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W) emulsions stabilized by whey protein isolate
Journal of Food Engineering 263 (2019) 253–261
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The effect of denaturation degree of protein on the microstructure, rheology and physical stability of oil-in-water (O/W) emulsions stabilized by whey protein isolate
T
Nataly Dapuetoa, Elizabeth Troncosob,c, Camila Mellaa, Rommy N. Zúñigaa,c,* a
Bioprocess Engineering Laboratory, Department of Biotechnology Universidad Tecnológica Metropolitana, Las Palmeras 3360, P.O. Box 7800003, Ñuñoa, Santiago, Chile Bioprocess Engineering Laboratory, Department of Chemistry Universidad Tecnológica Metropolitana, Las Palmeras 3360, P.O. Box 7800003, Ñuñoa, Santiago, Chile c Programa Institucional de Fomento a la I+D+i Universidad Tecnológica Metropolitana, Ignacio Valdivieso 2409, P.O. Box 8940577, San Joaquín, Santiago, Chile b
A R T I C LE I N FO
A B S T R A C T
Keywords: Protein denaturation Protein aggregation Interfacial properties Rheology Stability Microstructure
The objective of this work was to study the effect of denaturation degree of WPI dispersions used as surfactant on the microstructure, rheology, and physical stability of O/W emulsions. Emulsions with different oil contents (10%, 20% and 30% w/w) were formulated using sunflower oil, as the dispersed phase, and WPI dispersions with different degrees of denaturation (0%, 15%, 30%, 45% and 60%), as continuous phase. The emulsions were characterized in terms of (i) microstructure, quantified by optical microscopy and image analysis, (ii) rheological properties, based on flow curve tests, and (iii) physical stability, evaluated by static multiple light scattering. The diffusional migration of proteins to the oil–water interface was slightly affected by denaturation degree of proteins. Microscopy images of the emulsions revealed that droplet size distribution and mean droplet sizes were strongly affected by the denaturation degree of protein dispersions above 30% and by the oil content at 30%. The rheology of emulsions presented a shear-thinning behavior for all conditions studied. The physical stability of the emulsions increased with an aggregation degree up to 45%, presumably because of the increased apparent viscosity of the continuous phase.
1. Introduction
properties due to the presence of both hydrophobic and hydrophilic amino acids, improving the formation and stability of colloidal systems. Whey protein isolate (WPI) is one of the highest-quality proteins, given its amino acid content (i.e., high essential, branched-chain, and leucine amino acid content) and rapid digestibility (Devries and Phillips, 2015). Due to their wide techno-functional properties, whey proteins are commonly used as structuring agents in food formulations (Dombrowski et al., 2016). The variety of functional groups in WPI allows them to stabilize water, fat and air-based structures (i.e., gels, emulsions, and foams, respectively) (Kulozik, 2007; Schmitt et al., 2007). WPI is mainly composed by β-lactoglobulin (50%), α-lactalbumin (15–20%) and bovine serum albumin (5–7%), their surface activity and colloid-stabilizing characteristics (Dombrowski et al., 2016; Martínez et al., 2009; Schmitt et al., 2007) allows them to act as emulsifiers to stabilize oil-water interfaces. These properties of WPI make it one of the most versatile food ingredients. Thermal treatment can induce changes in the functional performance of whey proteins. Whey proteins, such as β-lactoglobulin and α-
An emulsion is a mixture of two immiscible liquids, one of them dispersed as droplets (i.e., dispersed phase) within the other (i.e., continuous phase). A wide variety of natural products, food ingredients, and final products can be considered to consist either entirely or partially as emulsions (Chung and McClements, 2014). Emulsion-based food products have been intensely studied, exhibiting a wide range of physicochemical and organoleptic properties. The stability of emulsion systems is crucial for food processing, storage, and handling, hence the understanding and manipulation of bulk properties of the emulsion systems are of utmost importance for the food industry. Shelf-life, mouth-feel, and flow properties are largely determined by interactions among system constituents (Bellalta et al., 2012). An important challenge for food emulsion science is therefore to understand, monitor, and control the changes in colloidal interactions, rheology, and microstructure during processing and storage (Dalgleish, 2006). In this context, proteins have good emulsifying and emulsion stabilizing
* Corresponding author. Bioprocess Engineering Laboratory, Department of Biotechnology Universidad Tecnológica Metropolitana Las Palmeras 3360, P.O. Box 7800003, Ñuñoa, Santiago, Chile. E-mail address: [email protected] (R.N. Zúñiga).
https://doi.org/10.1016/j.jfoodeng.2019.07.005 Received 23 February 2019; Received in revised form 4 July 2019; Accepted 6 July 2019 Available online 09 July 2019 0260-8774/ © 2019 Elsevier Ltd. All rights reserved.
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2.2. Methods
lactalbumin, are particularly heat sensitive and can be affected by the application of heat in a targeted manner to make use of their potential to create or optimize food structures (Kulozik, 2007). According to Meklo and Foegeding (1999), the reaction products of heat treatment over WPI could be called “polymers” or “aggregates”. The former implies covalent bonding. The latter is a general term, which covers a range of intermolecular interactions. The structure and resulting functional properties of these protein-based structures depend on numerous conditions, including protein concentration, applied heating protocol, electrostatic interactions, and the presence of co-solutes (Foegeding, 2015; Guyomarc'h et al., 2015; Nicolai and Durand, 2013). As protein aggregates/polymers are complex structures, whose size may be as large as a few hundred nanometers, their behavior may differ from that of native proteins (Dombrowski et al., 2016; Rullier et al., 2008). Rheological behavior of whey protein based emulsions depend markedly on the concentration of native (undenatured) and aggregated proteins (Ҫakir-Fuller, 2015). According to Dombrowski et al. (2016), aggregates/polymers play a significant role in stabilizing interfaces, as particle size directly affects the diffusion processes and thus surface covering. Native proteins had shown faster stabilization of interfaces, mainly due to the slower diffusion of bigger particles such as aggregates toward the interface (Moussier et al., 2019). Even this interface is very thin (in the nanometer range), it represents a large surface area and controls to a great extent the physicochemical stability of emulsions (Berton-Carabin et al., 2018). Currently, the development of novel food-grade particles, such as heat-induced aggregates/polymers or microgels, capable of effectively stabilizing air/water interfaces has attracted considerable interest. However, no clear conclusions regarding the requirements of specific particle properties for interface stabilization could be drawn from literature, due to the complexity of the physicochemical properties of aggregates. In order to overcome this problem, some studies employed only one time-temperature protocol for the thermal generation of aggregates/polymers. Different ratios of native WPI and aggregates/ polymers were studied for interfacial, rheological, and foaming properties (Davis and Foegeding, 2004; Maticorena et al., 2018; Zhu and Damodaran, 1994). Changes in protein adsorption to the air/water interface and interfacial rheological properties as altered by the aggregates/polymers were hypothesized to cause differences in foaming properties (Davis and Foegeding, 2004). However, this approach has not been studied for WPI stabilized emulsions to date. A better understanding of the effect of thermal treatments on the physicochemical properties of WPI could lead to a rational control over functional performance, such as their ability to form and stabilize food emulsions. Inferring from the above-mentioned studies, we hypothesize that varying the ratio between native and denatured WPI will affect the specific physical properties of the emulsion and their stability could be increased by the use of WPI aggregates. Therefore, the objective of this work was to study the effect of denaturation degree of WPI dispersions used as surfactant on the rheological and stability properties of oil-inwater (O/W) emulsions.
2.2.1. Formation of WPI dispersions Dispersions of WPI at 10% w/w protein basis in ultra-pure water were prepared by slow stirring (200 rpm) at 25 °C for 2 h, using a magnetic stirrer, avoiding foam formation. The WPI dispersions were left at 4 °C for at least 12 h to allow complete hydration of the protein. 2.2.2. Heat aggregation of WPI dispersions Samples (3 mL) of WPI dispersions were heated in test tubes (inner diameter: 7 mm; thickness 1 mm; length: 120 mm) in order to induce protein denaturation and aggregation. The tubes were immersed in a water bath (Memmert, model Basic WNB, Germany) at a constant temperature of 70 °C for 15 min. After the heat treatment, samples were cooled to ambient temperature (25 °C). According to Ryan et al. (2013), near complete aggregation of denatured proteins can occur in a few minutes when heating WPI, depending on protein dispersion and heating process conditions. Confirmation of denaturation and aggregation of whey proteins after the thermal treatment was made through HPLC and DLS measurements, respectively. Various ratios of denatured WPI dispersions (15%, 30%, 45%, and 60%) were created by mixing native with denatured dispersions by volume (Davis and Foegeding, 2004; Maticorena et al., 2018). All procedures were done in triplicate. 2.2.3. Emulsion formation WPI-stabilized emulsions were prepared from a dispersed and an aqueous phase. The dispersed phase consisted of sunflower oil; whereas the aqueous phase corresponded to WPI dispersions. In order to elaborate the O/W emulsions, sunflower oil was added dropwise to WPI dispersions while mixing at 25 °C, using a rotor-stator homogenizer (Kinematika, model PT-MR 2500, Switzerland) at 3000 rpm for a duration of 3 min. Emulsions with different oil contents (10%, 20% and 30% w/w) were formulated. DLS measurements of protein dispersions were done before and after the homogenization process in order to confirm that no protein aggregation occurred as a consequence of the stirring applied. 2.3. Measurements 2.3.1. Determination of denaturation degree using HPLC analysis The denaturation degree of α-lactalbumin and β-lactoglobulin (main proteins of WPI) was determined by HPLC as described in detail by Zúñiga et al. (2010). According to this method, only native whey proteins that have a retention time identical as the standard fractions (α-lactalbumin, product L6010; β-lactoglobulin, product L3908, SigmaAldrich, Germany) are detected. Therefore, any changes in the tertiary structure of proteins would result in a drift of the retention time, and consequently, these molecules would not be detected as native (i.e. denatured). The denatured whey proteins were separated from the solution by shifting the pH value to 4.6 followed by centrifugation at 4130 rpm for 20 min. The supernatant (i.e. soluble proteins) was filtered through a membrane filter (0.45 μm pore size, Mixed Cellulose Ester, DISMIC 25AS, Advantec MFS Inc., Japan) and the concentration of native whey proteins in the supernatant was determined by HPLC coupled to a DAD detector at 220 nm (UHPLC, Dionex Ultimate 3000, Thermo Scientific, USA). A gradient of solvent A (water:acetonitrile:trifluoroacetic acid 900:100:1 v/v) and solvent B (water:acetonitrile:trifluoroacetic acid 100:900:1 v/v) was applied. The gradient started with 20% of solvent B and increased to 46% B over 30 min, and for the next 6 min the gradient returned to the initial conditions. Analysis was carried out at 25 °C, using a flow of 1.5 mL/min with a C18 5 μm 120 Å, 4.6 × 150 mm column (Acclaim™ 120, Thermo Scientific, USA). Integration and comparison of the elution profiles of WPI dispersions enabled the extents of denaturation to be determined. The
2. Materials and methods 2.1. Materials Whey protein isolate (WPI) (Provon 190, Glanbia Nutritionals Inc., USA) was used as the surface-active agent in emulsion formation. According to the supplier, the composition of WPI was 92.62% of protein (dry basis), 3.34% of moisture, and 2.99% of ash. The pH of the native WPI dispersion was about 6.3. A commercial brand of sunflower oil (Natura™, Córdoba, Argentina) was used as a dispersed phase. Ultrapure water (resistivity of 15 MΩ-cm) was employed for the preparation of all samples.
