Monitoring of lactic acid fermentation in culture broth using ultrasonic velocity

Monitoring of lactic acid fermentation in culture broth using ultrasonic velocity

Journal of Food Engineering 78 (2007) 1083–1091 www.elsevier.com/locate/jfoodeng Monitoring of lactic acid fermentation in culture broth using ultras...

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Journal of Food Engineering 78 (2007) 1083–1091 www.elsevier.com/locate/jfoodeng

Monitoring of lactic acid fermentation in culture broth using ultrasonic velocity Pablo Resa a b

a,*

, Toma´s Bolumar b,1, Luis Elvira a, Gaspar Pe´rez b, Francisco Montero de Espinosa a

Departamento de Sen˜ales, Sistemas y Tecnologı´as Ultraso´nicos, Instituto de Acu´stica (CSIC), c/. Serrano 144, 28006 Madrid, Spain Laboratorio de Bacterias La´cticas, Instituto de Agroquı´mica y Tecnologı´a de Alimentos (CSIC), 46100 Burjassot (Valencia), Spain Received 24 June 2005; accepted 19 December 2005 Available online 14 February 2006

Abstract The fermentations of several carbohydrates (glucose, galactose and lactose) have been monitored measuring ultrasonic velocity during the growth of Lactobacillus casei in basal MRS media. Under the conditions used, this microorganism is basically homofermentative and sugars are predominantly transformed into lactic acid. A remarkable correlation was found between the ultrasonic velocity and the bacterial catabolism. These results could be used to model changes occurring during lactic acid fermentations and show the great potential of this non-invasive technique for monitoring biotechnological processes.  2006 Elsevier Ltd. All rights reserved. Keywords: Fermentation; Ultrasound; Monitoring; Lactic acid; Lactose

1. Introduction Lactic acid bacteria (LAB) are widely used in the food industry to manufacture several fermented foods such as dairy, meat or diverse vegetable products. Their fermentative metabolism restricts them to use the glycolytic intermediates as proton acceptors, therefore, they convert sugars (e.g. glucose, galactose and lactose) to organic acids, mostly lactic acid (Liu, 2003). LAB are classified according to the availability of specific pathways to metabolise carbohydrates. Homofermentative bacteria generate two moles of lactic acid per mole of glucose; and heterofermentive bacteria produce equimolar amounts of lactic acid, carbon dioxide and ethanol (Caplice & Fitzgerald, 1999). However, there is still another group of facultative heterofermentative LAB, which can use either pathway depending *

Corresponding author. Tel.: +34 91 561 88 06; fax: +34 91 411 76 51. E-mail addresses: [email protected] (P. Resa), [email protected] csic.es (T. Bolumar). 1 Tel.: +34 96 390 00 22. 0260-8774/$ - see front matter  2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.jfoodeng.2005.12.021

on the type of sugar available. The microorganism used in this work, Lactobacillus casei, belongs to the latter group and normally carries out a homolactic fermentation from hexoses and lactose under anaerobic or microaerophilic conditions. Lactic acid is used in chemical, food, cosmetic, textile and pharmaceutical industries as an acidifier, preservative, green solvent, for the production of emulsifying agents and, recently, for the synthesis of biodegradable polymers for medical applications (Oh et al., 2005). Industrial production of lactic acid is based on the fermentation of molasses and low-cost carbon sources; however, a rising number of works are focussing on the economical production of lactic acid from lactose-rich dairy residues, such as whey permeate (Amrane, 2005; Cristiani-Urbina et al., 2000; Sethuran, Sethuran, Hatti-Kaul, & Mattiasson, 1999). The lactic acid growth is a very complex process for which an efficient monitoring is required. Nowadays, efficient data acquisition systems for physicochemical parameters are commonly used and, for example, accurate

