Phase separation in milk protein and amylopectin mixtures

Food Hydrocolloids 16 (2002) 127±138

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Phase separation in milk protein and amylopectin mixtures Petra W. de Bont, Geert M.P. van Kempen, Rob Vreeker* Unilever Research Vlaardingen, Olivier van Noortlaan 120, 3313 AT Vlaardingen, The Netherlands Received 9 February 2001; accepted 11 June 2001

Abstract The phase separation behaviour of milk protein (colloidal casein) and amylopectin mixtures was studied. The phase boundary between stable and unstable mixtures was determined by visual observation and confocal microscopy (CSLM). In the latter case, an image analysis procedure (the variance measure) was used. The phase boundary was also calculated using depletion theory as developed by Vrij, A. (1976). Polymers at interfaces and the interactions in colloidal dispersions. Pure and Applied Chemistry, 48, 4, 471±483. Good agreement was obtained between calculated and measured phase boundaries. The CSLM study revealed the appearance of protein aggregate structures when phase separation occurred. Qualitatively, the appearance of the structures was similar to that of rennet- or acid-induced milk protein aggregates. At high concentrations, the aggregates form a network with gel-like properties. The occurrence of aggregate structures has not been reported before for phase separating milk protein±polysaccharide mixtures. So far, emulsion-like microstructures have been observed with milk proteins concentrated in spherical droplets. The observed microstructural difference could be explained using earlier experimental observations reported by Sperry, P. R. (1984). Morphology and mechanism in latex ¯occulated by volume restriction. Journal of Colloid and Interface Science, 99, 1, 97±108 and a theoretical description of phase separation in colloid±polymer mixtures developed by Lekkerkerker, H. N. W., Poon, W. C. K., Pusey, P. N., Stroobants, A., and Warren, P. B. (1992). Phase behaviour of colloid 1 polymer mixtures. Europhysics Letters, 20, 6, 559±564 and is ascribed to a low value of the polymer±colloid size ratio. q 2002 Elsevier Science Ltd. All rights reserved. Keywords: Phase separation; Depletion interaction; Microstructure; Confocal microscopy; Image analysis

1. Introduction Polysaccharides are often used as thickening agents or stabilisers in dairy-based products. Their main function is to improve product texture (organoleptic properties) and physical stability (water binding). Mixtures of proteins and polysaccharides are usually not stable. After preparation, they tend to demix into protein-rich areas and polysaccharide-rich areas. This phenomenon is also called phase separation. The microstructure of phase-separated systems is very similar to that of oil-in-water emulsions, i.e. they consist of `droplets' of protein solution in a continuous polysaccharide solution or the other way around (i.e. droplets of polysaccharide solution in a continuous protein solution). Several authors have recently studied phase separation in milk protein (colloidal casein) and polysaccharide mixtures. Bourriot, Garnier, and Doublier (1999a,b,c); Schorsch, Clark, Jones, and Norton (1999a); Schorsch, Jones, and Norton (1999b) measured phase diagrams for micellar casein±locust bean gum and guar * Corresponding author. E-mail address: [email protected] (R. Vreeker).

gum mixtures. Tuinier and de Kruif (1998, 1999) studied phase separation in mixtures of milk protein and exocellular polysaccharide produced by a lactic acid bacterium. In this last case, the observed phase behaviour was analysed on the basis of Vrij's depletion theory for colloid±polymer mixtures (Vrij, 1976). Milk was considered as a dispersion of colloidal particles (casein micelles) with a radius rc < 100 nm in an aqueous phase containing various minerals (e.g. Ca, Mg, phosphate), lactose and small (,5 nm) globular proteins. In the analysis, the casein micelles were considered to behave effectively as hard spheres (de Kruif, 1992). Exocellular polysaccharides added to the colloidal dispersion were assumed to cause attractive interactions between the casein particles as a result of depletion effects (see the next section). The phase boundary (binodal) between stable and unstable protein±polysaccharide mixtures was calculated and shown to be in good agreement with the experimentally observed phase boundary. This supports the idea that depletion interactions are the driving force for phase separation in milk protein±polysaccharide mixtures. The same authors also studied phase separation in mixtures of milk protein and guar gum (Tuinier, ten Grotenhuis, & de Kruif, 2000). The molecular weight and

0268-005X/02/$ - see front matter q 2002 Elsevier Science Ltd. All rights reserved. PII: S 0268-005 X(01)00 070-4

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Fig. 1. Schematic picture of the depletion interaction mechanism.

