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The physicochemical parameters during dry heating strongly influence the gelling properties of whey proteins
Journal of Food Engineering 112 (2012) 296–303
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The physicochemical parameters during dry heating strongly influence the gelling properties of whey proteins Muhammad Gulzar a,b,c, Valérie Lechevalier a,b, Saïd Bouhallab a,b, Thomas Croguennec a,b,⇑ a
AGROCAMPUS OUEST, UMR 1253, F-35042 Rennes, France INRA, UMR 1253, F-35042 Rennes, France c University of Veterinary and Animal Sciences, Abdul Qadir Jilani Road, Lahore, Pakistan b
a r t i c l e
i n f o
Article history: Received 24 January 2012 Received in revised form 23 April 2012 Accepted 6 May 2012 Available online 14 May 2012 Keywords: Dry-heating Whey protein powder pH Water activity Temperature of dry heating Gelling properties
a b s t r a c t In this study we determined the composition (proportion of native proteins, soluble and insoluble aggregates) and quantified the gelling properties (gel strength and water holding capacity) of pre-texturized whey proteins by dry heating under controlled physicochemical conditions. For this purpose, a commercial whey protein isolate was dry heated at 80 °C (up to 6 days), 100 °C (up to 24 h) and 120 °C (up to 3 h) under controlled pH (2.5, 4.5 or 6.5) and water activity (0.23, 0.32, or 0.52). Gelling properties were quantified on heat-set gels prepared from reconstituted pre-texturized proteins at 10% and pH 7.0. The formation of dry-heat soluble aggregates enhanced the gelling properties of whey proteins. The maximal gelling properties was achieved earlier by increasing pH and water activity of powders subjected to dry heating. An optimized combination of the dry heating parameters will help to achieve better gelling properties for dry heated whey proteins. Ó 2012 Elsevier Ltd. All rights reserved.
1. Introduction Protein dry heating is intensively used in pharmaceutical and food industry for viral and microbial decontamination of thermosensible proteins. It was noticed that prolonged dry heating also induces denaturation and aggregation of proteins, which could lead to an improvement in the functional properties (gelling, foaming, and emulsifying) of proteins (Kato et al., 1990; Mine, 1997; Watanabe et al., 2000; Matsudomi et al., 2001; Desfougeres et al., 2011). Despite the numerous studies conducted on dry heating of egg white proteins, the process of dry heating is still not well controlled at industrial scale resulting in the variability of functional properties of final products. Functional properties of dry heated proteins are affected by powder physicochemical parameters such as pH (Mine, 1996, 1997; Matsudomi et al., 2001) and water activity, aw (Hammershoj et al., 2006; Van der Plancken et al., 2007) but also conditions for dry heating (Hammershoj et al., 2006). In contrast to egg white proteins, the impact of dry heating on the functional properties of whey proteins was sparsely investigated (Ibrahim et al., 1993; Li et al., 2005) although whey proteins are extensively used to produce various ingredients for food and non-food industries. In addition the natural pH range for whey pro⇑ Corresponding author at: AGROCAMPUS OUEST, UMR 1253, F-35042 Rennes, France. Tel.: +33 2 23 48 59 27. E-mail address: [email protected] (T. Croguennec). 0260-8774/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jfoodeng.2012.05.006
teins, from neutral (sweet whey) to acidic (acid whey), was out of the pH range covered in the studies on the dry heating of egg white proteins for functional improvement purposes. Recent works showed that the dry heating in acidic pH range (pH 2.5–6.5) gives pH-specific aggregates (Gulzar et al., 2011) and also improves the emulsifying and foaming properties of food proteins (Li et al., 2005; Desfougeres et al., 2008). Then, dry heating under acidic conditions constitutes an opportunity to explore for the devise of new whey protein ingredients. In this work we assessed the impact of physicochemical parameters of powder like pH (neutral to acidic), water activity (aw) and processing parameters (temperature and time of dry heating) on the composition (aggregation level of proteins) and gelling properties (gel strength and water holding capacity of heat set gels) of whey proteins (WPI) during the course of dry heating. The aim of the study was to get predictive models for the gelling properties of dry heated whey protein from its composition and the physicochemical parameters used for dry heating (pH and aw of whey protein powders and heat treatment). The pH, aw and temperature (time) ranges under investigation were from 6.5 to 2.5, from 0.23 to 0.52 and from 80 °C (up to 6 days) to 120 °C (up to 3 h), respectively. The pH range covered the diversity of whey proteins produced in the industry and extended toward acidic pH (up to pH 2.5), where whey proteins are heat treated in solution to get specific aggregates (Bolder et al., 2006; Oboroceanu et al., 2010). An aw of 0.23 and heat treatment of 80 °C (up to 6 days) corresponds
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more or less to the aw of spray dried powders produced in the industry and heat treatment classically used for dry heating of egg white proteins to improve their functional properties respectively (Matsudomi et al., 1991; Handa et al., 2001). In some samples aw and temperature were increased to accelerate the mechanism of denaturation/aggregation of whey proteins. 2. Materials and methods 2.1. Materials The spray-dried WPI (Prolacta, Lactalis Ingredient, Bourgbarré, France) contains 90.1 ± 1.0% proteins (w/w) of which 82% is b-lg and 18% is a-La, 6.7 ± 0.2% moisture, 0.88 ± 0.08% of free lactose. Once reconstituted at 10 g/L, the WPI solution had a pH of 6.5. Protein solubility at pH 7.0 and pH 4.6 was 97 ± 3% and 93 ± 3%, respectively. All other chemicals were from Sigma Aldrich (SaintQuentin-Fallavier, France). 2.2. Characterization of spray dried WPI powder Protein content in WPI powder was determined by the Kjeldahl method. The protein composition of the WPI was determined after protein separation on a Vydac C4 214 TP5215 (150 2.1 cm i.d.) reversed-phase chromatography column (AIT, Houilles, France) set on a Waters chromatography system, consisting of a Waters 2695 Separation Module, a Waters 2487 Dual k Absorbance Detector and a Empower chromatography application software (Waters) to acquire, process and report chromatographic information. Moisture content in powder was determined by desiccation at 102 °C for 5 h. Lactose content was quantified using a Lactose/D-Galactose enzymatic kit (Boehringer Mannheim, Darmstadt, Germany). 2.3. Preparation of dry heated powders Spray-dried WPI was dissolved in distilled water at a protein concentration of 15% and the solution was adjusted to three different pH values (2.5, 4.5 and 6.5) using HCl and lyophilized. Then, the samples containing 10 g of powder were stored for 2 weeks in desiccators having three different saturated salt (CH3CO2K, MgCl26H2O and Mg (NO3)2) solutions to reach water activities of 0.23, 0.32, and 0.52 in the powders, respectively. The water activity of powders was checked by aw meter (aw-meter; Novasina RTD 200/0 and RTD 33, Pfäffikon, Switzerland). Powders (pH 2.5, 4.5, and 6.5) adjusted to three different water activities (0.23, 0.32, and 0.52) were heated at 80, 100 and 120 °C for time periods of
pH 7.0
1
Dry heated Proteins
Centrifugation (10,000g, 15min)
Total Sample
No pH adjustment
pH 4.6
1, 3, 6 days, 8, 16, 24 h, and 1, 2, 3 h, respectively, in hermetically sealed bottles. Control samples were not subjected to dry heat treatment. 2.4. Determination of protein fractions Powders were reconstituted in NaCl solutions to have a final concentration of 1% of whey proteins and 0.12 M NaCl in all the samples (solution 1). A part of solution 1 was centrifuged at 10,000g for 15 min using an Eppendorf 5415C Micro Centrifuge (Scientific Support, Hayward, California) in order to remove insoluble aggregates at pH 7. The supernatant (solution 2) contained soluble aggregates and residual native proteins. In the remaining part of solution 1, HCl (1 N) was added to reach a pH value of 4.6. Acidified sample was centrifuged at 10,000g for 15 min using an Eppendorf 5415C Micro Centrifuge (Scientific Support, Hayward, California). Centrifugation resulted in the removal of both soluble and insoluble aggregates at pH 7; subsequently, supernatant at pH 4.6 (solution 3) with only residual native proteins (soluble proteins at pH 4.6) was recovered. The diagrammatic representation of preparation of samples is given in Fig. 1. All the samples were prepared in duplicate. The protein concentration in solutions 1, 2 and 3 was determined by the Lowry method (Lowry et al., 1951) using bovine serum albumin (BSA) as standard. The amount of soluble aggregates was calculated by subtracting protein concentration in solution 3 to solution 2. 2.5. Gelling properties quantification Powders were reconstituted in NaCl solutions containing 0.02% NaN3 to have a final concentration of 10% of whey proteins and 0.12 M NaCl in all the samples. The samples were stirred for at least 48 h for complete dissolution and their pH was adjusted to 7. Then, the samples were put into polyvinylidene tubing of 2.17 cm diameter and heated in a water bath at 90 °C for 30 min. After heating, the gels were immediately cooled by immersing in water for 30 min. The gels were then put at room temperature for 1 h. The tubings were removed and the gels were cut into sections of 20 mm long using 2 parallel metal wires to measure gel strength and WHC. Each piece was placed vertically in a previously weighed Petri dish containing a Whatman paper number 541 and pressed using Universal Testing Machine (Instron, model 4501, Guyancourt, France) equipped with a 4-cm diameter stainless steel plate. The displacement of the plate occurred at stable speed of 0.2 mm per second up to 18 mm (90% of compression) by a plunger with a 100 N load cell. The gel strength was measured as the maximum force at rupture (typical data graph for measuring gel
Residual Native Soluble Aggregates (soluble at pH 7.0)
2
Insoluble Aggregates
Residual Native (soluble at pH 4.6)
Soluble Aggregates Insoluble Aggregates Fig. 1. A diagrammatic representation of preparation of samples.
