WO2009121416A1 - Infrared monitoring of bioalcohol production - Google Patents
Infrared monitoring of bioalcohol production Download PDFInfo
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- WO2009121416A1 WO2009121416A1 PCT/EP2008/054096 EP2008054096W WO2009121416A1 WO 2009121416 A1 WO2009121416 A1 WO 2009121416A1 EP 2008054096 W EP2008054096 W EP 2008054096W WO 2009121416 A1 WO2009121416 A1 WO 2009121416A1
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- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12P—FERMENTATION OR ENZYME-USING PROCESSES TO SYNTHESISE A DESIRED CHEMICAL COMPOUND OR COMPOSITION OR TO SEPARATE OPTICAL ISOMERS FROM A RACEMIC MIXTURE
- C12P7/00—Preparation of oxygen-containing organic compounds
- C12P7/02—Preparation of oxygen-containing organic compounds containing a hydroxy group
- C12P7/04—Preparation of oxygen-containing organic compounds containing a hydroxy group acyclic
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3577—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing liquids, e.g. polluted water
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/02—Food
- G01N33/14—Beverages
- G01N33/146—Beverages containing alcohol
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2201/00—Features of devices classified in G01N21/00
- G01N2201/12—Circuits of general importance; Signal processing
- G01N2201/129—Using chemometrical methods
Definitions
- Bioalcohol including methanol, ethanol and butanol from fermentation of biological materials become increasing important.
- Bioalcohol may be produced directly from fermentation of sugars, such as the sugars found in sugar canes and sugar beets, or al-ternatively from starch or cellulose.
- sugars such as the sugars found in sugar canes and sugar beets
- starch and cellulose are similar in that the starch or cellulose must be converted to sugar by an enzymatic process.
- the use of these two raw materials does however differ in that the enzymes for starch to sugar conversion are currently commercially available, whereas the enzymes for cellulose to sugar conversion have not gained wide usage yet.
- Starch based raw materials for bio fuel include grain, such as corn, wheat and barley, switch grass but any starch containing plant may in principle be used.
- Dry and wet animal feed is subsequently produced.
- Infections with lactic acid and/or acetic acid bacteria are important to avoid, as they will affect the efficiency of the yeast. Lactic acid bacteria usually occur in the beginning of the fermentation where high levels of sugar are available. Acetic acid bacteria are mainly encountered at later stages, as they feed on ethanol.
- NIR NIR spectroscopy
- Chromatographic methods in general require filtration of the sample, but yield a higher accuracy.
- the present invention is aimed at overcoming some of the drawbacks of the current methods. This is realised by using transmission spectroscopy in the spectral range known as mid-IR (1000-5000 cm- 1 ). A spectrum of a number of samples is collected from an instrument, which may be based on the well known FTIR technology. From a set of samples and a corresponding set of reference values or other known parameters of interest for this set of samples, a calibration model may be made by multivariate statistical methods such as PLS. This calibration model is subsequently applied on unknown mid-IR spectra to provide a determination of the parameter of interest.
- mid-IR 1000-5000 cm- 1
- the parameters may be chemical parameters such as pH, concentrations of constituents, such as simple alcohols, sugar alcohols, organic acids, and saccharides - including monosaccharides, disaccharides, oligosaccharides and polysaccharides, but it may also be an index of fermentation performance, reflecting factors such as the risk level of fermentation infection, the rate of fermentation, stress level of yeast and bacteria and other important performance characteristics of the fermentation. Such an index may be determined by application of a suitable calibration model, or from a set rules and formulae applied on the other parameters of interest.
- the samples were taken by the lab technicians from taps where the fermentation broth leaves the fermentor. Multiple samples were discarded prior to selecting a sample, which was to avoid "old" sample material and sediments in the tubing.
- the fermentation samples were at approx. 30 °C at the sampling time. Cook samples were at approx. 100 °C.
- HPLC DP4+, DP3, maltose, glucose, glycerol, acetic acid, lactic acid, and ethanol
- the reference samples were filtered twice: first through a coffee filter, and then using a syringe filter with a pore size of 0.2 ⁇ m to avoid particles in the HPLC.
- the sample was transferred to the FT mid-IR instrument cuvette using a disposable pipette.
