OSMOTIC DEHYDRATION OF FISH: PRINCIPAL COMPONENT ANALYSIS

UNIVERSITY OF NOVI SAD FACULTY OF TECHNOLOGY NOVI SAD ACTA PERIODICA TECHNOLOGICA APTEFF, 45, 1-283 (2014) ACTA PERIODICA TECHNOLOGICA (formerly Zbornik radova Tehnološkog fakulteta and Proceedings of Faculty of Technology) publishes articles from all branches of technology (food, chemical, biochemical, pharmaceutical), process engineering and related scientific fields. Articles in Acta Periodica Technologica are abstracted by: Chemical Abstracts, Columbus, Ohio, Referativnyi zhurnal -Khimija, VINITI, Moscow, listed in Ulrich’s International Periodical Directory, and indexed in the Elsevier Bibliographic databases – SCOPUS. ISSN 1450-7188 (Print) ISSN 2406-095X (Online) CODEN: APTEFF UDC 54:66:664:615 Publisher University of Novi Sad, Faculty of Technology Novi Sad Bulevar cara Lazara 1, 21000 Novi Sad, Serbia For Publisher Prof. Dr. Zoltan Zavargo, Dean Editor-in-Chief Prof. Dr. Sonja Đilas Editorial Board From Abroad Prof. Dr. Živko Nikolov Texas A and M University, Biological and Agricultural Engineering Department, College Station, TX, USA Prof. Dr. Erika Békássy-Molnár University of Horticulture and Food Industry, Budapest, Hungary Prof. Dr. Željko Knez University of Maribor, Faculty of Chemistry and Chemical Technology, Maribor, Slovenia Dr. T.S.R. Prasada Rao Indian Institute of Petroleum, Dehra Dun, India Prof. Dr. Đerđ Karlović Margarine Center of Expertise, Kruszwica, Poland Dr. Szigmond András Research Institute of Hungarian Sugar Industry, Budapest, Hungary Dr. Andreas Reitzmann Institute of Chemical Process Engineering, University Karlshruhe, Germany From Serbia Prof. Dr. Vlada Veljković Prof. Dr. Spasenija Milanović Prof. Dr. Vladimir Srdić Prof. Dr. Slobodan D. Petrović Prof. Dr. Jonjaua Ranogajec Dr. Anamarija Mandić ACTA PERIODICA TECHNOLOGICA APTEFF, 45, 1-283 (2014) CONTENT FOOD TECHNOLOGY Vesna D. Dragičević, Snežana D. Mladenović Drinić, Vojka B. Babić, Milomir R. Filipović, Zoran F. Čamdžija, Dragan R. Kovačević THE VARIATIONS IN MAIZE GRAIN COMPOSITION INDUCED BY DIFFERENT ENVIRONMENTS ....................................................... 1 Dragutin A. Djukić, Milorad M. Radović, Leka G. Mandić, Slavica M. Vesković Moračanin EFFECT OF BREAD DOUGH MIXING METHOD ON RYE BREAD QUALITY ..................................................................................... 11 Jelena S. Filipović, Lato L. Pezo, Nada K. Filipović, Vladimir S. Filipović THE EFFECT OF QUANTITY OF ADDED EGGS ON WHOLE MEAL PASTA QUALITY ................................................................... 23 Nevena M. Hromiš, Vera L. Lazić , Siniša L. Markov, Žužana G. Vaštag, Senka Z. Popović, Danijela Z. Šuput, Natalija R. Džinić IMPROVEMENT OF ANTIOXIDANT AND ANTIMICROBIAL ACTIVITY OF CHITOSAN FILM WITH CARAWAY AND OREGANO ESSENTIAL OILS ....... 33 Biljana Lj. Lončar, Lato L. Pezo, Ljubinko B. Lević, Vladimir S. Filipović, Milica R. Nićetin, Violeta M. Knežević, Tatjana A. Kuljanin OSMOTIC DEHYDRATION OF FISH: PRINCIPAL COMPONENT ANALYSIS ....................................................................................... 45 Nurgin R. Memiši, Slavica M. Vesković Moračanin, Marija M. Škrinjar, Mirela D. Iličić, Mira Đ. Ač STORAGE TEMPERATURE: A FACTOR OF SHELF LIFE OF DAIRY PRODUCTS ................................................................................... 55 Tamara Đ. Premović, Sanja B. Dimić, Olga F. Radočaj, Etelka B. Dimić IMPACT OF THE SEED STORAGE TIME ON THE QUALITY OF COLD-PRESSED SUNFLOWER OIL ................................................................ 