foams prepared from whey protein isolate and egg white protein: 1. physical, microstructural, and...

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JFS E: Food Engineering and Physical Properties

Foams Prepared from Whey Protein Isolateand Egg White Protein: 1. Physical,Microstructural, and Interfacial PropertiesXIN YANG, TRISTAN K. BERRY, AND E. ALLEN FOEGEDING

ABSTRACT: Foams were prepared from whey protein isolate (WPI), egg white protein (EWP), and combinations ofthe 2 (WPI/EWP), with physical properties of foams (overrun, drainage 1/2 life, and yield stress), air/water inter-faces (interfacial tension and interfacial dilatational elasticity), and foam microstructure (bubble size and dynamicchange of bubble count per area) investigated. Foams made from EWP had higher yield stress and stability (drainage1/2 life) than those made from WPI. Foams made from mixtures of EWP and WPI had intermediate values. Foam sta-bility could be explained based on solution viscosity, interfacial characteristics, and initial bubble size. Likewise,foam yield stress was associated with interfacial dilatational elastic moduli, mean bubble diameter, and air phasefraction. Foams made from WPI or WPI/EWP combinations formed master curves for stability and yield stress whennormalized according to the above-mentioned properties. However, EWP foams were excluded from the commontrends observed for WPI and WPI/EWP combination foams. Changes in interfacial tension showed that even the low-est level of WPI substitution (25% WPI) was enough to cause the temporal pattern of interfacial tension to mimic thepattern of WPI instead of EWP, suggesting that whey proteins dominated the interface. The higher foam yield stressand drainage stability of EWP foams appears to be due to forming smaller, more stable bubbles, that are packedtogether into structures that are more resistant to deformation than those of WPI foams.

Keywords: egg, interfacial tension, microstructure, protein functionality, whey protein isolate

Introduction

Foaming is a common technique used to create unique struc-tures and textures in foods (Campbell and Mougeot 1999). Pro-

teins, such as egg white protein (EWP) and whey protein isolate(WPI), are surfactant molecules that contribute to the formationand stabilization of foams. The amount of air incorporation (foam-ability) is similar between EWP and WPI foams but differences existin foam stability and rheological properties (DeVilbiss and others1974; Pernell and others 2000, 2002; Davis and Foegeding 2007).Whey protein foams are less stable (that is, shorter drainage time)than EWP foams formed at the same protein concentration (Aryanaand others 2002; Davis and Foegeding 2007). The precise reasonfor differences in foam stability has not been established; how-ever, models describing drainage from polyhedral foams includevariable such as: continuous phase density and viscosity, lamellaethickness and height, bubble radius, and difference between capil-lary and disjoining pressures (Dickinson 1992; Damodaran 2005).

While overrun and foam stability are typical properties mea-sured to characterize foams, yield stress is also of importance(Pernell and others 2000). As with drainage stability, EWP producesfoams with higher yield stress values than WPI foams (Pernell andother 2000; Davis and Foegeding 2007). Yield stress has been mod-eled in polyhedral foams and concentrated emulsions based on: in-terfacial tension, bubble radius, and volume fraction (Princen andKiss 1989). In protein foams, a positive relationship has been es-tablished between yield stress and interfacial dilatational elasticity

MS 20080651 Submitted 7/28/2008, Accepted 3/22/2009. Authors are withDept. of Food, Bioprocessing and Nutrition Sciences, North Carolina StateUniv., Raleigh, NC 27695-7624, U.S.A. Direct inquiries to author Foegeding(E-mail: allen [email protected]).

rather than interfacial tension (Davis and others 2004, 2005; Davisand Foegeding 2004), which is a logical expansion of the Princenand Kiss (1989) model to more complex protein foams.

Since bubble radius is a component of foam stability and yieldstress, a measurement of bubble size is required to understandthese properties. Bubble size measurements are difficult sincefoams are thermodynamically unstable and continuously changethrough creaming, coalescence, or disproportionation (Murray2007; Dickinson and others 2002). Confocal laser scanning mi-croscopy (CLSM) is useful for foams because it can image thin sec-tions of a thick specimen (Murray 2007). Dynamic changes of foammicrostructure have been investigated using CLSM and correlatedto destabilization processes of bubbles (Lau and Dickinson 2005;Raikos and others 2007).

The foaming functionality of egg white appears to result fromcomplex interactions among the individual proteins rather than at-tributable to a single protein component (Johnson and Zabik 1981;Dickinson 1992). However, the interactions are still not completelyunderstood (Damodaran 2005). In foams made from mixtures ofthe 2 major whey proteins, β-lactoglobulin and α-lactalbumin, in-creasing the amount of β-lactoglobulin causes a linear increasein overrun and a nonlinear increase in yield stress (Luck andothers 2002), suggesting a mixed protein interface. Combinationsof whey protein concentrate and egg white protein were shownto have a synergistic effect on foam stability (Aryana and others2002); suggesting that WPI and EWP mixtures may show improvedfunctionality.

While differences between foaming properties of egg white andwhey proteins have long been observed (Peter and Bell 1930),there is still a lack of understanding of precisely what causes thesedifferences. Therefore, the objective of this investigation was to

C© 2009 Institute of Food Technologists R© Vol. 74, Nr. 5, 2009—JOURNAL OF FOOD SCIENCE E259doi: 10.1111/j.1750-3841.2009.01179.xFurther reproduction without permission is prohibited

E:FoodEngineering&PhysicalProperties

Whey protein and egg white foams . . .

determine what properties contribute to the differences in EWPand WPI foams. A complete characterization of foams requires de-termining how macroscopic properties (overrun, stability, and yieldstress) are determined by structures formed on the microscopicscale and at the molecular level (Rodrıguez Patino and others 2008).This was done by determining how combinations of EWP and WPIalter the physical properties observed at the macroscopic scale(foam overrun, stability, and yield stress) and relating these prop-erties to measurements of foam microstructure (bubble size anddynamic changes of bubble count per area) and the air–water inter-faces (interfacial tension and dilatational elasticity). The effects ofsugar on foam properties and transformation from a liquid to solidfoam will be covered in a separate article.

