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Modelling of methylcellulose thermogelation as a function of polymer concentration and dissolution media properties
LWT - Food Science and Technology 60 (2015) 811e816
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Modelling of methylcellulose thermogelation as a function of polymer concentration and dissolution media properties Cristina Alamprese*, Manuela Mariotti degli Studi di Milano, Via Celoria 2, 20133 Milano, Italy Department of Food, Environmental and Nutritional Sciences (DeFENS), Universita
a r t i c l e i n f o
a b s t r a c t
Article history: Received 23 April 2014 Received in revised form 28 October 2014 Accepted 31 October 2014 Available online 7 November 2014
A large number of factors can influence hydrocolloid properties, but little basic research has been performed on this topic, mainly evaluating one factor at a time. The aim of this work was to study the thermogelation of methylcellulose as a function of polymer concentration (1e3 g/100 g), and pH (4e10) and salt concentration (50e150 mmol/L) of the aqueous dissolution buffer. To simultaneously evaluate the effects of the different factors and of their interactions, a Box Behnken Design of Experiment was applied. Thermogelation was evaluated by means of fundamental and empirical rheological methods. Significant response surface models describing methylcellulose structuring properties as a function of the three considered factors were calculated. In particular, buffer pH and concentration seemed to mainly influence the fundamental rheological behavior of the methylcellulose systems, whereas variables evaluated at higher strains were especially affected by the polymer concentration. The salt-out effect of the phosphate salts used is also discussed. The obtained models represent a first step for a deeper knowledge of the molecular interactions in food systems. They could be exploited in the development of new foods, making easier the modulation of the structural and textural features of products. © 2014 Elsevier Ltd. All rights reserved.
Keywords: Methylcellulose thermogelation pH Salt concentration Design of experiment Rheology
1. Introduction Food companies are continuously searching for new nonconventional products for people having specific dietary preferences or restrictions (vegans, vegetarians, high cholesterol people, intolerant or allergic people, etc.). Generally, structure and texture are crucial aspects in developing these products, because the performances of traditional foods are difficult to achieve when some basic ingredients are replaced by substitution. To make up for the lack of conventional structuring ingredients (e.g. gluten proteins, sucrose, fats), hydrocolloids (non-starch polysaccharides) are usually added to control or minimize possible defects. Moreover, gums and stabilizers are incorporated into a range of diverse food formulations, for instance to offer resistance to undesired physical
Abbreviations: ANOVA, analysis of variance; BC, buffer concentration; DoE, Design of Experiment; F, firmness; FS, frequency sweep; G0 , storage or elastic modulus; G00 , loss or viscous modulus; G*, complex modulus; LOF, lack of fit; LSD, Fisher's Least Significant Difference; MC, methylcellulose; R2, determination coefficient; SS, strain sweep; Tgel, gelation point; TS, temperature sweep; tan d, damping factor; h*, complex viscosity. * Corresponding author. Tel.: þ39 0250319187; fax: þ39 0250319190. E-mail addresses: [email protected] (C. Alamprese), manuela. [email protected] (M. Mariotti). http://dx.doi.org/10.1016/j.lwt.2014.10.067 0023-6438/© 2014 Elsevier Ltd. All rights reserved.
processes such as crystallization, gravitational sedimentation and mechanical disaggregation, which might otherwise occur during distribution and storage. The addition of gums to food products very often changes the perceived character of foods, thus favoring or not consumer acceptance (Marcotte, Taherian Hoshahili, & Ramaswamy, 2001). Among hydrocolloids, methylcellulose (MC) is widely used in food products, due to its particular property of reversible thermal gelation: MC solutions gel when heated and the gels reliquefy when cooled (Kobayashi, Huang, & Lodge, 1999; Vigouret, Rinaudo, & res, 1996). One well-known application of this property, Desbrie along with MC film forming ability, is its use in batter formulas or as edible coating for moisture retention and oil reduction in fried foods (Albert & Mittal, 2002; Balasubramaniam, Chinnan, Mallikarjunan, & Phillips, 1997; Garcia, Ferrero, Bertola, Martino, & Zaritzkya, 2002; Holownia, Chinnan, Erickson, & Mallikarjunan, 2000; Primo-Martin et al., 2010; Sanz, Fernandez, Salvador, Munoz, & Fiszman, 2005). MC is also used in gluten-free bread or pasta to mimic the viscoelastic properties of gluten (Alamprese, Casiraghi, & Pagani, 2007; Mariotti, Lucisano, & Pagani, 2013; Onyango, Unbehend, & Lindhauer, 2009; Toufeili et al., 1994). Thermogelation of MC also makes it useful as a thickener in those sauces that require heating, as it prevents them from becoming
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fluid during that process, thus allowing the preservation of the expected consistency and appearance (Zecher & Van Coillie, 1992). Thermoreversible gelation of macromolecules in aqueous solutions has been attributed to the formation of a three-dimensional crosslinked structure. Since this sol-gel transformation is reversible within a given temperature range, it does not involve the making or breaking of any covalent bonds, and the physical crosslinks in the gel network structure are due to non-covalent interactions. Gelation of MC solution is primarily caused by the hydrophobic interaction between molecules containing methoxyl substitution. Owing to unfavorable contact with water, hydrophobic blocks associate, leading to crosslinking. The viscosity increases progressively with the formation of a three-dimensional network, res, Hirrien, & but these gels are completely reversible (Desbrie Rinaudo, 1998). Hydrocolloid properties are mainly determined by the shape of their molecules. The shapes are complex, because the polysaccharide molecules themselves are polymolecular and/or polydisperse, because polysaccharide molecules in solutions and gels are in a constant state of dynamic flux, and because segments of molecules may pass in and out of different physical states. The nature of the aqueous environment surrounding hydrocolloids also affects the conformations of the individual molecules. The amount of water present and the temperature of the environment, for instance, determine the mobility of polymer chain segments (Saha & Bhattacharya, 2010). In particular, structures of many hydrogels are sensitive to different environmental properties, such as temperature, solvent, coexisting solutes including ions, pH, electrical or magnetic field (Xu, Wang, Tam, & Li, 2004). Several studies have been carried out to quantify the rheological characteristics of MC in aqueous solutions (Bain et al., 2012; Bodvik res et al., 1998; Funami et al., 2007; Haque & et al., 2010; Desbrie res, Axelos, & Rinaudo, Morris, 1993; Hirrien, Chevillard, Desbrie 1998; Sarkar, 1995; Wang & Li, 2005; Wang, Li, Chen, & Yang, 2007; Wang, Li, Liu, Xu, & Liu, 2006; Xu & Li, 2005) or in food formulations (Balasubramaniam et al., 1997; Garcia et al., 2002; Holownia et al., 2000; Onyango et al., 2009; Primo-Martin et al., 2010; Sanz et al., 2005), but none of them systematically investigated the combined effects of more than two factors. On the contrary, a deeper characterization of the MC gelation properties as simultaneously affected by several factors is important to allow a more conscious choice for different end-use applications. In this context, the aim of this work was to methodically study the thermogelation process of MC in aqueous systems, as a function of three experimental factors: polymer concentration (1e3 g/ 100 g), pH (4e10) and salt concentration (50e150 mmol/L) of the dissolution buffer. To simultaneously evaluate the effects of the different factors and of their interactions, a Box Behnken Design of Experiment (DoE) was applied, and experimental results were analyzed by the response surface methodology.