67 Đorđe B. Psodorov, Đura N. Vujić, Marijana M. Ačanski, Kristian A. Pastor, Radojka N. Razmovski, Snežana Ž. Kravić THE CONTENT OF BUCKWHEAT FLOUR IN WHEAT BREAD ........................ 79 Vladimir R. Vukić, Katarina G. Kanurić, Spasenija D. Milanović, Mirela D. Iličić, Dajana V. Hrnjez, Marjan I. Ranogajec CORRELATION OF THE MICROSTRUCTURE WITH VISCOSITY AND TEXTURAL PROPERTIES DURING MILK FERMENTATION BY KOMBUCHA INOCULUM ................................................ 89 Jelena J. Vulić, Aleksandra S. Velićanski, Dragana D. Četojević-Simin, Vesna T. Tumbas Šaponjac, Sonja M. Djilas, Dragoljub D. Cvetković, Siniša L. Markov ANTIOXIDANT, ANTIPROLIFERATIVE AND ANTIMICROBIAL ACTIVITY OF FREEZE-DRIED RASPBERRY ...................................................... 99 CHEMICAL TECHNOLOGY AND PROCESS ENGINEERING Darjana Ž. Ivetić, Radovan P. Omorjan, Mirjana G. Antov ADSORPTION OF CELLULASES ONTO SUGAR BEET SHREDS AND MODELING OF THE EXPERIMENTAL DATA ......................... 119 Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Jaroslava V. Švarc-Gajić, Strahinja Z. Kovačević CHEMOMETRIC ANALYSIS OF METAL CONTENTS IN DIFFERENT TYPES OF CHOCOLATES .............................................................. 129 Siniša L. Markov, Ana M. Vidaković TESTING METHODS FOR ANTIMICROBIAL ACTIVITY OF TiO2 PHOTOCATALYST.............................................................. 141 Tajudeen A.O. Salau, Sunday A. Oke, Desmond E. Ighravwe SIMULATION OF BENDING STRESS VARIATION IN LONG BURIED THICK-WALLED PIPES UNDER THE EARTH’S MOVEMENT USING COMBINED LINEAR DYNAMICS AND BEAM THEORIES ............................. 153 BIOCHEMICAL AND PHARMACEUTICAL ENGINEERING Evgenija A. Djurendić, Marina P. Savić, Suzana S. Jovanović-Šanta, Marija N. Sakač, Vesna V. Kojić, Mihály Szécsi, Aleksandar M. Oklješa, Mihalj M. Poša, Katarina M. Penov-Gaši ANTIOXIDANT AND CYTOTOXIC ACTIVITY OF MONOAND BIS-SALICYLIC ACID DERIVATIVES ...................................................... 173 Branislav D. Jović, Jovana J. Ajduković, Evgenija A. Djurendić, Aleksandar D. Nikolić FTIR INVESTIGATION OF SOLVENT-INDUCED CARBONYL BAND SHIFTS OF 17-HYDROXY-17Α-PICOLYL-ANDROST-4-EN-3-ONE. ............ 191 Danijela M. Pecarski, Zorica D. Knežević-Jugović, Suzana I. Dimitrijević-Branković, Katarina R. Mihajilovski, Slobodan M. Janković COMPARATIVE ANALYSIS OF THE CHEMICAL COMPOSITION AND ANTIMICROBAL ACTIVITIES OF SOME OF LAMIACEAE FAMILY SPECIES AND EUCALIPTUS (Eucaliptus globules M)......................... 201 Sanja M. Petrović, Laura Tugulea †, Dejan Z. Marković, Marcela Barbanta-Patrascu CHLOROPHYLL A AND CHLOROPHYLLIDE A INSIDE LIPOSOMES MADE OF SATURATED AND UNSATURATED LIPIDS: A POSSIBLE IMPACT OF THE LIPIDS MICROENVIRONMENT ............................................ 215 Marija M. Radojković, Zoran P. Zeković, Biljana P. Dojčinović, Zorica S. Stojanović, Aleksandra D. Cvetanović, Dragan D. Manojlović CHARACTERIZATION OF Morus SPECIES IN RESPECT TO MICRO, MACRO, AND TOXIC ELEMENTS ................................................. 229 Zorana Z. Rončević, Bojana Ž. Bajić, Jovana A. Grahovac, Siniša N. Dodić, Jelena M. Dodić EFFECT OF THE INITIAL GLYCEROL CONCENTRATION IN THE MEDIUM ON THE XANTHAN BIOSYNTHESIS ................................... 239 Zorana Z. Rončević, Jovana A. Grahovac, Damjan G. Vučurović, Siniša N. Dodić, Bojana Ž. Bajić, Ivana Ž. Tadijan, Jelena M. Dodić OPTIMIZATION OF MEDIUM COMPOSITION FOR THE PRODUCTION OF COMPOUNDS EFFECTIVE AGAINST Xanthomonas campestris BY Bacillus subtilis ......................................................... 