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percentage of denaturation (β-lg and α-la) was determined as the difference in the total amount of denaturable protein (Equation (1)).
DD (%) = 1 −
RDP × 100% TDP
where D is the protein bulk diffusion coefficient, t is the time elapsed since the formation of the oil/water interface, π is a numerical constant and C0 is the bulk protein concentration. Assuming that diffusion towards the interface controls the adsorption process, a plot of Π against time1/2 will be linear for short times and the diffusion rate constant (kdiff) can be derived from the slope of this plot (Dombrowski et al., 2016; Martínez et al., 2009; Maticorena et al., 2018).
(1)
where DD is the denaturation degree (%), RDP is the residual denaturable protein and TDP is the total denaturable protein in the WPI dispersion. It should be noted that this method measured the extent of protein denaturation relative to the level of denaturable protein in commercial WPI.
2.3.4. Microstructure of WPI-stabilized emulsions Emulsion microstructure was analyzed by means of light microscopy. This microstructural characterization was carried out in terms of droplet size and droplet size distribution. Droplet size was determined from images of the emulsions obtained with an inverted light microscope (Olympus, model CKX41, Japan), and using concave slides to avoid deformation of droplets. Images were recorded with a digital CCD camera (M-Shot Digital Imaging System, model MD90, China) connected to the microscope and image processing for droplet size analysis was carried out semi-automatically with the camera imaging software (M-Shot Digital Imaging System, version 9.0). The boundaries of droplets were manually traced and the image analysis software measured and calculated the size of the traced objects. The droplet sizes of the WPI-stabilized emulsions were measured directly after emulsification. A substantial number of droplets (N = 450) were counted to obtain statistical estimates of droplet size distribution in each sample. A droplet size distribution was generated by grouping the droplets into classes. The frequency distribution of droplet sizes was computed using Microsoft Excel (Microsoft® Excel, 2010). The relative frequency of any class interval was calculated as the number of droplets in that class (class frequency) divided by the total number of droplets and expressed as a percentage. The mean droplet diameter (DM) of the class with the highest frequency (i.e., mode) and the standard deviation of the class belonging to DM were calculated (Zúñiga et al., 2011).
2.3.2. Aggregate size measurements Aggregate sizes were determined by a dynamic light scattering (DLS) instrument (Zetasizer Nano-ZS, Malvern Instruments, Worcestershire, UK). The instrument was used in the backscattering configuration where detection is done at a scattering angle of 90°. Protein samples were diluted 100 times with ultrapure water to avoid an effect known as multiple scattering. The path length of the light was set automatically by the apparatus depending on the sample turbidity (attenuation). Dispersions were examined in a 1-cm path–length spectroscopic glass cell at 25 °C. The autocorrelation function was calculated from the fluctuation of the scattered intensity with time. From the polynomial fit of the logarithm of the correlation function, using the “cumulant” method, the diffusion coefficient of the molecules was calculated and hence the hydrodynamic diameter using the Stokes–Einstein equation (Zúñiga et al., 2010). 2.3.3. Dynamic interfacial tension (DIT) measurements between WPI dispersions and sunflower oil For the interfacial tension experiments, WPI dispersions were diluted to a factor of 1:10 using ultra-pure water. This dilution was required to bring out interfacial properties among samples and minimize the viscous effect on protein diffusion to the oil–liquid interface (Maticorena et al., 2018; Schmitt et al., 2007; Zúñiga et al., 2011). Changes in the WPI interfacial tension were measured with an automated contact angle goniometer (Ramé-Hart Inc., model 250-F4, NJ, USA). DIT measurement (τ) was based on the pendant drop method, where an axisymmetric drop (9 μL) of WPI dispersion at 25 °C was delivered and allowed to stand at the tip of the needle for 30 min inside a quartz container with 30 mL of oil to achieve protein adsorption at the oil-water interface. Drop images were captured at different time intervals with the CCD camera of the equipment. The DIT of the WPI dispersions was calculated by analyzing the profile of the drop by image analysis with the DROPimage Advanced software and then by fitting the Laplace equation to the drop shape. To validate the results, it was experimentally corroborated that the interfacial tension of the sunflower oil/pure water system (26.6 ± 0.5 mN/m) was almost the same as previously reported (26.45 ± 0.46 mN/m) for the same system (Pawlik et al., 2010). Results obtained from the DIT measurements were interpreted in terms of interfacial pressure, which was defined as the decrease in interfacial tension of a pure solvent caused by the addition of the protein:
Π = τw − τp
2.3.5. Rheological evaluation of WPI-stabilized emulsions Rheological tests were made in a controlled shear rate rheometer (Anton Paar, ReolabQC, Osterreich). Samples of emulsions were carefully poured into the rheometer cup and allowed to stand 2 min before shearing. The test temperature was set at 25 °C using a peltier controller (Peltier RheolabQC plus, C-PTD180/AIR/QC). The test geometry was a coaxial cylinder geometry conforming to DIN 53018. The rheological characterization of emulsions was performed using a flow curve test, where the shear rate was increased linearly from 0.1 to 100 s−1 during 400 s. Over the range of shear rates, the experimental flow curves of the emulsions were described by the Power Law model as follows:
σ = K × γ˙ n
where σ is the shear stress (Pa), K is the consistency index (Pa s ), γ˙ is the shear rate (s−1), and n is the flow behavior index (dimensionless). 2.3.6. Physical stability of the WPI-stabilized emulsions The stability of emulsions was determined by static multiple light scattering using a vertical scan analyzer (TurbiScan MA2000, Formulaction, France). The backscattering (BS) and transmission intensities of an incident near-infrared light (λ = 880 nm) were both measured automatically every 40 μm along the 70 mm cell height. The BS intensity variations along the sample height and over time gave a qualitative indication about the evolution of the distribution and movements of the droplets during destabilization. Emulsion samples (~7.5 mL) were placed into cylindrical glass tubes and stored at 5 °C. The BS from the WPI-stabilized emulsions were then measured at room temperature (25 °C) as a function of time. The Turbiscan Stability Index (TSI) is a statistical parameter used to estimate the suspension stability. The TSI consider the sum of all
(2)
where Π is the interfacial pressure of the dispersion (mN/m), τw is the interfacial tension of pure water (26.6 mN/m at 25 °C), and τp is the interfacial tension of the WPI dispersion (mN/m) at the same temperature. Protein diffusion towards interface can be characterized by Equation (3), where the change in surface pressure is correlated with time (Dombrowski et al., 2016; Martínez et al., 2009; Maticorena et al., 2018).
D × t 1/2 ⎞ Π = 2C0 ⎛ ⎝ π ⎠
(4) n
(3) 255
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3.2. Dynamic interfacial tension (DIT) measurements between WPI dispersions and oil
destabilization processes occurring in the emulsions. Thus, in order to compare between emulsion samples, results of stability are presented as TSI, which was calculated according to the following expression (Sun et al., 2015; Xu et al., 2016):
The rate at which a surfactant adsorbs onto a new created interface is one of the important factors to consider during emulsion formation. In this study, the DIT measurements decreased with time due to the diffusion and adsorption of protein at the oil/water interface (data not shown), decreasing thermodynamically unfavorable contact between oil and water. Surface pressure (Π) was calculated from the DIT data using Equation (2) (Fig. 2). Theoretically, the evolution of Π is the result of the adsorption of protein molecules from the bulk of the dispersion and adsorption at the oil/water interface. In this way, the driving force for adsorption phenomena is the difference in concentration between current surface and the surface at equilibrium conditions (Wang and Narsimhan, 2005). WPI adsorption at the oil/ water interface was always characterized by a rapid increase (~90 s) in Π (Fig. 2, insert) followed by a slow evolution towards an equilibrium value. This evolution is likely due to the occurrence of different phenomena, starting with an initial stage where fast protein diffusion and adsorption at the interface take place, followed by a slower step where the conformational rearrangement of the protein at the interface occurs (Tripp et al., 1995). Minimal differences can be seen when varying the degree of denaturation of WPI dispersions on Π kinetics (Fig. 2); with Π values ranged from about 2 to 17 mN/m. Native whey proteins can diffuse faster to the interface due to their smaller size compared with aggregates/ polymers. For highly diluted dispersions (0.0017% w/w), Moussier et al. (2019) found a shorter lag time (< 5 s) for native WPI than for thermal aggregated WPI (20 s). Lag time was defined as the value when the surface tension varied by more than 5% from its starting value, indicating a slower diffusion of bigger particles. For more concentrated dispersions (~0.1% w/w), Schmitt et al. (2007) argued that it is reasonable to expect similar adsorption kinetics at small time scales (~50 s), because of an initial decrease in surface tension is mainly due to the diffusion of native proteins. Thus, the increase in Π with time could be due to the diffusion and absorption of native protein at the oil/ water interface. Therefore, Π values will be dominated by the amount of native protein, but not by the physicochemical properties of the WPI aggregates. These results explain the trends observed in Fig. 2. It has been shown that during the thermal treatment of globular proteins denaturation/aggregation of protein molecules occurs (Zúñiga et al., 2010), and the rate and extent of this phenomenon is a function of processing (e.g., protein concentration, temperature-time relationship) and environmental conditions (e.g., pH, ionic strength, among others). Because all dispersions were subjected to the same thermal treatment and were under the same milieu condition, it is highly probable that the aggregates/polymers formed had identical physicochemical properties, not affecting significantly the surface properties of the dispersions. The diffusion rate constant (kdiff) represents the diffusional migration of proteins to the oil–water interface, behavior that in fact increases Π. Table 1 shows the kdiff values (obtained from Π against time1/2 plots) for native and thermally-treated WPI dispersions. Values of kdiff were in the range of 0.843–0.907 mN/m s0.5 and no statistical differences were found (p > 0.05) between kdiff values; albeit kdiff increased up to a denaturation degree of 30% and then decreased. A previous study of our research group showed that the highest kdiff values were obtained for native protein dispersions and there was a decreasing trend in kdiff with an increase in the aggregation degree (Maticorena et al., 2018). Values of kdiff obtained in this work were in the same order of magnitude as previous studies. Dombrowski et al. (2016) obtained kdiff values in the range of 0.50–0.79 mN/m s0.5 for diffusion of β-lactoglobulin (pH between 6.8 and 8.0 and NaCl addition between 20 and 130 mM) to the air/water interface, and Maticorena et al. (2018) obtained kdiff values ranging from 0.34 to 0.92 mN/m s0.5 for WPI dispersions with pH between 5.5 and 6.5, and from 0.53 to
h=H
TSI =
∑
∑h = 0 |BSt (h) − BSt − 1 (h)| H
t=1
(5)
where BS is the backscatter intensity, t is the scanning time, h is the height of the measurement per 40 μm, and H is the height of the sample in the measuring cell.
