Mechanical spectra and calorimetric evaluation of gelatin–xanthan gum systems with high levels of co-solutes in the glassy state

Food Hydrocolloids 30 (2013) 531e540

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Mechanical spectra and calorimetric evaluation of gelatinexanthan gum systems with high levels of co-solutes in the glassy state Filiz Altay a, Sundaram Gunasekaran b, * a b

Istanbul Technical University, Faculty of Chemical and Metallurgical, Department of Food Engineering, Maslak, Istanbul 34469, Turkey University of Wisconsin-Madison, Department of Biological Systems Engineering, 460 Henry Mall, Madison, WI 53706, USA

a r t i c l e i n f o

a b s t r a c t

Article history: Received 30 April 2012 Accepted 26 June 2012

Mechanical properties of gelatinexanthan gum (XG) mixtures with high levels of co-solutes were examined by dynamic mechanical analysis (DMA). The mechanical spectra of the samples were modeled according to the WilliamseLandeleFerry (WLF) equation/free-volume theory, which requires an entropic lightly cross-linked network. For the a dispersion, E0 and E0 0 superposed with the horizontal shift factor aT, which was temperature-dependent according to the WLF equation; no other secondary dispersion mechanism was detected. The addition of XG to gelatin networks with high levels of co-solutes changed the glass transition temperature (Tg) and kinetics of glass transition and glassy states. In the glassy state, the WLF equation was unable to follow progress in the mechanical properties, which were better described by the Andrade equation. The calorimetric measurements of the gelatineXG systems were made using a modulated temperature differential scanning calorimetry (MTDSC) to improve the determination of Tg. The samples were exposed to two cooling and heating cycles to provide a controlled recent thermal history in the temperature range of 40  C to 70  C. The Tg values of the samples were determined from the second heating cycle in the reversing heat signal. The calorimetric Tg values increased with increasing glucose syrup:sucrose ratio due to increased crosslinking, whereas mechanical Tg decreased with increased XG content due to network formation. Ó 2012 Elsevier Ltd. All rights reserved.

Keywords: Gelatin Xanthan gum Tg Glassy state WLF equation Andrade equation Free volume DMA Modulated DSC

1. Introduction Gelatinepolysaccharide mixtures have been extensively investigated in terms of gel formation, gel structure, texture and stability to tailor these properties for many food and pharmaceutical applications (Fonkwe, Narsimhan, & Cha, 2003; Kasapis, 2008; Kasapis & Al-Marhoobi, 2005; Sharma, George, Button, May, & Kasapis, 2011). For instance, mixtures of biopolymer and co-solute have been used to control the mobility transition temperatures of residual water in drug/capsule matrixes below the glass transition temperatures (Tg) (Slade & Franks, 2002). An understanding of structureefunction relations of individual components in a mixed system containing protein and polysaccharide is also of particular interest for creating use of functional ingredients in foods (Sharma et al., 2011). Dynamic mechanical measurements are extensively used to investigate structureeproperty relationships in amorphous synthetic polymers during vitrification (Kasapis, Al-Marhobi, & Sworn, 2001). Such techniques are complementary to differential * Corresponding author. Tel.: þ1 608 262 1019; fax: þ1 608 262 1228. E-mail address: [email protected] (S. Gunasekaran). 0268-005X/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.foodhyd.2012.06.013

scanning calorimetry (DSC) and are suited to studying the molecular motions that give rise to Tg and relaxations below Tg, being approximately 1000 times more sensitive than DSC for such transitions (Kalichevsky, Blanshard, & Marsh, 1993). The synthetic polymer approach, in which the idea of molecular mobility governing the kinetics of phase/state transitions and chemical reactions is applied, has been extended to food biopolymers (Levine & Slade, 1988; Kasapis et al., 2001; Kasapis, Abeysekara, Atkin, Deszczynski, & Mitchell, 2002; Kasapis, Al-Marhoobi, Deszczynski, Mitchell, & Abeysekara, 2003). This approach has been applied extensively together with free-volume theory to highconcentration mixtures of sugars and biopolymers (Deszczynski, Kasapis, MacNaughton, & Mitchell, 2003; Kasapis, Al-Marhoobi, & Giannouli, 1999; Kasapis et al., 2001; Kasapis, Desbrieres, AlMarhoobi, & Rinaudo, 2002; Kasapis & Sworn, 2000) and it has been reported that small addition of polysaccharides to sugarcontaining systems accelerate their vitrification (Kasapis et al., 2001). At a glasserubber transition (the onset of long-range microBrownian motions), there is a large decrease in the modulus (typically from 109.5 to 106.5 Pa for an amorphous polymer) and a pronounced loss peak (in tan d and E00 ). In biopolymers the drop in

