t¼ kr2 � T� � ð1Þ

With the initial condition:

T ¼ Ti at t ¼ 0 ð2ÞBoundary conditions are given below. x coordinate is

presented as a representative for all the coordinates.At surface, convection and phase change was considered:

qjx¼xs¼ h Ts � Toilð Þ � l

A

dm

dtð3Þ

At the center, symmetry boundary condition was used:

@T

@x

����x¼xc

¼ 0 ð4Þ

During simulations convective heat transfer coefficientwas determined by trial and error until the experimentaldata were matched. Literature values were used as start-ing point.

Governing Equations and Boundary Conditions for Micro-wave Frying For microwave frying, a local heat generation

term due to absorbed electromagnetic microwave power wasincluded in the conventional energy balance equation.

ρCp@T

@t¼ kr2 � T� �þ q

� ð5Þ

Absorbed microwave power was calculated using theLambert’s law as given for the x direction only.

q� ¼ q0e

� x=Dpð Þ ð6Þwhere penetration depth was defined as

Dp ¼ c

2pf0; 5"0

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi

1þ "00

"0

� �2s

� 1

0

@

1

A

0

@

1

A

�1=2

ð7Þ

Lambert’s law assumes power absorption as an exponen-tial decay, and it is valid only for semi-infinite geometrywith dimensions much larger than the wavelength or forlarge geometries where microwave penetration depth islower than thickness of the sample (Campanone andZaritzky 2010; Oliveira and Franca 2002). Turntable is usedin microwave oven for enhancing uniformity. In addition,presence of oil and free floating food sample in the fryingmedium makes solution of Maxwell equations for micro-wave absorption almost impossible. Therefore, for simplic-ity Lambert’s law prediction was used with the expense ofaccuracy. Boundary conditions for the energy equation(Eq. 5) for microwave frying were same as in conventionalfrying.

Simulation Geometry and mesh were formed with geometrydrawing and meshing capabilities of a software (ANSYSWorkbench 12.0, ANSYS Inc., USA). Heat transfer equa-tions were solved using a computational fluid dynamicprogram (FLUENT in ANSYS Workbench), which cansolve continuity, momentum transfer, and energy transferequations. Heat generation due to microwave heating andthe latent heat loss at the surface due to evaporation wereincluded in the solution with the inclusion of user-definedfunctions. Time step was set as 0.1 s. The simulations wererun on a personal computer with Windows 32 bit operatingsystem (Intel® Core™ 2.4 GHz 2.0 GB memory). Thermaland dielectric properties used in the simulations are pre-sented in Table 1.

Table 1 Thermal and dielectric properties of chicken

Thermal and dielectric properties Source

Specific heat, Cp 3.521 kJ/kg K (Siripon et al. 2007)

Thermal conductivity, k 0.5093 W/m K (Siripon et al. 2007)

Dielectric constant, ε′ 49.0 (Lyng et al. 2005)

Dielectric loss factor, ε″ 16.1 (Lyng et al. 2005)

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Convective heat transfer coefficient (h) of the oil duringboth conventional and microwave frying and, the microwavesurface heat absorption (q0) during microwave frying weredetermined by trial and error until the simulations matched theexperimental data. There was an on and off time for micro-wave heating. The heat transfer coefficient was determined forthe off time where there was only convective heating. Theobtained heat transfer coefficient was used during the on time,and q0 determined by trial and error until the simulation resultswere matched with the experimental data. The end results ofthe simulated data were compared with the experimental databy using the root mean squared error (RMSE). Experimentaldata points had higher time intervals than simulation datapoints. Therefore, only the simulation data corresponding tosame time intervals with the experimental data were used inRMSE calculations.

Results and Discussion

Microwave frying gave a faster heating rate due to internalheat absorption compared to conventional frying (Fig. 1).During microwave frying, the center temperature reaches to100°C in about 30 s while in conventional frying it takesmore than 160 s. The results indicate that microwave fryingcan be an alternative process for reducing the processingtime and probably reducing the oil consumption as well.