2.4. Statistical analysis of data Analysis of variance (ANOVA) tests were used to analyze the data at a confidence level of 95%, using the Statgraphics Centurion XVI software (Manugistics Inc., Statistical Graphics Corporation, Rockville, USA). Differences between samples were evaluated using Multiple Range Test, by means of the Least Significant Differences (LSD) multiple comparison method.
3. Results and discussion 3.1. Denaturation and aggregation of whey proteins Measurements by means of HPLC were done in order to determine changes in the tertiary structure of whey proteins (α-lactalbumin and βlactoglobulin, main proteins of WPI), and consequently, in the native state of them. According to the procedure employed, WPI dispersion presented 0% of denaturation, the elution profile for WPI dispersions at pH 4.6 and dispersions without a change in pH were the same (result not shown). Moussier et al. (2019) found a denaturation degree of 0.6% for commercial WPI, corroborating present results. The integration and comparison of the WPI elution profiles (Fig. 1) enabled the extents of denaturation to be determined. After the thermal treatment, the degree of denaturation of WPI dispersions was 75%. In addition, results from DLS measurements showed that size distribution curves of thermally treated WPI dispersions shifted to larger sizes, meaning that WPI aggregates were formed (Guyomarc'h et al., 2015; Nicolai and Durand, 2013; Zúñiga et al., 2010).
Absorbance at 220 nm (AU) 50 -lactoglobulin Native WPI Denatured WPI
40
30
-lactalbumin
20
10
0 5
10
15
20
25
30
Retention time (min) Fig. 1. Protein profiles of the supernatants from native WPI and denatured WPI dispersions. 256
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Interfacial pressure (mN/m) 16
Interfacial pressure (mN/m) 12
12
Eq. 2
10
Denaturation degree (%) 0 15 30 45 60
8
4
8 6 4 2 0
2
4 6 Time0.5 (s0.5)
8
10
0 0
200
400
600
800
1000 1200 1400 1600 1800
Time (s) Fig. 2. Evolution of the interfacial pressure for WPI dispersions at different denaturation degrees. Insert graph shows the evolution of the interfacial pressure for times employed in calculation of the diffusion rate constant.
1.01 mN/m s0.5 for dispersions with NaCl addition between 1% and 2% (w/w). The fact that the kdiff values obtained in this study were independent of the denaturation degree of protein dispersion confirms that native protein dominates the adsorption phenomena and the change in interfacial pressure at small times scale.
size distributions, with emulsions formulated at 30% oil showing the widest size distribution. Although only slight differences were found in the relationship between Π and protein denaturation degree (Fig. 2), the microstructure of the O/W emulsions stabilized by thermally treated WPI dispersions presented clear differences regarding droplet sizes. Interfacial tension measurements were done at a fixed interfacial area (i.e., given by the volume of the pendant drop), but the amount of interfacial area created during homogenization processes relies not only on the capacity of surfactant of decreasing interfacial tension, but also on its concentration (McClements, 2005). Concentration of native protein decreases as the denaturation degree increases, thus diminishing the capacity of WPI dispersions to stabilize the new created interfaces during the homogenization process, which finally generated larger sizes and wider size distribution of oil droplets, as observed in Figs. 3 and 4, respectively. In addition, the apparent viscosity of the continuous phase of the emulsions influences its flow behavior properties during homogenization. As the apparent viscosity of the continuous phase increased with denaturation degree (see point 3.4), the efficiency of the homogenization process could be reduced, resulting in the formation of large oil droplets. According to McClements (2005), at sufficiently high shear rates (as in a rotor stator homogenizer) oil droplets elongated and broken up into smaller droplets, which depends on the ratio of the apparent viscosities of the droplet and continuous phase (μD/μC). Changes in droplet size distributions are also coincident with the steepest change in consistency coefficient observed in Fig. 5.
3.3. Microstructure of WPI-stabilized emulsions The droplet characteristics, in particular droplet size, are extremely important to obtain stable emulsions. In addition, it has been regarded as an indirect method to determine the emulsification ability of proteins. Clear differences in droplet sizes can be observed both qualitatively from micrographs (Fig. 3), and quantitatively from size distribution curves (Fig. 4), where larger sizes of droplets were obtained with an increase in the denaturation degree. The appearance of gray “noise” in the background of the micrographs corresponds to the formation of protein aggregates during thermal treatment, which increases in number as the denaturation degree increased (Fig. 3). At the lowest oil content (10% w/w), no differences were found in droplet sizes at denaturation degrees up to 30%. Above this threshold, droplet sizes augmented with the denaturation degree of the WPI dispersions, moving the size distribution curves to larger sizes (Fig. 4). The same behavior was observed for emulsions fabricated with 20% and 30% oil, but in these cases, droplets increased their sizes above 15% of protein denaturation. Higher levels of denaturation generated wider droplet Table 1 Diffusion rate constant values for the diffusional interfacial pressure model. Parameter
Denaturation degree (%) 0 0.5
kdiff (mN/m s R2 *
)
0.843 ± 0.039 0.973
15 a
0.863 ± 0.096 0.971
30 a
0.907 ± 0.026 0.972
Different letters indicate significant differences (p < 0.05) for different denaturation degrees. 257
45 a
60 a
0.868 ± 0.050 0.976
0.850 ± 0.037a 0.973
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Relative frequency (%) 35
Oil content 10% (w/w) 30
Denaturation degree (%)
25
0 15 30 45
20
60
15 10 5 0 0
10
20
30
40
Droplet diameter ( m) Relative frequency (%) 40
Oil content 20% (w/w)
Denaturation degree (%) 0 15 30 45 60
30
20
10
0
Fig. 3. Gallery of images from optical microscopy of O/W emulsions stabilized by WPI with different denaturation degrees of protein and oil contents. Images are presented without digital processing.
0
10
20
30
40
Droplet diameter ( m) Relative frequency (%)
For all size distributions in Fig. 4, the mean droplet diameter (DM) of the class with the highest frequency and their corresponding standard deviation, were calculated (Table 2). In agreement with previous discussions, both denaturation degree and oil content had significant effects over the DM values. For emulsions with 10% of oil, DM values were significantly different (p < 0.05) above 30% of denaturation, but for emulsions with 20% and 30% oil, DM values were significantly different (p < 0.05) over 15% of denaturation (Table 2). Oil content of emulsions also influenced droplet diameters; DM values were statistically different (p < 0.05) at oil contents over 10% for denaturation degrees of 0% and 15%, whereas at 30% of denaturation, the three levels of oil presented different DM values, and for 45% and 60% of denaturation, DM values were statistically higher (p < 0.05) at 30% of oil. In this study, the droplet size of emulsions stabilized by thermallytreated whey proteins will be determined for the amount of native protein and not by the physicochemical properties of aggregates/ polymers (e.g., size, morphology, surface charge and surface hydrophobicity), which explains the trends observed in Figs. 3 and 4. It is probable that physicochemical properties of aggregates/polymers could affect the rheological and physical stability of O/W emulsions. In our case, only the amount of aggregates affected the rheological and physical stability of emulsions, because the thermal treatment was the same for all WPI dispersions. In summary, when the amount of native protein is not enough to stabilize new interfaces, larger droplet sizes are obtained, explaining the trends observed in Figs. 3 and 4, and results from Table 2. In the
50
Oil content 30% (w/w)
Denaturation degree (%) 0 15 30 45 60
40
30
20
10
0 0
20
40
60
Droplet diameter ( m) Fig. 4. Relative frequency distribution curves of oil droplet sizes for O/W emulsions stabilized by WPI with different denaturation degrees and oil contents.
same way, when the oil content in the formulation of emulsions was higher, there was not enough native protein to cover the new interfaces created. 258
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Consistency coefficient (Pa sn) 0,10
networks between oil droplets and the alignment of aggregates with the flow field. The values obtained for the consistency coefficient (K) were plotted against the denaturation degree of WPI dispersions for the three oil concentrations used (Fig. 5). It can be observed that the increase in the denaturation degree as well as the oil content augmented the values of K. In general, for denaturation degrees over 30%, the increase in K values was more evident. An exponential relationship (R2 between 0.990 and 0.996) was found between denaturation degree and K values (Fig. 5), suggesting a strong dependence of the rheology of the WPIstabilized emulsions with the volumetric fraction of the thermally formed aggregates. Recently, Maticorena et al. (2018) observed that the higher the aggregation degree, the higher was the apparent viscosity of WPI dispersions, because of the increased interactions between the reactive groups of the protein molecules, the aqueous phase, and the higher volumetric fraction of aggregates. The hydrodynamic size of the protein molecules increased with the aggregation degree (Zúñiga et al., 2010), hence increasing apparent viscosity due to the formation of aggregates/polymers via sulfhydryl-disulfide interchange reactions (Zhu and Damodaran, 1994). Large aggregates/polymers (or microgels) have the capacity to trap solvent in their porous structure, increasing the apparent viscosity of protein dispersions (Dickinson, 2017; Murphy et al., 2016). Subsequently, as apparent viscosity of the continuous phase increased, the emulsion viscosity increased as well. The consistency coefficient also increased with oil content. For emulsions with lower oil contents, the particles are far apart and the inter-particle interactions are relatively weaker. As oil content increases, the particles become closer, which leads to the packing of the oil droplets, and the inter-particle interactions get stronger, giving a non-Newtonian behavior. The attractive forces between droplets drive the formation of flocs, which normally could evolve into a space-filling particulate network (Bellalta et al., 2012). This, in turn, increased the apparent viscosity of emulsions. According to the above explanation, the apparent viscosity of the WPI-stabilized emulsions was influenced by both denaturation degree of the WPI in the continuous phase and the amount of oil content in the dispersed phase.
Oil content (% w/w) 10 20 30
0,08
0,06
0,04
0,02
0,00 0
10
20
30
40
50
60
Denaturation degree (%) Fig. 5. Consistency coefficient of O/W emulsions stabilized by WPI with different denaturation degrees and oil contents. Lines shows an exponential relationship between denaturation degree and consistency coefficient.
