Ultrasonic vacuum drying technique as a novel process for shortening the drying period for beef and chicken meats

Innovative Food Science and Emerging Technologies xxx (2014) xxx–xxx

INNFOO-01193; No of Pages 9

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Innovative Food Science and Emerging Technologies

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Ultrasonic vacuumdrying technique as a novel process for shortening the drying periodfor beef and chicken meats

Mehmet Başlar ⁎, Mahmut Kılıçlı, Omer Said Toker, Osman Sağdıç, Muhammet AriciYildiz Technical University, Chemical and Metallurgical Engineering Faculty, Food Engineering Department, 34210 Istanbul, Turkey

⁎ Corresponding author. Tel.: +90 2123834579; fax: +E-mail address: [email protected] (M. Başlar).

http://dx.doi.org/10.1016/j.ifset.2014.06.0081466-8564/© 2014 Elsevier Ltd. All rights reserved.

Please cite this article as: Başlar, M., et al., Ulchicken meats, Innovative Food Science and E

a b s t r a c t
a r t i c l e i n f o
Article history:Received 31 March 2014Accepted 13 June 2014Available online xxxx

Editor Proof Received Date 14 July 2014

Keywords:DryingBeefChickenUltrasoundVacuum dryingModeling

In the present study, a novel drying technique using a combination of ultrasound and vacuum dehydration wasdeveloped to shorten the time for the drying of beef and chickenmeats. Themeats were dried using three differ-ent techniques, namely ultrasonic vacuum (USV) drying, vacuumdrying and oven drying at 55, 65 and 75 °C. Themeats dried fasterwith USV thanwith the vacuumand oven drying techniques. The drying time for the USV, vac-uum and oven drying techniques at 75 °C was determined as 300, 480 and 750 min for beef and 330, 570 and780min for chicken, respectively. The drying ratewas significantly influenced by the drying techniques and tem-peratures. The lowest energy consumption was determined in the USV technique. The drying data were success-fully fitted to 10 models (R2: 0.9140–0.9991). According to the results, the USV drying technique shortened thedrying period of beef and chicken.Industrial relevance: Beef and chicken meats dried faster with the USV dryingmethod than with the vacuum andoven drying techniques. The novel drying technique could be used to improve efficiency of the vacuum dryingtechnique. Combination of ultrasound and vacuum treatment consumed lower energy compared with ovenand vacuum drying.

© 2014 Elsevier Ltd. All rights reserved.

1. Introduction

Foods tend to deteriorate chemically and microbiologically duringstorage due to their high water activity, which negatively influencesthe nutritional value and sensory properties of the product as well asthe formation of detrimental compounds. Therefore, various preserva-tion methods have been improved to extend the shelf life of productssince ancient times. Drying is one of the oldest preservation techniquesinwhichmass and heat transfers occur simultaneously (Akpinar, 2006).Meat products are dried for different aims such as powdered meat,fermented sausages and dry-cured hams (Arnau, Serra, Comaposada,Gou, & Garriga, 2007). Dried meats are used as an ingredient in variousfood products; for instance, dried chicken, sliced or cubic, can be addedto ready-to-eat noodle formulations (Natharanakule, Kraiwanichkul, &Soponronnarit, 2007). Hot air drying is the most widely used method;however, it causes the deterioration of aroma compounds (Timoumi,Mihoubi, & Zagrouba, 2007), the degradation of nutritional compounds(Suvarnakuta, Devahastin, & Mujumdar, 2005) and lipid oxidation(Toujani, Hassini, Azzouz, & Belghith, 2013). Drying is the most expen-sive step during manufacturing of dried meat products due to the timeand effort to control the system and preserve the product and theenergy consumed during the drying process (Traffano-Schiffo, Castro-Giráldez, Fito, & Balaguer, 2014). Since the meat sector is one of the

90 2123834571.

trasonic vacuum drying technmerging Technologies (2014),

most important sectors in the European Union (Traffano-Schiffo et al.,2014), creating a new drying technique as an alternative to traditionalones to decrease cost and increase the quality of the dried product isvery important for the food industry.

In recent years, attempts have been made to shorten the dryingperiod to improve the energy efficiency of the drying process and thequality of the dried products (Chou & Chua, 2001). The quality of thedried products could be improved by decreasing the drying tempera-ture or the drying period. Therefore, instead of oven or convective dry-ing, vacuum drying is widely preferred. Moreover, some pretreatmentsare used in order to speed up the drying process. Ultrasound treatmentis widely used as a pretreatment technique to accelerate drying. Apply-ing ultrasound interrupts the continuity of themembranes, and thus in-creases the mass transfer rate between the cell and its extracellularsurroundings (Nowacka, Wiktor, Śledź, Jurek, & Witrowa-Rajchert,2012). Ultrasound treatment is connected to drying during the processand as a preliminary treatment positively affects the drying process interms of improving the quality of the dried products and reducing theenergy consumed during drying. Ultrasound can be applied to improvethe convective heat transfer coefficient (Lima & Sastry, 1990), to accel-erate freezing rates during freezing of potatoes (Li & Sun, 2002) or toincreasemass transfer for different products and processes such as brin-ing ofmeat and cheese (Muralidhara, Ensminger, & Putnam, 1985; Sajas& Gorbatow, 1978). However, although ultrasound treatment can beused in many ways to accelerate drying processes, it has not been con-nected with vacuum drying. Therefore, in the present study, ultrasound

ique as a novel process for shortening the drying period for beef andhttp://dx.doi.org/10.1016/j.ifset.2014.06.008

http://dx.doi.org/10.1016/j.ifset.2014.06.008

mailto:[email protected]


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Fig. 1. A schematic view of the novel drying technique composed of ultrasound and vacu-um systems.

