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Food Hydrocolloids 32 (2013) 453e462

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Food Hydrocolloids

journal homepage: www.elsevier .com/locate/ foodhyd

Characterization of rheological interactions of Gleditsia triacanthosgum with some hydrocolloids: Effect of hydration temperature

Ebubekir Cengiz a, Mahmut Dogan b,*, Safa Karaman b

aNevsehir University, Tourism Faculty, Gastronomy and Culinary Arts Department, 50300, Nevsehir, Turkeyb Erciyes University, Engineering Faculty, Food Engineering Department, 38039, Kayseri, Turkey

a r t i c l e i n f o

Article history:Received 11 May 2012Accepted 28 January 2013

Keywords:GumGleditsia triacanthosHydration temperatureRheologyFuzzy modelLinear and non-linear models

* Corresponding author. Tel.: þ90 352 207 6666/32E-mail addresses: dogan@erciyes.edu.tr,

(M. Dogan).

0268-005X/$ e see front matter Crown Copyright �http://dx.doi.org/10.1016/j.foodhyd.2013.01.018

a b s t r a c t

In this study, synergistic interactions were investigated between Gleditsia triacanthos (Gt) gum and somecommonly used hydrocolloids (xanthan, k-carrageenan, carboxymethyl cellulose (CMC) and alginate).Two different hydration temperatures (25 and 80 �C) were used and apparent viscosity of gum blendswas determined. Linear and nonlinear fuzzy models were constructed for the estimation of apparentviscosity of gum blends. Gt gum showed non-Newtonian pseudoplastic behavior in the range of studiedconcentrations and shear rates. Gt generally showed good synergistic interactions with selected hy-drocolloids and the best one was Gt-xanthan blend because of the good interaction due to the associationof xanthan double helicoidal structure with sequences of unsubstituted mannosyl residues in the gal-actomannan based Gt gum. The effect of hydration temperature was found to be very significant in termsof rheological behavior of gum solution. Fuzzy models showed very high estimation accuracy comparedto linear models (R2 > 0.999). All of these findings showed that gum obtained from Gleditsia triacanthosseeds, sole or combined with other hydrocolloids can be utilized as a new and efficient thickening agentand fuzzy models can be used to predict the apparent viscosity of gum blends.

Crown Copyright � 2013 Published by Elsevier Ltd. All rights reserved.

1. Introduction

Water soluble gums, also called as hydrocolloids, are widelybeing used in food industry to modify the texture, appearance andrheological characteristics because they can stabilize emulsions anddispersions (Rosell, Rojas, & Benedito de Barber, 2001). The term ofgum has been used for the description of some polysaccharideswhich are naturally occurred in some sources (Willimas & Phillips,2000). Many plants synthesize gum exudates as a result of theprotection mechanism against mechanical or microbial injuries(Rana et al., 2011). In general, some hydrocolloids have a gal-actomannan based structure which means that the major sugarsare galactose andmannose. They are natural polysaccharides, basedon b-(1-4)-D-mannan backbone with single D-galactose brancheslinked a-(1-6), obtained from the seed endosperm of Leguminoseae(Kök, Hill, & Mitchell, 1999). Guar gum, locust bean gum, fenugreekgum and tara gum are well known galactomannan based hydro-colloids and they are used on industrial scale. They are widely usedin textile, pharmaceutical, biomedical, cosmetics and food in-dustries due to their different functional properties mainly as

751; fax: þ90 352 4375784.doganmahmut38@gmail.com

2013 Published by Elsevier Ltd. All

thickening and stabilizing agents in a range of applications(Srivastava & Kapoor, 2005; Vieira, Mendes, Gallão, & de Brito,2007). The combinations of more than one type of hydrocolloidsare effectively used to apply to higher requests for practical use infood industries. In this way, rheological properties can be modifiedor enhanced and cost savings during manufacturing may also beprovided (Norziah, Foo, & Karim, 2006; Walkenström, Kidman,Hermansson, Rasmussen, & Hoegh, 2003). A disperse systemwhich has a higher viscosity can be produced with blending ofmore than one hydrocolloid compared to that of sole ones and thisis called as synergism (Lapasin & Pricl, 1995, p. 439). In this sense,many studies were conducted to investigate the viscous synergismamong the commonly used hydrocolloids (Ahmed, Ramaswamy, &Ngadi, 2005; Dogan, Toker, Aktar, & Goksel, 2013; Fitzsimons, Tobin,& Morri, 2008; Kayacier & Dogan, 2006; Pai & Khan, 2002; Pinheiroet al., 2011; Shobha & Tharanathan, 2009; Toker, Dogan, & Goksel,2012; Zhang & Kong, 2006).

Gleditsia triacanthos (Gt) is moderately fast growing treecommonly found in America, Middle Europe and Mediterraneancountries including Turkey (Üner & Altınkurt, 2004). Its seeds arecomposed of testa (27% w/w), embryo (39% w/w) and endosperm(34% w/w) (Manzi, Mazzini, & Cerezo, 1984). Galactomannan-richnatural polysaccharide presence in the endosperm of Gt hasbeen reported (Mazzini & Cerezo, 1979). It contains variable

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Table 1Experimental design of gum mixtures.

Sample Gt concentrations (%) Selected gum Concentrations (%)

1 0.5 e 02 0.4 Alginate 0.13 0.25 Alginate 0.254 0.1 Alginate 0.45 0 Alginate 0.56 0.4 k-carrageenan 0.17 0.25 k-carrageenan 0.258 0.1 k-carrageenan 0.49 0 k-carrageenan 0.510 0.4 Xanthan 0.111 0.25 Xanthan 0.2512 0.1 Xanthan 0.413 0 Xanthan 0.514 0.4 CMC 0.115 0.25 CMC 0.2516 0.1 CMC 0.417 0 CMC 0.5

Gt: Gleditsia triacanthos gum; CMC: Carboxymethyl cellulose.

