Journal of Chromatographic Science 2013;51:764– 779
doi:10.1093/chromsci/bms257 Advance Access publication January 27, 2013
Review Article
New Approaches to the Kinetic Study of Alcoholic Fermentation by Chromatographic
Techniques
Georgia Ch. Lainioti and George Karaiskakis*
Department of Chemistry, University of Patras, GR-26504 Patras, Greece
*Author to whom correspondence should be addressed. Email: [email protected]
Received 1 October 2012; revised 19 December 2012
The kinetics of the fermentation process has gained increasing
interest, not only in the scientific community, but in the industrial
world as well. Information concerning the improvement of batch
fermentation performance may potentially be valuable for the
designing of scale-up processes. Intensive studies have been conducted with the use of various chromatographic techniques, such
as conventional gas chromatography, reversed-flow gas chromatography (RFGC), high-performance liquid chromatography, field-flow
fractionation and others. In the present study, specific focus is
placed on the employment of RFGC, a method that can successfully
be applied for the determination of physicochemical quantities,
such as reaction rate constants and activation energies, at each
phase of the alcoholic fermentation. In contrast to conventional
chromatographic techniques, RFGC can lead to substantial information referring to the evaluation of fermentation kinetics at any time
of the process. Moreover, gravitational field-flow fractionation, a
sub-technique of field-flow fractionation, presents the ability to
monitor the proliferation of Saccharomyces cerevisiae cells through
their elution profiles that can be related to the different cell growth
stages. The combination of the two techniques can provide important information for kinetic study and the distinction of the growth
phases of yeast cell proliferation during alcoholic fermentations
conducted under different environmental conditions.
Introduction
Alcoholic fermentation
“Wine fermentation must be a decomposition that occurs
when the sugar-fungus uses sugar and nitrogenous substances
for growth, during which, those elements not so used are preferentially converted to alcohol,” explained Schwann in his
paper entitled “A Preliminary Communication Concerning
Experiments on Fermentation of Wine and Putrefaction” (1).
Alcoholic fermentation is one of the oldest procedures in the
history of humanity. Yeast converts grape sugar into roughly
equal parts of ethanol and carbon dioxide, producing heat.
Alcoholic fermentation is a combination of complex interactions involving the variety of must, microbiota and winemaking technology. The concept of inoculating grape juice
with selected starter cultures of Saccharomyces cerevisiae to
encourage rapid, consistent fermentation has become widely
accepted within the wine industry (2, 3). With the progress of
biotechnology, many changes have been made to traditional
wine-making procedures. Immobilized cells have been extensively used in food and fermentation industries due to their
advanced properties toward free cell systems. The employment
of biocatalysts has been important in many industries for centuries because they are attractive catalysts for a wide range of
chemical transformations. This can be attributed to their
advanced properties in comparison with free cell systems, such
as improved productivity and products of higher quality. The
support material on which the Saccharomyces cerevisiae
strain will be immobilized is of utmost importance for an effective immobilization. Inorganic (g-aluminum, kissiris or
ceramic materials) (4 –7) or organic (cellulosic materials, polyacrylamide, carrageenan or alginates) materials (3, 8, 9), in addition to fruit pieces (apple and quince) (10, 11) have
successfully been used as immobilization supports.
With respect to the properties of yeast, yeast cells typically
operate under mild conditions of pH and temperature, leading
to the formation of highly pure products. As discussed in the
literature, the fermentation temperature can affect the microbial ecology of the grape must and the biochemical reactions
of yeast cells (12). In addition to affecting growth and survival,
temperature has many substantial effects on the metabolism
of yeast. One of the most marked is its influence on the fermentation rate (13). Cool temperatures dramatically slow the
fermentation rate and may cause its premature termination.
Excessively high temperatures may also induce stuck fermentation by disrupting enzyme and membrane functions. Because
yeast strains differ in this response, the optimum temperature
for vinification can vary widely (13).
It is well known from the literature that the life cycle of
yeast is activated from dormancy, when it is added to the fermentation liquid. Yeast growth follows four phases: the lag
phase, which appears after the inoculation of yeast cells in the
medium and represents the period of adjustment in their new
environment; the growth phase, during which yeast cells multiply and the growth rate becomes maximum; the stationary
phase, in which yeast cells develop their action as fermenting
organisms; and finally, the decline or death phase, during
which yeast cells die because of the high ethanol concentrations and the lack of nutrition substances in the fermentation
liquid (14 –16).
Alcoholic fermentation kinetics
With increasing interest in the industrial application of alcoholic fermentation, various kinetic models have been proposed in
the literature for cells suspended in batches or continuous
operations (17 –21). Parameters such as maximum specific
growth rate for growth phase have been measured, in addition
to biomass concentration, fermentation and substrate uptake or
dilution rate for steady-state fermentation. Kinetic models can
provide valuable information when the cell composition is
time-dependent. As stated before, the yeast growth cycle
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follows four phases, which are arbitrary because all of the
phases may overlap in time. The development of appropriate
mathematical models can be a good approximation for describing the cell growth cycle and the kinetics of fermentation.
In 1945, Monod reported an empirical equation to describe
cell growth as a function of the limiting substrate concentration (22). Since then, various models have been reported in the
literature describing the kinetics of alcoholic fermentation processes. A wide range of empirical models has been used to
study alcoholic fermentation in terms of cell concentration,
substrate utilization rate and ethanol production rate. The most
widely used model (21) provides the coefficients for substrate
uptake and product formation. The models of Monod (22) and
Teissier (23) represent inhibition-free kinetics. Edwards (24)
and Luong (25) provide equations for substrate inhibition
effects, whereas the models of Hinselwood (26), Ghose and
Tyagi (27) and Aiba et al. (28) include product inhibition
kinetics.
Gulnur et al. (29) used the models proposed by Monod (22)
and Hinselwood (26) for the description of immobilized
Saccharomyces cerevisiae cells at low and high initial glucose
concentrations. Blanco et al. (21) conducted a comparative
study of alcoholic fermentation under similar pH and temperature conditions, but different initial glucose concentrations of
culture medium. After testing various empirical models, the
Hinselwood model (26) was found to be the best for this work.
Gulnur et al. (29) presented a mathematical description for
the fermentation characteristics of Saccharomyces cerevisiae
cells immobilized on Ca-alginate gel beads in a stirred batch
system of different initial glucose concentrations. The experimental results were tested using 11 well-known mathematical
models, taking into account the possibility of glucose or
ethanol inhibition on both yeast cell growth and ethanol
production.
