CN105628644B - Device and method based on real time spectrum in situ on-line monitoring protease solution preocess - Google Patents
Device and method based on real time spectrum in situ on-line monitoring protease solution preocess Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 78
- 238000001228 spectrum Methods 0.000 title claims abstract description 44
- 238000011065 in-situ storage Methods 0.000 title claims abstract description 31
- 238000012544 monitoring process Methods 0.000 title claims abstract description 24
- 108091005804 Peptidases Proteins 0.000 title claims abstract description 8
- 239000004365 Protease Substances 0.000 title claims abstract description 8
- 102100037486 Reverse transcriptase/ribonuclease H Human genes 0.000 title claims abstract description 8
- 108010068370 Glutens Proteins 0.000 claims abstract description 38
- 239000007788 liquid Substances 0.000 claims abstract description 27
- 108090000765 processed proteins & peptides Proteins 0.000 claims abstract description 26
- 230000002401 inhibitory effect Effects 0.000 claims abstract description 20
- 238000006243 chemical reaction Methods 0.000 claims abstract description 15
- 239000000725 suspension Substances 0.000 claims abstract description 11
- 230000007062 hydrolysis Effects 0.000 claims abstract description 8
- 238000006460 hydrolysis reaction Methods 0.000 claims abstract description 8
- 238000005070 sampling Methods 0.000 claims abstract description 8
- 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
- 239000000523 sample Substances 0.000 claims description 16
- 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 6
- 108090000790 Enzymes Proteins 0.000 claims description 6
- 238000012937 correction Methods 0.000 claims description 5
- 230000007071 enzymatic hydrolysis Effects 0.000 claims description 5
- 238000006047 enzymatic hydrolysis reaction Methods 0.000 claims description 5
- 238000013459 approach Methods 0.000 claims description 4
- 229920001184 polypeptide Polymers 0.000 claims description 4
- 102000004196 processed proteins & peptides Human genes 0.000 claims description 4
- 238000003672 processing method Methods 0.000 claims description 3
- 206010034960 Photophobia Diseases 0.000 claims description 2
- 229910052738 indium Inorganic materials 0.000 claims description 2
- APFVFJFRJDLVQX-UHFFFAOYSA-N indium atom Chemical compound [In] APFVFJFRJDLVQX-UHFFFAOYSA-N 0.000 claims description 2
- 208000013469 light sensitivity Diseases 0.000 claims description 2
- GYHNNYVSQQEPJS-UHFFFAOYSA-N Gallium Chemical compound [Ga] GYHNNYVSQQEPJS-UHFFFAOYSA-N 0.000 claims 1
- 229910052733 gallium Inorganic materials 0.000 claims 1
- 238000005259 measurement Methods 0.000 description 8
- 238000001976 enzyme digestion Methods 0.000 description 7
- 230000003595 spectral effect Effects 0.000 description 5
- 239000000047 product Substances 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
- 239000012153 distilled water Substances 0.000 description 3
- 230000002255 enzymatic effect Effects 0.000 description 3
- 235000013305 food Nutrition 0.000 description 3
- 229910052736 halogen Inorganic materials 0.000 description 3
- 239000013307 optical fiber Substances 0.000 description 3
- 239000006228 supernatant Substances 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
- 241000209140 Triticum Species 0.000 description 2
- 235000021307 Triticum Nutrition 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 230000036772 blood pressure Effects 0.000 description 2
- 230000009849 deactivation Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 150000002367 halogens Chemical class 0.000 description 2
- 239000000413 hydrolysate Substances 0.000 description 2
- 238000002955 isolation Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 235000018102 proteins Nutrition 0.000 description 2
- 102000004169 proteins and genes Human genes 0.000 description 2
- 108090000623 proteins and genes Proteins 0.000 description 2
- 230000017854 proteolysis Effects 0.000 description 2
- 239000000243 solution Substances 0.000 description 2
- WFKWXMTUELFFGS-UHFFFAOYSA-N tungsten Chemical compound [W] WFKWXMTUELFFGS-UHFFFAOYSA-N 0.000 description 2
- 102000015427 Angiotensins Human genes 0.000 description 1
- 108010064733 Angiotensins Proteins 0.000 description 1
- 101000984728 Chiropsoides quadrigatus Angiotensin-converting enzyme inhibitory peptide Proteins 0.000 description 1