E. Cengiz et al. / Food Hydrocolloids 32 (2013) 453e462454

mannose:galactose ratio depending on the extraction and purifi-cation techniques. Sciarini, Maldonado, Ribotta, Pérez, and León(2009) investigated the chemical composition and functionalproperties of Gt gum which is extracted by using three differentextraction methods and they reported that the extraction methodseffected the mannose:galactose ratio in the structure of gum.Pinheiro et al. (2011) investigated the rheological characteristics ofk-carrageenan or xanthan and their blendwith Gt at different ratiosand reported that galactomannan based Gt interacted with k-carrageenan and xanthan synergistically.

During the last decade, new and functional computationalmodeling techniques have been introduced to solve the engineer-ing problems. Artificial intelligence techniques are the softcomputing modeling techniques which are used to solve theproblems in non-linear systems. Artificial neural networks (ANN),fuzzy logic techniques and adaptive neuro fuzzy inference systemswhich is the combination of ANN and fuzzy inference system (FIS)are commonly used methods due to their high nonlinear functionalcharacteristics are very appropriate for the modeling of thenonlinear process. These techniques are very efficient to solve thecomplicated problems and non-linear systems impossible to bemodeled mathematically with only sets of data available (Cobaner,2011). Additionally, these techniques are very quick and easy to beapplied while the conventional methods require solving compli-cated equations or conducting the tedious test (Sivanandam,Sumathi, & Deepa, 2007). Blending of the some hydrocolloids infood formulations is effective technique to produce a dispersesystem having higher viscosity value compared to the sum of theviscosities of the individual hydrocolloid dispersion consideredseparately. This phenomenon is known as viscous synergism(Hernández, Dolz, Dolz, Delegido, & Pellicer, 2001; Lapasin & Pricl,1995). It is also reported that the viscosity of blended hydrocolloidsincreases nonlinearly with the increase of hydrocolloid concen-tration above a certain concentration values (Hernández et al.,2001).

The first aim of the present study was to investigate the rheo-logical characterization of galactomannan based Gt gum producedfrom its seeds and to determine the synergistic interactions be-tween Gt and some commonly used hydrocolloids such as xanthan,k-carrageenan, alginate and carboxymethyl cellulose (CMC) at twodifferent hydration temperatures (25 and 80 �C). The second aimwas to construct fuzzy models which can be used to estimate theapparent viscosity values of blended hydrocolloid solution due tothe nonlinearity of viscosity increase of blended gum solutions.

2. Materials & methods

2.1. Materials

Gt pods were collected from the trees in Kayseri, Turkey. Seedswere manually separated from the pods and stored at room con-ditions. Xanthan, CMC, k-carrageenan were provided by SigmaAldrich (Taufkirchen, Germany) and alginate was provided byCargill Inc. (_Istanbul, Turkey).

2.2. Methods

2.2.1. Preparation of Gt gumA procedure described by Carqueira et al. (2009) was followed.

Firstly Gt seeds were washed with tap water and kept on the trays atroom temperature for 12 h. Then the seeds were milled using a lab-oratory type grinder (Herzog-Milling, HPF, Germany). Material ob-tained was suspended in distilled water (1:40 w/v) and boiled for30 min. The boiled mixture was filtered using a layer of gauze. Aftermixing the filtrate with distilled water (40 mL), boiling and filtration

process were repeated and the filtrate was centrifuged for 20 min(Nüve, 800R, Turkey) at 2000 g to remove impurities. The superna-tants were precipitated with ethanol (96% v/v). Precipitated materialwas dried in oven (Nüve, ES120, Turkey) at 30 �C for 12 h and driedmaterial wasmilled using a grinder (Herzog-Milling, HPF, Germany).

2.2.2. Experimental designExperimental design is shown in Table 1. Four different mixture

concentrations were arranged for each gum samples (Gt, xanthan,k-carrageenan, alginate and CMC). All the solutions were alsoformed at a total concentration of 0.5% (w/w) and stirred withmagnetic stirrer (Stuart, CB 162, ABD) at 25 and 80 �C for 1 h. Thehydration temperature of 80 �C for Gt and its mixture for othergums was determined according to the Pinheiro et al. (2011). Toshow the hydration and its effect on the rheology of solutions, roomtemperature was selected to be 25 �C. After hydration at 80 �C, thesamples were inserted directly to the heat controlled water bathadjusted to 25 �C (Memmert WNB 22, Germany) and cooled tomeasurement temperature (25 �C) at about 30 min. The flasks werecovered with a parafilm for the inhibition of evaporation. Table 1shows 17 different samples containing various Gt and selectedgum concentrations. To determine synergistic interactions betweenGt gum and the others, mixtures were prepared at the concentra-tion of the 0.5%, 0.4%, 0.25%, 0.1% (w/w) (Table 1).

2.2.3. Physicochemical & rheological analysisMoisture and ash content of hydrocolloids were determined

according to American Association of Cereal Chemists AACC (1995)methods. Color measurement of dried gum powder was performedusing a colorimeter (Lovibond RT Series Reflactance Tintometer,England). For the determination of the yield, total weight of en-dosperms was divided to the seed weight of 100 g (w/w). pH valuesof samples were determined at 25 �C using a pH-meter (WTW e

Inolab, Weilheim, Germany). Water holding capacity (WHC) ofsamples was determined at room temperature (25 � 2 �C)according to the procedure described by AACC (1995). For thispurpose, 0.5 g sample was suspended with 50 mL distilled waterand stirred using a vortex for 1 min and centrifuged (Nüve, 800R,Turkey) at 1600 g for 10 min. After removing the free water fromthe suspension, WHC was calculated using the following equation.

WHCðmL=gÞ ¼ Wsediment �Wsample

Wsample(1)

where W is weight.

E. Cengiz et al. / Food Hydrocolloids 32 (2013) 453e462 455

Oil holding capacity (OHC) of samples was determined at roomtemperature (25 � 2 �C) according to the procedure described byAACC (1995). For this purpose, 0.5 g sample was suspended with10mL of corn oil (Ülker, Turkey) and stirred using a vortex for 1 minand centrifuged (Nüve, 800R, Turkey) at 800 g for 10 min. Afterremoving the free oil from the suspension, OHC was calculatedusing the following equation.