3.4. Rheological behavior of the WPI-stabilized emulsions The results obtained from the rheological tests indicated that higher values of shear stress were obtained with an increase in the denaturation degree and oil content when emulsions were subjected to shear forces. At denaturation degrees over 30%, the increase in shear stress values was more significant. Across the range of shear rates studied, all emulsions behaved as shear-thinning fluids. In order to verify and quantify this fact, the data from rheograms of the emulsions (not shown) were fitted to the Power Law model (Equation (4)), finding a good agreement between the experimental data and the model (R2 above 0.970). Flow behavior index (n) values were in the range of 0.85 to 0.64, confirming the shear-thinning behavior of the emulsions. Generally speaking, the rheological properties of emulsions are mainly determined by the volumetric fraction of the dispersed phase and their size and size distribution. However, surfactants may also play an important role in the rheological behavior of emulsions. Aggregation stability of droplets is determined mainly by the nature and concentration of a surfactant in the system creating and stabilizing the emulsion (Derkach, 2009). The shear-thinning behavior of emulsions represents a structural breakdown that may occur because of the spatial redistribution of the particles under a shear field, the alignment of nonspherical particles with the flow field, or the deformation and disruption of flocs (McClements, 2005). When an initial external force is applied to the system, the flocs or aggregates present greater resistance to flow than the individual droplets. However, as the shear rate is increased, the aggregates are deformed and disrupted (Ҫakir-Fuller, 2015) For WPI-stabilized emulsions, pseudoplasticity may be attributed to intermolecular interactions resulting from the attractions between adjacent aggregated molecules with the formation of weak transient
3.5. Physical stability of the WPI-stabilized emulsions Emulsion stability can be associated with no discernible changes from a thermodynamically stable state and/or no changes of droplets in their size distribution, state of aggregation, or spatial arrangement within the emulsion, over the time-scale of study (McClements, 2005). Modification of a backscattering (BS) signal can occur as a function of time and particle migration or size change, and it is graphically reported in the form BS increase or BS decrease (Celia et al., 2009). Results are presented as BS profiles at the end of the storage period (20 days) (Fig. 6a). BS profiles of emulsions stabilized by native WPI showed a different pattern for emulsions stabilized by thermally treated WPI, at three oil concentrations. For emulsions stabilized by thermally treated WPI creaming of oil droplets and sedimentation of protein particles could be seen on the top and bottom of the tube; no detection of flocculation or coalescence was observed from BS curves. When
Table 2 Mean droplet diameter (μm) and standard deviation of the class with the highest frequency for O/W emulsions stabilized by whey protein isolatea. Oil content (% w/w)
Denaturation degree (%) 0
10 20 30
15 aA
3.26 ± 0.41 4.55 ± 0.39aB 4.64 ± 0.65aB
30 aA
45 aA
3.25 ± 0.40 4.70 ± 0.46aB 4.81 ± 0.68aB
3.23 ± 0.42 5.02 ± 0.67bB 7.38 ± 1.40bC
60 bA
7.74 ± 0.45 7.25 ± 0.77cA 8.53 ± 1.41cB
9.25 ± 0.71cA 9.15 ± 0.66dA 14.59 ± 1.68dB
a Different lower case letters indicate significant differences (p < 0.05) between denaturation degrees, whereas different upper case letters indicate significant differences (p < 0.05) between oil contents.
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a
b Backscattering (%) Denaturation degree (%)
Oil content 10% (w/w) 0,6
0 15 30 45 60
TSI (-) 12 Oil content 10% (w/w)
Denaturation degree (%)
10
0 20 40 60 80
8
0,4
6 4 0,2
2 0
0,0 0
20
40
60
0
5
Tube heigh (mm)
10
15
20
Time (day)
Backscattering (%) Denaturation degree (%)
Oil content 20% (w/w) 0,6
0 15 30 45 60
0,4
TSI (-) 5 Oil content 20% (w/w)
Denaturation degree (%) 0 20 40 60 80
4
3
2 0,2
1
0
0,0 0
10
20
30
40
50
60
70
0
5
Tube heigh (mm)
10
15
20
Time (day)
Backscattering (%)
TSI (-) 5
Oil content 30% (w/w)
Oil content 30% (w/w)
Denaturation degree (%)
0,6
0 15 30 45 60
0,4
Denaturation degree (%)
4
0 20 40 60 80
3
2 0,2
1
0
0,0 0
10
20
30
40
50
60
70
0
5
10
15
20
Time (day)
Tube heigh (mm)
Fig. 6. (a) Backscattering profiles as a function of the tube length after 20 days and (b) Turbiscan stability index (TSI) of WPI-stabilized O/W emulsions with different denaturation degrees and oil contents.
proteins are used to stabilize emulsions, they tend to create charged and stable interfaces; in other words, they created structured interfacial layers with repulsive forces between them (Derkach, 2009; Walstra, 2003). These protein-coated interfacial layers decreased the flocculation, interface breakdown, and coalescence. Emulsion stability was expressed as TSI, where the lower TSI values correspond to the more stable system. The TSI values increased with storage time for all experimental conditions, indicating that WPI-stabilized emulsions are prone to physical destabilization (Fig. 6b). Emulsions stabilized with native WPI showed the highest TSI values at the three oil contents employed. Stability of emulsions was increased with denaturation degree up to 45%, independent of the oil content
Table 3 Turbiscan stability index (TSI) for O/W emulsions stabilized by whey protein isolate at 20 days of storage at 5 °C. Oil content (% w/w)
10 20 30
Denaturation degree (%) 0
15
30
45
60
10.81 4.35 3.76
2.73 2.87 3.36
1.99 2.06 2.26
1.73 1.82 1.85
1.90 2.25 2.95
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(Fig. 6 and Table 3). At 60% of denaturation, TSI values increased. These results can be explained in terms of the microstructure of the emulsions and rheology of the continuous phase. In general, smaller particles have a lower tendency to cream. According to Stokes law, the creaming velocity of a droplet is proportional to its radius squared, and a bigger radius would have a greater tendency to aggregate, leading to a greater probability of collision (McClements, 2005). On the other hand, the presence of protein aggregates increased the apparent viscosity of the continuous phase (Maticorena et al., 2018), which contributes to emulsion stability by decreasing the rate of droplet movement. For emulsions stabilized with native WPI or denatured up to 30%, droplet size distributions and mean droplet diameter of emulsions were quite similar (Fig. 4 and Table 2). However, the consistency coefficient increased in an exponential relationship with denaturation degree (Fig. 5), giving a better stability when denaturation degree increased up to 30%. At 45% of denaturation, the lowest TSI values were found. Although size distributions shifted to larger diameters (Fig. 4) and mean droplet diameters were statistically larger than lower denaturation degrees (Table 2), these emulsions had a significant increase in consistency coefficient (Fig. 5). This probably caused the best stability among all emulsions. TSI values found for emulsions with 60% of WPI denaturation can be attributed to the precipitation of protein and creaming of oil on the bottom and top of the tube, respectively (Fig. 5a). At this level of denaturation, the biggest droplets were found (Fig. 4). Probably, the volume of protein particles was too high, causing the precipitation of the aggregates. From the microstructural, rheological and stability results presented in this study, it is possible to establish that mixing native with denatured WPI can be considered as a strategy to tailor physical properties of food emulsions in order to create new protein-based products.
Technology 9, 551–587. Celia, C., Trapasso, E., Cosco, D., Paolino, D., Fresta, M., 2009. Turbiscan Lab® Expert analysis of the stability of ethosomes® and ultradeformable liposomes containing a bilayer fluidizing agent. Colloids Surfaces B Biointerfaces 72, 155–160. Chung, C., McClements, D.J., 2014. Structure-function relationships in food emulsions: improving food quality and sensory perception. Food Struct. 1, 106–126. Dalgleish, D.G., 2006. Food emulsions – their structures and structure-forming properties. Food Hydrocolloids 20, 415–422. Davis, J.P., Foegeding, E.A., 2004. Foaming and interfacial properties of polymerized whey protein isolate. J. Food Sci. 69, C404–C410. Derkach, S.R., 2009. Rheology of emulsions. Adv. Colloid Interface Sci. 151, 1–23. Devries, M.C., Phillips, S.M., 2015. Supplemental protein in support of muscle mass and health: advantage whey. J. Food Sci. 80, A8–A15. Dickinson, E., 2017. Biopolymer-based particles as stabilizing agents for emulsions and foams. Food Hydrocolloids 68, 219–231. Dombrowski, J., Johler, F., Warncke, M., Kulozik, U., 2016. Correlation between bulk characteristics of aggregated β-lactoglobulin and its surface and foaming properties. Food Hydrocolloids 61, 318–328. Foegeding, E.A., 2015. Food protein functionality – a new model. J. Food Sci. 80, C2670–C2677. Guyomarc'h, F., Famelart, M.-H., Henry, G., Gulzar, M., Leoniil, J., Hamon, P., Bouhallab, S., Croguennec, T., 2015. Current ways to modify the structure of whey proteins for specific functionalities – a review. Dairy Sci. Technol. 95, 795–814. Kulozik, U., 2007. Structuring dairy products by means of processing and matrix design. In: Aguilera, J.M., Lillford, P.J. (Eds.), Food Materials Science. Principles and Practice. Springer, New York, pp. 439–473. Martínez, M.J., Carrera-Sánchez, C., Rodríguez-Patino, J.M., Pilosof, A.M.R., 2009. Interactions in the aqueous phase and adsorption at the air-water interface of caseinoglycomacropeptide (GMP) and β-lactoglobulin mixed systems. Colloids Surfaces B Biointerfaces 68, 39–47. Maticorena, E., Alarcón, C., Troncoso, E., Zúñiga, R.N., 2018. The degree of protein aggregation in whey protein isolate (WPI)-based dispersions modifies their surface and rheological properties. CyTA - J. Food 16, 146–155. McClements, D.J., 2005. Food Emulsions: Principles, Practices, and Techniques, second ed. CRC Press, Boca Raton. Meklo, S., Foegeding, E.A., 1999. Formation of whey protein polymers: effect of a twostep heating process on rheological properties. J. Texture Stud. 30, 137–149. Moussier, M., Bosc, V., Michon, C., Pistre, V., Chaudemanche, C., Huc-Mathis, D., 2019. Multi-scale understanding of the effects of the solvent and process on whey protein emulsifying properties: application to dairy emulsion. Food Hydrocolloids 87, 869–879. Murphy, R.W., Farkas, B.E., Jones, O.G., 2016. Dynamic and viscoelastic interfacial behavior of β-lactoglobulin microgels of varying sizes at fluid interfaces. J. Colloid Interface Sci. 466, 12–19. Nicolai, T., Durand, D., 2013. Controlled food protein aggregation for new functionality. Curr. Opin. Colloid Interface Sci. 18, 249–256. Pawlik, A., Cox, P.W., Norton, I.T., 2010. Food grade duplex emulsions designed and stabilized with different osmotic pressures. J. Colloid Interface Sci. 352, 59–67. Rullier, B., Novales, B., Axelos, M.A.V., 2008. Effect of protein aggregates on foaming properties of α-lactoglobulin. Colloid. Surf. Physicochem. Eng. Asp. 330, 96–102. Ryan, K.N., Zhong, Q., Foegeding, E.A., 2013. Use of whey protein soluble aggregates for thermal stability - a hypothesis paper. J. Food Sci. 78, R1105–R1115. Schmitt, C., Bovay, C., Rouvet, M., Shojaei-Rami, S., Kolodziejczyk, E., 2007. Whey protein soluble aggregates rom heating with NaCl: physicochemical, interfacial, and foaming properties. Langmuir 23, 4155–4166. Sun, C., Wu, T., Liu, R., Liang, B., Tian, Z., Zhang, E., Zhang, M., 2015. Effect of superfine grinding and microparticulation on the surface hydrophobicity of whey protein concentrate and its relation to emulsion stability. Food Hydrocolloids 51, 512–518. Tripp, B.C., Magda, J.J., Andrade, J.D., 1995. Adsorption of globular proteins at the air/ water interface as measured via dynamic surface tension: concentration dependence, mass-transfer considerations, and adsorption kinetics. J. Colloid Interface Sci. 173, 16–27. Walstra, P., 2003. Physical Chemistry of Foods. Marcel Dekker, New York (Chapter 11). Wang, Z., Narsimhan, G., 2005. Interfacial dilatational elasticity and viscosity of β-lactoglobulin at air−water interface using pulsating bubble tensiometry. Langmuir 21, 4482–4489. Xu, D., Zhang, J., Cao, Y., Wang, J., Xiao, J., 2016. Influence of microcrystalline cellulose on the microrheological property and freeze-thaw stability of soybean protein hydrolysate stabilized curcumin emulsion. LWT – Food Science and Technology 66, 590–597. Zhu, H., Damodaran, S., 1994. Heat-induced conformational changes in whey protein isolate and its relation to foaming properties. Journal of Agricultural and Food Science 42, 846–855. Zúñiga, R.N., Tolkach, A., Kulozik, U., Aguilera, J.M., 2010. Kinetics of formation and physicochemical characterization of β-lactoglobulin aggregates. J. Food Sci. 75, E261–E268. Zúñiga, R.N., Kulozik, U., Aguilera, J.M., 2011. Ultrasonics generation of aerated gelatin gels stabilized by whey protein β-lactoglobulin. Food Hydrocolloids 25, 958–967. Ҫakir-Fuller, E., 2015. Enhanced heat stability of high protein emulsion systems provided by microparticulated whey proteins. Food Hydrocolloids 47, 41–50.