- 229910001218 Gallium arsenide Inorganic materials 0.000 description 1
- 229920002472 Starch Polymers 0.000 description 1
- 244000269722 Thea sinensis 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
- 238000005119 centrifugation Methods 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 238000011437 continuous method Methods 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
- 238000006911 enzymatic reaction Methods 0.000 description 1
- 238000000855 fermentation Methods 0.000 description 1
- 230000004151 fermentation Effects 0.000 description 1
- 230000002209 hydrophobic effect Effects 0.000 description 1
- 230000001077 hypotensive effect Effects 0.000 description 1
- 230000005764 inhibitory process Effects 0.000 description 1
- 239000010977 jade Substances 0.000 description 1
- 238000004811 liquid chromatography Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 229910052757 nitrogen Inorganic materials 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000002203 pretreatment Methods 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
- 235000019698 starch Nutrition 0.000 description 1
- 239000008107 starch Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000001629 suppression Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000002834 transmittance 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
- -1 tungsten halogen Chemical class 0.000 description 1
- 238000002604 ultrasonography Methods 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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Abstract
The invention discloses the device and method based on real time spectrum in situ on-line monitoring protease solution preocess, belong to protease solution preocess on-line monitoring field.The gluten protein suspension of various concentration is digested, enzymolysis process timing sampling, chemical method monitors the important parameter in enzymolysis process, degree of hydrolysis, the peptide concentration of enzymolysis liquid, the ACE inhibiting rate of enzymolysis liquid；Its real time spectrum in situ is quickly acquired to collected enzymolysis liquid；Spectrum collected is pre-processed；Using joint section least square method degree of being hydrolyzed, the peptide concentration of enzymolysis liquid, the screening in the optimal spectrum section of the ACE inhibiting rate of enzymolysis liquid；Calibration model and prediction model are established using joint section least square method；The judgement of real-time monitoring and reaction end in situ is carried out to enzymolysis process using above-mentioned prediction model.It is monitored using enzymolysis process of the prediction model to the gluten protein suspension that concentration of substrate is 10 g/L, predicted value and the measured value goodness of fit are higher.
Description
Technical field:
The present invention relates to protease solution preocess to monitor field on-line, refers in particular to one kind and is existed based near infrared spectrum in real time in situ
A kind of technology of line monitoring gluten protein enzymolysis process.
Background technique:
Wheat gluten protein is the by-product of starch processing, and protein content is up to 85%, is rich in hydrophobic amino acid, is one
The very potential enzymatic isolation method of kind prepares the raw material of blood pressure lowering peptide.During enzymatic isolation method prepares blood pressure lowering peptide, the hydrolysis of albumen
The ACE of the concentration of polypeptide and characterization hydrolysate hypotensive activity in degree DH (Degree of hydrolysis), hydrolysate
Inhibiting rate (The inhibition on angiotensin converting-I enzyme inhibitory) is to close very much
Three indexs of key, are the important evidences for judging enzyme digestion reaction terminal.When traditional chemical gauging DH, need to introduce NaOH,
The quality of final polypeptide products is influenced to a certain extent.And the peptide concentration and ACE of conventional offline measurement hydrolyzate inhibit to live
Property when need the enzyme deactivation by sampling from reactor, the complicated procedures such as centrifugation, heavy workload and due to having left reactive site and
It cannot obtain accurate result.Therefore a kind of quick, continuous method monitoring enzymatic hydrolysis in situ in enzymolysis reactor is needed
Important parameter in reaction, to judge enzyme digestion reaction terminal.