OHCðmL=gÞ ¼ Wsediment �Wsample

Wsample(2)

where W is weight.For the determination of mannose:galactose ratio of Gt gum, the

method described by Leschziner and Cerezo (1970) was conducted.For this aim, 0.2 g hydrocolloid sample was hydrolyzed with 20 mLof 0.5 M H2SO4 at 95 �C for 12 h. After the hydrolysis, the solutionwas neutralized with NaOH and the volume was adjusted to 50 mLwith distilled water. The tubes were centrifuged (Hettich Universal320, Germany) at 1300 g for 10 min and then the supernatant wasfiltered using a 0.45 mm nylon filter (Sartorious Stedim Biotech,Gottingen, Germany). High Performance Liquid Chromatography-Refractive Index Detector (HPLC-RID, Agilent 1100 Series, USA)equipped with a manual injection quaternary pump (U.S.A) andZorbax carbohydrate column (4.6 � 250 mm, 5 mm particle size)which is thermostated at 25 �C was used for the determination ofmonosaccharide composition. 20 mL of the filtrate was injected tothe column. Theflow rate ofmobile phase (80:20 acetonitrile:water,v/v) was set to 1.4 mL/min. Major sugar composition (galactose andmannose) was determined by the comparison of retention timeswith authentic standards and the amounts of sugars were calcu-lated according to the calibration curves for each sugar.

Rheological analyses were carried out using a strain/stresscontrolled rheometer (Thermo-Haake Rheostress1, Karlsruhe, Ger-many) equipped with a temperature-control unit (Thermo-HaakeK15, Karlsruhe, Germany). The samples were sheared using a cone-plate configuration (cone diameter 35 mm, angle 4�). The apparentviscosity of solutions was recorded in the range of 5e100 s�1 shearrate at 25 �C. During the shearing, a total of 24 data points wererecorded at 10 s intervals. Each measurement was replicated withtwo repetitions. Power law model was used for the calculations ofconsistency coefficient and flow behavior index as following.

ha ¼ K _gn�1 (3)

where ha is the apparent viscosity (mPa s), K is the consistencycoefficient (mPa sn), g is shear rate (1/s) and n is flow behaviorindex.

2.2.4. Linear and non-linear models for the estimation of apparentviscosity of binary gum mixtures

In the linear modeling, expected viscosity of binary gum mix-tures in a solution was calculated using Eq. (4).

Fig. 1. Architectu

hmix ¼ XAhA þ XBhB (4)

where hmix is the apparent viscosity of binary gum mixture, XA andXB are the weight fractions of gum A and B, respectively, and hA andhB are the apparent viscosity of sole gum A and B, respectively at50 s�1.

In non-linear modeling procedure, Adaptive Neuro FuzzyInference System (ANFIS) combines the performance of ANN andFIS was used. To construct the ANFIS models for the estimation ofapparent viscosity of samples, fuzzy logic toolbox of MATLAB 7.0.1was used. In order to conduct this, all apparent viscosity data ofsamples were classified. Firstly, half of the selected data (360 datapoints) were determined as training data matrix. One hundred andeighty data points, which are different from the training data, wereselected for the testing and validation of fuzzy model system,separately. To determine the best fit in fuzzy model, differentcombinations were trained. For this reason, three different mem-bership function (mf) numbers (3, 4 or 5) and two different types ofmembership function for output (constant or linear) were studiedand constructed 6 fuzzy models with these parameters for eachbinary mixtures containing Gt and studied gum. Type of member-ship function for input was selected as triangular mf for all fuzzymodels. To construct a fuzzy model, Gt concentration, selectedhydrocolloid concentration, hydration temperature and shear ratevalues were selected as input while the apparent viscosity wasoutput. 10 learning epochs and a radius of 0.5 were used for thedevelopment and implementation of models. In ANFIS modeling,Sugeno type fuzzy system was used because it has high neurallearning ability, interpretability and computational efficiency.Sugeno type fuzzy system has a basic structure based on the ruleswith several inputs x, y. and one output f. The linguistic variablesshould have been provided instead of or in addition to numericalvariables to construct a fuzzy system. After that, the fuzzy systemneeds some IF/THEN fuzzy rules for the characterization of therelationship between the fuzzy variables. For a first order Sugenofuzzy model, a typical rule set with two fuzzy if/then rules can bewritten as follows (Cobaner, 2011; Sayed, Tavakolie, & Razavi,2003);

Rule 1: if x is A1 and y is B1; then f1 ¼ p1xþ q1yþ r1; (5)

Rule 2: if x is A2 and y is B2; then f2 ¼ p2xþ q2yþ r2; (6)

where x and y are the inputs, Ai and Bi are the fuzzy sets; fi is theoutput within the fuzzy region determined by the fuzzy rule; p1, q1and r1 are the design parameters obtained during training phase(Fig. 1). As can be seen from the Fig. 1, ANFIS architecture imple-menting these two rules, shows is the circles which indicates afixed node, while the square which indicates an adaptive node.ANFIS structure is constructed by five layers namely fuzzificationlayer (1), rule layer (2), normalization layer (3), defuzzification layer

re of ANFIS.

E. Cengiz et al. / Food Hydrocolloids 32 (2013) 453e462456

(4) and output layer (5). A detailed description can be found in thestudy of Yilmaz (2012).

Coefficient of determination (R2), root mean square error(RMSE) and mean absolute error (MAE) were used as comparisoncriterion to evaluate the accuracy of constructed models as follows:

RMSE ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi1n

Xn

i¼1

hiobserved � hipredicted

� �2vuut (7)

MAE ¼ 1n

Xn

i¼1

���hiobserved � hipredicted

��� (8)

inwhich n is the number of data, hi is the apparent viscosity used asoutput.

R2 ¼ 1�Pn

i¼1

h�hobs;i

���hpre;i

�i

Pni¼1

h�hobs;i

���hpre;i

�i2

2

(9)

where hobs,i is the observed data (apparent viscosity, h), hpre,i is thepredicted data, hpre;i is the mean value of experimental data and n isthe number of data points.