- the cuvette was closed quickly afterwards in order to avoid evaporation of ethanol.
- SNV Standard Normal Variate
- Spectral preprocessing such as SNV, detrend, or first derivative was applied to the NIR spectra, and a PLS calibration was developed. The calibration and validation results are based on exactly the same calibration and validation samples as for the mid-IR analysis.
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- Chemical & Material Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Organic Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Analytical Chemistry (AREA)
- Food Science & Technology (AREA)
- Zoology (AREA)
- Wood Science & Technology (AREA)
- Spectroscopy & Molecular Physics (AREA)
- General Chemical & Material Sciences (AREA)
- Microbiology (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Biotechnology (AREA)
- Medicinal Chemistry (AREA)
- Bioinformatics & Cheminformatics (AREA)
- General Engineering & Computer Science (AREA)
- Genetics & Genomics (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
Abstract
A device for determining one or more parameters of interest for raw materials, intermediates and products of bioalcohol production, comprising a sample presentation unit, a source of radiation and a means of detection characterised in that the source of radiation and the means of detection are configured for recorded one or more spectral characteristics in the spectral region from 1000 cm-1 to 5000 cm-1.
Description
Description
Infrared monitoring of bioalcohol production
[0001] As the concern over greenhouse gas emissions increases the production of bioalcohols including methanol, ethanol and butanol from fermentation of biological materials become increasing important. Bioalcohol may be produced directly from fermentation of sugars, such as the sugars found in sugar canes and sugar beets, or al-ternatively from starch or cellulose. The use of starch and cellulose is similar in that the starch or cellulose must be converted to sugar by an enzymatic process. The use of these two raw materials does however differ in that the enzymes for starch to sugar conversion are currently commercially available, whereas the enzymes for cellulose to sugar conversion have not gained wide usage yet. Starch based raw materials for bio fuel include grain, such as corn, wheat and barley, switch grass but any starch containing plant may in principle be used.
[0002] Great efforts are made to identify the optimum temperature, pH and other operational conditions of the liquefication and saccharification process for specific bio-mass sources, and accordingly the operation of a bio-ethanol plant is characterised by a high level of process monitoring. [0003] One possible example of a continuous fermentation process for production of bioethanol consists of the following steps:
Receival of the raw materials such as corn at the weighbridge. Near Infrared analysis of moisture, starch and possibly other nutrients. Milling of the corn using hammer mills.
Cooking and enzymatic hydrolysis in order to break the starch down to glucose that the yeast will feed on. Regular samples are taken from the slurry tank, liquefaction tanks as well as the flash wessel. These samples are tested for pH, sugars (classified by the degree of polymerisation (DP) of saccharides; DP4+ (DP>4), DP3 (DP=3), maltose, and glucose or by the Dextrose Equivalent - DE), and solids. Continuous fermentation. The fermentors are kept at almost constant ethanol and sugar contents, and the liquid is continuously transferred between the tanks. Ethanol, pH, sugars (DP4+, DP3, maltose, and
glucose), glycerol, infection (as detected by lactic and acetic acid), yeast count, and solids is determined on these tanks.
Distillation and purification (using molecular sieves). Impurities in the product may be analysed by gas chromatography (GC).
Dry and wet animal feed is subsequently produced.
[0004] Infections with lactic acid and/or acetic acid bacteria are important to avoid, as they will affect the efficiency of the yeast. Lactic acid bacteria usually occur in the beginning of the fermentation where high levels of sugar are available. Acetic acid bacteria are mainly encountered at later stages, as they feed on ethanol.
[0005] As the person skilled in the art will realise alternative implementations of such processes will include batch processes, and various intermediates between batch and continuos fermentation, also known as semi-batch fermentation.
[0006] The analytical methods currently employed are NIR spectroscopy or chromatoprahic methods. NIR is characterised by ease of use and sample handling with little or no sample pre-treatment. Chromatographic methods in general require filtration of the sample, but yield a higher accuracy.
[0007] The present invention is aimed at overcoming some of the drawbacks of the current methods. This is realised by using transmission spectroscopy in the spectral range known as mid-IR (1000-5000 cm-1). A spectrum of a number of samples is collected from an instrument, which may be based on the well known FTIR technology. From a set of samples and a corresponding set of reference values or other known parameters of interest for this set of samples, a calibration model may be made by multivariate statistical methods such as PLS. This calibration model is subsequently applied on unknown mid-IR spectra to provide a determination of the parameter of interest.
