APTEFF, 44, 1-321 (2013) DOI: 10.2298/APT1344011C UDC: 66.047.3:664.151.2]:637.5’64 BIBLID: 1450-7188 (2013) 44, 11-19 Original scientific paper OSMOTIC DEHYDRATION OF PORK MEAT CUBES - RESPONSE SURFACE METHOD ANALYSIS Biljana Lj.Ćurčića*, Lato L. Pezob, Ljubinko B. Levića, Violeta M. Kneževića, Milica R. Nićetina, Vladimir S. Filipovića and Tatjana A. Kuljanina a University of Novi Sad, Faculty of Technology Novi Sad, Bulevar Cara Lazara 1, 21000 Novi Sad, Serbia University of Belgrade, Institute of General and Physical Chemistry, Student's square 12,11000 Beograd, Serbia b The main objective was to examine the influence of different osmotic parameters on the mass transfer kinetics during osmotic treatment of pork meat (M. triceps brachii). The system’s response parameters observed were: water loss (WL), solid gain (SG), final dry matter content (DM) and water activity (aw). The optimum osmotic parameters seem to be: osmotic time of 4 h, molasses solution concentration of 72% and solution temperature of 45oC. These conditions were determined using Response Surface Methodology (RSM), and by superimposing the contour plots of each process variable. The predicted responses for the optimum drying conditions were: DM of 64.5%, WL in the close vicinity of 0.53, SG about 0.15 and aw in the range of 0.83 to 0.84. KEY WORDS: оsmotic dehydration, pork meat, sugar beet molasses, Response surface method INTRODUCTION Meat represents a cellular system with great biochemical and structural complexity, created by a network of muscular fibers surrounded by connective tissue (1, 2). Physicochemical, sensory, and technological properties of meat are related to the water content (3). Many traditional techniques, such as salting, drying, cooking, smoking, and marinating, are used to prevent spoilage of meat by reducing its water content (4). One of the potential preservation techniques for producing products with low water content and improved nutritional, sensorial and functional properties, is osmotic treatment (OT). During the OT, partial mass transfer is caused by the difference in the osmotic pressure: water outflow from the product to the solution, the solute transfer from the solution to the product, and leaching out of the products own solutes (5). The main advantages of OT are water removal in liquid form, usage of mild temperatures, reuse of the osmotic solution, improvement of the texture and color, no chemical pretreatment, energy efficiency, providing a stable and quality product. (6,7). The mass transfer mechanism and the quality of the final product are influenced by many factors such as composition, concen*Corresponding author: Biljana Lj. Ćurčić, University of Novi Sad, Faculty of Technology Novi Sad, Bulevar Cara Lazara 1, 21000 Novi Sad, Serbia, e-mail: biljacurcic@yahoo.com 11 APTEFF, 44, 1-321 (2013) DOI: 10.2298/APT1344011C UDC: 66.047.3:664.151.2]:637.5’64 BIBLID: 1450-7188 (2013) 44, 11-19 Original scientific paper tration and temperature of the osmotic agent, immersion time, agitation of the osmotic solution, the solution to sample ratio, the nature and thickness of the food material and, pretreatment (8,9,10). Solutions containing salt and sugar are common osmotic agents for food dehydration (11, 4). Salt solutions, because of their influence on water activity depression, are widely used in traditional meat processing, but there are several advantages if the ternary water/salt/sugar solutions, which are being used as immersion solutions (12,13). High salt concentrations decrease the water holding capacity, which contributes to meat dehydration and shrinkage, while there is no swelling of muscle fibers or myofibrils (3, 14). Sugar beet molasses is an excellent medium for OT, primarily due to the high dry matter (80%) and specific nutrient content (15,16,17). The OT in molasses provides a complex flavor to dehydrated meat, which can be corrected with different spices and aromas. The obtained meat product can be used for the production of jerky snacks or stuffing for different bakery products. The specific