2.2.5. Statistical analysisAll statistical analyses were conducted using SAS system Sta-

tistical Analysis System (SAS, 1988). Analysis of variance (ANOVA)was carried out using Duncan multiple comparison tests to deter-mine the differences between means.

3. Results & discussions

3.1. Physicochemical properties

Physicochemical properties of Gt gum and other studied gumswere tabulated in Table 2. Extraction yield of Gt gum was deter-mined to be 16.9%. In general, extraction yield changes dependingon the extraction methods, especially extraction solvent. Sciariniet al. (2009) used hot water, 2 N NaOH and water and they re-ported that the extraction yield of Gt gum was 11.9%, 23.06% and,34.16%, respectively. Extraction yields of gum from Gt were alsoreported to be 15.4% (Manzi et al., 1984), 18% (Mirzaeva,Rakhmanberdyeva, Kristallovich, Rakhimov, & Shtonda, 1998) and15e20% (Leschziner & Cerezo, 1970). Moisture content of gums wasdetermined in the range of 7.8e10.70%while the ash content was inthe range of 2.9e32.4%. The highest ash content was determined fork-carrageenan while the lowest was in Gt gum. pH values of sam-ples were found to be close to each other but the differences weredetermined to be significant (p < 0.05). Galactose and mannosecontent of the Gt gum was determined to be 19.3 and 48%. Sciariniet al. (2009) reported that the galactose and mannose content ofgumwere in the range of 15.5e18.2% and 43.1e48.4% depending onthe extraction methods. WHC and OHC of Gt were found to be

Table 2Physicochemical properties of Gleditsia triacanthos gum and other used gums.

Sample Yield (%) Moisture (%) pH WHC (mL/g) O

Alginate e 8.0a 6.3b 12.2b 3k-carrageenan e 9.1b 6.2d 33.3a 3Xanthan e 10.7c 6.1e 34.7a 3CMC e 7.8a 6.6a 12.8b 3Gleditsia triacanthos 16.9 8.8b 6.2c 14.6b 3

WHC: Water holding capacity, OHC: Oil holding capacity, CMC: Carboxymethyl cellulosdifferences (p < 0.05).

14.6 mL/g and 3.1 mL/g, respectively. The highest WHC values weredetermined to be 33.3 and 34.7 mL/g for k-carrageenan and xan-than gum, respectively. Sciarini et al. (2009) reported that theWHCof Gt gum was in the range of 8.19e15.20 g/g depending on theextraction process. Gt was found to be less white (L value is 74.5)compared to other gums (Table 2).

3.2. Rheological properties

3.2.1. Effect of hydration temperature on the rheology of gums andtheir blends

Gt and gum mixtures showed non Newtonian shear-thinningbehavior as the apparent viscosity decreased with the increasein shear rate. Fig. 2 shows the effect of hydration temperature onthe flow behavior curves of alginate and Gt and their mixtures. Ingeneral, hydration temperature significantly affected (p < 0.05)the apparent viscosity values of gum solutions. Apparent viscosityvalue of sole Gt gum (36.8 mPa s) at 50 s�1 and 25 �C hydrationtemperature was found to be lower (Fig. 2a) compared to apparentviscosity value (65.3 mPa s) at 50 s�1 and 80 �C hydration tem-perature (Fig. 2b). While apparent viscosity value of alginate at25 �C was higher than that of Gt gum, at 80 �C, apparent viscosityof Gt was found to be higher than that of alginate. At low hydra-tion temperature (25 �C), alginate and Gt mixture showed a goodsynergistic interaction because apparent viscosity values ofmixture were determined to be higher compared to those of solegums (Fig. 2a). Decrease in alginate concentration and increase inGt gum concentration in the mixture caused a decrement in theapparent viscosity values of mixture at 25 �C. At 50 s�1, apparentviscosity of alginate (0.4%) and Gt (0.1%) mixture was found to be62.1 mPa s while the apparent viscosity of alginate (0.1%) and Gt(0.4%) was 48.1 mPa s. On the contrary, at 80 �C, apparent viscosityincreased with the decrease of alginate and increase of Gt con-centration. Mixture of alginate and Gt showed a good synergisticinteraction at both hydration temperatures depending on themixture ratio because apparent viscosity values of their mixturewere found to be higher compared to apparent viscosity of solegums. Maximum synergistic effect was observed for the mixturecontaining 0.1% alginate and 0.4% Gt and hydrated at 25 �C. For thesamples hydrated at 80 �C, maximum synergistic effect wasobserved for the mixture containing 0.25% alginate and 0.25% Gt.As is known, alginate is a natural biopolymer which has a linearchain of 1e4 linked b-D-manuronic acid and a-L guluronic acidresidue (Gombotz & Wee, 1998; Valenga et al., 2011). Valenga et al.(2011) reported that the alginate showed a significant synergisticinteraction with a galactomannan extracted from the seeds ofLeucaena leucocephala. They concluded that the alginate is ananionic polysaccharide which has a linear chain and gal-actomannan is a neutral one and probably, the main reason in theincrease of apparent viscosity of mixture prepared with alginateand a galactomannan is the intermolecular association effectsoccurring between the polysaccharides especially include severalhydrogen bonds. Similar study was conducted by Walkenströmet al. (2003) and they found that alginate which has low

HC (mL/g) Ash (%) Man (%) Gal (%) L a b

.1b 19.0b e e 81.5b 3.6d 12.3d

.5a 32.4a e e 77.5d 5.6a 15.7b

.2ab 9.5d e e 80.4c 4.7c 14.5c

.3ab 18.1c e e 85.6a 2.3e 7.5e

.1b 2.9e 48.0 19.3 74.5e 5.1b 16.2a

e, Man: Mannose, Gal: Galactose. Different superscript letters show the significant

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Fig. 2. Flow behavior curve of Gt (Gleditsia triacanthos) and alginate gum and their mixtures at different concentrations. a: hydration temperature is 25 �C and b: hydrationtemperature is 80 �C.