Simulation was matched with the experimental data byusing a heat transfer coefficient that changes with time forconventional frying (Fig. 2a). The heat transfer equationswhich gave matching results for the experimental data weredemonstrated below.

h ¼ 400þ 3t W=m2K� �

for the first 30 s ð8Þh ¼ 580� 3t W=m2 K

� �for the last 140 s ð9Þ

This indicates that heat transfer coefficient varied duringcommercial frying. It started as 400 W/m2 K and reached a

0

10

20

30

40

50

60

70

80

90

100

110

0 20 40 60 80 100 120 140 160 180

Tem

pera

ture

(oC

)

Time (s)

Microwave Frying

Conventional Frying

Fig. 1 Center temperatures of the chicken breast samples duringmicrowave and conventional frying processes (with ± standarddeviations)

0

20

40

60

80

100

120

140

160

180

200

0 20 40 60 80 100 120 140 160 180

Tem

pera

ture

(oC

)

Time (s)

Oil

Conventional Frying

Simulation

0

20

40

60

80

100

120

140

160

180

200

0 5 10 15 20 25 30 35

Tem

pera

ture

(oC

)

Time (s)

Oil

Microwave Frying

Simulation

(a)

(b)

Fig. 2 Experimental (with ± standard deviations) and simulated tem-perature profiles of the geometric center of the chicken breast samplewith the oil temperature a during conventional frying process; b duringmicrowave frying

0

0.5

1

1.5

2

2.5

3

0 50 100 150 200 250 300 350

Moi

stur

e co

nten

t (g

wat

er/ g

dry

sol

id)

Time (s)

Conventional Frying

Microwave Frying

Fig. 3 Moisture content of the chicken samples as function of timeduring conventional and microwave frying (with ± standard deviations)

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maximum of 490 W/m2 K and dropped to 160 W/m2 K atthe end of frying. This result is expected because duringdeep frying convective heat transfer coefficient can rangefrom 90 to 1.100 W/m2 K and strongly coupled with thebulk movement of the oil during frying (Farkas andHubbard 2000; Hubbard and Farkas 1999; Yildiz et al.2007).

At the beginning of frying, heat transfer is by naturalconvection and as the frying progress due to evaporationturbulence enhances the heat transfer. Toward the end offrying, evaporation ceases and this reduces the heat transfercoefficient. Halder et al. (2007) and Hubbard and Farkas(1999) stated that deep fat frying can be divided in twophases: boiling phase and non-boiling phase. In addition,the boiling phase can be broken in two stages: first, surfaceboiling stage where sudden loss of free moisture at thesurface enhances heat transfer and crust start to form; sec-ond, falling rate stage where crust thickens, vapor masstransfer decreases, and heat transfer decreases (Halder etal. 2007; Hubbard and Farkas 1999).

Convective heat transfer coefficient for the microwavefrying were determined by using the experimental datawhen there was only convective heating which was duringthe microwave off time (Fig. 2b). Due to short heating time,variation of the heat transfer coefficient with time was notconsidered for microwave frying simulations. Constant heattransfer coefficient values were used in the trials during theoff time. Microwave simulations gave an average convec-tive heat transfer coefficient of 500 W/m2 K. This is a highervalue when compared to conventional frying. Moisture losswas higher in microwave frying when compared to conven-tional frying (Fig. 3). This may lead higher turbulence in theoil and hence higher heat transfer coefficient. RMSE valuesfor conventional frying and microwave frying, which were0.59 and 2.49°C, respectively, demonstrates a good fit forthe simulations. RMSE value was higher for microwaveheating because the transition between the on and off timesduring microwave heating was set to be very sharp in thesimulations compared to the experimental data.

Conclusion

Microwave frying gave a shorter frying time, which can beused to reduce the processing time. Convective heat transfercoefficients obtained from the simulations showed a highervalue for microwave frying which may be due to higherturbulence during microwave frying. Heat transfer coeffi-cient can vary with time during frying as there are manystages during the process.

Acknowledgments The project is supported by the grant BAP-03-14-2010-07.

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