CN113189043A - Real-time online monitoring method for enzymolysis reaction of euphausia superba - Google Patents
Real-time online monitoring method for enzymolysis reaction of euphausia superba Download PDFInfo
- Publication number
- CN113189043A CN113189043A CN202110520644.3A CN202110520644A CN113189043A CN 113189043 A CN113189043 A CN 113189043A CN 202110520644 A CN202110520644 A CN 202110520644A CN 113189043 A CN113189043 A CN 113189043A
- Authority
- CN
- China
- Prior art keywords
- enzymolysis
- antarctic krill
- real
- reaction
- euphausia superba
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000006243 chemical reaction Methods 0.000 title claims abstract description 74
- 238000000034 method Methods 0.000 title claims abstract description 62
- 238000012544 monitoring process Methods 0.000 title claims abstract description 49
- 241000239370 Euphausia superba Species 0.000 title claims abstract description 43
- 241000239366 Euphausiacea Species 0.000 claims abstract description 89
- 238000006460 hydrolysis reaction Methods 0.000 claims abstract description 58
- 230000007062 hydrolysis Effects 0.000 claims abstract description 57
- 238000002329 infrared spectrum Methods 0.000 claims abstract description 38
- 230000002255 enzymatic effect Effects 0.000 claims abstract description 32
- 108090000765 processed proteins & peptides Proteins 0.000 claims abstract description 27
- 239000000413 hydrolysate Substances 0.000 claims abstract description 26
- 238000001228 spectrum Methods 0.000 claims abstract description 23
- 239000007788 liquid Substances 0.000 claims abstract description 19
- 238000005516 engineering process Methods 0.000 claims abstract description 13
- 238000001514 detection method Methods 0.000 claims abstract description 12
- 238000006047 enzymatic hydrolysis reaction Methods 0.000 claims abstract description 12
- 230000007071 enzymatic hydrolysis Effects 0.000 claims abstract description 11
- 238000002790 cross-validation Methods 0.000 claims abstract description 7
- 108010009736 Protein Hydrolysates Proteins 0.000 claims abstract description 5
- 235000013372 meat Nutrition 0.000 claims description 29
- 102000008133 Iron-Binding Proteins Human genes 0.000 claims description 28
- 108010035210 Iron-Binding Proteins Proteins 0.000 claims description 28
- HEMHJVSKTPXQMS-UHFFFAOYSA-M Sodium hydroxide Chemical compound [OH-].[Na+] HEMHJVSKTPXQMS-UHFFFAOYSA-M 0.000 claims description 27
- 239000000758 substrate Substances 0.000 claims description 26
- 239000000243 solution Substances 0.000 claims description 24
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 20
- 230000027455 binding Effects 0.000 claims description 19
- 102000004169 proteins and genes Human genes 0.000 claims description 19
- 108090000623 proteins and genes Proteins 0.000 claims description 19
- 238000002835 absorbance Methods 0.000 claims description 18
- 239000000523 sample Substances 0.000 claims description 11
- 102000004190 Enzymes Human genes 0.000 claims description 9
- 108090000790 Enzymes Proteins 0.000 claims description 9
- 238000009835 boiling Methods 0.000 claims description 9
- 108091005658 Basic proteases Proteins 0.000 claims description 8
- 238000004448 titration Methods 0.000 claims description 8
- 238000004925 denaturation Methods 0.000 claims description 7
- 230000036425 denaturation Effects 0.000 claims description 7
- 238000009777 vacuum freeze-drying Methods 0.000 claims description 7
- 238000010438 heat treatment Methods 0.000 claims description 6
- 230000010355 oscillation Effects 0.000 claims description 6
- 239000007864 aqueous solution Substances 0.000 claims description 5
- 238000011156 evaluation Methods 0.000 claims description 5
- 238000002156 mixing Methods 0.000 claims description 5
- 239000006228 supernatant Substances 0.000 claims description 5
- 229910000359 iron(II) sulfate Inorganic materials 0.000 claims description 3