radius of the guar gum was varied systematically and its effect on the phase boundary was examined. Again, a satisfactory description of the experimental results was given on the basis of Vrij's depletion theory. The objective of the present work is to describe the phase separation behaviour and microstructure of milk protein and amylopectin systems. The system studied was prepared from high heat milk powder and potato amylopectin at various concentrations. The phase boundary was determined visually and by confocal microscopy. In the latter case, an image analysis procedure (the variance measure) was applied. The phase behaviour was described on basis of Vrij's depletion theory, using the same approach as Tuinier and de Kruif (1999). This approach requires information with respect to the molecular weight and radius of gyration of the amylopectin. These parameters were determined by intrinsic viscosity measurements and size exclusion chromatography (SEC). The microstructure of the milk protein±amylopectin mixture was also studied by CSLM. It will be shown that the microstructure is signi®cantly different from that observed in phase separating mixtures of, e.g. milk protein±locust bean gum. Additional information on the microstructure of phase separating mixtures was obtained from small deformation rheology (G 0 , G 00 ). Finally, we tried to relate the observed differences in microstructure to a colloid±polymer model study described in the literature (Sperry, 1984) and to a theoretical description of phase separation in colloid±polymer mixtures developed by Lekkerkerker, Poon, Pusey, Stroobants, and Warren (1992). 2. Depletion interaction Addition of non-adsorbing polymers to a colloidal dispersion may lead to phase separation. The phase separation process results from an entropic interaction, also known as depletion interaction. Theoretical expressions for the depletion interaction potential between two ¯at plates were ®rst given by Asakura and Oosawa (1954). Later, Vrij (1976) developed a model for the depletion interaction potential between two colloidal spherical particles in a

non-adsorbing polymer solution. From a qualitative point of view, the depletion interaction can be understood in terms of a repulsive interaction between the colloidal particles and the polymers. Each colloidal particle is surrounded by a layer in which the centre of the polymer cannot penetrate. This excluded layer is called the depletion layer and its thickness, D, is of the order of the radius of gyration of the polymer molecule (Fig. 1). When two colloidal particles approach each other such that their depletion layers start to overlap, the available volume for the polymer increases. The increase in volume causes the total entropy to increase and, hence, the free energy to decrease. In effect, this causes an attractive interaction between the colloidal particles. Vrij (1976) derived the following expression for the interaction potential (U(r)) between two approaching colloids (diameter s c) in the presence of polymers with a diameter s p: 11 U…r† ˆ 2P p Voverlap …r† 0

0 , r , sc

s c # r # …s c 1 s p †

…1†

r . …s c 1 s p †;

here r is the distance between the centres of the two colloids and P p ( ˆ cpRT/M) the osmotic pressure of a polymer solution with concentration cp and molar mass M. Voverlap(r) is the overlap volume existing between the two colloids, caused by the overlap of the two approaching depletion layers and is given by the following expression: Voverlap …r† ˆ

1 p…s c 1 s p †3 6

! 3r r3 1 :  12 2…s c 1 s p † 2…s c 1 s p †3

…2†

To calculate the phase diagram we follow the approach of Tuinier and de Kruif (1999). These authors argued that the binodal could be approximated by the spinodal. At the spinodal, the osmotic compressibility becomes zero:

2P c ˆ 0: 2f

…3†

For the osmotic pressure of the colloids, we can write down a virial expression:

P c Vc ˆ f 1 B2 f2 1 ¼; kB T

…4†

where Vc …ps c3 =6† is the volume of the colloidal sphere, B2 is the second osmotic virial coef®cient and f the colloid volume fraction. For low volume fractions (f , 0.2), higher order terms can be neglected. Combining Eqs. (3) and (4) results in a relation between the B2sp and the volume fraction (f sp) of the colloids at the spinodal: Bsp 2 ˆ2

1 : 2fsp

…5†

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129

phases have been encountered when the attraction between the colloids is relatively deep and short ranged (Poon, Pirie, & Pusey, 1995; Verhaegh & Lekkerkerker, 1997, 1999). Above a certain polymer concentration, aggregation of the colloidal particles takes place and the mixtures are temporarily arrested in a space-spanning particle gel. 3. Image analysis

Fig. 2. Illustration of the in¯uence of the chosen resolution (res.) on the variance (var.) measure of a CSLM image of a mixed and a phase separated (sep.) system.

Statistical mechanics provides another relation for B2,    2p Z1 2 U…r† B2 ˆ r 1 2 exp 2 dr: …6† Vc 0 kB T The binodal approximated by the spinodal is now calculated as follows. First, B2 is calculated at a certain polymer concentration cp using Eqs. (1) and (6). Then, from Eq. (5), the colloid volume fraction at the spinodal, f sp, is calculated. Repeating this procedure for different polymer concentrations cp results in a phase boundary (f sp ±cp graph) for colloid±polymer mixtures. One has to realise that the approach of Vrij is only valid in the dilute regime, where only pair interactions are involved, and that an ideal polymer solution is assumed. Another assumption is that the depletion layer thickness equals the radius of the polymer. Tuinier, Vliegenthart, and Lekkerkerker (1997) have shown that for a large polymer (relative to the colloid) the depletion layer thickness is less than the radius of gyration of the polymer. This decreasing depletion layer would result in a shift of the binodal to the higher concentration region. Several authors (Gast, Russel, & Hall, 1986; Lekkerkerker et al., 1992) have performed theoretical studies on phase transitions in colloid±polymer systems. An important parameter is the size ratio of the polymer and colloid …j ˆ s p =s c †. This j parameter is related to the attraction range of the colloids. Different phase behaviour is predicted for low and high values of j . A colloidal ¯uid±solid transition is predicted to occur when the size ratio j is smaller than 0.3 (i.e. for narrow ranges of attraction). For j . 0.3, instead of one, Lekkerkerker et al. (1992) predicted three different regions in the phase diagram: a gas±liquid, a gas± liquid±solid and a gas±solid region. The theoretical predictions are in agreement with experimental results obtained by Sperry (1984) and Faers and Luckham (1997) for latex colloids and hydroxyethylcellulose polymers. In addition to the different thermodynamic phases, non-equilibrium