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modulus at Tg is often much smaller due to presence of partial crystallinity or some form of crosslinking such as hydrogen bonding. In dynamic mechanical thermal analysis (DMTA) measurements, the size of the tan d peak is thought to reflect the volume fraction of the material undergoing the transition. Crosslinking reduces the size of the transition and the drop in E0 at Tg. The large breadth of the transition may reflect a wide variety of components or else a wide variety of degrees of order within the sample, as it reflects a very broad distribution of relaxation times (Kalichevsky et al., 1993). Tg from DMTA is obtained at the maximum value of tan d (Kasapis & Al-Marhoobi, 2000). The highest temperature loss peak is generally referred as to a, which, for an amorphous polymer, corresponds to the glass transition. In partially crystalline polymers, one or more transitions may be observed above Tg. These have been attributed to chain motions within the crystal that couple with rearrangements of disordered material at the crystal surfaces. Lower temperature transitions are generally labeled b, g, d. with decreasing temperature. They are due to local mode relaxations of the main chain, or rotations of terminal groups or other side chains. The magnitude of these transitions is much smaller than Tg and is evident from a peak in tan d and in E00 . The drop in E0 is generally very small. Low temperature transitions can give information about mobility in the glassy state and the effect of hydration (Kalichevsky et al., 1993). DMTA studies of low moisture content biopolymer systems show that they are partially hydrophilic resulting in a significant amount of polymerepolymer interactions by hydrogen bonding or hydrophobic interactions. These interactions may result in very high glass transition temperatures in the absence of plasticizers. In many cases the glass transition of the pure biopolymer is unattainable as sample degradation occurs before Tg is reached. The Tg of biopolymers is very sensitive to moisture content. Therefore, it is very important to know the moisture content and how to control it. Due to water loss during an experiment, it is difficult to test whether the mechanical transition observed in hydrated biopolymers is reversible, especially for samples with Tg above room temperature. It is generally only possible to observe the glass transition of many biopolymers in the presence of plasticizers which reduce Tg, enabling Tg to be attained before decomposition occurs. In biopolymers, the effect of a plasticizer may depend on how it affects hydrogen bonding or hydrophobic interactions. Plasticizer and biopolymer hydrophobicity are also important regarding compatibility, which is necessary for plasticization to occur (Kalichevsky et al., 1993). 2. Modeling the a mechanism Timeetemperature superposition (TTS) is often used to extend the measurement of rheological behavior over a wider frequency range. TTS principle assumes that a change in frequency is equivalent to a change in temperature, i.e., it assumes that changing the temperature only shifts the transition on the time scale, but does not change the shape or nature of the relaxation process (Kalichevsky et al., 1993). The principle of TTS or method of reduced variables has been used for constructing master curves of mechanical spectra, spanning many decades of frequency. Isothermal data obtained by frequency sweeps at several temperatures are shifted along the frequency axis and overlaid to obtain a master curve at an arbitrarily chosen reference temperature. The superposition of curves from frequency sweeps at constant temperature intervals yields the shift factor (aT) which indicates how much the time scale of measurement shifts with temperature (Ferry, 1980). The underlying basis of the principle of timeetemperature superpositioning is the equivalence between time (or frequency) and temperature as they affect molecular processes that influence the viscoelastic behavior of polymeric

materials and glass-forming small molecules (Slade & Levine, 1993). Exact matching of the shapes of adjacent curves is one of the criteria for the applicability of TTS. The other two criteria are: (a) the same values of aT must superpose all the viscoelastic functions; (b) the temperature dependence of aT must have a reasonable form consistent with experience (Ferry, 1980). For the last criterion, Williams, Landel, and Ferry (1955) proposed an equation known as the WilliamseLandeleFerry (WLF) equation. The WLF equation to describe the temperature dependence of aT:

C o ðT  To Þ log10 aT ¼  o1 C2 þ T  To

(1)

where, C1o and C2o are the WLF constants. Fitting the shift factors of the rubbery/Tg region to the WLF/free-volume framework was achieved by plotting 1/log aT against 1/(T  To) and obtaining the two parameters C1o and C2o from the slope and intercept of the linear fit, respectively. In terms of theory of free volume, the parameters C1o and C2o correspond to B/2.303fo and fo/af, respectively. For simplicity, B value was taken as unity (Williams et al., 1955). The form of Equation (1) is independent of the choice of To. It is useful to double check the values of C1o and C2o by re-computing C11 andC21 at a second reference temperature, T1, which are related as follows (Ferry, 1980):

C1o ¼ 

C11 C21 C21 þ To  T1



C2o ¼ C21 þ To  T1

(2)

(3)

Ferry (1980) also stated that To can be replaced by Tg in Equations (1)e(3). In which case aT, C1o and C2o are referred to as aTg , C1g andC2g , respectively. A somewhat more objective procedure is based on the observation from Equation (4) that

To  C2o ¼ T1  C21 hTN

(4)

where, TN is a fixed temperature at which, regardless of the arbitrary choice of To, log aT becomes infinite in accordance with the WLF equation. The temperature TN is called the Vogel temperature because a similar characteristic temperature was used in an empirical equation for temperature dependence of viscosity by Vogel in 1921. As a rule of thumb, TN is usually about 50  C below the Tg (Ferry, 1980). The temperature dependency of viscosity is determined by an energy barrier for hole formation which must be related to the average free volume present. The apparent activation energy for viscoelastic relaxation times, DHa, is given as follows (Ferry, 1980):