Currently, general on-line measurement and control system are only limitted to temperature, pressure and flow etc., and to chemical component in the process
Effectively continuous measurement is not can be carried out still with many physical property variables, therefore, online spectral technique comes into being, it is with live shape
Spectrum sensing technology based on microphysics amount and mi-crochemistry amount on the basis of molecular level under condition, relies on mini optical fibre
The use of spectrometer plays important work in the process monitoring of the industrial departments such as chemical industry, pharmacy, light industry and high molecular material
With.For current this microminiature portable near infrared spectrometer combination fibre-optical probe since its is at low cost, speed is fast, pollution-free, just
In real-time, on-line analysis and control the advantages that.In recent years, spectrum monitoring means were widely used in the mistake in food processing process
Range monitoring and quality determination.Such as the on-line monitoring (publication number: CN103616383A) of Bacterial community in Food fermentation processes, it is 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 utilization
Visible-to-Near InfaRed diffuse spectral technology detection fresh tea leaves nitrogen content method (publication number: CN101382488A).But mesh
These preceding methods can't smoothly be applied to the reaction system of aqueous solution.
It is a kind of suitable for real-time monitoring enzyme in situ enzymolysis reactor the present invention is directed to be established using online spectral technique
The method for solving reaction, quickly to judge the terminal of enzyme digestion reaction.
Summary of the invention:
The purpose of the present invention is using the optical fiber of near infrared spectrometer combination in real time in situ can immersion cell, establish one kind and exist
The method of line monitoring gluten protein enzymolysis process.The quick of proteolysis process is aimed at, in situ, real-time monitoring.The present invention
A method of gluten protein enzymolysis process is monitored on-line based on real time spectrum in situ, is carried out as steps described below:
(1) gluten protein is digested, enzymolysis process timing sampling, chemical method monitors its enzymolysis process.
(2) its real-time near infrared spectrum in situ is quickly acquired to collected enzymolysis liquid；
(3) Pretreated spectra；
(4) screening in optimal spectrum section；
(5) model foundation and prediction；
(6) prediction in real time in situ is carried out to enzymolysis process using above-mentioned prediction model
It is 20-50g/L gluten protein suspension that wherein the enzymatic hydrolysis of gluten protein described in step (1), which is concentration of substrate, enzyme
Measure 6460U/g, 50 DEG C of hydrolysis temperature, enzymolysis time 0-80min.Enzymolysis process index is gluten protein degree of hydrolysis, in enzymolysis liquid
Peptide concentration and enzymolysis liquid ACE inhibiting rate.
Wherein step (2) real time spectrum in situ acquires near infrared spectrum using microminiature light-near infrared optical fiber spectrograph,
Spectrometer probe is can immersion transmittance probes.
Wherein Pretreated spectra described in step (3) be first derivative, second dervative, standardization normalized (SNV),
Multiplicative scatter correction (MSC) processing method is pre-processed.
Wherein the selection in optimal spectrum section described in step (4) refers to using joint section least-squares regression approach
(Si-PLS) DH of gluten protein, the peptide concentration of hydrolyzate and the optimal spectrum section of ACE inhibiting rate are selected.
Wherein model foundation and prediction described in step (5), which refer to, is divided into calibration set (59), forecast set (29 for sample sets
It is a) using joint section least-squares regression approach (Si-PLS) foundation correction and prediction model.
Wherein described in step (6), real-time monitoring in situ is carried out to enzymolysis process using above-mentioned prediction model and is referred to, to building
An enzymolysis process outside mould carries out the monitoring of In situ spectroscopic, predicts the DH in enzymolysis process, the peptide concentration and ACE of enzymolysis liquid
Inhibiting rate, comparison prediction value and measured value calculate residual error.
The beneficial effects of the present invention are:
It, can be in enzymolysis reactor using the method based on real time spectrum in situ on-line monitoring gluten protein enzymolysis process
Important indicator (DH, enzymolysis liquid peptide concentration, ACE inhibiting rate) in the proteolysis reaction process of monitoring in real time in situ.With paddy
PrPC is sample, using real time spectrum reaction system in situ, utilizes Matlab2009b and joint section least square method
(Si-PLS) model is established, using related coefficient and relative error as measurement index, establishes gluten protein DH, enzymolysis liquid is more
Peptide concentration, the regression model of ACE inhibiting rate.The coefficient R of DH prediction model is 0.9570, residual error 1.73%；Polypeptide is dense
The coefficient R of degree is 0.9840, residual error 0.79mg/mL；The coefficient R of ACE inhibiting rate is 0.9536, and residual error is
5.12%；It is monitored using enzymolysis process of the prediction model to the gluten protein suspension that concentration of substrate is 10g/L, predicted value
It is higher with the measured value goodness of fit.
