CN105628644A - Device and method for on-line monitoring of protein enzymolysis process based on in-situ real-time spectrum - Google Patents
Device and method for on-line monitoring of protein enzymolysis process based on in-situ real-time spectrum Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 91
- 238000001228 spectrum Methods 0.000 title claims abstract description 49
- 238000012544 monitoring process Methods 0.000 title claims abstract description 34
- 238000011065 in-situ storage Methods 0.000 title claims abstract description 6
- 102000004169 proteins and genes Human genes 0.000 title abstract description 4
- 108090000623 proteins and genes Proteins 0.000 title abstract description 4
- 108010068370 Glutens Proteins 0.000 claims abstract description 39
- 239000000725 suspension Substances 0.000 claims abstract description 12
- 230000007062 hydrolysis Effects 0.000 claims abstract description 10
- 238000006460 hydrolysis reaction Methods 0.000 claims abstract description 10
- 238000005070 sampling Methods 0.000 claims abstract description 7
- 239000000758 substrate Substances 0.000 claims abstract description 7
- 239000000126 substance Substances 0.000 claims abstract description 6
- 238000012216 screening Methods 0.000 claims abstract description 3
- 108090000765 processed proteins & peptides Proteins 0.000 claims description 24
- 230000001629 suppression Effects 0.000 claims description 19
- 239000000523 sample Substances 0.000 claims description 15
- 108091005804 Peptidases Proteins 0.000 claims description 11
- 239000004365 Protease Substances 0.000 claims description 11
- 102100037486 Reverse transcriptase/ribonuclease H Human genes 0.000 claims description 11
- 238000007654 immersion Methods 0.000 claims description 8
- 238000002329 infrared spectrum Methods 0.000 claims description 7
- 102000004190 Enzymes Human genes 0.000 claims description 4
- 108090000790 Enzymes Proteins 0.000 claims description 4
- 238000013459 approach Methods 0.000 claims description 4
- 238000012937 correction Methods 0.000 claims description 4
- 239000013307 optical fiber Substances 0.000 claims description 4
- 229920001184 polypeptide Polymers 0.000 claims description 3
- 102000004196 processed proteins & peptides Human genes 0.000 claims description 3
- 238000003672 processing method Methods 0.000 claims description 2
- 238000002834 transmittance Methods 0.000 claims description 2
- 238000006243 chemical reaction Methods 0.000 abstract description 15
- 235000018102 proteins Nutrition 0.000 abstract description 3
- 230000005764 inhibitory process Effects 0.000 abstract 2
- 239000007788 liquid Substances 0.000 abstract 2
- 239000000243 solution Substances 0.000 description 19
- 238000001976 enzyme digestion Methods 0.000 description 11
- 230000003595 spectral effect Effects 0.000 description 5
- 230000002255 enzymatic effect Effects 0.000 description 4
- 238000005259 measurement Methods 0.000 description 4
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Chemical compound O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 4
- HEMHJVSKTPXQMS-UHFFFAOYSA-M Sodium hydroxide Chemical compound [OH-].[Na+] HEMHJVSKTPXQMS-UHFFFAOYSA-M 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 3
- 238000003556 assay Methods 0.000 description 3
- 239000012153 distilled water Substances 0.000 description 3
- 229910052736 halogen Inorganic materials 0.000 description 3
- 150000002367 halogens Chemical class 0.000 description 3
- WFKWXMTUELFFGS-UHFFFAOYSA-N tungsten Chemical compound [W] WFKWXMTUELFFGS-UHFFFAOYSA-N 0.000 description 3
- 229910052721 tungsten Inorganic materials 0.000 description 3
- 239000010937 tungsten Substances 0.000 description 3
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 description 2
- ISWSIDIOOBJBQZ-UHFFFAOYSA-N Phenol Chemical compound OC1=CC=CC=C1 ISWSIDIOOBJBQZ-UHFFFAOYSA-N 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 230000036772 blood pressure Effects 0.000 description 2
- 235000013305 food Nutrition 0.000 description 2
- 238000002955 isolation Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 239000000047 product Substances 0.000 description 2
- 230000017854 proteolysis Effects 0.000 description 2
- 239000006228 supernatant Substances 0.000 description 2
- 229910001218 Gallium arsenide Inorganic materials 0.000 description 1
- 206010034960 Photophobia Diseases 0.000 description 1
- 108010009736 Protein Hydrolysates Proteins 0.000 description 1
- 229920002472 Starch Polymers 0.000 description 1
- 241001122767 Theaceae Species 0.000 description 1
- 150000001413 amino acids Chemical class 0.000 description 1
- 239000007864 aqueous solution Substances 0.000 description 1
- 230000001580 bacterial effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000009835 boiling Methods 0.000 description 1