247 Vladislava M. Šošo, Marija M. Škrinjar, Nevena . Blagojev, Slavica M. Vesković Moračanin IDENTIFICATION OF AFLATOXIGENIC FUNGI USING POLYMERASE CHAIN REACTION-BASED ASSAY ......................................... 259 Slavica M. Vesković Moračanin, Dragutin A. Đukić, Nurgin R. Memiši BACTERIOCINS PRODUCED BY LACTIC ACID BACTERIA – A REVIEW ....... 271 IN MEMORIAM Academician Paula Putanov .......................................................................................... 287 INSTRUCTION FOR MANUSCRIPT PREPARATION ACTA PERIODICA TECHNOLOGICA APTEFF, 45, 1-283 (2014) ɋȺȾɊɀȺȳ ɉɊȿɏɊȺɆȻȿɇȺ ɌȿɏɇɈɅɈȽɂȳȺ . , . . . , , џ , . , . ........................... 1 .Ђ , . , . , M. .......................................................................... 11 . , . , . , . ........................................................... 23 . , . . , , . . , , . , . ................................................................ 33 . , . . . . A . . , , TA , . , . .................................................................................... 45 . Ђ. , , , , T . , : .................................................................... 55 Ђ. , . , . , . .................................................. 67 Ђ ђ . . ,Ђ , . , . , . , . .......................... 79 Vladimir R. Vukić, Katarina G. Kanurić, Spasenija D. Milanović, Mirela D. Iličić, Dajana V. Hrnjez, Marjan I. Ranogajec , ...................................................................................... 89 . . , . , , . . , . , , . A, A ...................................................... 99 ɏȿɆɂȳɋɄȺ ɌȿɏɇɈɅɈȽɂȳȺ ɂ ɉɊɈɐȿɋɇɈ ɂɇɀȿȵȿɊɋɌȼɈ . , . , . .................................. 119 . , . - , . - , . ...................................................... 129 . , . TiO2 џ . . ................................................... 141 , . , . ......................................................................... 153 ȻɂɈɏȿɆɂȳɋɄɈ ɂ ɎȺɊɆȺɐȿɍɌɋɄɈ ɂɇɀȿȵȿɊɋɌȼɈ .Ђ , , , . . . , , . . - , . , . , ............................................... 173 . , . , .Ђ , . FTIR 17- -17α- - -4- -3. ...................................................... 191 . , . . - - , , . , . LAMIACEAE (Eucaliptus globules M)............................................................................................ 201 . † , - , . , Ђ : J . ? ....................................... 215 , , . . , , . . , ................................................................... 229 . , , , Morus . . . , . , . ................................................... 239 . , . . , , . . , . , , . Xanthomonas campestris Bacillus subtilis ................................................................................ 247 . , . , . , . .............. 259 . , – .Ђ , . ....................................................................................... 271 IN MEMORIAM ........................................................................................... 287 ɍɉɍɌɋɌȼɈ ɁȺ ɉɂɋȺȵȿ ɊȺȾȺ APTEFF, 45, 1-283 (2014) DOI: 10.2298/APT1445045L UDC: 66.047.3:664.151.2]:637.56 BIBLID: 1450-7188 (2014) 45, 45-53 Original scientific paper OSMOTIC DEHYDRATION OF FISH: PRINCIPAL COMPONENT ANALYSIS Biljana Lj. Lončar1*, Lato L. Pezo2, Ljubinko B. Lević1, Vladimir S. Filipović1, Milica R. Nićetin1, Violeta M. Knežević1, Tatjana A. Kuljanin1 1 University of Novi Sad, Faculty of Technology Novi Sad, Bulevar Cara Lazara 1, 21000 Novi Sad, Serbia, 2 Institute of General and Physical Chemistry, 11000 Beograd, Serbia Osmotic treatment of the fish Carassius gibelio was studied in two osmotic solutions: ternary aqueous solution – S1, and sugar beet molasses – S2, at three solution temperatures of 10, 20 and 30oC, at atmospheric pressure. The aim was to examine the influence of type and