Detailed description of the invention:
Fig. 1 is that present invention real time spectrum in situ monitors gluten protein enzymolysis process quantitative model analysis flow chart diagram on-line；
Fig. 2 is that original position real time spectrum used in the present invention monitors gluten protein enzymolysis process device on-line；Wherein 1 is enzyme
Reaction tank is solved, 2 be gluten protein suspension, and 3 be thermometer, and 4 be agitating device, and 5 pop one's head in for immersion transmitted ray, and 6 be halogen
Tungsten light source, 7 be microminiature near infrared spectrometer, and 8 be signal collecting and controlling system.
Specific embodiment:
Fig. 1 is that present invention real time spectrum in situ monitors gluten protein enzymolysis process quantitative model analysis flow chart diagram on-line；
It is indicated in the present invention with the variation of the ACE inhibiting rate of peptide concentration, enzymolysis liquid in degree of hydrolysis (DH), enzymolysis liquid
The variation of entire enzyme digestion reaction process.
The measurement of DH uses pH-stat method；The measurement of enzymolysis liquid peptide concentration uses good fortune beautiful jade phenol method, enzymolysis product ACE suppression
The measurement of rate processed is according to document " Jia et al..The use of ultrasound for enzymatic preparation
Of ACE-inhibitory peptides from wheat germ protein.Food Chem.119,336 (2010) " into
Row.
Specific continuous mode is as follows:
(1) prepared respectively with distilled water concentration of substrate 20,30,40, the gluten protein suspension 1500mL of 50g/L according to
1.3.2 the method described in is digested, enzymolysis time 80 minutes, first 20 minutes at interval of taking within 2 minutes a sample, latter 60 points
Clock took a sample at interval of 5 minutes, and each sampling amount is 1mL, boiling water bath enzyme deactivation 10min was used after sampling rapidly, after cooling
10000g is centrifuged 10min, and collection supernatant is stored in be measured at 4 DEG C.While sampling, Real-Time Optical in situ is carried out in reaction tank
The acquisition of spectrum.Amount to 88 samples.
(2) gluten protein DH, peptide concentration, the determined off-line of ACE inhibiting rate: the measuring method of peptide concentration is will be above-mentioned
Sample dilutes 50 times respectively, the trichloroacetic acid of equal proportion volume addition 15%, reacts 30min in 30 DEG C of water-bath, 5000g from
Heart 10min collects supernatant according to Forint phenol method and measures peptide concentration to remove high molecular weight protein；The measuring method of DH refers to
PH-state method；Liquid chromatography of the measuring method of ACE inhibiting rate referring to Jia et al. in enzymolysis product.
Fig. 2 is that original position real time spectrum used in the present invention monitors gluten protein enzymolysis process device on-line.1 is anti-for enzymatic hydrolysis
Ying Chi, 2 be gluten protein suspension, and 3 be thermometer, and 4 be agitating device, and 5 pop one's head in for immersion transmitted ray, and 6 be tungsten halogen lamp
Light source, 7 be microminiature near infrared spectrometer, and 8 be signal collecting and controlling system.When whole system works, in enzyme digestion reaction pond 1
The middle enzymatic hydrolysis for carrying out gluten protein suspension, opens agitating device 4, and immersion transmitted ray probe 5 is protruded into gluten protein and is hanged
It is in supernatant liquid 2 and fixed, immersion transmitted ray probe 5 is transmitted to by the sending light source of halogen tungsten lamp light source 6 and is adopted in enzyme digestion reaction pond
Collection sample spectra feedback is acquired and stores into microminiature near infrared spectrometer 7 and by signal collecting and controlling system 8.
(3) in gluten protein enzymolysis process in situ real time spectrum acquisition: use the NIRQUEST256-2.5 of ocean company
Type near-infrared micro spectrometer (U.S.'s marine optics) combines to be digested in TP300 transmission immersion fibre-optical probe acquisition enzymolysis process
The near infrared spectrum of liquid, using near infrared light sensitivity highest indium GaAs (InGaAs) detector, spectral region 800-
2500nm.Specific spectra collection condition are as follows: using distilled water as background, transmission mode, the light path of 2mm acquires to be digested in enzymolysis process
The atlas of near infrared spectra of liquid, scanning times are 16 times, resolution ratio 9.5nm, signal-to-noise ratio 10000:1, in the close of 800-2500nm
Contain 256 variables in IR regions altogether.3 spectrum of each sample continuous acquisition, take its average value as the original of the sample
Beginning spectrum.