Caro et al. (30) proposed a kinetic expression that accounts
for the temperature dependence in batch alcoholic fermentations. According to that, the specific growth rates of
Saccharomyces cerevisiae at 20 and 158C were 0.090 and
0.024 h21, respectively. Moreover, Ozilgen et al. (31) proposed
simple mathematical models for simulating microbial growth,
reducing sugar utilization and increasing ethanol production
and temperature in a spontaneous wine-making process. They
calculated the rate constants for the third phase between
0.039 h21 (fast fermentation) and 0.042 h21 (slow
fermentation).
Ciani et al. (32) determined the growth kinetics and fermentation behavior of five non-Saccharomyces yeast species associated with wine-making. The specific growth rates for
Saccharomyces cerevisiae, calculated by cell number and dry
weight, were 0.262 and 0.085 h21, respectively. Giovanelli
et al. (33) reported specific growth rates of Saccharomyces
cerevisiae equal to 0.13 h21 under aerobic conditions and
0.07 h21 under anaerobic conditions.
Furthermore, according to Birol et al. (34), the observed
maximum specific growth rates were determined between
0.191 and 0.201 h21. Godia et al. (17) used a different technique, based on the integration of the different rate equations
in the modeling of batch alcoholic fermentation using
Saccharomyces cerevisiae at different temperature and initial
sugar concentrations. The kinetic parameters for the maximum
specific growth rate and the maximum specific fermentation
rate were calculated using two mathematical models. Chen
et al. (20) presented a modified kinetic model suitable for continuous cultures and ethanol fermentations under high gravity
fermentation conditions, through which the specific growth
rate of Saccharomyces cerevisiae and the ethanol production
rate for different initial and residual glucose concentrations
were determined. The maximum values of 0.146 and
1.172 h21, respectively, were illustrated at an initial glucose
concentration of 200 g/L.
Differences observed in the proposed kinetic models
confirm that the equation parameters depend not only on the
species of the used microorganism, but also on other factors,
such as fermentation temperature and glucose concentration.
Chromatographic techniques for the study of alcoholic
fermentation
Chromatographic techniques are widely used for determining
volatile compounds and ethanol content in wines and alcoholic
beverages. Such compounds are important for the classification,
quality control and sensory evaluation of wines (35, 36).
Fernandes et al. (37) used different multidimensional chromatographic techniques to study wine aroma pattern changes
during malolactic fermentation (MLF). Ethyl lactate enantiomeric ratios were determined using online multidimensional
gas chromatography. The values corresponded with a spontaneous MLF. Offline multidimensional high-performance liquid
chromatography/gas chromatography (HPLC/GC) was used to
deconvolute and enrich the sample and to ease enantioselective chromatography. Aroma compounds were analyzed by
HPLC.
Peinado et al (38) used an Agilent 6890 Series Plus gas chromatograph with electronic pressure control to develop and
validate a simple method for quantifying many of the most important volatile compounds and polyols in wine in a single
chromatographic run.
The composition and content of odor compounds determine
the quality of alcoholic products. The smell of an alcoholic beverage is the effect of many chemical compounds with different
properties (such as polarity or volatility) occurring at widely
differing concentrations. The chemical composition of the
odors depends on the quality and type of the raw materials and
on the conditions of the fermentation process. Gas chromatography–olfactometry (GC–O) studies on the odor of alcoholic
beverages usually have the goal of determining the relationship
between the composition and the content of volatile compounds and the organoleptic properties of products such as
beer (39, 40), wines (41, 42) and whiskeys (43), in addition to
the identification and comparison of the compounds entering
the aroma of different alcoholic beverages, such as wines (44 –
51) or cognacs (52, 53).
Distilled alcoholic beverages, wines and beers, are often
characterized by GC or gas chromatography– mass spectroscopy (GC–MS) analysis of fatty acids and their esters, which
contribute to the taste and quality of these commodities. Fatty
acids in wines are mostly straight-chain C6– C10 acids. They
are derived from yeast during fermentation, and from the firm
tissues of the grapes. As in distilled alcoholic beverages, fatty
acids in wine occur as free acids and ethyl esters at low levels
New Approaches to the Kinetic Study of Alcoholic Fermentation by Chromatographic Techniques 765
(mg/L). GC analysis of the major aroma components has been
conducted by means of solvent extraction with 1,1,2-trichlorotrifluoroethane (Kaltron or Freon 113) using a large sample to
solvent ratio (100:1) (54). The required sensitivity for GC –
flame ionization detection (FID) analysis was achieved by large
volume injection with solvent removal in a program temperature vaporizer (PTV) liner. Recently, the applications of solidphase microextraction (SPME) to the GC analysis of wines have
frequently been reported in literature. Vas et al. demonstrated
(55) that SPME-GC – MS was a simple, quick and sensitive approach for characterization of wines. Regarding distilled alcoholic beverages, strong anion-exchange solid-phase extraction
(SAX-SPE) has been used for the selective isolation of organic
acids from wines. In the procedure reported by Deng (56), the
ethyl ester derivatives of C4 –C18 fatty acids and other organic
acids were extracted by dichloromethane and reproducibly
quantified by GC– FID using internal standards. The applicability of supercritical fluid extraction –gas chromatography (SFE –
GC) for analyzing wine aroma has been evaluated by Blanch
et al., using PTV as an interface to trap the analytes (57).
Conventional GC has also been applied by Tsakiris et al. (58)
to examine the quality of wines by determining methanol and
ethanol concentrations. Moreover, Mallouchos et al. (59)
reported the analysis of volatile compounds during the alcoholic fermentation of grape must using free and immobilized cells
on delignified cellulosic materials (DCM) with the help of
SPME. Repeated batch fermentations were conducted using
biocatalysts and free cells at temperatures of 20, 15 and 108C.
SPME was used to monitor the formation of volatile alcohols,
acetate esters and ethyl esters of fatty acids. The kinetics of
volatile production was similar for free and immobilized cells.
In a further study, Kandylis et al. (60) used GC to evaluate the
ethanol productivity (dP/dt) and additionally to calculate the
activation energies of free and immobilized cells using a form
of the Arrhenius equation:
lnðdP =dt Þ ¼ lnðAX Þ Ea=RT
ð1Þ
where X is the cell mass concentration (g/L).