Image analysis has been applied on CSLM images of milk protein±amylopectin mixtures in order to determine the phase boundary in an objective way. Each image contains 512 £ 512 pixels, with a grey value range from 0 to 255. Homogeneous (non phase separated) mixtures give rise to CSLM images with a more or less constant grey value, whereas images of phase separated mixtures will contain regions with `high' grey values (white) and regions with `low' grey values (black). These differences in grey values can be measured in various ways, using, for example, texture analysis methods (JaÈhne, 1997). One of the most simple texture analysis methods, applicable to this problem is the grey value variance measure. This measure estimates the variance (s 2) of the grey values of all the pixels in the image by using the sample variance (Kendall & Stuart, 1977):

s2 ˆ

N 1 X  2; …x 2 x† N 2 1 iˆ1 i

…7†

where N stands for the total amount of pixels, xi for the grey value of the i-th pixel and x for the mean grey value. This variance measure operates directly on the grey-value pixel intensities of the acquired CSLM images. It, therefore, does not require the segmentation of the recorded image. Segmentation of, or distinction between, the various phases of a mixed system of soft-condensed matter is a notoriously dif®cult task. (One of the simplest forms of segmentation is thresholding, which makes a binary decision about the class membership based on the intensity value of the evaluated pixel.) The proposed variance measure, therefore, offers a major advantage over classical methods that do require the segmentation of the acquired image. We have used the variance measure, normalised by the  of the original CSLM image, as a mean intensity (x) measure for the homogeneity of the image. The normalisation was done to make the results independent of ¯uctuations in the total ¯uorescence intensity. A high value of this measure, therefore, indicates a phase separated system, whereas a low value represents a mixed (homogeneous) system. The resolution of the CSLM images determines which size of inhomogeneities the variance measure is most sensitive to. For images taken (well) below the diffractionlimited optical resolution of the microscope, the magni®cation of the objective used, determines the resolution. Fig. 2 illustrates the in¯uence of the resolution on the variance

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measure used, in a simpli®ed model of a homogeneous and a phase separated two-phase system. The six blocks represent homogeneous (mixed) and separated systems analysed at high, low and the `right' resolution. The 16 squares in the high resolution blocks (left) represent the `elementary particles' of the system, and their colours represent the greyvalues at particle resolution. At high resolution, the size of the pixel is equal to the size of the elementary particles. At low resolution (right) and `right' resolution, the pixel size is indicated by the grey boxes containing 16 and four `elementary particles', respectively. The colours of the pixels represent the grey values obtained after averaging over the `elementary particles' present in each pixel. At high resolution, each pixel represents a single particle. Both the mixed and separated system have the same amount of `elementary particles', but with different spatial arrangements. Since the variance measure is insensitive to the spatial arrangement of the pixels (see Eq. (7)), the variance measured in both systems will be equal. At low resolution, the pixels have the same grey-values, which again results in equal variance values. In the middle con®guration, the pixel grey values are an average of only four particles, representing an area smaller than the size of the `clusters' formed in the separated system. This yields pixel values which differ from the mixed system, giving different variance values between the two systems. An experimental conformation on this explanation is given in Fig. 7 and explained in the results.

4. Experimental 4.1. Sample preparation High heat skimmed milk powder (ex. Friesland Coberco Dairy Foods, The Netherlands) was used (water content 2.3 wt%). A stock solution was prepared by dissolving 28.6 wt% of the powder in demineralised water (overall protein content 10.6% with 8.5% caseins). Milk-permeate was obtained from a solution of 28.6 wt% of low heat skimmed milk powder in demineralised H2O. The solution was ultra-®ltrated through a ®lter with a cut-off of 8 nm. The ®nal pH of the permeate was around 6.3. Chemical analysis showed that after ®ltration 0.6 wt% of proteinaceous material was still present in the permeate. The permeate further contained Ca (0.06%), Mg (0.02%), P (0.1%) and 12.5% of lactose. The polysaccharide used was an amylopectin (AP) extracted from potato starch (ex. AVEBE, The Netherlands). The following characteristics were provided by the supplier: a dry matter content of 964 mg/g, a phosphorus content of 0.78 mg/g (dm) and an amylose content of 0%. A stock solution was prepared by dissolving amylopectin (10 wt%) in milk-permeate at 658C under stirring conditions. All stock solutions were preserved by adding 0.03 wt% of

