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Method to evaluate foaming performance
Jounml of Food En@wwing 36 (1998) 445-452 1998 Elsevier Science Limited. All rights reserved Printed in Great Britain 0260-8774198 $19.00 +(I.00
0 PII:
SO260-8774(98)00063-6
ELSEVIER
Method to Evaluate Foaming Performance Anabela Raymundo,” * Jose Empi? “Instituto
Superior de Agronomia,
“Instituto
Superior Ttcnico,
and Isabel Sousaa
Universidade Tecnica de Lisboa. Tapada da Ajuda 1399. Lisboa, Codex, Portugal Universidade Tecnica de Lisboa. Av. Rovisco Pais 1096, Lisboa, Codex, Portugal
(Received
7 August 1997; revised 13 April 1998)
ABSTRACT in this work, a methodology to evaluate foaming capacity and stability is proposed. With this method the foam volume decay is followed and the overrun [(foam volume -solution volume)isolution volume] plotted against time. The integral of overrun decay for a jixed period was tried out as a single parameter to describe foam properties, i.e. foaming capacity and foam stability. It was concluded that using this single parameter; the foaming stability index (ES.I.),, the application of statistical experimental design methodology to optimise foaming becomes straightforward. As an example of an application of this method, the denaturation extent of the protein was optimised to improve the foaming properties of Lupin protein isolate. 0 1998 Elsevier Science Limited. A 11rights reserved
INTRODUCTION Foaming properties are normally characterised city) and the volume loss over time (foaming
by the initial
volume
*To whom correspondence 3602036.
Tel. 00 351 1 3602040;
(foaming
capa-
stability). When the aim is to develop a foam product it is useful to quantify these two properties using a single quantity. In food foams the main characteristics responsible for foaming performance are the foam ability-the capacity of the continuous phase to include air (or another gas) and the foam stability-the ability to retain the gas for a certain period of time (Prins, 1988). Foaming ability is determined by the increase of the volume, just after the introduction of the gas into solution. The stability of the foam relates to the decrease of foam volume with time. should
be addressed. 445
Pax: 00 351 1
A. Raymundo et al.
446
There are several methods to measure these properties, the most common of which are the measurement of volume (Richert et al., 1974; Sathe et al., 1982) or conductivity (Kato et al., 1983) decrease with time. The way in which this decrease is evaluated is important when comparing results. Usually, the initial overrun value [(foam volume-volume of solution)/volume of solution x 1001 is taken as the measure of foam ability, but to quantify foam stability there are several proposed methods. Sathe et al. (1982) and Messinger et al. (1987) proposed to follow the foam volume decrease with time as such. Waniska and Kinsella (1979) and Kim and Kinsella (1985) measured the rate of foam liquid drainage with time and used a log plot to calculate a rate constant of drainage or half life of liquid in the foam. Kato et al. (1983) correlated the foam conductivity decay to the volume decrease with time and calculated a foam stability index from a linear decrease of conductivity and volume with time, using an extrapolation of the second linear branch of the exponential curve. In the present work these methods are discussed and two other different possibilities to quantify the foaming properties are proposed. The usefulness of one of these methods, the Foam stability index (FSI,), is shown in an example where it is used to evaluate the effect of protein heat induced denaturation upon protein foaming properties. The convenience of this single value approach to describe the foaming performance is demonstrated through its use in the optimisation of protein denaturation by the response surface methodology (RSM), a situation for which the usual multiparametric approach would become ambiguous or inconclusive.
MATERIALS
AND METHODS
Protein solutions White lupin protein isolate (L9000) obtained from Mittex Anlagenbau GubfH D88250 Weingarten with a protein content of 90% and 8% of fat, was used to prepare 3% (w/v) solutions, in a pH = 7.4 phosphate buffer as described in the literature (Kato et al., 1983; King et al., 1985), using strong magnetic stirring for approximately 15 min at room temperature. Denaturation
of protein and foam production
Protein solutions were kept at different temperatures by immersion in a water bath, with moderate magnetic stirring, for different periods of time and rapidly cooled in an ice water bath until room temperature. The foams were produced by air dispersion with a single speed air dispersor B. Braun Melsungem type 853512 (West Germany), during 10 min in 15 ml of 3% (w/ v) protein heated treated solutions, contained in a 2.5 cm diameter graduated glass cylinder. Repeatability (Y) is the maximum expected difference, with 95% confidence, between two values determined by the same operator under the same experimental conditions, and can be calculate as (Olschimke, 1980): xl-X2=r,‘1/(2n,)+1/(2n2) where x1 and x2 are the average values of n, and n2 replicates.