concentration of the used hypertonic agent, temperature and immersion time on the water loss, solid gain, dry mater content, aw and content of minerals (Na, K, Ca and Mg). S2 solution has proven to be the best option according to all output variables. KEY WORDS: osmotic treatment, Fish, Sugar beet molasses, PCA INTRODUCTION Fish meat is very beneficial for human health due to its specific chemical composition (1).This valuable source of nutrients is one of the most perishable foods, and needs to be processed. The main reason for short shelf life of fish meat is high moisture content (2, 3). Advantageous method for water content reduction of cellular material is osmotic treatment (OT) (4). OT is recognized as a mild temperature processing method based on the principle of osmosis, where difference between the sample and its surrounding medium is the main force for dewatering process (5, 6). The rate of water diffusion from the biological material depends upon various factors: type, concentration, temperature and agitation of the osmotic solution, the size and structure of food material and solution to sample mass ratio (7). Multi-components salt-sugar aqueous solutions have been successfully used for OT (8, 9). Meat or fish are usually dehydrated in aqueous solutions with salt as a main component (10,11), however in some countries are well-known sweet salted fish products obtained by OT in salt and sweet hypertonic solutions (12, 13). According to the recent papers, sugar beet molasses as hypertonic medium is highly effective for OT of fruits (14), vegetables (15) and meat (16, 4, 17). High amounts of solids (»80%), and specific nutrient composition (50% sucrose, 1% raffinose and less than 1% invert sugar, considerable amounts of minerals, proteins, vitamins, glutamic acid, organic acids, pectin, etc.) make sugar beet molasses a unique and efficient hypertonic solution (15, 18). * Corresponding author: Biljana Lj. Lončar, University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21000 Novi Sad, Serbia, e-mail: biljacurcic@yahoo.com 45 APTEFF, 45, 1-283 (2014) DOI: 10.2298/APT1445045L UDC: 66.047.3:664.151.2]:637.56 BIBLID: 1450-7188 (2014) 45, 45-53 Original scientific paper The objective of the presented work was to investigate the effects of the processing time, temperature, concentration of osmotic solutions on the mass transfer phenomena during OT of fish Carassius gibelio in sugar beet molasses and aqueous ternary solution (concentrated salt and sugar aqueous solution). Principal Component Analysis (PCA) is used to evaluate the quality of the obtained products, processed under different process parameters. The aim was to determine the minerals content (Na, K, Ca, Mg), dry matter (DM) content, water loss (WL), solid gain (SG), and water activity (aw) as a function of the process variables and to find the optimum osmotic treatment conditions. EXPERIMENTAL Osmotic dehydration of fish The OT was carried out in laboratory jars under atmospheric pressure in heat chamber at the solution temperatures of 10, 20and 30oC. Prussian carp (Carassius gibelio) was purchased on a local market in Novi Sad, Serbia, shortly prior to the experiment. The initial moisture content of untreated samples was 75.34%. Fish samples were filleted and cut into pieces (1x1cm) using kitchen slicer and scissors. After the preparation, the samples were measured and immersed in hypertonic solutions for 5 hours. The sample to solution ratio was 1:5 (w/w), which can be considered high enough to neglect the changes of solution concentration during the process. On every 15 minutes, the fish samples in the