Kinetics of spontaneous wine production

Kinetics of spontaneous wine production M. Ozilgen, M. ~elik and T. F. Bozoglu Food Engineering Department, Middle East Technical University, Ankara, Turkey

Sabstrate eonsnmption, ethanol production, microbial growth, and temperature increase in a fermentation vessel are metabolically interrelated biological phenomena. In spontaneous wine J~'rmentations, mixed cultures of various microbial species are involved in the fermentation process. Due to the continuously changing species eontribttting to the mierobial popnhttion, these metabolically interrelated parameters are treated separately in the enology literature. In the present stttdy, mathematical models are presented to interrelate these parameters, by employing the data obtainedJ?om a totally ,neontrolled spontaneous wine production process. Ethanol prodttction rates were rehtted to biomass production with a modified L,edeking-Piret equation. In the ethanol production phase of the process, total microbial growth did not slow down with ethanol aceam,lation. This might be cansed by the compensating effects of temperat,re increase. Ethanol prodttction yield of the cult,re increased with ethanol aceamalation in the medium, possibly due to elimination of the low-alcohol-talerant, poor alcoholproducing species. Microbial growth was simtdated with the logistic eqaation in the malo-lactie .[ermentation phase.

Keywords:Spontaneous fermentation; mixed culture: kinetics Introduction The wine production process can be analyzed in two phases: alcoholic fermentation and m a l o - l a c t i c fermentation. During the alcoholic fermentation process, wine microorganisms c o n s u m e the fermentable sugars and produce ethanol. A spontaneous wine production process is actually a mixed-culture and multiproduct process, c o m m e n c e d by the natural microorganisms of the grapes. Natural grape microorganism consists of various genera of molds (Monilia, Mucor, Penieillium, Aspergillus, Rhizopus, Botrytis, etc.), yeasts (Saecharomyces, Debaromyees, Torulopsis, Candida, Pichia, etc.) and lactic acid and acetic acid bacteria.~-3 Generally, wine yeast, Saccharomyces cerevisiae, is extremely low in population on the grapes. In the winemaking process, the wine yeasts multiply with a strong fermentative capacity, excluding most of the other microorganisms from the broth, and eventually invade the raw grape juice. 2 During the first hours of fermentation, low levels of yeasts of the genera Rhodotorula, Pichia, Candida, and Metschnikowia were reported to

Address reprint requests to Prof. Mustafa Ozilgen at the Food Engineering Department, Middle East Technical University, 06531 Ankara, Turkey Received 15 February 1990; revised 5 July 1990

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be present in red Bordeaux wines. 3 These yeasts were reported to die with c o m m e n c e m e n t of alcoholic fermentation. Torulopsis stellata, Saccharomyces eereuisiae, and Kloeekera apiculata (Hansenula uvarum) proliferated in these wines to conduct alcoholic fermentation. K. apiculata and T. stellata were reported to die during the course of the alcoholic fermentation, and the wines were eventually dominated by Saccharomyces cerevisiae. 3 Wine fermentations are indeed multiproduct fermentations. Biochemical aspects of wine fermentations are very complex and involve a very large n u m b e r of fermentation products, as recently reviewed by LafonLafourcade. 2 Some of the molds are aerobic and induce a weak alcoholic fermentation. ~ Certain yeast species, such as Kloeekera apiculata and Torulopsis stellata, may produce large amounts of volatile acids. 4 Acetate and glycerol may also be produced at the expense of the ethanol yield." Consumption of the fermentable sugars for production of c o m p o u n d s other than alcohol reduces ethanol production. Although numerous combinations of microbial species are involved in the alcoholic fermentations, generally more alcohol-tolerant microorganisms dominate the culture eventually. More alcohol-tolerant microorganisms are usually better ethanol producers than the disappearing microorganisms. Therefore, ethanol production efficiency of the culture should increase with ethanol accumulation. © 1991