(4) in gluten protein enzymolysis process in situ real time spectrum pretreatment: analyze software with Matlab 2009b, respectively
SNV, MSC, 1 order derivative are carried out to spectrum, it is pre- to obtain optimal spectrum with least square method PLS modeling for the pretreatment of 2 order derivatives
Processing method.The modeling result of final SNV preprocess method is better than other preprocess methods.Details are shown in Table 1.
The optimum of the monitoring index model of 1 different pretreatments spectrum of table
(5) foundation of calibration model: the spectrum of 88 samples is pre-processed with SNV preprocess method, is divided into correction
Collect (59) and (29) two parts of forecast set.The chemometrics algorithm used is joint section least square regression (Si-
PLS), cross validation is carried out through leaving-one method, is directed to the DH of gluten protein, the peptide concentration and ACE inhibiting rate of enzymolysis liquid respectively
Optimal spectrum range is filtered out, its calibration model and prediction model are established.As the result is shown: in gluten protein enzymolysis process
DH, the peptide concentration of enzymolysis liquid and the Si-PLS model of ACE inhibiting rate have good estimated performance, and details are shown in Table 2.
The selection of monitoring index spectrum range and modeling result in 2 enzymolysis process of table
(6) prediction of enzymolysis process: with distilled water prepare concentration of substrate be 10g/L gluten protein suspension 1500mL by
It is digested according to method described in (1), and acquires spectrum.The spectrum of acquisition is brought into the prediction model established in (5)
In, the peptide concentration and ACE inhibiting rate of DH, enzymolysis liquid during gluten protein enzyme digestion reaction are predicted, then will prediction
Value is compared with actual value.Details are shown in Table 3.
3 enzymolysis process prediction result of table
Table 3 is shown, model is established using Matlab2009b and joint section least square method (Si-PLS), with phase relation
Several and relative error establishes gluten protein DH, enzymolysis liquid peptide concentration, the regression model of ACE inhibiting rate as measurement index.
The coefficient R of DH prediction model is 0.9570, residual error 1.73%；The coefficient R of peptide concentration is 0.9840, and residual error is
0.79mg/mL；The coefficient R of ACE inhibiting rate is 0.9536, residual error 5.12%；It is to concentration of substrate using prediction model
The enzymolysis process of the gluten protein suspension of 10g/L is monitored, and predicted value and the measured value goodness of fit are higher.Utilize spectral information
The predicted value and actual measured value that substitution model obtains have the higher goodness of fit, and the Si-PLS prediction model established in (5) can
Enzymolysis process to predict the enzymolysis process of gluten protein well, for on-line real time monitoring gluten protein.