(I)
447
Method to evaluate foaming peformance
Repeatability of foaming procedure was evaluated using 10 replicates the integration of foaming overrun decay for 180 min [eqn (6)].
of FSI, i.e.
Foam evaluation The volume decrease with time was followed by direct readings of the foam volume in the 25 cm diameter graduated glass cylinder with 50 + 1 ml of capacity, as previously described by (Richert er al., 1974; Sathe et al., 1982). Alternatively, Kim and Kinsella (1985) measured the volume of the drained liquid remaining in the foam. Other possibility of foam characterisation is the determination of conductivity decrease with time, as suggested by Kato et al. (1983). This was measured by an open celf immersed in the foam in a Metrohm conductivimeter at room temperature. The foam ability, i.e. the capacity of the continuous phase to include air, can be determined as the initial value of overrun: Overrun =
Foam volume -Solution
volume
Solution volume
x 100
(2)
or the initial value of conductivity. The foam stability, i.e. the ability to retain air for a certain period of time, can be evaluated from the plot of overrun vs time or conductivity vs time. Essentially two different methods have been proposed to quantify this phenomenon. Kato et crl. ( 1983) recommend the use of the following expressions: Stability index = V,,.AtIAV.
(3)
where AV is the change in volume of foam occurring during the time interval ,4t and V. is the volume of the foam at 0 time or Stability index = C,,.AtIAC,
(4)
where AC is the change in conductivity of foam occurring during the time interval At and Co is the conductivity of the foam at 0 time. Wiseman and Price (1987) simply calculated the percentage of the overrun decay observed during a fixed period of time. Alternatively, we suggest two different possible ways of treating this data plot. An exponential equation: Y = exp( A + Bx)
(5)
can be fitted to the overrun (I’) vs time (x) plot. This exponential curve turns possible to calculate the derivative at a specific time t. Furthermore, a straight line can be generated from that point t. The intercept, (a), of this line can be a measure of foam ability, as a percentage of overrun ($6) and the slope (m) a measure of foam stability, which represents a rate of volume decay with time (s ‘). This method is similar to that previously described by Kato et al. (1983). Another option is to integrate this exponential eqn (5) over a certain period of time. The value of the integral, representing the area under the curve, can be interpreted as a measure of the foam properties as a whole. It can be defined as the foam stability index F.S.I., at a specific time t:
448
A. Raymundo et al.
FSIt=
’ exp(A + Bt)dt. s f,,
(6)
This index reflects both the foam capacity and foam stability as these two properties can be quantified by the increase of the area above the exponential curve, reflecting the decrease of foam volume with dimensions of time, i.e. can be expressed in seconds, but minutes is a better time scale for foams. The F.S.I., index was applied to optimise foaming performance of a vegetable protein, to demonstrate the advantages of this method. Optimization of thermai denaturation The optimisation of the extent of protein denaturation for foaming performance was carried out using the response surface methodology (RSM) as described earlier (e.g. Mitchell et al., 1986). The independent variables considered were time and temperature, ranging from 6 to 34 min and 46-74°C respectively, at five levels defined by a central composite rotatable design (Box & Hunter, 1957) using as dependent variable (response) the proposed foaming stability index at 180 min: F.S.I.iXO. This specific time was considered to be long enough to allow to industrial processing of the produced foams. Table 1 compiles the conditions for each experiment and the respective results. The time should considered according to the nature of the foam produced. If the foam is unstable it should be reduced, if it is very stable the discrimination between cases will improve for longer times.
RESULTS
AND DISCUSSION
The foaming method by air dispersion on the protein solution showed a good repeatability. This repeatability was determined as 5.25, using the FS1180 values calculated for 10 foam replicates. This is considered to be a reasonable value, representing 0.03% of the FSI value.