NaN3. Samples of different compositions were prepared by combining appropriate amounts of the milk protein, amylopectin and permeate stock solutions. In this way, samples were prepared with similar pH and salt levels. For the bulk phase separation measurements and the CSLM measurements, a total amount of 15 and 10 g of each sample was prepared, respectively. 4.2. Characterisation of amylopectin 4.2.1. Intrinsic viscosity measurements The intrinsic viscosity of amylopectin solutions was determined by extrapolating the reduced viscosity versus concentration graph to zero concentration. Amylopectin was dissolved in an aqueous NaOH solution at pH 10 and in permeate. Solutions were ®ltrated using a 5 mm Millipore ®lter. A capillary viscometer Schott-GeraÈtte, model AVS 300 with a water-bath, was used. The measuring temperature was 258C. 4.2.2. Size exclusion chromatography (SEC) measurements Amylopectin was characterised by AVEBE (The Netherlands) using SEC on-line coupled to a refractive index (RI) detector. The used eluent was DMSO:H2O ˆ 90:10 (v/v%) (it was not possible to use permeate as an eluent). A Kratos-pump Spectro¯ow 400 and RI-detector ERC-7510 (Erma Optical Works) were used with several columns in series (PLgel Guard 7.5 mm ID £ 50 mm (particle size 5 mm) 1 PLgel MIXED-D 7.5 mm ID £ 300 mm (particle size 5 mm) 1 PLgel MIXED-A 7.5 mm ID £ 300 mm (particle size 20 mm) 1 PLgel MIXED-A 7.5 mm ID £ 300 mm (particle size 20 mm)). The molecular weight of the sample (Mw) was estimated from a calibration with dextrans (DXT4K (Mw ˆ 4300) and DXT550K (Mw ˆ 548,300), purchased from Viscotek Benelux. 4.3. Bulk phase separation measurements Samples with different amylopectin and casein concentrations were transferred to 20 ml glass vials and left at room temperature. The sample height was approximately 3 cm. All samples were observed for at least 4 weeks. In phase separating systems, a clear border line between lower and upper phase could be distinguished, with the lower layer being enriched in proteins. In highly concentrated samples, ®rst indications of phase separation were observed after more than 8 days. In less concentrated samples, phase separation was already visible after 1±2 days. After 2 months, all systems still showed a pH of 6.3, the same as the pH of the solvent (permeate). 4.4. Confocal scanning laser microscopy (CSLM) The proteins were labelled with a solution of Rhodamine B (ex. Aldrich) (0.001 wt%) in demineralised water. Laser light with a wavelength of 568 nm was used to induce ¯uorescence. Images were made using a Bio-Rad

P.W. de Bont et al. / Food Hydrocolloids 16 (2002) 127±138

Fig. 3. Reduced viscosities of amylopectin dissolved in water at pH ˆ 10 (V) and in permeate at 258C (B).

MRC1024 equipped with an argon/krypton laser, combined with a Zeiss Axiovert (inverted) microscope. Different objectives were used, resulting in image widths of 520, 260, 130 and 65 mm. Four to ®ve scans were Kalman (a noise reduction ®lter) averaged during creation of one image. This Kalman ®lter was used as it was implemented in the Bio-Rad acquisition software. Different mixtures with a casein content of 0.5, 1.1, 2.1 and 4.2 wt% and several amylopectin contents were prepared to study with CSLM. After mixing for 1.5 h, each sample (10 g) was transferred to a special sample holder. This sample holder (a Perspex tube (f ˆ 2 cm) with an objective glass glued to one end) made it possible to observe the bottom of the sample. The sample height was approximately 3 cm. All pictures presented here were measured between 15 and 30 min after preparation of the sample. It was checked that Rhodamine B did not in¯uence the macroscopical phase separation behaviour. The above-described image analysis (see Section 3) has been applied on the obtained CSLM images. This procedure was implemented using SCIL-Image (TNO-TPD, The Netherlands) and DIPlib (Delft Image Processing Library). 4.5. Determination of dynamic moduli Dynamic moduli (G 0 , G 00 ) were obtained from small deformation measurements using a Bohlin CS-50 controlled stress rheometer equipped with a concentric cylinder measuring cell (double gap geometry). Measurements were made at 1% strain and 1 Hz frequency. The measurement temperature was 208C. The mixtures were poured into the measurement cell of the rheometer directly after preparation (i.e. before the onset of phase separation) and covered with a thin layer of paraf®n oil to prevent evaporation. The measurements were started after approximately 8 min. 5. Results 5.1. Characterisation of amylopectin Reduced viscosities of amylopectin dissolved in H2O