Butterworth-Heinemann

Kinetics of spontaneous wine production: M. Ozilgen et al. Biological reasons for ethanol inhibition have been studied substantially. Ethanol accumulation in the fermenters was reported to inhibit various metabolic activities, including specific growth rate, specific ethanol production rate, cell viability, and substrate consumption. 5-s At high ethanol concentrations, ethanol accumulates in the cells and kills them. 6 Ethanol stress changes the lipid composition of the plasma membranes of the yeasts and also inhibits maltose and glucose transport across the plasma membrane. 9-j~ After completion of the alcoholic fermentation, malo-lactic fermentation starts in wine. During malo-lactic fermentation, lactic acid bacteria use malic acid as a substrate to produce lactic acid. Due to decarboxylation of malic acid, the acidity of the wine slightly decreases and its pH value increases. ~2Various strains of Leuconostoc, Pediococcus, and Lactobacillus are involved in the maio-lactic fermentation. ~~3j4 Although different trends may be observed with different wines, at the end of the malo-lactic fermentation the maximum biomass concentration of the lactic acid microorganisms may reach the same level as the maximum biomass concentration attained in the alcoholic fermentation. L~ There are very few studies concerning mathematical modeling of wine fermentations. ~'-~ These studies are concerned mainly with pure culture fermentations with S. cerevisiae. Some of these studies were made with extremely limited experimental data. I6"lv Microbial growth, substrate utilization, ethanol production, and temperature increase are metabolically related biological changes occurring during wine fermentation; i.e. substrate is consumed in the energy metabolism, the major end-product of the energy metabolism under anaerobic conditions is ethanol, heat is released as the by-product of the energy metabolism, and the energy is used to produce new cells. Due to the continuously changing microbial species of the mixed culture, these metabolically related changes are treated mostly as separate parameters in the enology literature. In the present study, kinetic models are sought to relate these parameters.

sugar concentrations were followed with the L a n e - E y non general volumetric method, j9 Temperature was measured with an ordinary laboratory thermometer. The pH values were measured with a pH meter (Corning, Model 10, England).

Results and discussion Since the wine-making process involves different phases, the results of each phase are discussed separately. Alcoholic fermentation process

Growth of the biomass was simulated in three phases: (i) Exponential growth (ii) Stationary phase (iii) Death phase

The process of making white wine was followed in one of the local wineries. Grapes from Thrace and Central Anatolia were crushed, and their seeds and skins were separated. Fermentation was done in rectangular concrete fermentation vessels with no microbial inoculation and with no temperature or other means of control. About 20,000 L of wine was produced in each of these fermentation vessels during any of the experiments. There were no agitators in the fermentation vessels, but release of CO 2 supplied considerable agitation. Biomass concentration was followed at 650 nm, after clearing the broth from the suspended solids and using the centrifuged fermentation broth as a blank, with a spectrophotometer (Shimadzu, UV-120-02, Japan). Ethanol concentration was followed with an ebulliometer (Salleron and Dujaroins, No 45748, France). Reducing

(1)

dX d~- = 0

(2)

dX dt -

kX

(3)

Total biomass concentration, denoted by X, was actually a mixed culture, and the microbial species contributing to X were changing in time. Exponential growth prevailed until the beginning of the stationary phase with no apparent ethanol inhibition. This result might have been caused by the temperature increase. The temperature increase could enhance growth to compensate for the negative effect of the product inhibition; thus, a constant value was observed for parameter/.L. The stationary growth phase, as described by equation (2), started after depletion of the fermentable sugars and took about 15 h. Yeast cells formed flocks and precipitated towards the end of the alcoholic fermentation process. Equation (3) actually represents the disappearance rate of the yeasts from the medium via settling. The Luedeking-Piret equation is one of the most common product formation models: dP

Materials and methods

dX ~- = #X

J--7 =

~X +

dX

/3 ~ -

(4)

The Luedeking-Piret equation was originally used to simulate lactic acid production by Lactobacillus delbrueckii. 2° It was later used to simulate other processes, i.e., xanthan gum 2j and amino acid production. 22 Equation (4) was valid for pure culture fermentations only. The parameters ~ and/3 were constants. The term ~X simulated the non-growth-associated product formation rate, i.e. product formation by the cells when they were not growing. The term /3(dX/dt) shows the growth-associated product formation rate, i.e. additional product formation when the cells were growing. In spontaneous wine fermentations, as the process proceeds, alcohol-sensitive microorganisms are inhibited and the alcohol-tolerant microorganisms dominate the culture. Alcohol-tolerant microorganisms are generally better alcohol producers. With the elimination of