L) according to the Box Behnken experimental design described at x 2.4. A purposely standardized hot/cold preparation technique was applied: MC powder was previously dispersed by gently mixing in 2/3 of the total buffer at 80 C and then stirred by an Ultra Turrax T25 (Janke & Kunkel, IKA Labortechnik, Staufen, Germany) at 9500 rpm for 2 min. Subsequently, the rest of the buffer - conditioned at 4 C - was added, and the dispersion was transferred in a refrigeration chamber (4 ± 2 C), where it was continuously mixed on a magnetic stirrer for 18 h to allow maximum hydration of MC molecules. Before analyses, MC dispersions were kept at 20 C for 30 min. 2.2. Empirical rheological properties Empirical rheological tests were carried out by using a 3365 Instron Universal Testing Machine (Instron Division of ITW Test and Measurement Italia S.r.l., Trezzano sul Naviglio, Italy) on 30 g samples poured into 45 mm diameter polythene hinged-lid containers and conditioned at 80 C for 30, 60, 90, and 120 min. Penetration tests were performed at a constant rate of 50 mm/min, using a 27 mm diameter plate connected to a 100 N load cell. Penetration was continued down to 25% of the initial height of the sample. Results represent gel firmness, calculated as the load (N) at 15% strain. Four measurements were carried out for each sampling time (n ¼ 4). 2.3. Fundamental rheological properties Fundamental rheological evaluations were performed by means of dynamic oscillatory tests, using a Physica MCR 300 Rheometer (Anton Paar GmbH, Graz, Austria), supported by the software Rheoplus/32 (v. 3.00, Physica Messtechnik GmbH, Ostfildern, Germany) and equipped with a 50 mm parallel plate geometry (PP50) gapped to 2 mm. In order to determine the linear viscoelastic region of the MC dispersions at 80 C, strain sweeps (SS) were run at a frequency of 1 Hz at a strain range of 0.01e100%. Mechanical spectra were evaluated by means of frequency sweeps (FS) performed at 80 C, over the range 0.1e10 Hz, at a constant strain of 0.1% chosen from the linear viscoelastic region of the samples. Before SS and FS tests at 80 C, samples were heated at a constant rate of 3 C/min under a strain of 0.1% and a frequency of 1 Hz. For the experimental design analysis, data from SS and FS curves were extrapolated at a strain of 0.1% and at a frequency of 1 Hz, respectively. The thermogelation process was studied carrying out temperature sweeps (TS) from 20 to 80 C, at a constant heating rate of 3 C/min, an oscillation frequency of 1 Hz and an applied strain of 0.1%. The gel point was taken as the temperature at which the crossover between storage (G0 ) and loss (G00 ) modulus occurred. All the analyses were performed in triplicate (n ¼ 3) on each sample.
2. Experimental section 2.4. Experimental design and data analysis 2.1. Materials and sample preparation Commercial grade MC (M0512) was purchased from SigmaeAldrich (St. Louis, MO, USA). According to the product specification, the average molecular weight was 88,000 g/mol, the viscosity of a 2 g/100 g aqueous solution was 4000 mPa s, the methoxy content ranged from 27.5 to 31.5%, and the degree of substitution was 1.5e1.9. Potassium salts for buffer preparation (K2HPO4 and KH2PO4) €n (Seelze, Germany). were obtained from Riedel-de Hae MC dispersions were prepared by varying MC concentration (1e3 g/100 g), pH (4e10) and buffer concentration (50e150 mmol/
To simultaneously evaluate the main and the interaction effects of hydrocolloid concentration and dissolution media properties (pH and salt concentration) on the MC thermogelation process, a threefactor Box-Behnken DoE was applied, with three replications of the central point. Box-Behnken is a rotatable DoE based on three levels of each factor, and it combines the mid-levels of some factors with the extreme levels of others. The combinations of only extreme levels are not included in the design. A total of 15 experiments were thus performed in a random order to avoid systematic biases and to minimize the effects of unexpected variability in the observed responses due to extraneous factors.
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Design data were analyzed by response surface regression for a second order polynomial model, according to the following equation (Montgomery, 2001):
y ¼ b0 þ b1 x1 þ b2 x2 þ b3 x3 þ b12 x1 x2 þ b13 x1 x3 þ b23 x2 x3 þ b11 x21 þ b22 x22 þ b33 x23 þ ε where: y is the value of the considered response variable; x1, x2 and x3 are the values of MC concentration, pH, and buffer concentration (BC), respectively; b0 is a constant value; b1, b2, and b3 are linear coefficients; b12, b13, and b23 are interaction coefficients; b11, b22 and b33 are quadratic coefficients; ε is the random error. In order to determine the significance of each coefficient, one way analysis of variance (ANOVA) was carried out. The Unscrambler 9.8 software (CAMO ASA, Oslo, Norway) was used for experimental design development and data analysis. Run order of the experimental design trials in the coded and actual factor levels is reported in Table 1. Empirical rheological properties were also analyzed by means of ANOVA with Fisher's Least Significant Difference (LSD) multiple comparison procedure (Statgraphics Plus 5.1, Statistical Graphics Corp., Herndon, VA, USA) to discriminate among the averaged values obtained at the different gelation time. 3. Results and discussion 3.1. Analysis of effects To carry out DoE analysis, besides the gel firmness during gelation time (F 30 min, F 60 min, F 90 min, and F 180 min) and the gel point obtained by the temperature sweep curves (Tgel), some properties related to the fundamental rheological behavior of the MC systems were also determined. In particular, the elastic modulus (G0 ), viscous modulus (G00 ), damping factor (tan d), complex modulus (G*), and complex viscosity (h*) values were extrapolated from the SS and FS curves at 80 C, at 0.1% strain and 1 Hz frequency, respectively. Thus, 15 response variables were investigated in total. The normal distribution plots of the response variables were then studied. Fundamental rheological data, with the exception of the damping factor values, required a logarithmic transformation in order to approximate normal distributions. A preliminary examination of main effects and linear interactions between pairs of factors was carried out with the Table 1 Run order of the experimental design trials in the coded and actual factor levels. Run
Cube011 Cube010 Cube001 Cube008 Cube004 Cube009 Cube005 Cent-a Cube002 Cent-b Cube007 Cent-c Cube003 Cube012 Cube006
Coded factors
Actual factors
MC
pH
BC
MC
pH
BC
0 0 1 þ1 þ1 0 1 0 þ1 0 1 0 1 0 þ1
1 þ1 1 0 þ1 1 0 0 1 0 0 0 þ1 þ1 0
þ1 1 0 þ1 0 1 1 0 0 0 þ1 0 0 þ1 1
2 2 1 3 3 2 1 2 3 2 1 2 1 2 3
4 10 4 7 10 4 7 7 4 7 7 7 10 10 7
150 50 100 150 100 50 50 100 100 100 150 100 100 150 50
MC, methylcellulose concentration (g/100 g); pH, buffer pH; BC, buffer concentration (mmol/L).