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miniaturised sensors have been developed for the in situ measurement of pH and pO2 (Schu¨gerl, 2001). Fast analysis devices, or systems, would be highly desirable as they would allow an on-line response to the changes in media components. However, most on-line systems currently used have a low accuracy. On this background, ultrasound is becoming a promising technique for the on-line monitoring of chemical reactions and biological processes. Most important features of ultrasonic systems are robustness, non-invasiveness, precision, low cost, rapidity and easy automation. Furthermore, ultrasound can be used to analyse opaque materials, offering an alternative to electromagnetic waves based devices. Recently, on-line ultrasonic techniques have been used for monitoring alcoholic fermentations (Becker, Mitzscherling, & Delgado, 2001, 2002; Resa, Elvira, & Montero de Espinosa, 2004b), dairy fermentations (Elvira, Resa, & Espinosa, 2002) and dough fermentations (Elmehdi, Page, & Scanlon, 2003). Nevertheless, this technique is very sensitive to physical parameters such as temperature, pressure or particle size, which may sometimes be a disadvantage. The main objective of this work was to find a relationship between ultrasonic velocity propagation and the biochemical changes occurring during lactic acid fermentation in liquid media. Measurements of ultrasonic velocity in the binary mixtures water–glucose, water–galactose, water–lactose and water–lactic acid have been carried out and used to understand ultrasonic velocity changes. The suitability of the ultrasonic measurement technique for monitoring biotechnological processes is also discussed. 2. Theory 2.1. Homofermentation L. casei produces lactic acid as the major end-product in sugar fermentation under the experimental conditions employed. Glucose is metabolised via the glycolytic pathway, galactose via the tagatose 6-phosphate pathway and the disaccharide lactose previously undergoes a cleavage to galactose and glucose (De Vos & Vaughan, 1994; Kandler, 1983). Eventually, the simplified fermentation reactions can be expressed as C6 H12 O6 ! 2C3 H6 O3 glucose

ð1Þ

lactate

C6 H12 O6 ! 2C3 H6 O3 galactose

ð2Þ

lactate

C12 H22 O11 þ H2 O ! 4C3 H6 O3 lactose

water

ð3Þ

lactate

and for the lactose metabolism,

 0  water wlactose  wlactose wwater ¼ w0water  MMlactose  0  M lactate wlactose  wlactose wlactate ¼ 4 M lactose

ð4Þ

ð5Þ

Superscript 0 refers to the beginning of the fermentation and M represents the molar mass. In these equations, wglucose and wlactose have been chosen as the independent variables. 2.2. Ultrasonic velocity in liquid mixtures In a liquid, the longitudinal phase velocity, c, may be expressed as   oP 1 c2 ¼ ð6Þ ¼ oq S jS q Here, P is the pressure, S stands for the entropy,   1 oV jS ¼  V oP S

ð7Þ

is the adiabatic compressibility, q¼

M V

ð8Þ

is the density, V is the molar volume and M is the molar weight. It is assumed that the propagation of elastic waves is adiabatic and reversible. Many approaches have been proposed for expressing the ultrasonic velocity as a function of the properties of the pure components in liquid mixtures. Urick (1947) proposed a linear dependence of density and compressibility with the volume concentration of suspended particles. Burton (1948) measured propagation parameters in several liquid mixtures and discussed results from the point of view of molecular associations. Danusso (1951) arrived to the Urick’s equation by another path. Nutsch-Kuhnkies (1965) proposed the well-known Free Length Theory based on the collision factor and on the space filling factor for organic liquids. Many other attempts have been made to calculate the sound velocity in binary mixtures. Further explanations can be found in the literature (Douhe´ret, Davis, Reis, & Blandamer, 2001; Sette, 1961). Nevertheless none of these expressions has shown to be valid for every liquid mixtures. In this work, we have considered the semi-empirical model proposed by Resa et al. (2004b). At low concentration and for small changes, we assume that the ultrasonic velocity, c123, in a ternary mixture 1–2–3 can be expressed as Dc123 ðDw2 ; Dw3 Þ ¼ Dc12 ðDw2 Þ þ Dc13 ðDw3 Þ

The relations between the mass concentrations, wi, are deduced from these fermentation reactions. For the glucose (and galactose) metabolism, we have wlactate ¼ w0glucose  wglucose

(

ð9Þ

where c12 and c13 represent the ultrasonic velocity in the corresponding binary mixtures, which have been experimentally obtained. Subscript 1 represents the solvent, whilst w2 and w3 stand for the mass concentration of solutes. It can be noticed that, in this equation, the interaction between solutes is not taken into account. The advantage

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of this approach is that the ultrasonic velocity in a ternary mixture can be easily obtained from the measurements of the binary mixtures.

this tube. A pH probe was also introduced through the bottle plug to monitor on-line the lactic acid production (Fig. 1).