DHa ¼ R


2 dðln aT Þ ¼ 2:303RC1o C2o T 2 = C2o þ T  To dð1=TÞ

(5)

where R is the gas constant. This is also called as the energy of vitrification (Ev) (Kasapis, Al-Marhoobi, & Mitchell, 2003). The dramatic increase in DHa with decreasing temperature, especially near Tg, can be explained by the drastic decrease in relative free volume. To obtain a quantitative expression with free-volume parameters which can be related to the WLF coefficients, Doolittle’s viscosity equation is modified as follows (Ferry, 1980):

ln h ¼ ln A þ B

uo u  uf ¼ ln A þ B uf uf

(6)

F. Altay, S. Gunasekaran / Food Hydrocolloids 30 (2013) 531e540

where, A and B are empirical constants, uf is free volume which is the difference between the total (u) and the occupied (uo) volumes of a molecule. Viscosities of a polymer, h and ho, at two temperatures T and To can be related by the shift factor, aT, as follows (Ferry, 1980):

aT ¼

hT r ho To ro



  To ro þ ln Tr

(8)

    B 1 1 To ro þ ln  Tr 2:303 f fo

(9)

1 1  f fo



where, f is the fractional free volume (uf/u) and fo is the fractional free volume at To. In practice, this equation is almost always used without the last term (Ferry, 1980):

log10 aT ¼

  B 1 1  2:303 f fo

(10)

It may be assumed that f increases linearly with temperature in accordance with the relation (Ferry, 1980):

f ¼ fo þ af ðT  To Þ

(11)

where, af is the thermal expansion coefficient which undergoes a discontinuity at Tg. Substitution of Equation (11) in Equation (10) gives (Ferry, 1980):

log10 aT ¼ 

ðB=2:303fo ÞðT  To Þ fo =af þ T  To

(12)

which is identical in form with the WLF equation. Accordingly, the WLF constants are equal to (Ferry, 1980):

C1o ¼

C2o ¼

B 2:303fo fo

af

Ea 1 1  2:303R T To

(15)

where, Ea is the activation energy, To is the reference temperature and R is the gas constant. Activation energy can be calculated from the slope of the plot of log aT versus 1/T. 3. Calorimetric measurements

or

log10 aT ¼

log aT ¼

533



(7)

where, r and ro are the density of the sample at T and reference temperature To. Equations (6) and (7) produce the following at the reference temperature of To (Ferry, 1980):

ln aT ¼ B



(13)

(14)

Williams et al. (1955) reported that B can be taken as unity, although Ferry (1980) stated that it may be 0.9  0.3 or 1.6  0.6, depending on the calculation method. Equations (12)e(14) can also be expressed for Tg. The free-volume fraction decreases with decreasing temperature to about 0.025  0.003 at Tg, and both h (T) and timeetemperature shift factors are correlated with free volume in the temperature range of Tg and Tg þ 100 K (Williams et al., 1955). Although universal values for C1o and C2o are 17.44 and 51.6 K, respectively, Williams et al. (1955) reported that values of Co1 ¼ 8.86 and Co2 ¼ 101.6 K are somewhat better approximations. Yıldız and Kokini (2001) stated that the WLF constants for food polymers appear to be material-specific. The temperature dependence of viscoelasticity in the lowest region of the temperature can be described by the mathematical expression of Andrade (Deszczynski et al., 2003):

DSC helps in the investigation of the nonequilibrium nature of food products and processes. It can be used to characterize kinetic transition from the glassy-solid to rubbery-liquid state in many completely amorphous and partially crystalline food materials. DSC results can be used to evaluate the concept that product quality and stability depend on the maintenance of food systems in kinetically metastable, dynamically constrained, time dependent glassy and/or rubbery states rather that in equilibrium thermodynamic phases. The central focus of a polymer science approach to thermal analysis studies of structureefunction relationships in food systems is the insights obtained by the fundamental similarities between synthetic amorphous polymers and glass-forming food materials with regard to their thermal and thermomechanical properties (Levine & Slade, 1990). Modulated temperature differential scanning calorimetry (MTDSC) is a thermoanalytical technique which involves the application of a sinusoidal (modulated) heating signal to a sample. In MTDSC, the total heat flow response can be separated into reversing and non-reversing components. The total heat flow is given by:

dQ dT ¼ Cp þ f ðt; TÞ dt dt

(16)

