Flavor Release - American Chemical Society

Chapter 13

Flavor Release as a Unit Operation: A Mass Transfer Approach Based on a Dynamic Headspace Dilution Method 1

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Michèle Marin , I. Baek , and AndrewJ.Taylor 1

Downloaded by CORNELL UNIV on October 17, 2016 | http://pubs.acs.org Publication Date: September 7, 2000 | doi: 10.1021/bk-2000-0763.ch013

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Food Process Engineering Department, INAPG-INRA, 78850 Thiverval-Grignon, France Division of Food Sciences, University of Nottingham, Loughborough, Leicestershire LE12 5RD, United Kingdom

In physical terms, the mass transfer of flavor compounds between two (or more) phases is the main mechanism of flavor release. Flavor release between air and static aqueous solutions has been studied with the API-MS device. Using both mass transfer modeling and experimental results obtained from a dynamic dilution method, the contribution of the physical properties of the volatiles as well as the environmental conditions in the system were evaluated. Thermodynamic and kinetic properties of five volatiles were estimated for different aqueous solutions, with a variable concentration of sugar. It was also pointed out that the flavor release is at first a function of the volatility of the flavor molecule (K, the partition coefficient at equilibrium). Furthermore, kinetic properties (mass transfer coefficient) as well as hydrodynamic parameters (Reynolds number, flow rate, surface exhange area) were collected in an original dimensionless term and its effect on the flavor release was discussed depending on the value of K .

A quantitative description of flavor perception in a food product needs to take into account mechanisms that are complex and which differ, depending on the type of food studied. The consumer appreciation of flavor release includes psychosensorial aspects as well as social ones. Nevertheless, it is well known that physics and chemistry play a major role. Modeling the physical mechanism of flavor release is not new. Most of the emphasis has been placed on the volatile flavor compounds (1, 2, 3). The physical mechanism of flavor release is based on sequential transfer of volatile flavor molecules (aroma compounds) from one phase to another. Initially the volatile compounds are contained in a food product but ultimately, the volatiles have to be transported into the air phase so they can reach the olfactory receptors. For

© 2000 American Chemical Society

Roberts and Taylor; Flavor Release ACS Symposium Series; American Chemical Society: Washington, DC, 2000.

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example, when a container of food (bottle, bag, can) is opened, the volatiles are diluted by the surrounding air and transported to the olfactory receptors by the orthonasal route. In the mouth, food is coated with saliva, broken down by mastication and the flavor compounds are transported across the saliva film to the air-ways of the nose by the retronasal route. In both cases, environmental conditions like temperature, size of the food product, or velocity of the gas flow have an important effect on the release. Using a chemical engineering approach, this paper seeks to identify the key physical parameters controlling flavor release from a product to the air phase. Flavor release was studied as a unit operation, such as distillation, stripping or extraction. Indeed, mass transfer of the flavor compounds are associated with momentum and heat transfer, and concepts like equilibrium stage, mass balance, and transfer are powerful analogies. The theoretical approach developed was based on experimental data obtained with a technique that allowed the release of a series of molecules to be monitored simultaneously, under dynamic headspace conditions, and in different environmental systems (4). Thus, the model was developed to describe the release from a static liquid phase, and from this, the key factors controlling the physical mechanism were obtained. Although the model was developed for a simple system, the principles behind the model were capable of further extrapolation to other flavor release situations.

A Dynamic Headspace Dilution Method Using Atmospheric Pressure Ionization Mass Spectrometry (API-MS), an interface has been developed that allows real time measurement of volatile release at low concentrations (5). Headspace sampling methods have been developed to measure static headspace as well as dynamic release of volatile compounds present in different kind of mediums (food products) and over short time periods (less than 10 minutes) (6). The theoretical approach is based on the experimental conditions which involve a liquid phase containing several volatiles in a closed cell. After equilibrium between the liquid and air at atmospheric pressure, the gas phase was diluted by introducing fresh air at a fixed flow rate (Figure 1). The liquid phase contained five aroma compounds at low concentrations (from 10" to 10" kg/m ), and at a constant temperature (25°C). This system resembles the situation in real food products such as beverages, when a sealed container (volatile under equilibrium) is opened and the volatiles are diluted by the surrounding air over time. The volatile profile resulting from this process is perceived by consumers during their first "sniff and can play a major role in food acceptance. By connecting the air outlet of the cell via the interface to the API-MS equipment, the concentration of each volatile as a function of time was determined as mg/m after calibration with authentic standards. A n example of an experimental release curve is given in Figure 2. At the start of the experiment, the system was 3

4

3

3


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sealed to ensure equilibrium between the air and liquid phases. Thus, the first concentration (time equal to zero) measured through the API-MS was the equilibrium concentration in the headspace but, thereafter, the decrease in concentration of each compound was measured with time.