2 M. Başlar et al. / Innovative Food Science and Emerging Technologies xxx (2014) xxx–xxx

and vacuum processes were combined as a novel drying technique. Inthis method, the advantages of both processes were used to shortenthe drying period. To our knowledge, no studies on the use of ultra-sound and vacuum combined to dry meat or any other food productshave been conducted.

The objective of thepresent study is to develop a newdryingmethodby combining ultrasound and vacuum processes. For this aim, beef andchicken meats were dried with oven, vacuum and ultrasonic vacuumtechniques at different temperatures (55 °C, 65 °C and 75 °C). Thedrying data were modeled with various drying models to determinethe change in the moisture content of the meat samples as a functionof drying time.

2. Materials and methods

2.1. Materials

Top round beef and chicken breast, used as raw material in thepresent study, were obtained from a butcher in Istanbul, Turkey. Topground beef meat was obtained from beef at 2-years old (Balıkesir,Turkey). Chicken breast meat was obtained from broiler chicks (Ross308) at 6 weeks (Erpiliç A.Ş., Bolu, Turkey). Physicochemical propertiesof the meats analyzed are presented in Table 1. Beef meat and chickenbreast were cut to a size of 5 cm × 5 cm × 1 cm (30 ± 0.5 g).

2.2. Physicochemical properties of meat samples

Dry matter, ash and protein content of meat samples was deter-mined in the present study. Dry matter content of sliced meat sampleswas determined by a modified procedure of AOAC (1995). Meat sam-ples were dried at 105 °C by drying oven until constant weight wasreached. Ash content of the samples was determined by incineratingthem at 600 °C for 5 h in a muffle oven (Daihan, F-12, South Korea).Protein content of the samples was determined by the Kjeldahlmethod.The Kjeldahl system consists of an infrared heater, a distillator and atitrator (Behr InKjel 625P/S5/TB1, Germany). Twentymilliliters of sulfu-ric acid was added to 2 g meat samples and then 2 Kjeldahl tablets(SIAL) were added. The prepared mixture was burned with an infraredKjeldahl heater according to the following conditions: 50% power for 30min, 70% for 30min and 100% for 60min. Themaximum heating powerof the system (100%) is 1500 W. Then the burned solution was dilutedwith NaOH (40%), boric acid (5% w/v) was added and then this mixturewas titrated with 0.1 N HCl using an automatic titrator until 4.6 pH wasreached. The factor 6.25 was used for calculation of protein content. Fatcontent of sampleswas determined by the Soxhletmethod. Fat found inmeat samples was extracted from dried meat samples with hexane bythe Soxhlet extraction system (Daihan, WHM-12293, South Korea).After evaporation of hexane by a rotary evaporator, the extracted fatwas weighed and it was divided by initial weight of the meat samplesto determine fat content.

2.3. Drying of meat samples with different techniques

The USV technique is composed of an ultrasoundwater bath (Daihan,WUC-D10H, South Korea) and a vacuum pump (KNF N838.3KT.45.18,Germany) as shown in Fig. 1. In this technique, meat samples were putinto a conical flask which was connected to a vacuum pump as seen in

Table 1Physicochemical properties of beef and chicken meats used in the present study.

Beef Chicken

Dry matter (%) 25.94 ± 0.21 25.29 ± 0.35Protein (%) 22.89 ± 0.20 21.86 ± 0.45Fat (%) 1.61 ± 0.05 1.75 ± 0.08Ash (%) 1.23 ± 0.04 1.13 ± 0.02

Please cite this article as: Başlar, M., et al., Ultrasonic vacuum drying technchicken meats, Innovative Food Science and Emerging Technologies (2014),

Fig. 1. Then vacuum treated sample was sonicated at 40 kHz using anultrasonic bath (Daihan, WUC-D10H, South Korea) (amplitude: 100%,power: 590 W, volume: 10 L). The temperature of the ultrasound waterbath was controlled (thermocouple (k-type, Omega Engineering Inc.,USA)) and fluctuation of the water temperature in the bath wasprevented by circulation of water. The weight of the meat samplesdried with three different techniques at different temperatures asmentioned above was measured at each 30 min. All weighing processestake 15 s after removing of the sample from the drying system, whichwas important for obtaining reproducible drying curves (Jamradloedluk,Nathakaranakule, Soponronnarit, & Prachayawarakorn, 2004).

2.4. Mathematical modeling of drying kinetics

Both meat samples were dried with US–vacuum (USV) drying, vac-uum drying and oven drying at 55, 65 and 75 °C until about 25% mois-ture content (d.b.).

MR ¼ w−we

w0−weð1Þ

wherew is themoisture content at any time,we is the equilibriummois-ture content andw0 is the initial moisture content of the meat samples.In the present study, this equation was simplified to MR = w / w0

described by Rayaguru and Routray (2012) since we was very smallcompared to w or w0.

In the present study, the obtained drying data (time versus MR)were modeled by 10 different models and equations of them arepresented in Table 2. In these equations, MR represents the moistureratio of the samples at any time and t is the drying time. The obtaineddata were fitted to the models and their corresponding constantswere calculated using Statistica program software (StatSoft Inc., USA).Moreover, drying rate (DR) and effective moisture diffusivity (Deff)were calculated according to Eqs. (2) and (3), respectively (Doymaz,2013) for both beef and chicken meat samples.

DR ¼ Mt−MtþΔt

Δtð2Þ

whereMt andMt + Δt are the moisture content of the samples at time tand t + Δt, respectively, and t is the time (min).

MR ¼ 8π2 exp −

π2Deff t

4L2

!ð3Þ

where Deff is the effective moisture diffusivity (m2/s) and L is the halfthickness of meat slab.