This equation describes the curve obtained by plotting
ln(dP/dt) versus 1/T. From the slope and intercept of this
straight line, the activation energy, Ea, and the Arrhenius preexponential factor, A, can be calculated. More specifically,
these studies, after a theoretical consideration, concluded that
the support may behave as a catalyst or a promoter of the catalytic activity of the enzymes involved in the fermentation
process, causing a reduction in the activation energy. The activation energy of the immobilized cells on corn starch gel cells
was 36% smaller than that of free cells (62.2 and 97.4 kJ/mol,
respectively), confirming the catalytic activity of the immobilization support. Furthermore, using the common form of the
Arrhenius equation
k ¼ A expðEa=RT Þ
ð2Þ
and substituting Ea and A, the reaction rate constants were calculated for free and immobilized cells at temperatures between
15 and 308C. Immobilization and temperature significantly
affected the reaction rate constants ( p , 0.01 in both cases),
and a strong interaction was also observed between them
766 Lainioti and Karaiskakis
( p , 0.01). More specifically, an apparent rate constant was
measured for the whole fermentation process at 308C that was
1.8-fold higher than that of free cells (0.808 and 0.454 h21, respectively). A decrease in fermentation temperature made the
reaction rate constant of immobilized cells, for the whole fermentation process at 158C, 3.6-fold higher than that of free
cells (0.223 and 0.061 h21, respectively). These results prove
that starch gel acts as a catalyst.
The aim of this review, concerning the new approaches to
the kinetic study of alcoholic fermentation, is to present the
techniques of reversed-flow gas chromatography (RFGC) and
field-flow fractionation (FFF) for the determination of physicochemical quantities related to the kinetics of the alcoholic fermentation and for the analysis of yeast cell proliferation during
alcoholic fermentations conducted under different environmental conditions.
New Approaches
Reversed-flow gas chromatography
Theory
The principle on which the RFGC method is based is illustrated
in Figure 1A.
A long diffusion column, of length L1, containing the liquid
at its bottom, is connected perpendicularly to the mid-point of
a so-called sampling column, of length l 0 þ l, and the whole
cell is thermostated inside the oven of the chromatograph. The
two ends of the sampling column are connected to the carrier
gas inlet and the flame ionization detector through a four-port
valve, as shown. By switching this valve from one position
(solid lines) to the other (dashed lines), the direction of the
carrier gas flow through the column of length l 0 þ l is reversed,
producing sample peaks in the recorder line.
It has been pointed out in previous work (61, 62) that if the
gas flow is reversed for a short time, t 0 , shorter than both gas
hold-up times in the column sections l 0 and 1, and then
restored again to the original direction, a symmetrical sample
peak is produced, as shown in Figure 1B. The maximum
height, H, of the peak, measured from the ending baseline, is
given by
H 2c ðl 0 ; t0 Þ
ð3Þ
where c (l 0 , t0) is the vapor concentration at x ¼ l 0 , and the
time t0 is measured from the moment of placing the liquid at
the bottom of a column of length (L1 þ L2) (L1 is the diffusion
column and L2 is the column in which the liquid is placed)
(61) to the last backward reversal of gas flow.
It has been shown (61) that each sample peak produced by a
short flow reversal is symmetrical and its maximum height, H,
from the ending baseline is given by
H ¼
2kc Dcg
f1 exp½2ðkc L1 þ DÞt0 =L12 g
U ðkc L1 þ DÞ
ð4Þ
where kc is the mass transfer coefficient for solute evaporation,
D is the diffusion coefficient of the solute vapor into the
carrier gas, cg is the concentration of the vapor in equilibrium
Figure 1. Schematic representation of the experimental arrangement of the RFGC system for the determination of ethanol concentration in the fermentation medium (A);
sample peaks of ethanol at 308C obtained by RFGC (B). From Ref.[78], with permission.
with the bulk liquid phase concentration, cl, at the working
temperature and u is the linear velocity of the carrier gas.
Modification of Eq. 4 leads to two approximate solutions,
one for short times and one for long times. The latter approximation is as follows (63):
lnðH1 H Þ ¼ lnH1 ð2kc L1 þ DÞ=L12 t0
ð5Þ
where H1 is the infinity value for the peak height, given by the
expression to the left of the brackets in Eq. 4, i.e., [u(kcL1 þ D)].
Eq. 5 shows that a plot of ln(H1 – H) versus t0 should be
linear, and from the slope –2(kcL1 þ D)/L21, a first approximation value for kc can be calculated from the known value of L1
and a theoretically calculated value of D. This value of kc can
be used to plot the data at short times according to the shorttime approximation, which is as follows (63, 64):
"
ln H
L1
1=2
2t0
!#
1=2
þ k c t0
"
#
4kc cg D 1=2
L2 1
¼ ln
1 u
p
4D t0
ð6Þ
From the slope 2L 21/4D of a plot of the left-hand side of Eq. 6
versus 1/t0, the first experimental value is found for D. This
can be used with the slope found from the plot of Eq. 5 to calculate a better approximation of the kc value, and this is used
to replot Eq. 6 for a better approximation of the D value. These
iterations can be continued until no significant changes result
in the values of kc and D, but it is not usually necessary to go
beyond the first iteration.
As mentioned before, the height of the sample peaks reaches
a maximum value, H ¼ H1, after which it remains constant.
The relation between the maximum height, H1, and the
ethanol concentration, cl, is given by Eq. 7 (63, 64):
cg ¼
c1 uH1
¼
ðL1 =D þ 1=kc Þ
K
2
ð7Þ
where K is the partition coefficient.
The preceding procedure was repeated in different fermentation periods (tx) from the beginning to the end of the fermentation process and the corresponding values of Hx were
New Approaches to the Kinetic Study of Alcoholic Fermentation by Chromatographic Techniques 767
measured. It is known that fermentation is a continuous
process; taking into account that samples were drawn from the
fermentation mixture in different time periods (from the beginning to the end) of this process, the measured H1 values
can be combined with the H01 value, which is the value of H1
at the end of the fermentation. The value of H01 corresponds to
the final ethanol concentration. The relation between H01 and
H1 has been already derived (63, 64) and has the final form:
lnðH10 H1 Þ ¼ ln H10 ktx
ð8Þ
where k is the rate constant for the ethanol production, which
can easily be calculated by plotting ln(H01 2H1) against tx.
Experimental
As mentioned previously, the development of appropriate
mathematical models can provide valuable information about
the life cycles of yeast cells. The estimation of the duration of
each of the previously discussed phases (lag, growth, stationary
and decline) is of great importance because it allows the determination of the rate constants for each phase of the fermentation process. The aforementioned can be conducted by
developing an appropriate mathematical model for the analysis
of the experimental data obtained from a versatile gas chromatographic technique, RFGC. RFGC can be applied for the determination of ethanol production during alcoholic fermentation
processes by measuring the ethanol produced at any time during
the fermentation process. A gas chromatograph (Shimadzu-8A)
equipped with an FID was used for the separation and quantitation
of ethanol (Figure 1A). The chromatograph was slightly modified
to include a T-shaped cell constructed from a glass chromatographic tube inside the chromatographic oven and a four-port
gas valve (Figure 1A).