TABLE 1 Experimental
Time (min.) 10 30 10 30 6 34 20 20 20 20
Design for the Optimization of the White Lupin Protein Thermal Denaturation and Respective Experimental Results Temperature (“C)
FSIM, (min)
50 50 70 70 60 60 46 74 60 60
10.42 12.33 19.04 14.79 14-72 15.04 13.42 17.46 18.50 18.10
439
Method to evaluate foaming performance
Preliminary experiments were conducted to choose conductivity or volume to quantify the foaming properties. The measurement of draining liquid it is out of scope because it takes too long for this kind of foams to drain. The phenomena of destabilisation of lupin protein foams is more related with shrinkage, i.e. reduction of the volume of the air bubbles. The results obtained with conductivity measurements (Fig. 1) can only be used to follow foam behaviour for about 30 min. After this period of time conductivity remains constant, while the volume keeps changing. In this case of stable foams conductivity is a less sensitive method. Another argument in favour of the volume measurements is that no probe is introduced on the foam, i.e. no mechanical disturbance on foaming air cells, at any moment of foam existence. In the food industry the time needed for the foam to be stable waiting to be processed can be greater than 30 min. For this reason it is thought that measurements of volume are more useful than the conductivity to follow the stability of the foam protein. Using the foam volume decrease with time to evaluate foaming performance, the optimisation of protein thermal denaturation was carried out using the integration method, i.e. the F.S.I., index. The main advantage of the F.S.I., method is the possibility of using optimisation procedures. This can be done by applying the response surface methodology to optimise the time and temperature of denaturation, using F.S.I.,,,, as the response (Table 1). The following mathematical model is obtained, with R* = 0.8069: Y= -82.0+1.7x,
+2.6x2-2.0x
lO-2x:-
1.7~1O-~x;-
1.5 x 1O-2x,x2,
where Y is the F.S.I.IXO, xl is the time of thermal denaturation tion temperature.
(7)
and x2 the denatura-
0
10 nin.
0 30 nin. A 40 Kin. l native
&QQQQQQQ 000000000 l-444444 5
,
50
100
150
Time (min.) Fig. 1. Conductivity
variation
with time for lupin protein 10.30 and 40 min.
foams heat treated
at 6O”C, during
450
A. Raymundo et al.
The maximisation of this model [eqn (5)] led us to the optimal conditions of denaturation: time = 14 min and temperature = 73°C. In Fig. 2 one can see the respective response surface. If one applies the derivation method a value for foam capacity, the intercept (a) of the derivative at a specific time is obtained, and another value, the slope (m) of the derivative, as a measure of foam stability. If the optimisation is applied to foam capacity (maximisation of a) the foam stability is neglected, which is not the purpose, because stability is fundamental. On the other hand, if the optimisation is achieved for foam stability (minimisation of m), the foam capactty would become secondary. The results of two experiments of the experimental design earlier described on Table 1, and the results of the foam produced with the optimum conditions found (73°C 14 min) are shown in Fig. 3 as examples, and can be compared by analysis of variance (Table 2). From this figure it can be seen that the foam produced with protein denatured at 74°C during 20 min has the higher foam capacity, but is the less stable foam. The foam produced with the optimum denaturation condtttons has less foam ability than the others, but it is more stable and has a higher FSIEW From this picture it can be observed that the foam capacity and the foam stability can show opposite variation. For this reason, it is important to consider the FSI, index
76
0
Tempo (min.)
Fig. 2. Surface response
the thermal denaturation of Lupinus albus protein, foams.
to produce food
Method
to evaluate
foaming
451
performance
FSll80
14 tin.,FSll80 = 19292 min.
100
= 17460
min.
20
473%,
_~~~_1
FSll80
min.
+74OC,
_+_ _.-_. 50
tin.,
= 19040
/
150
200
Time (min.)
Fig. 3. Variation
of overrun with time for three foams produced isolate denatured at different conditions.
with white Lupin protein
when the aim is to obtain a foam with high capacity to include air and good stability over time.