E. Cengiz et al. / Food Hydrocolloids 32 (2013) 453e462 457

mannuronic acid/guluronic acid ratio showed a strong synergisticinteraction with pectin which has high esterification degree.Similar results related to pectin and alginate synergism were re-ported by Gohil (2011). Voron’ko, Derkach, and Izmailova (2002)also reported that the combination of alginate and gelatin pro-vided a synergism in the rheological characteristics of the result-ing multicomponent gels. Synergism between karaya gum andalginate (Le Cerf & Muler, 1994) and guar gum and alginate (Dong-Bao, Li-Hua, Qing, & Xiao-Zhen, 2004) was also reported.

The effect of hydration temperature on flow behavior curves ofcarrageenan, Gt and their mixtures is illustrated in Fig. 3. All sam-ples showed pseudoplastic behavior and the effect of hydrationtemperature on the apparent viscosity values of samples was foundto be significant (p < 0.05). Increase in hydration temperature wasfound to be effective (p < 0.05) on the apparent viscosity incre-ment. The apparent viscosity of sole Gt gum at 50 s�1 and 25 �Chydration temperature was found to be 36.8 mPa s while theapparent viscosity of carrageenan was 23.7 mPa s at same condi-tions (Fig. 3a). Increase in hydration temperature from 25 �C to80 �C, increased the apparent viscosity values of Gt and carra-geenan gum from 36.8 to 65.3 and 23.7 to 40.1, respectively(Fig. 3b). Apparent viscosity values of Gt and carrageenan mixturedecreased with the increase of Gt and decrease of carrageenan gumconcentration at 25 �C. But at 80 �C, increase of Gt gum concen-tration in the mixture increased the apparent viscosity values offinal mixture. The apparent viscosity of gum mixture containing0.4% carrageenan and 0.1% Gt gumwas found to be 38.7mPa swhilethe apparent viscosity of 0.1% carrageenan and 0.4% Gt was57.3 mPa s at 80 �C hydration temperature. Maximum synergisticeffect was found for the mixtures containing 0.4% carrageenan and

020406080

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a) 0.5% Gt0.5% Carreg0.4% Carreg+0.1% Gt0.25% Carreg+0.25% Gt0.1% Carreg+0.4% Gt

Fig. 3. Flow behavior curve of Gt (Gleditsia triacanthos) and carrageenan gum and their mitemperature is 80 �C.

0.1% Gt gum at 25 �C. On the contrary to this, for the samples hy-drated at 80 �C, generally an antagonistic effect was observedbecause the apparent viscosity values of mixtures were found to belower than that of sole gums. It means that at 80 �C hydrationtemperature, synergism weakened and for that reason, carra-geenan showed low viscosity at high hydration temperature. It wasreported that all carrageenans hydrate at high temperatures andkappa and iota carrageenans in particular exhibit a low fluid vis-cosity. On cooling, these carrageenans set depending on the cationspresent, to form a range of gel textures (Imeson, 2000). k-carra-geenan is a complex mixture of sulfated galactans which hasrepeating disaccharide units of 3-linked b-D-galactose-sulfate and4-linked 3,6-anhydro-a-D-galactose (Arda, Kara, & Pekcan, 2009).Many studies in the literature showed that k-carrageenan is syn-ergistic with some gums such as locust bean gum and konjacmannan (Arda et al., 2009; Dunstan et al., 2001; Goycoolea,Richardson, Morris, & Gidley, 1995; Pinheiro et al., 2011; Stading& Hermansson, 1993; Yamazaki, Kurita, & Matsumura, 2008). Lo-cust bean gumwhich is a very well known galactomannan shows agood synergistic interaction with k-carrageenan in aqueous solu-tion for gelation. Dea and Morrison (1975) proposed a mechanismfor the interaction between the linear segments of the D-mannosebackbone of galactomannan and double-stranded helix of k-carrageenan. Additionally, Pinheiro et al. (2011) reported that thesynergistic effect of k-carrageenan and galactomannans dependentto both mannose/galactose ratio and the fine structure of the gal-actomannans. They also reported that Gt gum showed a synergis-tically interaction with k-carrageenan but the effect was found tobe lower compared to synergistic effect between k-carrageenanand locust bean gum or guar gum.

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xtures at different concentrations. a: hydration temperature is 25 �C and b: hydration

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Pa s)

Shear rate (s-1)

a) 0.5% Gt0.5% Xant0.4% Xant+0.1% Gt0.25% Xant+0.25% Gt0.1% Xant+0.4% Gt

0500

100015002000250030003500400045005000

0 50 100

Ap

paren

t visco

sity (m

Pa s)

Shear rate (s-1)

b) 0.5% Gt0.5% Xant0.4% Xant+0.1% Gt0.25% Xant+0.25% Gt0.1% Xant+0.4% Gt

Fig. 4. Flow behavior curve of Gt (Gleditsia triacanthos) and xanthan gum and their mixtures at different concentrations. a: hydration temperature is 25 �C and b: hydrationtemperature is 80 �C.

E. Cengiz et al. / Food Hydrocolloids 32 (2013) 453e462458

Fig. 4 illustrates the flow behavior of Gt, xanthan and theirmixtures at different ratios at two different hydration tempera-tures. The xanthan gum and Gt gum and their mixtures showedpseudoplastic behavior. Apparent viscosity decreased with the in-crease of shear rate. Increase of hydration temperature increasedthe apparent viscosity of Gt, xanthan and their mixture (p < 0.05).Apparent viscosity of xanthan gum was determined to be106.3 mPa s at 50 s�1 and 25 �C (Fig. 4a) while the apparent vis-cosity of Gt was 36.8 mPa s at same conditions. But they wererecorded as 89.9 and 65.3 mPa s at 50 s�1 and 80 �C, respectively(Fig. 4b). Additionally, at both hydration temperatures, increase ofGt concentration in the mixture increased the apparent viscosity offinal mixture. For example, the apparent viscosity of gum mixturecontaining 0.4% xanthan and 0.1% Gt gum was determined to be90.6 and 285.7 mPa s at 25 and 80 �C, respectively while theapparent viscosity of gum mixture containing 0.1% xanthan and0.4% Gt gumwas 128.5 and 720 mPa s at 25 and 80 �C, respectively.The maximum synergistic effect among the studied gum mixtureswas observed for the xanthan and Gt mixture at both hydrationtemperatures. Xanthan gum which is an extracellular poly-saccharide produced by Xanthomonas campestris and it is a penta-saccharide having a repeating units with a b-1,4 linked cellulosicbackbone and attached with a charged trisaccharides side chaindocked on glucose residue (Pinheiro et al., 2011). Pinheiro et al.(2011) reported that the synergistic interaction between gal-actomannans and xanthan and they also reported that the bestsynergism was observed for the ratio of 20% xanthan/80% gal-actomannan. Many studies regarding the interaction of xanthanand galactomannans are present in the literature (Cairns, Miles, &Morris, 1986; Cheetham, McCleary, Teng, Lum, & Maryanto, 1986;

b

0

50

100

150

200

250

300

0 50 100

Ap

paren

t visco

sity (m

Pa s)