objective in this study was to examine the influence of temperature of osmotic solution, immersion time and osmotic solution concentration on the efficiency of OT of pork meat. Response surface methodology (RSM) is used for optimizing the process parameters. EXPERIMENTAL Pork meat (M. triceps brachii) was purchased at local market, just before the use. The initial moisture content of meat was 72.83%. Before the OT, the meat was cut into cubes of approximate dimensions 1x1x1cm. Sugar beet molasses of the inital dry matter content of 85.04% was diluted to the concentration of 60, 70 and 80% w/w using distilled water. The sample to solution ratio was 1:5 (w/w). The process was performed at solution temperature of 20, 35 and 50oC with manual agitation every 15 minutes under atmospheric pressure. After 1, 3 and 5 hours, the samples were taken out to be lightly washed with water and gently blotted to remove excessive water. The process variables were coded, according to the literature (18,19), and the values asigned are given in Table 1. Table 1. Coded values of the treatment variables Treatment variables X1 X2 X3 Time (h) Temperature ( o C) Solution concent. (%) -1 1 20 60 Coded values 0 +1 3 5 35 50 70 80 The DM of samples was determined by drying at 105ºC in a heat chamber to constant mass (Instrumentaria Sutjeska, Croatia). All analytical measurements were carried out in accordance to the AOAC method (20). Water activity (aw) was measured using a water activity measurement device (TESTO 650, Germany) with an accuracy of ±0.001 at 25ºC. Soluble solids content of solutions was measured using an Abbe refractometer, Carl Zeis Jenna at 20ºC. 12 APTEFF, 44, 1-321 (2013) DOI: 10.2298/APT1344011C UDC: 66.047.3:664.151.2]:637.5’64 BIBLID: 1450-7188 (2013) 44, 11-19 Original scientific paper Table 2. Experimental design and data for the response surface analysis Run No. t T C 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 -1 0 +1 -1 0 +1 -1 0 +1 -1 0 +1 -1 0 +1 -1 0 +1 -1 0 +1 -1 0 +1 -1 0 +1 -1 -1 -1 -1 -1 -1 -1 -1 -1 0 0 0 0 0 0 0 0 0 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 -1 -1 -1 0 0 0 +1 +1 +1 -1 -1 -1 0 0 0 +1 +1 +1 -1 -1 -1 0 0 0 WL 0.23 0.41 0.47 0.24 0.37 0.42 0.24 0.40 0.46 0.28 0.47 0.52 0.29 0.42 0.46 0.27 0.43 0.47 0.39 0.55 0.58 0.33 0.45 0.48 0.38 0.50 0.55 Sugar beet molasses SG aw DM 0.08 0.91 37.18 0.12 0.89 50.28 0.14 0.88 56.53 0.09 0.91 39.19 0.12 0.89 48.45 0.15 0.89 53.87 0.07 0.91 38.83 0.11 0.89 50.93 0.13 0.87 56.29 0.08 0.87 43.42 0.14 0.85 60.64 0.16 0.81 66.72 0.10 0.91 43.36 0.14 0.87 54.33 0.15 0.88 58.25 0.08 0.90 42.84 0.13 0.88 56.62 0.15 0.86 61.23 0.15 0.88 50.59 0.17 0.83 65.56 0.21 0.80 71.11 0.12 0.89 47.78 0.15 0.87 58.11 0.16 0.87 61.06 0.12 0.88 49.53 0.15 0.86 61.67 0.16 0.85 67.21 In order to describe the mass transfer kinetics of the OT, the experimental data for three key process variables are usually used, and these are: the moisture content, the change in the weight, and the change in the soluble solids. Using these, the WL and SG values were calculated as described in the literature (21,22). The accepted 33 full factorial, central composite experimental design, with 3 levels and 3 parameters in 1 block was taken from the literature (18, 19, 23, 24). The RSM method was selected to estimate the main effect of the process variables on the mass transfer variables. The independent variables were: time (X1) of 1, 3 and 5 h; solution temperature (X2) of 20, 35 and 50oC; X3 is the solution concentration (60, 70 and 80% w/w), and the dependent variables were the responses: DM (Y1), WL (Y2), SG (Y3), and aw (Y4). 