Table 2Drying models used in the present study to fit data obtained from drying of beef and chicken meats at different conditions.

Model names Equation Reference

Lewis (Newton) MR = exp (−k · t) Bruce (1985)Page MR = exp (−k · tn) Madamba, Driscoll, and Buckle (1996)Modified Page MR = exp (−(k · t)n) White, Bridges, Loewer, and Ross (1981)Henderson and Pabis MR = a exp (−(k · t)) Henderson and Pabis (1961)Logarithmic MR = a exp (−(k · t)) + c Togrul and Pehlivan (2002)Two-term MR = a exp (−k0 · t) + b exp (−k1 · t) Henderson (1974)Two-term exponential MR = a exp (−k · t) + (1 − a) exp (−k · a · t) Henderson (1974)Wang and Singh MR = 1 + a · t + b · t2 Wang and Singh (1978)Diffusion approach MR = a exp (−k · t) + (1 − a) exp (−k · b · t) Yaldiz, Ertekin, and Uzun (2001)Thompson t = a lnMR + b (lnMR)2 Thompson, Peart, and Foster (1968)

MR: Moisture ratio.

3M. Başlar et al. / Innovative Food Science and Emerging Technologies xxx (2014) xxx–xxx

Temperature dependency of Deff was calculated using the Arrheniusequation expressed as the following (Eq. (4)) (Mota, Luciano, Dias,Barroca, & Guine, 2010).

Deff ¼ D0eff exp − Ea

RT

� �ð4Þ

whereDeff0 is the diffusivity for infinite temperature (m2/s), T is the dry-

ing temperature (Kelvin), Ea is the activation energy (J/mol) and R is thegas constant (8.31451 J/mol K).

2.5. Energy consumption

Energy consumed at each process during drying of the samples wasmeasured using an energy meter (PeakTech 9035, Germany) as men-tioned in the study of Baslar and Ertugay (2013).

2.6. Statistical analysis

Drying kinetics data of the samples were analyzed using Statistica6.0 software (StatSoft Inc., USA). Nonlinear regression analysis was per-formed based on the Levenberg–Marquardt algorithm to calculate cor-responding parameters of the models mentioned in Table 2. Validationof the statistical models was determined using R2, χ2 and RMSE values

0.0

0.2

0.4

0.6

0.8

1.0

0.0 5.0 10.0 15.0 20.0 25.0

MR

Time (h)

Oven

Vacuum

USV

55 oC

0.0

0.2

0.4

0.6

0.8

1.0

0.0 5.0 10.0

MR

Ti

75

Fig. 2. Drying curves of top round beef m


calculated using the following equations (Delgado, Pereira, Baptista,Casal, & Ramalhosa, 2014):

SST ¼Xni¼1

yexp;i−ypred;i� �2 ð5Þ

SST ¼Xni¼1

yexp−yave� �2 ð6Þ

R2 ¼ 1− SSESST

ð7Þ

RMSE ¼ffiffiffiffiffiffiffiffiffiffiffiffiSSEn−m

rð8Þ

χ2 ¼

Xni¼1

yexp;i−ypred;i� �2

n−mð9Þ

yexp,i and ypred,i are the experimental and predictedMR values of ith ob-servation, and n andm are the observation number and number of con-stants in the corresponding model (Togrul & Pehlivan, 2003; Yaldiz &Ertekin, 2001).

0.0

0.2

0.4

0.6

0.8

1.0

0.0 5.0 10.0 15.0 20.0 25.0

MR

Time (h)

Oven

Vacuum

USV

65 oC

15.0 20.0 25.0me (h)

Oven

Vacuum

USV

oC

eat dried with different techniques.



0.0

0.2

0.4

0.6

0.8

1.0

0 5 10 15 20 25

MR

Time (h)

Oven

Vacuum

USV

55 oC

0.0

0.2

0.4

0.6

0.8

1.0

0 5 10 15 20 25

MR

Time (h)

Oven

Vacuum

USV

65 oC

0.0

0.2

0.4

0.6

0.8

1.0

0 5 10 15 20 25

MR

Time (h)

Oven

Vacuum

USV

75 oC

Fig. 3. Drying curves of chicken breast meat dried with different techniques.


3. Results and discussion

3.1. Physicochemical properties of meat samples

The dry matter content of the beef and chicken meats was 25.94%and 25.29%, respectively (Table 1). As seen in the table, protein is themajor component of both meat types except for water. The proteincontent of the beef and chicken meat samples was 22.89% and 21.86%,respectively. The fat contentwas 1.61% and 1.75% for the beef and chick-enmeat samples, and the ash contentwas 1.23% and 1.13%, respectively.The chemical composition of the meat samples was very similar. Ourfindings are consistent with the literature in which it was reportedthat meat tissue consists of approximately 75% water, 20% protein,2.5% fat, 1.5% ash and 1% carbohydrate (Candogan, 2013).

Table 3Drying time and energy consumption of different drying techniques applied to beef and chicke

Sample Drying method Temp.(°C) Drying time (h)

Beef US/vacuum 55 16.565 10.075 5.0

Vacuum 55 18.065 14.575 8.0

Oven 55 25.565 17.075 12.5

Chicken US/vacuum 55 16.565 7.075 5.5

Vacuum 55 18.565 13.075 9.5

Oven 55 20.065 14.575 13.0

a consump: consumption.b DR: Drying rate calculated according to Eq. (2).c Deff: Effective moisture diffusivity calculated using Eq. (3).