3
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which transforms a set of possibly correlated variables into new variables, which are mutually orthogonal (uncorrelated) linear combinations of the original variables. These new variables are called principal components (PCs). Each component is defined by the coefficients in the linear combination of the original variables. Samples were then classified by hierarchical cluster analysis (HCA) from the 4 or 5 first PCA dimensions using Parti-decla procedure of SPADÒ (Decisia, Pantin, France).
100
Gel Strength (N)
80
60
3. Results and discussion
40
20
0 0
3
6
9
12
15
18
Plunger displacement (mm) Fig. 2. Force of heat-set gels of whey proteins without dry heat treatment (control sample, thin line) and of whey proteins pretexturized by dry heat treatment, 16 h at 100 °C (thick line) versus plunger displacement. Arrows indicate the maximal gel strength at rupture.
strength at rupture are given on Fig. 2). Water holding capacity (WHC) was calculated from the amount of water recovered in the Petri dish containing the Whatman paper after compression of the vertically set gel according to the following equation:
M M1 100 M
ð1Þ
where M is the amount of water in gel; M1 is the amount of water released. Gel strength and WHC measurements were done in triplicate. 2.6. Statistical analysis The set of data was subjected to statistical analysis by General Linear Model (GLM) procedure of Statgraphics PlusÒ (Manugistics, Rockville, MD, USA). The model of analysis were
Y ijkl ¼ l þ awi þ pHj þ T k þ t l þ ðaw aw Þi þ ðaw pHÞij þ ðaw TÞik þ ðaw tÞil þ ðpH pHÞj þ ðpH TÞjk þ ðpH tÞjl þ ðT TÞj þ ðT tÞjl þ ðt tÞl
ð2Þ
where Y represents the percentage of residual native proteins, soluble aggregates or insoluble aggregates, the gel strength or gel water holding capacity (WHC), ‘‘aw’’ is the water activity (i = 0.23, 0.32 or 0.52), pH (j = 2.5, 4.5 or 6.5), ‘‘T’’ is the temperature (k = 80, 100 or 120 °C), ‘‘t’’ is the time (hours) for heat treatment (l = 0, 1, 2 or 3 h (120 °C); 0, 8, 16 or 24 h (100 °C); 0, 24, 72 or 144 h (80 °C). Before statistical analysis, all the predictive variables were rescaled by taking the lower value as 1 and the maximum value as +1.
Y ¼ a þ b X þ c X2
ð3Þ
where, Y is either the gel strength or WHC and X denotes the percentage of soluble aggregates (%). Data were also subjected to statistical analysis by principal component analysis (PCA) using Copri procedure of SPADÒ (Decisia, Pantin, France). It is a multivariate statistical method,
For building the limits of the experimental design, preliminary experiments were carried out in order to identify dry heating times leading to similar level of denaturation of whey proteins for the dry heating temperature domain investigated. These experiments were conducted on whey protein powders at pH 6.5 and adjusted at aw 0.23. For dry heating temperature fixed at 80, 100 and 120 °C the maximal dry heating time leading to similar level of denaturation of whey proteins were 144, 24 and 3 h, respectively. This correspondence of dry heating conditions (temperature/time) fit with a z value (increase [or decrease] in temperature necessary to make the reaction proceed 10 times faster [slower]) for the disappearance of native whey proteins of 24 °C. These dry heating times were identified by the maximum value +1 in the rescaled predictive variables. All other dry heating times were rescaled in function of the maximal dry heating time at each dry heating temperature from 1 (control sample) to +1. The maximal dry heating time (rescaled at +1) at intermediate temperature in the range 80–120 °C (for instance 108 °C) is obtained by resolution of the equation: 132T 24
tT ¼ 10
ð4Þ
with T, the dry heating temperature and tT, maximal time of dry heating at temperature T. This equation representing the maximal time of dry heating at one selected temperature for whey protein dry-heating in the range 80–120 °C delimits the experimental domain investigated in this study. pH from 2.5 to 6.5 and aw from 0.23 to 0.52 for dry heat treatment are the other limits of the experimental domain. In order to determine the impact of physicochemical and processing parameters (variables: water activity, pH, temperature and time of dry heating) during dry heating on the composition of dry heated proteins and their gelling properties as well as to determine the interactions among these variables, the set of data was subjected to GLM. The models for the percentage of residual native proteins, soluble aggregates, insoluble aggregates, as well as gel strength (N) and gel water holding capacity (%) in function of the physicochemical and processing parameters of dry heating are given in the following equations:
Residual native ð%Þ ¼ 37:98 32:69 time 4:48 pH 8:17 aw 2:85 ðaw temperatureÞ 8:29 ðaw timeÞ 6:44 ðpH timeÞ 2
þ 8:50 temperature2 þ 12:40 time
ð5Þ Soluble aggregates ð%Þ ¼ 44:53 3:80 temperature þ 15:14 time 3:35 pH 4:41 aw 5:98 ðaw pHÞ 8:68 ðaw timeÞ 4:44 ðpH timeÞ 7:94 a2w 2
18:29 time
ð6Þ
299
NS NS NS 0.0013 NS NS 0.002 0.0137 NS 0.0471 NS NS NS NS NS <10 0.0188 <104 NS <104 NS NS NS NS NS 0.0003 <104 <104 NS 0.0002 0.0459 NS 0.0148 0.0442 NS NS 0.0006 0.0036 NS NS <10 0.0019 <104 NS NS
R2 (%)
89.2 66.5 78.9 74.9 59.9 <10 <104 0.0145 <104 <104 <10 NS <104 NS 0.0683
4
Time time Temp Temp pH pH aw aw
4
0.0001 0.0198 <104 0.0001 <104 <10 <104 <104 <104 <104
All the models follow a second order polynomial evolution versus time of dry heating. The percentage of residual native proteins and insoluble aggregates exhibit opposite trends: The percentage of residual native proteins continuously decreases with extended dry heating time (Eq. (5)) whereas the percentage of insoluble aggregates continuously increased (Eq. (7)). In contrast, the percentage of soluble aggregates and the gelling properties (gel strength and WHC) increase to a maximum for intermediate heating time (level 0) and when the heating time is extended the percentage of soluble aggregates and the gelling properties start decreasing (Eqs. (6), (8), and (10)). This result clearly points out soluble aggregates are for a large part responsible for the increase of the gelling properties of dry heated proteins. The formation of insoluble aggregates and/or the lack of sufficient amount of residual native protein after extended dry heating times have detrimental effects on gelling properties of proteins in agreement with previous results (Mine, 1997). In addition, time of dry heating in interaction with powder aw and pH also affects the composition of dry heated proteins and the gel strength. The effect of these factors and interactions with time will be discussed below.