osmotic solutions were stirred to provide better homogenization of the osmotic solution, because of the amount of diffused water from the samples. Aqueous ternary osmotic solution was made from sucrose in the quantity of 1.200 g/kg water, NaCl in the quantity of 350 g/kg water and distilled water. This solution (S1) was diluted with distilled water to the concentrations of 60, 52.5 and 45% w/w. Sugar beet molasses, obtained from the sugar factory Pećinci, Serbia, with the initial dry matter content of 85.04% w/w, was diluted to th econcentrations of 60, 70 and 80% w/w (this solution was marked as S2). After each sampling time (1, 3 and 5 hours), fish samples were taken out from solutions (S1 and S2), lightly washed with distilled water, gently blotted with paper to remove excessive water from the surface and weighted. In order to describe the mass transfer kinetics of the osmotic dehydration (OD), experimental data from three key process variables are usually obtained: the moisture content, change in weight and the change in soluble solids. Using these, WL and SG, were calculated for different solutions and processing times (4,14,15): m  z  mf  z f   g [1] WL  i i   mi  g fresh sample  m f  s f  mi  si   g [2]   mi  g fresh sample  where mi and mf are the initial and final weight (g) of the samples, respectively; zi and zf are the initial and final mass fraction of water (g water/g sample), respectively; si and sf are the initial and final mass fraction of total solids (g total solids/ g sample), respectiveSG  46 APTEFF, 45, 1-283 (2014) DOI: 10.2298/APT1445045L UDC: 66.047.3:664.151.2]:637.56 BIBLID: 1450-7188 (2014) 45, 45-53 Original scientific paper ly. The mass loss during OD can be evaluated by subtracting the SG from the WL. The moisture content in the DM at any time can be calculated by dividing the subtracted initially water present and the WL, with the initial dry solids. Physico-chemical analyses The DM content of the fresh and treated samples was determined by drying at 105oC for 24 hours in a heat chamber (Instrumentaria Zagreb, Croatia). The value of aw for the osmotically treated samples was measured using a water activity measurement device (TESTO 650, Germany) with an accuracy of ±0.001 at 25ºC. Soluble solids content of the molasses solutions was measured using an Abbe refractometer (Carl Zeis, Jenna, Germany) at 20oC. All analytical measurements were carried out in accordance to the AOAC method (19). All experiments were repeated three times and presented using descriptive statistics (20). Processing temperature (T): 10, 20, 30oC, immersion time (t): 1, 3 and 5h, S1 concentration (c): 60, 52.5 and 45% w/w, S2 concentration: 60, 70 and 80% w/w. Response Surface Methodology The Response Surface Method (RSM) was selected to estimate the main effect of the process variables on the mass transfer variables during the OT of fish. The experimental data used for the optimization study were obtained using a central composite full factorial design (3 level-3 parameter) with 27 runs (1 block). The independent variables were temperature, T (X1) of 10, 20 and 30oC; osmotic time t (X2) of 1, 3 and 5h; X3 is the concentration of osmotic solution, c (45, 52.5 and 60% w/w for S1 solution and 60, 70 and 80% w/w for S2 solution), and the dependent variables observed were the response: WL (Y1), SG (Y2), aw (Y3), DM (Y4), Na (Y5), K (Y6), Ca (Y7) and Mg (Y8). A model was fitted to the response surface generated by the experiment. The model used was a function of the following variables: Yk   k 0    ki X i    kii X i2   3 3 i 1 i 1 3  2 i 1 j  i 1 kij X i X j , k=1-8, [3] where: βkn