where, dQ/dt is the total heat flow (J/s or W), Cp is the specific heat capacity (J/K) and f(t,T) represents a function of temperature and time. The Cp dT/dt term represents the reversing component, which is dependent on the rate of change of temperature (heating rate, dT/ dt) and the specific heat capacity. Chemical or physical events dependent on the absolute temperature achieved in the instrument and the rate of heat loss or gain for the process (or on the kinetics of the transition) is seen as a contribution from the f(t,T) component (Royall, Craig, & Doherty, 1998). The kinetic component or nonreversing heat flow is the arithmetic difference between the total heat flow and the reversing heat flow (Verdonck, Schaap, & Thomas, 1999). The sample is not in equilibrium with the temperature program for the duration of the transition, the f(t,T) component is considered to represent non-reversing, kinetically controlled events and is a function of absolute temperature and time, whereas the heat capacity contribution is thermodynamically reversing and is a function of heating rate (Royall et al., 1998). Conventional DSC records the total heat flow at any temperature; hence both the reversing and non-reversing components are measured simultaneously. However, MTDSC has the ability to separate the heat capacity and the kinetic components. The signal separation is particularly useful when identifying and isolating glass transitions which are seen only in the reversing heat flow signal (Royall et al., 1998). On the other hand, processes such as enthalpic relaxation, crystallization, evaporation, decomposition and curing are resolved into the non-reversing heat flow. Melting can occur in the reversing heat flow as well as in the non-reversing heat flow (Verdonck et al., 1999). The objectives of this study were to determine effects of moisture content, xanthan gum (XG) addition and glucose syrup (GS): sucrose ratio on mechanical and calorimetric Tg values of gelatin with high levels of co-solutes and to characterize glass transition

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and the glassy state using the WLF equation/free-volume theory and Arrhenius kinetics, respectively.

molds and cut into cylindrical discs. Average aspect ratio (height/ diameter) of the specimens was 0.42  0.02.

4. Materials and methods

4.3. DMA measurements

4.1. Materials

Storage (E0 ) and loss (E00 ) moduli were measured by smallamplitude dynamic measurements in a DMA (7e PerkineElmer, Chicago, IL) with PyrisÔ software. Experiments were performed in compression using a 10-mm diameter parallel plate system at 1 rad/s. The recorded strain values ranged from 0.01% to 5% during measurements. Aged gel samples were loaded at 0  C and cooled to 60  C at a scan rate of 1  C/min. Tg was obtained at the maximum value of tan d (Kasapis & Al-Marhoobi, 2000). Frequency sweeps (0.1e100 rad/s) were performed by interrupting heating runs from 60  C to 15  C at constant temperature intervals of 5  C. Heating between frequency sweeps was at a rate of 1  C/min. The purge gas was helium. For each sample, two measurements were performed.

Pigskin gelatin (Type B) and laboratory grade sucrose were purchased from EM Science and Fischer Chemicals, respectively. GS was provided by Cargill, IA, USA (Lot number C007138). The dextrose equivalent (DE) of glucose syrup was 43.4 and the total solid content was 80.53%. The water content of the GS was considered in calculating the composition of samples. The food grade XG (Lot number 3D0724A) was provided by CP Kelco U.S. Inc., Chicago, IL. 4.2. Sample preparation Several gelatineXG systems were prepared. For each, the required amount of gelatin and XG were dissolved separately in deionized water to prepare 10% solution at 75  C and 600 rpm for 20 min and 4% solution at 60  C and 425 rpm for 2 h, respectively. The required amount of sucrose was mixed with 1/3 part of water in a temperature-controlled kettle. Then GS, gelatin, and XG solution were added into the sucrose solution. The mixture was stirred at about 90  C for 30e60 min depending on the desired level of total solids, which was checked by a refractometer (Atago N-3E, Japan). Total solids content of the gels, which were cured overnight in a refrigerator at 0  C, were determined using the AOAC method (AOAC, 1990); the moisture contents were calculated by subtracting total solids content from one hundred. The compositions of all samples tested are presented in Table 1. The gelatineXG systems were investigated at two moisture contents (20 and 25%), three gelatin:XG ratios (5:0, 9:1, and 4:1) and three GS:sucrose ratios (<1, 1 and >1) at each moisture content. For each sample, two batches were prepared and tested. Freshly prepared samples were poured into 17-mm inner diameter, 66-mm long aluminum tube molds. The inside surfaces of the molds were coated with vegetable oil to prevent the gel from sticking. The ends of the molds were closed with rubber stoppers. The tubes were placed vertically in a refrigerator at 0  C for overnight. Prior to measurement, the gels were removed from the

4.4. DSC measurements DSC measurements were performed using a Modulated DSC (2920 TA Instruments, New Castle, DE) with a refrigerated cooling system (RCS) attached. Nitrogen was used as the purge gas, flowing at a rate of 35 mL/min through the DSC cell, and at 150 mL/min through the RCS unit. Hermetic aluminum pans were used. The DSC heat flow and the heat capacity were calibrated using indium and sapphire, respectively. Aged gels of 10e20 mg were cooled from 25  C to 70  C (the first cooling cycle), left there for 10 min, and heated from 70  C to 40  C (the first heating cycle) and cooled from 40  C to 70  C (the second cooling cycle) and then heated from 70  C to 40  C (the second heating cycle) at 1  C/min. Temperature amplitude was 0.53  C with 40 s of modulation. The first cooling and heating cycles were performed to provide a controlled recent thermal history (Borde, Bizot, Vigier, & Buleon, 2002; Nowakowski & Hartel, 2002). The onset, midpoint and end temperatures were determined using the instrument’s software (TA Instruments Inc., Universal Analysis, Version 2.6D, Thermal Solutions Release 2.7). The onset temperature is the intersection of the first and second tangents, the midpoint temperature is halfway between the onset and end of the glass transition region, and the end temperature is the intersection of the second and third