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analysis of effects (Table 2). Significance of effects was established based on the experimental errors calculated considering the central point replicates. The high number of significant effects demonstrated a high influence of the three factors studied on the thermogelation behavior of MC dispersions, as well as a good repeatability in both the preparation and the evaluation of the central points. Besides the significant main effects, also some linear interactions were significant, thus proving that the influence of one factor on a response variable is often not independent from the level of the other factors. From the analysis of effects it was possible to notice that MC concentration had a direct influence on almost all the investigated response variables, whereas pH and BC indirectly affected only the fundamental rheological properties of MC dispersions. None of the investigated factors affected gel firmness after 30 min, probably because of the still ongoing evolution of the gel structure. 3.2. Response surfaces After the analysis of effects, response surface methodology was applied to the experimental data in order to obtain, for each response variable, a model able to plot that response, in the best possible way, as a function of the three considered factors. The significance of each model and of each coefficient within the model was determined using ANOVA. For various response variables, some coefficients came out to be not significant, thus the model described at x 2.4 was accordingly simplified, considering only the significant factors. Table 3 shows the coded coefficients of the fitted models, with the related determination coefficient (R2) and lack of fit (LOF) values. First of all it can be noticed that almost all the fitted models were highly significant (P < 0.01), with no significant LOF values (P > 0.05). LOF tests the error in response prediction, thus a P value higher than 0.05 means that the calculated model describes the true shape of the response surface. A significant LOF was found only for the model concerning the firmness of MC gels after 60 min at 80 C (P < 0.05). This was probably due to persistent system instability during gel formation. In fact, for gel firmness after 30 min, it was not possible to calculate a significant model, because the structure was still in evolution and not yet stable. Actually, as already reported by Vigouret et al. (1996), in a dilute regime (MC concentration < 3.9 g/100 mL) aggregation is visible for temperature higher than 35 C and it is a time-dependent phenomenon. Kinetics of gel formation depends on polymer concentration: at a given temperature, the equilibrium is reached in longer times when polymeric concentration is smaller. In order to confirm this hypothesis, results related to the empirical rheological behavior of MC dispersions were analyzed by means of ANOVA with Bonferroni's multiple comparison procedure (P 0.05), in order to discriminate among the averaged values of the same sample obtained at different gelation times (Table 4). As it can be seen, at the beginning of the 80 C storage period, there was a steep increment of gel firmness, and no definite structure properties could be outlined. From 90 min on, the majority of the systems reached stability, making possible a precise modeling of gel firmness. Simple models were found for this property, consisting of the main effects (linear effects) and at most of one linear interaction effect (Table 3). The only significant experimental factor, with a high and direct influence on gel firmness, was the MC concentration (b1 coefficient). The importance of this factor was evidenced also by the slope of the response surface related to the gel firmness after 180 min at 80 C (Fig. 1). In fact, comparing samples obtained with different MC concentrations and the same environmental conditions, it was possible to highlight the high influence of the hydrocolloid concentration on gel firmness. For instance, at pH 4 and BC 100 mM,
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Table 2 Results of the analysis of effects. Penetration test
MC pH BC MC*pH MC*BC pH*BC
TS
SS
F 30 min
F 60 min
F 90 min
F 180 min
Tgel
G0
G00
Tan d
G*
h*
FS G0
G00
Tan d
G*
h*
ns ns ns ns ns ns
þþþ ns ns ns ns þ
þþ ns e ns e ns
þ ns ns ns e ns
þ e e ns ns ns
ns þ ns ns
þ ns ns ns ns ns
ns ns ns ns ns ns
þ þ ns ns
þ þ ns ns
þ þ þ ns
þ e e þ þ ns
ns ns ns ns ns ns
þ þ þ ns
þ þ þ ns
MC, methylcellulose concentration; pH, buffer pH; BC, buffer concentration; TS, temperature sweep test; SS, strain sweep test; FS, frequency sweep test; F, firmness; Tgel, gelation point; G0 , elastic modulus; G00 , viscous modulus; tan d, damping factor; G*, complex modulus; h*, complex viscosity; ns, not significant; þ/, P 0.05; þ þ/ , P 0.01; þ þ þ/ , P 0.001.
Table 3 Coded coefficients, determination coefficient (R2) and lack of fit (LOF) values of the fitted models.
b0 F 60 min F 90 min F 180 min Tgel G0 SS G00 SS Tan d SS G* SS h* SS G0 FS G00 FS Tan d FS G* FS h* FS
b1 *
9.053 9.693ns 10.349ns 45.700*** 1.893*** 1.387*** 0.290* 1.909*** 1.110** 2.024** 1.381*** 0.237* 2.037*** 1.205*
b2 ***
b3 ns
0.145 0.293ns 0.020ns 0.846** 0.116** 0.055ns 0.013ns 0.116** 0.116** 0.108* 0.052ns 0.009ns 0.107* 0.107*
6.197 5.811*** 6.371** 3.950*** 0.114ns 0.314** 0.043ns 0.116ns 0.116ns 0.191ns 0.343** 0.034ns 0.193ns 0.193ns
b12 ns
0.006 0.042ns 0.039ns 0.089*** 0.006** 0.002ns 0.001ns 0.006** 0.006** 0.007* 0.003ns 0.001ns 0.007* 0.007*
b13
e e e 1.200* 0.191* e e 0.191* 0.191* 0.228* e e 0.227* 0.227*
b23
e 2.393* e 0.343ns e e e e e e e 0.041* e e
ns
0.820 e e 1.443* e e e e e e e e e e
b11
b22
b33
R2
LOF
e e e 1.393* e e 0.028ns e e e e e e e
e e e 0.321ns 0.228** e 0.052* 0.224** 0.224** 0.268*
e e e 0.993ns 0.218** e 0.062* 0.213* 0.213* e e e e e
0.843*** 0.755** 0.553* 0.976** 0.891** 0.634** 0.753* 0.891** 0.891** 0.786** 0.690** 0.804** 0.787** 0.787**
0.035* 0.056 0.129 0.515 0.099 0.219 0.988 0.077 0.081 0.055 0.137 0.381 0.056 0.056
0.071*** 0.262* 0.262*
F, firmness; Tgel, gelation point; G0 , elastic modulus; G00 , viscous modulus; tan d, damping factor; G*, complex modulus; h*, complex viscosity; SS, strain sweep; FS, frequency sweep; ns, not significant; *, P 0.05; **, P 0.01; ***, P 0.001.
the sample Cube001 (1 g/100 g MC) showed firmness values after 90 and 180 min at 80 C that were 23% of those observed for the sample Cube002 (3 g/100 g MC). A complete quadratic model was calculated for the gelation temperature (Tgel), with a very high significance (P < 0.001 or P < 0.01) of the three linear terms and a low (P < 0.05) or null significance of the other terms. The highest effect was exerted by MC concentration, as highlighted by the highest b coefficient, followed by pH and BC, which were indirectly correlated to the gel point (Fig. 2).
Table 4 Firmness (N) of methylcellulose gels during gelation at 80 C. Run
Firmness 30 min
Cube001 Cube002 Cube003 Cube004 Cube005 Cube006 Cube007 Cube008 Cube009 Cube010 Cube011 Cube012 Cent-a Cent-b Cent-c
0.04 9.06 1.56 0.90 1.87 2.91 1.22 3.06 2.53 0.04 0.05 5.42 3.92 5.14 6.85
± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.01a 0.82a 0.11a 0.03a 0.09a 0.11a 0.24a 0.19a 0.23a 0.01a 0.01a 0.38a 0.10a 0.25a 0.43a
Firmness 60 min 2.22 13.92 2.72 14.14 3.66 19.08 2.18 13.22 8.80 3.83 8.35 9.12 11.54 11.00 12.02
± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.11b 0.98b 0.08b 1.35b 0.18b 0.38b 0.15b 0.62c 0.45b 0.56ab 1.11b 0.17c 0.33c 0.61b 0.41b
Firmness 90 min 3.28 14.19 3.28 16.33 4.45 24.09 2.32 5.21 10.01 5.61 12.22 7.44 11.53 12.07 13.36
± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.22bc 1.73b 0.06d 0.15b 0.06c 0.35c 0.21bc 0.83b 0.31c 0.34b 1.26c 0.49b 0.20c 0.53c 0.57c
As an example, the temperature sweep curves reported in Fig. 3 show the direct effect of MC concentration and the inverse effect of pH and BC on the gel point (defined as the temperature at which the crossover between G0 and G00 occurs): when the MC concentration increased, the gelation temperature was higher (Fig. 3a), whereas, with the increase of pH or BC, the gel point occurred at lower temperatures (Fig. 3b and c). The effect of the hydrocolloid concentration on the gel point of MC solutions is probably related to the amount of energy necessary to cause the sol-gel transition, which is a linear function of polymer concentration (Wang & Li, 2005). The effect of BC on the gelation temperature is in agreement with previous findings by Xu et al. (2004), which demonstrated the salt-assisting and salt-suppressing features of different salts on the sol-gel transition of aqueous MC solutions. In particular, they
Firmness 180 min 3.57 15.42 3.09 21.81 4.75 24.16 2.57 3.56 9.92 5.25 12.13 10.42 10.86 12.70 15.02
± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
1.00c 0.52b 0.11c 2.42c 0.08d 0.87c 0.02c 0.51a 0.23c 0.48b 0.77c 1.11d 0.40b 0.80c 0.70d
aed Data followed by different letters in the same row are significantly different (P < 0.05; n ¼ 4).