3.2. Drying kinetics of meat samples

The drying curves (time versus moisture ratio (MR)) of the beef andchicken meat samples dried with three techniques (ultrasonic vacuum[USV], vacuum and oven) at different temperatures are presented inFigs. 2 and 3, respectively. The MR decreased exponentially with timein both meat samples; this was in agreement with the results reportedin different studies in which different materials were dried (Doymaz,2005; Hii, Law, & Cloke, 2009; Iguaz, San Martin, Maté, Fernández, &Vírseda, 2003; Markowski, Bialobrzewski, & Modrzewska, 2010;Perea-Flores et al., 2012). A fast decrease in the MR was observed forall drying techniques applied at different temperatures at the beginningof thedryingprocess; however, this reduction rate decreased as thedry-ing proceeded. As shown in the figures, the slope of the curves changed

n meats.

Energy consump (kW·h)a DR (h−1)b Deff (m2/s)c

3.808 0.158 1.75 × 10−8

3.268 0.261 3.03 × 10−8

2.036 0.519 5.28 × 10−8

3.527 0.145 1.69 × 10−8

3.412 0.180 2.43 × 10−8

2.286 0.326 3.41 × 10−8

4.145 0.102 1.06 × 10−8

3.548 0.153 1.68 × 10−8

3.324 0.208 2.76 × 10−8

3.808 0.167 1.70 × 10−8

2.288 0.388 3.85 × 10−8

2.239 0.499 5.73 × 10−8

3.624 0.149 1.38 × 10−8

3.059 0.212 2.14 × 10−8

2.714 0.287 2.82 × 10−8

3.251 0.138 1.14 × 10−8

3.026 0.191 1.83 × 10−8

3.457 0.210 2.68 × 10−8



Table 4Estimated model parameters and statistical parameters obtained from fitting of the drying models for beef meat.

Model Parameter Ultrasonic vacuum Vacuum Oven

55 °C 65 °C 75 °C 55 °C 65 °C 75 °C 55 °C 65 °C 75 °C

Lewis k 0.1327 0.2283 0.3996 0.1276 0.1828 0.2595 0.0811 0.1274 0.2075RMSE 0.0192 0.0219 0.0230 0.0246 0.0309 0.0296 0.0331 0.0198 0.0248R2 0.9942 0.9927 0.9932 0.9897 0.9836 0.9867 0.9759 0.9933 0.9900χ2 0.0004 0.0005 0.0006 0.0006 0.0009 0.0009 0.0011 0.0004 0.0006

Page k 0.1362 0.2504 0.3731 0.1536 0.2496 0.2851 0.1102 0.1361 0.2622N 0.9891 0.9430 1.070 0.9113 0.8278 0.9329 0.8812 0.9688 0.8621RMSE 0.0188 0.0199 0.0195 0.0191 0.0081 0.0278 0.0226 0.0196 0.0075R2 0.9942 0.9944 0.9951 0.9934 0.9899 0.9880 0.9829 0.9939 0.9992χ2 0.0004 0.0004 0.0005 0.0004 7 × 10−5 0.0009 0.0005 0.0004 6 × 10−5

Modified Page k 0.1328 0.2296 0.3985 0.1286 0.1878 0.2604 0.0822 0.1276 0.2116n 0.9892 0.9428 1.0703 0.9110 0.8282 0.9349 0.9201 0.9687 0.8624RMSE 0.0191 0.0199 0.0204 0.0188 0.0071 0.0276 0.0082 0.0189 0.0071R2 0.9943 0.9140 0.9947 0.9934 0.9991 0.9884 0.9751 0.9938 0.9992χ2 0.0004 0.0004 0.0005 0.0004 5 × 10−5 0.0009 0.0002 0.0004 5 × 10−5

Henderson a 0.9758 0.9639 1.0047 0.9545 0.9276 0.9682 0.9281 0.9692 0.9483k 0.1290 0.2191 0.4017 0.1210 0.1679 0.2499 0.0742 0.1229 0.1955RMSE 0.0173 0.0178 0.0229 0.0191 0.0201 0.0272 0.0189 0.0165 0.0181R2 0.9953 0.9951 0.9933 0.9936 0.9930 0.9888 0.9876 0.9952 0.9947χ2 0.0003 0.0004 0.0006 0.0004 0.0004 0.0008 0.0004 0.0003 0.0003

Logarithmic a 1.0361 1.0011 1.1507 0.9447 0.8901 1.0277 1.0581 1.0395 0.9112k 0.1086 0.1955 0.2928 0.1255 0.2057 0.2130 0.0541 0.1011 0.2363c −0.0790 −0.0404 −0.1709 0.0143 0.0664 −0.0748 −0.1584 −0.0910 0.0637RMSE 0.0136 0.0162 0.0113 0.0186 0.0131 0.0256 0.0197 0.0128 0.0104R2 0.9971 0.9960 0.9984 0.9937 0.9971 0.9901 0.9914 0.9973 0.9982χ2 0.0002 0.0003 0.0002 0.0004 0.0002 0.0008 0.0004 0.0002 0.0001

Two-term a 21.065 0.4769 0.5024 −10.189 −11.994 −1.8886 0.4624 0.6842 10.909k1 0.1789 0.2192 0.4016 0.1210 0.1679 0.3081 0.0742 0.1229 0.1955b −20.111 0.4870 0.5023 11.144 12.921 2.8528 0.4657 0.2850 −9.960k2 0.1821 0.2191 0.4017 0.1210 0.1679 0.2863 0.0742 0.1229 0.1955RMSE 0.0147 0.0178 0.0228 0.0191 0.0201 0.0272 0.0189 0.0165 0.0181R2 0.9966 0.9951 0.9933 0.9936 0.9930 0.9889 0.9876 0.9952 0.9947χ2 0.0002 0.0004 0.0008 0.0004 0.0005 0.0010 0.0004 0.0003 0.0004