CONCLUSIONS In the evaluation of foam materials, the use of different methods can make a difference in the interpretation of the results. When optimisation of foaming performance is needed, the use of a single parameter to describe the foam properties is very useful. One such parameter, obtained by integration of the volume decay with time, expresses the foaming performance and was designated the F.S.I.,. this method results are realistic and easy to compare. The fact that most foam applica-
Variance
TABLE 2 for FSI,,,, for the Experiments at 7O”C, 10 min; 74”C, 20 min and 73”c’, 14 min
Analysis
FSI,,,,
(min)
70°C‘. IO min 74°C 20 min 73°C. 14 min
10038 16770 19270
One-way ANOVA: [I = 7.51 x 10 ~“).
at the
FSll,yo (min) I Y027 16836 19203 0.05 level
The
Average
19054 16786 19397 means
are
significantly
19040 16797 19290 different
185.25 1 I7Y.75 9’725%I (F =
152’).
452
A. Raymundo et al.
tions in the food industry are due to batch processing, which requires production of the foam prior to use, implies a defined value of specific time interval t to be considered for each particular case. When t = 0, F.S.I.,, represents the foam ability. The best foaming performance of a white lunin protein was achieved after a controlled denatura%n at 73°C during 14 min, when xthe specific time interval was considered to be 180 min.
ACKNOWLEDGEMENTS To Professor To JNICT for financially supporting this work (FMRH/BM/1273/93). A.C. Diogo for fruitful discussions on the topic of derivative and integration method.
REFERENCES Box, G.E.P. & Hunter, J.S. (1957). Multi-factor experimental designs for exploring response surfaces. Ann. Math. Statistics. 28, 195-206. Kato, A., Takahashi, A., Matsudomi, N. & Kobayashi, K. (1983). Determination of foaming properties of proteins by conductivity measurements. 1. Food Sci., 48, 62-65. Kim, S.H. & Kinsella, J.E. (1995). Surface active properties of food proteins. 1. Food Sci., 50, 1526-1530. King, J., Aguirre, C. & Pablo, S. (1985). Functional properties of lupin protein isolates. J. Food Sci., 50, 82-86. Messinger, J.K., Rupnow, J.H., Zeece, M.G. & Anderson, R.L. (1987). Effect of partial proteolysis and succinylation on functionality of corn germ protein isolate. J. Food Sci., 52, 1620-1624.
Mitchell, J.R., Back, H., Gregson, K., Harding, S. & Mather, S. (1986). Optimization of products and processes. In: Chemistry and Physics of Baking, Blanshard, J.M.V. et al. (eds.). Royal Society of Chemists, London, pp. 236-249. Olschimke, D. (1980). Aplication de la repetabilite et de la reproductibilite dans l’analyse des denreees alimentaires. O.I.V., F.V.711. Prins, A. (1988). Principles of foam stability. In: Advances in Food Emulsions and Foams, Dickinson, E. & Stainsby, G. (eds.). Elsevier Applied Science, London, pp. 91-123. Richert, S.H., Morr, C.V. & Cooney, C.M. (1974). Effect of heat and other factors upon foaming properties of whey protein concentrates. J. Food Sci., 39, 43-48. Sathe, S.K., Deshpande, S.S. & Salunkhe, D.K. (1982). Functional properties of lupin seed proteins and protein concentrates. J. Food Sci., 47, 491-497. Waniska, R.D. & Kinsella, J.E. (1979). Foaming properties of proteins: evaluation of a column aeration apparatus using ovalbumin. J. Food Sci., 44, 1398-1402. Wiseman, M.O. & Price, R. (1987). Functional properties of protein concentrates from pressed jojoba meal. Cereal Chem., 64, 94-97.
0 PII:
SO260-8774(98)00063-6
ELSEVIER
Method to Evaluate Foaming Performance Anabela Raymundo,” * Jose Empi? “Instituto
Superior de Agronomia,
“Instituto
Superior Ttcnico,
and Isabel Sousaa
Universidade Tecnica de Lisboa. Tapada da Ajuda 1399. Lisboa, Codex, Portugal Universidade Tecnica de Lisboa. Av. Rovisco Pais 1096, Lisboa, Codex, Portugal
(Received
7 August 1997; revised 13 April 1998)
ABSTRACT in this work, a methodology to evaluate foaming capacity and stability is proposed. With this method the foam volume decay is followed and the overrun [(foam volume -solution volume)isolution volume] plotted against time. The integral of overrun decay for a jixed period was tried out as a single parameter to describe foam properties, i.e. foaming capacity and foam stability. It was concluded that using this single parameter; the foaming stability index (ES.I.),, the application of statistical experimental design methodology to optimise foaming becomes straightforward. As an example of an application of this method, the denaturation extent of the protein was optimised to improve the foaming properties of Lupin protein isolate. 0 1998 Elsevier Science Limited. A 11rights reserved
INTRODUCTION Foaming properties are normally characterised city) and the volume loss over time (foaming
by the initial
volume
*To whom correspondence 3602036.