NS 0.0119 0.0197 <104 NS
3.1. Effect of dry heating time
Residual native Soluble aggregates Insoluble aggregates WHC Gel strength
In these equations, only the physicochemical and processing parameters and their interactions which are significant at p-values less than 0.05 are considered (Table 1). The models R2 values for the percentage of residual native proteins, soluble aggregates and insoluble aggregates as well as gel strength and water holding capacity are 89.2%, 66.5%, 78.9%, 59.9%, and 74.9%, respectively. The models give the combination of variables to control the composition (residual native proteins, soluble and insoluble aggregates) of dry heated whey proteins and to optimize their gelling properties (gel strength and water holding capacity). Among the physicochemical and processing parameters investigated in this study, time of dry heating is the most prevalent variable for explaining the changes in composition and gelling properties of dry heated proteins. Powder aw and pH are also significant variables in all the models, but their effects are tuned by an interaction with the time of dry heating. Finally, the effect of dry heating temperature is less but this was expected regarding the way the experimental design was built (see above). The GLM also indicates interactions between some variables affecting both powder composition and gel properties (Table 1). The effect of these variables and their interactions are discussed below.
Temp time
ð9Þ
4
2
pH time
1:97 pH2 5:26 time
pH Temp
Water holding capacity ¼ 96:02 þ 1:41 pH 1:67 temperature þ 4:60 time 0:89 ðaw temperatureÞ
aw time
ð8Þ
aw Temp
2
þ 2:59 a2w 11:00 time
aw pH
3:90 ðaw timeÞ 7:05 ðpH timeÞ
4
Gel strength ¼ 28:17 3:63 pH 4:04 time
aw
ð7Þ
pH
2
10:82 temperature2 þ 6:11 time
4
þ 13:86 ðaw timeÞ þ 10:87 ðpH timeÞ þ 5:91 a2w
Time
þ 12:66 aw þ 4:71 ðaw pHÞ þ 4:22 ðaw temperatureÞ
Temp
þ 17:53 time þ 7:71 pH
Variable
Insoluble aggregates ð%Þ ¼ 20:00 þ 3:32 temperature
Table 1 The table represents the R2 values of the models for residual native proteins, soluble and insoluble aggregates, gel strength and water holding capacity (WHC) as well as the p-values of different variables and their significant interactions obtained by GLM. NS, non significant.
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3.2. Effect of dry heating temperature Taking into account all the data of the GLM, the model (Eq. (5)) indicates that the dry heating temperature has a quadratic effect on the percentage of residual native whey proteins. The average percentage of residual native proteins is lower for a dry heating temperature fixed at 100 °C than at 80 or 120 °C. The effect of dry heating temperature is dependent on powder aw as indicated by the interaction between these two variables. The percentage of soluble aggregates linearly decreases by increasing the dry heating temperature while the percentage of insoluble aggregates tends to increase (Eqs. (6) and (7)). However the temperature effect is quite small compared to other variables in the different models describing the composition of dry heated powder. The temperature for dry heating does not affect the gel strength. In contrast, an increase of the temperature for dry heating decreases WHC of whey protein gel. This decrease follows the de-
crease in the percentage of soluble aggregates in dry heated samples. 3.3. Effect of pH Increasing the pH for dry heating from 2.5 to 6.5 induces a decrease of the percentage of residual native proteins. This decrease is accompanied by the formation of soluble aggregates and insoluble aggregates. However for a given dry heating time, the percentage of soluble aggregates continuously decreases and the percentage of insoluble aggregates increases when pH increases. For instance, the models (Eqs. (6) and (7)) indicate that at pH 2.5 and 6.5, the percentage of soluble aggregates obtained for longer heating times are 49% and 33%, respectively, while the percentages of insoluble aggregates reach 25% and 65% respectively (when the other variables are fixed at level 0). The change in whey protein composition is also dependent on an interaction between pH and
Fig. 3. Principal component analysis showing the two principal components of significant 10 variables: (A) correlation circle of continuous variables (gelling properties, native proteins, soluble aggregates, insoluble aggregates, water activity, pH, temperature and time of dry heating). (B) the distribution of different samples and their classes determined by hierarchical cluster analysis. The different classes are noted 1, 2 and 3 and are obtained by the Ward method using the Euclidean distance between samples and/or clusters to merge (bottom-upapproach) in a field defined by the 5 principal components of the PCA. Classes 1, 2 and 3 gather 50, 52 and 18 samples, respectively, and its mean Euclidean distance is 2.230, 1.652 and 14.674, respectively.
M. Gulzar et al. / Journal of Food Engineering 112 (2012) 296–303
time of dry heating. This result is in agreement with previous studies showing that the rate of heat denaturation/aggregation of whey proteins in dry state is influenced by the pH of the powder (Gulzar et al., 2011); The rate of denaturation/aggregation of whey proteins increased by increasing the pH during dry heating leading to larger amount of insoluble aggregates (Mine, 1996; Gulzar et al., 2011). The pH for dry heating also impact on the gelling properties (gel strength and WHC). In GLM (Table 1), the p-values of effect of pH for gel strength and water holding capacity are <104 and 0.0001, respectively. According to the model, the gel strength is maximal for a whey protein powder dry heated at pH 2.5 for intermediate dry heating time (level 0). The gel strength decreases with increasing pH for dry heating and this decrease is accentuated when dry heating time is extended (level +1). The weakest gels are obtained for dry heated powders containing the higher amount of insoluble aggregates (pH 6.5 and longer heating time). The presence of insol-
301
uble aggregates is detrimental to obtain whey protein gels with high gel strength. In contrast, the moderate denaturation/aggregation of whey proteins at pH 2.5, leading mainly to soluble aggregates, enhances the gelling behavior of dry heated whey proteins. In contrast to gel strength, gel WHC follows a second order polynomial evolution according to pH for dry heating: the WHC is increased by increasing pH from 2.5 to 4.5 and then level off. Hence, the quantity of aggregates (soluble and insoluble) required for good WHC is higher than for maximal gel strength. 3.4. Effect of water activity The results of GLM show that increasing powder aw decreases the percentage of residual native proteins after one defined dry heating time. The denatured proteins are first converted into soluble aggregates and then insoluble aggregates. This is indicated by
Fig. 4. Principal component analysis using the samples containing only soluble aggregates, showing the two principal components of significant variables: (A) correlation circle of continuous variables (gelling properties, native proteins, soluble aggregates, water activity, pH, temperature and time). (B) The distribution of different samples and their classes determined by hierarchical classification are presented in. The different classes are noted 1, 2 and 3 and are obtained by the Ward method using the Euclidean distance between samples and/or clusters to merge (bottom-up approach) in a field defined by the 4 principal components of the PCA. Classes 1, 2 and 3 gather 21, 23, and 24 samples respectively and its mean Euclidean distance is 0.9, 3.92 and 4.09, respectively.