Fig. 1. Response surface of methylcellulose (MC) gel firmness after 180 min at 80 C (ionic strength, 100 mmol/L).
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Fig. 2. Response surface of gelation temperature ( C) of methylcellulose (MC) systems (pH, 7).
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observed that the phosphate ion has a strong salting out effect, which results in a decreasing of the temperature transition of the MC solution. The effect is due to ion hydration in the aqueous solution and to the strength of interactions between ions and water molecules. Thus ions tend to compete with MC chains for water molecules, succeeding in attracting more water molecules surrounding them. This competition causes the decrease of MC solubility in water. As a result, at the same temperature, there are more hydrophobic aggregates of MC in a MC solution containing salts than in a MC solution not containing salts, thus accelerating the formation of the MC gel. The higher the salt concentration, the lower the transition temperature. To the best of our knowledge, the influence of pH on the gel point of MC solutions has not been studied so far. However, considering the use of phosphate salts in this study, it is reasonable that at higher pH values a higher dissociation degree occurred, thus
Fig. 3. Temperature sweep curves of some methylcellulose systems. Thick lines, G0 ; thin lines, G00 ; MC, methylcellulose concentration; BC, buffer concentration; Tgel, gelation temperature.
Fig. 4. Response surface of (a) logG0 (Pa; MC concentration, 2 g/100 g) and (b) log G00 (Pa; buffer concentration, 100 mmol/L) values obtained by FS curves of methylcellulose (MC) systems at 80 C.
Fig. 5. Strain sweep (a) and frequency sweep (b) curves of some methylcellulose (MC) dispersions at 80 C. MC, methylcellulose concentration; BC, buffer concentration. In (b), full symbols refer to G0 values, empty symbols to G00 values.
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increasing the ionic strength of the dissolving medium. This resulted in a higher phosphate ion concentration, determining a lower sol-gel transition temperature, as above explained. As regards the response variables extrapolated from the fundamental rheology curves, models related to G0 , G* and h* were very similar, both for SS and FS tests. These results were expected, because the rheological behavior of MC gels at 80 C was characterized by the predominance of the elastic modulus against the viscous one, typical of a solid-like material. Quadratic incomplete models were calculated, in which pH and BC had an indirect significant effect, whereas the MC concentration did not significantly influence these rheological variables. In particular, the highest absolute values in pH b coefficients demonstrated a higher influence of this factor in comparison with that of BC. In the case of G00 values calculated from the SS and FS curves at 80 C, linear models were obtained and only MC concentration had a significant and direct effect. Thus, it could be concluded that the biopolymer concentration governed the viscous behavior of the system, whereas the environmental conditions (pH and BC) had a major effect on the solid-like component, probably influencing the amount and the strength of the hydrophobic interactions among MC molecules. As an example, response surfaces related to G0 and G00 values obtained from FS tests are reported in Fig. 4. Models for tan d showed only some significant quadratic terms, with low values of b coefficients. The effects of pH and BC on the SS and FS curves can be observed in Fig. 5, where the behavior of some samples at the same MC concentration is reported. In particular, in Fig. 5a a reduction of G* and of the linear viscoelasticity region with an increase of BC were evident, but the increase in pH had a definitely higher effect, according to the significant values of the linear b12 (P < 0.05) and quadratic b22 (P < 0.01) interaction terms (Table 3). As expected, FS curves (Fig. 5b) were typical of strong gels, with G0 always higher than G00 and not dependent on the frequency value (Steffe, 1996, chap. 5). The effect of BC increase was clear on G0 and not observable on G00 . In fact, in the model related to G00 , the b3 coefficient of BC was not significant (P > 0.05) (Table 3). The decreasing of G0 with an increase in pH and BC could be ascribed to the salting out effect of phosphate buffer, as already explained. The accelerated structure formation could be responsible for a more disordered and porous matrix. In fact, Bain et al. (2012) observed a more porous structure and lower G0 values in those hydrogel samples made with MC and a mixture of citrate and tartrate salts, which have a salt-out effects, in comparison with gels containing only MC. 4. Conclusions The linear and interactions effects of polymer concentration, pH and salt concentration on the thermogelation properties of methylcellulose dispersions were demonstrated. Significant response surface models were able to describe the methylcellulose structuring properties as a function of three considered experimental factors. In particular, pH and buffer concentration seemed to influence mainly the fundamental rheological behavior of the methylcellulose systems (determined under low strain), whereas those variables evaluated at higher strains were especially affected by the polymer concentration. In particular, the salting out effect of the phosphate salts used dramatically affected the structural properties of methylcellulose gels. The obtained models represent a first step for a deeper knowledge of the molecular interactions in food systems. They should be extended to include other factors, such as protein, lipid or sucrose concentration. Then such models might prove useful in development of new foods, making easier the modulation of the structural and textural features of products as a function of recipes, technological processes, and consumer requirements.
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Aggregation and network formation of aqueous methylcellulose and hydroxypropylmethylcellulose solutions. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 354, 162e171. res, J., Hirrien, M., & Rinaudo, M. (1998). A calorimetric study of methylDesbrie cellulose gelation. Carbohydrate Polymers, 37, 145e152. Funami, T., Kataoka, Y., Hiroe, M., Asai, I., Takahashi, R., & Nishinari, K. (2007). Thermal aggregation of methylcellulose with different molecular weights. Food Hydrocolloids, 21, 46e58. Garcia, M. A., Ferrero, C., Bertola, N., Martino, M., & Zaritzkya, N. (2002). Edible coatings from cellulose derivatives to reduce oil uptake in fried products. Innovative Food Science and Emerging Technologies, 3, 391e397. Haque, A., & Morris, E. R. (1993). Thermogelation of methylcellulose. Part I: molecular structures and processes. Carbohydrate Polymers, 22, 161e173. res, J., Axelos, M. A. V., & Rinaudo, M. (1998). Hirrien, M., Chevillard, C., Desbrie Thermogelation of methylcelluloses: new evidence for understanding the gelation mechanism. Polymer, 39, 6251e6259. Holownia, K. I., Chinnan, M. S., Erickson, M. C., & Mallikarjunan, P. (2000). Quality evaluation of edible film-coated chicken strips and frying oils. Journal of Food Science, 65, 1087e1090. Kobayashi, K., Huang, C., & Lodge, T. P. (1999). Thermoreversible gelation of aqueous methylcellulose solutions. Macromolecules, 32, 7070e7077. Marcotte, M., Taherian Hoshahili, A. R., & Ramaswamy, H. S. (2001). Rheological properties of selected hydrocolloids as a function of concentration and temperature. Food Research International, 34, 695e703. Mariotti, M., Lucisano, M., & Pagani, M. A. (2013). The role of buckwheat and HPMC on the breadmaking properties of some commercial gluten-free bread mixtures. Food Hydrocolloids, 30, 393e400. Montgomery, D. G. (2001). Design and analysis of experiments (5th ed.). New York: John Wiley and Sons. Onyango, C., Unbehend, G., & Lindhauer, M. G. (2009). Effect of cellulose-derivatives and emulsifiers on creep-recovery and crumb properties of gluten-free bread prepared from sorghum and gelatinised cassava starch. Food Research International, 42, 949e955. Primo-Martin, C., Sanz, T., Steringa, D. W., Salvador, A., Fiszman, S. M., & vanVliet, T. (2010). Performance of cellulose derivatives in deep-fried battered snacks: oil barrier and crispy properties. Food Hydrocolloids, 24, 702e708. Saha, D., & Bhattacharya, S. (2010). Hydrocolloids as thickening and gelling agents in food: a critical review. Journal of Food Science and Technology, 47, 587e597. Sanz, T., Fernandez, M. A., Salvador, A., Munoz, J., & Fiszman, S. M. (2005). Thermogelation properties of methylcellulose (MC) and their effect on a batter formula. Food Hydrocolloids, 19, 141e147. Sarkar, N. (1995). Kinetics of thermal gelation of methylcellulose and hydroxypropylmethylcellulose in aqueous solutions. Carbohydrate Polymers, 26, 195e203. Steffe, J. F. (1996). Rheological methods in food process engineering (2nd ed.). East Lansing: Freeman Press. Toufeili, I., Dagher, S., Shadarevian, S., Noureddine, A., Sarakbi, M., & Farran, M. T. (1994). Formulation of gluten-free pocket-type flat breads: optimisation of methylcellulose, gum Arabic, and egg albumen levels by response surface methodology. Cereal Chemistry, 71, 594e601. res, J. (1996). Thermogelation of methylcelluVigouret, M., Rinaudo, M., & Desbrie lose in aqueous solutions. Journal de Chimie Physique et de Physico-Chimie Biologique, 93, 858e869. Wang, Q., & Li, L. (2005). Effects of molecular weight on thermoreversible gelation and gel elasticity of methylcellulose in aqueous solution. Carbohydrate Polymers, 62, 232e238. Wang, Q., Li, L., Chen, G., & Yang, Y. (2007). Effects of magnetic field on the solgel transition of methylcellulose in water. Carbohydrate Polymers, 70, 345e349. Wang, Q., Li, L., Liu, E., Xu, Y., & Liu, J. (2006). Effects of SDS on the sol-gel transition of methylcellulose in water. Polymer, 47, 1372e1378. Xu, Y., & Li, L. (2005). Thermoreversible and salt-sensitive turbidity of methylcellulose in aqueous solution. Polymer, 46, 7410e7417. Xu, Y., Wang, C., Tam, K. C., & Li, L. (2004). Salt-assisted and salt-suppressed sol-gel transitions of methylcellulose in water. Langmuir, 20, 646e652. Zecher, D., & Van Coillie, R. (1992). Cellulose derivatives. In A. Imeson (Ed.), Thickening and gelling agents for food (pp. 40e65). Glasgow: Blackie.