Tel. 00 351 1 3602040;
(foaming
capa-
stability). When the aim is to develop a foam product it is useful to quantify these two properties using a single quantity. In food foams the main characteristics responsible for foaming performance are the foam ability-the capacity of the continuous phase to include air (or another gas) and the foam stability-the ability to retain the gas for a certain period of time (Prins, 1988). Foaming ability is determined by the increase of the volume, just after the introduction of the gas into solution. The stability of the foam relates to the decrease of foam volume with time. should
be addressed. 445
Pax: 00 351 1
A. Raymundo et al.
446
There are several methods to measure these properties, the most common of which are the measurement of volume (Richert et al., 1974; Sathe et al., 1982) or conductivity (Kato et al., 1983) decrease with time. The way in which this decrease is evaluated is important when comparing results. Usually, the initial overrun value [(foam volume-volume of solution)/volume of solution x 1001 is taken as the measure of foam ability, but to quantify foam stability there are several proposed methods. Sathe et al. (1982) and Messinger et al. (1987) proposed to follow the foam volume decrease with time as such. Waniska and Kinsella (1979) and Kim and Kinsella (1985) measured the rate of foam liquid drainage with time and used a log plot to calculate a rate constant of drainage or half life of liquid in the foam. Kato et al. (1983) correlated the foam conductivity decay to the volume decrease with time and calculated a foam stability index from a linear decrease of conductivity and volume with time, using an extrapolation of the second linear branch of the exponential curve. In the present work these methods are discussed and two other different possibilities to quantify the foaming properties are proposed. The usefulness of one of these methods, the Foam stability index (FSI,), is shown in an example where it is used to evaluate the effect of protein heat induced denaturation upon protein foaming properties. The convenience of this single value approach to describe the foaming performance is demonstrated through its use in the optimisation of protein denaturation by the response surface methodology (RSM), a situation for which the usual multiparametric approach would become ambiguous or inconclusive.
MATERIALS
AND METHODS
Protein solutions White lupin protein isolate (L9000) obtained from Mittex Anlagenbau GubfH D88250 Weingarten with a protein content of 90% and 8% of fat, was used to prepare 3% (w/v) solutions, in a pH = 7.4 phosphate buffer as described in the literature (Kato et al., 1983; King et al., 1985), using strong magnetic stirring for approximately 15 min at room temperature. Denaturation
of protein and foam production
Protein solutions were kept at different temperatures by immersion in a water bath, with moderate magnetic stirring, for different periods of time and rapidly cooled in an ice water bath until room temperature. The foams were produced by air dispersion with a single speed air dispersor B. Braun Melsungem type 853512 (West Germany), during 10 min in 15 ml of 3% (w/ v) protein heated treated solutions, contained in a 2.5 cm diameter graduated glass cylinder. Repeatability (Y) is the maximum expected difference, with 95% confidence, between two values determined by the same operator under the same experimental conditions, and can be calculate as (Olschimke, 1980): xl-X2=r,‘1/(2n,)+1/(2n2) where x1 and x2 are the average values of n, and n2 replicates.
(I)
447
Method to evaluate foaming peformance
Repeatability of foaming procedure was evaluated using 10 replicates the integration of foaming overrun decay for 180 min [eqn (6)].
of FSI, i.e.
Foam evaluation The volume decrease with time was followed by direct readings of the foam volume in the 25 cm diameter graduated glass cylinder with 50 + 1 ml of capacity, as previously described by (Richert er al., 1974; Sathe et al., 1982). Alternatively, Kim and Kinsella (1985) measured the volume of the drained liquid remaining in the foam. Other possibility of foam characterisation is the determination of conductivity decrease with time, as suggested by Kato et al. (1983). This was measured by an open celf immersed in the foam in a Metrohm conductivimeter at room temperature. The foam ability, i.e. the capacity of the continuous phase to include air, can be determined as the initial value of overrun: Overrun =
Foam volume -Solution
volume
Solution volume
x 100
(2)
or the initial value of conductivity. The foam stability, i.e. the ability to retain air for a certain period of time, can be evaluated from the plot of overrun vs time or conductivity vs time. Essentially two different methods have been proposed to quantify this phenomenon. Kato et crl. ( 1983) recommend the use of the following expressions: Stability index = V,,.AtIAV.