Materials and Methods

MaterialsTwo commercial samples of whey protein isolate (WPI 1 and

WPI 2) were obtained. Provon 190 (91% protein, dry basis) was sup-plied by Glanbia Foods Inc. (Twin Falls, Idaho, U.S.A.) and BiPro(93% protein, dry basis) was supplied by Davisco Foods Int. Inc. (LeSueur, Minn., U.S.A.). Both WPIs were stored at room temperature(22 ± 2 ◦C). Spray dried egg white protein (P-18J, 81% protein, drybasis) was obtained from Henningsen Foods Inc. (Omaha, Nebr.,U.S.A.) and stored at 4 ◦C. For the experiments of foams and in-terfaces, EWPs to be mixed with 2 sources of WPIs were obtainedfrom 2 production lots. The sodium hydroxide (ACS pellets) waspurchased from Fisher Scientific Inc. (Fair Lawn, N.J., U.S.A.). Hy-drochloric acid was obtained from Mallinckrodt Inc. (Hazelwood,Mo., U.S.A.). Sodium fluorescein was obtained from Sigma-Aldrich(St. Louis, Mo., U.S.A.). Deionized water was from a Dracor WaterSystems (Durham, N.C., U.S.A.) purification system, with resistivityof ≥18.2 M� cm.

Protein solutionsProtein powders were mixed with deionized water and stirred

overnight (14 to 16 h) at room temperature (22 ± 2 ◦C) to allow forfull hydration. Before final adjustment to 10% (w/v) protein, the pHwas adjusted to 7 using 1N NaOH or 1N HCl. Protein solutions of5 WPI/EWP ratios (100/0, 75/25, 50/50, 25/75, and 0/100) were pre-pared by mixing WPI and EWP solutions.

Foam generationA Kitchen Aid Ultra Power Mixer (Kitchen Aid, St. Joseph’s, Mich.,

U.S.A.) with a 4.3 L stationary bowl and rotating beaters was usedto generate the foams from protein solutions. A total of 200 mL ofprotein solutions were whipped for 20 min at a speed setting of 8(planetary rpm of 225 and beater rpm of 737). Each treatment wasreplicated a minimum of 3 times.

OverrunOverrun was measured according to the method of Phillips and

others (1987). Foam was gently scooped into a standard weigh boat(100 mL), leveled using a rubber spatula, and weighed. This pro-cess was repeated a minimum of 10 times per foam and was com-pleted within 20 min after whipping. The 10 overrun data pointswere found to be stable over the measurement time (Figure 1). Themean of 10 weights was used for overrun and air phase fraction cal-culations according to Eq. 1 and 2 (Campbell and Mougeot 1999).

%Overrun = (wt.100 mL solution) − (wt.100 mL foam)wt.100 mL foam

× 100 (1)

Air phase fraction(φ) = % overrun(% overrun + 100)

(2)

Each treatment was replicated a minimum of 3 times.

Yield stressYield stress was measured using a vane attachment to a Brook-

field 25xLVTDV-ICP viscometer (Brookfield Engineering Lab. Inc.,Middleboro, Mass., U.S.A.) (Pernell and others 2000). Immediatelyafter foam generation, the vane (10 mm in diameter and 40 mmin length) was gently inserted into the foam until the top edge waseven with the foam surface. The vane was then rotated at a speedof 0.3 rpm. Maximum torque response (M 0) was used to calculateyield stress according Eq. 3 (Dzuy and Boger 1985; Steffe 1992).

τ0 = M0(hd + 1

6

) (πd 3

2

) (3)

where τ0 is the yield stress, and h and d are the height and diameterof the vane. Three consecutive measurements throughout the bowlwere completed within 5 min after foam generation and averaged.A minimum of 3 replications were conducted for each treatment.

Foam stability (drainage 1/2 life)Foam stability was measured by recording the length of time re-

quired for half of the prefoam mass to drain (Phillips and others1990). Special bowls with a 6-mm diameter hole were used for sta-bility measurements. After foam generation, the bowl was placed ina ring stand over a scale with a weigh boat and the hole uncovered.The time necessary for half the mass to drain was recorded as thedrainage 1/2 life. A longer drainage 1/2 life corresponds to greaterfoam stability. Each treatment was replicated for a minimum of 3times to obtain average drainage 1/2 life.

Viscosity measurementsViscosity of prefoam protein solutions was measured on a con-

trolled stress rheometer (StressTech, Reologica Instruments AB,Lund, Sweden) using cup and bob geometry (measuring systemCCE25) according to the method of Davis and Foegeding (2004).After a preshear at 50 s−1 for 30 s, viscosity was tested over a range

Figure 1 --- Sequential overrun measurements of foamsprepared from 10% (w/v) protein solutions of 5 WPI/EWPratios at pH 7. Overrun measurements were completedwithin 20 min. Two sources of whey protein isolates wereutilized: WPI 1 and WPI 2. WPI 1: � WPI, �75WPI/25EWP,� 50WPI/50EWP, � 25WPI/75EWP, � EWP; WPI 2: ◦ WPI,� 75WPI/25EWP, � 50WPI/50EWP, ♦ 25WPI/75EWP, � EWP.

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of shear rates (0.5 s−1 to 225 s−1). The rheological behavior of pro-tein solutions was described by a power law model as shown inEq. 4:

σ = K.nγ (4)

where σ and.γ are shear stress and shear rate, and K and n are con-

sistency constant and flow behavior index, respectively. All mea-surements were carried out at room temperature (22 ± 2 ◦C) andreplicated a minimum of 3 times.