3. Materials and methods

3.4. Ultrasonic velocity

3.1. Binary mixtures

The method for the determination of the ultrasonic velocity was described in a previous paper (Resa et al., 2004b). Ultrasonic velocity was measured using a toneburst pulse through-transmission technique. Two transducers were attached face to face at the outer sides of the glass bottle and coupled to it with a silicone layer, one for emitting the ultrasonic pulse and the other transducer for receiving it after travelling through the medium. Both transducers were identically made of a PZT 5A piezoelectric ceramic, bonded to a Plexiglas plate. Araldite D was used as backing. The emitting transducer was excited at its resonant frequency, around 2 MHz, using an Agilent 33250A pulse generator. Received signals were acquired using a Tektronix TDS 220 digital oscilloscope and, via a general purpose interface bus (GPIB), stored in a computer. The signals were analysed using a fast Fourier transform (FFT) algorithm to obtain the time of flight, s, which is the time taken by the ultrasonic pulse to travel through the sample. Time of flight variations, Ds, are proportional to the FFT signal phase variations, Du:

The solutes used to make the binary mixtures were distilled water, D(+)-galactose (purity >99%, Boehringer Ingelheim Bioproducts Partnership, Heidelberg, Germany), D(+)-glucose (purity >99%, Panreac, Barcelone, Spain), L(+)-lactic acid (purity >99%, Sigma Aldrich Chemie, Steinheim, Germany) and lactose 1-hydrate (purity >98%, Panreac, Barcelone, Spain). The uncertainty of mass concentrations was estimated to be approximately ±0.05%. Components were weighed using a Sartorius 1216 MP digital balance with a ±0.1 g precision. Discrete amounts of solute were gradually added to distilled water and stirred until complete dissolution (i.e. when sound parameters remained constant). Then, ultrasonic velocity was acquired using the technique described below. 3.2. Lactic acid fermentations The culture media was composed by a MRS basal medium supplemented with 0.5% (w/v) of the appropriate sugar, at 37 C under static conditions (Veyrat, Monedero, & Perez-Martinez, 1994) supplemented with sugar at 2% (p/V). Basal MRS culture broth was sterilised at 121 C for 20 min. Sugar (glucose, galactose or lactose) was sterilised using 0.2 lm pore size filters (Sarstedt, Nu¨mbrecht, Germany) and added to the basal MRS broth in aseptic conditions. A Teflon stirrer bar was also introduced into the medium to get proper shaking during the fermentation (see Fig. 1), and therefore, assured good homogenisation. The LAB strain used was L. casei CECT 5275. A preculture to prepare inoculum was grown in MRS fermenting broth (Scharlau Chemie S.A., Barcelona, Spain) supplemented with lactose at 2% (wt:vol) and incubated overnight at 37 C. Cells were harvest, centrifuging at 4000 rpm for 10 min, washed with distilled water, and then re-suspended in distilled water. Fermentation was started after inoculating at 0.05 absorbency units the cited strain into the described medium. Fermentations were carried out in square glass 250-ml bottles.

Ds ¼ 

Du 2pf

ð10Þ

The ultrasonic velocity, c, in the medium was calculated dividing the distance, d, travelled by the wave through the liquid, corresponding to the inner diameter of the bottle, and the time of flight: c¼

d c0 ¼ s0 þ Ds 1 þ c0dDs

ð11Þ

where c0 is the initial velocity. The changes in the speed of sound uncertainty was estimated to be smaller than ±0.08 m/s. 3.5. Liquid density determination The density of the fermentation medium was determined using an Anton Paar DMA 35 tube densimeter with an accuracy of ±1 kg/m3.