Shear rate (s-1)

a) 0.5% Gt0.5% CMC0.4% CMC+0.1% Gt0.25% CMC+0.25% Gt0.1% CMC+0.4% Gt

Fig. 5. Flow behavior curve of Gt (Gleditsia triacanthos) and CMC gum and their mixtures at dis 80 �C.

Goycoolea et al., 1995; Mannion et al., 1992). Morris, Rees, Young,Walkinshaw, and Darke (1977) suggested that the mechanism ofxanthan and galactomannan synergistic interaction is an inter-molecular binding between the ordered (helix) xanthan andunsubstituted or poorly substituted regions of galactomannanbackbone. And also, the synergistic interaction between xanthanand galactomannan is strongly depended on the galactose contentbecause the ability of galactomannans to show synergism withxanthan increases with decrease in galactose content (Morris et al.,1977). Similarly, Shobha and Tharanathan (2009) reported that theconcentration of xanthan plays an important role in the occurringof synergistic interaction for the biopolymers.

Flow behavior curves of Gt, CMC and their mixtures at differentratios were illustrated in Fig. 5. They showed pseudoplasticbehavior which is similar to other studied gums. Hydration tem-perature effect was found to be statistically significant (p< 0.05) forthe increase of apparent viscosity of Gt and CMC mixture. In gen-eral, apparent viscosity increased with the increase of hydrationtemperature. It was recorded to be 110 mPa s for the mixturecontaining 0.4% CMC and 0.1% Gt while the apparent viscosity ofmixture containing 0.1% CMC and 0.4% Gt at 25 �C. The apparentviscosity of these mixtures was determined to be 129.2 and114.4 mPa s, respectively at 80 �C. The maximum synergistic effectwas observed from the mixture containing 0.1% CMC and 0.4% Gt at25 �C. Especially, at 80 �C, CMC showed a high synergistic inter-action in the mixture composed of 0.25% CMC and 0.25% Gt. Amongthe all studied gums, CMC showed the highest apparent viscosityvalues. It was reported that the CMC is very important water sol-uble gums for food industry and it is a copolymer of two differentunit; b-D-glucose and b-D-glucopyranose 2-O-(carboxymethyl)-

0

50

100

150

200

250

300

350

0 50 100

Ap

paren

t visco

sity (m

Pa s)

Shear rate (s-1)

) 0.5% Gt0.5% CMC0.4% CMC+0.1% Gt0.25% CMC+0.25% Gt0.1% CMC+0.4% Gt

ifferent concentrations. a: hydration temperature is 25 �C and b: hydration temperature

Table 3Rheological parameters of gum mixture solutions (0.5% w/v) at different hydrationtemperatures (25 and 80 �C).

Sample Hydration temperature

25 �C 80 �C

K (mPa sn) n R2 K (mPa sn) n R2

1 77 0.8101 0.9997 202 0.7069 0.99922 126 0.7530 0.9996 255 0.6796 0.99923 141 0.7670 0.9997 227 0.7177 0.99944 133 0.8035 0.9997 157 0.7797 0.99965 134 0.8099 0.9996 107 0.8311 0.99976 84 0.8047 0.9997 154 0.7388 0.99957 147 0.7048 0.9997 674 0.3208 0.97458 316 0.5344 0.9981 220 0.5721 0.99799 113 0.6029 0.9990 789 0.2456 0.988210 4367 0.1183 0.8691 15020 0.1395 0.900011 1875 0.2595 0.9775 162489 0.0047 0.266312 1903 0.2264 0.9918 15721 0.0279 0.303313 2324 0.2129 0.9976 2003 0.2098 0.999514 417 0.6083 0.9990 417 0.6083 0.999015 449 0.6185 0.9992 718 0.5951 0.998816 487 0.6232 0.9992 511 0.6469 0.999117 579 0.6295 0.9993 500 0.6563 0.9993

K: Consistency coefficient, n: Flow behavior index, R2: Coefficient of determination.

E. Cengiz et al. / Food Hydrocolloids 32 (2013) 453e462 459

monosodium salt which are linked with b-1,4-glycosidic bondsalong the macromolecule (Charpentier et al., 1997; Olaru, Olaru,Stoleriu, & Timpu, 1998; To�grul & Arslan, 2003). Yaseen, Herald,Aramouni, and Alavi (2005) reported that apparent viscosity ofsome selected hydrocolloids and they concluded that the apparentviscosity of CMC was determined to be higher compared to that ofguar, k-carrageenan, xanthan, locust bean gum, pectin and gumarabic. Zhang and Kong (2006) investigated the synergistic vis-cosity of aqueous polysaccharide blends of hydroxypropyl guargum and CMC and they reported that the zero shear viscosity wasdetermined to be greater than that of combined zero shear viscosityof the components and they concluded that the formation ofinterpolymer complex between the mixed hydroxypropyl guar

Table 4Testing performance of fuzzy models for apparent viscosity of Gt gum mixtures with alg

NMFs MFTI MFTO R2

X1 X2 X3

Gt þ alginate 3 trimf constant 0.9870 0.9718 0.94 trimf constant 0.9920 0.9746 0.95 trimf constant 0.9940 0.9754 0.93 trimf linear 0.9950 0.9758 0.94 trimf linear 0.9960 0.9759 0.95 trimf linear 0.9963 0.9760 0.9