(3)
where AV is the change in volume of foam occurring during the time interval ,4t and V. is the volume of the foam at 0 time or Stability index = C,,.AtIAC,
(4)
where AC is the change in conductivity of foam occurring during the time interval At and Co is the conductivity of the foam at 0 time. Wiseman and Price (1987) simply calculated the percentage of the overrun decay observed during a fixed period of time. Alternatively, we suggest two different possible ways of treating this data plot. An exponential equation: Y = exp( A + Bx)
(5)
can be fitted to the overrun (I’) vs time (x) plot. This exponential curve turns possible to calculate the derivative at a specific time t. Furthermore, a straight line can be generated from that point t. The intercept, (a), of this line can be a measure of foam ability, as a percentage of overrun ($6) and the slope (m) a measure of foam stability, which represents a rate of volume decay with time (s ‘). This method is similar to that previously described by Kato et al. (1983). Another option is to integrate this exponential eqn (5) over a certain period of time. The value of the integral, representing the area under the curve, can be interpreted as a measure of the foam properties as a whole. It can be defined as the foam stability index F.S.I., at a specific time t:
448
A. Raymundo et al.
FSIt=
’ exp(A + Bt)dt. s f,,
(6)
This index reflects both the foam capacity and foam stability as these two properties can be quantified by the increase of the area above the exponential curve, reflecting the decrease of foam volume with dimensions of time, i.e. can be expressed in seconds, but minutes is a better time scale for foams. The F.S.I., index was applied to optimise foaming performance of a vegetable protein, to demonstrate the advantages of this method. Optimization of thermai denaturation The optimisation of the extent of protein denaturation for foaming performance was carried out using the response surface methodology (RSM) as described earlier (e.g. Mitchell et al., 1986). The independent variables considered were time and temperature, ranging from 6 to 34 min and 46-74°C respectively, at five levels defined by a central composite rotatable design (Box & Hunter, 1957) using as dependent variable (response) the proposed foaming stability index at 180 min: F.S.I.iXO. This specific time was considered to be long enough to allow to industrial processing of the produced foams. Table 1 compiles the conditions for each experiment and the respective results. The time should considered according to the nature of the foam produced. If the foam is unstable it should be reduced, if it is very stable the discrimination between cases will improve for longer times.
RESULTS
AND DISCUSSION
The foaming method by air dispersion on the protein solution showed a good repeatability. This repeatability was determined as 5.25, using the FS1180 values calculated for 10 foam replicates. This is considered to be a reasonable value, representing 0.03% of the FSI value.
TABLE 1 Experimental
Time (min.) 10 30 10 30 6 34 20 20 20 20
Design for the Optimization of the White Lupin Protein Thermal Denaturation and Respective Experimental Results Temperature (“C)
FSIM, (min)
50 50 70 70 60 60 46 74 60 60
10.42 12.33 19.04 14.79 14-72 15.04 13.42 17.46 18.50 18.10
439
Method to evaluate foaming performance
Preliminary experiments were conducted to choose conductivity or volume to quantify the foaming properties. The measurement of draining liquid it is out of scope because it takes too long for this kind of foams to drain. The phenomena of destabilisation of lupin protein foams is more related with shrinkage, i.e. reduction of the volume of the air bubbles. The results obtained with conductivity measurements (Fig. 1) can only be used to follow foam behaviour for about 30 min. After this period of time conductivity remains constant, while the volume keeps changing. In this case of stable foams conductivity is a less sensitive method. Another argument in favour of the volume measurements is that no probe is introduced on the foam, i.e. no mechanical disturbance on foaming air cells, at any moment of foam existence. In the food industry the time needed for the foam to be stable waiting to be processed can be greater than 30 min. For this reason it is thought that measurements of volume are more useful than the conductivity to follow the stability of the foam protein. Using the foam volume decrease with time to evaluate foaming performance, the optimisation of protein thermal denaturation was carried out using the integration method, i.e. the F.S.I., index. The main advantage of the F.S.I., method is the possibility of using optimisation procedures. This can be done by applying the response surface methodology to optimise the time and temperature of denaturation, using F.S.I.,,,, as the response (Table 1). The following mathematical model is obtained, with R* = 0.8069: Y= -82.0+1.7x,
+2.6x2-2.0x
lO-2x:-
1.7~1O-~x;-
1.5 x 1O-2x,x2,
where Y is the F.S.I.IXO, xl is the time of thermal denaturation tion temperature.