Table 1 Composition of each sample. Sample number

Moisture content (%)

Gelatin (%)

XGa (%)

GS# (%)

Sucrose (%)

Gelatin:XG ratio

GS:sucrose ratio

1 2 3 4 5 6 7 8 9

25

5 4.5 4 5 4.5 4 5 4.5 4

e 0.5 1 e 0.5 1 e 0.5 1

40 40 40 35 35 35 30 30 30

30 30 30 35 35 35 40 40 40

5:0 9:1 4:1 5:0 9:1 4:1 5:0 9:1 4:1

1.33:1 1.33:1 1.33:1 1:1 1:1 1:1 0.75:1 0.75:1 0.75:1

10 11 12 13 14 15 16 17 18

20

5 4.5 4 5 4.5 4 5 4.5 4

e 0.5 1 e 0.5 1 e 0.5 1

45 45 45 37.5 37.5 37.5 35 35 35

30 30 30 37.5 37.5 37.5 40 40 40

5:0 9:1 4:1 5:0 9:1 4:1 5:0 9:1 4:1

1.5:1 1.5:1 1.5:1 1:1 1:1 1:1 0.88:1 0.88:1 0.88:1

a

XG: xanthan gum; # GS: glucose syrup.

F. Altay, S. Gunasekaran / Food Hydrocolloids 30 (2013) 531e540

tangents. Tg was taken as the midpoint temperature on the reversing heat flow during the second heating cycle (Royall et al., 1998). The reference was an empty hermetically sealed aluminum DSC pan. Three runs were recorded for each sample and the average was reported.

535

9

3 log E' log E" tan delta

8

4.5. Statistical analyses The mean and standard deviation of the replicate measurement data were calculated using Excel (Microsoft 7) and factorial ANOVA (analysis of variance) was used to determine the significance of differences among the treatment levels at p ¼ 0.01, using commercial statistical software (SPSS, IBM Statistics, Version 20.0).

2 6

Tan δ

Log (E’or E”, Pa)

7

5 4 1 3 2 1 -3

0 -2

-1

0

1

2

3

4

5

6

7

8

5. Results and discussion The changes in viscoelasticity observed with temperature were presented as a function of frequency. Fig. 1 illustrates the mechanical spectra of E0 and E00 for sample containing 4.5% gelatin þ 0.5% XG þ 40% GS þ 30% sucrose. Mechanical spectra for all samples as a function of frequency were the same. In Fig. 1, the temperature dependency of frequency sweep data appears to follow same pattern at most temperatures. However, at very low temperatures, i.e., <45  C, frequency data are scattered, meaning the temperature dependency follows a different kinetic at lower temperatures. Using the principle of TTS, the viscoelastic data for gelatineXG mixtures produced master curves that cover a frequency window of almost 10 orders of magnitude in Fig. 2. The reference

a

Fig. 2. Master curve for the sample 2 (4.5% gelatin þ 0.5% xanthan gum þ 40% glucose syrup þ 30% sucrose). Reference temperature: 15  C.

temperature of 15  C was used. Thus, Fig. 2 becomes the mechanical analog of the effect of temperature seen in the passage from the glass transition to the glassy state in the cooling curve. Master curves for all samples were obtained similarly (Altay, 2006). Success of TTS suggests minimal changes occur within gelatineXG gum systems with co-solute at high concentration over a temperature 40 to 15  C, as moduli exhibit similar temperature dependences (Ferry, 1980). In the literature, for similar systems, the most accepted theory is that polymers become stretched and

8

-55°C -50°C -45°C -40°C -35°C -30°C -25°C -20°C -15°C -10°C -5°C 0°C 5°C 10°C 15°C

Log (E’, Pa)

7

6

5

4 -1

b

0

Log (ω, rad/s)

1

2

8

Log (E”, Pa)

7

6

5

4 -1

0

1

2

-55°C -50°C -45°C -40°C -35°C -30°C -25°C -20°C -15°C -10°C -5°C 0°C 5°C 10°C 15°C

Log (ω, rad/s) Fig. 1. Frequency sweeps of (a) E0 , and (b) E00 for the sample 2 (4.5% gelatin þ 0.5% xanthan gum þ 40% glucose syrup þ 30% sucrose).

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F. Altay, S. Gunasekaran / Food Hydrocolloids 30 (2013) 531e540

a

14 12 10

Log a T

8 6 4 2 0 -2 -4 -60

b

-50

-40

-10 -30 -20 Temperature (oC)

0

10

20

3

1 / Log aT

2 y = -10.784x - 0.1822 2 R = 0.993

1 0 -1 -2 -3 -0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

1 / (T-To) Fig. 3. (a) Temperature dependency of the shift factor aT within the glass transition and glassy state for sample 2. The solid line reflects the WLF fit. (b) The WLF plot.

lightly cross-linked to form a flexible network. Junction zones are stabilized by regions of thermally stable entanglements and hydrogen bonding (Nickerson, Paulson, & Speers, 2004). The effect of temperature on viscoelastic functions through the glass transition region can be followed by the WLF equation, which was derived on the basis of the free-volume concept (Williams et al., 1955). That is, the segments of a polymer chain can be seen as rigid bodies and the free volume as the holes present between these segments due to packing irregularities. In polymer melts, the proportion of free volume is usually 30% of the total volume. On lowering the temperature to the glass transition region the free volume decreases to about 3%. A wide range of materials follows this theory and the thermal expansion coefficient (af) is assumed to undergo a discontinuity at the Tg (Deszczynski et al., 2003).