are constant regression coefficients. Analysis of variance (ANOVA) and response surface regression method (RSM) were performed using StatSoft Statistica, for Windows, ver. 10 program. The model was obtained for each dependent variable (or response), where factors were rejected when their significance level was p<0.05. Principal component analysis The PCA is a mathematical procedure used as a central tool in exploratory data analysis (21). It is a multivariate technique in which the data are transformed into orthogonal components that are linear combinations of the original variables. The PCA is done by eigenvalue decomposition of a data correlation matrix (22). This transformation is defined in such a way that the first component has the largest possible variance. This analysis 47 APTEFF, 45, 1-283 (2014) DOI: 10.2298/APT1445045L UDC: 66.047.3:664.151.2]:637.56 BIBLID: 1450-7188 (2014) 45, 45-53 Original scientific paper is used to achieve maximum separation among the clusters of parameters (17). This approach, evidencing spatial relationship between the processing parameters, enabled a differentiation between the different samples in both solutions (S1 and S2). For the PCA, use was made of the program StatSoft Statistica 10 (20). RESULTS AND DISCUSSIONS The obtained experimental data were presented using basic descriptive statistics, Table 1. The variables WL, SG, aw, DM, and the content of Na, K, Ca and Mg varied significantly, implying that fitting of the experimental data could be performed using ANN modeling. Table 1. Experimental results WL SG aw DM Na K Ca Mg 0.02 Ternary aqueous solution – S1 Maximum 0.36 0.08 0.90 44.08 0.19 0.30 0.01 Minimum 0.09 0.02 0.03 7.62 0.03 0.01 0.00 0.00 Average 0.19 0.04 0.85 30.69 0.13 0.29 0.01 0.02 Std. dev. 0.49 0.12 0.95 60.45 0.26 0.31 0.01 0.02 Variance 7.59×10-3 4.30×10-4 7.27×10-4 5.81×101 1.08×10-3 3.92×10-5 1.45×10-7 3.08×10-6 0.03 Sugar beet molasses – S2 Maximum 0.39 0.09 0.88 47.83 0.50 0.78 0.05 Minimum 0.11 0.02 0.02 8.32 0.14 0.20 0.02 0.01 Average 0.14 0.05 0.84 33.51 0.28 0.50 0.02 0.02 Std. dev. 0.54 0.12 0.92 64.27 0.75 1.15 0.08 0.05 Variance 1.11×10-2 4.60×10-4 5.27×10-4 6.93×101 1.90×10-2 4.01×10-2 4.04×10-4 4.51×10-5 The most intensive increase in the DM content was achieved during the OT of fish in the S2 solution. The DM content increased from the initial 24.66 to 47.83 % in S2 solution, concentrated to 80% w/w, or to 44.08% in S1 solution, concentrated to 60% w/w, after 5 hours of experiment. The large difference in the osmotic pressure between the hypertonic solution and the fish tissue, causes a high initial loss of the water at the beginning of the dehydration process. The maximum of WL and SG was achieved after 5 hours at the maximum concentrations. The SG value indicates the degree of penetration of solids from the hypertonic solution into the fish sample. The aim of the OT is the achievement of as low as possible solid uptake, and the most acceptable results were achieved by using S2 solution, concentrated to 80% w/w. Tables 2 and 3 show the influences of the process variables on the observed responses for the OT of fish in S1 and S2 solution. The analysis revealed that the linear terms contributed substantially in most of the cases to the generation of a significant SOP model. The linear terms of SOP model were found significant, at p<0.05 level, 48 APTEFF, 45, 1-283 (2014) DOI: 10.2298/APT1445045L UDC: 66.047.3:664.151.2]:637.56 BIBLID: 1450-7188 (2014) 45, 45-53 Original scientific paper 95% confidence limit, and their influence was found as being most important in the majority of model calculations. Table 