- 239000006227 byproduct Substances 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 238000002790 cross-validation Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000000855 fermentation Methods 0.000 description 1
- 230000004151 fermentation Effects 0.000 description 1
- 239000000413 hydrolysate Substances 0.000 description 1
- 230000002209 hydrophobic effect Effects 0.000 description 1
- 230000001077 hypotensive effect Effects 0.000 description 1
- 229910052738 indium Inorganic materials 0.000 description 1
- APFVFJFRJDLVQX-UHFFFAOYSA-N indium atom Chemical compound [In] APFVFJFRJDLVQX-UHFFFAOYSA-N 0.000 description 1
- 230000002401 inhibitory effect Effects 0.000 description 1
- 239000010977 jade Substances 0.000 description 1
- 208000013469 light sensitivity Diseases 0.000 description 1
- 238000004811 liquid chromatography Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 229910052757 nitrogen Inorganic materials 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 238000002203 pretreatment Methods 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
- 210000000582 semen Anatomy 0.000 description 1
- 235000019698 starch Nutrition 0.000 description 1
- 239000008107 starch Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- YNJBWRMUSHSURL-UHFFFAOYSA-N trichloroacetic acid Chemical compound OC(=O)C(Cl)(Cl)Cl YNJBWRMUSHSURL-UHFFFAOYSA-N 0.000 description 1
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- 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
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
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- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
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- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
The invention discloses a device and a method for on-line monitoring of protein enzymolysis process based on in-situ real-time spectrum, and belongs to the field of on-line monitoring of protein enzymolysis process. The method comprises the following steps: conducting enzymolysis on gluten protein suspension liquids with different concentrations, conducting timing sampling in the enzymolysis process, and monitoring important parameters, such as the degree of hydrolysis, the hydrolysis concentration of an enzymolysis solution and the ACE inhibition ratio of the enzymolysis solution, in the enzymolysis process by a chemical method; quickly collecting the in-situ real-time spectrum of the collected enzymolysis solution; pretreating the collected spectrum; screening the optimal spectrum areas of the degree of hydrolysis, the hydrolysis concentration of the enzymolysis solution and the ACE inhibition ratio of the enzymolysis solution by adopting a synergy interval least square method; establishing a calibration model and a prediction model by adopting the synergy interval least square method; conducting in-situ real-time monitoring and reaction endpoint judging on the enzymolysis process by utilizing the prediction model. The enzymolysis process of the gluten protein suspension liquid with the substrate concentration of 10 g/L is monitored by utilizing the prediction model, and the goodness of fit of the predicted value and the measured value is relatively high.
Description
Technical field:
The present invention relates to protease solution preocess on-line monitoring field, refer in particular to a kind of a kind of technology based on original position real-time near infrared spectrum on-line monitoring gluten protein enzymolysis process.
Background technology:
Semen Tritici aestivi gluten protein is the by-product of starch processing, and protein content is up to 85%, rich in hydrophobic amino acid, is a kind of very potential enzymatic isolation method raw material of preparing blood pressure lowering peptide. Prepare in blood pressure lowering peptide process at enzymatic isolation method, in the degree of hydrolysis DH (Degreeofhydrolysis) of albumen, hydrolyzate polypeptide concentration and characterize hydrolyzate hypotensive activity ACE suppression ratio (Theinhibitiononangiotensinconverting-Ienzymeinhibitory) right and wrong three indexs of the normally off key, be the important evidence judging enzyme digestion reaction terminal. During traditional chemical gauging DH, it is necessary to introduce NaOH, affect the quality of final polypeptide products to a certain extent. And conventional offline needs through sampling from reactor when measuring the peptide concentration of hydrolyzed solution and ACE inhibitory activity, enzyme denaturing, centrifugal wait complicated procedures, workload is big and can not obtain result accurately owing to have left reactive site. It is thus desirable to a kind of quick, continuous print method important parameter in the monitoring enzyme digestion reaction of enzymolysis reactor situ, in order to judge enzyme digestion reaction terminal.