The logarithmic dependence of the shift factors as a function of temperature for gelatin/XG mixture is shown in Fig. 3(a). From Fig. 3(a), the shift factors follow closely the predictions of the WLF equation only within the temperature range of the glass transition region seen in the cooling curve. Fitting the shift factors of the glass transition region to the WLF/free-volume framework can be achieved by plotting 1/log aT against 1/(T  To) and obtaining the two parameters C1o and C2o from the slope and intercept of the linear fit, respectively (Fig. 3(b)). The WLF parameters for all samples are listed in Table 2. The experimental Tg values (from maximum value of tan d (Kasapis & Al-Marhoobi, 2000)) obtained from cooling curves as the reference temperature apply to Equations (2) and (3), g g and then C1 , and C2 values were calculated (Table 2). A range for the fractional free volume and the thermal expansion coefficient at Tg obtained from Equations (13) and (14) are also given in Table 2. Free volume at Tg is expected to collapse to something between 2 and 4% of the total volume (Kasapis, 2001). From Table 2, free volume of most of the samples decreased to 2e4% of the total volume. For synthetic polymers, af ranges between 1.7  104 and 12.5  104 (1/K) (Ferry, 1980). Most of af values of samples fell in this range (Table 2). Free volumes of in situ gelatin gels with high levels of co-solutes increased with moisture content (Altay, 2006). At 20% moisture content, free volumes remained relatively constant, whereas they decreased with the addition of XG at 25% moisture level. Free volumes of cured gels increased with the XG addition in the lack of water (Table 2). At 25% moisture level, the addition of 0.5% XG increased free volumes, while further addition of XG free volumes generally decreased. Based on previous studies, the curing process affected the network structure that leads to change free volume within the molecule. According to Ferry (1980), the occupied volume should remain constant at constant temperature and pressure. However, spontaneous contraction of a glassy sample occurs after quenching it to a temperature near or below Tg over a period of time. The decrease in free volumes can be seen especially for gels without XG gum (Table 2). From Fig. 3(a), it can be seen that the shift factors do not follow the WLF equation below Tg. These deviation points from the WLF kinetic are also given in Table 2. Due to fact that below Tg the temperature dependency of aT did not follow the WLF kinetic, this region can be considered as glassy state. The temperature

Table 2 The WLF equation parameters C1o , C2o , C1g and C2g , energy of vitrification (Ev), fg, ag at Tg, deviation point from the WLF kinetic and activation energy for the glassy states for all samples. Sample no.a

Tg (K)

To (K)

Co1

Co2 (K)

Cg1

Cg2 (K)

Ev (kJ/mol) at Tg

fg range

af at Tg (1/K)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

249 238 236 255 237 234 251 227 232 243 245 235 241 235 238 241 253 231

258 258 258 258 258 258 258 258 258 258 258 258 258 258 258 258 258 258

10.28 5.49 14.93 8.89 11.20 8.87 11.77 4.52 8.70 10.42 7.36 5.10 22.68 8.91 9.19 14.95 9.73 11.35

94.00 59.19 144.50 74.03 116.51 95.09 102.54 62.21 102.46 96.36 58.97 65.32 204.97 67.45 106.06 143.24 62.02 79.55

11.37 8.29 17.61 9.26 13.66 11.87 12.63 9.02 11.66 12.34 9.45 7.87 24.73 13.51 11.33 16.96 10.58 17.18

85.00 39.19 122.50 71.03 95.51 71.09 95.54 31.21 76.46 81.36 45.97 42.32 187.97 44.45 86.06 126.24 57.02 52.55

159 229 153 162 154 175 159 285 157 172 236 197 146 321 143 149 227 334

0.038e0.038 0.052e0.052 0.024e0.025 0.046e0.048 0.032e0.032 0.036e0.037 0.034e0.035 0.044e0.052 0.037e0.037 0.034e0.036 0.046e0.046 0.055e0.057 0.017e0.018 0.030e0.034 0.037e0.039 0.025e0.026 0.041e0.041 0.035e0.035

4.49 13.37 2.01 6.60 3.33 5.15 3.6 15.43 4.87 4.33 10.00 13.04 0.93 7.23 4.45 2.03 7.20 4.81

a b

See Table 1 for compositions of different samples. The deviation point from the WLF kinetic can be considered as the point where glassy state starts.