2. Analysis of variance (ANOVA) for osmotic tretment of fish in S1 solution Term WL SG aw DM Na K Ca Mg t 0.134* 0.008* 0.008* 877.350* 0.020* 0.001* 0.000* 0.000* t2 0.011* 0.000 0.000** 46.856* 0.000 0.000** 0.000 0.000* T * * * 433.077 * * * 0.000* * 2 0.006 0.002 0.003 * 0.003 0.000 0.000 T 0.000 0.000 0.000 4.373 0.000 0.000 0.000 0.000 c 0.038* 0.001* 0.007* 108.242* 0.004* 0.000* 0.000* 0.000* c2 0.001* 0.000 0.000 2.851* 0.000 0.000* 0.000 0.000* t×T 0.000 * 0.000 0.000 ** 0.021 * 13.313 0.000 * ** 0.000* 0.000 0.000 ** 0.000* 0.000 0.000 * 0.000 0.000* 0.000 0.000* t×c 0.001 0.000 0.001 T×c 0.001* 0.000** 0.000 20.185 Error 0.001 0.000 0.001 10.551 0.000 0.000 0.000 0.000 r2 0.993 0.963 0.967 0.993 0.983 0.974 0.980 0.999 0.000 *Significant at p<0.05 level, **Significant at p<0.10 level, 95% confidence limit Table 3. Analysis of variance (ANOVA) for osmotic tretment of fish in S2 solution Term WL SG aw DM Na K Ca Mg t 0.023* 0.002* 0.000* 146.842* 0.043* 0.084* 0.000* 0.000* t2 0.013* 0.000* 0.000* 62.232* 0.002* 0.003 0.000 0.000 T 0.000 0.000* 0.000* 26.868* 0.034* 0.079* 0.001* 0.000 T2 0.007* 0.000* 0.000 3.788* 0.012* 0.011* 0.001* 0.000* c 0.001 0.000 0.001* 0.607 0.000 0.000 0.000 0.000 c2 0.001 0.000 0.000** 0.422 0.000 0.000 0.000 0.000 t×T 0.001 0.000 0.000 0.180 0.005* 0.032* 0.000* 0.000* * 11.653 * t×c 0.001 0.000 0.000 0.000 0.001 0.000 0.000 T×c 0.011* 0.000 0.000* 8.392* 0.000 0.000 0.000 0.000 Error 0.013 0.000 0.001 10.791 0.008 0.036 0.000 0.000 r2 0.955 0.976 0.953 0.994 0.983 0.966 0.978 0.913 *Significant at p<0.05 level, **Significant at p<0.10 level, 95% confidence limit The most important influences on the response variables exerted the linear term of t, for S1 solution, while the influence of the other linear terms (T and c) was also found to be statistically significant for the calculation in the most of the cases. The linear term of c was more important for the calculation of WL, aw, and minerals content, while the linear term of T was more imoprtant for the calculation of SG and DM. The calculation of the observed response variables for the OT of fish in the S2 solution was mostly influenced by the linear term of t. The influence of the quadratic term was also very important for the calculation of WL, SG, aw and DM (statistically significant at p<0.05 level, 95% confidence limit). The linear term of T was important for the calculation of aw and DM calculation, as well as for the evaluation of the observed 49 APTEFF, 45, 1-283 (2014) DOI: 10.2298/APT1445045L UDC: 66.047.3:664.151.2]:637.56 BIBLID: 1450-7188 (2014) 45, 45-53 Original scientific paper mineral contents. The quadratic term of T was influential for the calculation of WL and SG, as well as for the observed mineral contents. The interchange term of t × T in the SOP models for mineral calculation was also found to be statistically significant at p<0.05 level, 95% confidence limit. Principal component analysis (PCA) The PCA applied to the given data set (Table 1) showed a differentiation between the samples according to the process parameters and is used as a tool in exploratory data analysis to characterize and differentiate the neural network input parameters (Fig. 1). 