Contents lists available at ScienceDirect
LWT - Food Science and Technology journal homepage: www.elsevier.com/locate/lwt
Modelling of methylcellulose thermogelation as a function of polymer concentration and dissolution media properties Cristina Alamprese*, Manuela Mariotti degli Studi di Milano, Via Celoria 2, 20133 Milano, Italy Department of Food, Environmental and Nutritional Sciences (DeFENS), Universita
a r t i c l e i n f o
a b s t r a c t
Article history: Received 23 April 2014 Received in revised form 28 October 2014 Accepted 31 October 2014 Available online 7 November 2014
A large number of factors can influence hydrocolloid properties, but little basic research has been performed on this topic, mainly evaluating one factor at a time. The aim of this work was to study the thermogelation of methylcellulose as a function of polymer concentration (1e3 g/100 g), and pH (4e10) and salt concentration (50e150 mmol/L) of the aqueous dissolution buffer. To simultaneously evaluate the effects of the different factors and of their interactions, a Box Behnken Design of Experiment was applied. Thermogelation was evaluated by means of fundamental and empirical rheological methods. Significant response surface models describing methylcellulose structuring properties as a function of the three considered factors were calculated. In particular, buffer pH and concentration seemed to mainly influence the fundamental rheological behavior of the methylcellulose systems, whereas variables evaluated at higher strains were especially affected by the polymer concentration. The salt-out effect of the phosphate salts used is also discussed. The obtained models represent a first step for a deeper knowledge of the molecular interactions in food systems. They could be exploited in the development of new foods, making easier the modulation of the structural and textural features of products. © 2014 Elsevier Ltd. All rights reserved.
Keywords: Methylcellulose thermogelation pH Salt concentration Design of experiment Rheology
1. Introduction Food companies are continuously searching for new nonconventional products for people having specific dietary preferences or restrictions (vegans, vegetarians, high cholesterol people, intolerant or allergic people, etc.). Generally, structure and texture are crucial aspects in developing these products, because the performances of traditional foods are difficult to achieve when some basic ingredients are replaced by substitution. To make up for the lack of conventional structuring ingredients (e.g. gluten proteins, sucrose, fats), hydrocolloids (non-starch polysaccharides) are usually added to control or minimize possible defects. Moreover, gums and stabilizers are incorporated into a range of diverse food formulations, for instance to offer resistance to undesired physical
Abbreviations: ANOVA, analysis of variance; BC, buffer concentration; DoE, Design of Experiment; F, firmness; FS, frequency sweep; G0 , storage or elastic modulus; G00 , loss or viscous modulus; G*, complex modulus; LOF, lack of fit; LSD, Fisher's Least Significant Difference; MC, methylcellulose; R2, determination coefficient; SS, strain sweep; Tgel, gelation point; TS, temperature sweep; tan d, damping factor; h*, complex viscosity. * Corresponding author. Tel.: þ39 0250319187; fax: þ39 0250319190. E-mail addresses: [email protected] (C. Alamprese), manuela. [email protected] (M. Mariotti). http://dx.doi.org/10.1016/j.lwt.2014.10.067 0023-6438/© 2014 Elsevier Ltd. All rights reserved.
processes such as crystallization, gravitational sedimentation and mechanical disaggregation, which might otherwise occur during distribution and storage. The addition of gums to food products very often changes the perceived character of foods, thus favoring or not consumer acceptance (Marcotte, Taherian Hoshahili, & Ramaswamy, 2001). Among hydrocolloids, methylcellulose (MC) is widely used in food products, due to its particular property of reversible thermal gelation: MC solutions gel when heated and the gels reliquefy when cooled (Kobayashi, Huang, & Lodge, 1999; Vigouret, Rinaudo, & res, 1996). One well-known application of this property, Desbrie along with MC film forming ability, is its use in batter formulas or as edible coating for moisture retention and oil reduction in fried foods (Albert & Mittal, 2002; Balasubramaniam, Chinnan, Mallikarjunan, & Phillips, 1997; Garcia, Ferrero, Bertola, Martino, & Zaritzkya, 2002; Holownia, Chinnan, Erickson, & Mallikarjunan, 2000; Primo-Martin et al., 2010; Sanz, Fernandez, Salvador, Munoz, & Fiszman, 2005). MC is also used in gluten-free bread or pasta to mimic the viscoelastic properties of gluten (Alamprese, Casiraghi, & Pagani, 2007; Mariotti, Lucisano, & Pagani, 2013; Onyango, Unbehend, & Lindhauer, 2009; Toufeili et al., 1994). Thermogelation of MC also makes it useful as a thickener in those sauces that require heating, as it prevents them from becoming
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fluid during that process, thus allowing the preservation of the expected consistency and appearance (Zecher & Van Coillie, 1992). Thermoreversible gelation of macromolecules in aqueous solutions has been attributed to the formation of a three-dimensional crosslinked structure. Since this sol-gel transformation is reversible within a given temperature range, it does not involve the making or breaking of any covalent bonds, and the physical crosslinks in the gel network structure are due to non-covalent interactions. Gelation of MC solution is primarily caused by the hydrophobic interaction between molecules containing methoxyl substitution. Owing to unfavorable contact with water, hydrophobic blocks associate, leading to crosslinking. The viscosity increases progressively with the formation of a three-dimensional network, res, Hirrien, & but these gels are completely reversible (Desbrie Rinaudo, 1998). Hydrocolloid properties are mainly determined by the shape of their molecules. The shapes are complex, because the polysaccharide molecules themselves are polymolecular and/or polydisperse, because polysaccharide molecules in solutions and gels are in a constant state of dynamic flux, and because segments of molecules may pass in and out of different physical states. The nature of the aqueous environment surrounding hydrocolloids also affects the conformations of the individual molecules. The amount of water present and the temperature of the environment, for instance, determine the mobility of polymer chain segments (Saha & Bhattacharya, 2010). In particular, structures of many hydrogels are sensitive to different environmental properties, such as temperature, solvent, coexisting solutes including ions, pH, electrical or magnetic field (Xu, Wang, Tam, & Li, 2004). Several studies have been carried out to quantify the rheological characteristics of MC in aqueous solutions (Bain et al., 2012; Bodvik res et al., 1998; Funami et al., 2007; Haque & et al., 2010; Desbrie res, Axelos, & Rinaudo, Morris, 1993; Hirrien, Chevillard, Desbrie 1998; Sarkar, 1995; Wang & Li, 2005; Wang, Li, Chen, & Yang, 2007; Wang, Li, Liu, Xu, & Liu, 2006; Xu & Li, 2005) or in food formulations (Balasubramaniam et al., 1997; Garcia et al., 2002; Holownia et al., 2000; Onyango et al., 2009; Primo-Martin et al., 2010; Sanz et al., 2005), but none of them systematically investigated the combined effects of more than two factors. On the contrary, a deeper characterization of the MC gelation properties as simultaneously affected by several factors is important to allow a more conscious choice for different end-use applications. In this context, the aim of this work was to methodically study the thermogelation process of MC in aqueous systems, as a function of three experimental factors: polymer concentration (1e3 g/ 100 g), pH (4e10) and salt concentration (50e150 mmol/L) of the dissolution buffer. To simultaneously evaluate the effects of the different factors and of their interactions, a Box Behnken Design of Experiment (DoE) was applied, and experimental results were analyzed by the response surface methodology.