M. Gulzar et al. / Journal of Food Engineering 112 (2012) 296–303
A)
48 43
gel strength (N)
the quadratic effect of aw on the percentage of soluble aggregates and the linear increase of the percentage of insoluble aggregates with powder aw. In addition, the composition of the dry heated powders is affected by an interaction (aw time). The lower the aw, the slower the conversion of native proteins into insoluble aggregates. In fact, when the aw in the powder is reduced, molecular motions are decreased leading to a slowing down of diffusion-controlled reactions (Zhou and Labuza, 2007). In other words, proteins have less chance of making aggregates. The powder composition is also affected by the interactions (aw temperature) and (aw pH). Protein stability toward heat denaturation is increased by decreasing the water activity of whey proteins (Zhou and Labuza, 2007). These authors have shown that at aw of 0.23, 0.32 and 0.52 the proteins in WPI have a denaturation temperature of 163, 150, and 132 °C, respectively. So the concomitant decrease in the denaturation temperature and increase in the mobility of protein molecules at higher aw enhances the denaturation/aggregation of whey proteins during dry heating explaining the (aw temperature) interaction. The effect of aw is also dependent on the pH of the powder subjected to dry heating. At pH 2.5, the percentage of soluble and insoluble aggregates in the dry heated powder is weakly affected by powder aw. In contrast the powder aw has strong impact on the ratio between soluble and insoluble aggregates when pH increases. Gel strength is affected by powder aw (quadratic effect) and an interaction (aw time) while the WHC is affected by an interaction (aw temperature). The set of data was also subjected to principal component analysis (PCA). The principal component 1 and 2 of PCA explain 90.58% of variability showing the reliability of analysis (Fig. 3A). The results of PCA shows a positive correlation (0.71) among gel strength and water holding capacity, however both the gel strength and water holding capacity have a negative correlation (0.76 and 0.85, respectively) with insoluble aggregates. However, it has been observed that the gelling properties (gel strength and WHC) were only correlated with soluble aggregates at 21% and 36%, respectively, and residual native proteins at 46% and 49% respectively; gel strength and water holding capacity are projected in between residual native proteins and soluble aggregates. The same data were also subjected to hierarchical cluster analysis using the Ward method (Fig. 3B). All the samples have been classified into three classes using the 5 first PCA dimensions. In the 1st class (50 samples), the samples were composed of mainly native proteins (82.4 ± 8.8%) and a small amount of denatured/ aggregated proteins. The 2nd class (52 samples) gathered the samples which have the larger amount of soluble aggregates (48.5 ± 10.6%) in addition to residual native proteins (37.3 ± 12.7%). The samples in this class exhibit better gelling properties than control sample. In the 3rd class (18 samples), all the samples contained insoluble aggregates (69.4 ± 18.2%) and formed gels with strength and water holding capacity significantly lower than control sample. These results indicate that the solubility of dry heated proteins at heating pH is indispensable for good gelling properties which is also in agreement with previous results (Mine, 1997). In fact, if insoluble aggregates are present in the samples then the quantity of proteins that participates in the formation of gel network is reduced. So, in order to estimate the fractions of soluble aggregates and native residual proteins that optimize the strength and water holding capacity of the gel of dry heated samples, the samples with insoluble aggregates (with an error of ±10% to take into account the error of method for measurement) were excluded and the new set of data was subjected again to principal component analysis (Fig. 4). It was observed that the WHC was positively correlated (0.83) with the quantity of soluble aggregates in the samples and at the same time have negative correlation (0.80) with residual native proteins. In contrast, the gel strength
38 33 28 23 18 0
20 40 60 Soluble Aggregates (%)
80
0
20 40 60 Soluble Aggregates (%)
80
B) 100 97
WHC (%)
302
94 91 88 85 82
Fig. 5. Representation of the relative gel strength (%) (A) and WHC (%) (B) as a function of the fraction of soluble aggregates (%) in the samples. The model prediction is indicated in straight line. Confidence limit at 95% and prediction limit at 95% are indicated by dashed lines and dotted lines respectively.
was not correlated with soluble aggregates and residual native proteins. The hierarchical cluster analysis of these samples resulted in 3 classes. In the 1st class (21 samples) the samples have the higher gel strength (36.5 ± 5.0 N) and a moderate quantity of soluble aggregates (from 28 ± 9.5%) and native proteins (67.8 ± 10.3%). In the 2nd class (23 samples) the samples with good WHC (96.2 ± 1.7%) are presented. These samples have higher quantity of soluble aggregates (54.6 ± 7.9%). In the 3rd class (24 samples), the samples have the lower gelling properties and contain mainly native proteins (87.5 ± 6.4%) or very small amount of soluble aggregates. In order to determine the proportion of residual native proteins and soluble aggregates leading to maximum gel strength and gel WHC, the data were subjected to a GLM. The equations for maximum gel strength (N) and WHC (%) are given below with soluble aggregates expressed in percentage of total proteins in the samples (%):
Gel Strength ðNÞ ¼ 21:03 þ 0:80 soluble aggregates 0:012 soluble aggregates 2
ð10Þ
Water holding capacityðWHCÞ ¼ 85:10 þ 0:20 soluble aggregates
ð11Þ
Gel strength (Eq. (11)) follows a second order polynomial evolution according to the percentage of soluble aggregates. In the absence of dry heat treatment (control sample), the gel strength was 21.03 N. According to the model, the gel strength was enhanced up to 34.66 N by increasing the proportion of soluble aggregates in the samples up to 30–40% (Fig. 5A). If the proportion of soluble aggregates is increased above 40% then a decrease in the gel strength is observed suggesting that a substantial amount of residual native proteins is required for optimizing the connectivity
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of dry heated proteins during the heat set gelation and obtaining gels with high gel strength in agreement with Nicolai et al., 2011. However the model does not explain the large part of variability in the experimental data expressed by a R2 (%) value of 40%. For instance the gels formed from samples having a proportion of soluble aggregates between 30% and 40%, exhibit gel strength from 28.14 to 44.52 N. This indicates that the gel strength depends upon certain other parameters also. In fact our previous results (Gulzar et al., 2011) using the same WPI, showed that in addition to the quantity of aggregates, the structure of the soluble aggregates changes according to the conditions for dry heating, especially pH conditions: the size of soluble aggregates and the type of bonding in the aggregates changed according to the pH for dry heating (Mine, 1996; Gulzar et al., 2011). This study does not integrate the physical and chemical properties (type, shape, and size) of aggregates, which may explain the dispersion of the data on gel strength of dry heated whey proteins. The model for gel WHC (Eq. 11) has high significance level as its probability was less than 104. The WHC has strong linear relation (0.83) with soluble aggregates. In this study the proportion of soluble aggregates vary up to 67%; in this range, if the proportion of soluble aggregates increases in the samples, the gel WHC is enhanced (Fig. 5B). Consequently, the proportion of soluble aggregates required for WHC is higher than for gel strength in agreement with the results of Mine (1997). In addition, the model explains higher part of the variation in the data as the value of R2 was 69.5 (%). 4. Conclusion Dry heating strongly affects the gelling properties of whey proteins. The gel strength and water holding capacity of dry heated proteins are improved up to a maximum point then they start decreasing due to excessive denaturation/aggregation of whey proteins leading to insoluble aggregates. It was observed that the optimal point for gel strength and water holding capacity may be achieved earlier by increasing the pH, water activity or temperature during dry heating. The optimal point for water holding capacity requires higher amount of soluble aggregates than for optimal gel strength. In dry heated samples with an absence of insoluble aggregates the water holding capacity of heat set gels increase linearly with the amount of soluble aggregates. The structure and properties of soluble aggregates obtained by dry heating give them an excellent ability to reduce water release from heat set gels, but they seem to have a limited reactivity for building gels exhibiting high strength. However, dry heating conditions leading to samples containing residual native proteins and soluble aggregates up to 35–40% give the higher gel strength improvement. Powder water activity and pH significantly affect the functional properties of whey proteins so a strict control of these parameters is necessary to ensure the reproducibility of final product. Modelization of these physicochemical parameters helps us to standardize dry heat treatment for maximum gelling properties and also reduces the energy consumption during dry heating.