Gt þ carrageenan 3 trimf constant 0.9056 0.8912 0.84 trimf constant 0.9479 0.9364 0.95 trimf constant 0.9681 0.9593 0.93 trimf linear 0.9795 0.9717 0.94 trimf linear 0.9920 0.9858 0.95 trimf linear 0.9963 0.9904 0.9

Gt þ xanthan 3 trimf constant 0.9326 0.9178 0.94 trimf constant 0.9638 0.9526 0.95 trimf constant 0.9779 0.9694 0.93 trimf linear 0.9859 0.9791 0.94 trimf linear 0.9942 0.9897 0.95 trimf linear 0.9971 0.9933 0.9

Gt þ CMC 3 trimf constant 0.9890 0.9868 0.94 trimf constant 0.9950 0.9917 0.95 trimf constant 0.9970 0.9929 0.93 trimf linear 0.9979 0.9937 0.94 trimf linear 0.9985 0.9941 0.95 trimf linear 0.9987 0.9941 0.9

NMFs: Number of Membership Function, MFTI: Membership Function Type of Input, MFTOAbsolute Error, R2: Coefficient of determination, X1: Training data, X2: Test data, X3: Vali

gum and CMC components, which leads to excluded volumes andnetwork structures, may be attributed to the viscosity synergism.

Ostwaldede Waele model parameters of all studied sole gumand gum mixture are shown in Table 3. All sole gum and theirblends with each other at different ratios showed shear thinningbehavior because their flow behavior index values were calculatedto be lower than unity. Also, Gt gum which is not very well knownin industrial application showed a pseudoplastic behavior which issimilar to others. The consistency coefficient of samples changedsignificantly depending on the gum concentrations in the mixtures.The highest consistency coefficient values were observed for thexanthan gum/Gt blends which ranged from 1903 to 4367 mPa s at25 �C. Increase in hydration temperature increased the consistencycoefficients significantly (p < 0.05). Flow behavior indexes werecalculated to be lower than unity because all samples showedpseudoplastic behavior. Generally, coefficients of determinationwere found to be rather high except two blends containing xanthanin high quantity which were hydrated at 80 �C. The reason behindthe low determination coefficients is likely due to the gelation ofxanthan and Gt mixture which has high xanthan ratio at high hy-dration temperature. For this reason, Ostwaldede Waele modelcould not explain the rheological behavior of these two blendswhich are 0.25% xanthan and 0.25% Gt and 0.4% xanthan and 0.1%Gt. Kayacier and Dogan (2006) reported that the gums are highmolecular weight hydrophilic biopolymers and their solutions havegenerally non-Newtonian pseudoplastic behavior which theirapparent viscosity decreases with the increase of shear rate andtheir flow behavior index values are lower than unity. And also,they reported that there were many mathematical models tocharacterize the their rheological behavior but the most commonlyused model was Ostwaldede Waele because it fits very well withthe rheological data of gum solutions. Sciarini et al. (2009) inves-tigated the chemical composition and functional properties of Gtgum and they reported that the Gt gum has a pseudoplastic shearthinning behavior. Similar results were also reported by other re-searchers (Garcia-Ocha, Santos, Casas, & Gómez, 2000; Kayacier &

inate, carrageenan, xanthan and CMC.

RMSE MAE

X1 X2 X3 X1 X2 X3

814 0.0027 0.0048 0.0036 2.7163 5.3154 4.7698847 0.0021 0.0046 0.0033 2.0963 5.1946 4.4019856 0.0018 0.0045 0.0032 1.8296 5.1653 4.3396861 0.0017 0.0045 0.0032 1.7511 5.1439 4.3160862 0.0015 0.0045 0.0032 1.6191 5.0965 4.2672861 0.0014 0.0045 0.0032 1.5670 5.0717 4.2841840 0.0135 0.0139 0.0144 8.3067 10.1272 10.4096295 0.0102 0.0110 0.0114 5.2667 7.5073 7.8518532 0.0080 0.0090 0.0094 3.7142 6.3248 6.5982665 0.0064 0.0077 0.0081 3.4691 6.2494 6.6071821 0.0040 0.0059 0.0060 2.2421 5.2942 5.5525874 0.0028 0.0051 0.0052 1.7608 5.0880 5.3201196 0.2610 0.3113 0.2947 26.8037 27.5747 26.5447560 0.1927 0.2419 0.2216 15.1827 16.1751 15.9899726 0.1511 0.1991 0.1773 9.7025 11.8314 10.9120815 0.1211 0.1691 0.1477 9.6042 12.0893 11.3979907 0.0779 0.1283 0.1088 5.8172 8.7664 8.2299934 0.0549 0.1106 0.0947 3.7415 7.5336 6.7952872 0.0072 0.0082 0.0084 3.7158 4.9356 5.5953922 0.0049 0.0065 0.0066 2.3863 4.1091 4.8117941 0.0038 0.0060 0.0058 1.9635 3.9269 4.5704949 0.0032 0.0057 0.0054 1.7925 3.8144 4.5092957 0.0027 0.0055 0.0049 1.5526 3.6359 4.3082959 0.0025 0.0055 0.0048 1.4210 3.6050 4.2462

: Membership Function Type of Output, RMSE: Root Mean Square Error, MAE: Meandation data, Gt: Gleditsia triacanthos gum, CMC: Carboxymethyl cellulose.

Table 5Comparison of linear and fuzzy model performance for the estimation of apparent viscosity values (mPa s) of gum mixtures at 50 s�1.