The oven of the system contained the sampling column, consisting of two sections of lengths l ¼ l 0 ¼ 100 cm and the diffusion column with length L1 ¼ 43 cm. At the lower end of
diffusion column, a glass vessel (L2 ¼ 5 cm) containing the fermentation mixture was connected. The two columns comprised the sampling cell, which was connected to the carrier
gas inlet and the detector so that the carrier gas flow through
the sampling column (no carrier gas flows through the diffusion column) could be reversed in direction at any time
desired. This can be done by using a four-port valve to connect
the ends of the sampling column to the carrier gas supply and
the detector, as shown schematically in Figure 1A. An analytical
column (2 m 1/4 in. 2 mm glass) packed with 5%
Carbowax-20 M and 80/120 mesh Carbopack BAW, which was
kept at 1158C, was placed before the detector to separate
ethanol from the by-products of alcoholic fermentation. The
temperature of the detector was set at 1508C, whereas the
temperature of the chromatographic cell was 758C. The experiments were conducted under constant flow rate (20 mL/min)
using helium as carrier gas.
An aliquot of 0.5 mL of the fermentation mixture was added
to the glass vessel (Figure 1A) at constant temperature and
pressure. By the time a concentration-time curve appeared, the
chromatographic procedure began by reversing the carrier gas
flow direction through the Shimadzu valve for 6 s. This period
of time was shorter than the gas hold-up time in both sections
l and l 0 . When the flow of the carrier gas was restored to its
768 Lainioti and Karaiskakis
original direction, sampling peaks were recorded, like those
shown in Figure 1B.
Finally, solutions with different ethanol concentration (%, v/v)
in triply distilled water were placed into the glass vessel at the
end of the diffusion column and the values of H1 were measured. These values and their corresponding ethanol concentrations were plotted and a calibration curve (slope ¼ 1.202 cm/M,
intercept ¼ 0.041 cm and R 2 ¼ 0.999) was obtained. According
to the calibration curve and by measuring the height of the
sample peaks during the fermentation process, the unknown
ethanol concentrations of each fermentation mixture can be
found.
Applications on kinetic study of alcoholic fermentation
RFGC is a sub-technique of inverse gas chromatography, which
was introduced in 1980 by Professor N. A. Katsanos (67) and
his colleagues (at the University of Patras, Greece). RFGC
involves the change of the carrier gas flow direction at various
time intervals. It has a vast number of applications in a wide
scientific field, such as the determination of diffusion coefficients (68 –71), adsorption equilibrium constants (72 –74),
Lenard-Jones parameters (75), activity coefficients (76), rate
constants for alcoholic fermentations, gaseous reactions (77 –
81) and heterogenous catalytic reaction (82– 88), and molecular diameters and critical volumes (89).
The RFGC technique was first applied for the kinetic study
of the alcoholic fermentation process on the industrial scale in
conjunction with measurements of suspended particles in the
fermenting medium by Economopoulos et al. (66). It was
found that the overall process consists of four phases that have
different first-order rate constants during ethanol formation.
The RFGC technique provides an easy study of the chemical
kinetics during each phase of the overall process.
As reported by Lainioti et al. (16), RFGC was one of the separation techniques that was used for the distinction of the
growth phases of Saccharomyces cerevisiae cell cycles at different temperatures and pH values. As previously mentioned
(in the “Introduction”), alcoholic fermentation is divided into
four phases, which can be correlated to the growth cycle
phases of AXAZ-1 cells (77, 16). As a result, the four slopes in
Figure 2 correspond to the lag, growth, stationary and decline
phases of the alcoholic fermentation processes. The estimation
Figure 2. Variation of ln(H01 – H1) with time for AXAZ-1 cells at pH 5 and T ¼
308C for the first (diamonds), second (squares), third (triangles) and fourth (circles)
alcoholic phases. From Ref.[16], with permission.
of the duration of each of the fermentation phases is of great
importance because it allows the determination of physicochemical parameters of crucial interest, such as rate constants
and activation energies, for each phase of the fermentation
process.
According to the slopes of Figure 2, which result from Eq. 8,
the values of reaction rate constants, k, for ethanol production
can be calculated at the four phases of the alcoholic fermentations conducted with free and immobilized cells at various
initial glucose concentrations.
The results presented in Table I are mean values of the rate
constants; their standard deviations are also given. The aforementioned slopes were confirmed from the R 2 values, which
were within 0.960 –0.999.
The greatest values of the reaction rate constants were
observed at the second and fourth phases (growth and decline
phase, respectively), whereas the lowest and almost stable
values were observed at the first phase (lag phase), during
which the total biomass concentration did not show any
change.
As reported by Lainioti et al. (77), RFGC was applied for the
kinetic study of the alcoholic fermentation process conducted
with cells of the alcohol-resistant and psychrophilic
Saccharomyces cerevisiae AXAZ-1 yeast strain, either free or
immobilized on wheat, barley and corn grains or on potato
pieces. Repeated alcoholic fermentations with must of varying
initial glucose concentrations were performed to estimate the
catalytic efficiency of the biocatalysts used in the present
study. In this work, each fermentation process consisted of
three phases, which corresponded to the growth, stationary
and decline phases of the alcoholic fermentation. The literature
shows that the duration of the lag phase is highly dependent
on the fermentation efficiency of yeast cells, the conditions of
the fermentation procedure, the immobilization carrier and
other factors. Considering the great fermentation efficiency of
AXAZ-1 cells immobilized on wheat, barley, corn grains and
potato pieces, and their quick adaptation in the fermentation
liquid, the lag phase is not easily observed. In the present
work, the rate constants k1 and k2, which correspond to
the growth and stationary phases, were decreased when the
glucose concentration increased. This can be attributed to the
negative influence of the osmotic stress that high sugar contents of the fermentation liquid exert in the growth of yeast
cells. The values of k3, which correspond to the decline phase
for all systems, reached a maximum value at an initial glucose
concentration of 205 g/L, which indicated that this glucose
concentration comprised the best environment for them to
ferment. Additionally, the values of k3 rate constants for
Table I
Rate Constants, k, with their Standard Deviations for the Fermentation Phases of AXAZ-1 Cells at
pH 5.0 and at 30, 25, 20 and 158C, Obtained by RFGC (From Ref.[16], with permission)
Temperature (8C)
30
25
20
15
k 103 (h21)
First phase
Second phase
Third phase
Fourth phase
8.2 + 0.4
6.7 + 0.3
6.4 + 0.1
5.5 + 0.1
200.0 + 0.8
130.0 + 0.8
70.0 + 0.8
30.3 + 0.2
45.0 + 0.9
30.3 + 1.2
15.2 + 0.4
8.0 + 0.2
200.0 + 0.9
120.2 + 0.7
70.2 + 0.7
30.3 + 0.8
ethanol production in the decline phase were of the same
order of magnitude as those observed at the growth phase.