13 APTEFF, 44, 1-321 (2013) DOI: 10.2298/APT1344011C UDC: 66.047.3:664.151.2]:637.5’64 BIBLID: 1450-7188 (2013) 44, 11-19 Original scientific paper The following second order polynomial (SOP) model was fitted to the data. Four models of the following form were developed to relate four the responses (Y) to the three process variables (X): 3 3 i 1 i 1 2 3 Yk   k 0    ki X i    kii X i2     kij X i X j , k=1-4, [1] i 1 j i 1 where: β0, βi, βii, βij are the constant regression coefficients; Y, either WL (Y1), SG (Y2), aw (Y3) and DM (Y4); X1, time; X2 temperature and X3, concentration. Statistical analysis and verification of the experiments Analysis of variance (ANOVA) and RSM were performed using the StatSoft Statistica for Windows, ver. 10 program. The model was obtained for each dependent variable (or response), where the factors were rejected when their significance level was less than 95%. The graphs of the responses with significant parameters were superimposed to determine optimum drying conditions. After establishing the optimum conditions, separate experiments were performed for the validation of the models. RESULTS AND DISCUSSION Table 2 shows the changes in WL, SG, aw and DM parameters in the samples during OT. As predicted, the process leads to an increase in DM of all meat samples regardless of the conditions used. The most intensive increase in DM was observed as the increase from the initial 27.17 to 71.11 % in the solution concentrated to 80% w/w, after 5 hours. The maximum value of WL (0.58) was achieved, after 5 hours, at the highest molasses concentrations (80% w/w), and with the maximum immersion time (5 h). Table 2 shows that SG increases with the immersion time. The aim of OT is the achievement of as low as possible solid uptake, and the most acceptable results were achieved by using molasses concentrated to 80% w/w (0.17 g/g i.s.w.), after 3 hours of osmotic process. To determine optimal condition for the OT water loss/solid gain ratio must be considered. The highest value of WL/SG ratio was 3.64, achieved by the immersion of meat for 3 hours in sugar beet molasses of 70% concentration, at 20oC. The RSM was conducted to determine the optimum OT conditions (considering maximum of measured WL and DM, with the lesser SG and aw). Table 3 shows the ANOVA calculation regarding the response models developed when the experimental data were fitted to a response surface. The response surface used the SOP in the form of Eq. [1] in order to predict all the dependent variables. The analysis revealed that the linear terms contributed substantially in all of the cases to generate a significant SOP model. The SOP models for all variables were found to be statistically significant and the response surfaces were fitted to these models. The linear terms of the SOP model were found significant at the 95% confidence level, and their influence was most important in all the model calculations. 14 APTEFF, 44, 1-321 (2013) DOI: 10.2298/APT1344011C UDC: 66.047.3:664.151.2]:637.5’64 BIBLID: 1450-7188 (2013) 44, 11-19 Original scientific paper Table 3. Analysis of variance for the four responses Term Source dF Linear Time Temp. Conc. Time Temp. Conc. Time×Temp Time×Conc Temp×Conc Error 1 1 1 1 1 1 1 1 1 17 Quad. Interaction Error r2 WL 0.160* 0.056* 0.006* 0.016* 0.001* 0.000ns 0.001* 0.003* 0.003* 0.002 99.1 Sum of squares SG aw DM 0.011* 0.006* 1190.825* 0.008* 0.005* 518.592* 0.000ns 0.003* 45.784* * ns 0.001 0.000 86.180* ns ns 0.000 0.000 2.102ns * ns 0.001 0.000 0.278ns ns ns 0.000 0.000 0.000ns ns * 0.000 0.001 34.361* * * 0.001 0.001 26.484* 0.001 0.001 16.427 95.7 93.0 99.3 *Significant at p<0.05 level, 95% confidence limit, nsNot significant, dF – degrees of freedom The ANOVA test shows the significant effects of the independent variables to the responses and which of responses are significantly affected by the varying treatment combinations (Table 4). The WL was significantly affected by all the process variables at the 95% confidence level. The main influential variable seems to be the treatment time. Table 4. Regression models coefficients (based on coded data) of the SOP models for the four responses β0 β1 β2 β3 β11 β22 β33 β12 β13 β23 WL 0.2290±0.2431ns 0.0832±0.0145* -0.0060±0.0022* -0.0009±0.0168ns -0.0131±0.0012* 0.0001±0.0000* -0.0000±0.0000ns -0.0003±0.0001* 0.0008±0.0002* 0.0001±0.0000* SG 0.7637±0.1720* 0.0205±0.0102ns -0.0051±0.0016* -0.0182±0.0048* -0.0023±0.0008* 0.0000±0.0000ns 0.0001±0.0000* -0.0001±0.0001ns 0.0002±0.0001ns 