4. Conclusions The diffusional migration of proteins to the oil–water interface was slightly affected by the denaturation degree, confirming that native proteins play a dominant role in the decrease of interfacial tension at short times. The microstructure of emulsions was affected by the denaturation degree, with larger droplet diameters obtained when native protein was less than 70%. Mixing of native and denatured/aggregated WPI dispersions can be an alternative to improve emulsion rheology and stability, because the fraction of native protein dominates the adsorption process at the oil–water interface, and the denatured/aggregated fraction gives the necessary apparent viscosity for stabilizing emulsions. These results will eventually lead to a better understanding of the colloidal basis of emulsion stability, thus having important implications for the design and production of food emulsions. Conflicts of interest All authors declare no conflict of interest. Acknowledgements R.N. Zúñiga thanks to the financial support of CONICYT by means of the FONDECYT Project 1140031. References Bellalta, P., Troncoso, E., Zúñiga, R.N., Aguilera, J.M., 2012. Rheological and microstructural characterization of WPI-stabilized O/W emulsions exhibiting time-dependent flow behavior. LWT – Food Science and Technology 46, 237–381. Berton-Carabin, C.C., Sagis, L., Schroën, K., 2018. Formation, structure, and functionality of interfacial layers in food emulsions. Annual Review of Food Science and
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Journal of Food Engineering journal homepage: www.elsevier.com/locate/jfoodeng
The effect of denaturation degree of protein on the microstructure, rheology and physical stability of oil-in-water (O/W) emulsions stabilized by whey protein isolate
T
Nataly Dapuetoa, Elizabeth Troncosob,c, Camila Mellaa, Rommy N. Zúñigaa,c,* a
Bioprocess Engineering Laboratory, Department of Biotechnology Universidad Tecnológica Metropolitana, Las Palmeras 3360, P.O. Box 7800003, Ñuñoa, Santiago, Chile Bioprocess Engineering Laboratory, Department of Chemistry Universidad Tecnológica Metropolitana, Las Palmeras 3360, P.O. Box 7800003, Ñuñoa, Santiago, Chile c Programa Institucional de Fomento a la I+D+i Universidad Tecnológica Metropolitana, Ignacio Valdivieso 2409, P.O. Box 8940577, San Joaquín, Santiago, Chile b
A R T I C LE I N FO
A B S T R A C T
Keywords: Protein denaturation Protein aggregation Interfacial properties Rheology Stability Microstructure
The objective of this work was to study the effect of denaturation degree of WPI dispersions used as surfactant on the microstructure, rheology, and physical stability of O/W emulsions. Emulsions with different oil contents (10%, 20% and 30% w/w) were formulated using sunflower oil, as the dispersed phase, and WPI dispersions with different degrees of denaturation (0%, 15%, 30%, 45% and 60%), as continuous phase. The emulsions were characterized in terms of (i) microstructure, quantified by optical microscopy and image analysis, (ii) rheological properties, based on flow curve tests, and (iii) physical stability, evaluated by static multiple light scattering. The diffusional migration of proteins to the oil–water interface was slightly affected by denaturation degree of proteins. Microscopy images of the emulsions revealed that droplet size distribution and mean droplet sizes were strongly affected by the denaturation degree of protein dispersions above 30% and by the oil content at 30%. The rheology of emulsions presented a shear-thinning behavior for all conditions studied. The physical stability of the emulsions increased with an aggregation degree up to 45%, presumably because of the increased apparent viscosity of the continuous phase.
1. Introduction
properties due to the presence of both hydrophobic and hydrophilic amino acids, improving the formation and stability of colloidal systems. Whey protein isolate (WPI) is one of the highest-quality proteins, given its amino acid content (i.e., high essential, branched-chain, and leucine amino acid content) and rapid digestibility (Devries and Phillips, 2015). Due to their wide techno-functional properties, whey proteins are commonly used as structuring agents in food formulations (Dombrowski et al., 2016). The variety of functional groups in WPI allows them to stabilize water, fat and air-based structures (i.e., gels, emulsions, and foams, respectively) (Kulozik, 2007; Schmitt et al., 2007). WPI is mainly composed by β-lactoglobulin (50%), α-lactalbumin (15–20%) and bovine serum albumin (5–7%), their surface activity and colloid-stabilizing characteristics (Dombrowski et al., 2016; Martínez et al., 2009; Schmitt et al., 2007) allows them to act as emulsifiers to stabilize oil-water interfaces. These properties of WPI make it one of the most versatile food ingredients. Thermal treatment can induce changes in the functional performance of whey proteins. Whey proteins, such as β-lactoglobulin and α-
An emulsion is a mixture of two immiscible liquids, one of them dispersed as droplets (i.e., dispersed phase) within the other (i.e., continuous phase). A wide variety of natural products, food ingredients, and final products can be considered to consist either entirely or partially as emulsions (Chung and McClements, 2014). Emulsion-based food products have been intensely studied, exhibiting a wide range of physicochemical and organoleptic properties. The stability of emulsion systems is crucial for food processing, storage, and handling, hence the understanding and manipulation of bulk properties of the emulsion systems are of utmost importance for the food industry. Shelf-life, mouth-feel, and flow properties are largely determined by interactions among system constituents (Bellalta et al., 2012). An important challenge for food emulsion science is therefore to understand, monitor, and control the changes in colloidal interactions, rheology, and microstructure during processing and storage (Dalgleish, 2006). In this context, proteins have good emulsifying and emulsion stabilizing
* Corresponding author. Bioprocess Engineering Laboratory, Department of Biotechnology Universidad Tecnológica Metropolitana Las Palmeras 3360, P.O. Box 7800003, Ñuñoa, Santiago, Chile. E-mail address: [email protected] (R.N. Zúñiga).
https://doi.org/10.1016/j.jfoodeng.2019.07.005 Received 23 February 2019; Received in revised form 4 July 2019; Accepted 6 July 2019 Available online 09 July 2019 0260-8774/ © 2019 Elsevier Ltd. All rights reserved.
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2.2. Methods
lactalbumin, are particularly heat sensitive and can be affected by the application of heat in a targeted manner to make use of their potential to create or optimize food structures (Kulozik, 2007). According to Meklo and Foegeding (1999), the reaction products of heat treatment over WPI could be called “polymers” or “aggregates”. The former implies covalent bonding. The latter is a general term, which covers a range of intermolecular interactions. The structure and resulting functional properties of these protein-based structures depend on numerous conditions, including protein concentration, applied heating protocol, electrostatic interactions, and the presence of co-solutes (Foegeding, 2015; Guyomarc'h et al., 2015; Nicolai and Durand, 2013). As protein aggregates/polymers are complex structures, whose size may be as large as a few hundred nanometers, their behavior may differ from that of native proteins (Dombrowski et al., 2016; Rullier et al., 2008). Rheological behavior of whey protein based emulsions depend markedly on the concentration of native (undenatured) and aggregated proteins (Ҫakir-Fuller, 2015). According to Dombrowski et al. (2016), aggregates/polymers play a significant role in stabilizing interfaces, as particle size directly affects the diffusion processes and thus surface covering. Native proteins had shown faster stabilization of interfaces, mainly due to the slower diffusion of bigger particles such as aggregates toward the interface (Moussier et al., 2019). Even this interface is very thin (in the nanometer range), it represents a large surface area and controls to a great extent the physicochemical stability of emulsions (Berton-Carabin et al., 2018). Currently, the development of novel food-grade particles, such as heat-induced aggregates/polymers or microgels, capable of effectively stabilizing air/water interfaces has attracted considerable interest. However, no clear conclusions regarding the requirements of specific particle properties for interface stabilization could be drawn from literature, due to the complexity of the physicochemical properties of aggregates. In order to overcome this problem, some studies employed only one time-temperature protocol for the thermal generation of aggregates/polymers. Different ratios of native WPI and aggregates/ polymers were studied for interfacial, rheological, and foaming properties (Davis and Foegeding, 2004; Maticorena et al., 2018; Zhu and Damodaran, 1994). Changes in protein adsorption to the air/water interface and interfacial rheological properties as altered by the aggregates/polymers were hypothesized to cause differences in foaming properties (Davis and Foegeding, 2004). However, this approach has not been studied for WPI stabilized emulsions to date. A better understanding of the effect of thermal treatments on the physicochemical properties of WPI could lead to a rational control over functional performance, such as their ability to form and stabilize food emulsions. Inferring from the above-mentioned studies, we hypothesize that varying the ratio between native and denatured WPI will affect the specific physical properties of the emulsion and their stability could be increased by the use of WPI aggregates. Therefore, the objective of this work was to study the effect of denaturation degree of WPI dispersions used as surfactant on the rheological and stability properties of oil-inwater (O/W) emulsions.