This behavior may be because once the decline phase begins,
yeast cells have already reached their maximum values. This
means that the production of ethanol occurs at a high rate
because there are large numbers of cells in the fermentation
liquid at this moment. Consequently, what is called the decline
phase in the present work corresponds to an initial stage of
the decline phase of the growth cycle of yeast cells. The
decline phase was not completed due to the great fermentation efficiency of AXAZ-1 cells, which managed to rapidly terminate the fermentation processes.
In another work by Lainioti et al. (78), RFGC was employed
for the determination of the alcoholic fermentation phases and
kinetic parameters for free and immobilized cell systems at different initial glucose concentrations and temperature values.
The immobilization of the wine yeast Saccharomyces cerevisiae AXAZ-1 was accomplished on wheat and corn starch gels
to prepare new biocatalysts of great interest for the fermentation industry. With great accuracy, resulting from a literature
review, RFGC led, to the determination of reaction rate constants and activation energies at each phase of the fermentation
processes. With respect to many factors (immobilization
carrier and fermentation conditions), yeast cells may have a
quick and easy adaptation in the fermentation environment. In
addition to this, the lag phase in many cases is too short to be
detected. Thus, in this work, three phases appeared in the
diagram showing the variation of ln(H01 – H1) versus tx , corresponding to the growth, stationary and decline phases, respectively. Rate constants k1 and k3, which correspond to growth
and decline phases, reached a maximum value at initial glucose
concentration of 205 g/L for all systems in which the higher
number of yeast cells was observed, as shown from the results
of Table II.
This behavior indicates that this glucose concentration comprised the best environment for cells to ferment. After the concentration of 205 g/L, a decrease in the rate constants (k1 and
k3) was observed in free and immobilized systems with an increase in glucose concentration. This can be attributed to the
Table II
Rate Constants, k, with their Standard Deviations, for Each Phase of Alcoholic Fermentation in
the Presence and Absence of an Immobilization Carrier (Wheat and Corn Starch Gels) at
Different Initial Glucose Concentrations (From Ref.[78], with permission)
Initial glucose concentration (g/L)
k (103 h21)
First phase
Wheat starch gel
177.1 + 0.1
205.2 + 0.3
246.8 + 0.2
300.1 + 0.8
Corn starch gel
177.2 + 0.2
205.1 + 0.1
247.0 + 0.3
300.0 + 0.4
Free cells
177.1 + 0.7
204.9 + 0.7
247.0 + 0.2
300.2 + 0.6
Second phase
Third phase
71.6 + 0.8
93.4 + 0.6
28.6 + 0.6
15.2 + 1.0
15.0 + 0.6
14.8 + 0.7
4.2 + 0.2
4.2 + 0.1
94.8 + 0.8
99.5 + 0.3
28.1 + 0.9
23.6 + 0.8
126.6 + 0.9
158.7 + 0.5
31.4 + 1.1
16.6 + 0.6
24.7 + 0.7
15.9 + 0.3
5.1 + 0.6
4.3 + 0.6
110.0 + 0.9
120.0 + 0.4
38.3 + 0.8
27.8 + 0.6
40.1 + 0.9
48.4 + 0.8
11.8 + 0.9
10.9 + 0.6
4.9 + 0.9
4.9 + 0.8
4.5 + 0.2
1.8 + 0.03
31.5 + 0.7
35.8 + 0.9
18.4 + 0.8
12.5 + 0.6
New Approaches to the Kinetic Study of Alcoholic Fermentation by Chromatographic Techniques 769
negative influence of the osmotic stress that high sugar contents of the fermentation liquid exert in the growth of yeast
cells. The rate constant k2, which corresponds to the stationary
phase, was decreased with the increased glucose concentration
in all systems. Comparing free and immobilized systems, the
rate constants for immobilized cells were higher than those
observed in free cells. By summarizing the previously mentioned results, the increase in glucose concentrations had a
negative influence on the growth of AXAZ-1 cells and rate constant values. Moreover, the decrease of fermentation temperature caused substantial reductions in the viability of immobilized
cells and in rate constant values.
Because the rate constants for ethanol production have been
calculated by the RFGC technique, activation energies for each
phase of the alcoholic fermentations can be determined from
the Arrhenius equation (Eq. 2).
Through the slope of the graphical representation of lnk
versus 1/T (Figure 3) as reported by Lainioti et al. (78), corn
starch gel presented lower values of activation energies than
those of wheat starch gel, as shown in Table III.
However, the two supports presented higher catalytic efficiency than free cell systems, because they presented 32 and
39% reduced activation energies for the first (growth) phase of
the alcoholic fermentations, 22 and 32% for the second (stationary) phase and 17 and 23% for the third (decline) phase,
when wheat and corn starch gel were used, respectively.
Moreover, considering the results of a previously mentioned
work (16), the activation energy for the first (lag) phase of the
alcoholic fermentation process was 18.4 + 0.4 kJ/mol, whereas
for the remaining phases (second, growth; third, stationary;
fourth, decline), higher values were observed: 90.5 + 0.2,
94.5 + 0.3 and 95.6 + 0.5 kJ/mol, respectively.
The results of activation energies, given in Table III, are in
the same order of magnitude with previous studies published
in literature (60, 79), in which the activation energy of AXAZ-1
cells immobilized on corn starch gel and potato pieces was
62.2 and 61.1 kJ/mol, respectively, for the whole fermentation
process. This agreement of bibliographic and experimental
values confirms the reliability of the RFGC method for the
kinetic study of the alcoholic fermentation process and the
great catalytic activity of the immobilized AXAZ-1 cells.
Moreover, it shows that the immobilization carrier may act as a
catalyst or a promoter of the catalytic activity of the enzymes
involved in the fermentation process.
Field-flow fractionation
Theory
FFF is classified as a one-phase chromatographic technique in
which an externally adjusted force field is applied to the suspended particles under motion in a channel. The particles are
pushed to one of the channel walls so that they occupy a thin
layer close to the accumulation wall. The thickness of the layer is
an explicit function of the applied field, particle size and density of
both particles and carrier solution. It is an elution technique, and
as in classical chromatography, sample components elute at retention volumes that are related, and often rigorously predictable, to
various physicochemical properties of the retained species.
The FFF technique is ideally suited to analytical-scale separation and characterization of particles (80, 81). Different kind
of fields have been applied to FFF. They can be a sedimentation
field or a thermal gradient, an electrical field or a secondary
flow. The type of field defines the FFF sub-techniques, which,
therefore, shows wide applicability. Gravitational field-flow fractionation (GrFFF) is the simplest and cheapest among FFF techniques. It is a subset of sedimentation field-flow fractionation
(SdFFF) that is suitable for the separation and characterization
of various micrometer-sized particles of different origin (90,
91). It employs Earth’s gravitational field applied perpendicularly to a very thin, empty channel. GrFFF is very appealing in the
field of biological applications. It has been applied to living
samples such as parasites (92) and blood cells (93) because of
its simplicity, low cost and reduced risk of sample degradation.