3.3. Experimental cell 3.6. Continuous monitoring of pH The fermentation medium was placed in a square glass bottle with a 57.8 mm inner side, which was immersed in a thermostatic water bath at 37.00 ± 0.01 C. It was constantly stirred with a magnetic stirrer to ensure its homogeneity. Periodical samples were taken through a tube inserted across the bottle plug. Atmospheric pressure was maintained without contamination with a 0.2 lm pore size syringe filter (Sarstedt, Nu¨mbrecht, Germany) at the end of

The pH was measured on-line during fermentation with a pH electrode (Metler Toledo, Greifensee, Switzerland) connected to a recorder-control unit, Biostat B (Sartorius Biotech, Melsungen, Germany). Averaged values were automatically acquired every half-hour by means of a PC interface. The accuracy was estimated to be ±0.01 pH units.

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Fig. 1. Experimental set-up.

3.7. Analysis

3.8. Cell density

Samples were carefully pumped out without perturbing the on-line measurements in order to determine the sugar and lactic acid concentrations, as well as the cell density. They were centrifuged at 10,000 rpm for 10 min and supernatant was immediately frozen till use. Lactose, glucose and galactose were determined using the method of dinitrosalicylic acid (DNSA) reagent (Miller, 1954). DNSA reagent consisted of 1% 3,5-DNSA, 30% sodium potassium tartrate and 0.4 M NaOH. Briefly, 0.25 ml samples were mixed with 0.25 ml of DNSA reagent and heated for 4 min in boiling water. Then, 4 ml of distilled water were added and the absorbance was measured at 550 nm. Lactic acid was determined using an enzymatic kit of Boehringer Mannheim (Darmstadt, Germany) according to the manufacturer’s instructions.

The number of bacteria per volume unit was deduced from measurements of the optical density at 550 nm with a spectrophotometer (Spectronic 20 D, Milton Roy Company, PA, USA). A standard curve (optical density vs. cell density) was drawn specific for L. casei and it was used to correlate both magnitudes. In order to study the effect of the bacterial cell concentration on the ultrasonic velocity, L. casei cells were grown in 2% lactose MRS medium, harvested, washed twice with sterile water and centrifuged to obtain the concentrated cell suspension. The cell density of this suspension was determined and aliquots were gradually added to water in the flask of the ultrasonic measuring device. Then, the speed of sound was obtained using the same technique employed for binary mixtures.

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4. Results and discussion

7.0

4.1. Influence of solute concentrations on ultrasound velocity

6.5 6.0 5.5

pH

The ultrasonic velocity in water–glucose, water–galactose, water–lactose and water–lactic acid binary mixtures was measured and represented as a function of the solute mass concentrations (Fig. 2). Solid lines are cubic interpolations of the experimental data. These results agree with previous measurements of the ultrasonic velocity in the water–lactose–lactic acid ternary mixtures at 30 C (Resa, Bolumar, Elvira, Pe´rez, & Montero de Espinosa, 2004a) and the sound velocity displayed in some monosaccharide-water binary mixtures (McClements, 1997). These data show that, at the same concentration, ultrasonic velocity in the carbohydrate mixtures grows faster than in the water–lactic acid mixture (Fig. 2). It is also interesting to note that the sound velocity in glucose, galactose and lactose solutions are moderately different. In order to determine the lactic acid concentrations during the fermentations from pH measurements, a calibration curve of pH as a function of lactate in basal MRS medium was obtained (Fig. 3). This curve is used to predict the lactate production in Figs. 5(b), 6(b), 7(c), and 8(c).

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5.0 4.5 4.0 3.5 3.0 0.0

0.5

1.0

1.5

2.0

2.5

Mass concentration of lactic acid (%) Fig. 3. Variation of pH as a function of lactate mass concentration in basal MRS medium.

1524.2

During bacterial fermentations, in addition to the consumption of nutrients and physicochemical changes, the number of bacterial cells normally grows. This can be quantified and may constitute a relevant parameter that increases several orders of magnitude during a given experiment. Changes on the speed of sound produced by suspensions of L. casei cells of known concentrations were measured in distilled water (Fig. 4). Data clearly showed

Ultrasonic velocity (m/s)

1524.1

4.2. Influence of bacterial cell concentration on ultrasound velocity

1524.0

1523.9

1523.8

1523.7

1523.6 0

5

10

15

20

25

30

35

9

Concentration of bacteria (10 /ml)

Fig. 4. Ultrasonic velocity in a suspension of L. casei in pure water, at T = 37 C and f = 2 MHz.