131

(pH ˆ 10) and in permeate are given in Fig. 3. The intrinsic viscosities were found to be [h ]0 ˆ 117 and 31 ml/g, respectively. The results indicate that the hydrodynamic volume of amylopectin dissolved in H2O is higher than when dissolved in permeate. It is speculated that the decrease of intrinsic viscosity in permeate is caused by the presence of Ca 21, which may interact with the negative phosphate groups of amylopectin, leading to a reduction in the volume of the polymer coil. SEC-analysis showed that the amylopectin used consists of a low and a high molecular weight fraction. The following results were found for the latter fraction: Mn ˆ 12,260,000, Mw ˆ 24,090,000 and Pd(Mw/Mw) ˆ 2.0. These values are well within the range of values given in the literature (Bello-Perez, ParedesLopez, Roger, & Colonna, 1996; Erlander, Purvians, & Grif®n, 1968). As shown by Einstein, the intrinsic viscosity [h ]0 of spheres is given by (Macosko, 1994): ‰hŠ0 ˆ

5 4pR3H Nav ; 2 3 Mn

…8†

where Nav is Avogadro's number, RH the hydrodynamic radius and Mn the number averaged molar mass. From Eq. (8) and using the values for [h ]0 and Mn, a hydrodynamic radius of 39 nm is determined for amylopectin in permeate. Using a theoretical value for the ratio Rg/RH ˆ 1.27 given by Freire, Rey, and Garcia de la Torre (1986), results in a radius of gyration of 50 nm. These values will be used in the phase boundary calculations. 5.2. Macroscopical observations Fig. 4 shows the phase diagram of milk protein± amylopectin systems as obtained by visual inspection after 4 weeks. This graph shows two regions: a homogeneous and a phase separated region. Note the relatively high concentration of amylopectin needed to induce phase separation; much lower concentrations of polysaccharide were required to induce phase separation in mixtures of micellar casein±locust bean gum (Schorsch et al., 1999a,b), micellar casein±guar gum (Bourriot et al., 1999a,b,c) and milk protein±exocellular polysaccharide (Tuinier & de Kruif, 1998, 1999). Fig. 5a shows the (normalised) height of the protein-rich sediment layer as a function of amylopectin concentration. The casein concentration was kept constant at 2.7%. Up to 1% amylopectin the sample is homogeneous (one layer). At higher concentrations, two layers are formed. Note that the height of the protein-rich sediment layer increases with increasing amylopectin concentration. Similar behaviour was observed at other casein concentrations. At ®rst instance, this result is surprising as one would expect an increase in the height of the amylopectin-rich top layer and, thus, a reduction in the height of the protein-rich sediment layer, upon addition of amylopectin. An increasing sediment height with increasing polymer

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P.W. de Bont et al. / Food Hydrocolloids 16 (2002) 127±138

Fig. 4. Bulk phase separation in mixtures of milk proteins and amylopectin as determined by visual inspection (X ˆ not phase separated, S ˆ phase separated). The drawn line represents the binodal as calculated according to Vrij's theory.

concentration was also found by Sperry (1984) for a model system, containing latex colloids and hydroxyethylcellulose; rc ˆ 600 nm, rp ˆ 46 nm. The author suggested a simple model to explain this observation (Fig. 5b). At low polymer concentration, the colloidal particles are supposed to form a more compact sediment layer. At higher polymer concentrations, a space spanning network of colloidal particles is formed, which contains domains of polysaccharide trapped within this network structure, which results in an increasing sediment height. The similarity between Sperry's model system and the milk protein±amylopectin suggests that, also in our case, network formation is occurring at the highest levels of amylopectin. This is con®rmed by CSLM measurements. A CSLM observation after 4 weeks of a 4.2% casein/2.9% amylopectin system (micrograph not shown) shows a network-like structure with protein-rich areas entrapping amylopectin-rich areas. 5.3. Microscopical observations (CSLM) and image analysis CSLM images are presented in Fig. 6 for mixtures consisting of 2.1 or 4.2% caseins with several amounts of amylopectins. The 2.1% casein and 1.5% amylopectin

sample showed a rather homogeneous CSLM image, representative of a non phase separating/stable system. The other images shown in Fig. 6 showed phase separation, with protein-rich areas (white) and amylopectin-rich areas (black). The pictures reveal aggregates of protein particles. The sizes of the protein-rich areas appear to depend on the composition of the mixture and decrease with increasing amylopectin concentration. The number of protein-rich areas increases with increasing casein concentration. The shape of the protein-rich areas also seem to depend on the amylopectin concentration. At low concentrations, the protein aggregates seem to be isolated, whereas at higher concentrations they seem to be more connected. Performing a scan into the z-direction (x±y is the horizontal observation plane) of the sample (up to 40 mm) reveals the interconnection of the aggregated protein areas (network formation) at higher concentrations of caseins and/or amylopectin. Our CSLM observations are in line with those observed in a model study on colloidal polymethylmethacrylate particles and polystyrene mixtures (size ratio: j ˆ 0.08) performed by de Hoog and Lekkerkerker (to be submitted). Fig. 7 shows the application of the described variance measure on several CSLM images. A strong increase (a step) in variance with increasing amylopectin concentration

Fig. 5. (a) The (normalised) sediment height of 2.7% casein and x% amylopectin mixtures, where x ˆ 0, 0.5, 1, 1.5, 1.9, 2.4 and 2.9 (the sediment is formed by the protein-rich phase); (b) normalised sediment height (fsed) and microstructural appearance as suggested by Sperry (1984) for a colloid±polymer mixture with polymer concentration increasing in the order c1 ! c4.