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Acknowledgement We would like to thank Higher Education Commission of Pakistan and INRA, Rennes for the financial support of this work. We are highly grateful to Marie Hélène Famelart for help in gelling experiments and Pierre Schuck for the provision of commercial WPI. References Bolder, S.G., Hendrickx, H., Sagis, L.M.C., van der Linden, E., 2006. Fibril assemblies in aqueous whey protein mixtures. Journal of Agricultural and Food Chemistry 54, 4229–4234. Desfougeres, Y., Jardin, J., Lechevalier, V., Pezennec, S., Nau, F., 2011. Succinimidyl residue formation in hen egg-white lysozyme favors the formation of intermolecular covalent bonds without affecting its tertiary structure. Biomacromolecules 12, 156–166. Desfougeres, Y., Lechevalier, V., Pezennec, S., Artzner, F., Nau, F., 2008. Dry-heating makes hen egg white lysozyme an efficient foaming agent and enables its bulk aggregation. Journal of Agricultural and Food Chemistry 56, 5120–5128. Gulzar, M., Bouhallab, S., Jeantet, R., Schuck, P., Croguennec, T., 2011. Influence of pH on the dry heat-induced denaturation/aggregation of whey proteins. Food Chemistry 129, 110–116. Hammershoj, M., Rasmussen, H.C., Carstens, J.H., Pedersen, H., 2006. Drypasteurization of egg albumen powder in a fluidized bed. II. Effect on functional properties: gelation and foaming. International Journal of Food Science and Technology 41, 263–274. Handa, A., Hayashi, K., Shidara, H., Kuroda, N., 2001. Correlation of the protein structure and gelling properties in dried egg white products. Journal of Agricultural and Food Chemistry 49, 3957–3964. Ibrahim, H.R., Kobayashi, K., Kato, A., 1993. Improvement of the surface functionalproperties of beta-lactoglobulin and alpha-lactalbumin by heating in a dry state. Bioscience Biotechnology and Biochemistry 57, 1549–1552. Kato, A., Ibrahim, H.R., Watanabe, H., Honma, K., Kobayashi, K., 1990. Structural and gelling properties of dry-heating egg-white proteins. Journal of Agricultural and Food Chemistry 38, 32–37. Li, C.P., Enomoto, H., Ohki, S., Ohtomo, H., Aoki, T., 2005. Improvement of functional properties of whey protein isolate through glycation and phosphorylation by dry heating. Journal of Dairy Science 88, 4137–4145. Lowry, O.H., Rosebrough, N.J., Farr, A.L., Randall, R.J., 1951. Protein measurement with the Folin phenol reagent. Journal of Biological Chemistry 193, 265–275. Matsudomi, N., Ishimura, Y., Kato, A., 1991. Improvement of gelling properties of ovalbumin by heating in dry state. Agricultural and Biological Chemistry 55, 879–881. Matsudomi, N., Takahashi, H., Miyata, T., 2001. Some structural properties of ovalbumin heated at 80 °C in the dry state. Food Research International 34, 229–235. Mine, Y., 1996. Effect of pH during the dry heating on the gelling properties of egg white proteins. Food Research International 29, 155–161. Mine, Y., 1997. Effect of dry heat and mild alkaline treatment on functional properties of egg white proteins. Journal of Agricultural and Food Chemistry 45, 2924–2928. Nicolai, T., Britten, M., Schmitt, C., 2011. Beta-lactoglobulin and WPI aggregates: formation, structure and applications. Food Hydrocolloids 25, 1945–1962. Oboroceanu, D., Wang, L.Z., Brodkorb, A., Magner, E., Auty, M.A.E., 2010. Characterization of beta-lactoglobulin fibrillar assembly using atomic force microscopy, polyacrylamide gel electrophoresis, and in situ Fourier transform infrared spectroscopy. Journal of Agricultural and Food Chemistry 58, 3667– 3673. Van der Plancken, I., Van Loey, A., Hendrickx, M., 2007. Effect of moisture content during dry-heating on selected physicochemical and functional properties of dried egg white. Journal of Agricultural and Food Chemistry 55, 127–135. Watanabe, K., Nakamura, Y., Xu, J.Q., Shimoyamada, M., 2000. Inhibition against heat coagulation of ovotransferrin by ovalbumin dry-heated at 120 °C. Journal of Agricultural and Food Chemistry 48, 3965–3972. Zhou, P., Labuza, T.P., 2007. Effect of water content on glass transition and protein aggregation of whey protein powders during short-term storage. Food Biophysics 2, 108–116.
Contents lists available at SciVerse ScienceDirect
Journal of Food Engineering journal homepage: www.elsevier.com/locate/jfoodeng
The physicochemical parameters during dry heating strongly influence the gelling properties of whey proteins Muhammad Gulzar a,b,c, Valérie Lechevalier a,b, Saïd Bouhallab a,b, Thomas Croguennec a,b,⇑ a
AGROCAMPUS OUEST, UMR 1253, F-35042 Rennes, France INRA, UMR 1253, F-35042 Rennes, France c University of Veterinary and Animal Sciences, Abdul Qadir Jilani Road, Lahore, Pakistan b
a r t i c l e
i n f o
Article history: Received 24 January 2012 Received in revised form 23 April 2012 Accepted 6 May 2012 Available online 14 May 2012 Keywords: Dry-heating Whey protein powder pH Water activity Temperature of dry heating Gelling properties
a b s t r a c t In this study we determined the composition (proportion of native proteins, soluble and insoluble aggregates) and quantified the gelling properties (gel strength and water holding capacity) of pre-texturized whey proteins by dry heating under controlled physicochemical conditions. For this purpose, a commercial whey protein isolate was dry heated at 80 °C (up to 6 days), 100 °C (up to 24 h) and 120 °C (up to 3 h) under controlled pH (2.5, 4.5 or 6.5) and water activity (0.23, 0.32, or 0.52). Gelling properties were quantified on heat-set gels prepared from reconstituted pre-texturized proteins at 10% and pH 7.0. The formation of dry-heat soluble aggregates enhanced the gelling properties of whey proteins. The maximal gelling properties was achieved earlier by increasing pH and water activity of powders subjected to dry heating. An optimized combination of the dry heating parameters will help to achieve better gelling properties for dry heated whey proteins. Ó 2012 Elsevier Ltd. All rights reserved.
1. Introduction Protein dry heating is intensively used in pharmaceutical and food industry for viral and microbial decontamination of thermosensible proteins. It was noticed that prolonged dry heating also induces denaturation and aggregation of proteins, which could lead to an improvement in the functional properties (gelling, foaming, and emulsifying) of proteins (Kato et al., 1990; Mine, 1997; Watanabe et al., 2000; Matsudomi et al., 2001; Desfougeres et al., 2011). Despite the numerous studies conducted on dry heating of egg white proteins, the process of dry heating is still not well controlled at industrial scale resulting in the variability of functional properties of final products. Functional properties of dry heated proteins are affected by powder physicochemical parameters such as pH (Mine, 1996, 1997; Matsudomi et al., 2001) and water activity, aw (Hammershoj et al., 2006; Van der Plancken et al., 2007) but also conditions for dry heating (Hammershoj et al., 2006). In contrast to egg white proteins, the impact of dry heating on the functional properties of whey proteins was sparsely investigated (Ibrahim et al., 1993; Li et al., 2005) although whey proteins are extensively used to produce various ingredients for food and non-food industries. In addition the natural pH range for whey pro⇑ Corresponding author at: AGROCAMPUS OUEST, UMR 1253, F-35042 Rennes, France. Tel.: +33 2 23 48 59 27. E-mail address: [email protected] (T. Croguennec). 0260-8774/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jfoodeng.2012.05.006
teins, from neutral (sweet whey) to acidic (acid whey), was out of the pH range covered in the studies on the dry heating of egg white proteins for functional improvement purposes. Recent works showed that the dry heating in acidic pH range (pH 2.5–6.5) gives pH-specific aggregates (Gulzar et al., 2011) and also improves the emulsifying and foaming properties of food proteins (Li et al., 2005; Desfougeres et al., 2008). Then, dry heating under acidic conditions constitutes an opportunity to explore for the devise of new whey protein ingredients. In this work we assessed the impact of physicochemical parameters of powder like pH (neutral to acidic), water activity (aw) and processing parameters (temperature and time of dry heating) on the composition (aggregation level of proteins) and gelling properties (gel strength and water holding capacity of heat set gels) of whey proteins (WPI) during the course of dry heating. The aim of the study was to get predictive models for the gelling properties of dry heated whey protein from its composition and the physicochemical parameters used for dry heating (pH and aw of whey protein powders and heat treatment). The pH, aw and temperature (time) ranges under investigation were from 6.5 to 2.5, from 0.23 to 0.52 and from 80 °C (up to 6 days) to 120 °C (up to 3 h), respectively. The pH range covered the diversity of whey proteins produced in the industry and extended toward acidic pH (up to pH 2.5), where whey proteins are heat treated in solution to get specific aggregates (Bolder et al., 2006; Oboroceanu et al., 2010). An aw of 0.23 and heat treatment of 80 °C (up to 6 days) corresponds
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more or less to the aw of spray dried powders produced in the industry and heat treatment classically used for dry heating of egg white proteins to improve their functional properties respectively (Matsudomi et al., 1991; Handa et al., 2001). In some samples aw and temperature were increased to accelerate the mechanism of denaturation/aggregation of whey proteins. 2. Materials and methods 2.1. Materials The spray-dried WPI (Prolacta, Lactalis Ingredient, Bourgbarré, France) contains 90.1 ± 1.0% proteins (w/w) of which 82% is b-lg and 18% is a-La, 6.7 ± 0.2% moisture, 0.88 ± 0.08% of free lactose. Once reconstituted at 10 g/L, the WPI solution had a pH of 6.5. Protein solubility at pH 7.0 and pH 4.6 was 97 ± 3% and 93 ± 3%, respectively. All other chemicals were from Sigma Aldrich (SaintQuentin-Fallavier, France). 2.2. Characterization of spray dried WPI powder Protein content in WPI powder was determined by the Kjeldahl method. The protein composition of the WPI was determined after protein separation on a Vydac C4 214 TP5215 (150 2.1 cm i.d.) reversed-phase chromatography column (AIT, Houilles, France) set on a Waters chromatography system, consisting of a Waters 2695 Separation Module, a Waters 2487 Dual k Absorbance Detector and a Empower chromatography application software (Waters) to acquire, process and report chromatographic information. Moisture content in powder was determined by desiccation at 102 °C for 5 h. Lactose content was quantified using a Lactose/D-Galactose enzymatic kit (Boehringer Mannheim, Darmstadt, Germany). 2.3. Preparation of dry heated powders Spray-dried WPI was dissolved in distilled water at a protein concentration of 15% and the solution was adjusted to three different pH values (2.5, 4.5 and 6.5) using HCl and lyophilized. Then, the samples containing 10 g of powder were stored for 2 weeks in desiccators having three different saturated salt (CH3CO2K, MgCl26H2O and Mg (NO3)2) solutions to reach water activities of 0.23, 0.32, and 0.52 in the powders, respectively. The water activity of powders was checked by aw meter (aw-meter; Novasina RTD 200/0 and RTD 33, Pfäffikon, Switzerland). Powders (pH 2.5, 4.5, and 6.5) adjusted to three different water activities (0.23, 0.32, and 0.52) were heated at 80, 100 and 120 °C for time periods of