Ultrasonic velocity (m/s)

1600

a linear relationship between bacterial numbers and ultrasonic velocity. During laboratory experiments cell concentrations reach figures between 109 and 1010 cells/ml. In this work, fermentations had approximately 6 · 109 cells/ml (Figs. 7 and 8(b)), that would correspond to a low increase in ultrasonic velocity (0.1 m/s). This would mean that, in the order of the megahertz frequency used in this work, the incidence of bacterial growth is small.

1580

1560

1540

4.3. Monitoring of ultrasound velocity during sugar fermentations

1520

0

2

4

6

8

10

12

14

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18

20

Mass concentration (%)

Fig. 2. Ultrasonic velocity in the water–galactose ( ), water–glucose ( ), water–lactose ( ) and water–lactic acid ( ) binary mixtures, at T = 37 C and f = 2 MHz.

During the lactic acid fermentation, sugars are mostly transformed into lactic acid and, therefore, a decrease in the velocity would be expected from Eq. (9). Fig. 5(a) displays the ultrasonic velocity variation and the pH during

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P. Resa et al. / Journal of Food Engineering 78 (2007) 1083–1091 6.5

6.5 0.0

6.0

-0.4 5.5 -0.6

-1.0 4.5 -1.2 -1.4

4.0

6.0 -0.5 5.5

5.0

-1.0

pH

5.0

-0.8

Variation of ultrasonic velocity (m/s)

-0.2

pH

Variation of ultrasonic velocity (m/s)

0.0

4.5 -1.5 4.0

-1.6 3.5 0

5

10

a

15

20

25

30

3.5

-2.0

35

0

Time (h)

5

10

15

20

25

30

35

40

Time (h)

a 2.0

1.6

Mass concentration of lactic acid (%)

Mass concentration of lactic acid (%)

1.8

1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0

1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0

-0.2 0

b

1.8

5

10

15

20

25

30

35

-0.2

Time (h)

Fig. 5. (a) Ultrasonic velocity variation at f = 2 MHz ( ) and pH ( ) during the lactic acid fermentation of a modified basal MRS medium ðw0glucose ¼ 2%Þ by L. casei, at T = 37 C. (b) Lactic acid mass concentration calculated from ultrasonic velocity ( ) and pH ( ) measurements during the lactic acid fermentation showed in (a).

the lactic acid fermentation of a basal MRS medium with 2% glucose by L. casei. Both plots show a great similarity even though the pH falls earlier, possibly because of its logarithmic dependence. The fermentation had almost finished after 26 h (Fig. 5). At this point, a decrease of 1.3 m/s in the sound velocity and of 2.3 pH units had occurred. Density measurements changes, at the end of the fermentation, were not significant enough and thus it was not possible to use this parameter to monitor the lactic fermentation, nor to relate to ultrasonic velocity. Fig. 5(b) shows the lactic acid concentration calculated from pH measurements and from ultrasonic velocity changes. A notable similarity is observed. Therefore, it is possible to assert that the ultrasonic velocity changes during the glucose fermentation in basal MRS medium are mainly due to the transformation of sugar into lactate. Changes in ultrasonic velocity and pH were also monitored during L. casei growth in 2% galactose MRS medium (Fig. 6(a)). Fermentation of galactose-containing medium proceeded slower than glucose medium, as expected in a

0

b

5

10

15

20

25

30

35

40

Time (h)

Fig. 6. (a) Ultrasonic velocity variation at f = 2 MHz ( ) and pH ( ) during the lactic acid fermentation of a modified basal MRS medium ðw0galactose ¼ 2%Þ by L. casei, at T = 37 C. (b) Lactic acid mass concentration calculated from ultrasonic velocity ( ) and pH ( ) measurements during the lactic acid fermentation showed in (a).

