Food Control 11 (2000) 291±296
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On-line monitoring of fermentation processes by a new remote dispersive middle-infrared spectrometer Ph. Fayolle, D. Picque *, G. Corrieu Inst. Nat. de la Rech. Agron., Lab. de Genie et Microbiologie des Procedes Alimentaires, 78850 Thiverval-Grignon, France Received 1 January 1999; received in revised form 22 October 1999; accepted 25 October 1999
Abstract A middle infrared spectrometer coupled with a new attenuated total re¯ectance probe by optical ®bres was developed to solve the problem of on-line analysis in the bioreactors. The measurement of sugars, ethanol and organic acid concentrations was investigated during alcoholic and lactic fermentations. This apparatus was able to operate between 5.5 and 10.5 lm with a reasonably good repeatability (CV < 5%) between 6 and 10 lm. The standard errors of prediction were between 1.4 g lÿ1 (for galactose) and 4.5 g lÿ1 (for fructose). Ó 2000 Elsevier Science Ltd. All rights reserved. Keywords: Middle infrared spectroscopy; On-line measurements; Alcoholic fermentation; Lactic fermentation
1. Introduction In fermentation processes on-line measurements can only determine physical parameters, except for broth pH and the concentrations of oxygen and carbon dioxide in exhaust gas. To solve the problem of on-line measurement of biochemical compounds (substrates and metabolites), the coupling of bioreactors to powerful analytical systems such as chromatographic analysers or infrared spectrometers, may be used. Near-infrared analysis (NIR) and mid-infrared analysis (MIR) is a rapid technique (several seconds) as no sample handling is required. Alberti, Phillips, Fink and Wacasz (1985) estimated sugar and alcohol content by Fourier transform MIR spectroscopy with attenuated total re¯ectance (ATR) circle cell from a fed batch culture of Saccharomyces cerevisiae. Fairbrother, George and Williams (1991) used the same kind of device to determine lactose and ethanol content during fermentation of cheese whey. Vaccari, Dosi, Campi, Gonzalez-Vara and Matteuzzi (1994) presented an NIR application for monitoring
*
Corresponding author. Tel.: +33-1-30815485; fax: +33-130815597. E-mail address:
[email protected] (D. Picque).
lactic acid production during fermentation. Concentrations of lactic acid, glucose and biomass estimated by on-line NIR spectroscopy and by the conventional laboratory methods were similar. A more reliable method uses the transfer of infrared light from the spectrometer to the dip sensor through an optical ®bre to take on-line measurements. Several applications were described but not dealt with in fermentation processes. Kemsley, Wilson, Poulter and Day (1993) used sapphire ATR probe coupled with a ¯uoride glass optical ®bre to determine sugars in fruit juices. The sapphire ATR probe did not however allow the spectral analysis of the ®ngerprint zone between 7±14 lm because the cut-o wavenumber is 5 lm. Dupuy, Huvenne, Legrand and Le Bourlout (1995) recorded the spectra of dierent edible oils with ZnSe ATR probe coupled with chalcogenide ®bre. The edible oils were then discriminated by principal component analysis. These results were only laboratory trials, but they showed that an ATR probe is potentially suitable for taking remote measurements. In this paper, a dispersive Mid-IR spectrometer coupled with a new ATR sensor (crystal of germanium and silver halide ®bre) was set up for taking remote measurements in real time. Apparatus performance was evaluated to determine the main compound content (sugars, organic acids, ethanol) in alcoholic and lactic fermentations.