[0008] The parameters may be chemical parameters such as pH, concentrations of constituents, such as simple alcohols, sugar alcohols, organic acids, and saccharides - including monosaccharides, disaccharides, oligosaccharides and polysaccharides, but it may also be an index of fermentation performance, reflecting factors such as the risk level of
fermentation infection, the rate of fermentation, stress level of yeast and bacteria and other important performance characteristics of the fermentation. Such an index may be determined by application of a suitable calibration model, or from a set rules and formulae applied on the other parameters of interest.
Example 1
[0009] 131 fermentation samples were collected during the trial. They were well distributed between all fermentors. A slight overrepresentation of the early fermentation is present due to the fact that they are sampled more often - a result of the fact that these steps are more critical.
[0010] The samples were taken by the lab technicians from taps where the fermentation broth leaves the fermentor. Multiple samples were discarded prior to selecting a sample, which was to avoid "old" sample material and sediments in the tubing. The fermentation samples were at approx. 30 °C at the sampling time. Cook samples were at approx. 100 °C.
[0011] To avoid false correlations between parameters 28 of the samples were spiked with maltose (two samples), glucose (two samples), acetic acid (12 samples), and lactic acid (12 samples) at different realistic levels. The fermentation broth samples (approx. 400 ml_) were spiked with the pure constituents prior to filtering.
[0012] The reference results for the fermentation samples (including the 28 spiked samples) were obtained from: • A pH meter (pH)
HPLC (DP4+, DP3, maltose, glucose, glycerol, acetic acid, lactic acid, and ethanol)
[0013] The reference samples were filtered twice: first through a coffee filter, and then using a syringe filter with a pore size of 0.2 μm to avoid particles in the HPLC.
[0014] The analysis time was 20-30 minutes, and the analyses were performed by two identical HPLCs. All results were recorded as w/w%. Only single determinations were performed.
FT mid-IR measurements
[0015] The preparation of the samples for the FT mid-IR analysis was as follows:
Filtering using a coffee filter into an open plastic cup - exactly the same sample that was used for the HPLC, but without 0.2 μm filtering.
The samples for FT mid-IR analysis were taken shortly after the HPLC samples in order to avoid any evaporation.
It is possible to obtain enough sample volume to perform a single FT mid-IR determination within approx. one minute.
After filtering the samples were kept in tightly closed 30 mL containers prior to analysis.
The sample was transferred to the FT mid-IR instrument cuvette using a disposable pipette.
The cuvette was closed quickly afterwards in order to avoid evaporation of ethanol.
The samples were measured in triplicate (sample change between replicates)
After the analysis the cuvette was cleaned with a soft paper wipe [0016] Calibrations were developed for all nine parameters in the fermentation samples: pH, DP4+, DP3, maltose, glucose, lactic acid, glycerol, acetic acid, and ethanol.
[0017] The Standard Normal Variate (SNV) preprocessing method was applied prior to developing a single PLS calibration model for each of the nine parameters, which were developed based on 97 samples; the optimal number of PLS factors was selected based on the cross validated results. All 28 spiked samples were included in the calibration set along with two thirds of the natural samples. Validation was based on the remaining 34 samples (systematically selected to cover the whole trial). NIR measurements
[0018] Exactly the same 131 fermentation samples were measured on a NIR instrument prior to filtering, i.e. the raw process samples were analysed. No other sample preparation was required. The samples were measured in reflectance mode.
[0019] Only single determinations were obtained from the NIR instrument. [0020] Calibrations were developed for seven of the nine parameters in the fermentation samples: pH, DP4+, DP3, maltose, glucose, glycerol, and
ethanol. It was not possible to establish any correlations for lactic and acetic acid when the spiked samples were included. When they were excluded it became possible - especially for acetic acid. This was, however, solely due to the aforementioned correlations to the sugars and ethanol and thus not to real spectral information from acetic acid. This indicates that the NIR method is unable to detection fermentation infections.
[0021] Spectral preprocessing such as SNV, detrend, or first derivative was applied to the NIR spectra, and a PLS calibration was developed. The calibration and validation results are based on exactly the same calibration and validation samples as for the mid-IR analysis.