2.2.1. Formation of WPI dispersions Dispersions of WPI at 10% w/w protein basis in ultra-pure water were prepared by slow stirring (200 rpm) at 25 °C for 2 h, using a magnetic stirrer, avoiding foam formation. The WPI dispersions were left at 4 °C for at least 12 h to allow complete hydration of the protein. 2.2.2. Heat aggregation of WPI dispersions Samples (3 mL) of WPI dispersions were heated in test tubes (inner diameter: 7 mm; thickness 1 mm; length: 120 mm) in order to induce protein denaturation and aggregation. The tubes were immersed in a water bath (Memmert, model Basic WNB, Germany) at a constant temperature of 70 °C for 15 min. After the heat treatment, samples were cooled to ambient temperature (25 °C). According to Ryan et al. (2013), near complete aggregation of denatured proteins can occur in a few minutes when heating WPI, depending on protein dispersion and heating process conditions. Confirmation of denaturation and aggregation of whey proteins after the thermal treatment was made through HPLC and DLS measurements, respectively. Various ratios of denatured WPI dispersions (15%, 30%, 45%, and 60%) were created by mixing native with denatured dispersions by volume (Davis and Foegeding, 2004; Maticorena et al., 2018). All procedures were done in triplicate. 2.2.3. Emulsion formation WPI-stabilized emulsions were prepared from a dispersed and an aqueous phase. The dispersed phase consisted of sunflower oil; whereas the aqueous phase corresponded to WPI dispersions. In order to elaborate the O/W emulsions, sunflower oil was added dropwise to WPI dispersions while mixing at 25 °C, using a rotor-stator homogenizer (Kinematika, model PT-MR 2500, Switzerland) at 3000 rpm for a duration of 3 min. Emulsions with different oil contents (10%, 20% and 30% w/w) were formulated. DLS measurements of protein dispersions were done before and after the homogenization process in order to confirm that no protein aggregation occurred as a consequence of the stirring applied. 2.3. Measurements 2.3.1. Determination of denaturation degree using HPLC analysis The denaturation degree of α-lactalbumin and β-lactoglobulin (main proteins of WPI) was determined by HPLC as described in detail by Zúñiga et al. (2010). According to this method, only native whey proteins that have a retention time identical as the standard fractions (α-lactalbumin, product L6010; β-lactoglobulin, product L3908, SigmaAldrich, Germany) are detected. Therefore, any changes in the tertiary structure of proteins would result in a drift of the retention time, and consequently, these molecules would not be detected as native (i.e. denatured). The denatured whey proteins were separated from the solution by shifting the pH value to 4.6 followed by centrifugation at 4130 rpm for 20 min. The supernatant (i.e. soluble proteins) was filtered through a membrane filter (0.45 μm pore size, Mixed Cellulose Ester, DISMIC 25AS, Advantec MFS Inc., Japan) and the concentration of native whey proteins in the supernatant was determined by HPLC coupled to a DAD detector at 220 nm (UHPLC, Dionex Ultimate 3000, Thermo Scientific, USA). A gradient of solvent A (water:acetonitrile:trifluoroacetic acid 900:100:1 v/v) and solvent B (water:acetonitrile:trifluoroacetic acid 100:900:1 v/v) was applied. The gradient started with 20% of solvent B and increased to 46% B over 30 min, and for the next 6 min the gradient returned to the initial conditions. Analysis was carried out at 25 °C, using a flow of 1.5 mL/min with a C18 5 μm 120 Å, 4.6 × 150 mm column (Acclaim™ 120, Thermo Scientific, USA). Integration and comparison of the elution profiles of WPI dispersions enabled the extents of denaturation to be determined. The
2. Materials and methods 2.1. Materials Whey protein isolate (WPI) (Provon 190, Glanbia Nutritionals Inc., USA) was used as the surface-active agent in emulsion formation. According to the supplier, the composition of WPI was 92.62% of protein (dry basis), 3.34% of moisture, and 2.99% of ash. The pH of the native WPI dispersion was about 6.3. A commercial brand of sunflower oil (Natura™, Córdoba, Argentina) was used as a dispersed phase. Ultrapure water (resistivity of 15 MΩ-cm) was employed for the preparation of all samples.
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percentage of denaturation (β-lg and α-la) was determined as the difference in the total amount of denaturable protein (Equation (1)).
DD (%) = 1 −
RDP × 100% TDP
where D is the protein bulk diffusion coefficient, t is the time elapsed since the formation of the oil/water interface, π is a numerical constant and C0 is the bulk protein concentration. Assuming that diffusion towards the interface controls the adsorption process, a plot of Π against time1/2 will be linear for short times and the diffusion rate constant (kdiff) can be derived from the slope of this plot (Dombrowski et al., 2016; Martínez et al., 2009; Maticorena et al., 2018).
(1)
where DD is the denaturation degree (%), RDP is the residual denaturable protein and TDP is the total denaturable protein in the WPI dispersion. It should be noted that this method measured the extent of protein denaturation relative to the level of denaturable protein in commercial WPI.
2.3.4. Microstructure of WPI-stabilized emulsions Emulsion microstructure was analyzed by means of light microscopy. This microstructural characterization was carried out in terms of droplet size and droplet size distribution. Droplet size was determined from images of the emulsions obtained with an inverted light microscope (Olympus, model CKX41, Japan), and using concave slides to avoid deformation of droplets. Images were recorded with a digital CCD camera (M-Shot Digital Imaging System, model MD90, China) connected to the microscope and image processing for droplet size analysis was carried out semi-automatically with the camera imaging software (M-Shot Digital Imaging System, version 9.0). The boundaries of droplets were manually traced and the image analysis software measured and calculated the size of the traced objects. The droplet sizes of the WPI-stabilized emulsions were measured directly after emulsification. A substantial number of droplets (N = 450) were counted to obtain statistical estimates of droplet size distribution in each sample. A droplet size distribution was generated by grouping the droplets into classes. The frequency distribution of droplet sizes was computed using Microsoft Excel (Microsoft® Excel, 2010). The relative frequency of any class interval was calculated as the number of droplets in that class (class frequency) divided by the total number of droplets and expressed as a percentage. The mean droplet diameter (DM) of the class with the highest frequency (i.e., mode) and the standard deviation of the class belonging to DM were calculated (Zúñiga et al., 2011).
2.3.2. Aggregate size measurements Aggregate sizes were determined by a dynamic light scattering (DLS) instrument (Zetasizer Nano-ZS, Malvern Instruments, Worcestershire, UK). The instrument was used in the backscattering configuration where detection is done at a scattering angle of 90°. Protein samples were diluted 100 times with ultrapure water to avoid an effect known as multiple scattering. The path length of the light was set automatically by the apparatus depending on the sample turbidity (attenuation). Dispersions were examined in a 1-cm path–length spectroscopic glass cell at 25 °C. The autocorrelation function was calculated from the fluctuation of the scattered intensity with time. From the polynomial fit of the logarithm of the correlation function, using the “cumulant” method, the diffusion coefficient of the molecules was calculated and hence the hydrodynamic diameter using the Stokes–Einstein equation (Zúñiga et al., 2010). 2.3.3. Dynamic interfacial tension (DIT) measurements between WPI dispersions and sunflower oil For the interfacial tension experiments, WPI dispersions were diluted to a factor of 1:10 using ultra-pure water. This dilution was required to bring out interfacial properties among samples and minimize the viscous effect on protein diffusion to the oil–liquid interface (Maticorena et al., 2018; Schmitt et al., 2007; Zúñiga et al., 2011). Changes in the WPI interfacial tension were measured with an automated contact angle goniometer (Ramé-Hart Inc., model 250-F4, NJ, USA). DIT measurement (τ) was based on the pendant drop method, where an axisymmetric drop (9 μL) of WPI dispersion at 25 °C was delivered and allowed to stand at the tip of the needle for 30 min inside a quartz container with 30 mL of oil to achieve protein adsorption at the oil-water interface. Drop images were captured at different time intervals with the CCD camera of the equipment. The DIT of the WPI dispersions was calculated by analyzing the profile of the drop by image analysis with the DROPimage Advanced software and then by fitting the Laplace equation to the drop shape. To validate the results, it was experimentally corroborated that the interfacial tension of the sunflower oil/pure water system (26.6 ± 0.5 mN/m) was almost the same as previously reported (26.45 ± 0.46 mN/m) for the same system (Pawlik et al., 2010). Results obtained from the DIT measurements were interpreted in terms of interfacial pressure, which was defined as the decrease in interfacial tension of a pure solvent caused by the addition of the protein:
Π = τw − τp
2.3.5. Rheological evaluation of WPI-stabilized emulsions Rheological tests were made in a controlled shear rate rheometer (Anton Paar, ReolabQC, Osterreich). Samples of emulsions were carefully poured into the rheometer cup and allowed to stand 2 min before shearing. The test temperature was set at 25 °C using a peltier controller (Peltier RheolabQC plus, C-PTD180/AIR/QC). The test geometry was a coaxial cylinder geometry conforming to DIN 53018. The rheological characterization of emulsions was performed using a flow curve test, where the shear rate was increased linearly from 0.1 to 100 s−1 during 400 s. Over the range of shear rates, the experimental flow curves of the emulsions were described by the Power Law model as follows:
σ = K × γ˙ n
where σ is the shear stress (Pa), K is the consistency index (Pa s ), γ˙ is the shear rate (s−1), and n is the flow behavior index (dimensionless). 2.3.6. Physical stability of the WPI-stabilized emulsions The stability of emulsions was determined by static multiple light scattering using a vertical scan analyzer (TurbiScan MA2000, Formulaction, France). The backscattering (BS) and transmission intensities of an incident near-infrared light (λ = 880 nm) were both measured automatically every 40 μm along the 70 mm cell height. The BS intensity variations along the sample height and over time gave a qualitative indication about the evolution of the distribution and movements of the droplets during destabilization. Emulsion samples (~7.5 mL) were placed into cylindrical glass tubes and stored at 5 °C. The BS from the WPI-stabilized emulsions were then measured at room temperature (25 °C) as a function of time. The Turbiscan Stability Index (TSI) is a statistical parameter used to estimate the suspension stability. The TSI consider the sum of all
(2)
where Π is the interfacial pressure of the dispersion (mN/m), τw is the interfacial tension of pure water (26.6 mN/m at 25 °C), and τp is the interfacial tension of the WPI dispersion (mN/m) at the same temperature. Protein diffusion towards interface can be characterized by Equation (3), where the change in surface pressure is correlated with time (Dombrowski et al., 2016; Martínez et al., 2009; Maticorena et al., 2018).