- 238000002372 labelling Methods 0.000 claims description 3
- 230000003287 optical effect Effects 0.000 claims description 3
- RXBKMJIPNDOHFR-UHFFFAOYSA-N Phenelzine sulfate Chemical compound OS(O)(=O)=O.NNCCC1=CC=CC=C1 RXBKMJIPNDOHFR-UHFFFAOYSA-N 0.000 claims description 2
- 230000002452 interceptive effect Effects 0.000 claims description 2
- 238000012795 verification Methods 0.000 claims description 2
- JBRZTFJDHDCESZ-UHFFFAOYSA-N AsGa Chemical compound [As]#[Ga] JBRZTFJDHDCESZ-UHFFFAOYSA-N 0.000 claims 1
- 229910052738 indium Inorganic materials 0.000 claims 1
- APFVFJFRJDLVQX-UHFFFAOYSA-N indium atom Chemical compound [In] APFVFJFRJDLVQX-UHFFFAOYSA-N 0.000 claims 1
- 102000004196 processed proteins & peptides Human genes 0.000 abstract description 8
- 230000000975 bioactive effect Effects 0.000 abstract description 7
- 238000005259 measurement Methods 0.000 abstract description 4
- 230000003595 spectral effect Effects 0.000 abstract description 4
- 235000018102 proteins Nutrition 0.000 description 15
- 238000002360 preparation method Methods 0.000 description 10
- 238000004519 manufacturing process Methods 0.000 description 9
- WSFSSNUMVMOOMR-UHFFFAOYSA-N Formaldehyde Chemical compound O=C WSFSSNUMVMOOMR-UHFFFAOYSA-N 0.000 description 6
- 229910000530 Gallium indium arsenide Inorganic materials 0.000 description 6
- KXNLCSXBJCPWGL-UHFFFAOYSA-N [Ga].[As].[In] Chemical compound [Ga].[As].[In] KXNLCSXBJCPWGL-UHFFFAOYSA-N 0.000 description 6
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 4
- 238000007781 pre-processing Methods 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 3
- 238000006911 enzymatic reaction Methods 0.000 description 3
- 238000010606 normalization Methods 0.000 description 3
- 239000000047 product Substances 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- NHJVRSWLHSJWIN-UHFFFAOYSA-N 2,4,6-trinitrobenzenesulfonic acid Chemical compound OS(=O)(=O)C1=C([N+]([O-])=O)C=C([N+]([O-])=O)C=C1[N+]([O-])=O NHJVRSWLHSJWIN-UHFFFAOYSA-N 0.000 description 2
- 230000002378 acidificating effect Effects 0.000 description 2
- 235000001014 amino acid Nutrition 0.000 description 2
- 150000001413 amino acids Chemical class 0.000 description 2
- 238000012569 chemometric method Methods 0.000 description 2
- 238000001816 cooling Methods 0.000 description 2
- 238000012937 correction Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000004907 flux Effects 0.000 description 2
- 235000013305 food Nutrition 0.000 description 2
- 238000011065 in-situ storage Methods 0.000 description 2
- 229910052742 iron Inorganic materials 0.000 description 2
- 229920001184 polypeptide Polymers 0.000 description 2
- 238000002203 pretreatment Methods 0.000 description 2
- 230000035945 sensitivity Effects 0.000 description 2
- KUCOHFSKRZZVRO-UHFFFAOYSA-N terephthalaldehyde Chemical compound O=CC1=CC=C(C=O)C=C1 KUCOHFSKRZZVRO-UHFFFAOYSA-N 0.000 description 2
- 229910021642 ultra pure water Inorganic materials 0.000 description 2
- 239000012498 ultrapure water Substances 0.000 description 2
- 239000002028 Biomass Substances 0.000 description 1
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- 241001428166 Eucheuma Species 0.000 description 1
- WHUUTDBJXJRKMK-UHFFFAOYSA-N Glutamic acid Natural products OC(=O)C(N)CCC(O)=O WHUUTDBJXJRKMK-UHFFFAOYSA-N 0.000 description 1
- CKLJMWTZIZZHCS-REOHCLBHSA-N L-aspartic acid Chemical compound OC(=O)[C@@H](N)CC(O)=O CKLJMWTZIZZHCS-REOHCLBHSA-N 0.000 description 1
- WHUUTDBJXJRKMK-VKHMYHEASA-N L-glutamic acid Chemical compound OC(=O)[C@@H](N)CCC(O)=O WHUUTDBJXJRKMK-VKHMYHEASA-N 0.000 description 1
- POLBLONFVZXVPI-UHFFFAOYSA-N N-methyl-sec-pseudobrucine Natural products O=C1CC2C3C(CC4=O)OCC=C2CN(C)CCC11C3N4C2=C1C=C(OC)C(OC)=C2 POLBLONFVZXVPI-UHFFFAOYSA-N 0.000 description 1
- 238000004497 NIR spectroscopy Methods 0.000 description 1
- FLBVMURVUYAZMG-UHFFFAOYSA-N Novacin Natural products CN1CCC23C4C5C(CC(=O)N4c6cc(C)c(C)cc26)OCC=C(C1)C5CC3=O FLBVMURVUYAZMG-UHFFFAOYSA-N 0.000 description 1