Interfacial tensionInterfacial tension of prefoam solution bubbles was measured

using a pendant drop method (Myrvold and Hansen 1998). Anautomated contact angle goniometer (Rame-Hart Inc., MountainLakes, N.J., U.S.A.) was used for data collection and calculationsin combination with the DROPimage computer program. A 16-μLpendant drop of prefoam solution was generated by a computer-controlled syringe from a stainless-steel capillary into an environ-mental chamber with standing water at its bottom to minimizeevaporation. A digital camera captured the image of the pendantdrop every 2 s for a total of 600 s and interfacial tension wascalculated based on shape parameters. All samples were equili-brated to room temperature (22 ± 2 ◦C) before measurement. Val-ues reported are the averages of a minimum of 3 replications. Thesystem was calibrated using high-performance liquid chromatog-raphy (HPLC) water with an interfacial tension of 72.3 mN/m atroom temperature (22 ± 2 ◦C). The estimated experimental error is±1 mN/m. Values reported represent a minimum of 3 replications.

Interfacial dilatational modulusTo measure dilatational viscoelasticity of the interfaces, sinu-

soidal oscillations of the drops’ areas (Myrvold and Hansen 1998)were increased by volume amplitude of 0.5 μL at a frequency of0.1Hz. The resulting changes in interfacial tension and interfacialarea were collected and used to calculate the dilatational modu-lus utilizing the DROPimage software. Drops were suspended for300 s before measurement. Values reported are the averages of aminimum of 3 replications.

Density determinationDROPimage software requires inputs of component phase den-

sities to calculate interfacial tension from drop shape analysis.A Mettler-Toledo DE40 density meter (Mettler-Toledo, Columbus,Ohio, U.S.A.) equipped with a viscosity correction card was used tomeasure the density of each solution at room temperature (22 ±2 ◦C). The accuracy of the instrument is 1 × 10−4 g/cm3. Each solu-tion was evaluated in triplicate and averaged.

Confocal microscopy—protein foamConfocal imaging of protein foams was based on the method of

Pernell and others (2002). Sodium fluorescein (Sigma-Aldrich) wasadded at a level of 0.1 mM to the protein solutions used for mi-croscopy directly before foaming. The fluorescein dissolved read-ily in the protein solutions before mixing commenced. After whip-ping, a small amount of foam was loaded into a single-welled mi-croscope slide with a nr 1.5 coverslip attached to the bottom usingsilicon grease and immediately used for microscope imaging. Aninverted Leica DM IRBE (Leica Microsystems, Wetzlar, Germany)confocal laser-scanning microscope imaged the samples. An argonlaser excited samples at 488 nm, and light was collected at a rangefrom 500 to 550 nm, with a transmitted light differential interfer-

ence contrast (DIC) image recorded simultaneously. A HC PL FLU-OTAR 10.0×, with a 0.30 numerical aperture, was the objective usedfor 10× magnification. Collected images were viewed using Leicaconfocal software (version 2.61, Leica Microsystems).

Images were collected as a series of z-stacks for each foam. A z-stack was defined as the range from where bubbles were first visi-ble to where they no longer appeared as separate entities (generallyabout 80 μm in depth). Software calculated the optimal number ofsections for the stack (generally around 22 sections), and the entirestack was imaged. The field of vision was then moved to anotherrandom position in the foam and repeated until 5 stacks were com-pleted (total imaging time of about 10 min).

Time-lapse data were also collected for all foam samples. Di-rectly after foam preparation and slide loading, a single plane wasfocused into the foam. Images were taken every 5 s for 10 min,with both confocal and DIC images recorded simultaneously. Thiswas completed once per prepared slide. Leica software was used tocombine the 120 time-lapse images per treatment into a time-lapsevideo.

Image analysisImage analysis of confocal images was performed using Meta-

Morph Imaging System software, version 6.1 (Molecular Devices,Downington, Pa., U.S.A.). The image was thresholded to convertit to binary, allowing objects (air bubbles) to stand out against the

Table 1 --- ANOVA of main factor effects with WPI 1 andWPI 2 data analyzed jointly.

Source of variance Properties F P-value

WPI/EWP ratio Overrun 1.51 0.238Yield stress 396 < 0.0001Drainage 1/2 life 144 < 0.0001Viscosity 4.40 0.0103Interfacial tension 71.2 < 0.0001Interfacial elasticity 59.8 < 0.0001Mean bubble area 24.2 < 0.0001Median bubble area 24.3 < 0.0001

WPI source Overrun 44.4 < 0.0001Yield stress 2048 < 0.0001Drainage 1/2 life 456 < 0.0001Viscosity 16.4 0.0006Interfacial tension 26.9 < 0.0001Interfacial elasticity 546 < 0.0001Mean bubble area 75.3 < 0.0001Median bubble area 124 < 0.0001

Table 2 --- ANOVA of main factor effects with WPI 1 andWPI 2 data analyzed separately.