pH 7.0
1
Dry heated Proteins
Centrifugation (10,000g, 15min)
Total Sample
No pH adjustment
pH 4.6
1, 3, 6 days, 8, 16, 24 h, and 1, 2, 3 h, respectively, in hermetically sealed bottles. Control samples were not subjected to dry heat treatment. 2.4. Determination of protein fractions Powders were reconstituted in NaCl solutions to have a final concentration of 1% of whey proteins and 0.12 M NaCl in all the samples (solution 1). A part of solution 1 was centrifuged at 10,000g for 15 min using an Eppendorf 5415C Micro Centrifuge (Scientific Support, Hayward, California) in order to remove insoluble aggregates at pH 7. The supernatant (solution 2) contained soluble aggregates and residual native proteins. In the remaining part of solution 1, HCl (1 N) was added to reach a pH value of 4.6. Acidified sample was centrifuged at 10,000g for 15 min using an Eppendorf 5415C Micro Centrifuge (Scientific Support, Hayward, California). Centrifugation resulted in the removal of both soluble and insoluble aggregates at pH 7; subsequently, supernatant at pH 4.6 (solution 3) with only residual native proteins (soluble proteins at pH 4.6) was recovered. The diagrammatic representation of preparation of samples is given in Fig. 1. All the samples were prepared in duplicate. The protein concentration in solutions 1, 2 and 3 was determined by the Lowry method (Lowry et al., 1951) using bovine serum albumin (BSA) as standard. The amount of soluble aggregates was calculated by subtracting protein concentration in solution 3 to solution 2. 2.5. Gelling properties quantification Powders were reconstituted in NaCl solutions containing 0.02% NaN3 to have a final concentration of 10% of whey proteins and 0.12 M NaCl in all the samples. The samples were stirred for at least 48 h for complete dissolution and their pH was adjusted to 7. Then, the samples were put into polyvinylidene tubing of 2.17 cm diameter and heated in a water bath at 90 °C for 30 min. After heating, the gels were immediately cooled by immersing in water for 30 min. The gels were then put at room temperature for 1 h. The tubings were removed and the gels were cut into sections of 20 mm long using 2 parallel metal wires to measure gel strength and WHC. Each piece was placed vertically in a previously weighed Petri dish containing a Whatman paper number 541 and pressed using Universal Testing Machine (Instron, model 4501, Guyancourt, France) equipped with a 4-cm diameter stainless steel plate. The displacement of the plate occurred at stable speed of 0.2 mm per second up to 18 mm (90% of compression) by a plunger with a 100 N load cell. The gel strength was measured as the maximum force at rupture (typical data graph for measuring gel
Residual Native Soluble Aggregates (soluble at pH 7.0)
2
Insoluble Aggregates
Residual Native (soluble at pH 4.6)
Soluble Aggregates Insoluble Aggregates Fig. 1. A diagrammatic representation of preparation of samples.
3
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which transforms a set of possibly correlated variables into new variables, which are mutually orthogonal (uncorrelated) linear combinations of the original variables. These new variables are called principal components (PCs). Each component is defined by the coefficients in the linear combination of the original variables. Samples were then classified by hierarchical cluster analysis (HCA) from the 4 or 5 first PCA dimensions using Parti-decla procedure of SPADÒ (Decisia, Pantin, France).
100
Gel Strength (N)
80
60
3. Results and discussion
40
20
0 0
3
6
9
12
15
18
Plunger displacement (mm) Fig. 2. Force of heat-set gels of whey proteins without dry heat treatment (control sample, thin line) and of whey proteins pretexturized by dry heat treatment, 16 h at 100 °C (thick line) versus plunger displacement. Arrows indicate the maximal gel strength at rupture.
strength at rupture are given on Fig. 2). Water holding capacity (WHC) was calculated from the amount of water recovered in the Petri dish containing the Whatman paper after compression of the vertically set gel according to the following equation:
M M1 100 M
ð1Þ
where M is the amount of water in gel; M1 is the amount of water released. Gel strength and WHC measurements were done in triplicate. 2.6. Statistical analysis The set of data was subjected to statistical analysis by General Linear Model (GLM) procedure of Statgraphics PlusÒ (Manugistics, Rockville, MD, USA). The model of analysis were
Y ijkl ¼ l þ awi þ pHj þ T k þ t l þ ðaw aw Þi þ ðaw pHÞij þ ðaw TÞik þ ðaw tÞil þ ðpH pHÞj þ ðpH TÞjk þ ðpH tÞjl þ ðT TÞj þ ðT tÞjl þ ðt tÞl
ð2Þ
where Y represents the percentage of residual native proteins, soluble aggregates or insoluble aggregates, the gel strength or gel water holding capacity (WHC), ‘‘aw’’ is the water activity (i = 0.23, 0.32 or 0.52), pH (j = 2.5, 4.5 or 6.5), ‘‘T’’ is the temperature (k = 80, 100 or 120 °C), ‘‘t’’ is the time (hours) for heat treatment (l = 0, 1, 2 or 3 h (120 °C); 0, 8, 16 or 24 h (100 °C); 0, 24, 72 or 144 h (80 °C). Before statistical analysis, all the predictive variables were rescaled by taking the lower value as 1 and the maximum value as +1.
Y ¼ a þ b X þ c X2
ð3Þ
where, Y is either the gel strength or WHC and X denotes the percentage of soluble aggregates (%). Data were also subjected to statistical analysis by principal component analysis (PCA) using Copri procedure of SPADÒ (Decisia, Pantin, France). It is a multivariate statistical method,
For building the limits of the experimental design, preliminary experiments were carried out in order to identify dry heating times leading to similar level of denaturation of whey proteins for the dry heating temperature domain investigated. These experiments were conducted on whey protein powders at pH 6.5 and adjusted at aw 0.23. For dry heating temperature fixed at 80, 100 and 120 °C the maximal dry heating time leading to similar level of denaturation of whey proteins were 144, 24 and 3 h, respectively. This correspondence of dry heating conditions (temperature/time) fit with a z value (increase [or decrease] in temperature necessary to make the reaction proceed 10 times faster [slower]) for the disappearance of native whey proteins of 24 °C. These dry heating times were identified by the maximum value +1 in the rescaled predictive variables. All other dry heating times were rescaled in function of the maximal dry heating time at each dry heating temperature from 1 (control sample) to +1. The maximal dry heating time (rescaled at +1) at intermediate temperature in the range 80–120 °C (for instance 108 °C) is obtained by resolution of the equation: 132T 24
tT ¼ 10
ð4Þ
with T, the dry heating temperature and tT, maximal time of dry heating at temperature T. This equation representing the maximal time of dry heating at one selected temperature for whey protein dry-heating in the range 80–120 °C delimits the experimental domain investigated in this study. pH from 2.5 to 6.5 and aw from 0.23 to 0.52 for dry heat treatment are the other limits of the experimental domain. In order to determine the impact of physicochemical and processing parameters (variables: water activity, pH, temperature and time of dry heating) during dry heating on the composition of dry heated proteins and their gelling properties as well as to determine the interactions among these variables, the set of data was subjected to GLM. The models for the percentage of residual native proteins, soluble aggregates, insoluble aggregates, as well as gel strength (N) and gel water holding capacity (%) in function of the physicochemical and processing parameters of dry heating are given in the following equations:
Residual native ð%Þ ¼ 37:98 32:69 time 4:48 pH 8:17 aw 2:85 ðaw temperatureÞ 8:29 ðaw timeÞ 6:44 ðpH timeÞ 2
þ 8:50 temperature2 þ 12:40 time
ð5Þ Soluble aggregates ð%Þ ¼ 44:53 3:80 temperature þ 15:14 time 3:35 pH 4:41 aw 5:98 ðaw pHÞ 8:68 ðaw timeÞ 4:44 ðpH timeÞ 7:94 a2w 2
18:29 time
ð6Þ
299
NS NS NS 0.0013 NS NS 0.002 0.0137 NS 0.0471 NS NS NS NS NS <10 0.0188 <104 NS <104 NS NS NS NS NS 0.0003 <104 <104 NS 0.0002 0.0459 NS 0.0148 0.0442 NS NS 0.0006 0.0036 NS NS <10 0.0019 <104 NS NS
R2 (%)
89.2 66.5 78.9 74.9 59.9 <10 <104 0.0145 <104 <104 <10 NS <104 NS 0.0683
4
Time time Temp Temp pH pH aw aw
4
0.0001 0.0198 <104 0.0001 <104 <10 <104 <104 <104 <104
All the models follow a second order polynomial evolution versus time of dry heating. The percentage of residual native proteins and insoluble aggregates exhibit opposite trends: The percentage of residual native proteins continuously decreases with extended dry heating time (Eq. (5)) whereas the percentage of insoluble aggregates continuously increased (Eq. (7)). In contrast, the percentage of soluble aggregates and the gelling properties (gel strength and WHC) increase to a maximum for intermediate heating time (level 0) and when the heating time is extended the percentage of soluble aggregates and the gelling properties start decreasing (Eqs. (6), (8), and (10)). This result clearly points out soluble aggregates are for a large part responsible for the increase of the gelling properties of dry heated proteins. The formation of insoluble aggregates and/or the lack of sufficient amount of residual native protein after extended dry heating times have detrimental effects on gelling properties of proteins in agreement with previous results (Mine, 1997). In addition, time of dry heating in interaction with powder aw and pH also affects the composition of dry heated proteins and the gel strength. The effect of these factors and interactions with time will be discussed below.