- 108091005804 Peptidases Proteins 0.000 description 1
- 239000004365 Protease Substances 0.000 description 1
- 102100037486 Reverse transcriptase/ribonuclease H Human genes 0.000 description 1
- 108090000787 Subtilisin Proteins 0.000 description 1
- 108010056079 Subtilisins Proteins 0.000 description 1
- 102000005158 Subtilisins Human genes 0.000 description 1
- 241000324401 Superba Species 0.000 description 1
- 239000004784 Superba Substances 0.000 description 1
- 239000003513 alkali Substances 0.000 description 1
- 235000021120 animal protein Nutrition 0.000 description 1
- 235000003704 aspartic acid Nutrition 0.000 description 1
- 239000002585 base Substances 0.000 description 1
- OQFSQFPPLPISGP-UHFFFAOYSA-N beta-carboxyaspartic acid Natural products OC(=O)C(N)C(C(O)=O)C(O)=O OQFSQFPPLPISGP-UHFFFAOYSA-N 0.000 description 1
- 239000005018 casein Substances 0.000 description 1
- BECPQYXYKAMYBN-UHFFFAOYSA-N casein, tech. Chemical compound NCCCCC(C(O)=O)N=C(O)C(CC(O)=O)N=C(O)C(CCC(O)=N)N=C(O)C(CC(C)C)N=C(O)C(CCC(O)=O)N=C(O)C(CC(O)=O)N=C(O)C(CCC(O)=O)N=C(O)C(C(C)O)N=C(O)C(CCC(O)=N)N=C(O)C(CCC(O)=N)N=C(O)C(CCC(O)=N)N=C(O)C(CCC(O)=O)N=C(O)C(CCC(O)=O)N=C(O)C(COP(O)(O)=O)N=C(O)C(CCC(O)=N)N=C(O)C(N)CC1=CC=CC=C1 BECPQYXYKAMYBN-UHFFFAOYSA-N 0.000 description 1
- 235000021240 caseins Nutrition 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 230000029087 digestion Effects 0.000 description 1
- 238000010494 dissociation reaction Methods 0.000 description 1
- 230000005593 dissociations Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000002496 gastric effect Effects 0.000 description 1
- 235000013922 glutamic acid Nutrition 0.000 description 1
- 239000004220 glutamic acid Substances 0.000 description 1
- 238000000265 homogenisation Methods 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
Images
Classifications
-
- 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
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N1/00—Sampling; Preparing specimens for investigation
- G01N1/28—Preparing specimens for investigation including physical details of (bio-)chemical methods covered elsewhere, e.g. G01N33/50, C12Q
-
- 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
- G01N21/3103—Atomic absorption analysis
Landscapes
- Physics & Mathematics (AREA)
- Spectroscopy & Molecular Physics (AREA)
- General Health & Medical Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Health & Medical Sciences (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
- Preparation Of Compounds By Using Micro-Organisms (AREA)
Abstract
A real-time online monitoring method for an enzymolysis reaction of antarctic krill belongs to the technical field of real-time online monitoring of the enzymolysis of bioactive peptides. Firstly, determining the hydrolysis degree of the euphausia superba enzymatic hydrolysate, and simultaneously performing near infrared spectrum real-time online detection on the enzymatic hydrolysate to obtain near infrared spectra of the euphausia superba enzymatic hydrolysate with different enzymatic hydrolysis times; and then performing spectrum pretreatment by using OPUS software and a first derivative method at 9400-7496 cm‑1、6104～5448cm‑1And (4) constructing an online monitoring model of the enzymolysis reaction of the euphausia superba in the spectral region by adopting a partial least square method. The euphausia superba enzymolysis reaction on-line monitoring model based on the Fourier transform near infrared spectrum technology is constructed, and correlation coefficients (R) are interactively verified2) 0.982, cross-validation Root Mean Square Error (RMSECV) 0.721; by usingThe established enzymolysis liquid model predicts the hydrolysis degree of the antarctic krill enzymolysis liquid, the deviation between a predicted value and an actual measurement value is less than 1%, and the goodness of fit is high.