Enzyme Microb. Technol., 1991, vol. 13, March

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F i g u r e 1 C o u r s e o f f e r m e n t a t i o n w i t h fast f e r m e n t e d wine. Exp e r i m e n t a l data are s h o w n in s y m b o l s : (©) pH; ( I ) t e m p e r a t u r e ; (O) r e d u c i n g s u g a r s ; (&) e t h a n o l ; (X) b i o m a s s . S i m u l a t i o n s are s h o w n with solid lines ( ). N u m e r i c a l v a l u e s o f the m o d e l p a r a m e t e r s are: /x - 0.024 h 1; k - 0.039 h 1; ~ 0.0045% ethanol/OD650 h;/3 = 3.6 + 0,15 P + 0.086 p2 % ethanol/OD650; Yx = 14.3 OD650/% r e d u c i n g sugars; Yp - 0.54% e t h a n o l / % r e d u c i n g sugars;Kl=O.OO48h-1;K2=O.17°Ch 1;/x m 0 . 1 1 5 h 1;Xma × = 1.24 OD650

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2 C o u r s e o f f e r m e n t a t i o n with the s l o w f e r m e n t e d w i n e . E x p e r i m e n t a l data are s h o w n in the s a m e s y m b o l s as in Figure 1. N u m e r i c a l v a l u e s o f the m o d e l p a r a m e t e r s a r e : / x = 0.006 h 1; k 0.042 h - l ; c< = 0.0045% ethanol/ODss0 h;/3 = 3,6 + 1 . 2 5 P + 0.004 p2% ethanol/OD650; Yx 0.04 OD~so/% r e d u c i n g s u g a r s ; Yp 10% e t h a n o l / % r e d u c i n g s u g a r s ; K 1 - 0.004 h 1; K2 = 0.08 ° C h 1;/xm = 0.032 h 1; Xmax = 1,08OD65 o

duction. All the reducing sugars were consumed before the beginning of the stationary phase. the lower alcohol-producing species, the alcohol production yield of the culture increases; thus, parameter /3 might be related to the ethanol concentration in the medium: B = B0 + /3l P + B2P2

(5)

Equation (5) is an arbitrarily suggested polynomial function, with constants/30,/31 , and/32. The numerical values of parameters /3o, /3~, and /32 depend on the microorganisms contributing to the total population. In pure cultures where ethanol yield of the microorganisms is constant, only parameter/30 may simulate the ethanol production yield. Parameters/3~ and/32 introduce the effect of the ethanol concentration on the ethanol production rates. Analysis of the experimental data indicated that nongrowth-associated ethanol formation rates, i.e., ~X, were substantially smaller than the growth-associated ethanol formation rates; therefore, variation of parameter a with ethanol concentration was neglected. Experimental data indicated that no ethanol was produced after the end of the exponential growth phase. The slight decrease in ethanol concentration in the other growth phases might be attributed to ethanol loss via evaporation. Substrate utilization in the exponential growth phase was:

dS dt

-

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+

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The logistic equation has been used in various studies, i.e. xanthan fermentationzj and amino acid production. 2~The equation was used to simulate growth of the biomass during malo-lactic fermentation: -/zMX

1-

(7)

Lactic acid bacteria were the major species contributing to the total biomass concentration X. The term /,MX simulates exponential growth when parameter X is much smaller than its maximum attainable value Xm,×. Microbial growth stops when lactic acid concentration reaches a certain level in the medium. Parameter Xm~X is the biomass concentration attained at this level of the lactic acid concentration. The term (1 - X/Xm.,O introduces the inhibitory effects of the fermentation products, i.e. lactic acid, on the growth rate of the biomass. A slight increase was observed in the pH value of the wines during the malo-lactic fermentation (Figures 1 and 2).