microorganism where glucose is preferred (Veyrat et al., 1994; Viana, Monedero, Dossonnet, Pe´rez-Martı´nez, & Deutscher, 2000). However, a greater decrease of 1.7 m/s in the sound velocity was noticed in galactose medium, likely because the ultrasonic velocity in the water–galactose mixture was greater than in the water–glucose mixture (Fig. 2). Therefore, metabolisation of this sugar led to a greater fall in velocity. Fig. 6(b) shows the lactic acid concentration calculated from pH measurements and from ultrasonic velocity changes. Again, a noteworthy resemblance is observed. Consequently, the ultrasonic velocity changes during the galactose fermentation in basal MRS medium are mainly due to the transformation of sugar into lactate. Then, growth of L. casei in 2% lactose MRS was also assayed and changes of ultrasonic velocity, pH, lactose, lactic acid mass concentrations and cell density were measured (Fig. 7). Ultrasonic velocity decreased by 0.4 m/s; less than in monosaccharide fermentations as expected

P. Resa et al. / Journal of Food Engineering 78 (2007) 1083–1091 6.5

0.1

6.0

0.0 5.5 -0.1 5.0 -0.2

pH

Variation of ultrasonic velocity (m/s)

0.2

4.5 -0.3 4.0

-0.4

-0.5

3.5 0

5

10

15

20

25

30

35

Time (h)

a

7

2.5

4 1.0

3

2

0.5

9

Lactose mass concentration (%)

5 1.5

Concentration of bacteria (10 /ml)

6 2.0

1 0.0 0 0

5

10

15

b

20

25

30

35

Time (h)

Mass concentration of lactic acid (%)

2.0

effect is caused by the accumulation of glycolytic intermediates dealing to a transient repression or to any other physiological phenomenon, it should be determined by further experiments. On this occasion, the lactic acid concentrations predicted from pH measurements and from ultrasonic velocity are somewhat different (Fig. 7(c)). Perhaps, this is related to the physiological phenomenon that provokes the halt in pH. In general terms, it could be noticed that modifications in the pH coincided in time with changes in ultrasonic velocity in all the cases studied (Figs. 5–7). Moreover, in monosaccharide fermentations, the slope of ultrasonic velocity was proportional to the modifications in pH. Therefore, it can be suggested that pH and ultrasound are detecting the same or parallel processes. Hence, consumption of lactose and generation of lactic acid cause an increase in ultrasound velocity. This methodology has been used to monitor dairy fermentations (Elvira et al., 2002). Different physicochemical events are occurring during these processes, that include clumping of casein micelles, protein coagulation, production of microbial exopolysaccharides and changes in various solute concentrations due to the bacterial metabolism, i.e. lactose fermentation. In order to understand the influence of lactose fermentation on the ultrasound velocity changes, another assay was set up with a lactose concentration similar to that found in milk (50 g/l). Results are similar to those obtained with 2% lactose (Fig. 8), with a slight difference in the ultrasonic velocity drop 0.6 m/s, possibly due to the different lactic acid yields. 4.4. Predicted vs. observed data

1.5

1.0

0.5

0.0

0

c

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5

10

15

20

25

30

35

Time (h)

Fig. 7. (a) Ultrasonic velocity variation at f = 2 MHz ( ), pH ( ), (b) lactose mass concentration ( ) and bacterial growth ( ) during the lactic acid fermentation of a modified basal MRS medium ðw0lactose ¼ 2%Þ by L. casei, at T = 37 C. (c) Lactic acid mass concentrations measured ( ) and calculated from ultrasonic velocity ( ) and pH ( ) measurements during the lactic acid fermentation showed in (a).

from the lower velocity of the binary water–lactose mixture (Fig. 2). An interesting fermentation halt was repeatedly observed after 5 h in lactose fermentations, which corresponded to an ultrasonic velocity raising. Whether this