Description
Technical Field
The invention belongs to the technical field of real-time online monitoring of enzymolysis of bioactive peptides, and particularly relates to a real-time online monitoring method for enzymolysis reaction of euphausia superba. The method can dynamically monitor the hydrolysis process on a biological active peptide enzymolysis preparation production line, and realize intelligent controllable enzymolysis, thereby obtaining the target active peptide to the maximum extent.
Background
Antarctic krill (Eucheuma superba) is one of the largest single biological resources on earth. According to the statistics of the Food and Agricultural Organization (FAO) of the United nations, the total biomass of the Antarctic krill is about 1.25-7.25 hundred million tons, the annual fishing amount is about 0.13-1 hundred million tons, and the total fishing amount is equivalent to the total fishing amount of the oceans in the world. Because of being rich in high-quality protein, the protein is considered as the largest and the last potential animal protein resource bank on the earth. The Antarctic krill meat has a protein content as high as 72% and is rich in acidic amino acids (glutamic acid and aspartic acid), and the acidic amino acids have rich iron binding sites. Therefore, the Antarctic krill meat is a very potential raw material for preparing the iron-bonded active peptide by a biological enzymolysis method.
In the process of preparing iron-binding active peptides by biological enzymolysis, the degree of enzymolysis has an important influence on the iron-binding activity, and is usually expressed by the Degree of Hydrolysis (DH). Enzymatic reactions may release active peptides having iron binding sites, however, excessive hydrolysis may destroy the iron binding sites that have been exposed, thereby reducing the iron binding activity of the peptide. Thus, determining the degree of hydrolysis to achieve a controlled enzymatic hydrolysis of the protease has an important role in the iron binding activity of the enzymatic hydrolysate. At present, pH-stat titration, formaldehyde titration, terephthaldehyde, trinitrobenzene sulfonic acid, and the like are commonly used as methods for measuring the degree of hydrolysis. The pH-stat titration method can monitor the hydrolysis degree in real time, and the hydrolysis degree is calculated according to the consumption of the sodium hydroxide solution in the enzymolysis process; however, the quality of the final polypeptide product may be affected by the addition of sodium hydroxide to the enzymatic hydrolysate. The formaldehyde titration method, the terephthaldehyde method and the trinitrobenzene sulfonic acid method all need to measure the hydrolysis degree off line, so that the time consumption is long, the workload is large, and the data have hysteresis. Therefore, there is a need to establish a real-time on-line monitoring method of the enzymatic reaction process to achieve a controlled preparation of iron-binding active peptides.
In recent years, near infrared spectroscopy has been applied to on-line monitoring of enzymatic reaction processes. Such as: the device and the method for monitoring the protein enzymolysis process on line based on the in-situ real-time spectrum (publication number: CN105628644A), the method for monitoring the preparation of the macromolecular polypeptide in-situ real time based on the gastrointestinal digestion (publication number: CN108107018A) and the research on the near infrared spectrum on-line monitoring technology of the casein enzymolysis reaction process (Chinese food bulletin, 2019,19(12): 220-227). The research adopts a grating type near infrared spectrum technology, and monochromatic light sequentially passes through a sample according to the wavelength through the rotating light splitting of a grating and enters a detector for detection. To obtain a high-resolution spectrum, a light beam (slit) needs to be limited, so that the light flux is reduced and the detection sensitivity is reduced; the measurement precision is low, the resolution is low, and the wavelength accuracy is poor; the collected near infrared spectrum is easily interfered by stray light; the scanning speed is slow, usually 1 time/min, and the expansion performance is poor. Therefore, the grating type near infrared technology can be used for laboratory research and is not suitable for real-time online detection on a bioactive peptide enzymolysis preparation production line.
Partial Least Squares (PLS) is an algorithm widely used for near-infrared analysis, is listed in ASTM-E-1655 infrared multivariate quantitative analysis standard, and is used as a standard algorithm for near-infrared analysis.
The judgment of the degree of the model is generally carried out by three evaluation indexes: first, theOne determines the coefficient R for the model2The size of the prediction value determines the degree of closeness of correlation between the prediction value and the measured value; the second is the predicted root mean square error RMSECV, which reflects the degree of deviation between the predicted and measured values at the time of cross-checking. A good model should have a high R2And lower RMSECV values. Therefore, the invention uses R in the modeling process2And RMSECV is used as an index, a proper spectrum preprocessing mode, a spectrum interval and a dimension are selected, and a prediction model is established.