L) according to the Box Behnken experimental design described at x 2.4. A purposely standardized hot/cold preparation technique was applied: MC powder was previously dispersed by gently mixing in 2/3 of the total buffer at 80 C and then stirred by an Ultra Turrax T25 (Janke & Kunkel, IKA Labortechnik, Staufen, Germany) at 9500 rpm for 2 min. Subsequently, the rest of the buffer - conditioned at 4 C - was added, and the dispersion was transferred in a refrigeration chamber (4 ± 2 C), where it was continuously mixed on a magnetic stirrer for 18 h to allow maximum hydration of MC molecules. Before analyses, MC dispersions were kept at 20 C for 30 min. 2.2. Empirical rheological properties Empirical rheological tests were carried out by using a 3365 Instron Universal Testing Machine (Instron Division of ITW Test and Measurement Italia S.r.l., Trezzano sul Naviglio, Italy) on 30 g samples poured into 45 mm diameter polythene hinged-lid containers and conditioned at 80 C for 30, 60, 90, and 120 min. Penetration tests were performed at a constant rate of 50 mm/min, using a 27 mm diameter plate connected to a 100 N load cell. Penetration was continued down to 25% of the initial height of the sample. Results represent gel firmness, calculated as the load (N) at 15% strain. Four measurements were carried out for each sampling time (n ¼ 4). 2.3. Fundamental rheological properties Fundamental rheological evaluations were performed by means of dynamic oscillatory tests, using a Physica MCR 300 Rheometer (Anton Paar GmbH, Graz, Austria), supported by the software Rheoplus/32 (v. 3.00, Physica Messtechnik GmbH, Ostfildern, Germany) and equipped with a 50 mm parallel plate geometry (PP50) gapped to 2 mm. In order to determine the linear viscoelastic region of the MC dispersions at 80 C, strain sweeps (SS) were run at a frequency of 1 Hz at a strain range of 0.01e100%. Mechanical spectra were evaluated by means of frequency sweeps (FS) performed at 80 C, over the range 0.1e10 Hz, at a constant strain of 0.1% chosen from the linear viscoelastic region of the samples. Before SS and FS tests at 80 C, samples were heated at a constant rate of 3 C/min under a strain of 0.1% and a frequency of 1 Hz. For the experimental design analysis, data from SS and FS curves were extrapolated at a strain of 0.1% and at a frequency of 1 Hz, respectively. The thermogelation process was studied carrying out temperature sweeps (TS) from 20 to 80 C, at a constant heating rate of 3 C/min, an oscillation frequency of 1 Hz and an applied strain of 0.1%. The gel point was taken as the temperature at which the crossover between storage (G0 ) and loss (G00 ) modulus occurred. All the analyses were performed in triplicate (n ¼ 3) on each sample.
2. Experimental section 2.4. Experimental design and data analysis 2.1. Materials and sample preparation Commercial grade MC (M0512) was purchased from SigmaeAldrich (St. Louis, MO, USA). According to the product specification, the average molecular weight was 88,000 g/mol, the viscosity of a 2 g/100 g aqueous solution was 4000 mPa s, the methoxy content ranged from 27.5 to 31.5%, and the degree of substitution was 1.5e1.9. Potassium salts for buffer preparation (K2HPO4 and KH2PO4) €n (Seelze, Germany). were obtained from Riedel-de Hae MC dispersions were prepared by varying MC concentration (1e3 g/100 g), pH (4e10) and buffer concentration (50e150 mmol/
To simultaneously evaluate the main and the interaction effects of hydrocolloid concentration and dissolution media properties (pH and salt concentration) on the MC thermogelation process, a threefactor Box-Behnken DoE was applied, with three replications of the central point. Box-Behnken is a rotatable DoE based on three levels of each factor, and it combines the mid-levels of some factors with the extreme levels of others. The combinations of only extreme levels are not included in the design. A total of 15 experiments were thus performed in a random order to avoid systematic biases and to minimize the effects of unexpected variability in the observed responses due to extraneous factors.
C. Alamprese, M. Mariotti / LWT - Food Science and Technology 60 (2015) 811e816
Design data were analyzed by response surface regression for a second order polynomial model, according to the following equation (Montgomery, 2001):
y ¼ b0 þ b1 x1 þ b2 x2 þ b3 x3 þ b12 x1 x2 þ b13 x1 x3 þ b23 x2 x3 þ b11 x21 þ b22 x22 þ b33 x23 þ ε where: y is the value of the considered response variable; x1, x2 and x3 are the values of MC concentration, pH, and buffer concentration (BC), respectively; b0 is a constant value; b1, b2, and b3 are linear coefficients; b12, b13, and b23 are interaction coefficients; b11, b22 and b33 are quadratic coefficients; ε is the random error. In order to determine the significance of each coefficient, one way analysis of variance (ANOVA) was carried out. The Unscrambler 9.8 software (CAMO ASA, Oslo, Norway) was used for experimental design development and data analysis. Run order of the experimental design trials in the coded and actual factor levels is reported in Table 1. Empirical rheological properties were also analyzed by means of ANOVA with Fisher's Least Significant Difference (LSD) multiple comparison procedure (Statgraphics Plus 5.1, Statistical Graphics Corp., Herndon, VA, USA) to discriminate among the averaged values obtained at the different gelation time. 3. Results and discussion 3.1. Analysis of effects To carry out DoE analysis, besides the gel firmness during gelation time (F 30 min, F 60 min, F 90 min, and F 180 min) and the gel point obtained by the temperature sweep curves (Tgel), some properties related to the fundamental rheological behavior of the MC systems were also determined. In particular, the elastic modulus (G0 ), viscous modulus (G00 ), damping factor (tan d), complex modulus (G*), and complex viscosity (h*) values were extrapolated from the SS and FS curves at 80 C, at 0.1% strain and 1 Hz frequency, respectively. Thus, 15 response variables were investigated in total. The normal distribution plots of the response variables were then studied. Fundamental rheological data, with the exception of the damping factor values, required a logarithmic transformation in order to approximate normal distributions. A preliminary examination of main effects and linear interactions between pairs of factors was carried out with the Table 1 Run order of the experimental design trials in the coded and actual factor levels. Run
Cube011 Cube010 Cube001 Cube008 Cube004 Cube009 Cube005 Cent-a Cube002 Cent-b Cube007 Cent-c Cube003 Cube012 Cube006
Coded factors
Actual factors
MC
pH
BC
MC
pH
BC
0 0 1 þ1 þ1 0 1 0 þ1 0 1 0 1 0 þ1
1 þ1 1 0 þ1 1 0 0 1 0 0 0 þ1 þ1 0
þ1 1 0 þ1 0 1 1 0 0 0 þ1 0 0 þ1 1
2 2 1 3 3 2 1 2 3 2 1 2 1 2 3
4 10 4 7 10 4 7 7 4 7 7 7 10 10 7
150 50 100 150 100 50 50 100 100 100 150 100 100 150 50
MC, methylcellulose concentration (g/100 g); pH, buffer pH; BC, buffer concentration (mmol/L).