P.W. de Bont et al. / Food Hydrocolloids 16 (2002) 127±138

133

Fig. 5. (continued)

is observed at the highest magni®cation. For 2.1% casein, this step is observed at 1.9% amylopectin, whereas for 4.2% casein, this step is shown at 1.5%. At higher amylopectin concentrations, the variance is decreasing, but its value stays rather high. At the lowest concentrations of caseins (0.5%, not shown) the step is less pronounced, but still visible. The amylopectin concentrations, where a step in variance is

Fig. 7. Normalised variance ( ˆ variance/mean intensity) determined from several CSLM images as a function of amylopectin concentration (%) in mixtures containing 2.1 and 4.2% casein. Image width: V ˆ 65 mm, B ˆ 130 mm, O ˆ 260 mm, £ ˆ 520 mm.

observed, correspond well with the concentrations where bulk phase separation appears (Fig. 4). This is illustrated in Fig. 8, where the variance measure is represented in a casein±amylopectin contour plot. The experimental phase boundary, as determined in Fig. 4, is near the contour line with a variance equal to 20. Above this contour line, the

Fig. 6. CSLM images of mixtures containing 2.1 and 4.2% casein (C) and x% amylopectin (AP), where x ˆ 1.5, 1.9, 2.4 and 4.8. Image width is 65 £ 5 mm. White colour ˆ protein-rich area; black colour ˆ amylopectin-rich area.

Fig. 8. Contour plot showing the normalised variance ( ˆ variance/mean intensity) determined from CSLM images (width ˆ 65 £ 65 mm) in the casein (%)±amylopectin (%) plane. The `experimental' phase boundary is represented by the thick solid line.

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is that information about phase separation can be obtained within several hours after preparation of the mixture, in contrast with the several weeks needed when visual observation is used to establish the occurrence of phase separation. 5.4. Dynamic moduli of phase separating milk protein± amylopectin mixtures

Fig. 9. Dynamic moduli and tan d ( ˆ G 00 /G 0 ) as a function of time for a mixture containing 2.7% casein and 4.8% amylopectin.

variance increases rapidly, which shows that the sudden increase in variance corresponds with the observed phase boundary. The circular behaviour of the contour lines is due to the fact that the variance decreases slightly after the sudden increase. An experimental con®rmation of the qualitative explanation given in Section 3 on the in¯uence of the resolution on the variance measure is given in Fig. 7. The variance values are measured at different magni®cations. At low amylopectin concentration, the system is mixed, at higher concentrations the system phase separates. For low magni®cation (image width 520 mm) the variance values do not differ much for the mixed and separated systems, whereas for high magni®cation (image width 65 mm) the difference in variance values is large. This indicates that the highest obtainable resolution of the used microscope is more or less the `right' resolution for the variance measure of the systems investigated in this paper. (Since the `elementary particles' of the systems investigated are well below the optical resolution of the CSLM, the highresolution situation, as illustrated in Fig. 2, could not be replicated in this experiment.) The obtained results clearly show that CSLM combined with the method of the variance measure can be used as an objective tool to determine the phase boundary of phase separating systems. The advantage of the analysis procedure

Milk protein±amylopectin mixtures were characterised by small deformation measurements. Dynamic moduli (G 0 , G 00 ) were measured as a function of time during the phase separation process. Fig. 9 shows results for a mixture containing 2.7 wt% casein micelles and 4.8 wt% amylopectin. Initially, G 0 and G 00 are small quantities with G 0 . G 00 . Both moduli gradually increase with time, indicating changes in the microstructure of the mixture. After ca. 3 h, G 0 has become larger than G 00 (tan d , 1). The timedependence of the dynamic moduli is characteristic for gelling biopolymer solutions and suggests formation of a gel-like network structure in the milk protein±amylopectin system during phase separation. This is consistent with the observation of interconnected protein aggregate structures (a network) in the confocal micrographs of phase-separated mixtures (Fig. 6) and the model suggested by Sperry (1984) (Fig. 5b). At long measurement times (.8 h), large ¯uctuations are observed in the dynamic moduli (data not shown), with G 0 still larger than G 00 . These ¯uctuations are attributed to the occurrence of bulk phase separation in the milk protein±amylopectin system. 6. Discussion 6.1. Comparison between experiment and theory Vrij's depletion interaction potential was used for calculating the phase boundary of milk protein±amylopectin systems. The result is shown in Fig. 4, using parameters for amylopectin as given in Table 1. To transform f sp (volume fraction of the caseins) into concentration [%], a volume fraction of casein micelles in reconstituted skim milk (2.8% caseins) of 0.13, as determined by Jeurnink and de Kruif (1993), was used. Vrij's model gives a remarkably good description of our experimental results, which suggests that the concept of depletion interaction is allowed in a quantitative description