Results
[0022] The results of the calibration on the samples from the fermentor outlet were promising. The RMSEP (Root of Means Squared Error of Prediction) for the validation samples were significantly lower for the calibration based on mid-IR spectra than for the calibration based on NIR spectra, as shown in table 1.
Table 1
Mid IR NIR
Parameter Range RMSEP RMSEP
PH 3.18-4.08 0.044 0.076
DP4+ - high 0 .57-9.99 % 0.14% 0.42%
DP4+ - low 0 .57-1.00 % 0.05% 0.25%
DP3 0 .05-0.50 % 0.03% 0.03%
Maltose (DP2) - high 0 .28-2.59 % 0.07% 0.18%
Maltose (DP2) - low 0 .28-1.00 % 0.06% 0.18%
Glucose - high 0 .01-6.24 % 0.12% 0.26%
Glucose - low 0 .01-1.00 % 0.05% 0.18%
Lactic acid 0 .07-0.72 % 0.01 % NA
Glycerol 0 .82-1.36 % 0.01 % 0.02%
Acetic acid 0 .00-0.25 % 0.01 % NA
Ethanol - full range 5. 82-12.80 % 0.15% 0.19%
Ethanol - high 10 .00-12.80 % 0.15% 0.12%
[0023]
Example 2
[0024] Similar procedures were followed in the generation of calibrations for the analysis of the process intermediate - mash. The results were also in this case better for the mid-IR than for the NIR spectra.
[0025]
Table 2
Mid IR NIR
Parameter Range RMSEP RMSEP
PH 4.24-6.07 0.131 0.205
Glucose 0.28-8.93 0.37% 0.80%
Maltose 0.42-2.93 0.17% 0.22%
DP3 0.23-2.06 0.18% NA
DP4+ 6.08-26.01 1.75% 1.91 %
DE (calibrated) 6.0-58.5 2.41 % 5.07%
Claims
1. A device for determining one or more parameters of interest for raw materials, intermediates and products of bioalcohol production, comprising a sample presentation unit, a source of radiation and a means of detection characterised in that the source of radiation and the means of detection are configured for recorded one or more spectral characteristics in the spectral region from 1000 cm-1 to 5000 cm-1.
2. A device according to claim 1 characterised in that some or all of the one or more parameters of interest is taken from the group consisting of pH, concentrations of compounds taken from the group consisting of simple alcohols preferably methanol, ethanol and butanol; sugar alcohols preferably glycerol and mannitol; organic acids, preferably lactic acid, acetic acid, and succinic acids; saccharides preferably pentose, and hexose further preferably glucose, fructose, lactose, and maltose; individual saccharides; grouped oligosaccharides, preferably oligo-saccharides grouped by the degree of polymerisation further preferably DP3, DP4, DP5, DP3+, DP4+ and DP5+; and poly-saccharides as well as indexes related to fermentation performance, preferably infection indexes, rate of fermentation, stress level, and fermentability.
3. A device according to claim 1 or claim 2 characterised in that said sample presentation unit is configured for transmission spectroscopy, by having the optical interfaces of said radiation source and said means of detection on opposite sides of the sample presentation unit.
4. A device according to claims 1-3 further comprising a sample inlet directly on the sample compartment characterised in that said inlet is configured to fill said sample presentation unit with less than 3 ml of sample.
5. A system comprising a device according to any claim above and further comprising a means of data processing equipped with an appropriate calibration model characterised in that said one or more parameters of interest are calculated by said means of data processing, on the basis of the one or more spectral characteristics recorded, and said calibration model.
6. A device according to any claim above characterised in that said sample presentation unit comprises two surfaces transparent to said infrared radiation, further characterised in that said sample presentation unit is configured to position a low volume of sample by pipette.
7. A device according to any of the claims 1-3 or 5-6 above characterised in that the inside of the sample presentation unit may be made available for direct application of the sample to be analysed.
8. A method for determining one or more parameters of interest for raw materials, intermediates and products of bioalcohol production, comprising a sample compartment, a light source and a means of detection characterised in that the light source and the means of detection are configured for mid infrared spectroscopy.
9. A method according to claim 8 characterised in that the sample is filtered by a filter with a mesh less than 50 microns prior to analysis.