Two-term exponential a 1.2694 0.6721 1.5314 0.4355 0.1872 0.6376 0.0821 1.1690 0.2970k 0.1411 0.2617 0.4871 0.2088 0.7945 0.3066 0.8955 0.1307 0.5213RMSE 0.0190 0.0218 0.0190 0.0201 0.0086 0.0295 0.0181 0.0198 0.0074R2 0.9943 0.9928 0.9954 0.9924 0.9987 0.9869 0.9879 0.9934 0.9991χ2 0.0004 0.0005 0.0004 0.0004 8 × 10−5 0.0010 0.0003 0.0004 6 × 10−5

Wang and Singh a −0.1089 −0.1864 −0.3189 −0.1069 −0.1496 −0.2128 −0.0675 −0.1047 −0.1703b 0.0034 0.0099 0.0282 0.0033 0.0064 0.0130 0.0013 0.0032 0.0083RMSE 0.0295 0.0352 0.0213 0.0363 0.0486 0.0425 0.0445 0.0301 0.0430R2 0.9863 0.9811 0.9942 0.9745 0.9593 0.9727 0.9560 0.9846 0.9701χ2 0.0009 0.0014 0.0006 0.0014 0.0025 0.0020 0.0021 0.0010 0.0020

Diffusion a −2.4579 0.0586 0.1355 0.0611 0.1868 0.0581 0.0897 0.0420 0.2507b 0.9505 0.0422 1.0000 0.0335 0.1666 0.0509 0.0255 0.0378 0.2759k 0.1577 5.0445 0.3996 3.5377 0.8880 4.7532 2.840 3.2028 0.5852RMSE 0.0191 0.0152 0.0230 0.0172 0.0082 0.0252 0.0136 0.0154 0.0073R2 0.9943 0.9965 0.9932 0.9946 0.9988 0.9904 0.9900 0.9956 0.9991χ2 0.0004 0.0003 0.0007 0.0003 7 × 10−5 0.0008 0.0002 0.0003 6 × 10−5

Thompson a −8.4368 −4.7433 −2.9711 −8.2280 −4.8466 −4.6372 −14.351 −8.6965 −4.3611b −0.6350 −0.2371 −0.3653 −0.1522 0.6003 −0.5371 −1.4006 −0.6080 0.4416RMSE 0.3283 0.1793 0.0646 0.5359 0.3129 0.3178 0.8419 0.2854 0.2535R2 0.9955 0.9965 0.9983 0.9884 0.9948 0.9835 0.9838 0.9965 0.9954χ2 0.1145 0.0355 0.0051 0.3036 0.1049 0.1145 0.7371 0.0864 0.0696


during drying, indicating that the drying rates changed during the dry-ing period. This change was observed to be larger than that in the ovendrying data. For example, the drying rate decreased after 5.6 h and 7 hfor the beef and chicken meats, respectively, oven dried at 75 °C. Ac-cording to the kinetic theory, the drying process is composed of threestages. In the first stage, known as the induction period, the waterflowmechanisms are coupled (Traffano-Schiffo et al., 2014). In the sec-ond stage, the drying rate reaches the maximum value, and in the thirdstage, the falling drying rate period, thewaterflux from the inside to thesurface of the sample is smaller than the surface evaporation rate(Traffano-Schiffo et al., 2014). Natharanakule et al. (2007) divided thedrying period into three stages and reported that the drying rate waslower in the second and third stages than in the first stage. Proteinsmight be denaturated since meats are subjected to heat during drying;therefore, a gel matrix is formed. As a result, removing water from in-side parts of the samples is more difficult (Natharanakule et al., 2007).


Moreover, surface moisture evaporates quickly at the initial stage ofthe drying process due to the higher heat transfer andmass transfer co-efficient (Toujani et al., 2013). Both meat samples dried faster in dryingprocesses carried out at higher temperatures, which was consistentwith previous studies (Giri & Prasad, 2007; Krokida & Marinos-Kouris,2003; Laopoolkit & Suwannaporn, 2011). This can be explained by thefact that higher drying temperatures cause higher heat and mass trans-fer (Toujani et al., 2013). In other words, increasing the drying temper-ature decreased the drying period. The drying period of the dryingtechniques at different temperatures is shown in Table 3. As shown inthis table, the type of drying technique and the drying temperature in-fluenced the drying period. The drying time required for drying thebeef sample with the USV technique at 55 °C, 65 °C and 75 °C was16.5 h, 10.0 h and 5.0 h, respectively and that for the chicken meatwas 16.5 h, 7.0 h and 5.5 h, respectively. Among the drying techniquesused in this study, the shortest drying period was observed in the USV



Table 5Estimated model parameters and statistical parameters obtained from fitting of the drying models for chicken meat.

Model Parameters Ultrasonic vacuum Vacuum Oven

55 °C 65 °C 75 °C 55 °C 65 °C 75 °C 55 °C 65 °C 75 °C

Lewis k 0.1285 0.2931 0.4305 0.1054 0.1628 0.2141 0.0883 0.1389 0.1989RMSE 0.0223 0.0311 0.0295 0.0314 0.0212 0.0306 0.0410 0.0287 0.0183R2 0.9928 0.9854 0.9876 0.9792 0.9928 0.9858 0.9572 0.9881 0.9953χ2 0.0005 0.0010 0.0010 0.0010 0.0005 0.0010 0.0017 0.0009 0.0003