0.0001±0.0000* aw 0.5487±0.1943* 0.0148±0.0116ns 0.0020±0.0018ns 0.0100±0.0054ns 0.0017±0.0010ns 0.0000±0.0000ns -0.0001±0.0000ns -0.0001±0.0001ns -0.0004±0.0001* -0.0001±0.0000* DM 35.5226±20.3650ns 4.1966±1.2132* -0.1348±0.1848ns -0.0899±0.5678ns -0.9475±0.1003* -0.0026±0.0018ns -0.0022±0.0040ns -0.0001±0.0095ns 0.0846±0.0142* 0.0099±0.0019* * Significant at p<0.05 level, 95% confidence limit, nsNot significant The quadratic terms for the treatment time and temperature are also significant, while the quadratic terms of concentration were found not significant. The interrelation terms were found statistically significant at the 95% confidence level. The SG is most affected by time, and the temperature terms are also significant at the 95% confidence level. The concentration terms were found not significant. aw is most affected by time (at the 95% confidence level). The DM is most significantly affected by time, and the impact of the temperature and concentration terms were also found significant at the 95% confidence 15 APTEFF, 44, 1-321 (2013) DOI: 10.2298/APT1344011C UDC: 66.047.3:664.151.2]:637.5’64 BIBLID: 1450-7188 (2013) 44, 11-19 Original scientific paper level. Table 4 also shows the residual variance, where the lack of fit variation represents the other contributions except for the first order terms. A significant lack of fit generally shows that the model failed to represent the data in the experimental domain at which points were not included in the regression (23). All SOP models had insignificant lack of fit tests, which means that all the models represented the data satisfactorily. The coefficient of determination, r2, is defined as the ratio of the explained variation to the total variation, and is explained by its magnitude (24). A high r2 indicates that the variation was accounted for, and that the data fitted satisfactorily to the proposed model (SOP in this case. The r2 values for WL (99.1), SG (95.7), aw (93.0) and DM (99.3), were found very satisfactory and showed the good fitting of the model to the experimental results. Table 4 shows the regression coefficients for the response SOP models of DM, WL, SG and aw used by Eq. [1] for predicting the values at optimum conditions. Using these equations, the contour plots of WL, SG, aw and DM, have been plotted, and afterwards superimposed to ascertain the optimum osmotic dehydration conditions for pork meat cubes in sugar beet molasses solution (Fig. 1). Temperature WL=0 40 a w= 35 .52 DM = 0.8 5 75 63 3 3.5 Time a w= 0.8 5 A WL=0.52 DM=6 3 Temperature: 45oC 60 4 4.5 5 .16 WL=0.54 aw =0 .83 70 65 30 Concentration: 72% 2.5 SG=0 5 =6 A WL=0.54 a w= 0.8 3 SG =0 .1 4 DM 4 45 80 SG= 0.16 Concentration SG =0 .1 5 =6 DM 50 2.5 3 3.5 4 4.5 5 Time Figure 1. Optimum regions obtained after superimposing the contour plots of the system responses The optimization of the OT is performed to ensure rapid processing conditions (with as low as possible immersion time), yielding an acceptable product quality (with high WL and low SG), and a high throughput capacity. An optimum operating area was derived with a few iterative steps in finding the processing parameters that gave the highest DM (between 63 and 64%) and WL (0.52-0.54), with relatively low SG (between 0.14 and 0.16) and aw (0.83-0.85). The optimal area is crosshatched and the point A was deduced by approximating the optimum position in the obtained area on the graph. The contour plots of both WL and SG showed that the maximum value was a bit lower than the upper right corner of the both plots, tending to grow with temperature and processing time, while aw decreased with all process parameters. The optimum OT conditions for 16 APTEFF, 44, 1-321 (2013) DOI: 10.2298/APT1344011C UDC: 66.047.3:664.151.2]:637.5’64 BIBLID: 1450-7188 (2013) 44, 11-19 Original scientific paper pork meat cubes, dehydrated in sugar beet molasses solution are as follows: immersion time of 4 h, solution concentration and temperature of 72% and 45oC. The desired responses for the optimum drying conditions were: DM of 64.5%, WL in the