Figure 1. Schematic view of the cell

Figure 2. Curve shape as volatiles are detected as a function of time from APIMS device (t =connection, ^dynamic headspace dilution, tf=disconnection) 0

Mass Transfer of Flavor Compounds As air flows through the headspace of the system, the concentration of the volatile in the gas phase as a function of time (C(t) in kg/m ) is the result of a mass balance between release from the sample phase and removal in the air stream crossing the system: 3

dC(t) V.——= J(t). A - ù.C(t) at

1

eq 1 3

V is the fixed volume of the whole gas compartment (m ), assuming a wellmixed gas phase. A is the sample-gas interface area (m ) and Ù is the gas flow rate through the system (m .s ). The mass flux (J(t)) through the surface is the result of the transport from the sample to the air which was composed of three steps. 2

3

_1

Diffusion of the Volatile from the Bulk of the Sample to the Interface During the short experimental time frame, it was assumed that the concentration of the volatiles in the bulk liquid phase (C'(x,t) in kg/m ) remained constant and was only modified in the liquid layer near the interface. The sample was considered as a semi-infinite medium. The expression of mass transport of the volatile in the liquid 3


156

was first represented with the generalized Fick law (7). For a mono-directional transport along the x-axis (x distance from the interface), the differential equation is: 2

dC'(x,t)__ d C'(x,t) dt " dx D

e

q

2

2

The diffusion coefficient (D) depends on the type of volatile, the medium, and the temperature.


Partition of the Molecule at the Interface At the interface itself, a local thermodynamic equilibrium can be assumed (8). The relationship between the concentration in the sample and the gas phase is usually given by the partition coefficient (K): 'χ,.Ρ,'Ο^ν

eq3

V

where p ^ T ) is the vapor pressure for the pure component i (Pa), P , the total T

pressure in the gas phase (Pa) and, V and V are the volume for one mole of the liquid and of the gas phases respectively (πΛπιοΓ ). If the volatile is highly diluted in the liquid phase, the activity coefficient γ can be assumed to be independent of the 1

concentration of the volatile in the liquid, and is equal to a constant value y ~. In this 0

case, the product γ~ . P . ( Τ ) is a constant (Henry's constant), reflecting the molecule volatility in the medium. Then, Κ depends only on the temperature (9).

Transport of the Molecule in the Gas Phase Knowing that the gas phase is flowing over the sample surface, mass transport can be represented with an empirical mass transfer coefficient (kg) that is analogous to a diffusion coefficient divided by an equivalent limiting layer thickness, with: J(t) = kg(C*(t)-C(t)) eq4 3

C * is the concentration (kg.m ) in the gas phase at the gas-liquid interface (wall), which is equal to K.C'(x=0), the product of the partition coefficient with the liquid concentration at the wall. Hence: J(t) = kg(K. C (x = 0, t) - C(t)) eq 5 At the interface between liquid and gas, the mass transfer is represented by: 1

-D^T )

o

= kg(KC(x = 0,t)-C(t))

e

i

6

At time zero, the initial concentration is assumed to be uniform in both phases : C(t = 0) = K.C'(t = 0) = C eq7 The properties of the volatiles during the experiment were assumed to be constant. It is obvious that the thermodynamic properties (partition coefficient) are strongly linked to the kinetic ones. The system of equations (1, 2, 5, 6 and 7) were m a x


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solved numerically using Matlab software (The Matworks Inc., USA) with Simulink tool box. Concentration profiles in each phase were calculated as a function of time, also depending on the distance in the liquid medium. Based on comparison with the experimental data, the properties of the volatiles which influenced release were identified.