Samplesa Hydration temperature

25 �C 80 �C

Measured Estimated withlinear model

Estimated withfuzzy model

Measured Estimated withlinear model

Estimated withfuzzy model

0.4% Alg þ 0.1% Gt 62 55 63 67 58 650.25% Alg þ 0.25% Gt 57 48 57 76 61 730.1% Alg þ 0.4% Gt 48 41 51 74 63 730.4% Carreg þ 0.1% Gt 50 26 50 39 45 380.25% Carreg þ 0.25% Gt 44 30 44 50 53 540.1% Carreg þ 0.4% Gt 38 34 38 57 60 570.4% Xant þ 0.1% Gt 91 92 88 286 85 2790.25% Xant þ 0.25% Gt 99 72 99 414 78 5980.1% Xant þ 0.4% Gt 129 51 134 720 70 7030.4% CMC þ 0.1% Gt 110 11 118 129 118 1420.25% CMC þ 0.25% Gt 99 87 103 150 98 1500.1% CMC þ 0.4% Gt 91 57 91 111 79 108

a Alg: Alginate, Carreg: Carrageenan, Xant: Xanthan, CMC: Carboxymethyl cellulose.

E. Cengiz et al. / Food Hydrocolloids 32 (2013) 453e462460

Dogan, 2006; Medina-Torres, Brito-De la Fuente, Torrestiana-Sán-chez, & Katthain, 2000).

3.2.2. Estimation of apparent viscosity of gum blends with linearand nonlinear models

As stated before, the blending of certain types of hydrocolloidscan produce a greater viscosity compared to viscosities of sole gumsused in the blend and this increase is due to synergistic interactionsbetween the gums (Hernández et al., 2001; Lapasin & Pricl, 1995). Itwas reported that there are some proposed equations to quantifythe synergistic effect for the blended gums. In linear models,experimental viscosity is compared to estimated viscosity which isdefined with a linear combination with the taking into account ofthe relative proportions of the gums in the blends (Howell, 1994).Hernández et al. (2001) reported that the dispersion viscosity

Fig. 6. Measured and computed apparent viscosity values o

increases nonlinearly above a certain concentration value andbecause of that, nonlinear models can define the synergism betterthan linear ones. In the present study, linear and nonlinear fuzzymodels were compared for the estimation of apparent viscosity ofblends. Fuzzy models are nonlinear models and they are commonlyused in the modeling of the complex food structures because theyhave a nonlinear nature and these complex nonlinear systems fitwithin the realm of neuro-fuzzy techniques (Abu Ghoush,Samhouri, Al-Holy, & Herald, 2008). In many studies in the litera-ture, fuzzy models were used effectively for the estimation of in-terval values (Abu Ghoush et al., 2008; Karaman & Kayacier, 2011;Samhouri, Abu-Ghoush, Yaseen, & Herald, 2009; Toker, Dogan,Canıyılmaz, Ersöz, & Kaya, 2013). For the estimation of apparentviscosity values of gum blends, different fuzzy models were con-structed and evaluated their performances. Table 4 shows the

f gum mixtures using fuzzy model in validation period.

E. Cengiz et al. / Food Hydrocolloids 32 (2013) 453e462 461

model performance parameters of the constructed fuzzy models.Six different fuzzy models were developed for the each gum blendand their some performance criteria; coefficient of determination,root mean square error and mean absolute error were determined.The increase in number of membership function increased thecoefficient of determination and decreased the errors. Membershipfunction type for output was changed while the membershipfunction type for input was set to be triangular (trimf). It is clearlyseen that the linear membership function was determined to bemore effective compared to constant in the prediction of apparentviscosity for each blends. In Table 5, measured and estimatedapparent viscosity values using linear and nonlinear fuzzy modelfor each gum blendwere presented. The fuzzymodels showed goodestimation accuracy compared to linear models. The apparent vis-cosity values of samples were predicted to be very close tomeasured ones. For example, apparent viscosity of gum blendcontaining 0.4% alginate and 0.1% Gt was measured to be 62.1 mPa sat 50 s�1 and 25 �C hydration temperature. The apparent viscositywas predicted to be 55 and 63 mPa s at same conditions by linearand nonlinear fuzzy models, respectively. Similarly, apparent vis-cosity of gum blend containing 0.1% CMC and 0.4% Gt wasmeasuredto be 111 mPa s at 50 s�1 and 80 �C. It is predicted to be 79 and108mPa s by linear and nonlinear fuzzy models at same conditions.Fig. 6 illustrates the fuzzy model scattering plots. The fuzzy modelperformance in the estimation of apparent viscosity was found tobe very high. Samhouri et al. (2009) constructed fuzzy clusteringbased models for the surface interactions and emulsions of selectedwhey protein concentrate combined to i-carrageenan and gumarabic solutions and they conclude that the fuzzy model achievedaccuracies of 94%, 97%, 98%, and 94% for predicting emulsion ac-tivity index, emulsion stability index, surface tension, and interfa-cial tension, respectively. Karaman and Kayacier (2011) developed afuzzy model for the estimation of apparent viscosity of molassesand they reported that fuzzy models are very effective for theestimation of parameters of nonlinear complex food system. Inaddition, Toker et al. (2012) established a fuzzymodel to predict therheological parameters of the hot chocolate beverage based on theWHC of the gums and swelling power of the starch found in theformulation of the product. The constructed fuzzy models can beused effectively for the determination of apparent viscosity ofblended gums.

4. Conclusions

Gt is a good hydrocolloid source and it can be used for theproduction of gumwhich is alternative to the commonly used oneson industrial scale. Gt gum showed non Newtonian pseudoplasticbehavior as apparent viscosity decreased with the increase of shearrate. Gt showed synergistic interaction with selected some hydro-colloids depending on the sole gum concentration in the blends.The best synergism was observed between Gt and xanthan gumcompared to others due to the association of xanthan double he-licoidal structure with sequences of unsubstituted mannosyl resi-dues in the galactomannan based Gt gum compared to others.Hydration temperature affected the synergism and apparent vis-cosity values. Increase in hydration temperature provided a sig-nificant increase in apparent viscosity values because gooddissolution. Linear and nonlinear models were compared for theestimation of apparent viscosity of blends depending on thecomponent concentration and it was concluded that fuzzy modelswhich were used a nonlinear modeling techniques showed goodresults and high accuracy in the predicting the unmeasured ex-pected apparent viscosity with high coefficient of determination. Gtgum can ideally be used on industrial scale as a galactomannanbased hydrocolloid.

Acknowledgements

The authors would like to thank to Erciyes University ScientificResearch Project Unit for financial support of this Master Thesiswork with the project code of FBY09-1100.

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