close vicinity of 0.53, SG about 0.15 and aw in the range of 0.83 to 0.84. The contour plot for DM showed a saddle point configuration, and its value rose to the upper right corner of the plot, with the increase of all process variables. To determine the adequacy of the SOP models, independent experiments were performed under the optimum conditions for validation (24). Table 5 shows the model validation results. Very good coefficients of variation (CV) of less than 10% for all process variables were calculated. The CV values higher than 15% for the response variables show a great influence to the statistically minor significance of its SOP model (24). The low CV values for the response variables DM, WL, SG and aw indicate the adequacy of these models. Table 5. Predicted and observed responses at optimum conditions Standard Coefficient deviation of variation Sugar beet molasses, Time=4 h, Conc.= 72%, Temp.= 45oC. DM 64.50 64.09 1.04 1.62 WL 0.53 0.52 0.05 9.62 SG 0.15 0.16 0.01 6.25 aw 0.83 0.82 0.06 7.32 Responses Predicted Observed CONCLUSION Osmotic treatment of pork presents some advantages compared with common drying techniques, such as minimizing heat damage to meat and reducing energy costs. The use of OT, as a complementary treatment in food processing, particularly prior to drying and freezing operations, reduces energy requirements of these processes. Sugar beet molasses as a hypertonic solution was selected in this research, due to its high dry matter content and the enrichment of meat in nutrients, which penetrate from the molasses to the meat tissue. The optimum process parameters for the OT of pork cubs were: osmotic time of 4 h, molasses solution concentration of 72%, and temperature of 45oC. The predicted responses for the optimum drying conditions in sugar beet molasses solution were: DM of 64.5%, WL in the close vicinity of 0.53, SG about 0.15 and aw in the range of 0.83 to 0.84. During the OT of meat, water removing process was most intensive at the beginning, and after 3 h had a tendency of stabilization. The use of sugar beet molasses as osmotic agent is economically and environmentally reasonable, because it is a side product of sugar industry. Acknowledgеments These results are part of the project supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia, TR-31055, 2011-2014. 17 APTEFF, 44, 1-321 (2013) DOI: 10.2298/APT1344011C UDC: 66.047.3:664.151.2]:637.5’64 BIBLID: 1450-7188 (2013) 44, 11-19 Original scientific paper REFERENCES 1. Castro-Giraldez, M. and Fito, P. Non-equilibrium thermodynamic approach to analyze the pork meat (Longissimus dorsi) salting process. J.Food Eng. 99 (2010) 24-30. 2. Puolanne, E. and Halonen, M.: Theoretical aspects of water-holding in meat. Meat Sci. 86 (2010) 151-165. 3. Barat, J., Alino, M., Fuentes, A., Grau, R. and Romero, J. B.: Measurement of swelling pressure in pork meat brining. J.Food Eng. 93 (2009) 108-113. 4. Collignan, A., Bohuon, P., Deumier, F. and Poligne, I.: Osmotic treatment of fish and meat products. J. Food Eng. 49 (2001) 153-162. 5. 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Куљанина а Универзитет у Новом Саду, Технолошки факултет Нови Сад, Бул. цара Лазара 1, 21000 Нови Сад, Србија, Универзитет у Београду, Институт за општу и физичку хемију, Студентски трг 12, 11000 Београд, Србија б Основни циљ рада је испитивање утицаја различитих параметара на кинетику преноса масе током осмотске дехидратације свињског меса (M. triceps brachii). Посматрани одзиви система су: губитак воде (WL), прираштај суве материје (SG), коначни садржај суве материје (DM) и активност воде (aw). Добијени оптимални осмотски параметри су: време од 4 сата, 72% концентрација раствора меласе и температура од 45oC. Ови услови су одређени применом методе одзивне површине (RSМ). Предвиђени одзиви за оптималне услове за сушење су: DM од 64,5%, WL у непосредној близини 0,53, SG око 0,15 и aw у распону од 0,83 до 0,84. Кључне речи: осмотска дехидрација, свињско месо, меласа шећерне репе, методa одзивне површине Received: 30 May 2013 Accepted: 25 September 2013 19