D × t 1/2 ⎞ Π = 2C0 ⎛ ⎝ π ⎠
(4) n
(3) 255
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3.2. Dynamic interfacial tension (DIT) measurements between WPI dispersions and oil
destabilization processes occurring in the emulsions. Thus, in order to compare between emulsion samples, results of stability are presented as TSI, which was calculated according to the following expression (Sun et al., 2015; Xu et al., 2016):
The rate at which a surfactant adsorbs onto a new created interface is one of the important factors to consider during emulsion formation. In this study, the DIT measurements decreased with time due to the diffusion and adsorption of protein at the oil/water interface (data not shown), decreasing thermodynamically unfavorable contact between oil and water. Surface pressure (Π) was calculated from the DIT data using Equation (2) (Fig. 2). Theoretically, the evolution of Π is the result of the adsorption of protein molecules from the bulk of the dispersion and adsorption at the oil/water interface. In this way, the driving force for adsorption phenomena is the difference in concentration between current surface and the surface at equilibrium conditions (Wang and Narsimhan, 2005). WPI adsorption at the oil/ water interface was always characterized by a rapid increase (~90 s) in Π (Fig. 2, insert) followed by a slow evolution towards an equilibrium value. This evolution is likely due to the occurrence of different phenomena, starting with an initial stage where fast protein diffusion and adsorption at the interface take place, followed by a slower step where the conformational rearrangement of the protein at the interface occurs (Tripp et al., 1995). Minimal differences can be seen when varying the degree of denaturation of WPI dispersions on Π kinetics (Fig. 2); with Π values ranged from about 2 to 17 mN/m. Native whey proteins can diffuse faster to the interface due to their smaller size compared with aggregates/ polymers. For highly diluted dispersions (0.0017% w/w), Moussier et al. (2019) found a shorter lag time (< 5 s) for native WPI than for thermal aggregated WPI (20 s). Lag time was defined as the value when the surface tension varied by more than 5% from its starting value, indicating a slower diffusion of bigger particles. For more concentrated dispersions (~0.1% w/w), Schmitt et al. (2007) argued that it is reasonable to expect similar adsorption kinetics at small time scales (~50 s), because of an initial decrease in surface tension is mainly due to the diffusion of native proteins. Thus, the increase in Π with time could be due to the diffusion and absorption of native protein at the oil/ water interface. Therefore, Π values will be dominated by the amount of native protein, but not by the physicochemical properties of the WPI aggregates. These results explain the trends observed in Fig. 2. It has been shown that during the thermal treatment of globular proteins denaturation/aggregation of protein molecules occurs (Zúñiga et al., 2010), and the rate and extent of this phenomenon is a function of processing (e.g., protein concentration, temperature-time relationship) and environmental conditions (e.g., pH, ionic strength, among others). Because all dispersions were subjected to the same thermal treatment and were under the same milieu condition, it is highly probable that the aggregates/polymers formed had identical physicochemical properties, not affecting significantly the surface properties of the dispersions. The diffusion rate constant (kdiff) represents the diffusional migration of proteins to the oil–water interface, behavior that in fact increases Π. Table 1 shows the kdiff values (obtained from Π against time1/2 plots) for native and thermally-treated WPI dispersions. Values of kdiff were in the range of 0.843–0.907 mN/m s0.5 and no statistical differences were found (p > 0.05) between kdiff values; albeit kdiff increased up to a denaturation degree of 30% and then decreased. A previous study of our research group showed that the highest kdiff values were obtained for native protein dispersions and there was a decreasing trend in kdiff with an increase in the aggregation degree (Maticorena et al., 2018). Values of kdiff obtained in this work were in the same order of magnitude as previous studies. Dombrowski et al. (2016) obtained kdiff values in the range of 0.50–0.79 mN/m s0.5 for diffusion of β-lactoglobulin (pH between 6.8 and 8.0 and NaCl addition between 20 and 130 mM) to the air/water interface, and Maticorena et al. (2018) obtained kdiff values ranging from 0.34 to 0.92 mN/m s0.5 for WPI dispersions with pH between 5.5 and 6.5, and from 0.53 to
h=H
TSI =
∑
∑h = 0 |BSt (h) − BSt − 1 (h)| H
t=1
(5)
where BS is the backscatter intensity, t is the scanning time, h is the height of the measurement per 40 μm, and H is the height of the sample in the measuring cell.
2.4. Statistical analysis of data Analysis of variance (ANOVA) tests were used to analyze the data at a confidence level of 95%, using the Statgraphics Centurion XVI software (Manugistics Inc., Statistical Graphics Corporation, Rockville, USA). Differences between samples were evaluated using Multiple Range Test, by means of the Least Significant Differences (LSD) multiple comparison method.
3. Results and discussion 3.1. Denaturation and aggregation of whey proteins Measurements by means of HPLC were done in order to determine changes in the tertiary structure of whey proteins (α-lactalbumin and βlactoglobulin, main proteins of WPI), and consequently, in the native state of them. According to the procedure employed, WPI dispersion presented 0% of denaturation, the elution profile for WPI dispersions at pH 4.6 and dispersions without a change in pH were the same (result not shown). Moussier et al. (2019) found a denaturation degree of 0.6% for commercial WPI, corroborating present results. The integration and comparison of the WPI elution profiles (Fig. 1) enabled the extents of denaturation to be determined. After the thermal treatment, the degree of denaturation of WPI dispersions was 75%. In addition, results from DLS measurements showed that size distribution curves of thermally treated WPI dispersions shifted to larger sizes, meaning that WPI aggregates were formed (Guyomarc'h et al., 2015; Nicolai and Durand, 2013; Zúñiga et al., 2010).
Absorbance at 220 nm (AU) 50 -lactoglobulin Native WPI Denatured WPI
40
30
-lactalbumin
20
10
0 5
10
15
20
25
30
Retention time (min) Fig. 1. Protein profiles of the supernatants from native WPI and denatured WPI dispersions. 256
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Interfacial pressure (mN/m) 16
Interfacial pressure (mN/m) 12
12
Eq. 2
10
Denaturation degree (%) 0 15 30 45 60
8
4
8 6 4 2 0
2
4 6 Time0.5 (s0.5)
8
10
0 0
200
400
600
800
1000 1200 1400 1600 1800
Time (s) Fig. 2. Evolution of the interfacial pressure for WPI dispersions at different denaturation degrees. Insert graph shows the evolution of the interfacial pressure for times employed in calculation of the diffusion rate constant.
1.01 mN/m s0.5 for dispersions with NaCl addition between 1% and 2% (w/w). The fact that the kdiff values obtained in this study were independent of the denaturation degree of protein dispersion confirms that native protein dominates the adsorption phenomena and the change in interfacial pressure at small times scale.
size distributions, with emulsions formulated at 30% oil showing the widest size distribution. Although only slight differences were found in the relationship between Π and protein denaturation degree (Fig. 2), the microstructure of the O/W emulsions stabilized by thermally treated WPI dispersions presented clear differences regarding droplet sizes. Interfacial tension measurements were done at a fixed interfacial area (i.e., given by the volume of the pendant drop), but the amount of interfacial area created during homogenization processes relies not only on the capacity of surfactant of decreasing interfacial tension, but also on its concentration (McClements, 2005). Concentration of native protein decreases as the denaturation degree increases, thus diminishing the capacity of WPI dispersions to stabilize the new created interfaces during the homogenization process, which finally generated larger sizes and wider size distribution of oil droplets, as observed in Figs. 3 and 4, respectively. In addition, the apparent viscosity of the continuous phase of the emulsions influences its flow behavior properties during homogenization. As the apparent viscosity of the continuous phase increased with denaturation degree (see point 3.4), the efficiency of the homogenization process could be reduced, resulting in the formation of large oil droplets. According to McClements (2005), at sufficiently high shear rates (as in a rotor stator homogenizer) oil droplets elongated and broken up into smaller droplets, which depends on the ratio of the apparent viscosities of the droplet and continuous phase (μD/μC). Changes in droplet size distributions are also coincident with the steepest change in consistency coefficient observed in Fig. 5.
3.3. Microstructure of WPI-stabilized emulsions The droplet characteristics, in particular droplet size, are extremely important to obtain stable emulsions. In addition, it has been regarded as an indirect method to determine the emulsification ability of proteins. Clear differences in droplet sizes can be observed both qualitatively from micrographs (Fig. 3), and quantitatively from size distribution curves (Fig. 4), where larger sizes of droplets were obtained with an increase in the denaturation degree. The appearance of gray “noise” in the background of the micrographs corresponds to the formation of protein aggregates during thermal treatment, which increases in number as the denaturation degree increased (Fig. 3). At the lowest oil content (10% w/w), no differences were found in droplet sizes at denaturation degrees up to 30%. Above this threshold, droplet sizes augmented with the denaturation degree of the WPI dispersions, moving the size distribution curves to larger sizes (Fig. 4). The same behavior was observed for emulsions fabricated with 20% and 30% oil, but in these cases, droplets increased their sizes above 15% of protein denaturation. Higher levels of denaturation generated wider droplet Table 1 Diffusion rate constant values for the diffusional interfacial pressure model. Parameter
Denaturation degree (%) 0 0.5
kdiff (mN/m s R2 *
)
0.843 ± 0.039 0.973
15 a
0.863 ± 0.096 0.971
30 a
0.907 ± 0.026 0.972
Different letters indicate significant differences (p < 0.05) for different denaturation degrees. 257
45 a
60 a
0.868 ± 0.050 0.976
0.850 ± 0.037a 0.973
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Relative frequency (%) 35
Oil content 10% (w/w) 30
Denaturation degree (%)
25
0 15 30 45
20
60
15 10 5 0 0
10
20
30
40
Droplet diameter ( m) Relative frequency (%) 40
Oil content 20% (w/w)
Denaturation degree (%) 0 15 30 45 60
30
20
10
0
Fig. 3. Gallery of images from optical microscopy of O/W emulsions stabilized by WPI with different denaturation degrees of protein and oil contents. Images are presented without digital processing.
0
10
20
30
40
Droplet diameter ( m) Relative frequency (%)
For all size distributions in Fig. 4, the mean droplet diameter (DM) of the class with the highest frequency and their corresponding standard deviation, were calculated (Table 2). In agreement with previous discussions, both denaturation degree and oil content had significant effects over the DM values. For emulsions with 10% of oil, DM values were significantly different (p < 0.05) above 30% of denaturation, but for emulsions with 20% and 30% oil, DM values were significantly different (p < 0.05) over 15% of denaturation (Table 2). Oil content of emulsions also influenced droplet diameters; DM values were statistically different (p < 0.05) at oil contents over 10% for denaturation degrees of 0% and 15%, whereas at 30% of denaturation, the three levels of oil presented different DM values, and for 45% and 60% of denaturation, DM values were statistically higher (p < 0.05) at 30% of oil. In this study, the droplet size of emulsions stabilized by thermallytreated whey proteins will be determined for the amount of native protein and not by the physicochemical properties of aggregates/ polymers (e.g., size, morphology, surface charge and surface hydrophobicity), which explains the trends observed in Figs. 3 and 4. It is probable that physicochemical properties of aggregates/polymers could affect the rheological and physical stability of O/W emulsions. In our case, only the amount of aggregates affected the rheological and physical stability of emulsions, because the thermal treatment was the same for all WPI dispersions. In summary, when the amount of native protein is not enough to stabilize new interfaces, larger droplet sizes are obtained, explaining the trends observed in Figs. 3 and 4, and results from Table 2. In the
50
Oil content 30% (w/w)
Denaturation degree (%) 0 15 30 45 60
40
30
20
10
0 0
20
40
60
Droplet diameter ( m) Fig. 4. Relative frequency distribution curves of oil droplet sizes for O/W emulsions stabilized by WPI with different denaturation degrees and oil contents.