2 92.27% 27 Factor 2: 3.74% Eigenvalue 8 (a) 6 4 2 0.97% 0.45% 0.04% 3.74% 1.43% 0.70% 0.40% 0 0 1 2 3 4 5 6 7 8 9 Eigenvalue number 18 25 22 9 26 15 SG 24 19 13 7 8 11 23 DM 21 Mg 17 0 4 14 Na 10 6 16 K 1 WL 5 Ca 20 -1 2 3 12 -2 -6 -4 -2 0 2 4 6 Factor 1: 92.27% 2 8 83.98% (c) 6 Factor 2: 8.60% Eigenvalue 10 (b) 1 4 2 2.97% 0.28% 8.60% 3.60% 0.55% 0.02% 0.01% 0 0 1 2 3 4 5 6 7 8 9 Eigenvalue number 10 1 0 -1 -2 -6 (d) 18 27 26 Ca 22 17 23 15 Na 13 K 14 7 WL24 21 10 19 1 8 11 20 12 DM 4 9 Mg SG 5 2 6 3 -4 -2 0 2 4 6 Factor 1: 83.98% a 25 16 w Figure 1. Eigenvalues of the correlation matrix for OT of Carassius gibelio in S1 (a) and S2 (c) solution and the biplots for treatment in S1 (b) and S2 (d) solution Dot captions in Figs. 1b and 1d are defined by the equations [4] for S1 and [5] for S2: T  20   c  52.5  t 3 2   i  1  1    1    3  1   3 , 10   12.5  2    T  20   c  70  t3 2   i  1  1    1    3  1   3 , 10   10  2    [4] [5] where: T is the processing temperature (10, 20 or 30oC), t is the immersion time (1, 3 or 5 h), c is the concentration (60, 70 or 80 % w/w for S1 or 45, 52.5 or 60 % w/w for S2). 50 APTEFF, 45, 1-283 (2014) DOI: 10.2298/APT1445045L UDC: 66.047.3:664.151.2]:637.56 BIBLID: 1450-7188 (2014) 45, 45-53 Original scientific paper As can be seen, there is a neat separation of the observed samples according to used assays. The quality results show that the first two principal components, accounting for 96.89 % and 98.37% of the total variability for solution S1 and S2, respectively, can be considered sufficient for data representation and the first two principal components for the integrated chemical and physical quality. The values of WL, SG, DM, and of the mineral contents were more influential for the calculation of the first factor coordinate, while aw was more influential for the calculation of the second factor coordinate, for both solutions. The influence of processing parameters can be observed in Fig. 1, with the samples processed with lower processing parameters located at the left side of both graphs. The PCA graphs showed quite good discrimination between the S1 and S2 solution. The Na content increased with the increase in all the process parameters for both S1 and S2 solutions, while the other mineral contents tended to increase only in the S2 solution, due to the high amounts of minerals in the molasses. Sugar beet molasses contains about: 3920mg/100g K, 100mg/100g Ca, 320 mg/100g Mg, and 680 mg/100g Na (23). CONCLUSION This paper presents the influence of the process parameters on the kinetics and chemical properties of the processed samples. The observed samples were characterized by physical and chemical analyses, and the parameters used in the statistical analysis were divided into input and output variables. The input variables were the immersion time, temperature and concentration (of ternary solution or sugar beet molasses), while the output variables were the water loss, solid gain, water activity, dry matter content, and the content of Na, K, Ca and Mg. 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Filipčev, B.: Nutrition profile, antioxidative potential and sensory quality of bread supplemented with sugar beet molasses (in Serbian), Ph.D. Thesis, University of Novi Sad, 2009. ɈɋɆɈɌɋɄA ȾȿɏɂȾɊȺTAɐɂȳȺ ɆȿɋȺ ɊɂȻȿ - ȺɇȺɅɂɁȺ ȽɅȺȼɇɂɏ ɄɈɆɉɈɇȿɇɌɂ 1 . *, . . 1 2 , , , , ђ w 30 C), , 1 . (Carassius gibelio) - 1 1 . 1, 21000 12-16, 11000 , , (10, 20 , 1 . 2 ( 1 . 1 , , - 2), . , , ((Na, K, Ca , , Mg). . Ʉʂɭɱɧɟ ɪɟɱɢ: o , , , Received: 13 June 2014. Accepted: 26 September 2014. 53 THIS ISSUE OF ACTA PERIODICA TECHNOLOGICA IS FINANCIALLY SUPPORTED BY: Ministry of Education, Science and Technological Development of Republic of Serbia Editorial: University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21000 Novi Sad, Serbia Phone: +381 21 485 3652 Fax:+381 21 450 413 e-mail: sdjilas@tf.uns.ac.rs Text-Proof-Reader: Prof. Dr. Luka Bjelica Typsetting: Branislav Bastaja Cover design: Živojin Katić Printed by Futura d.o.o., Petrovaradin Copies: 200