0956-7135/00/$ - see front matter Ó 2000 Elsevier Science Ltd. All rights reserved. PII: S 0 9 5 6 - 7 1 3 5 ( 9 9 ) 0 0 1 0 5 - X
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2. Experimental 2.1. Fermentation conditions ± analytical methods The four alcoholic and four lactic acid fermentations were carried out in a 15 l bioreactor (Biola®tte, St Germain, France). The must from INRA Pech Rouge (Gruissan, France) was thermostated at 20°C without aeration and agitation. For the lactic acid fermentation, the industrial medium, initially containing about 80 g/l of lactose, was inoculated with 0.008 g/l (DCW) of lactic acid bacteria (Lactobacillus Bulgaricus, LB12, Hansen, Arpagon, France), thermostated at 44°C and stirred at 100 rpm for the homogeneity of the medium. The substrates (glucose, fructose, lactose, galactose) and metabolites (ethanol, lactic acid) were determined by liquid chromatography. The analyser was composed of a model 510 pump, a WISP automatic injector, a Model 410 refractometer and a PC with Millenium software (Waters, St. Quentin, France). The column was an Aminex HPX87H (Biorad, Paris, France) with a mobile phase of 0.005 M H2 SO4 at a ¯owrate of 0.6 ml/ min. The internal standard was 1% propionic acid. 2.2. Materials The apparatus contains four elements: a dip ATR sensor, an optical ®bre, a dispersive spectrometer and a personal computer. The ATR crystal is composed of germanium. There are 11 re¯ections, and the transmission range is between 2±12 lm. The carbon coating (diamond like carbon) allowed for contact with food. The ATR accessory was designed in order to allow on-line and in-situ measurements of fermentation processes (Heuze, 1997). At each re¯ection within the crystal, there is a small eective penetration of an evanescent wave into the medium in contact with the crystal. One of the major advantages of the ATR method is that overall eective pathlength is very short, consequently eliminating one of the greatest diculties of the transmission method (Wilson, 1990). The high absorbtivity of the media is not problematic, the only criterion for the production of a good spectrum is that the sample should make ecient contact with the crystal. Even if the fermentation system contains particulate matter, the orientation of the probe in the fermentation media allowed any deposit of matter on the sensitive part of the ATR crystal. Remote measurements were taken using a 2 m silver halide ®bre (Ceramoptec, Lot-Oriel, Les Ulis, France), which transmitted between 5±13 lm. The new dispersive Mid-IR was made up of an MIR broadband source (MoSi2 ), a concave-ruled grating with a line density of 100 lines/mmÿ1 and a resolution of 120 nm in the range 5.5±10.5 lm (Jobin-Yvon, Longjumeau,
France). Spectral selection was operated using a grating instead of a Michelson interferometer as it costs less and the mechanical robustness to vibrations and shocks, for instance, was greater than an FT-IR. The detection equipment was composed of an optical chopper and a P5349 pyroelectric detector (GEC-Marconi, Paris, France). This spectrometer was controlled using an original software developed by SAGEM (Argenteuil, France) and INRA and carried out on a PC. The Matlab program (The Math Works, version 4.2a) was used for data processing. 2.3. Data acquisition and treatment methods The MIR spectra were averaged over four scans with a 60 nm numerical resolution. With this con®guration, recording time was about 3 min 30 s. The ATR crystal was set in the bioreactor and submerged in the medium. Water was used as background reference. Moreover, initial and ®nal media for the two types of fermentations were also tested as background references to remove contributions in the absorbance of unknown compounds and facilitate on-line measurements. During the fermentation, each sample single-beam spectrum is ratioed against the background single-beam spectrum (water, initial or ®nal medium). A mixture of glucose, fructose, ethanol and lactic acid was prepared to assess spectral repeatability and the detection threshold of the equipment. Data were processed conducted with partial least squares-1 (PLS-1) regressions (Geladi & Kowalski, 1986). Depending on the compound and the type of spectral data (nature of background reference), a one- or two-points baseline correction and mean-centring pretreatment were carried out before the models were established. One speci®c model was built for each compound. Three sets of samples from alcoholic and lactic acid cultures for calibration, validation and prediction were composed containing 35, 19 and 19 samples, respectively. The procedure for choosing the optimal number of scores and calculating the standard errors of calibration (SEC) and standard errors of prediction (SEP) has been described previously (Fayolle, Picque, Perret, Latrille & Corrieu, 1996). 3. Results 3.1. Assessment of apparatus performances Apparatus performances were characterised by taking into account three criteria: optical attenuation, spectral repeatability and detection threshold. (1) The optical attenuation of each part of the apparatus was determined in the 5±10 lm range (Table 1).