Source ofvariance Properties WPI F P-value

WPI/EWP ratio Overrun WPI 1 1.83 0.200WPI 2 1.36 0.315

Yield stress WPI 1 282 < 0.0001WPI 2 254 < 0.0001

Drainage 1/2 life WPI 1 79.4 < 0.0001WPI 2 561 < 0.0001

Viscosity WPI 1 5.54 0.0129WPI 2 0.950 0.477

Interfacial tension WPI 1 43.4 < 0.0001WPI 2 28.9 < 0.0001

Interfacial elasticity WPI 1 97.9 < 0.0001WPI 2 7.31 0.00180

Mean bubble area WPI 1 11.1 < 0.0001WPI 2 17.2 < 0.0001

Median bubble area WPI 1 13.6 < 0.0001WPI 2 26.3 < 0.0001

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background aqueous phase. Overlapping or touching bubbles wereseparated using a “cut” feature that allowed manual separation ofobjects when necessary. Because of the light reflection, pixels maybe missing from the center of some small bubbles (e.g., the trans-parent triangle areas indicated in Figure 5). In this case, a “join” fea-ture was used to manually outline these bubbles and to fill in theirbroken centers. An integrated morphometry analysis feature wasused to measure the object (bubble) area and object shape factorin each image. Shape factor was determined by the following equa-tion:

Shape factor = 4π area

perimeter2 (5)

A shape factor of 1 indicated a perfectly spherical bubble, whilelower shape factors showed a deviation from roundness. The edgebubbles with less than 50% of their estimated area visible weremanually deselected from analysis, preventing skewing the bubblesizes to smaller areas due to only a small portion of the bubble be-

Figure 2 --- Association between the interfacial elasticity(E′ ) and foam yield stress. Foams were prepared from 10%(w/v) protein solutions of 5 WPI/EWP ratios at pH 7. WPI1: � WPI, �75WPI/25EWP, � 50WPI/50EWP, � 25WPI/75EWP, � EWP; WPI 2: ◦ WPI, � 75WPI/25EWP, � 50WPI/50EWP, ♦ 25WPI/75EWP, � EWP. Dash line is drawn man-ually to show the association between the 2 parameters.Error bars represent 1 standard deviation of mean values.

Figure 3 --- Associations between foam drainage 1/2 life and prefoam solution properties for 10% (w/v) protein solu-tions of 5 WPI/EWP ratios at pH 7. μ is the solution apparent viscosity at a shear rate of 8.5 s−1; E′ is the interfacialelastic molulus; γ is the interfacial tension. Figure A is for the association between foam drainage 1/2 life and μ.Figure B shows the association between foam drainage 1/2 life and μ∗(E′ /γ ). Two sources of whey protein isolateswere utilized: WPI 1 and WPI 2. WPI 1: � WPI, �75WPI/25EWP, � 50WPI/50EWP, � 25WPI/75EWP, � EWP; WPI 2: ◦ WPI,� 75WPI/25EWP, � 50WPI/50EWP, ♦ 25WPI/75EWP, � EWP. The dash line indicates the linear relationship betweenthe 2 parameters for WPI and WPI/EWP combinations, corresponding to y = 21.4x – 10.5 (R2 = 0.848). Error barsrepresent 1 standard deviation of mean values.

ing analyzed. Observations showed that objectives with areas of lessthan 5 pixels were not actual bubbles. These values were excludedfrom the dataset of bubble areas for each image before furtheranalysis.

Both z-stack images and time-lapse images were analyzed foreach treatment. An image from the center of each z-stack was eval-uated, yielding 5 images and at least 200 bubbles analyzed per treat-ment. For time lapse images, only 1 visual frame was captured over10 min. The images from time 0, 2.5, 5, 7.5, and 10 min were ana-lyzed per treatment.

Statistical analysisData for foams (overrun, drainage 1/2 life, and yield stress), pre-

foam solutions (viscosity), interfaces (interfacial tension and inter-facial elastic modulus), and bubble size (mean bubble area andmedian bubble area) were analyzed using the general linear modelprocedure of the SAS statistical software package (version 9.1; SASInst. Inc., Cary, N.C., U.S.A.). Analysis of variance (ANOVA) wasconducted with means separation to determine differences be-tween treatments. Significant differences were established at P <

0.05.

Results and Discussion

Statistical analysisWhey protein isolates from 2 manufacturers (WPI 1 and WPI

2) were used to cover some of the differences that may be foundamong manufacturing processes (for example, composition andinteractions among components). This was intended to establishthe general effects of WPI rather than link to foaming propertieswith specific differences between WPI samples, which is beyondthis study as it would require 3 or more replications of each WPIand extensive component analysis. Table 1 shows the statisticalresults when WPI sources were analyzed jointly. Changes in theWPI/EWP ratio caused significant effects (P<0.05) in all proper-ties except overrun (Table 1). Similar overrun values are showed inFigure 1, indicating comparable foaming capacities of EWP, WPI,and their combinations. Since significant differences were detectedfor all properties between 2 sources of WPI (Table 1), data forWPI 1 and WPI 2 were analyzed separately (Table 2). Again, no


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significant difference was observed for overrun among 5 WPI/EWPratios for either WPI 1 (P = 0.200) or WPI 2 (P = 0.315). Changesin the WPI/EWP ratio caused significant difference (P < 0.05) in allthe other properties except for the viscosity of solutions containingWPI 2 (P = 0.477). In summary, with the main exception of overrun,the source of WPI (1 or 2) and WPI/EWP ratio had an effect on thefoaming properties.

Foam yield stressFoams transform from viscous fluids to semisolid like structures

and exhibit yield stress values when the air phase fractions increaseabove the random close pack air phase fraction of 0.64 (Mason1999). As the air phase fractions of all samples were greater than0.9, yield stress values were measured by a vane method (Pernelland others 2000). Foam yield stress has been previously modeledbased on Eq. 6 proposed by Princen and Kiss (1989) (Pernell andothers 2002; Davis and Foegeding 2004; Davis and others 2004,2005),

τ0 = γ

R32φ

1/3Y (φ) (6)

where τ0 is yield stress, γ is interfacial tension, R32 is the surface-volume mean drop (bubble) radius, φ is the gas volume fraction,and Y (φ) is an experimentally derived parameter. Foegeding andothers (2006) suggested that this model could be modified for pro-tein foams by replacing interfacial tension with the interfacial di-latational elastic modulus (E ′), as positive associations between E