At present, general online measurement and control system is only limitted to temperature, pressure and flow etc., and chemical composition in process and many physical property variablees still can not be carried out effectively continuous measurement, therefore, online spectral technique arises at the historic moment, it be with under field conditions based on the spectrum sensing technology of the microphysics amount on molecular level basis and mi-crochemistry amount, rely on the use of mini optical fibre spectrometer, play an important role in the process monitoring of the industrial departments such as chemical industry, pharmacy, light industry and macromolecular material. Current this microminiature portable near infrared spectrometer is in conjunction with fibre-optical probe owing to its cost is low, and speed is fast, pollution-free, it is simple to the advantages such as real-time, on-line analysis and control. In recent years, spectrum monitoring means were widely used in the process monitoring in food processing process and quality determination. The on-line monitoring (publication number: CN103616383A) of Bacterial community in Food fermentation processes, based on the method (publication number: CN201210124558) of the mid-infrared light spectrum quick test agricultural product oil content of horizontal ATR, a kind of utilize Visible-to-Near InfaRed diffuse spectral technology detection tea fresh leaves nitrogen content method (publication number: CN101382488A). But, these methods can't be applied to the reaction system of aqueous solution smoothly at present.
It is contemplated that utilize online spectral technique to set up a kind of method being applicable to and monitoring enzyme digestion reaction in real time at enzymolysis reactor situ, in order to quickly to judge the terminal of enzyme digestion reaction.
Summary of the invention:
It is an object of the invention to adopt the real-time near infrared spectrometer of original position in conjunction with optical fiber can immersion cell, a kind of method setting up on-line monitoring gluten protein enzymolysis process. Aim at the quick of proteolysis process, original position, monitor in real time. A kind of method based on original position real time spectrum on-line monitoring gluten protein enzymolysis process of the present invention, carries out as steps described below:
(1) gluten protein carrying out enzymolysis, enzymolysis process timing sampling, chemical method monitors its enzymolysis process.
(2) collected enzymolysis solution is quickly gathered the real-time near infrared spectrum of its original position;
(3) Pretreated spectra;
(4) screening that optimal spectrum is interval;
(5) model is set up and prediction;
(6) utilize above-mentioned forecast model that enzymolysis process is carried out original position real-time estimate
Wherein the gluten protein enzymolysis described in step (1) is concentration of substrate is 20-50g/L gluten protein suspension, enzyme concentration 6460U/g, hydrolysis temperature 50 DEG C, enzymolysis time 0-80min. Enzymolysis process index is the ACE suppression ratio of the peptide concentration in gluten protein degree of hydrolysis, enzymolysis solution and enzymolysis solution.
Wherein the described original position real time spectrum of step (2) adopts microminiature light-near infrared optical fiber spectrograph to gather near infrared spectrum, and spectrogrph probe is can immersion transmittance probes.
Wherein the Pretreated spectra described in step (3) is that first derivative, second dervative, standardization normalized (SNV), multiplicative scatter correction (MSC) processing method carry out pretreatment.
Wherein the selection in the optimal spectrum interval described in step (4) refers to the DH adopting the interval least-squares regression approach (Si-PLS) of associating to gluten protein, and the peptide concentration of hydrolyzed solution and the optimal spectrum interval of ACE suppression ratio select.
Wherein model described in step (5) is set up and prediction refers to and sample sets is divided into calibration set (59), it was predicted that collection (29) adopts the interval least-squares regression approach (Si-PLS) of associating to set up correction and forecast model.
Wherein described in step (6), utilize above-mentioned forecast model that enzymolysis process carries out original position to monitor in real time and refer to, an enzymolysis process outside to modeling carries out the monitoring of In situ spectroscopic, DH in prediction enzymolysis process, the peptide concentration of enzymolysis solution and ACE suppression ratio, comparison prediction value and measured value, calculate residual error.