Table 1 Molecular weight Mn, radius of gyration rg, polymer±colloid size ratio j (with rc ˆ 100 nm) and microstructure of several phase-separated milk protein± polysaccharide mixtures PS Guar gum LBG Amylopectin Dextran

rg (nm)

j ˆ rg/rc

Structure

References

1.09 £ 10 6

97.8

0.98

Droplet

8.5 £ 10 5 12.26 £ 10 6 2 £ 10 6

75 50 35.8

0.75 0.50 0.36

Droplet Network Network

Bourriot et al. (1999a,b,c); Frollini et al. (1995) Schorsch et al. (1999a,b) This work This work; Nordmeier (1993)

Mn (g/mol)

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Fig. 10. Phase boundaries calculated according to Vrij's model for several milk protein±polysaccharide mixtures (see Table 1). GG, guar gum; LBG, locust bean gum; AP, amylopectin; DT, dextran T2000.

of phase separation in mixtures of milk proteins and amylopectin. 6.2. Comparison with other milk protein±polysaccharide systems It has already been mentioned that relatively high concentrations of amylopectin are required to induce phase separation. Much lower concentrations were required in the case of, e.g. locust bean gum (Schorsch et al., 1999a,b) or guar gum (Bourriot et al., 1999a,b,c). This can be explained on basis of Vrij's model. Fig. 10 shows calculated phase boundaries for various milk protein±polysaccharide mixtures using the parameters given in Table 1. The ®gure, indeed, shows that the levels of guar gum or locust bean gum required to induce phase separation are much lower than in the case of amylopectin (or dextran). For example, at 5% casein, the calculated levels of guar gum or locust bean gum needed for phase separation are 0.02 and 0.04%, respectively. For amylopectin, the calculated amount is 1.4%. The experimentally determined levels are roughly 0.04% for guar gum (Bourriot et al., 1999a,b,c),

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0.05% for locust bean gum (Schorsch et al., 1999a,b) and 1.0% for amylopectin, respectively. The calculated phase boundaries give a good description of the experimental results for guar gum and locust bean gum found in the literature. This suggests that the concept of depletion interaction is allowed in a quantitative description of phase separation in mixtures of milk proteins and several polysaccharides. Fig. 11 shows CSLM micrographs of milk protein±guar gum and milk protein±dextran mixtures. Clear differences are observed in the microstructure of both systems. The milk protein±guar gum system shows an emulsion-like microstructure with proteins concentrated in spherical droplets. The microstructure is similar to that reported for micellar casein±guar gum (Bourriot et al., 1999a,b,c) and micellar casein±locust bean gum (Schorsch et al., 1999a,b). The microstructure of the milk protein±dextran systems is similar to that observed for the milk protein±amylopectin system with the appearance of protein aggregate structures. The data suggest that those polysaccharides which induce phase separation at low concentrations (locust bean gum, guar gum) give rise to droplet-shaped structures, whereas polysaccharides, which require high levels of polysaccharides to induce phase separation (amylopectin, dextran), give rise to aggregated microstructures. 6.3. Droplet versus aggregated structures Droplet and aggregate structures were also found by Sperry (1984) in a model study on latex spheres and hydroxyethylcellulose. The author showed that the observed microstructure depended on the size ratio of polymer and colloid (j ). The transition in microstructure was observed for j somewhere between 0.3 and 0.6. Above this transition point, a droplet-like structure and below an aggregated network was observed. It is of interest to see whether such

Fig. 11. CSLM images of a 1.35% casein and 0.5% guar gum mixture (left) and a 2.8% casein and 8% dextran T2000 mixture (right), image width is 65 £ 65 mm.

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Fig. 12. 2-D Fourier transforms of CSLM images: (W) 0.5% casein±3.4% amylopectin; (B) 1.1% casein±2.4% amylopectin. Image width 65 £ 65 mm.

a transition point also exists for the different milk protein± polysaccharide mixtures mentioned above. All necessary parameters for comparison are given in Table 1. Note that systems with a size ratio j # 0.5 (i.e. amylopectin, dextran) form aggregate structures, whereas systems with a large size ratio, .0.7 (i.e. locust bean gum, guar gum), form droplet structures. Apparently, a transition between aggregate structure and droplet-like structure takes place in the interval between j ù 0.5 and 0.7. This is in line with the results obtained by Sperry (1984). In Section 2 it was mentioned that the size ratio parameter j determines the nature of the phase transition in colloid± polymer mixtures. When this ratio is smaller than 0.3, theory predicts separation into ¯uid and crystal phases. For larger polymer to colloid size ratios, theory predicts the existence of several regions in the phase diagram, including a colloid gas±liquid coexistence region (Lekkerkerker et al., 1992). We propose that the droplet structures observed in mixtures of milk proteins and locust bean gum (j ˆ 0.75) or guar gum (j ˆ 0.98) can be associated with the occurrence of a gas±liquid transition. For mixtures of milk proteins and amylopectin (j ˆ 0.5) or dextran (j ˆ 0.36), theory predicts separation into ¯uid and crystal phases only, which explains the absence of dropletlike structures. The observation of aggregate structures in this case is typical for the non-equilibrium behaviour often encountered when the attraction between the colloids is relatively deep and short ranged (Poon et al., 1995; Verhaegh & Lekkerkerker, 1999). It is noted that the transition point predicted by theory (j tp ˆ 0.3) (Gast et al., 1986; Lekkerkerker et al., 1992) is slightly lower than the transition point observed in the case of milk protein±polysaccharide systems (0.5 # j tp # 0.7). The theories are developed for hard colloidal spheres and non-adsorbing polymers. A non-model system, such as the milk protein±polysaccharide system is not expected to behave as such an ideal system. The milk protein particles as well as the polysaccharides are polydisperse. Moreover, the colloids (protein particles) in this system are negatively charged. These factors in¯uence the interaction potential