813
analysis of effects (Table 2). Significance of effects was established based on the experimental errors calculated considering the central point replicates. The high number of significant effects demonstrated a high influence of the three factors studied on the thermogelation behavior of MC dispersions, as well as a good repeatability in both the preparation and the evaluation of the central points. Besides the significant main effects, also some linear interactions were significant, thus proving that the influence of one factor on a response variable is often not independent from the level of the other factors. From the analysis of effects it was possible to notice that MC concentration had a direct influence on almost all the investigated response variables, whereas pH and BC indirectly affected only the fundamental rheological properties of MC dispersions. None of the investigated factors affected gel firmness after 30 min, probably because of the still ongoing evolution of the gel structure. 3.2. Response surfaces After the analysis of effects, response surface methodology was applied to the experimental data in order to obtain, for each response variable, a model able to plot that response, in the best possible way, as a function of the three considered factors. The significance of each model and of each coefficient within the model was determined using ANOVA. For various response variables, some coefficients came out to be not significant, thus the model described at x 2.4 was accordingly simplified, considering only the significant factors. Table 3 shows the coded coefficients of the fitted models, with the related determination coefficient (R2) and lack of fit (LOF) values. First of all it can be noticed that almost all the fitted models were highly significant (P < 0.01), with no significant LOF values (P > 0.05). LOF tests the error in response prediction, thus a P value higher than 0.05 means that the calculated model describes the true shape of the response surface. A significant LOF was found only for the model concerning the firmness of MC gels after 60 min at 80 C (P < 0.05). This was probably due to persistent system instability during gel formation. In fact, for gel firmness after 30 min, it was not possible to calculate a significant model, because the structure was still in evolution and not yet stable. Actually, as already reported by Vigouret et al. (1996), in a dilute regime (MC concentration < 3.9 g/100 mL) aggregation is visible for temperature higher than 35 C and it is a time-dependent phenomenon. Kinetics of gel formation depends on polymer concentration: at a given temperature, the equilibrium is reached in longer times when polymeric concentration is smaller. In order to confirm this hypothesis, results related to the empirical rheological behavior of MC dispersions were analyzed by means of ANOVA with Bonferroni's multiple comparison procedure (P 0.05), in order to discriminate among the averaged values of the same sample obtained at different gelation times (Table 4). As it can be seen, at the beginning of the 80 C storage period, there was a steep increment of gel firmness, and no definite structure properties could be outlined. From 90 min on, the majority of the systems reached stability, making possible a precise modeling of gel firmness. Simple models were found for this property, consisting of the main effects (linear effects) and at most of one linear interaction effect (Table 3). The only significant experimental factor, with a high and direct influence on gel firmness, was the MC concentration (b1 coefficient). The importance of this factor was evidenced also by the slope of the response surface related to the gel firmness after 180 min at 80 C (Fig. 1). In fact, comparing samples obtained with different MC concentrations and the same environmental conditions, it was possible to highlight the high influence of the hydrocolloid concentration on gel firmness. For instance, at pH 4 and BC 100 mM,
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Table 2 Results of the analysis of effects. Penetration test
MC pH BC MC*pH MC*BC pH*BC
TS
SS
F 30 min
F 60 min
F 90 min
F 180 min
Tgel
G0
G00
Tan d
G*
h*
FS G0
G00
Tan d
G*
h*
ns ns ns ns ns ns
þþþ ns ns ns ns þ
þþ ns e ns e ns
þ ns ns ns e ns
þ e e ns ns ns
ns þ ns ns
þ ns ns ns ns ns
ns ns ns ns ns ns
þ þ ns ns
þ þ ns ns
þ þ þ ns
þ e e þ þ ns
ns ns ns ns ns ns
þ þ þ ns
þ þ þ ns
MC, methylcellulose concentration; pH, buffer pH; BC, buffer concentration; TS, temperature sweep test; SS, strain sweep test; FS, frequency sweep test; F, firmness; Tgel, gelation point; G0 , elastic modulus; G00 , viscous modulus; tan d, damping factor; G*, complex modulus; h*, complex viscosity; ns, not significant; þ/, P 0.05; þ þ/ , P 0.01; þ þ þ/ , P 0.001.
Table 3 Coded coefficients, determination coefficient (R2) and lack of fit (LOF) values of the fitted models.
b0 F 60 min F 90 min F 180 min Tgel G0 SS G00 SS Tan d SS G* SS h* SS G0 FS G00 FS Tan d FS G* FS h* FS
b1 *
9.053 9.693ns 10.349ns 45.700*** 1.893*** 1.387*** 0.290* 1.909*** 1.110** 2.024** 1.381*** 0.237* 2.037*** 1.205*
b2 ***
b3 ns
0.145 0.293ns 0.020ns 0.846** 0.116** 0.055ns 0.013ns 0.116** 0.116** 0.108* 0.052ns 0.009ns 0.107* 0.107*
6.197 5.811*** 6.371** 3.950*** 0.114ns 0.314** 0.043ns 0.116ns 0.116ns 0.191ns 0.343** 0.034ns 0.193ns 0.193ns
b12 ns
0.006 0.042ns 0.039ns 0.089*** 0.006** 0.002ns 0.001ns 0.006** 0.006** 0.007* 0.003ns 0.001ns 0.007* 0.007*
b13
e e e 1.200* 0.191* e e 0.191* 0.191* 0.228* e e 0.227* 0.227*
b23
e 2.393* e 0.343ns e e e e e e e 0.041* e e
ns
0.820 e e 1.443* e e e e e e e e e e
b11
b22
b33
R2
LOF
e e e 1.393* e e 0.028ns e e e e e e e
e e e 0.321ns 0.228** e 0.052* 0.224** 0.224** 0.268*
e e e 0.993ns 0.218** e 0.062* 0.213* 0.213* e e e e e
0.843*** 0.755** 0.553* 0.976** 0.891** 0.634** 0.753* 0.891** 0.891** 0.786** 0.690** 0.804** 0.787** 0.787**
0.035* 0.056 0.129 0.515 0.099 0.219 0.988 0.077 0.081 0.055 0.137 0.381 0.056 0.056
0.071*** 0.262* 0.262*
F, firmness; Tgel, gelation point; G0 , elastic modulus; G00 , viscous modulus; tan d, damping factor; G*, complex modulus; h*, complex viscosity; SS, strain sweep; FS, frequency sweep; ns, not significant; *, P 0.05; **, P 0.01; ***, P 0.001.
the sample Cube001 (1 g/100 g MC) showed firmness values after 90 and 180 min at 80 C that were 23% of those observed for the sample Cube002 (3 g/100 g MC). A complete quadratic model was calculated for the gelation temperature (Tgel), with a very high significance (P < 0.001 or P < 0.01) of the three linear terms and a low (P < 0.05) or null significance of the other terms. The highest effect was exerted by MC concentration, as highlighted by the highest b coefficient, followed by pH and BC, which were indirectly correlated to the gel point (Fig. 2).