The invention has the beneficial effects as follows:
Utilize the method based on original position real time spectrum on-line monitoring gluten protein enzymolysis process, it is possible to the important indicator (DH, enzymolysis solution peptide concentration, ACE suppression ratio) in the monitoring proteolysis course of reaction that enzymolysis reactor situ is real-time. With gluten protein for sample, adopt original position real time spectrum response system, Matlab2009b and the interval method of least square (Si-PLS) of associating is utilized to set up model, using correlation coefficient and relative error as measurement index, establish gluten protein DH, enzymolysis solution peptide concentration, the regression model of ACE suppression ratio. The coefficient R of DH forecast model is 0.9570, and residual error is 1.73%; The coefficient R of peptide concentration is 0.9840, and residual error is 0.79mg/mL; The coefficient R of ACE suppression ratio is 0.9536, and residual error is 5.12%; Utilize forecast model that the enzymolysis process of the gluten protein suspension that concentration of substrate is 10g/L is monitored, it was predicted that value and the measured value goodness of fit are higher.
Accompanying drawing illustrates:
Fig. 1 is original position real time spectrum on-line monitoring gluten protein enzymolysis process quantitative model analysis process figure of the present invention;
Fig. 2 is the original position real time spectrum on-line monitoring gluten protein enzymolysis process device used in the present invention; Wherein 1 is enzyme digestion reaction pond, and 2 is gluten protein suspension, and 3 is thermometer, and 4 is agitating device, and 5 pop one's head in for immersion transmitted ray, and 6 is halogen tungsten lamp light source, and 7 is microminiature near infrared spectrometer, and 8 is signal collecting and controlling system.
Detailed description of the invention:
Fig. 1 is original position real time spectrum on-line monitoring gluten protein enzymolysis process quantitative model analysis process figure of the present invention;
The present invention represents the change of whole enzyme digestion reaction process with the change of the peptide concentration in degree of hydrolysis (DH), enzymolysis solution, the ACE suppression ratio of enzymolysis solution.
The mensuration of DH adopts pH-stat method; The mensuration of enzymolysis solution peptide concentration adopts good fortune beautiful jade phenol method, the mensuration of enzymatic hydrolysate ACE suppression ratio carries out according to document " Jiaetal..TheuseofultrasoundforenzymaticpreparationofACE-inhibitorypeptidesfromwheatgermprotein.FoodChem.119,336 (2010) ".
Concrete mensuration process is as follows:
(1) with distilled water prepare respectively concentration of substrate 20,30,40, the gluten protein suspension 1500mL of the 50g/L method described in 1.3.2 carry out enzymolysis, enzymolysis time 80 minutes, within first 20 minutes, took a sample at interval of 2 minutes, within latter 60 minutes, took a sample at interval of 5 minutes, each sampling amount is 1mL, rapidly with boiling water bath enzyme denaturing 10min, the centrifugal 10min of 10000g after cooling after sampling, collect supernatant and be stored at 4 DEG C to be measured. While sampling, reaction tank carries out the collection of original position real time spectrum. Amount to 88 samples.
(2) gluten protein DH, peptide concentration, the determined off-line of ACE suppression ratio: the assay method of peptide concentration is for dilute 50 times respectively by above-mentioned sample, equal proportion volume adds the trichloroacetic acid of 15%, the water-bath of 30 DEG C is reacted 30min, the centrifugal 10min of 5000g, to remove high molecular weight protein, collects supernatant and measures peptide concentration according to Forint phenol method; The assay method of DH is with reference to pH-state method; In enzymatic hydrolysate, the assay method of ACE suppression ratio is with reference to the liquid chromatography of Jiaetal..
Fig. 2 is the original position real time spectrum on-line monitoring gluten protein enzymolysis process device used in the present invention. 1 is enzyme digestion reaction pond, and 2 is gluten protein suspension, and 3 is thermometer, and 4 is agitating device, and 5 pop one's head in for immersion transmitted ray, and 6 is halogen tungsten lamp light source, and 7 is microminiature near infrared spectrometer, and 8 is signal collecting and controlling system. During whole system work, enzyme digestion reaction pond 1 carries out the enzymolysis of gluten protein suspension, open agitating device 4, immersion transmitted ray is popped one's head in and 5 stretches in gluten protein suspension 2 and fix, halogen tungsten lamp light source 6 send light source and be transmitted to immersion transmitted ray probe 5 collected specimens spectrum in enzyme digestion reaction pond and feed back in microminiature near infrared spectrometer 7 and be acquired by signal collecting and controlling system 8 and store.