Regressions obtained from binary mixtures (Fig. 2) have been used to calculate lactic acid concentrations in Figs. 5(b), 6(b), 7(c) and 8(c). A good agreement between measured and predicted data happens in the case of monosaccharide fermentations. The little mismatch can be due to the bacterial anabolism (Fig. 4), the inaccuracy of Eq. (9), protein structural changes or the appearance of minor products. In fact, other products such as ethanol might significantly affect ultrasonic velocity (Giacomini, 1947). L. casei can produce millimolar amounts of ethanol (Gosalbes, Esteban, Gala´n, & Pe´rez-Martı´nez, 2000) and other compounds such as acetic acid (Gala´n and Pe´rez-Martı´nez, unpublished), which expressed in mass would mean about 24–25 mg/l of each compound. Correction for these and possibly other minor factors affecting sound transmission in liquid media can greatly improve the prediction power. In the case of lactose fermentation an important disagreement between measured and predicted data occurs. Nevertheless, it is interesting to observe the coincidence between the halt in pH and the increase in ultrasonic velocity. Further studies are desirable to investigate this phenomenon.

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0.0 6.0 -0.1 5.5 -0.2 5.0

-0.3 -0.4

pH

Variation of ultrasonic velocity (m/s)

0.1

4.5

-0.5 4.0 -0.6 3.5

-0.7 0

5

10

15

20

25

Time (h)

a

When sugar is transformed into lactic acid, the speed of sound decreases, with some differences between carbohydrates. The exponential increment of bacterial numbers slightly increase the ultrasonic velocity (at megahertz frequencies), but with little significance in the overall data. Fermentations are very complex processes. The availability of on-line and non-invasive measurement techniques will allow a better understanding of the process, by analysing as many data as possible. Thus, a better supervision and knowledge of the fermentation will facilitate the optimisation of the process and more detailed kinetic studies, improving their efficiency and increasing their applications. References

6.5 6

5 5.5 4 5.0 3

4.5

2

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3.0

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1

3.5

Concentration of bacteria (10 /ml)

Lactose mass concentration (%)

6.0

0 0

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b

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Mass concentration of lactic acid (%)

1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 -0.2 0

c

5

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Time (h)

Fig. 8. (a) Ultrasonic velocity variation at f = 2 MHz ( ), pH ( ), (b) lactose mass concentration ( ) and bacterial growth ( ) during the lactic acid fermentation of a modified basal MRS medium ðw0lactose ¼ 5%Þ by L. casei, at T = 37 C. (c) Lactic acid mass concentration measured ( ) and calculated from ultrasonic velocity variations ( ) and pH ( ) during the lactic acid fermentation showed in (a).

5. Conclusions This work shows the suitability of ultrasonic velocity to monitor on-line L. casei fermentation in culture media.

Amrane, A. (2005). Analysis of the kinetics of growth and lactic acid production for Lactobacillus helveticus growing on supplemented whey permeate. Journal of Chemical Technology and Biotechnology, 80, 345–352. Becker, T., Mitzscherling, M., & Delgado, A. (2001). Ultrasonic velocity—a non-invasive method for the determination of density during beer fermentation. Engineering in Life Sciences, 1(2), 61–67. Becker, T., Mitzscherling, M., & Delgado, A. (2002). Hybrid data model for the improvement of an ultrasonic-based gravity measurement system. Food Control, 13, 223–233. Burton, C. J. (1948). A study of ultrasonic velocity and absorption in liquid mixtures. Journal of the Acoustical Society of America, 20(2), 186–199. Caplice, E., & Fitzgerald, G. F. (1999). Food fermentations: Role of microorganisms in food production and preservation. International Journal of Food Microbiology, 50, 131–149. Cristiani-Urbina, E., Netzahuatl-Mun˜oz, A. R., Manriquez-Rojas, F. J., Jua´rez-Ramı´rez, C., Ruiz-Ordaz, N., & Galı´ndez-Mayer, J. (2000). Batch and fed-batch cultures for the treatment of whey with mixed yeast cultures. Process Biochemistry, 35, 649–657. Danusso, F. (1951). Velocita` ultrasonora e compressibilita` adiabatiche di miscele liquide atermiche o ideali. Lincei—Rend. Sc. fis. mat. e nat., Vol. X, 235–243. De Vos, W. M., & Vaughan, E. E. (1994). Genetics of lactose utilization in lactic acid bacteria. FEMS Microbiological Reviews, 15, 217–237. Douhe´ret, G., Davis, M. I., Reis, J. C. R., & Blandamer, M. J. (2001). Isentropic compressibilities—experimental origin and the quest for their rigorous estimation in thermodynamically ideal liquid mixtures. Chemphyschem, 2, 148–161. Elmehdi, H. M., Page, J. H., & Scanlon, M. G. (2003). Monitoring dough fermentation using acoustic waves. Transaction of IChemE, 81(Part C), 217–223. Elvira, L., Resa, P., & Espinosa, F. (2002). Montero de ultrasonic propagation and thermal changes during milk gelation processes. Proceedings of Forum Acusticum, Sevilla. Giacomini, A. (1947). Ultrasonic velocity in ethanol–water mixtures. Journal of the Acoustical Society of America, 19(4), 701–702. Gosalbes, M. J., Esteban, C. D., Gala´n, J. L., & Pe´rez-Martı´nez, G. (2000). Integrative food-grade expression system based on the lactose regulon of Lactobacillus casei. Applied and Environmental Microbiology, 66(11), 4822–4828. Kandler, O. (1983). Carbohydrate metabolism in lactic acid bacteria. Antonie van Leuwenhoek, 49, 209–224. Liu, S. Q. (2003). Practical implications of lactic acid and pyruvate metabolism by lactic acid bacteria in food and beverage fermentations. International Journal of Food Microbiology, 83, 115–131. McClements, D. J. (1997). Ultrasonic characterization of foods and drinks: Principles, methods and applications. Critical Reviews in Food Science and Nutrition, 37(1), 1–46.