It has also been used in the characterization of albumin (94),
liposomes (95) and colloidal materials (96 –101).
In normal FFF, the sample is forced toward the wall of the
channel by the applied field to form a layer of unique thickness, which depends upon the interaction of the sample with
the field and the opposing diffusion or Brownian motion of the
sample away from the wall. These opposing processes result in
a steady-state exponential layer distribution of sample near the
channel wall, given by the following (102):
c ¼ c0 expðx=l Þ
ð9Þ
where c is the concentration of sample at distance x from the
wall, c0 is the wall concentration (x ¼ 0) and l is the characteristic distance termed the mean layer thickness of the solute. As
the solute zones are swept down the channel, those with
larger l values penetrate faster moving streamlines and are
swept toward the end of the channel at a higher rate.
In the case of an exponential distribution and a parabolic
velocity profile confined between infinite parallel plates
Table III
Activation Energies, Ea, with their Standard Deviations, for Each Phase of Alcoholic
Fermentations in the Presence and Absence of the Immobilization Carrier (From Ref.[78], with
permission)
Biocatalyst
Figure 3. Arrhenius plots of lnk versus 1/T 103 (1/K) for the evaluation of the
activation energy of each phase of the alcoholic fermentations conducted with cells
immobilized on wheat (triangles), corn starch gels (squares) and free cells (circles).
From Ref.[78], with permission.
770 Lainioti and Karaiskakis
Wheat starch gel
Corn starch gel
Free cells
Ea (kJ/mol)
First phase
Second phase
Third phase
67.3 + 0.4
60.5 + 0.4
99.4 + 0.2
62.6 + 0.4
54.7 + 0.5
80.0 + 0.3
60.3 + 0.5
55.5 + 0.6
72.5 + 0.5
(Figure 4), the expression for the retention ratio R (void
volume V0/retention volume Vr) is found as follows (102):
R¼
V0
¼ 6l½cothð1=2lÞ 2l 6l
Vr
ð10Þ
where l ¼ l/w (w is the width of the channel, i.e., the distance
between the flat walls confining the flow) is a dimensionless
ratio, which is the basic retention parameter of FFF. The approximation R 6l is valid in the limit of high retention (small
R and small l), which is approximately valid for almost the
entire practical range of operating conditions in FFF.
In sedimentation FFF, l is related to the diameter d of a
spherical particle (for nonspherical particles, d is the Stokes
diameter, which is the diameter of a sphere of equal diffusivity), by the following expression (102):
l¼
6kT
pd 3 GwDr
ð11Þ
where k is the Boltzmann’s constant, T is the temperature, G ¼
v2r is the magnitude of the sedimentation field expressed as
acceleration (v is the angular velocity and r is the radius of the
centrifuge basket inside which the channel is fitted) and Dr is
the density difference between particle and carrier.
Combining Eqs. 10 and 11 leads to
pGwDrV0 3
d ¼ L d3
36kT
pGwDrV0
where L ¼
36kT
Vr ¼
ð12Þ
ð13Þ
Eq. 12 shows that in normal sedimentation FFF, the retention
volume increases with particle diameter until steric effects
dominate, at which transition point there is a foldback in
elution order. As the particle radius becomes appreciable compared with l, the mechanism of migration undergoes a transition from that of normal FFF to that of steric FFF. Steric FFF
predominates when the radius of the particle, a, exceeds the
mean layer thickness, l. Under these circumstances, the movement of the particle down the channel is determined largely
by the particle radius.
Whereas R, under normal conditions, is found from Eq. 10,
in steric FFF, the same parameter is given by the following
expression (102):
R ¼ 6g
a 3g d
¼
w
w
ð14Þ
where the factor g accounts for the drag-induced reduction in
velocity.
The retention volume, Vr, is therefore, given by the expression
Vr ¼
wV0 1 wV0 1
1
¼
¼ L0
d
6g a
3g a
wV0
where L0 ¼
3g
ð15Þ
ð16Þ
Eq. 15 shows that Vr in steric FFF is inversely proportional to particle diameter d, in contrast to the dependence on d 3 in normal
FFF, given by Eq. 12. Thus, the large particles tend to move more
quickly than the smaller ones in steric FFF, and the separation
mechanism is based on inherent particle size rather than on the
ability of a particle to undergo Brownian diffusion.
Experimental
The GrFFF system used for the kinetic study of the alcoholic fermentation, which has been described in detail elsewhere (103),
has the following dimensions: length, l ¼ 48.3 cm; breadth, a ¼
2.0 cm; thickness, w ¼ 0.021 cm. The channel void volume, V0,
measured by the elution of the non-retained sodium benzoate
peak, was found to be 2.025 cm3. A Gilson Minipuls 2 peristaltic
pump was used to pump the carrier solution and the sample to
the channel, whereas a Gilson model 112 UV/VIS detector operated at 254 nm, and a Linseis model L6522 recorder were also
used for sampling analysis. Polystyrene particles of different diameters (nominal 2.013 + 0.025, 4.991 + 0.035, 9.975 + 0.061,
15.02 + 0.08 and 20.00 + 0.10 mm) from Duke Scientific
Corporation, dispersed in triply distilled water, were used for
the optimization of the elution conditions. The carrier solution
was triply distilled water containing 0.5% v/v FL-70 (Fisher
Scientific Co.), a low-foaming, low-alkalinity and phosphate-,
chromate- and silicate-free mixture of anionic and cationic surfactant and 0.02% (w/v) sodium azide (Fluka AG) as bacteriocide. An aliquot of 25 mL was drawn from the fermentation
mixture and injected into the channel by a microsyringe.
Following injection, the longitudinal flow (50 mL/h) was
stopped for 10 min to allow sample relaxation. The general form
of fractograms from which the data were obtained is illustrated
in Figure 5, showing the detector signal.
Applications on kinetic study of alcoholic fermentation
The employment of analytical techniques has rapidly increased
in terms of the separation and characterization of macromolecules and micro-sized particles. One of the most widely used
separation techniques is FFF, which has proved, over more than
three decades, the ability to characterize supramolecular species
in a size range spanning many orders of magnitude (104). In industrial fermentation processes, such as baking, wine making,
brewing and potable and fuel grade alcohol production, yeasts
are added as promoters. In the past few years, the FFF technique
has been applied for the study of yeasts. More specifically, GrFFF
has been applied for the characterization of yeast cells (105,
106) and the study of the viability and activity of Saccharomyces
cerevisiae strains during wine fermentation (107, 108).