same way, when the oil content in the formulation of emulsions was higher, there was not enough native protein to cover the new interfaces created. 258
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Consistency coefficient (Pa sn) 0,10
networks between oil droplets and the alignment of aggregates with the flow field. The values obtained for the consistency coefficient (K) were plotted against the denaturation degree of WPI dispersions for the three oil concentrations used (Fig. 5). It can be observed that the increase in the denaturation degree as well as the oil content augmented the values of K. In general, for denaturation degrees over 30%, the increase in K values was more evident. An exponential relationship (R2 between 0.990 and 0.996) was found between denaturation degree and K values (Fig. 5), suggesting a strong dependence of the rheology of the WPIstabilized emulsions with the volumetric fraction of the thermally formed aggregates. Recently, Maticorena et al. (2018) observed that the higher the aggregation degree, the higher was the apparent viscosity of WPI dispersions, because of the increased interactions between the reactive groups of the protein molecules, the aqueous phase, and the higher volumetric fraction of aggregates. The hydrodynamic size of the protein molecules increased with the aggregation degree (Zúñiga et al., 2010), hence increasing apparent viscosity due to the formation of aggregates/polymers via sulfhydryl-disulfide interchange reactions (Zhu and Damodaran, 1994). Large aggregates/polymers (or microgels) have the capacity to trap solvent in their porous structure, increasing the apparent viscosity of protein dispersions (Dickinson, 2017; Murphy et al., 2016). Subsequently, as apparent viscosity of the continuous phase increased, the emulsion viscosity increased as well. The consistency coefficient also increased with oil content. For emulsions with lower oil contents, the particles are far apart and the inter-particle interactions are relatively weaker. As oil content increases, the particles become closer, which leads to the packing of the oil droplets, and the inter-particle interactions get stronger, giving a non-Newtonian behavior. The attractive forces between droplets drive the formation of flocs, which normally could evolve into a space-filling particulate network (Bellalta et al., 2012). This, in turn, increased the apparent viscosity of emulsions. According to the above explanation, the apparent viscosity of the WPI-stabilized emulsions was influenced by both denaturation degree of the WPI in the continuous phase and the amount of oil content in the dispersed phase.
Oil content (% w/w) 10 20 30
0,08
0,06
0,04
0,02
0,00 0
10
20
30
40
50
60
Denaturation degree (%) Fig. 5. Consistency coefficient of O/W emulsions stabilized by WPI with different denaturation degrees and oil contents. Lines shows an exponential relationship between denaturation degree and consistency coefficient.
3.4. Rheological behavior of the WPI-stabilized emulsions The results obtained from the rheological tests indicated that higher values of shear stress were obtained with an increase in the denaturation degree and oil content when emulsions were subjected to shear forces. At denaturation degrees over 30%, the increase in shear stress values was more significant. Across the range of shear rates studied, all emulsions behaved as shear-thinning fluids. In order to verify and quantify this fact, the data from rheograms of the emulsions (not shown) were fitted to the Power Law model (Equation (4)), finding a good agreement between the experimental data and the model (R2 above 0.970). Flow behavior index (n) values were in the range of 0.85 to 0.64, confirming the shear-thinning behavior of the emulsions. Generally speaking, the rheological properties of emulsions are mainly determined by the volumetric fraction of the dispersed phase and their size and size distribution. However, surfactants may also play an important role in the rheological behavior of emulsions. Aggregation stability of droplets is determined mainly by the nature and concentration of a surfactant in the system creating and stabilizing the emulsion (Derkach, 2009). The shear-thinning behavior of emulsions represents a structural breakdown that may occur because of the spatial redistribution of the particles under a shear field, the alignment of nonspherical particles with the flow field, or the deformation and disruption of flocs (McClements, 2005). When an initial external force is applied to the system, the flocs or aggregates present greater resistance to flow than the individual droplets. However, as the shear rate is increased, the aggregates are deformed and disrupted (Ҫakir-Fuller, 2015) For WPI-stabilized emulsions, pseudoplasticity may be attributed to intermolecular interactions resulting from the attractions between adjacent aggregated molecules with the formation of weak transient
3.5. Physical stability of the WPI-stabilized emulsions Emulsion stability can be associated with no discernible changes from a thermodynamically stable state and/or no changes of droplets in their size distribution, state of aggregation, or spatial arrangement within the emulsion, over the time-scale of study (McClements, 2005). Modification of a backscattering (BS) signal can occur as a function of time and particle migration or size change, and it is graphically reported in the form BS increase or BS decrease (Celia et al., 2009). Results are presented as BS profiles at the end of the storage period (20 days) (Fig. 6a). BS profiles of emulsions stabilized by native WPI showed a different pattern for emulsions stabilized by thermally treated WPI, at three oil concentrations. For emulsions stabilized by thermally treated WPI creaming of oil droplets and sedimentation of protein particles could be seen on the top and bottom of the tube; no detection of flocculation or coalescence was observed from BS curves. When
Table 2 Mean droplet diameter (μm) and standard deviation of the class with the highest frequency for O/W emulsions stabilized by whey protein isolatea. Oil content (% w/w)
Denaturation degree (%) 0
10 20 30
15 aA
3.26 ± 0.41 4.55 ± 0.39aB 4.64 ± 0.65aB
30 aA
45 aA
3.25 ± 0.40 4.70 ± 0.46aB 4.81 ± 0.68aB
3.23 ± 0.42 5.02 ± 0.67bB 7.38 ± 1.40bC
60 bA
7.74 ± 0.45 7.25 ± 0.77cA 8.53 ± 1.41cB
9.25 ± 0.71cA 9.15 ± 0.66dA 14.59 ± 1.68dB
a Different lower case letters indicate significant differences (p < 0.05) between denaturation degrees, whereas different upper case letters indicate significant differences (p < 0.05) between oil contents.
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a
b Backscattering (%) Denaturation degree (%)
Oil content 10% (w/w) 0,6
0 15 30 45 60
TSI (-) 12 Oil content 10% (w/w)
Denaturation degree (%)
10
0 20 40 60 80
8
0,4
6 4 0,2
2 0
0,0 0
20
40
60
0
5
Tube heigh (mm)
10
15
20
Time (day)
Backscattering (%) Denaturation degree (%)
Oil content 20% (w/w) 0,6
0 15 30 45 60
0,4
TSI (-) 5 Oil content 20% (w/w)
Denaturation degree (%) 0 20 40 60 80
4
3
2 0,2
1
0
0,0 0
10
20
30
40
50
60
70
0
5
Tube heigh (mm)
10
15
20
Time (day)
Backscattering (%)
TSI (-) 5
Oil content 30% (w/w)
Oil content 30% (w/w)
Denaturation degree (%)
0,6
0 15 30 45 60
0,4
Denaturation degree (%)
4
0 20 40 60 80
3
2 0,2
1
0
0,0 0
10
20
30
40
50
60
70
0
5
10
15
20
Time (day)
Tube heigh (mm)
Fig. 6. (a) Backscattering profiles as a function of the tube length after 20 days and (b) Turbiscan stability index (TSI) of WPI-stabilized O/W emulsions with different denaturation degrees and oil contents.
proteins are used to stabilize emulsions, they tend to create charged and stable interfaces; in other words, they created structured interfacial layers with repulsive forces between them (Derkach, 2009; Walstra, 2003). These protein-coated interfacial layers decreased the flocculation, interface breakdown, and coalescence. Emulsion stability was expressed as TSI, where the lower TSI values correspond to the more stable system. The TSI values increased with storage time for all experimental conditions, indicating that WPI-stabilized emulsions are prone to physical destabilization (Fig. 6b). Emulsions stabilized with native WPI showed the highest TSI values at the three oil contents employed. Stability of emulsions was increased with denaturation degree up to 45%, independent of the oil content
Table 3 Turbiscan stability index (TSI) for O/W emulsions stabilized by whey protein isolate at 20 days of storage at 5 °C. Oil content (% w/w)
10 20 30
Denaturation degree (%) 0
15
30
45
60
10.81 4.35 3.76
2.73 2.87 3.36
1.99 2.06 2.26
1.73 1.82 1.85
1.90 2.25 2.95
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(Fig. 6 and Table 3). At 60% of denaturation, TSI values increased. These results can be explained in terms of the microstructure of the emulsions and rheology of the continuous phase. In general, smaller particles have a lower tendency to cream. According to Stokes law, the creaming velocity of a droplet is proportional to its radius squared, and a bigger radius would have a greater tendency to aggregate, leading to a greater probability of collision (McClements, 2005). On the other hand, the presence of protein aggregates increased the apparent viscosity of the continuous phase (Maticorena et al., 2018), which contributes to emulsion stability by decreasing the rate of droplet movement. For emulsions stabilized with native WPI or denatured up to 30%, droplet size distributions and mean droplet diameter of emulsions were quite similar (Fig. 4 and Table 2). However, the consistency coefficient increased in an exponential relationship with denaturation degree (Fig. 5), giving a better stability when denaturation degree increased up to 30%. At 45% of denaturation, the lowest TSI values were found. Although size distributions shifted to larger diameters (Fig. 4) and mean droplet diameters were statistically larger than lower denaturation degrees (Table 2), these emulsions had a significant increase in consistency coefficient (Fig. 5). This probably caused the best stability among all emulsions. TSI values found for emulsions with 60% of WPI denaturation can be attributed to the precipitation of protein and creaming of oil on the bottom and top of the tube, respectively (Fig. 5a). At this level of denaturation, the biggest droplets were found (Fig. 4). Probably, the volume of protein particles was too high, causing the precipitation of the aggregates. From the microstructural, rheological and stability results presented in this study, it is possible to establish that mixing native with denatured WPI can be considered as a strategy to tailor physical properties of food emulsions in order to create new protein-based products.
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4. Conclusions The diffusional migration of proteins to the oil–water interface was slightly affected by the denaturation degree, confirming that native proteins play a dominant role in the decrease of interfacial tension at short times. The microstructure of emulsions was affected by the denaturation degree, with larger droplet diameters obtained when native protein was less than 70%. Mixing of native and denatured/aggregated WPI dispersions can be an alternative to improve emulsion rheology and stability, because the fraction of native protein dominates the adsorption process at the oil–water interface, and the denatured/aggregated fraction gives the necessary apparent viscosity for stabilizing emulsions. These results will eventually lead to a better understanding of the colloidal basis of emulsion stability, thus having important implications for the design and production of food emulsions. Conflicts of interest All authors declare no conflict of interest. Acknowledgements R.N. Zúñiga thanks to the financial support of CONICYT by means of the FONDECYT Project 1140031. References Bellalta, P., Troncoso, E., Zúñiga, R.N., Aguilera, J.M., 2012. Rheological and microstructural characterization of WPI-stabilized O/W emulsions exhibiting time-dependent flow behavior. LWT – Food Science and Technology 46, 237–381. Berton-Carabin, C.C., Sagis, L., Schroën, K., 2018. Formation, structure, and functionality of interfacial layers in food emulsions. Annual Review of Food Science and
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