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Table 1 Optical attenuation (dB) of each part of the apparatus at dierent wavelengths Optical attenuation (dB) Wavelength (lm) 5
6
7
8
9
10
Monochromator Optical ®ber Germanium crystal Window of the detector
6.1 1153.8 25.4 0.5
4.3 8.6 3.7 0.5
3.9 6.3 3.4 0.5
4.2 10.5 3.4 0.5
4.9 5.9 3.5 0.5
5.9 10.3 3.0 0.5
Total
1185.8
14.5
14.1
18.6
14.8
19.7
The total attenuation was approximately between 14 and 20 dB in the range 5.5±10 lm. These attenuations corresponded to 4% and 1% of the initial intensity, respectively. The main attenuation corresponded to optical ®bre between 6±10 lm and represented about 50% of the total. The attenuation was constant (0.5 dB) for the detector window throughout the spectral range. (2) Ten spectra of the mixture containing glucose, fructose, ethanol and lactic acid were recorded. Fig. 1 shows the mean of the 10 spectra and the coecient of variation (CV) in the 5.5±10.5 lm range. Between 6.6 and 10.2 lm, the values of the CV were lower than 5%. From 10.2 lm, they increased quickly. Transmission limit was reached, essentially due to the coating on the optical components (windows, lenses, etc.). (3) The detection threshold was determined using ®ve mixtures of the same compounds. The concentrations of each compound decreased from 15 to 1 g lÿ1 . The 5 spectra were displayed in Fig. 2. The average noise ¯uctuations for the apparatus under our experimental conditions were 1:25 10ÿ3 absorbance unit (a.u.). The intensity of a genuine absorption must be about four times (i.e., 5 10ÿ3 a.u.) that of the noise ¯uctuations to
Fig. 2. Spectra of 5 mixtures containing glucose, fructose, ethanol and lactic acid (15, 7, 3, 2 and 1 g lÿ1 ) in the range 5±12 lm.
be distinguishable (Banwell & McCash, 1994). Under our conditions, absorption peaks started to detach from the noise for concentrations higher than 2 g lÿ1 between 8.6±10.4 lm (range characterised by absorption of alcohol groups of the four compounds). Note that each compound in the mixture contained alcohol groups. The detection threshold between 8.6±10.4 lm therefore had to increase four-fold to reach 8 g lÿ1 . This level was con®rmed by the peak around 6.45 lm, assigned solely to lactic acid. The concentration of the compounds had to be higher than 7 g lÿ1 to obtain signi®cant absorbance. 3.2. Choice of a background reference
Fig. 1. Mean of 10 spectra of a mixture containing glucose, fructose, ethanol and lactic acid (30 g lÿ1 ) and coecient of variation (CV) in the range 5±12 lm.
Water is usually used as background reference with laboratory spectrometers. But in industrial conditions with the sensor set in the bioreactor, the use of water is not very convenient. Consequently, both initial and ®nal samples were used as background to dierentiate between the main substrates and products of fermentation processes and the other compounds in the medium. This strategy allowed the calibration of the apparatus under real measurement conditions with the dip IR probe (ATR crystal
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Table 2 Performances of the PLS-1 regressions according to the nature of the background reference (water, must or wine). Alcoholic fermentationa Background reference
Compound Glucose Fructose Ethanol
Water
Must
Wine
SECn
SEPn
SECn
SEPn
SECn
SEPn
1 1 1
1 1 1
0.71 0.63 1.00
0.92 0.97 1.50
0.73 0.69 1.08
0.89 1.00 1.46
a
SECn and SEPn represented the normalised Standard Error of Calibration and Prediction, respectively, with SEC and SEP obtained with water background reference as norm.
of germanium) in the reactor, without any handling. Table 2 compares the determination of compound contents of alcoholic fermentation with PLS-1 regressions. The results are similar for lactic fermentations. The SEC values obtained with must or wine were equal to ethanol and better for sugars in the results obtained with water background reference. The SEP values for sugar determination were the same, regardless of the nature of the background. However, the estimation of ethanol content was about 50% greater with wine or must than water. Nevertheless, it seems more useful to use initial media as background to monitor fermentation processes with this equipment, in industrial conditions. Further experiments were carried out with the initial media as background references.