′

and τ0 were observed in previous studies on WPI foams (Davis andFoegeding 2004; Davis and others 2004, 2005). Therefore, Eq. 6 wasmodified to the following equation:

τ0 = E ′

R32φ

1/3Y (φ) (7)

A plot of E ′ compared with τ0 (Figure 2) displayed a similar pos-itive relationship between E ′ and τ0, as was observed in previ-ous studies on WPI foams (Davis and Foegeding 2004; Davis andothers 2004, 2005); however, this was only true for WPI andWPI/EWP combinations. The deviations of EWP foams from thisrelationship suggested a dissimilarity of EWP from WPI andWPI/EWP combinations in interfacial and foam properties. The E ′

and τ0 of WPI and WPI/EWP combinations of WPI 1 were system-atically higher than those of WPI 2, but the general association be-tween E ′ and τ0 was similar for both WPI 1 and WPI 2. Interestingly,the mixed WPI/EWP systems had higher E ′ and τ0 values than WPI

Figure 4 --- Typical dynamicinterfacial tension measurements of10% (w/v) protein solutions of5 WPI/EWP ratios at pH 7. Twosources of whey protein isolateswere utilized: WPI 1 and WPI 2.◦ WPI, � 75WPI/25EWP, � 50WPI/50EWP, ♦ 25WPI/75EWP, ∇ EWP.

alone for both WPI 1 and WPI 2, suggesting an enhancing effect ofegg white protein on the foam yield stress and interfacial elastic-ity of whey proteins. This coincided with the observation of Aryanaand others (2002) that the combinations of WPI and EWP had syn-ergistic effects on foam properties. These results showed that yieldstress values of WPI and WPI/EWP foams could be attributed, inpart, to interfacial elastic moduli, while EWP foam showed a uniquebehavior, with much lower interfacial elasticity being associatedwith a high yield stress.

Foam stability (drainage 1/2 life)Polyhedral foams are composed of air bubbles separated by thin

films, with Plateau borders at the intersection of 3 thin films. Grav-ity causes liquid to move through the network of Plateau bordersand thin films, resulting in foam drainage (Wang and Narsimhan2006). A high continuous phase dynamic viscosity can slow the rateof drainage (Pugh 1996). Apparent dynamic viscosity data of all so-lutions were calculated at 8.5 s−1 based on a power law model fitover the shear rate sweep (Eq. 4). A shear rate of 8.5 s−1 was cho-sen because the typical shear rates experienced by materials un-der gravity induced drainage range from 0.1 to 10 s−1 (Barnes andothers 1989). However, plotting foam drainage 1/2 life against so-lution apparent viscosity (μ) showed no logical relationship be-tween the 2 variables (Figure 3A). Drainage 1/2 life was lowest for100% WPI foam and increased with progressive substitution of EWP(Figure 3A). Factors other than solution viscosity need to be ac-counted for to explain foam drainage 1/2 life.

Foam drainage, as measured in this investigation, is a dynamicprocess where fluid is draining at the same time that bubbles aredestabilized by coalescence and/or disproportionation. At the in-terfacial level, interfacial elasticity is proposed to increase bub-ble stability, with a cessation of disproportionation predicted atE

′/γ > 1/2 (Dickinson 1992). It is further proposed that a condi-

tion of E′/γ > 2 is more realistic in practice (Walstra 2003). Dickin-

son and others (2002) observed the shrinkage of single air bubblesbeneath a planar air–water interface and found that proteins form-ing an elastic film shrank at slower rates, demonstrating the con-tribution of interfacial elasticity in controlling disproportionation.High interfacial elasticity can also inhibit the rupture of thin filmsbetween neighboring bubbles and therefore impede coalescence(Wilde 2000). Since foam stability was dependent on destabiliza-tion of bubbles (disproportionation and/or coalescence) and solu-tion drainage, the interfacial relationship of E

′/γ in combination

with solution viscosity (μ) was used to explain the difference amongfoam drainage 1/2 life values. A parameter of E

′/γ was considered




rather than E′

alone, which is based on the cessation conditionof disproportionation predicted by Dickinson (1992) and Walstra(2003). Plotting foam drainage 1/2 life against μ∗(E

′/γ ) resulted in a

linear relationship (R2 = 0.848) between the 2 variables for WPI andWPI/EWP foams (Figure 3B). Again, EWP foams were apart fromthe common pattern. This result suggested that the foam stabilityof WPI and WPI/EWP depend on the solution viscosity as well asthe interfacial elasticity; while EWP foam showed higher foam sta-bility than the other foams even at a lower level of interfacial elas-ticity. The contribution of interfacial dilatational elasticity to thefoam drainage 1/2 life has also been observed in β-lactoglobulinand diglycerol esters (Alvarez and others 2008; Rodrıguez Patinoand others 2008) and soy globulins (Ruız-Henestrosa and others2008), while the associations between the 2 variables were depen-dent on protein compositions.

Interfacial tension and interfacial elasticityFrom the previously mentioned discussions, foam yield stress