NS 0.0119 0.0197 <104 NS
3.1. Effect of dry heating time
Residual native Soluble aggregates Insoluble aggregates WHC Gel strength
In these equations, only the physicochemical and processing parameters and their interactions which are significant at p-values less than 0.05 are considered (Table 1). The models R2 values for the percentage of residual native proteins, soluble aggregates and insoluble aggregates as well as gel strength and water holding capacity are 89.2%, 66.5%, 78.9%, 59.9%, and 74.9%, respectively. The models give the combination of variables to control the composition (residual native proteins, soluble and insoluble aggregates) of dry heated whey proteins and to optimize their gelling properties (gel strength and water holding capacity). Among the physicochemical and processing parameters investigated in this study, time of dry heating is the most prevalent variable for explaining the changes in composition and gelling properties of dry heated proteins. Powder aw and pH are also significant variables in all the models, but their effects are tuned by an interaction with the time of dry heating. Finally, the effect of dry heating temperature is less but this was expected regarding the way the experimental design was built (see above). The GLM also indicates interactions between some variables affecting both powder composition and gel properties (Table 1). The effect of these variables and their interactions are discussed below.
Temp time
ð9Þ
4
2
pH time
1:97 pH2 5:26 time
pH Temp
Water holding capacity ¼ 96:02 þ 1:41 pH 1:67 temperature þ 4:60 time 0:89 ðaw temperatureÞ
aw time
ð8Þ
aw Temp
2
þ 2:59 a2w 11:00 time
aw pH
3:90 ðaw timeÞ 7:05 ðpH timeÞ
4
Gel strength ¼ 28:17 3:63 pH 4:04 time
aw
ð7Þ
pH
2
10:82 temperature2 þ 6:11 time
4
þ 13:86 ðaw timeÞ þ 10:87 ðpH timeÞ þ 5:91 a2w
Time
þ 12:66 aw þ 4:71 ðaw pHÞ þ 4:22 ðaw temperatureÞ
Temp
þ 17:53 time þ 7:71 pH
Variable
Insoluble aggregates ð%Þ ¼ 20:00 þ 3:32 temperature
Table 1 The table represents the R2 values of the models for residual native proteins, soluble and insoluble aggregates, gel strength and water holding capacity (WHC) as well as the p-values of different variables and their significant interactions obtained by GLM. NS, non significant.
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3.2. Effect of dry heating temperature Taking into account all the data of the GLM, the model (Eq. (5)) indicates that the dry heating temperature has a quadratic effect on the percentage of residual native whey proteins. The average percentage of residual native proteins is lower for a dry heating temperature fixed at 100 °C than at 80 or 120 °C. The effect of dry heating temperature is dependent on powder aw as indicated by the interaction between these two variables. The percentage of soluble aggregates linearly decreases by increasing the dry heating temperature while the percentage of insoluble aggregates tends to increase (Eqs. (6) and (7)). However the temperature effect is quite small compared to other variables in the different models describing the composition of dry heated powder. The temperature for dry heating does not affect the gel strength. In contrast, an increase of the temperature for dry heating decreases WHC of whey protein gel. This decrease follows the de-
crease in the percentage of soluble aggregates in dry heated samples. 3.3. Effect of pH Increasing the pH for dry heating from 2.5 to 6.5 induces a decrease of the percentage of residual native proteins. This decrease is accompanied by the formation of soluble aggregates and insoluble aggregates. However for a given dry heating time, the percentage of soluble aggregates continuously decreases and the percentage of insoluble aggregates increases when pH increases. For instance, the models (Eqs. (6) and (7)) indicate that at pH 2.5 and 6.5, the percentage of soluble aggregates obtained for longer heating times are 49% and 33%, respectively, while the percentages of insoluble aggregates reach 25% and 65% respectively (when the other variables are fixed at level 0). The change in whey protein composition is also dependent on an interaction between pH and
Fig. 3. Principal component analysis showing the two principal components of significant 10 variables: (A) correlation circle of continuous variables (gelling properties, native proteins, soluble aggregates, insoluble aggregates, water activity, pH, temperature and time of dry heating). (B) the distribution of different samples and their classes determined by hierarchical cluster analysis. The different classes are noted 1, 2 and 3 and are obtained by the Ward method using the Euclidean distance between samples and/or clusters to merge (bottom-upapproach) in a field defined by the 5 principal components of the PCA. Classes 1, 2 and 3 gather 50, 52 and 18 samples, respectively, and its mean Euclidean distance is 2.230, 1.652 and 14.674, respectively.
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time of dry heating. This result is in agreement with previous studies showing that the rate of heat denaturation/aggregation of whey proteins in dry state is influenced by the pH of the powder (Gulzar et al., 2011); The rate of denaturation/aggregation of whey proteins increased by increasing the pH during dry heating leading to larger amount of insoluble aggregates (Mine, 1996; Gulzar et al., 2011). The pH for dry heating also impact on the gelling properties (gel strength and WHC). In GLM (Table 1), the p-values of effect of pH for gel strength and water holding capacity are <104 and 0.0001, respectively. According to the model, the gel strength is maximal for a whey protein powder dry heated at pH 2.5 for intermediate dry heating time (level 0). The gel strength decreases with increasing pH for dry heating and this decrease is accentuated when dry heating time is extended (level +1). The weakest gels are obtained for dry heated powders containing the higher amount of insoluble aggregates (pH 6.5 and longer heating time). The presence of insol-
301
uble aggregates is detrimental to obtain whey protein gels with high gel strength. In contrast, the moderate denaturation/aggregation of whey proteins at pH 2.5, leading mainly to soluble aggregates, enhances the gelling behavior of dry heated whey proteins. In contrast to gel strength, gel WHC follows a second order polynomial evolution according to pH for dry heating: the WHC is increased by increasing pH from 2.5 to 4.5 and then level off. Hence, the quantity of aggregates (soluble and insoluble) required for good WHC is higher than for maximal gel strength. 3.4. Effect of water activity The results of GLM show that increasing powder aw decreases the percentage of residual native proteins after one defined dry heating time. The denatured proteins are first converted into soluble aggregates and then insoluble aggregates. This is indicated by
Fig. 4. Principal component analysis using the samples containing only soluble aggregates, showing the two principal components of significant variables: (A) correlation circle of continuous variables (gelling properties, native proteins, soluble aggregates, water activity, pH, temperature and time). (B) The distribution of different samples and their classes determined by hierarchical classification are presented in. The different classes are noted 1, 2 and 3 and are obtained by the Ward method using the Euclidean distance between samples and/or clusters to merge (bottom-up approach) in a field defined by the 4 principal components of the PCA. Classes 1, 2 and 3 gather 21, 23, and 24 samples respectively and its mean Euclidean distance is 0.9, 3.92 and 4.09, respectively.