to 0.03 a.u. at 9.8 lm lower than the dierence for alcoholic fermentation. The production of lactic acid was characterised by the appearance of a peak at 6.45 lm. The scatter plots of estimated concentration values versus reference data are shown in Fig. 4 (A)±(C) for glucose, fructose, ethanol and in Fig. 5 (A)±(C) for lactose, galactose and lactic acid, respectively. Futhermore, there is no bias in the estimation of concentrations of the three compounds of alcoholic fermentation. The concentrations of galactose and lactic acid are slightly underestimated. Nevertheless, the scatter plots show a
3.3. Spectral evolution of fermentation broth and quantitative analysis Fig. 3 (A) and (B) show spectral evolution between 5.5 and 10.5 lm from alcoholic and lactic acid fermentations, respectively. The values of absorbance were negative, because the background reference is the initial medium. The principal vibrational assignments have previously been described for alcohol fermentation (Fayolle, Picque, Perret, Latrille & Corrieu, 1996) and lactic acid fermentation (Fayolle, Picque & Corrieu, 1997). The spectral evolution of alcoholic fermentation (Fig. 3(A)) was mainly characterised by a change in peak shape of the in the 8.5±10.5 lm range. The dierence in absorbance (DA) before and after culture at 9.4 lm was about 0.16 a.u. These modi®cations were caused by the progressive consumption of glucose and fructose by the yeast and the accumulation of ethanol in the broth. The spectra of lactic acid fermentation (Fig. 3(B)) were negative in the 6.8±10.4 lm range for the same reason. The progressive consumption of lactose caused a modi®cation in peak shape between 8.5±10.5 lm. However, the constant presence of saccharides during the fermentation (galactose was not consumed by the thermophilic lactic acid bacteria used) resulting in a DA equal
Fig. 3. Spectra of alcoholic fermentation (A) and lactic acid fermentation (B) media from the inoculation time until the end of the culture in the range 5.5±10.5 lm. Background reference was the ®rst sample.
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Fig. 5. Plots of the estimated concentration of lactose (A), galactose (B), lactic acid (C) as a function of the results of the reference method. Fig. 4. Plots of the estimated concentration of glucose (A), fructose (B), ethanol (C) as a function of the results of the reference methods.
good correlation between estimated concentration values and reference data. The SEC and SEP from the calibration and prediction sets are listed in Table 3. The SEC are between 1.6 and 3.8 g lÿ1 , depending on the compound. The SEP are between 1.4 and 4.5 g lÿ1 .
4. Conclusion This paper presented the performances of a new MIR spectrometer coupled with a dip MIR probe by optical ®bre. This apparatus seems to be the ®rst to allow the on-line monitoring of fermentation processes in real time. The transmission zone available was between 5.5 and 10.5 lm. The use of the initial media as background references facilitated the on-line measurements without signi®cant losses of quantitative performances. However, the estimation of concentrations was not accurate enough, compared to the technologist requirements, especially for the compounds of alcoholic fermentation (sugars < 2 g lÿ1 , ethanol < 1 g lÿ1 ). Improvements to the spectrometer (higher resolution power and shift of the transmission spectrum to small wavenumbers) are planned in order to increase the signal-to-noise ratio two
Table 3 Performances of the PLS-1 regressions for the estimation of glucose, fructose, ethanol concentrations for alcoholic fermentation and of lactose, galactose and lactic acid for lactic fermentation Compounds
SEC (g lÿ1 )
SEP (g lÿ1 )
Alcoholic fermentation Glucose Fructose Ethanol
2.8 3.8 3.0
3.5 4.5 3.8
Lactic acid fermentation Lactose Galactose Lactic acid
3.1 1.6 1.7
4.1 1.4 2.0
to three times. The detection threshold and the spectral repeatability should also be improved.
Acknowledgements The authors thank the French Ministere de lÕIndustrie et du Commerce Exterieure, and the Societe Anonyme de Telecommunication (Argenteuil, Groupe SAGEM) for their ®nancial support. They also thank N. Mathern for technical and scienti®c assistance.
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