Page k 0.1113 0.3224 0.4891 0.1022 0.1801 0.2170 0.0713 0.1141 0.1932n 1.0684 0.9252 0.8682 1.0153 0.9473 0.9921 1.0880 1.1001 1.0193RMSE 0.0193 0.0288 0.0209 0.0311 0.0192 0.0308 0.0424 0.0252 0.0184R2 0.9943 0.9877 0.9938 0.9788 0.9941 0.9861 0.9603 0.9908 0.9951χ2 0.0004 0.0010 0.0005 0.0010 0.0004 0.0011 0.0019 0.0007 0.0004

Modified Page k 0.1281 0.2942 0.4383 0.1054 0.1633 0.2142 0.0886 0.1385 0.1984n 1.0684 0.9256 0.8675 1.0148 0.9473 0.9916 1.0886 1.1007 1.0187RMSE 0.0196 0.0287 0.0197 0.0318 0.0194 0.0306 0.0431 0.0244 0.0180R2 0.9944 0.9876 0.9945 0.9793 0.9940 0.9858 0.9598 0.9914 0.9955χ2 0.0004 0.0009 0.0005 0.0011 0.0004 0.0010 0.0020 0.0006 0.0004

Henderson a 1.0071 0.9707 0.9550 0.9721 0.9678 0.9747 0.9847 1.0070 0.9979k 0.1295 0.2831 0.4090 0.1020 0.1567 0.2079 0.0867 0.1400 0.1984RMSE 0.0221 0.0291 0.0243 0.0288 0.0179 0.0291 0.0396 0.0286 0.0183R2 0.9929 0.9872 0.9916 0.9808 0.9949 0.9871 0.9578 0.9882 0.9953χ2 0.0005 0.0010 0.0007 0.0009 0.0003 0.0009 0.0016 0.0009 0.0004

Logarithmic a 1.1049 1.0098 0.9451 1.3239 1.0236 1.1415 3.0266 1.2437 0.9994k 0.1007 0.2544 0.4232 0.0542 0.1342 0.1436 0.0162 0.0864 0.1972c −0.1250 −0.0492 0.0134 −0.4009 −0.0718 −0.1986 −2.1189 −0.2802 −0.0024RMSE 0.0153 0.0285 0.0242 0.0205 0.0155 0.0214 0.0258 0.0112 0.0183R2 0.9966 0.9878 0.9917 0.9931 0.9961 0.9930 0.9891 0.9982 0.9953χ2 0.0003 0.0010 0.0008 0.0005 0.0003 0.0005 0.0007 0.0001 0.0004

Two-term a 0.4035 −0.0000 1.2958 0.4781 0.4765 0.5096 0.4920 0.8197 −3.9945k1 0.1295 −1.1059 0.4090 0.1020 0.1567 0.2079 0.0867 0.1400 0.1619b 0.6037 0.9600 −0.3407 0.4940 0.4913 0.4651 0.4927 0.1873 4.9884k2 0.1295 0.2714 0.4091 0.1020 0.1567 0.2079 0.0867 0.1400 0.1683RMSE 0.0221 0.0254 0.0243 0.0288 0.0179 0.0291 0.0396 0.0286 0.0181R2 0.9929 0.9903 0.9916 0.9808 0.9949 0.9871 0.9578 0.9882 0.9954χ2 0.0006 0.0009 0.0009 0.0009 0.0004 0.0011 0.0017 0.0009 0.0004

Two-term exponential a 1.5297 0.5429 0.1078 1.4391 0.6875 1.3653 1.5810 1.5910 1.3543k 0.1564 0.3905 3.5337 0.1220 0.1834 0.2381 0.1116 0.1755 0.2195RMSE 0.0184 0.0307 0.0152 0.0317 0.0211 0.0302 0.0418 0.0227 0.0180R2 0.9950 0.9858 0.9967 0.9803 0.9928 0.9862 0.9623 0.9925 0.9955χ2 0.0004 0.0011 0.0003 0.0011 0.0005 0.0010 0.0018 0.0006 0.0003

Wang and Singh a −0.1040 −0.2418 −0.3496 −0.0842 −0.1343 −0.1729 −0.0669 −0.1097 −0.1608b 0.0030 0.0170 0.0349 0.0020 0.0052 0.0084 0.0011 0.0033 0.0072RMSE 0.0215 0.0439 0.0477 0.0368 0.0350 0.0358 0.0417 0.0212 0.0214R2 0.9933 0.9710 0.9676 0.9770 0.9803 0.9806 0.9716 0.9935 0.9936χ2 0.0005 0.0022 0.0027 0.0014 0.0013 0.0014 0.0018 0.0005 0.0005

Diffusion a 1.0165 0.0694 0.1074 −4.2319 0.0484 0.4972 −11.276 −10.155 3.0414b −0.6855 0.0969 0.0392 0.9374 0.0460 1.0002 0.9618 0.9579 0.9447k 0.1172 2.7878 9.6782 0.1458 3.3352 0.2141 0.1378 0.2158 0.1767RMSE 0.0164 0.0268 0.0137 0.0317 0.0164 0.0306 0.0418 0.0222 0.0182R2 0.9961 0.9891 0.9973 0.9805 0.9957 0.9858 0.9630 0.9929 0.9954χ2 0.0003 0.0009 0.0003 0.0011 0.0003 0.0011 0.0019 0.0005 0.0004