Results and Discussion


Thermodynamic and Kinetics of Flavor Compounds Two kinds of factors characterized the flavor release: • the concentration of the flavor compounds as well as its properties within the medium, which are thermodynamic (partition coefficient) and kinetic (diffusion and mass transfer coefficients); • operating conditions like the geometry of the system (volume of the phases, surface exchange area), hydrodynamic factors (flow rate of the gas, gas stirred in the cell, non mobile liquid phase), thermal conditions (temperature). Applying the dynamic headspace dilution method to simple solutions of volatiles, the composition of the medium and the operating conditions were fixed and it was possible to identify the thermodynamic and the kinetic properties of the molecule. Five compounds were chosen in order to cover a wide range of properties (Table I). They were highly diluted in aqueous solutions, so there was no significant effect of volatile on the activity coefficient and the probability of any interaction (or reaction) between the molecules was negligible. Different concentrations of sugar (sucrose up to 50%) were added to the aqueous solutions while maintaining the flavor at the same concentration.

Table I. List of the Molecules Studied in Aqueous Solutions Molecule Acetaldehyde Diacetyl 2,5 -Dimethylpyrazine Dimethylsulfide Menthone

MW(z/mol) 44

86 108 62 154

3

Liquid concentration (kg/m )

1.1E-3 9.61E-4 8.37E-3 8.46E-4 8.93E-5

Partition Coefficients of Flavor Compounds Diluted in Aqueous Solutions The partition coefficients of the flavor compounds in water were estimated with static headspace analysis as well as by using the initial concentration from the dynamic headspace measurements (C in Figure 2), at a fixed temperature (25°C) (Table II). The experimental values of the partition coefficients obtained in aqueous solutions were in good agreement with the theoretical ones (literature or calculated data from an empirical model), which have been discussed previously (10). The molecules chosen have very different volatilities (corresponding to the partition max


158 coefficient values Κ) as well as different hydrophobicities ( γ~ increasing from acetaldehyde to menthone) (Table II). As a result, Κ varied from 2.5 χ 10" for dimethylsulfide (high volatility) to 5.7 χ 10" for 2,5-dimethylpyrazine (low volatility). Moreover, the experimental data obtained with two different concentrations of sucrose solutions (20% and 40%) showed an increase of the partition coefficient when increasing the sugar content, especially when the activity coefficient was high. The effects observed are in agreement with the literature data of activity coefficients, for other volatiles diluted in aqueous solutions with sugar which were measured in a dilutor cell at equilibrium (77). 2


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Table Π. Partition Coefficients of Flavor Compounds in Aqueous Solutions at 25°C Κ sucrose solutions Κ in water Molecule Κ in water 77 experimental experimental theoretical (10) 20% 40% (10) Acetaldehyde Diacetyl 2,5-Dimethylpyrazine Dimethylsulfide Menthone

4 11 23 208 24 870

2.9E-3 5.7E-4 6.3E-5 8.1E-2 6.9E-3

2.7E-3 3.9E-4 5.7E-5 2.5E-2 7.1E-3

3.3E-3 5.7E-4 6E-5 3E-2 7E-3

3.3E-3 9.7E-4 10E-5 6E-2 11E-3

Kinetic Properties of the Aqueous Flavored Solutions In Figure 3, the release curves for the five flavor compounds can be seen. The curves were obtained under the standard operating conditions and are plotted as relative concentration (C(t) over C(t=0)) as a function of time in order to compare the behavior of all compounds on the same scale. The kinetics of release seem to be directly related to the partition coefficient: the lowest change in release (highest C/C0 value) was seen for the less volatile 2,5-dimethylpyrazine and the highest change in release (lowest C/C0 value) was seen for the most volatile molecule, dimethylsulfide. By fitting the solution of the system of equations (1, 2, 5, 6 and 7) with the experimental data, the mass transfer coefficient in the gas phase and the diffusion coefficient in the liquid phase for each volatile were determined. As reported in Table III, the mass transfer coefficients of volatiles in the gas phase had the same order of magnitude (around 0.03 m/s) for all molecules. The mass transfer coefficients in air were determined using the well-known power law between dimensionless parameters (Sherwood number as a function of Reynolds and Schmidt numbers) (72). The experimental mass transfer coefficient obtained confirmed that there was turbulent flow in the gas phase due to the flow rate ( Ù ) and the geometry of the experimental cell. It has already been shown that increasing Ù tends to decrease the relative concentration in the gas phase (10, 13). The diffusion coefficients in the liquid (water) phase were similar for all of the molecules studied, ranging between 2 to 6 χ 10" m /s. These experimental values seem to be slightly higher than literature values quoted for low molecular weight molecules in water (14). This tendency was also confirmed when the theoretical values of diffusion coefficients in water were estimated with the Wilke and Chang equation (9) (Table 9

2


159 III). The apparent diffusion coefficient estimated with the dynamic headspace dilution method could be overestimated due to convection in the liquid phase, which could happen in practice and which should be added to the pure diffusion mechanism.