                 

104 104 104 104 104 104 104 104 104 104 104 104 104 104 104 104 104 104

Deviation point from the WLF kineticb <35 <40 <40 <35 <40 <45 <35 <40 <45 <40 <35 <45 <40 <30 <40 <35 <25 <30



C C  C  C  C  C  C  C  C  C  C  C  C  C  C  C  C  C 

Ea for glassy state (kJ/mol) 95 149 70 109 82 124 43 186 95 78 143 95 91 99 101 103 80 71

F. Altay, S. Gunasekaran / Food Hydrocolloids 30 (2013) 531e540 7

Log a T

6

y = 7781.4x - 29.911 2 R = 0.959

5

4 3 0.00425 0.0043 0.00435 0.0044

0.00445 0.0045 0.00455 0.0046 0.00465

1 / T (1/K) Fig. 4. Temperature dependency of the factor aT within the glassy state for sample 2. The straight line reflects the fit to Andrade equation.

dependency of viscoelasticity in the lowest region of the temperature can be described by the mathematical expression of Andrade (Deszczynski et al., 2003). Activation energy can be calculated from the slope of the plot of log aT versus 1/T (Fig. 4). Fig. 4 shows a good linear fit for the temperature dependence of aT for the samples. The Andrade equation fits of all samples. The activation energies for the glassy states are given in Table 2. From Table 2, in most cases, the deviation points from the WLF kinetic started at lower temperatures for samples containing XG. For these samples, Tg values were also lower. These results suggest that addition of XG decreased the glass transition region and the onset of glassy state, even though it accelerated the vitrification process (Altay, 2006; Altay & Gunasekaran, 2012). Activation energies in the glassy state were lower than vitrification energies. This is due to non-cooperative character of the sub-Tg motions, their activation energy values are rather low (Roudaut, Simatos, Champion, Contreras-Lopez, & Le Meste, 2004). 5.1. MTDSC results A typical result from the MTDSC run for the sample 1 (5% gelatin þ 40% GS þ 30% sucrose) is shown in Fig. 5. All heating and cooling cycles are included. It appears that the first and second cycles are similar; however Tg values were determined from the

537

second heating cycles. In Fig. 5, endotherms can be seen around 0  C in both cooling and heating cycles. At cooling cycles around 25  C a second endotherm can be seen where the baseline shifted, which may be considered as Tg. This second endotherm can be distinguished at heating cycles around 20  C. To elicit better interpretation, the total heat flow curves in Fig. 5 were separated into reversing and non-reversing heat flow signals for the second cooling and heating cycle (Fig. 6). In Fig. 6(a), on the reversing heat flow signal, the baseline shift can be seen clearly. This shift is accompanied an endotherm which can be detected from the non-reversing heat flow. If the baseline shift is accepted as Tg, and then the endotherm is called endothermic relaxation (Royall et al., 1998). In Fig. 6(b), the baseline shift in the reversing heat flow on the second heating was also detected at approximately the same temperature as in the second cooling cycle. This baseline shift was also accompanied by an exotherm, which can be determined from the non-reversing heat flow signal. In non-reversing heat flow an exotherm may indicate ice formation. The difference in Tg from the reversing heat flow signals between the cooling cycle and the heating cycle is called as Tg “shift” effect and it may be attributed to a kinetic effect (difference in the rate of formation and detection) or an annealing effect (difference in relaxation of the sample upon storage (Royall et al., 1998)). In Fig. 7, the determination of Tg is presented on the reversing heat flow signal. The Tg values obtained from second heating cycles for all samples are given in Table 3. Statistical analysis was applied to Tg values obtained from second heating cycle. According to the analysis, the most important factor affecting Tg was GS:sucrose ratio (F < 0.01). Tg values increased with increasing GS:sucrose ratio, which contains saccharide polymers. These polymers may have more crosslinking in the network, leading to increasing Tg. Furthermore, Tg was dependent on all two-interactions of three effects. For instance, the combined effect of moisture content and GS:sucrose ratio on Tg was significant (F < 0.01). At 25% moisture content, Tg values significantly increased for samples with GS:sucrose ratio > 1. Probably, in the presence of water, with the increasing GS:sucrose ratio, crosslinking in the molecule increased, so Tg also increased.

Fig. 5. The total heat flow for sample 1 (5% gelatin þ 40% glucose syrup þ 30% sucrose).

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F. Altay, S. Gunasekaran / Food Hydrocolloids 30 (2013) 531e540

Fig. 6. The reversing and non-reversing heat flow for sample 1 (5% gelatin þ 40% glucose syrup þ 30% sucrose) in the second cooling (a), second heating cycles (b), respectively.

5.2. Comparison of mechanical and calorimetric Tg Values of Tg obtained from mechanical measurements are more reliable than those obtained from calorimetric evaluation; however, they can complement each other (Kalichevsky et al.,

Fig. 7. The determination of Tg from the reversing heat flow signal for sample 1 (5% gelatin þ 40% glucose syrup þ 30% sucrose) in the second heating cycle.