Sanz et al. (107) used GrFFF to characterize several commercial active dry wine yeasts from Saccharomyces cerevisiae and
Saccharomyces bayanus. It was demonstrated that during the
wine fermentation process, differences in the elution curves
and peak profiles during fermentation can be related to the different cell growth stages. Moreover, the different fermentation
kinetic profiles of yeast strains could be correlated with the
corresponding fractograms monitored by GrFFF.
The effective capability of GrFFF to characterize winemaking yeast was further investigated by Sanz et al. (109) on
four different types of yeast (Cryoaromae, Fermol Rouge, Awri
350 and Killer). Figure 6A shows the fractogram of the yeast
sample Fermol Bouquet, which shows a broad profile with two
maxima that can be ascribed to a multimodal character of the
distribution of the Fermol Bouquet yeast population. Figure 6B
shows a bimodal distribution of the size of the sample
population.
New Approaches to the Kinetic Study of Alcoholic Fermentation by Chromatographic Techniques 771
Figure 4. Schematic representation of the experimental arrangement of the FFF technique.
Figure 5. Fractograms obtained by GrFFF, showing the peak profiles of: corn (A);
wheat starch granules (B). From Ref.[110], with permission.
Lainioti et al. (108) used GrFFF to study the effect of temperature (15, 20, 25 and 308C) on the fermentation kinetics
and the proliferation of the alcohol-resistant and psychrophilic
Saccharomyces cerevisiae (AXAZ-1) yeast strains in the
772 Lainioti and Karaiskakis
presence or absence of wheat starch granules as immobilization
carrier. As shown (Figure 7), fermentations at 308C for immobilized cells indicated a monomial yeast cell size distribution, for
0 h , t , 2 h, which was kept almost constant, according to
the values of retention volume (Vr) which correspond to the
maximum points of the resolution peaks.
This fact reveals an initial lag phase during which yeast is
adjusting to its new environment and beginning to grow in
size. Fermentations at 15, 20 and 258C began more slowly, as
observed by their longer lag phase (monomial distribution until
4.5 h) and the slower fermentation rate. As the fermentation
proceeded at 308C, the yeast cells tended to cluster together
(flocculate) and a bimodal size distribution was observed. At
this point, the yeast began to reproduce rapidly and the
number of yeast cells increased (thus known as the growth
phase). However, the growth phase was retarded at 15, 20 and
258C. At 308C, and for t . 8.5 h, a monomial distribution
appeared again, showing a steady-state period in which the size
of the strains remained almost constant. According to the
values of Vr for free cells, the way of cell proliferation proved
to be almost similar to that of immobilized cell systems. The
differences in the form of the fractograms are primarily due to
the absence of the wheat starch granules in the culture
medium. The results, in general, indicated that both systems
(free and immobilized cells) performed better at 308C,
whereas at lower temperatures, decreases were observed in the
fermentation rate and in the number of viable cells. The activation energy for the fermentation process was reduced in the
case of immobilized cells compared with free cells.
GrFFF was also applied to study the influence of pH and
initial glucose concentration on the growth of the
Saccharomyces cerevisiae yeast strain in the presence or the
Figure 6. Fractogram of the yeast sample Fermol Bouquet showing the three collected fractions: Fraction 1 from 4.5 to 10 min, Fraction 2 from 10 to 12 min, Fraction 3 from
12 to 17 min (A); size distribution and scanning electron micrograph of the Fermol Bouquet population, obtained under the conditions described in the “Experimental” section
(B). Total cells counted from 2 to 7 mm: 11,618. The fractions in Figure 6A are tentatively indicated on the Coulter size distribution pattern. From Ref.[109], with permission.
absence of corn and wheat starch granules as immobilization
carriers (110). Fermentations were conducted at different
values of pH (3.0, 4.0, 5.0 and 6.0) and initial glucose concentrations (177, 205, 247 and 300 g/L) to find the most favorable
situation for the growth and proliferation of Saccharomyces
cerevisiae cells. The results indicate that the growth of
yeast cells was enhanced at pH 5.0 and glucose concentrations
of 177 and 205 g/L. Higher glucose concentrations (247
and 300 g/L) acted as inhibitors to cell proliferation.
Immobilization on wheat starch provided wider peak profiles,
suggesting a broad size of cells and lower concentrations of
haploid cells than cells immobilized on corn starch granules.
The distinction of the phases of the yeast cell cycle was also
accomplished through the GrFFF technique. For further confirmation of the results, the Michaelis-Menten model was used
to calculate the Michaelis-Menten constant, Km, and the
maximal velocity, Vmax, which are indicative factors for the affinity of the enzymes or cells to the substrate and the number
of enzymatic or cellular molecules. The change of yeast populations was studied through the variation of the peak profiles in
the fractograms, because the GrFFF technique is able to detect
changes during the cell cycle. Differences observed in the
elution curves can be related to the different cell size distribution, the unlike cell density and the morphology and/or shape
(93). Figure 8 shows some selected fractograms for free and
immobilized cells at different fermentation time periods during
the alcoholic fermentations at pH 5.0 and glucose concentration of 205 g/L.
The fractograms of Figure 8 show that during the alcoholic
fermentations of free cells at glucose concentrations of 177
and 205 g/L (Figure 8A), the growth phase appeared at 4.5 h,
whereas the stationary and decline phases appeared at 8.5 and
12.0 h, respectively. However, with the increase of glucose
concentrations (247 and 300 g/L), the phases were slowed due
to the growth-inhibitory effect. During the fermentations of
cells immobilized on corn starch (Figure 8B), a bimodal yeast
cell size distribution (lag phase) was observed at 0 h , t ,
2.0 h for a glucose concentration of 205 g/L, which was kept
almost constant. As the fermentation proceeded, the growth
phase (trinomial distribution) appeared at 2.5 h , t , 7.5 h,
and it was followed by a stable distribution, which represented
the stationary phase (8.0 h , t , 10 h). The decline phase followed from 10.5 h until the end of the reaction, with a bimodal
distribution taking place again. Fermentations at 177 g/L
New Approaches to the Kinetic Study of Alcoholic Fermentation by Chromatographic Techniques 773
Figure 7. Fractograms obtained by GrFFF at T ¼ 308C and pH5.0 for: free cells at t ¼ 0, 6.5 and 18 h (A); cells immobilized on wheat starch granules at t ¼ 0 h, 6.5 and 12 h (B).