1.4

Figure 3. Release curve for the five volatiles studied. (Temperature = 25°C, Ù = 70 mL/min, V = 50.10' m , Initial concentration of headspace in equilibrium with the sample). The experimental data are marks and the solution of the model is the continuous line. 6

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Table ΙΠ. Kinetic properties of theflavorcompounds in water at 25°C

3E-9 2.5 E-9 5E-9

1.4 E-9 1.0 E-9 0.82 E-9

2.5 E-6 2.5 E-6 2 E-6

3E-2 3E-2 3E-2

kg in air (m/s) theo. Re=500 Re= 25000 4.0 E-2 0.72 E-2 3.4 E-2 0.62 E-2 3.2 E-2 0.57 E-2

5 E-9

1.1 E-9

3 E-6

3E-2

0.50 E-2

2.7 E-2

6 E-9

0.62 E-9

3 E-6

3E-2

0.12 E-2

2.3 E-2

D in water D in water (m /s) (m /s) exp. theo.

Molecule

2

2

a

kj in water (m/s) exp. d

kg in air (m/s) exp.

b

Acetaldehyde Diacetyl 2,5-Dimethyl pyrazine Dimethyl sulfide Menthone

e

and Colburn equation (12) ; (d) data obtained from eq 1, 10, 11 and 12 (10) Nevertheless, comparing experiments and modeling, it appears that increasing the sugar content in the aqueous solution tends to decrease the diffusion coefficient of the solute in this solution. When the viscosity of the sample was measured, the experimental values for the relative diffusion coefficient of the three molecules seemed to obey the well-known Stokes-Einstein equation (9), where D is inversely


160

proportional to the viscosity (Figure 4). The overall effect of adding sugar on flavor release is that the relative concentration of the volatile is lowered (Figure 5), due to a higher partition coefficient (the lowest C/CO value was seen for the most volatile molecule) and a lower diffusion coefficient (Table 2).


10

ι

0.01 0.001

0.01 Viscosity (Pa.s)

Figure 4. Relative diffusion coefficient of the volatiles (diacetyl, menthone, dimethylsulfide) in aqueous solutions with variable concentration in sucrose, as a function of the liquid viscosity (25°C).

Figure 5. Release profile of diacetyl in different sugar solutions (Γemperature = 25°C, ù = 45 mL/min, V= 100.10' m , Initial concentration of headspace in equilibrium with the sample). 6

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Simplification of the Model and Derivation of Dimensionless Parameters Now that a theoretical approach was developed and validated with experimental data, it was possible to extract key parameters that had a major influence on flavor release.


Initial Release (Transient State) The initial slope of the flavor release curves was similar for all volatiles (see Figure 3). Indeed, at time zero, assuming that the concentration in the gas phase is in equilibrium with the sample phase, the mass flux (J(t=0)) tends to zero and eq (1) and (7) give: C

< _% / .

d l

= .,)|

A V

dt

The slope of the curve of the relative concentration (C/C ), at initial time, is independent of the volatile and depends only on the operating conditions (gas flow rate and volume of the gas phase). But, taking into account the variation of the absolute value of the concentration: 0

«

=- f K . C

(

t

= 0)

eq9

A high partition coefficient (highly volatile molecule) as well as a high initial concentration in the liquid would led to a high decrease of the intensity seen during the first short period of time. Asymptotic Value of the Concentration (Steady State) Referring to the later part of the flavor release curves (see Figure 3), it is not so easy to extract a simple parameter from the modeling based on diffusion in the liquid phase. Assuming that pure diffusion was not completely achieved in the liquid sample, another representation for the modeling was proposed by defining an apparent mass transfer coefficient in the liquid phase (ki), which is equivalent to the diffusion coefficient (D) divided by an equivalent limiting layer (72). This approximation introduces a simplification in the system of equations which becomes: V . ^ = J(t).A-Ù.C(t) at J(t) = k (K.C'(t)-C(t))