(3) collection of gluten protein enzymolysis process situ real time spectrum: use NIRQUEST256-2.5 type near-infrared micro spectrometer (U.S.'s marine optics) of ocean company to gather the near infrared spectrum of enzymolysis solution in enzymolysis process in conjunction with TP300 transmission immersion fibre-optical probe, adopt indium GaAs (InGaAs) detector that near infrared light sensitivity is the highest, spectral region 800-2500nm. Concrete spectra collection condition is: with distilled water for background, transmission mode, and the light path of 2mm gathers the near infrared light spectrogram of enzymolysis solution in enzymolysis process, scanning times is 16 times, resolution 9.5nm, signal to noise ratio is 10000:1, altogether containing 256 variablees in the near infrared spectrum region of 800-2500nm. 3 spectrum of each sample continuous acquisition, take its meansigma methods original spectrum as this sample.
(4) pretreatment of gluten protein enzymolysis process situ real time spectrum: analyze software with Matlab2009b, respectively spectrum is carried out SNV, MSC, 1 order derivative, 2 order derivative pretreatment, model with method of least square PLS, obtain optimum preprocessing procedures. The modeling result of final SNV preprocess method is better than other preprocess methods. Details are in Table 1.
The optimum of the monitoring index model of table 1 different pretreatments spectrum
(5) foundation of calibration model: the spectrum SNV preprocess method of 88 samples is carried out pretreatment, is divided into calibration set (59) and (29) two parts of forecast set. The chemometrics algorithm adopted is the interval least square regression (Si-PLS) of associating, cross validation is carried out through leaving-one method, being respectively directed to the DH of gluten protein, the peptide concentration of enzymolysis solution and ACE suppression ratio filter out the spectrum range of the best, set up its calibration model and forecast model. Result shows: the DH in gluten protein enzymolysis process, and the peptide concentration of enzymolysis solution and the Si-PLS model of ACE suppression ratio have good estimated performance, and details are in Table 2.
The selection of monitoring index spectrum range and modeling result in table 2 enzymolysis process
(6) prediction of enzymolysis process: preparing concentration of substrate with distilled water is that the gluten protein suspension 1500mL of 10g/L method described in (1) carries out enzymolysis, and gathers spectrum. The spectrum of collection is brought in the forecast model set up in (5), the DH in gluten protein enzyme digestion reaction process, the peptide concentration of enzymolysis solution and ACE suppression ratio are predicted, then predictive value and actual value are compared. Details are in Table 3.
Table 3 enzymolysis process predicts the outcome
Table 3 shows, utilizes Matlab2009b and the interval method of least square (Si-PLS) of associating to set up model, using correlation coefficient and relative error as measurement index, establishes gluten protein DH, enzymolysis solution peptide concentration, the regression model of ACE suppression ratio. The coefficient R of DH forecast model is 0.9570, and residual error is 1.73%; The coefficient R of peptide concentration is 0.9840, and residual error is 0.79mg/mL; The coefficient R of ACE suppression ratio is 0.9536, and residual error is 5.12%; Utilize forecast model that the enzymolysis process of the gluten protein suspension that concentration of substrate is 10g/L is monitored, it was predicted that value and the measured value goodness of fit are higher. Utilize spectral information to substitute into the predictive value that draws of model and actual measured value has the higher goodness of fit, (5) the Si-PLS forecast model set up in can well predict the enzymolysis process of gluten protein, for the enzymolysis process of on-line real time monitoring gluten protein.
Claims (7)
1. based on the apparatus and method of original position real time spectrum on-line monitoring protease solution preocess, it is characterised in that carry out as steps described below:
(1) gluten protein carrying out enzymolysis, enzymolysis process timing sampling, chemical method monitors its enzymolysis process;
(2) collected enzymolysis solution is quickly gathered the real-time near infrared spectrum of its original position;
(3) Pretreated spectra;
(4) screening that optimal spectrum is interval;
(5) model is set up and prediction;
(6) utilize above-mentioned forecast model that protease solution preocess is carried out original position real-time estimate.