and may change the size ratio above which gas±liquid transitions are predicted to occur. This size ratio will probably shift to higher values, which makes the size ratio range of 0.5±0.7 found here rather acceptable (Lekkerkerker, 2000). 6.4. Fourier transformation of CSLM images Fourier transformation of CSLM images may be used to obtain quantitative information with respect to characteristic length scales in the system. In principle, the type of information obtained by transformation of CSLM images is similar to that obtained by small angle light scattering (SALS) (Verhaegh, 1996; Verhaegh & Lekkerkerker, 1999). Determination of the absolute value of the 2-D Fourier transform of all CSLM images followed by radially averaging, resulted, for example, in Fig. 12. For clearness, the ®rst pixel of the Fourier transform is removed; its intensity represents the mean value of the whole picture and dominates the other frequencies. All Fourier transforms show initially an increase in intensity as a function of frequency (q), followed by a decrease resulting in a maximum intensity at the low frequency range. However, some maxima were more pronounced than others. The appearance of a maximum indicates the presence of a characteristic length scale in the microstructure, much larger than the radius of the particles. The maxima of 0.5% casein/3.4% amylopectin and 1.1% casein/2.4% amylopectin have a frequency (q) of, respectively, 9 and 6 pixels, corresponding with a length scale in real space of 7.2 and 10.8 mm, respectively. A general observation of the Fourier transforms in a series of mixtures with constant casein concentration is the increase of the position of the maximum with increasing concentration of amylopectin, resulting in a decrease of the characteristic length scale. This is directly visible in the CSLM images shown in Fig. 6. A study already in progress is the determination of the time evolution of the milk protein±amylopectin systems via CSLM. This is done in order to see if different time scaling laws found in SALS experiments on model

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colloid±polymer mixtures (Pusey, Pirie, & Poon, 1993; Rouw, 1987; Verhaegh, 1996; Verhaegh & Lekkerkerker, 1999) are also valid in milk±polysaccharide systems. Besides Fourier analysis, other image analysis tools will also be used to determine the evolution of the characteristic length scales. 7. Conclusions The phase behaviour of milk protein±amylopectin mixtures was studied. Compared with other polysaccharides (exocellular polysaccharide, guar gum, and locust bean gum), phase separation occurs at a relatively high concentration of added amylopectin. A prediction on the basis of Vrij's depletion theory for polymer and colloid mixtures (Vrij. 1976) shows a remarkably good agreement with the experimental results. The experimental phase boundary could also be obtained by CSLM and image analysis (the variance measure). Phase boundaries obtained by visual observation and CSLM/ image analysis were in good agreement. An advantage of the CSLM/image analysis procedure is that information about phase separation can be obtained within several hours after preparation of the mixture, in contrast with the several weeks needed when visual observation is used to establish the occurrence of phase separation. CSLM revealed the appearance of protein aggregates for milk protein±amylopectin systems when phase separation occurs. At high concentrations these aggregates seem to form a network-like structure. This was supported by the evidence obtained from CSLM measurements, small deformation rheology and the increase of the protein sediment height with increased amylopectin levels. The formation of a network is different from the droplet formation observed, e.g. in the case of milk protein±guar gum or milk protein± locust bean gum systems. The observed microstructural difference could be explained using the experimental observations reported by Sperry (1984) and a theoretical description developed by Lekkerkerker et al. (1992) and is ascribed to a low value of the polymer±colloid size ratio for milk protein±amylopectin systems. Acknowledgements AVEBE is kindly acknowledged for supplying the potato amylopectin and performing the SEC analysis and Friesland Coberco Dairy Foods for supplying the high heat skimmed milk powder. Special thanks to C. Vooys of Unilever Research Vlaardingen for his useful assistance during the CSLM measurements and L. Delamair and A. Saffray for performing the intrinsic viscosity measurements. I. BodnaÂr, A.M. Ledeboer, H.N.W. Lekkerkerker and R. Tuinier are kindly acknowledged for fruitful discussions and support and A.H. Clark for critically reading the manuscript. This study was supported by the PBTS Research Program with

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