Thompson a −8.8515 −3.9822 −2.5204 −11.553 −7.1174 −5.4913 −14.448 −8.6662 −4.4773b −0.8478 −0.3990 −0.0962 −1.6356 −0.6691 −0.6288 −2.6697 −1.1697 0.3143RMSE 0.3237 0.2616 0.1496 0.5486 0.3517 0.2380 0.7421 0.1980 0.2989R2 0.9956 0.9853 0.9925 0.9900 0.9918 0.9932 0.9837 0.9979 0.9941χ2 0.1114 0.0790 0.0269 0.3176 0.1336 0.0629 0.5788 0.0420 0.0965


drying technique performed at 75 °C, approximately 2.5 times less thanthe oven drying technique for the beef and chicken meat samples. Asseen from the results, US treatment accelerated the drying process ofboth meat samples. Ultrasound treatment modified the diffusionboundary layer due to pressure variations, oscillating viscosities andmicrostreaming at the interfaces (Rodríguez, Mulet, & Bon, 2014). Agi-tation in the fluid produced by ultrasound can decrease the external re-sistance tomass transfer by increasing bulk transport within the sample(Mulet, Cárcel, Benedito, Simal, & Rosselló, 1999). Moreover, US wavescan cause a series of compressions and expansions of the sample,which results in pressure changes in solid material (Mulet, Cárcel,Sanjuán, & Bon, 2003). The sponge effect produced as a result of thesepressure changes accelerates removal of the moisture from the insidepart of the sample (Mulet et al., 2003). In addition, compressions andexpansions of the material can produce micro-channels appropriatefor fluid movement (Muralidhara et al., 1985). All these factors


mentioned above influence internal resistance to mass transfer (Muletet al., 2003). US treatment can also increase the heat transfer coefficient(Lima & Sastry, 1990; Sastry, Shen, & Baisdell, 1989), which can also ac-celerate the removal of moisture from the sample due to higher heattransfer. Drying time differences between the USV and the vacuum oroven drying technique increased as the drying temperature increased.Decreasing drying time is very important for the food industry sincemeat includes fat, which is degraded to peroxides when it is subjectedto heat treatment. Lipid oxidation causes deterioration in the qualityof meat products, and thus decreases storage shelf life and nutritionalvalue and negatively affects organoleptic characteristics (Contini et al.,2014). Therefore, fats could be less damaged when meat is dried withthis novel drying technique, USV, and vacuum drying instead of ovendrying. In addition, decreasing the drying period is significant for prod-ucts that contain thermolabile substances. As seen in Table 3, the oppo-site trend between the drying time and the drying rate (DR) was



Table 6Arrhenius equation parameters calculated for the Deff value of beef and chicken meatsamples.

Sample Dryingtechnique

Deff (m2/s)

Deff0 (m2/s) Ea (J/mol) R2

Beef USV 2 × 1016 50,144 0.9972Vacuum 3 × 1013 33,252 0.9983Oven 2 × 1015 46,123 0.9995

Chicken USV 1 × 1016 49,231 0.9694Vacuum 2 × 1013 32,371 0.9876Oven 2 × 1014 39,682 0.9983


observed, meaning that the DR increased with the drying temperature.In other words, the increase in temperature accelerated the drying pro-cess of the beef and chicken meats in all drying techniques. Higher dry-ing temperature resulted in a higher drying rate, indicating fasterreduction in moisture content; therefore, the drying time decreased.Similar results were reported for apple (Akpinar, Bicer, & Midilli,2003), pear (Doymaz, 2013; Guiné, Ferreira, Barroca, & Gonçalves,2007) and potato (Falade & Solademi, 2010).

Consumption of energy during the drying process should be consid-ered when selecting a drying technique to decrease the cost of theprocess used. Therefore, the amount of energy consumed during dryingis also summarized in Table 3. Energy consumed during drying ofmeat samples with the USV, vacuum and oven techniques varied be-tween 3.808 and 2.026 kW·h, 3.527 and 2.286 kW·h and 4.145 and3.324 kW·h for beef meat and 3.808 and 2.239 kW·h, 3.624 and2.714 kW·h and 3.457 and 3.026 kW·h for chicken meat, respectively.The energy consumed decreased as the drying temperature increasedfor all the processes. Therefore, a higher drying temperature should be se-lected regarding energy consumption, which is very important for reduc-ing the cost of the process. The order of the energy consumed in dryingprocess carried out at 65 °C and 75 °C was oven N vacuum N USV tech-nique in beef meat samples. The order of drying techniques in terms ofenergy consumption was similar in the chicken sample dried at 75 °C.However, at 55 °C and 65 °C, the order was USV N vacuum N oven andvacuum N oven N USV. Therefore, the USV drying technique could beused to dry the beef samples at all temperatures in terms of energy con-sumption. However, another important parameter is the quality of theend product, which is related to the functional properties of the product.Further studies should be conducted to compare the quality parametersof the different products dried with the USV, vacuum and oven dyingmethods.

3.3. Modeling of drying kinetics

Drying time versusMR data obtained experimentally from drying ofmeat samples with different techniques at different temperatureswere fitted to 10 models whose equations and related parameters arepresented in Table 2. The corresponding parameters of the models andthe R2, χ2 and RMSE values, calculated to observe the accuracy of themodels, are presented in Tables 4 and 5 for the beef and chickenmeats, respectively. The model with the higher R2 and lower χ2 andRMSE values has sufficient prediction ability. The R2 values of themodels varied between 0.9560 and 0.9991 for beef meat and 0.9982and 0.9598 for chicken meat. As seen from the tables, the R2 valueswere larger than 0.95, indicating a good fit since R2 value close tounity implies that the predicted datawere near the experimental dryingdata. This means that all established models successfully described therelation between time and MR. In other words. in fact, the MR of thesamples at any time of the drying process could be predicted usingthese models. Another statistical parameter calculated to compare themodel's accuracy was the RMSE value, which represents the differencesbetween the predicted and experimental values. Therefore, the fact thatRMSE close to zero is desired. The RMSE values calculated for beef meat


ranged from 0.0071 to 0.8419 for chicken meat. Regarding the RMSEvalues, the Thompson model was the worst model in terms of describ-ing theMR value as a function of time since the RMSE values varied be-tween 0.0646 and 0.8419 for beef meat and 0.1496 and 0.7421 forchicken meat. With the exception of the Thompson model, the othermodels can be used to predict theMR based on the drying time. Accord-ing to the results, the most appropriate models for beef meat were thefollowing:

USV drying technique at 55 °C, 65 °C and 75 °C: Logarithmic, two-term and logarithmic, respectively.