From Ref.[108], with permission.
proceeded almost the same as that at 205 g/L, whereas fermentations at 247 and 300 g/L began more slowly, shown by their
longer lag phases (lag phase until 6.5 h for 247 g/L and 10 h
for 300 g/L). The growth phase was slowed (7.0 h , t , 12 h
for 247 g/L and 10.5 h , t , 20 h for 300 g/L), and it was followed by a stable trinomial distribution, revealing the stationary
phase at 12.5 h for 247 g/L and at 20.5 h for 300 g/L. The
decline phase appeared at 19 and 29 h for concentrations of
247 and 300 g/L, respectively. For cells immobilized on wheat
starch at glucose concentration of 205 g/L (Fig. 8C), the
growth phase appeared at 2.5 h , t , 6.5 h, stationary phase at
7.0 h , t , 9.0 h and decline phase at 9.5 h, which lasted until
the end of the reaction.
In the fractograms of free cells, the second elution peak corresponds to the daughter cells, which have been separated from
mother cells (first elution peak) during the cell reproduction.
774 Lainioti and Karaiskakis
To relate the different GrFFF profiles with the kinetics of the
fermentation processes, the latter were monitored by the determination of fermentation time and reducing sugar contents (determination of Michaelis-Menten constants) at different time
periods. The lowest value of Km for free and immobilized cells
was found at pH 5.0 showing the high affinity of cells to the substrate at this pH value.
Combination of RFGC and FFF with other chromatographic
techniques
The combination of RFGC with GrFFF can enrich the information
concerning the kinetics of the fermentation process. In a study
conducted by Lainioti et al. (16), the GrFFF and the RFGC techniques were used for the kinetic study and distinction of the
growth phases of AXAZ-1 cell proliferation during alcoholic fermentations conducted under different environmental conditions.
Figure 8. Fractograms obtained by GrFFF at pH 5.0 and glucose concentrations of 205 g/L at t ¼ 2h, 6.5 and 8.5 h for free (A) and immobilized cells: on corn (B); wheat
starch granules (C). From Ref.[110], with permission.
The use of GrFFF for the determination of elution curves and retention volumes, in combination with RFGC, through which reaction rate constants were calculated, showed that the distinction
of the phases of the AXAZ-1 cell cycle with the GrFFF presented
similar times to the distinction of alcoholic fermentation phases
conducted with the RFGC technique.
Moreover, by the combination of the previously mentioned
techniques (GrFFF and RFGC) with HPLC (16, 110), through
which sugar consumption was determined, the maximal fermentation rates and the time of maximal populations were
determined, which appeared in the growth phase. Finally, the
application of both GrFFF and RFGC techniques in combination
with HPLC led to the determination of the ideal experimental
conditions (temperature and pH) for alcoholic fermentation
with AXAZ-1.
Advantages of RFGC
A detailed kinetic study of alcoholic fermentation in a factory,
following the various steps that lead to the final product, may
provide valuable information about the mechanism of the
whole process. This could help to reduce the total time of the
process, thus lowering the cost of the ethanol produced. A
mechanistic study of this kind cannot be based on conventional
methods of chemical analysis, like distillation or traditional GC,
because these methods may alter the composition of samples
taken at intermediate times, which will lead to erroneous
conclusions regarding the mechanism. Two possible sources of
error are the relatively high temperature used in the analysis
and the effects of the filling materials used to pack the chromatographic columns on the analysis mixture. The RFGC technique does not suffer from these two sources of error and can
be used for the present purposes. It is a flow perturbation
method that has been reviewed (61, 111) and described in
more detail in two books (63, 112).
Moreover, although conventional GC with FID or MS detection has repeatedly been used for measuring both ethanol concentration and by-products during the fermentation process,
RFGC can successfully be applied for the determination of not
only the ethanol concentration, but also of physicochemical
quantities such as reaction rate constants and activation energies related to the kinetics of each phase of the alcoholic fermentation. This will lead to substantial information referring to
the evaluation of the catalytic activity of biocatalysts.
Advantages of GrFFF
GrFFF is a simple, accurate and low-cost technique, with the
ability to monitor the proliferation of Saccharomyces cerevisiae cells through their elution profiles. As it has been demonstrated (107), differences in the elution curves and peak
profiles during fermentation can be related to the different cell
growth stages.
New Approaches to the Kinetic Study of Alcoholic Fermentation by Chromatographic Techniques 775
Because the GrFFF technique has a significant number of
applications on yeast cells, it has also proved to be a useful tool
for the study of the effects of experimental conditions ( pH and
temperature) on AXAZ-1 growth kinetics.
GrFFF is suitable to determine the variation of the size distribution of a cell. In combination with other analytical techniques, such as RFGC and HPLC, useful information can be
drawn for the monitoring of Saccharomyces cerevisiae
(AXAZ-1) cell proliferation and the kinetic parameters during
alcoholic fermentation.
Conclusions
The present work gives a broad overview of the methodologies
used for the kinetic study of alcoholic fermentation. The increasing interest in the industrial applications of alcoholic fermentation has led to the employment of various kinetic models
for cells suspended in batch or continuous operations.
Parameters such as maximum specific growth rate, biomass
concentration, fermentation and substrate uptake and dilution
rate, have been measured for steady-state fermentation. For
many batch processes, it is very important to define the
optimum conditions to achieve sufficient profitability. For this
reason, experiments have been conducted with specific kinetic
models testing pH and temperature conditions, initial glucose
concentrations of culture medium, the growth of yeast cells,
ethanol production and many other parameters. The development of appropriate mathematical models can be considered a
good approximation for describing the cell growth cycle and
the kinetics of fermentation.
In recent years, intensive studies have been conducted
regarding the kinetic study of alcoholic fermentation by chromatographic techniques. Conventional GC and HPLC have
been extensively used for ethanol concentration and sugar
uptake. The composition and content of odor compounds that
determine the quality of alcoholic products have been characterized by GC –MS–O. Distilled alcoholic beverages, wines and
beers, are often characterized by GC or GC– MS analysis of fatty
acids and their esters, which contribute to the taste and quality
of these commodities.
Specific attention is also placed on some new approaches for
the kinetic study of alcoholic fermentation. The review presents RFGC, a simple and precise technique, which leads with
great accuracy to the determination of reaction rate constants
and activation energies at each phase of the alcoholic fermentation process, characterizing the catalytic activity of yeast
cells. Moreover, GrFFF has been applied for the characterization of yeast cells and the study of the viability and activity of
Saccharomyces cerevisiae strains during wine fermentation.
Differences in the elution curves and peak profiles during fermentation can be related to the different cell growth stages.
The combination of RFGC and GrFFF with other chromatographic techniques can provide valuable information about
ethanol fermentation, growth cycles of yeast cells, sugar consumption and other parameters of vital important for the continuous fermentation process.
Although many chromatographic techniques and appropriate
mathematical models have been used for the kinetic study of
alcoholic fermentation, there is still need for improvement in
776 Lainioti and Karaiskakis
recognizable techniques. Further research is still required for
the optimization of functional parameters that are very important, considering the possibility of implementing new approaches
for the kinetic study of the fermentation processes into industrial
practice.
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