Claims (1)
1. based on real time spectrum in situ on-line monitoring protease solution preocess method, it is characterised in that as steps described below into
Row:
(1) gluten protein is digested, enzymolysis process timing sampling, chemical method monitors its enzymolysis process；
(2) while sampling, its real-time near infrared spectrum in situ is quickly acquired to enzymolysis liquid in reaction tank；
(3) Pretreated spectra；
(4) screening in optimal spectrum section；
(5) model foundation and prediction；
(6) prediction in real time in situ is carried out to protease solution preocess using above-mentioned prediction model；
It is 20-50 g/L gluten protein suspension, enzyme concentration that wherein the enzymatic hydrolysis of gluten protein described in step (1), which is concentration of substrate,
6460 U/g, 50 DEG C of hydrolysis temperature, enzymolysis time 0-80 min；Enzymolysis process index is gluten protein degree of hydrolysis, in enzymolysis liquid
The concentration of polypeptide and the ACE inhibiting rate of enzymolysis liquid；
Wherein described its near infrared spectrum in real time in situ that quickly acquires to enzymolysis liquid of step (2) refers to using NIRQUEST256-
2.5 type near-infrared micro spectrometer combination TP300 transmit the near-infrared of enzymolysis liquid in immersion fibre-optical probe acquisition enzymolysis process
Spectrum, using to the highest indium gallium arsinide detectors of near infrared light sensitivity,
Wherein Pretreated spectra described in step (3) is first derivative, second dervative, standardizes normalized (SNV), is polynary
Scatter correction (MSC) processing method is pre-processed；
Wherein the selection in optimal spectrum section described in step (4) refers to using joint section least-squares regression approach (Si-
PLS) the optimal spectrum section of DH, peptide concentration and ACE inhibiting rate are selected；
Wherein model foundation and prediction described in step (5), which refer to, is divided into calibration set 59 for sample sets, forecast set 29, uses
Joint section least-squares regression approach (Si-PLS) establishes correction and prediction model；
Wherein described in step (6), real-time monitoring in situ is carried out to enzymolysis process using above-mentioned prediction model and is referred to, it is outer to modeling
An enzymolysis process carry out the monitoring of In situ spectroscopic, predict that the DH in enzymolysis process, the peptide concentration and ACE of enzymolysis liquid inhibit
Rate, comparison prediction value and measured value calculate residual error, and prediction in real time in situ can be carried out to protease solution preocess.
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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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| 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 |
| WO2019091471A1 (en) * | 2017-11-13 | 2019-05-16 | 江苏大学 | Preparation of macromolecular polypeptide based on gastrointestinal digestion and method for in situ real-time monitoring process of same |
| CN110243782A (en) * | 2019-06-27 | 2019-09-17 | 江苏江大五棵松生物科技有限公司 | The ultrasound-enhanced extraction process INSITU REAL TIME of walnut protein based on sulfydryl |
| CN111474134A (en) * | 2020-04-24 | 2020-07-31 | 驻马店华中正大有限公司 | Method for controlling butyric acid fermentation by using online near infrared |
| CN112903627B (en) * | 2021-03-06 | 2023-01-24 | 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 |
| CN113189043B (en) * | 2021-05-13 | 2023-06-06 | 大连工业大学 | Real-time online monitoring method for euphausia superba enzymolysis reaction |
| CN114283896B (en) * | 2021-12-23 | 2022-11-18 | 江南大学 | Modeling method for monitoring component change model in enzymatic reaction process |
| CN115074409B (en) * | 2022-08-18 | 2022-12-06 | 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 |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101339186A (en) * | 2008-08-07 | 2009-01-07 | 中国科学院过程工程研究所 | Method for on-line detection for solid-state biomass bioconversion procedure |
| CN103558180A (en) * | 2013-11-04 | 2014-02-05 | 安徽古井贡酒股份有限公司 | Method for quickly detecting physicochemical indexes in saccharification leavening agents through near infrared |
| CN104774894A (en) * | 2015-03-27 | 2015-07-15 | 江苏大学 | Method for preparing gluten ACE inhibitory peptide through multi-mode ultrasonic wave strengthened enzymolysis |
| CN104846046A (en) * | 2015-01-30 | 2015-08-19 | 江苏大学 | Method for preparing gluten antihypertensive peptide based on sequential ultrasonic enhanced enzymolysis |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN103558180A (en) * | 2013-11-04 | 2014-02-05 | 安徽古井贡酒股份有限公司 | Method for quickly detecting physicochemical indexes in saccharification leavening agents through near infrared |
| CN104846046A (en) * | 2015-01-30 | 2015-08-19 | 江苏大学 | Method for preparing gluten antihypertensive peptide based on sequential ultrasonic enhanced enzymolysis |
| CN104774894A (en) * | 2015-03-27 | 2015-07-15 | 江苏大学 | Method for preparing gluten ACE inhibitory peptide through multi-mode ultrasonic wave strengthened enzymolysis |
Non-Patent Citations (2)
| Title |
|---|
| 特征谱区筛选在近红外光谱检测茶叶游离氨基酸含量中的应用;郭志明等;《光学 精密工程》;20090831;第1839-1844页 * |
| 超声辅助酶解谷朊粉制备 ＡＣＥ抑制肽工艺优化;刘树兴等;《陕西科技大学学报》;20141231;第110-114页 * |
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