Vacuum drying technique at 55 °C, 65 °C and 75 °C: Logarithmic forall of them.Oven drying technique at 55 °C, 65 °C and 75 °C: Logarithmic, loga-rithmic and modified Page, respectively.

Those for chicken meat were as follows:

USV drying technique at 55 °C, 65 °C and 75 °C: Logarithmic, diffu-sion and logarithmic, respectively.

Vacuum drying technique at 55 °C, 65 °C and 75 °C: Diffusion,modified Page and diffusion, respectively.Oven drying technique at 55 °C, 65 °C and 75 °C: Modified Page,logarithmic and modified Page, respectively.

Obtaining drying kinetics data and their modeling are necessaryto design, simulate and optimize the drying process or equipment(Perea-Flores et al., 2012). Themodel parameter k represents the dryingrate. The k coefficient is related to the rate ofmoisture removed from thesample (Perea-Flores et al., 2012). As seen in Tables 4 and 5, k increasedas the drying temperature increased. Moreover, the highest k value wasobserved in the data obtained from for the USV drying technique,followed by the vacuumand oven techniques. This resultwas consistentwith theDR and drying time results. Modeling of water losses at the de-termined condition is important to obtain higher-quality dried prod-ucts, which is provided by controlling and optimizing the processparameters (Clemente, Bon, Sanjuán, & Mulet, 2011).

3.4. Effective moisture diffusivity (Deff) and effect of temperature

Table 3 also presents the effective moisture diffusivity (Deff) of thedifferent drying techniques applied at different temperatures to drythe beef and chicken meat samples. The Deff value of the beef meatdriedwith theUSVmethod at 55 °Cwas 1.75×10−8m2/s and increasedto 5.28 × 10−8 m2/s as the drying temperature increased from 55 °C to75 °C. The Deff value of beef meat dried with the vacuum and oven dry-ing techniques at 55 °C was 1.69 × 10−8 and 1.06 × 10−8 m2/s, respec-tively, and increased to 3.41× 10−8 and 2.76× 10−8m2/s. TheDeff valueof chicken meat dried with the USV, vacuum and oven drying tech-niques at 55 °C was 1.70 × 10−8, 1.38 × 10−8 and 1.14×10−8 m2/s, re-spectively; they increased to 5.73 × 10−8, 2.82 × 10−8 and 2.68 × 10−8

m2/s as the drying temperature was set at 75 °C. The Deff values for thebeef and chicken meat samples were very close. The Deff value of thechicken meat dried with superheated steam at different temperatures(120 °C, 140 °C and 160 °C) ranged between 2.23 × 10−8 m2/s and7.74 × 10−8 m2/s, which is consistent with the results in this study(Natharanakule et al., 2007). The calculated Deff values were in agree-ment with the general range reported to be between 10−8 and 10−12

for biological materials (Zogzas, Maroulis, & Marinos-Kouris, 1996). Asseen from the results, as expected, the USV technique had the highestDeff value, followed by the vacuum and oven drying techniques,among the drying methods applied in the present study since US candisrupt cell walls; therefore, mass transfer is enhanced (Hu et al.,2008). The temperature dependency of the Deff value was determinedusing the Arrhenius equation (Eq. (4)). The magnitude of the corre-sponding parameters (Deff

0, Ea and R2) calculated by fitting the obtained




data is shown in Table 6. As indicated in this table, the R2 value of theestablished models varied between 0.9694 and 0.9995, indicating thatthese models well described the relation between the Deff value andthe drying temperature. The activation energy of Deff determined forbeef meat dried with the USV, vacuum and oven techniques was50,144 J/mol, 33,252 J/mol and 46,123 J/mol, respectively, and was49,231 J/mol, 32,371 J/mol and 39,682 J/mol, respectively, for chickenmeat. The Deff value of beef meat was very close to that of the chickenmeat. The most temperature-sensitive method was found to be the USVtechnique, and the least sensitive was the vacuum technique based onEa values. According to the results, the combination of theUS and vacuumprocesses is very effective for shortening the drying time and increasingthe drying rate, thus improving the energy efficiency of the process andthe nutritional quality of the dried products. Therefore, this novel tech-nique can be used instead of other drying techniques for dryingmany dif-ferent materials in the food industry.

4. Conclusion

Drying is the oldest method for preserving food products. In recentyears, researchers have exerted efforts to find a drying technique toproduce dried products that have higher quality and to reduce cost ofthe process by shortening the drying process. For this aim, ultrasoundtreatment and vacuum were combined as a novel drying technique todry beef and chickenmeats. To observe the efficiency of this novel tech-nique, the results were compared with those obtained for vacuum andoven drying techniques. According to these results, this novel technique(combination of ultrasound and vacuum)markedly accelerated the dry-ing process, which is very important for the food industry consideringenergy efficiency and the quality of dried products. In future research,the effect of this novel drying technique on the functional and nutrition-al properties of different food materials will be observed.

Acknowledgment

The authors of this work acknowledge financial support from the‘Scientific Research Project Coordination Office, Yildiz Technical Univer-sity’ in Turkey (Project Number: 2012-07-05-KAP05).

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Ultrasonic vacuum drying technique as a novel process for shortening the drying period for beef and chicken meats