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A)
48 43
gel strength (N)
the quadratic effect of aw on the percentage of soluble aggregates and the linear increase of the percentage of insoluble aggregates with powder aw. In addition, the composition of the dry heated powders is affected by an interaction (aw time). The lower the aw, the slower the conversion of native proteins into insoluble aggregates. In fact, when the aw in the powder is reduced, molecular motions are decreased leading to a slowing down of diffusion-controlled reactions (Zhou and Labuza, 2007). In other words, proteins have less chance of making aggregates. The powder composition is also affected by the interactions (aw temperature) and (aw pH). Protein stability toward heat denaturation is increased by decreasing the water activity of whey proteins (Zhou and Labuza, 2007). These authors have shown that at aw of 0.23, 0.32 and 0.52 the proteins in WPI have a denaturation temperature of 163, 150, and 132 °C, respectively. So the concomitant decrease in the denaturation temperature and increase in the mobility of protein molecules at higher aw enhances the denaturation/aggregation of whey proteins during dry heating explaining the (aw temperature) interaction. The effect of aw is also dependent on the pH of the powder subjected to dry heating. At pH 2.5, the percentage of soluble and insoluble aggregates in the dry heated powder is weakly affected by powder aw. In contrast the powder aw has strong impact on the ratio between soluble and insoluble aggregates when pH increases. Gel strength is affected by powder aw (quadratic effect) and an interaction (aw time) while the WHC is affected by an interaction (aw temperature). The set of data was also subjected to principal component analysis (PCA). The principal component 1 and 2 of PCA explain 90.58% of variability showing the reliability of analysis (Fig. 3A). The results of PCA shows a positive correlation (0.71) among gel strength and water holding capacity, however both the gel strength and water holding capacity have a negative correlation (0.76 and 0.85, respectively) with insoluble aggregates. However, it has been observed that the gelling properties (gel strength and WHC) were only correlated with soluble aggregates at 21% and 36%, respectively, and residual native proteins at 46% and 49% respectively; gel strength and water holding capacity are projected in between residual native proteins and soluble aggregates. The same data were also subjected to hierarchical cluster analysis using the Ward method (Fig. 3B). All the samples have been classified into three classes using the 5 first PCA dimensions. In the 1st class (50 samples), the samples were composed of mainly native proteins (82.4 ± 8.8%) and a small amount of denatured/ aggregated proteins. The 2nd class (52 samples) gathered the samples which have the larger amount of soluble aggregates (48.5 ± 10.6%) in addition to residual native proteins (37.3 ± 12.7%). The samples in this class exhibit better gelling properties than control sample. In the 3rd class (18 samples), all the samples contained insoluble aggregates (69.4 ± 18.2%) and formed gels with strength and water holding capacity significantly lower than control sample. These results indicate that the solubility of dry heated proteins at heating pH is indispensable for good gelling properties which is also in agreement with previous results (Mine, 1997). In fact, if insoluble aggregates are present in the samples then the quantity of proteins that participates in the formation of gel network is reduced. So, in order to estimate the fractions of soluble aggregates and native residual proteins that optimize the strength and water holding capacity of the gel of dry heated samples, the samples with insoluble aggregates (with an error of ±10% to take into account the error of method for measurement) were excluded and the new set of data was subjected again to principal component analysis (Fig. 4). It was observed that the WHC was positively correlated (0.83) with the quantity of soluble aggregates in the samples and at the same time have negative correlation (0.80) with residual native proteins. In contrast, the gel strength
38 33 28 23 18 0
20 40 60 Soluble Aggregates (%)
80
0
20 40 60 Soluble Aggregates (%)
80
B) 100 97
WHC (%)
302
94 91 88 85 82
Fig. 5. Representation of the relative gel strength (%) (A) and WHC (%) (B) as a function of the fraction of soluble aggregates (%) in the samples. The model prediction is indicated in straight line. Confidence limit at 95% and prediction limit at 95% are indicated by dashed lines and dotted lines respectively.
was not correlated with soluble aggregates and residual native proteins. The hierarchical cluster analysis of these samples resulted in 3 classes. In the 1st class (21 samples) the samples have the higher gel strength (36.5 ± 5.0 N) and a moderate quantity of soluble aggregates (from 28 ± 9.5%) and native proteins (67.8 ± 10.3%). In the 2nd class (23 samples) the samples with good WHC (96.2 ± 1.7%) are presented. These samples have higher quantity of soluble aggregates (54.6 ± 7.9%). In the 3rd class (24 samples), the samples have the lower gelling properties and contain mainly native proteins (87.5 ± 6.4%) or very small amount of soluble aggregates. In order to determine the proportion of residual native proteins and soluble aggregates leading to maximum gel strength and gel WHC, the data were subjected to a GLM. The equations for maximum gel strength (N) and WHC (%) are given below with soluble aggregates expressed in percentage of total proteins in the samples (%):
Gel Strength ðNÞ ¼ 21:03 þ 0:80 soluble aggregates 0:012 soluble aggregates 2
ð10Þ
Water holding capacityðWHCÞ ¼ 85:10 þ 0:20 soluble aggregates
ð11Þ
Gel strength (Eq. (11)) follows a second order polynomial evolution according to the percentage of soluble aggregates. In the absence of dry heat treatment (control sample), the gel strength was 21.03 N. According to the model, the gel strength was enhanced up to 34.66 N by increasing the proportion of soluble aggregates in the samples up to 30–40% (Fig. 5A). If the proportion of soluble aggregates is increased above 40% then a decrease in the gel strength is observed suggesting that a substantial amount of residual native proteins is required for optimizing the connectivity
M. Gulzar et al. / Journal of Food Engineering 112 (2012) 296–303
of dry heated proteins during the heat set gelation and obtaining gels with high gel strength in agreement with Nicolai et al., 2011. However the model does not explain the large part of variability in the experimental data expressed by a R2 (%) value of 40%. For instance the gels formed from samples having a proportion of soluble aggregates between 30% and 40%, exhibit gel strength from 28.14 to 44.52 N. This indicates that the gel strength depends upon certain other parameters also. In fact our previous results (Gulzar et al., 2011) using the same WPI, showed that in addition to the quantity of aggregates, the structure of the soluble aggregates changes according to the conditions for dry heating, especially pH conditions: the size of soluble aggregates and the type of bonding in the aggregates changed according to the pH for dry heating (Mine, 1996; Gulzar et al., 2011). This study does not integrate the physical and chemical properties (type, shape, and size) of aggregates, which may explain the dispersion of the data on gel strength of dry heated whey proteins. The model for gel WHC (Eq. 11) has high significance level as its probability was less than 104. The WHC has strong linear relation (0.83) with soluble aggregates. In this study the proportion of soluble aggregates vary up to 67%; in this range, if the proportion of soluble aggregates increases in the samples, the gel WHC is enhanced (Fig. 5B). Consequently, the proportion of soluble aggregates required for WHC is higher than for gel strength in agreement with the results of Mine (1997). In addition, the model explains higher part of the variation in the data as the value of R2 was 69.5 (%). 4. Conclusion Dry heating strongly affects the gelling properties of whey proteins. The gel strength and water holding capacity of dry heated proteins are improved up to a maximum point then they start decreasing due to excessive denaturation/aggregation of whey proteins leading to insoluble aggregates. It was observed that the optimal point for gel strength and water holding capacity may be achieved earlier by increasing the pH, water activity or temperature during dry heating. The optimal point for water holding capacity requires higher amount of soluble aggregates than for optimal gel strength. In dry heated samples with an absence of insoluble aggregates the water holding capacity of heat set gels increase linearly with the amount of soluble aggregates. The structure and properties of soluble aggregates obtained by dry heating give them an excellent ability to reduce water release from heat set gels, but they seem to have a limited reactivity for building gels exhibiting high strength. However, dry heating conditions leading to samples containing residual native proteins and soluble aggregates up to 35–40% give the higher gel strength improvement. Powder water activity and pH significantly affect the functional properties of whey proteins so a strict control of these parameters is necessary to ensure the reproducibility of final product. Modelization of these physicochemical parameters helps us to standardize dry heat treatment for maximum gelling properties and also reduces the energy consumption during dry heating.
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