and drainage 1/2 life could be normalized for WPI and WPI/EWPmixtures based on solution viscosity and interfacial characteris-tics. In contrast, EWP foams did not follow similar trends. Tempo-ral decreases in interfacial tension reflect the adsorption and re-arrangement of proteins at the air/water interface (Myrvold andHansen 1998), and these are seen in Figure 4. The EWP solutionsexhibited the most rapid interfacial tension decline rate, whereasall WPI/EWP solutions followed the pattern of WPI. The more rapiddecline rates and lower interfacial tension values of EWP than WPIwere also previously reported by Davis and Foegeding (2007). Al-though EWP exhibited a more rapid adsorption rate, similar in-terfacial tension decline patterns of WPI/EWP and WPI solutionssuggested that the interfacial active molecules in WPI rather thanthose in EWP appeared to determine interfacial tension. A sim-ilar phenomenon was observed in mixtures of β-casein and β-lactoglobulin at the air–water interface, where β-casein tended todominate interfacial properties of the mixed system (Ridout andothers 2004). Competitive adsorption at an interface depends onfactors beyond interfacial activity. If the protein reaching the inter-face first does not have a chance to unfold, it can be displaced bycompeting proteins (Dickinson 1999). As a result, WPI/EWP inter-faces demonstrated similar interfacial properties to WPI, in agree-ment with observations that the foaming properties (yield stressand drainage 1/2 life) of WPI/EWP foams tended to follow the pat-terns of WPI. The interfacial tension declined at a slower rate after5 min of aging. The interfacial tension at 5 min was recorded andaveraged from 3 replications. Statistical analysis (data not shown)indicated that no significant difference (P = 0.777) was detectedamong interfacial tension of WPI and WPI/EWP combinations pre-pared from either source of WPI, whereas interfacial tension of EWPwas significantly (P<0.05) lower than the others.

Interfacial elasticity (E ′) reflects the resistance of the adsorbedmolecules to dilatational deformations and depends on moleculeadsorption/desorption, intermolecular structural rearrangement,and intramolecular interactions at interfaces. The WPI/EWP com-binations showed the same interfacial tension values as WPI(Figure 4) but higher E ′ (Figure 2), which was true for eithersource of WPI. The same interfacial tension of WPI and WPI/EWPcombinations revealed that a component of WPI dominated theinterface. However, the presence of EWP molecules in WPI/EWPcombinations may affect interfacial tension gradients and inter-molecular interactions at air/water interfaces, resulting in higherE ′ than WPI. In addition, the presence of EWP also decreasedthe concentration of WPI in solutions and influenced the adsorp-tion/desorption rates of molecules during dilatational deforma-

tion. The foam yield stress and foam drainage 1/2 life of WPI/EWPcombinations changed with the interfacial rheology variations ac-cordingly (Figure 2 and 3), while EWP samples were excluded fromthe common trends. This supports the hypothesis that whey pro-teins dominate interfaces in mixed systems.

Foam microstructureConfocal laser scanning microscopy (CLSM) combined with im-

age analysis is a useful tool for characterizing bubble size dis-tributions of foams. Figure 5 shows CLSM images of WPI andEWP foams, which were taken immediately after foam generation.Sodium fluorescein is a water-soluble fluorescent dye that binds toprotein. Thus, the aqueous protein solution is shown as the lighter

Figure 5 --- Confocal laser scanning microscopic (CLSM)images of foams prepared from 10% (w/v) protein solu-tions of 5 WPI/EWP ratios at pH 7. Two sources of wheyprotein isolates were utilized: WPI 1 and WPI 2. The whitearrows indicate some examples of the transparent trian-gle areas that appeared in small bubbles due to the lightreflection.


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phase while air bubbles are black. An appropriate zoom scale wasselected to generate a clear view, resulting in different field size be-low each image.

These foam images (Figure 5) lead to several conclusions. First,the WPI and WPI/EWP combination foams of WPI 1 showed nu-merous smaller bubbles compared to those of WPI 2. Second,foams prepared from EWP had a large number of more closelypacked small bubbles compared to either WPI foam, which hadfewer bubbles of larger sizes. Third, the WPI/EWP combinationsappeared visually similar to both WPI and EWP, containing bothsmall and large bubbles. These characteristics of images werequantitatively analyzed by determining bubble shape and size. Thebubble shape factor is used as a parameter to evaluate the de-viation of a bubble from a spherical shape, with 1 indicating asphere and <1 showing the degree of nonspherical geometry. His-tograms of bubble shape factors for 2 treatments (representative ofall treatments) are shown in Figure 6. The shape factors generallyformed a distribution skewed toward the lower numbers and cen-tered around 0.85 to 0.90, suggesting that most bubbles were notperfect spheres. Therefore, instead of calculating bubble diame-ters based on spherical bubble-shape assumption, bubble area wasmeasured and analyzed. Utilizing bubble area as a method of im-age analysis has been previously done for cake batter (Hicasmazand others 2003; Kocer and others 2007).

The mean and median bubble areas for each treatment areshown in Figure 7. When grouped according to WPI source, foams

Figure 6 --- Histograms of bubbleshape factors in the CLSM images ofprotein foams prepared from 10%(w/v) protein solutions of 100% WPIor 100% EWP at pH 7. Two sourcesof whey protein isolates wereutilized: WPI 1 and WPI 2. A and Bare for 100% WPI foams preparedfrom WPI 1 and WPI 2, respectively.C and D are for 100% EWP foams.

Figure 7 --- Mean (I) and median (II)bubble area of the CLSM images ofprotein foams prepared from 10%(w/v) protein solutions of 5 WPI/EWPratios at pH 7. Two sources of wheyprotein isolates were utilized: WPI 1and WPI 2. Values with the sameletter are not significantly different,where the uppercase letters are forWPI 1 and the lowercase letters arefor WPI 2. Error bars represent 1standard deviation of mean values.

made from WPI 1 had significantly (P < 0.05) smaller bubbles thanfoams made from WPI 2. No significant differences were observedamong the mean bubble areas of the WPI/EWP combinations ofthe same source of WPI (data not shown). This suggests that theamount of WPI substituted for EWP into the combination foams,whether 25% or 75%, has a similar impact on bubble size. Themedian bubble area was smaller than the mean bubble area foreach treatment, suggesting right skewed bubble size distribution(Figure 7). This was in agreement with the composition of a largenumber of small bubbles and a few large bubbles in each image.