(7)
and x2 the denatura-
0
10 nin.
0 30 nin. A 40 Kin. l native
&QQQQQQQ 000000000 l-444444 5
,
50
100
150
Time (min.) Fig. 1. Conductivity
variation
with time for lupin protein 10.30 and 40 min.
foams heat treated
at 6O”C, during
450
A. Raymundo et al.
The maximisation of this model [eqn (5)] led us to the optimal conditions of denaturation: time = 14 min and temperature = 73°C. In Fig. 2 one can see the respective response surface. If one applies the derivation method a value for foam capacity, the intercept (a) of the derivative at a specific time is obtained, and another value, the slope (m) of the derivative, as a measure of foam stability. If the optimisation is applied to foam capacity (maximisation of a) the foam stability is neglected, which is not the purpose, because stability is fundamental. On the other hand, if the optimisation is achieved for foam stability (minimisation of m), the foam capactty would become secondary. The results of two experiments of the experimental design earlier described on Table 1, and the results of the foam produced with the optimum conditions found (73°C 14 min) are shown in Fig. 3 as examples, and can be compared by analysis of variance (Table 2). From this figure it can be seen that the foam produced with protein denatured at 74°C during 20 min has the higher foam capacity, but is the less stable foam. The foam produced with the optimum denaturation condtttons has less foam ability than the others, but it is more stable and has a higher FSIEW From this picture it can be observed that the foam capacity and the foam stability can show opposite variation. For this reason, it is important to consider the FSI, index
76
0
Tempo (min.)
Fig. 2. Surface response
the thermal denaturation of Lupinus albus protein, foams.
to produce food
Method
to evaluate
foaming
451
performance
FSll80
14 tin.,FSll80 = 19292 min.
100
= 17460
min.
20
473%,
_~~~_1
FSll80
min.
+74OC,
_+_ _.-_. 50
tin.,
= 19040
/
150
200
Time (min.)
Fig. 3. Variation
of overrun with time for three foams produced isolate denatured at different conditions.
with white Lupin protein
when the aim is to obtain a foam with high capacity to include air and good stability over time.
CONCLUSIONS In the evaluation of foam materials, the use of different methods can make a difference in the interpretation of the results. When optimisation of foaming performance is needed, the use of a single parameter to describe the foam properties is very useful. One such parameter, obtained by integration of the volume decay with time, expresses the foaming performance and was designated the F.S.I.,. this method results are realistic and easy to compare. The fact that most foam applica-
Variance
TABLE 2 for FSI,,,, for the Experiments at 7O”C, 10 min; 74”C, 20 min and 73”c’, 14 min
Analysis
FSI,,,,
(min)
70°C‘. IO min 74°C 20 min 73°C. 14 min
10038 16770 19270
One-way ANOVA: [I = 7.51 x 10 ~“).
at the
FSll,yo (min) I Y027 16836 19203 0.05 level
The
Average
19054 16786 19397 means
are
significantly
19040 16797 19290 different
185.25 1 I7Y.75 9’725%I (F =
152’).
452
A. Raymundo et al.
tions in the food industry are due to batch processing, which requires production of the foam prior to use, implies a defined value of specific time interval t to be considered for each particular case. When t = 0, F.S.I.,, represents the foam ability. The best foaming performance of a white lunin protein was achieved after a controlled denatura%n at 73°C during 14 min, when xthe specific time interval was considered to be 180 min.
ACKNOWLEDGEMENTS To Professor To JNICT for financially supporting this work (FMRH/BM/1273/93). A.C. Diogo for fruitful discussions on the topic of derivative and integration method.
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