«I

eqlO

0

V'^>=-J(t).A dt • with an overall mass transfer coefficient (ko)-

1

« Ι " * _ — +—

ko

eq 12.

kg ki

As seen in Figure 6, the model with the mass transfer coefficient in the liquid phase doesn't take into account the slight decrease characteristic of the diffusion model, but the overestimation of the relative concentration is less than 10% after 10 minutes. Consequently, the result of the simplified model was compared again systematically with the release curve of each volatile. Differences between the


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release of the five flavor compounds are in good agreement (10). As seen in Table III, similar to the diffusion coefficient, the mass transfer coefficients obtained in the liquid phase do not differ significantly from one flavor compound to another, and the order of magnitude (1 χ 10" m/s) is in accordance with literature values for a quasinon mobile liquid (12). This simplified model was used to define criteria to characterize flavor compounds in the asymptotic part of the release curve. In the steady state, assuming that the average concentration in the liquid phase is 6

constant due to the short time of the experiment (j(t) = ko(C(t = 0)-C(t)))> the variation of the concentration in the gas phase tends to zero ( J ( t ) . A - ù . C ( t ) -> 0), then: Downloaded by CORNELL UNIV on October 17, 2016 | http://pubs.acs.org Publication Date: September 7, 2000 | doi: 10.1021/bk-2000-0763.ch013

eq 13 C(t) C(t = 0)' 1+:

k A The variation of the relative concentration in the gas depends only on one 0

n

dimensionless parameter

, which is related to the operating conditions in the

k .A 0

system (gas flow rate, exchange surface) as well as the overall mass transfer coefficient (ko).

c/co

10 minutes

1 200

400

600

800

Time (s)

Figure 6. Comparison between experimental data (marks), and models based on diffusion coefficient (D) and on mass transfer coefficient in liquid phase (kj). (Diacetyl, Temperature = 25°C, Û = 70 mL/min, V = 50.10' m , Initial concentration of headspace in equilibrium with the sample). 6

3

It turns out that an increase in the surface (A) as well as a decrease of the flow rate ( ύ ) leads to an increase in the relative concentration, but the effect depends on the value of the overall mass transfer coefficient (ko), which is characteristic for each flavor compound providing other factors remain constant. The value of ko fixes the level of each flavor concentration in a fixed system but, as seen in equation (12), when Ù increases, ko could be modified at the same time, due to the value of kg. In Figure 7, the order of magnitude of the relative concentration (C/C ), for the 0


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asymptotic part of the flavor release curve, was represented as a function of the dimensionless number

u

, for a wide range of operating conditions : ύ ranged

k .A 0

2

2

2

from 1 mL/min to 1 L/min, A ranged from 1 c m to 10 cm , Κ ranged from 10" to 10" , kg from 10~ to 10" m/s and k, from 10" to 10" m/s. In Figure 7, two parts corresponding to two mechanisms are identified: 5

2

- when

Η k .A

3

6

8

is less than 0.1, the partition coefficient is the only property

0

determining the relative concentration;


when

is higher than 0.1, the mass transfer coefficients must be taken k .A G

into account to predict the amount of flavor released.

k

0

A

Figure 7. Relative concentration in the gas phase (C/C ), for the asymptotic part of the flavor release curve, as a function of the dimensionless number. Operating conditions for the model (continuous line): ù ranged from 1 mL/min to 1 L/min, A ranged from 1 cm to 10 cm , Κ ranged from 10' to 10' , k ranged from 10' to 10' m/s and k ranged from 10' to 10' m/s. Experimental data are marks. 0

2

2

2

5

2

3

g

6

8

t

Three types of behavior can be defined with this approach : • if J L _K_, the mass transfer in the gas phase is the limiting step. It is, for kg

•

> : >

kj

example, the case for 2,5-dimethylpyrazine (low volatility) in the nonstirred aqueous solutions in contact with air (non turbulent, Re=500). Increasing the convection inside the air phase will tend to modify its release profile. if J _ K_, the mass transfer in the liquid phase is the limiting step. It is, for kg

K

Flavor Release - American Chemical Society

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