P. Resa et al. / Journal of Food Engineering 78 (2007) 1083–1091 Miller, G. L. (1954). Use of dinitrosalicylic acid reagent for determination of reducing sugar. Analytical Chemistry, 31, 426–428. Nutsch-Kuhnkies, R. (1965). Uber schallkennlinien einiger bina¨rer mischungen und lo¨sungen. Acustica, 15, 383–386. Oh, H., Wee, Y. J., Yun, J. S., Han, S. H., Jung, S., & Ryu, H. W. (2005). Lactic acid production from agricultural resources as cheap raw materials. Bioresource Technology, 96(13), 1492–1498. Resa, P., Bolumar, T., Elvira, L., Pe´rez, G., Montero de Espinosa, F., (2004a). Ultrasonic velocity measurements in the ternary mixtures water–lactose–lactic acid, for the purpose of monitoring the lactic acid fermentation of lactose. Proceedings of IEEE International Ultrasonics, Ferroelectrics, and Frequency Control, Montre´al. Resa, P., Elvira, L., & Montero de Espinosa, F. (2004b). Concentration control in alcoholic fermentation processes from ultrasonic velocity measurements. Food Research International, 37, 587–594. Schu¨gerl, K. (2001). Progress in monitoring, modeling and control of bioprocesses during the last 20 years. Journal of Biotechnology, 85, 149–173.

1091

Sethuran, A., Sethuran, V., Hatti-Kaul, R., & Mattiasson, B. (1999). Lactic acid production by inmobilized Lactobacillus casei in recycle batch reactor: A step towards optimization. Journal of Biotechnology, 73, 61–70. Sette, D. (1961). Dispersion and absorption of sound waves in liquids and mixtures of liquids. In S. Flu¨gge (Ed.), Handbuch der Physik, BD. XI/1 (pp. 275–360). Berlin: Springer-Verlag. Urick, J. R. (1947). A sound velocity method for determining the compressibility of finely divided substances. Journal of Applied Physics, 18, 983–987. Veyrat, A., Monedero, V., & Perez-Martinez, G. (1994). Glucose transport by the phosphoenolpyruvate: Mannose phosphotransferase system in Lactobacillus casei ATCC 393 and its role in carbon catabolite repression. Microbiology, 140, 1141–1149. Viana, R., Monedero, V., Dossonnet, V., Pe´rez-Martı´nez, G., & Deutscher, J. (2000). Enzyme I and HPr from Lactobacillus casei: Their role in sugar transport, catabolite repression and inducer exclussion. Molecular Microbiology, 36, 570–584.