Foam stability (foam microstructure)A negative linear relationship (R2 = 0.702) was established be-

tween foam drainage 1/2 life and the mean bubble area on a log-log scale, regardless of the foam compositions (Figure 8). Thissuggested that a smaller initial bubble size contributed to higherfoam stability. Points of 100% EWP foam, as indicated by the arrows,were slightly deviated from the master curve on the right side, sug-gesting higher foam stability than those foams containing WPI atthe same level of bubble size. The foams containing WPI 1 showedhigher foam stability than those containing WPI 2, correspondingto smaller initial bubble sizes. Addition of EWP to either source ofWPI foams increased the foam stability as well as decreased the ini-tial bubble size.

The higher stability of bubbles with smaller initial size can beexplained based on bubble destabilization mechanisms. Creaming




happens in foam due to the density difference between gas andcontinuous phase. A larger bubble size leads to greater buoyancyforce and therefore a faster creaming rate according to Stokes law(Walstra 2003). Disproportionation occurs when gas diffuses fromsmall bubbles through the aqueous phase into larger bubbles, re-sulting in small bubbles shrinking and large bubbles growing. Thedriving force of this process is the difference of Laplace pressurebetween bubbles, which is dependent on the bubble size distribu-tion. Large bubbles in foam are getting larger due to disproportion-ation, and moving faster to the top due to creaming. The gatheringof large bubbles promotes coalescence, which is the rupturing of

Figure 8 --- The relationship between foam drainage 1/2 lifeand the mean bubble area. Foams were prepared from10% (w/v) protein solutions of 5 WPI/EWP ratios at pH 7.Two sources of whey protein isolates were utilized: WPI 1and WPI 2. WPI 1: � WPI, �75WPI/25EWP, � 50WPI/50EWP,� 25WPI/75EWP, � EWP; WPI 2: ◦ WPI, � 75WPI/25EWP,� 50WPI/50EWP, ♦ 25WPI/75EWP, � EWP. The dash lineindicates the power law relationship between the 2 vari-ables, corresponding to y = 104297x−0.846 (R2 = 0.702).Error bars represent 1 standard deviation of mean values.

Figure 9 --- Schematic illustration ofthe dynamic draining process infoams. From left to right, fluid isdraining through the lamella filmsbetween bubbles at the same timethat bubbles are growing orshrinking due to coalescence and/ordisproportionation. In eachrectangle, the bottom black partrepresents the drained solution andthe top white part corresponds tothe separated gas, with the foam inbetween. Type A foam has a smalleraverage bubble size than Type Bfoam. Therefore, Type A foam willtake longer than Type B foam toreach the state of “Draining 1/2mass of the prefoam solution.”

the film between 2 bubbles producing 1 larger bubble. These desta-bilization changes collectively result in an increase in bubble sizeand a decrease in bubble count. If we assume the destabilizationchanges in foams containing either source of WPI follow the samepattern, a simple illustration of bubble size changes, and corre-sponding draining process, is shown in Figure 9. A foam composedof smaller initial bubbles would take longer to drain 1/2 the mass,coinciding with the relationship shown in Figure 8. However, sincea finite amount of time is required between foam preparation andvisualization of bubbles in the microscope, the larger initial bub-ble size could be reflecting a faster destabilization rate. Whateverthe case, changes of bubbles in 100% EWP foam did not followthe same time scale, resulting in a slight deviation from the mastercurve (Figure 8). This once more showing the distinct differences infoams made from EWP alone.

To investigate the dynamic changes of bubbles, foams were im-aged with 1 frame kept in focus over 10 min. Analyses of time lapse

Figure 10 --- Changes of mean bubble area in the CLSMimages of foams over time. Foams were prepared from10% (w/v) protein solutions of 5 WPI/EWP ratios at pH7. Two sources of whey protein isolates were utilized:WPI 1 and WPI 2. WPI 1: ◦ WPI, � 75WPI/25EWP, � 50WPI/50EWP, ♦ 25WPI/75EWP; WPI 2: � WPI, �75WPI/25EWP, �50WPI/50EWP, � 25WPI/75EWP, � EWP.


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images are shown in Figure 10. The parameter of bubble count perunit area over time is a function of bubbles moving in and out of thefocus plane (stable bubble movement) and destabilization changesof disproportionation and/or coalescence, which will alter bub-ble size distributions and reduce bubble counts. Mixing EWP withWPI 1 increased the bubble number per area (Figure 10), coincidingwith smaller bubble size (Figure 7), but the same general decreas-ing trend was observed in all WPI 1 treatments. In contrast, foamsmade from WPI 2 had a range of bubble sizes and all showed a de-creasing trend over time. The biggest difference was for 100% EWPfoams, which showed no change in bubble number per area for the10 min of observation. While the molecular reason is beyond thisinvestigation, it is clear that creating small and stable bubbles con-tributes to the increased stability of EWP foams.

Determining which bubble destabilization process(es) is/are oc-curring in a foam is difficult by simply observing bubble count overtime. In bubble size distributions, coalescence leads to the appear-ance of larger bubbles and a decrease in the number of bubbles.Disproportionation should result in a bimodal distribution as thelarge bubbles grow at the expense of smaller bubbles (Pugh 1996);however, there will be a minimum observable (that is, countable)size depending on optical considerations that can skew the results.In viewing time-lapse videos, bubble coalescence was not observedwhile the shrinking and eventual disappearance of small bubblesand growth of large bubbles was seen. This leads to the conclusionthat disproportionation was the main destabilization mechanismseen in these foams. Disproportionation has also been observedusing CLSM time-lapse imaging as a destabilization mechanism infoams produced from a combination of egg white and invert sugar(Lau and Dickinson 2005). In theory, viscoelastic films such as thoseformed by proteins at the air–water interface should inhibit thediffusion of gas into the aqueous phase (Dickinson 1992; Walstra2003). However, research has found that even highly viscoelasticfilms do not stop disproportionation, only slowing it down slightly(Dickinson and others 2002; Du and others 2003). An interestingobservation by Dickinson and others (2002) was that the bubblesof β-lactoglobulin, which forms a strong and coherent interfacialfilm, formed residual protein particles and faded slowly at the endof the shrinking process, while the bubbles of other proteins dis-appeared rapidly. This phenomenon was not found in this study,