1993; Ngai & Roland, 2002). Glass formation is a second-order transition which can be detected by DSC. Calorimetric determination of Tg is affected by the heating rate, which should be given (Mazzrobre, Aguilera, & Buera, 2003). In addition, DSC scan imposes no frequency effects on data, which is no longer important in MTDSC (Kasapis, 2008). Tg values obtained from DMA and MTDSC measurements were reported in Table 3. Calorimetric Tg values were lower than mechanical Tg values, except for sample 8, 14 and 18 (Table 3). The sample 8, 14 and 18 which contain XG and over 37.5% sucrose, probably had more crosslinks that could be detected by the MTDSC. For other samples, network formation due to presence of gelatin, XG or both was prominent depending on the moisture content; therefore mechanical Tg values were higher than calorimetric Tg values. Differences between mechanical Tg and calorimetric Tg were reported in the literature (Kasapis, 2008). In a study, mechanical Tg in the presence of gelling polysaccharide were higher than calorimetric Tg (Jiang, Kasapis, & Kontogiorgos, 2011). According to the statistical analysis, the most important factor affecting calorimetric Tg was GS:sucrose ratio whereas it was gelatin:XG ratio for mechanical Tg (F < 0.01). Mechanical Tg values decreased with XG significantly. In addition, mechanical Tg was dependent on all two-interactions of three effects (F < 0.01). Different factors affecting mechanical and calorimetric Tg suggest that they based on different concepts. Mechanical Tg can be

F. Altay, S. Gunasekaran / Food Hydrocolloids 30 (2013) 531e540

539

Table 3 Total solids content (TSC) and Tg values obtained from DMA and MTDSC of samples.a Sample no.d

TSC (%)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

74.68 74.03 74.93 75.41 75.67 75.71 75.93 76.29 75.30 81.47 79.16 80.03 82.18 81.14 80.90 81.54 81.82 81.47

Gelatin:XG ratio

GS:sucrose ratio

Mechanical Tg ( C)b

5:0 9:1 4:1 5:0 9:1 4:1 5:0 9:1 4:1 5:0 9:1 4:1 5:0 9:1 4:1 5:0 9:1 4:1

>1 >1 >1 1 1 1 <1 <1 <1 >1 >1 >1 1 1 1 <1 <1 <1

23.91 35.23 37.40 18.14 35.51 38.74 22.32 46.04 41.43 29.86 27.91 37.57 31.71 38.29 34.86 32.21 20.15 41.71

Calorimetric Tg ( C)c From 2nd heating cycle

a b c d

                 

0.77 0.27 0.58 1.37 1.40 0.92 0.70 0.19 0.54 0.12 1.08 0.03 0.68 0.12 0.01 0.10 0.44 1.01

                 

0.33A 0.23B 1.50C 1.94A 1.16B 1.46C 0.62A 2.66B 0.81C 2.09D 0.04E 0.86F 2.66D 2.13E 2.24F 1.92D 0.31E 0.51F

25.45 39.59 41.74 43.44 47.11 41.29 49.53 41.50 47.92 39.31 39.55 48.73 42.59 35.02 37.87 46.44 39.92 32.95

                 

0.33A 2.56A 5.15A 1.55AB 0.72AB 0.40AB 0.84B 1.07B 0.63B 2.16D 2.18D 1.12D 3.86DE 0.38DE 0.88DE 0.30E 1.58E 0.38E

Values reported are mean  standard deviation. Means  SD (n ¼ 2); values within samples 1e9 followed by the same letter (in column, gelatin:XG effect) are not significantly different (p < 0.01). Means  SD (n ¼ 3); values within samples 10e18 followed by the same letter (in column, GS:sucrose effect) are not significantly different (p < 0.01). See Table 1 for compositions of different samples.

considered as a network Tg in such systems (Kasapis, 2012) because the addition of biopolymer accelerates the vitrification as forming a network. Similar results have been reported for gelatin/ k-carrageenan mixture (Kasapis & Al-Marhoobi, 2005). However, calorimetry provides information about the mobility of the sugar molecules (Aubuchon, Thomas, Theuerl, & Renner, 1998), and the small addition of biopolymer in this case is a mere crosscontamination (Kasapis, 2012). 6. Conclusions TTS is a powerful approach and provides a comprehensive description of polymer behavior during gelation of gelatineXG systems at high levels of co-solutes. TTS helps predict changes in structure of the network over time in relation to free-volume theory. As temperatures are lowered below Tg, the WLF equation becomes invalid. Therefore, an Arrhenius-type equation was used to characterize the kinetics in the glassy state. The addition of XG into gelatin with high levels of co-solute shifted the glassy state into lower temperatures. The total heat flow response in DSC can be separated into reversing and non-reversing components using MTDSC technique. Tg can be identified from the reversing heat flow signal of the second heating cycle. Tg values increased with increasing GS:sucrose ratio due to the increased crosslinking, which may lead to the formation of thermodynamically stable junction zones (Sworn & Kasapis, 1998). In contrast, mechanical Tg decreased significantly with increased XG content. Based on Tg results, mechanical and calorimetric data should be evaluated independently; however, they complement each other in understanding the network formation and mobility of sugar molecules in systems containing mixed biopolymers with high levels of cosolutes. Acknowledgment We are grateful to Prof. Richard Hartel of University of Wisconsin-Madison for accessing to DMA in his laboratory.

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