Table 4 Firmness (N) of methylcellulose gels during gelation at 80 C. Run
Firmness 30 min
Cube001 Cube002 Cube003 Cube004 Cube005 Cube006 Cube007 Cube008 Cube009 Cube010 Cube011 Cube012 Cent-a Cent-b Cent-c
0.04 9.06 1.56 0.90 1.87 2.91 1.22 3.06 2.53 0.04 0.05 5.42 3.92 5.14 6.85
± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.01a 0.82a 0.11a 0.03a 0.09a 0.11a 0.24a 0.19a 0.23a 0.01a 0.01a 0.38a 0.10a 0.25a 0.43a
Firmness 60 min 2.22 13.92 2.72 14.14 3.66 19.08 2.18 13.22 8.80 3.83 8.35 9.12 11.54 11.00 12.02
± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.11b 0.98b 0.08b 1.35b 0.18b 0.38b 0.15b 0.62c 0.45b 0.56ab 1.11b 0.17c 0.33c 0.61b 0.41b
Firmness 90 min 3.28 14.19 3.28 16.33 4.45 24.09 2.32 5.21 10.01 5.61 12.22 7.44 11.53 12.07 13.36
± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.22bc 1.73b 0.06d 0.15b 0.06c 0.35c 0.21bc 0.83b 0.31c 0.34b 1.26c 0.49b 0.20c 0.53c 0.57c
As an example, the temperature sweep curves reported in Fig. 3 show the direct effect of MC concentration and the inverse effect of pH and BC on the gel point (defined as the temperature at which the crossover between G0 and G00 occurs): when the MC concentration increased, the gelation temperature was higher (Fig. 3a), whereas, with the increase of pH or BC, the gel point occurred at lower temperatures (Fig. 3b and c). The effect of the hydrocolloid concentration on the gel point of MC solutions is probably related to the amount of energy necessary to cause the sol-gel transition, which is a linear function of polymer concentration (Wang & Li, 2005). The effect of BC on the gelation temperature is in agreement with previous findings by Xu et al. (2004), which demonstrated the salt-assisting and salt-suppressing features of different salts on the sol-gel transition of aqueous MC solutions. In particular, they
Firmness 180 min 3.57 15.42 3.09 21.81 4.75 24.16 2.57 3.56 9.92 5.25 12.13 10.42 10.86 12.70 15.02
± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
1.00c 0.52b 0.11c 2.42c 0.08d 0.87c 0.02c 0.51a 0.23c 0.48b 0.77c 1.11d 0.40b 0.80c 0.70d
aed Data followed by different letters in the same row are significantly different (P < 0.05; n ¼ 4).
Fig. 1. Response surface of methylcellulose (MC) gel firmness after 180 min at 80 C (ionic strength, 100 mmol/L).
C. Alamprese, M. Mariotti / LWT - Food Science and Technology 60 (2015) 811e816
Fig. 2. Response surface of gelation temperature ( C) of methylcellulose (MC) systems (pH, 7).
815
observed that the phosphate ion has a strong salting out effect, which results in a decreasing of the temperature transition of the MC solution. The effect is due to ion hydration in the aqueous solution and to the strength of interactions between ions and water molecules. Thus ions tend to compete with MC chains for water molecules, succeeding in attracting more water molecules surrounding them. This competition causes the decrease of MC solubility in water. As a result, at the same temperature, there are more hydrophobic aggregates of MC in a MC solution containing salts than in a MC solution not containing salts, thus accelerating the formation of the MC gel. The higher the salt concentration, the lower the transition temperature. To the best of our knowledge, the influence of pH on the gel point of MC solutions has not been studied so far. However, considering the use of phosphate salts in this study, it is reasonable that at higher pH values a higher dissociation degree occurred, thus
Fig. 3. Temperature sweep curves of some methylcellulose systems. Thick lines, G0 ; thin lines, G00 ; MC, methylcellulose concentration; BC, buffer concentration; Tgel, gelation temperature.
Fig. 4. Response surface of (a) logG0 (Pa; MC concentration, 2 g/100 g) and (b) log G00 (Pa; buffer concentration, 100 mmol/L) values obtained by FS curves of methylcellulose (MC) systems at 80 C.
Fig. 5. Strain sweep (a) and frequency sweep (b) curves of some methylcellulose (MC) dispersions at 80 C. MC, methylcellulose concentration; BC, buffer concentration. In (b), full symbols refer to G0 values, empty symbols to G00 values.
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C. Alamprese, M. Mariotti / LWT - Food Science and Technology 60 (2015) 811e816
increasing the ionic strength of the dissolving medium. This resulted in a higher phosphate ion concentration, determining a lower sol-gel transition temperature, as above explained. As regards the response variables extrapolated from the fundamental rheology curves, models related to G0 , G* and h* were very similar, both for SS and FS tests. These results were expected, because the rheological behavior of MC gels at 80 C was characterized by the predominance of the elastic modulus against the viscous one, typical of a solid-like material. Quadratic incomplete models were calculated, in which pH and BC had an indirect significant effect, whereas the MC concentration did not significantly influence these rheological variables. In particular, the highest absolute values in pH b coefficients demonstrated a higher influence of this factor in comparison with that of BC. In the case of G00 values calculated from the SS and FS curves at 80 C, linear models were obtained and only MC concentration had a significant and direct effect. Thus, it could be concluded that the biopolymer concentration governed the viscous behavior of the system, whereas the environmental conditions (pH and BC) had a major effect on the solid-like component, probably influencing the amount and the strength of the hydrophobic interactions among MC molecules. As an example, response surfaces related to G0 and G00 values obtained from FS tests are reported in Fig. 4. Models for tan d showed only some significant quadratic terms, with low values of b coefficients. The effects of pH and BC on the SS and FS curves can be observed in Fig. 5, where the behavior of some samples at the same MC concentration is reported. In particular, in Fig. 5a a reduction of G* and of the linear viscoelasticity region with an increase of BC were evident, but the increase in pH had a definitely higher effect, according to the significant values of the linear b12 (P < 0.05) and quadratic b22 (P < 0.01) interaction terms (Table 3). As expected, FS curves (Fig. 5b) were typical of strong gels, with G0 always higher than G00 and not dependent on the frequency value (Steffe, 1996, chap. 5). The effect of BC increase was clear on G0 and not observable on G00 . In fact, in the model related to G00 , the b3 coefficient of BC was not significant (P > 0.05) (Table 3). The decreasing of G0 with an increase in pH and BC could be ascribed to the salting out effect of phosphate buffer, as already explained. The accelerated structure formation could be responsible for a more disordered and porous matrix. In fact, Bain et al. (2012) observed a more porous structure and lower G0 values in those hydrogel samples made with MC and a mixture of citrate and tartrate salts, which have a salt-out effects, in comparison with gels containing only MC. 4. Conclusions The linear and interactions effects of polymer concentration, pH and salt concentration on the thermogelation properties of methylcellulose dispersions were demonstrated. Significant response surface models were able to describe the methylcellulose structuring properties as a function of three considered experimental factors. In particular, pH and buffer concentration seemed to influence mainly the fundamental rheological behavior of the methylcellulose systems (determined under low strain), whereas those variables evaluated at higher strains were especially affected by the polymer concentration. In particular, the salting out effect of the phosphate salts used dramatically affected the structural properties of methylcellulose gels. The obtained models represent a first step for a deeper knowledge of the molecular interactions in food systems. They should be extended to include other factors, such as protein, lipid or sucrose concentration. Then such models might prove useful in development of new foods, making easier the modulation of the structural and textural features of products as a function of recipes, technological processes, and consumer requirements.
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