Priority Applications (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/EP2008/054096 WO2009121416A1 (en) | 2008-04-04 | 2008-04-04 | Infrared monitoring of bioalcohol production |
| PCT/EP2008/057380 WO2009121423A1 (en) | 2008-04-04 | 2008-06-12 | Method and device for monitoring of bioalcohol liquor production |
| ARP090101194A AR071179A1 (en) | 2008-04-04 | 2009-04-03 | METHOD AND DEVICE FOR MONITORING THE PRODUCTION OF BIOALCOHOL LIQUOR |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/EP2008/054096 WO2009121416A1 (en) | 2008-04-04 | 2008-04-04 | Infrared monitoring of bioalcohol production |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2009121416A1 true WO2009121416A1 (en) | 2009-10-08 |
Family
ID=40230043
Family Applications (2)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/EP2008/054096 Ceased WO2009121416A1 (en) | 2008-04-04 | 2008-04-04 | Infrared monitoring of bioalcohol production |
| PCT/EP2008/057380 Ceased WO2009121423A1 (en) | 2008-04-04 | 2008-06-12 | Method and device for monitoring of bioalcohol liquor production |
Family Applications After (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/EP2008/057380 Ceased WO2009121423A1 (en) | 2008-04-04 | 2008-06-12 | Method and device for monitoring of bioalcohol liquor production |
Country Status (2)
| Country | Link |
|---|---|
| AR (1) | AR071179A1 (en) |
| WO (2) | WO2009121416A1 (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012066042A1 (en) * | 2010-11-17 | 2012-05-24 | Sekab E-Technology Ab | Nir measurements in production of a target chemical from cellulose |
| US8629399B2 (en) | 2009-09-22 | 2014-01-14 | Bp Corporation North America Inc. | Methods and apparatuses for measuring biological processes using mid-infrared spectroscopy |
| US20160011103A1 (en) * | 2014-07-08 | 2016-01-14 | Sumitomo Electric Industries, Ltd. | Optical measuring method and manufacturing method of the alcohol |
| JP2016223789A (en) * | 2015-05-27 | 2016-12-28 | 国立大学法人 香川大学 | Method for determining quantity of ethanol and glucose in mash and filter |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DK3129460T3 (en) * | 2014-04-11 | 2018-03-26 | Specshell Aps | Method for Online Monitoring of Mesh Processes Using Spectroscopy |
| DK3183571T3 (en) * | 2014-08-18 | 2021-03-22 | Foss Analytical As | DETERMINATION OF AN INGREDIENT-RELATED PROPERTY IN A SEVERAL MULTIPLE COMPONENT TEST |
| WO2020088728A1 (en) | 2018-10-30 | 2020-05-07 | Specshell Aps | Non-invasive continuous in line antifouling of atr-mir spectroscopic sensors |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DK1792653T3 (en) * | 2005-12-05 | 2008-03-10 | Foss Analytical As | Apparatus and method for spectrophotometric analysis |
-
2008
- 2008-04-04 WO PCT/EP2008/054096 patent/WO2009121416A1/en not_active Ceased
- 2008-06-12 WO PCT/EP2008/057380 patent/WO2009121423A1/en not_active Ceased
-
2009
- 2009-04-03 AR ARP090101194A patent/AR071179A1/en unknown
Non-Patent Citations (7)
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8629399B2 (en) | 2009-09-22 | 2014-01-14 | Bp Corporation North America Inc. | Methods and apparatuses for measuring biological processes using mid-infrared spectroscopy |
| WO2012066042A1 (en) * | 2010-11-17 | 2012-05-24 | Sekab E-Technology Ab | Nir measurements in production of a target chemical from cellulose |
| US20160011103A1 (en) * | 2014-07-08 | 2016-01-14 | Sumitomo Electric Industries, Ltd. | Optical measuring method and manufacturing method of the alcohol |
| JP2016223789A (en) * | 2015-05-27 | 2016-12-28 | 国立大学法人 香川大学 | Method for determining quantity of ethanol and glucose in mash and filter |
Also Published As
| Publication number | Publication date |
|---|---|
| AR071179A1 (en) | 2010-06-02 |
| WO2009121423A1 (en) | 2009-10-08 |
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