2. the apparatus and method based on original position real time spectrum on-line monitoring protease solution preocess according to claim 1, it is characterized in that wherein gluten protein enzymolysis described in step (1) is concentration of substrate is 20-50g/L gluten protein suspension, enzyme concentration 6460U/g, hydrolysis temperature 50 DEG C, enzymolysis time 0-80min; Enzymolysis process index is the ACE suppression ratio of the concentration of polypeptide in gluten protein degree of hydrolysis, enzymolysis solution and enzymolysis solution.
3. the apparatus and method based on original position real time spectrum on-line monitoring protease solution preocess according to claim 1, it is characterized in that wherein the described original position real time spectrum of step (2) adopts microminiature light-near infrared optical fiber spectrograph to gather near infrared spectrum, spectrogrph probe is can immersion transmittance probes.
4. the apparatus and method based on original position real time spectrum on-line monitoring protease solution preocess according to claim 1, it is characterised in that wherein the Pretreated spectra described in step (3) is that first derivative, second dervative, standardization normalized (SNV), multiplicative scatter correction (MSC) processing method carry out pretreatment.
5. the apparatus and method based on original position real time spectrum on-line monitoring protease solution preocess according to claim 1, it is characterised in that wherein the selection in the optimal spectrum interval described in step (4) refers to that the optimal spectrum interval of DH, peptide concentration and ACE suppression ratio is selected by the interval least-squares regression approach (Si-PLS) of employing associating.
6. the apparatus and method based on original position real time spectrum on-line monitoring protease solution preocess according to claim 1, it is characterized in that wherein model described in step (5) is set up and prediction refers to and sample sets is divided into calibration set (59), it was predicted that collection (29) adopts the interval least-squares regression approach (Si-PLS) of associating to set up correction and forecast model.
7. the apparatus and method based on original position real time spectrum on-line monitoring protease solution preocess according to claim 1, it is characterized in that wherein described in step (6), utilize above-mentioned forecast model that enzymolysis process carries out original position to monitor in real time and refer to, an enzymolysis process outside to modeling carries out the monitoring of In situ spectroscopic, DH in prediction enzymolysis process, the peptide concentration of enzymolysis solution and ACE suppression ratio, comparison prediction value and measured value, calculate residual error, protease solution preocess can be carried out original position real-time estimate��
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| PCT/CN2016/071579 WO2017107278A1 (en) | 2015-12-21 | 2016-01-21 | In-situ real-time spectrum based on-line protein enzymatic hydrolysis monitoring method and device |
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| CN106701846B (en) * | 2017-01-18 | 2020-09-18 | 华东理工大学 | Method for producing sodium gluconate by on-line monitoring and optimizing aspergillus niger fermentation |
| CN106701846A (en) * | 2017-01-18 | 2017-05-24 | 华东理工大学 | Method for on-line monitoring and optimization of aspergillus niger fermentation production of sodium gluconate |
| CN106967785A (en) * | 2017-02-27 | 2017-07-21 | 江苏科技大学 | A kind of enzymatic isolation method produces the method for real-time monitoring of blood sugar reducing peptide process |
| CN106967785B (en) * | 2017-02-27 | 2020-09-18 | 江苏科技大学 | Real-time monitoring method for process of producing hypoglycemic peptide by enzymolysis method |
| CN106832012A (en) * | 2017-03-31 | 2017-06-13 | 山东福洋生物科技有限公司 | A kind of production control method and preparation method of the converted starch of particular characteristic |
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| CN112903627A (en) * | 2021-03-06 | 2021-06-04 | 中国烟草总公司郑州烟草研究院 | Method for online determination of biological enzyme activity in tobacco processing process |
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| CN113189043B (en) * | 2021-05-13 | 2023-06-06 | 大连工业大学 | Real-time online monitoring method for euphausia superba enzymolysis reaction |
| CN114283896A (en) * | 2021-12-23 | 2022-04-05 | 江南大学 | Modeling method for monitoring component change model in enzymatic reaction process |
| CN114283896B (en) * | 2021-12-23 | 2022-11-18 | 江南大学 | Modeling method for monitoring component change model in enzymatic reaction process |
| CN115074409A (en) * | 2022-08-18 | 2022-09-20 | 意润健康产业（广州）有限公司 | Micromolecule active peptide separation and purification system based on organic animal and plant raw materials |
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| Publication number | Publication date |
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| CN105628644B (en) | 2019-08-27 |
| WO2017107278A1 (en) | 2017-06-29 |
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