T e m p e r a t u r e changes in the f e r m e n t a t i o n uessel Temperature changes in the fermentation vessel were modeled after making a thermal energy balance:

(6)

The term (l/Yx) (dX/dt) simulated reducing sugar utilization for biomass production, and the term (1 / Yp) (dP/ dt) simulated reducing sugar utilization for ethanol pro-

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Malo-lactic fermentation

Enzyme Microb. Technol., 1991, vol. 13, March

- 2 U g A ; ( T - Tenv) + V d X _ d(pCVT) i: I Y~,~ dt dt

(8)

where the term - ~] UiA i (T - Te.v) represents the eni=l

Kinetics of spontaneous wine production: M. Ozilgen et al. ergy loss from the fermenter surfaces, and the term (V/Yc,O (dX/dt) represents the thermal energy generation with microbial growth. This term was zero after the end of the exponential growth in the alcoholic fermentation. The term d(pCVT)/dI was the thermal energy accumulation. Equation (8) was rearranged after substituting equation (I) for dX/dt:

dT dt

m

Kl(Te. v - T) + K2e~'

=

(9)

The numerical value of parameter K 2 w a s zero after the end of the exponential growth phase of the alcoholic fermentation. Different microorganisms and different metabolic pathways involve into the alcoholic and malo-lactic fermentation processes.The experimental results implied that the thermal energy released in the malo-lactic fermentation process was negligible. Variation of the biomass concentration was simulated with equations (1-3) and (7). Ethanol production was simulated with equation (4), after substituting equation (5) for/3. Reducing sugar depletion and temperature variations were simulated with equations (6) and (9), respectively, These equations were solved numerically with 1-h time increments, after substituting the appropriate numerical values for the constants. Simulations are compared with the experimental data in Fi.~ures I and 2. Numerical values of the model constants are given in the figure legends. Using a polynomial function for ethanol concentration, given in equation (5), helped in simulation of the data. With pure culture studies, in the exponential growth phase, using a constant value for/3, i.e. /3 = /3o, gives from equations (4) and (1):

dP dt

-

6_

dX

(1o)

den's classifications. If the wine yeast should start dominating the culture after a few days of delay (as in Figure 2), numerical values of parameter ,8~ should be much higher in comparison with the numerical values of parameter/32. If the wine yeast should dominate the culture in the late exponential phase, a higher numerical value for parameter/32 should simulate the data. The numerical values of the parameters Yx and Ye depend on the variations of the competing microorganisms in the microbial population. A large value of Yx combined with a small value of Yp (as in Figure 1) may imply that substrate consumption was related more with ethanol production. A small value of Y, and large value of Yt, (as in Figure 2) may imply that substrate consumption was related more with biomass production.

Conclusions Simple mathematical models were presented for simulating microbial growth, reducing sugar utilization, ethanol production, and temperature increase in a spontaneous wine-making process. Although it was not possible to monitor variation of the individual microbial species contributing to the total microbial population, variation of the numerical values of the model parameters contributed to a better understanding of the relations of these microorganisms with each other and a better understanding of the contribution of these species to the individual steps of the wine-making process.

Acknowledgements We received substantial help from Mrs. Esen Ozkan and Mrs. G~ing6r Bayram during the initial stages of this study.

where (3(

4' = - +/3o

(1 !)

Nomenclature AI

Equation (10) represents Type I fermentation in Gaden's classification. 23 In Gaden's classifications, Type I fermentations are defined as the processes in which the product is the direct result of the energy metabolism. Ethanol fermentations are a typical textbook example of Type I fermentations, 23 Due to the mixed culture nature of the spontaneous wine fermentations, parameter 4' of equation (10) was modified and expressed as a function of ethanol concentration:

k KI

(Kj = 2 UiAi/pC V) i-I

K2

(12)

Numerical values of parameters/30,/31, and/32 depend on the time when the wine yeast dominates the culture. In pure culture fermentations, when the inoculum wine yeast takes over the culture at the beginning of the process, the numerical values of the parameters/3~ and /32 become zero, and the overall fermentation pattern becomes the same as the Type I fermentations in Ga-

constant in Equation 9. (K2 --

tz Xo/ Yc.,,lpC V) n

oc

4' = -- + /3o + ,Sf P + /~2 P2 /z

C

area of the ith surl:ace of the fermentation vessel (m 2) specific heat of the fermentation broth (kcal kg-I oC i) specific death rate (h-1) constant in equation (9)

P S t tM T T~°v

number of the surfaces in the fermentation vessel ethanol concentration (%) reducing sugars concentration (%) time (h) time after the commencement of malo-lactic fermentation (h) temperature of the fermentation vessel (°C) effective temperature outside the

Enzyme Microb. Technol., 1991, vol. 13, March

255

Papers fermentation vessel (°C) overall heat transfer coefficient for the ith wall of the fermentation vessel (kcal °C l m " h-I) volume of the fermentation vessel