Figure 11 --- Relationship between foam yield stress and γ /R∗32φ

1/3 (A) or E′ /R∗32φ

1/3 (B). γ is the interfacial tension;E′ is the interfacial elastic modulus; R32 is the surface-volume mean bubble radius, which was estimated usingthe area mean bubble radius (R20); φ is the air phase fraction. Foams were prepared from 10% (w/v) protein solu-tions of 5 WPI/EWP ratios at pH 7. Two sources of whey protein isolates were utilized: WPI 1 and WPI 2. WPI 1:� WPI, �75WPI/25EWP, � 50WPI/50EWP, � 25WPI/75EWP, � EWP; WPI 2: ◦ WPI, � 75WPI/25EWP, � 50WPI/50EWP, ♦25WPI/75EWP, � EWP. The solid lines indicate the best-fit linear relationships, corresponding to y = 0.167x – 75.4(R2 = 0.925) for A and y = 0.0611x + 13.4 (R2 = 0.978) for B. The dash lines indicate the linear relationships crossingthe zero point, corresponding to y = 0.0930x (R2 = 0.732) for A and y = 0.0700x (R2 = 0.952) for B.

but we did observe some stable bubbles being consistent overtime.

Modeling yield stressIn addition to the interfacial properties, the surface-volume

mean bubble radius (R32) also contributes to foam yield stress ac-cording to the Princen and Kiss (1989) model (Eq. 6) or the modi-fied one (Eq. 7). Since bubbles imaged were not perfectly spherical(Figure 6), the area mean bubble radius (R20) was calculated fromthe mean bubble area and utilized as an estimation of R32 in thesemodels. The air phase fraction of the bubbles was calculated fromoverrun measurements according to Eq. 2. The experimentally de-rived parameter Y (φ) was dependent on air phase fraction, whichshowed no significantly difference (Table 1, P = 0.238) amongfoams, and therefore can be considered as a constant. Linear rela-tionships (R2 = 0.732 to 0.978) were established between foam yieldstress (τ0) and γ /R∗

32φ1/3 (Figure 11A) or E

′/R∗

32φ1/3 (Figure 11B) for

WPI and WPI/EWP combinations, regardless of WPI source. Whiletreatments containing WPI 1 were located at the higher end of thecurve than those containing WPI 2, both appeared to be governedby the same linear pattern. Again, the 100% EWP samples were ex-cluded from the common trend with a higher yield stress than ex-pected. Since a negative yield stress has no meaning, the regressioncurves were evaluated with and without a forced intercept of zero.Setting the intercept to zero resulted in a decrease in the R-squarevalue, especially in the case of using interfacial tension in the model(Figure 11A). Replacing γ with E ′ increased the R-square value from0.732 to 0.952 for the linear regression crossing the zero point. Thissuggests that interfacial elasticity is more applicable then inter-facial tension to estimate yield stress value when using the the-oretical model in foams, supporting previous suggestions basedon interfacial data without bubble size considerations (Davis andFoegeding 2004; Davis and others 2004, 2005). The reason for thehigher yield stress value of 100% EWP samples is not clear. Taken lit-erally, it shows that some factor in EWP contributes greatly to yieldstress that cannot be accounted for by interfacial tension or elas-ticity, air phase fraction, or bubble size. While it is compelling tospeculated that a higher yield stress and stable bubbles are consis-tent with a weak network developing within the lamellae, this is atbest a suggestion to be tested in future investigations.




Conclusions

Combinations of WPI and EWP did not show a general ad-ditive effect in foaming properties. Temporal patterns for a

decrease in interfacial tension showed that WPI and WPI/EWPcombinations followed the same pattern while that of EWP wasdistinct. This indicated that WPI was dominating the interfacewhen both proteins were present. The foam yield stress anddrainage 1/2 life of WPI and WPI/EWP mixtures changed with theinterfacial elasticity in positive relationships, with the 100% EWPexcluded from the common trends, further supporting that wheyproteins dominate the air/water interfaces of the bubbles in themixed protein foams. A linear relationship was established betweenfoam drainage 1/2 life and bubble size on a log–log scale, suggest-ing smaller initial bubble size contributes to greater foam stability.The bubble counts per area in microstructure images of WPI andWPI/EWP foam decreased over time, while that of 100% EWP foamremained constant. The yield stress models suggested by Princenand Kiss (1989) and modified by Foegeding and others (2006) fit thedata for foams made with WPI and WPI/EWP mixtures, while EWPfoams deviated from the experimental derived models, exhibitinga higher yield stress than the other foams. The higher foam yieldstress and drainage stability of EWP foams appears to be due toforming smaller, more stable bubbles, that are packed together intostructures that are more resistant to deformation that those of WPIfoams.

AcknowledgmentsPaper nr FSR08-07 of the Journal Series of the Dept. of Food,Bioprocessing and Nutrition Sciences, North Carolina State Univ.,Raleigh, N.C. 27695-7624, U.S.A. Support from the North CarolinaAgricultural Research Service, Dairy Management Inc., and theSoutheast Dairy Foods Research Center are gratefully acknowl-edged. The use of trade names in this publication does not implyendorsement by the North Carolina Agricultural Research Serviceof the products named or criticism of similar ones not mentioned.The authors are very grateful of the gifts donated by Davisco FoodsIntl., Glanbia Foods and Henningsen Foods.

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