Ui V

( m 3)

metabolic heat generation yield of the microorganisms (OD650 kcal-l) amount of increase in ethanol concentration (%) for each unit of reducing sugar concentration used

Ycal

(%)

amount of increase in biomass concentration (OD65o) for each unit of reducing sugar concentration (%) used total concentration of the mixed species of the microorganisms (biomass) in the fermentation room (OD65o) maximum value of parameter X attained at the end of the malo-lactic fermentation (OD65o) value of parameter X at the beginning of the alcoholic fermentation

X

Xm.x xo

References 1

2 3 4 5 6 7 8 9 10 11 12 13 14

(OD650)

/3

/30,/3,,/32 4' /x /xM

256

constant in equation (4) [ethanol produced (%) by unit biomass present in the culture (OD650) in unit time (h)] constant in equation (4) [ethanol produced (%) per unit biomass produced (OD650)] constants in equation (5) constant specific growth rate (h-~) specific growth rate in malo-lactic fermentation (h ~) density of the fermentation broth (kg m 3)

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15 16 17 18 19 20 21 22 23

Amerine, M. A., Berg, H. W., Kunkee, R. E., Ough, C. S., Singleton, V. L. and Webb, A. D. The Technology o f Wine Making, 4th ed. Avi. Pub. Co., Westport, Connecticut, 1980, pp. 154-185 Lafon-Lafourcade, S. in Biotechnology (Reed, G., ed.) VerlagChemie, FRG, 1983, pp. 81-163 Fleet, G. H., Lafon-Lafourcade, S. and Ribereau-Gayon, P. AppI. Env. Microbiol. 1984, 40, 1034-1038 Benda, I. in Industrial Microbiology, 4th ed. (Reed, G., ed.) Avi Pub. Co., Westport, Connecticut, 1982, pp. 293-402 Ghose, T. K. and Tyagi, R. D. Biotechnol. Bioeng. 1979, 21, 1401-1420 Novak, M., Strethiano, P. and Moreno, M. Biotechnol. Bioeng. 1981, 23, 201-211 Lourerio, V. and van Uden, N. Biotechnol. Bioeng. 1982, 24, 1881-1884 Leao, C. and van Uden, N. Biotechnol. Bioeng. 1982, 24, 1581-1590 Beaven, M. J., Charpentier, C. and Rose, A. H. J. Gen. Microbiol. 1982, 128, 1447-1455 Thomas, D. S., Hossack, J. A. and Rose, A. H. Arch. Microbiol. 1978, 117, 239-245 Thomas, D. S. and Rose, A. H. Arch. Microbiol. 1979, 122, 49-55 Kunkee, R. E. in Chemisto, ofWinernaking ACS, USA, 1974, pp. 151-170 Wibowo, D., Eschenbruch, R., Davis, C. R., Fleet, G. H. and Lee, T. H. Am. J. Enol. Vitic. 1985, 36, 302-313 Costello, P. J., Morisson, G. J., Lee, T. H. and Fleet, G. H. Food Technol. Australia 1983, 35, 14-18 Davis, C. R., Wibowo, D., Eschenbruch, R., Lee, T. H. and Fleet, G. H. Am. J. Enol. Vitic 1985, 36, 290-301 Boulton, R. Biotech. Bioeng. Syrup. 1979, 9, 167-177 Boulton, R. Am. J. Enol. Vitic. 1980, 31, 40-45 El Haloui, N. R., Corrieu, G., Cleran, Y. and Cheruy, A. J. Ferm. Bioeng. 1989, 68, 131-135 Official Methods o f Analysis, 1lth ed. Association of Official Analytical Chemists, Washington, DC, 1970, pp. 537,937,938 Luedeking, R. and Piret, E. L. J. Biochem. Microb. Tech. Eng. 1959, 1,393-412 Weiss, R. M. and Ollis, D. F. Biotechnol. Bioeng. 1980, 22, 859-873 Ozilgen, M. Enzyme Microb. Te('hnol. 1988, 10, 1 I0-114 Bailey, J. E. and Ollis, D. F. Biochemical Engineering Fundamentals McGraw-Hill Book Co., New York, 1977, pp. 371-375