The invention aims to establish a real-time online monitoring method for an enzymolysis reaction of euphausia superba based on an online Fourier transform near infrared spectrum technology, and the method is applied to real-time online monitoring on a bioactive peptide enzymolysis preparation production line, so that technical support is provided for intelligent controllable enzymolysis.
Disclosure of Invention
The invention aims to provide a real-time online monitoring method for an enzymolysis reaction of euphausia superba, which can be applied to an enzymolysis preparation production line of bioactive peptides and aims to realize intelligent controllable enzymolysis.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a real-time online monitoring method for enzymolysis reaction of Antarctic krill is characterized in that the method realizes real-time monitoring of the enzymolysis process of the Antarctic krill by an online Fourier transform near infrared spectrum technology to prepare Antarctic krill peptide with iron binding activity, and comprises the following specific steps:
s1, adding water into the euphausia superba meat for homogenizing, and preparing euphausia superba meat homogenate liquid with the substrate protein concentration of 20-40 mg/mL; boiling in a water bath for 5-15 min to perform denaturation pretreatment, so as to obtain an enzymolysis substrate solution of the euphausia superba meat; after the solution is cooled to 40-60 ℃, adjusting the pH to 8.5, adding alkaline protease according to the proportion of 5000U/g substrate protein, and carrying out enzymolysis at the conditions of pH 8.5 and 40-60 ℃;
s2, determining the hydrolysis degree of the euphausia superba enzymatic hydrolysate with different enzymatic hydrolysis times by a pH-stat titration method in the enzymatic hydrolysis process of the euphausia superba meat enzymatic hydrolysis substrate solution in the step S1;
while measuring the degree of hydrolysisMixing 1mg/mL antarctic krill enzymolysis liquid with 2mM FeSO4Mixing the aqueous solutions, carrying out oscillation reaction for 10-20 min, adding 5mM felazine aqueous solution, carrying out oscillation reaction for 10-20 min, measuring absorbance at 562nm by using an enzyme-labeling instrument to obtain the iron binding activity of the euphausia superba enzymatic hydrolysate in different enzymolysis times, and determining the corresponding hydrolysis degree range as the optimal hydrolysis degree when the enzymatic hydrolysate has the highest iron binding activity;
performing near infrared spectrum real-time online detection on the antarctic krill enzymatic hydrolysate while determining the degree of hydrolysis to obtain near infrared spectra of the antarctic krill enzymatic hydrolysate at different enzymolysis times;
s3, performing spectrum pretreatment on the absorbance data of the near infrared spectrum obtained in the step S2 at different wavelengths by using OPUS software and a first derivative method, wherein the absorbance data is 9400-7496 cm-1、6104～5448cm-1The spectrum region adopts a partial least square method to construct the correlation between the absorbance data at different wavelengths in the near infrared spectrum of the Antarctic krill and the hydrolysis degree of the enzymolysis reaction so as to interactively verify the correlation coefficient (R)2) Establishing an online monitoring model of the enzymolysis reaction of the antarctic krill by taking a Root Mean Square Error (RMSECV) as an evaluation index through interactive verification;
s4, adding water into the euphausia superba meat for homogenizing, and preparing euphausia superba meat homogenate liquid with the protein concentration of 20-40 mg/mL; boiling in a water bath for 5-10 min to perform denaturation pretreatment, and obtaining an enzymolysis substrate solution of the euphausia superba meat; after the temperature of an enzymolysis substrate solution of the euphausia superba meat is cooled to 40-60 ℃, adjusting the pH to 8.5, adding alkaline protease according to the ratio of 5000U/g substrate protein, and starting enzymolysis under the conditions of pH 8.5 and 40-60 ℃; in the enzymolysis process, performing near infrared spectrum real-time online detection on enzymolysis liquid, performing spectrum pretreatment by using OPUS software and a first derivative method, converting absorbance data at different wavelengths of a real-time near infrared spectrum into a real-time enzymolysis reaction hydrolysis degree through an antarctic krill enzymolysis reaction online monitoring model constructed in the step S3, finishing the reaction when the hydrolysis degree reaches the optimal hydrolysis degree in the step S2, heating to inactivate enzymes, adjusting the pH to 7.0, centrifuging, collecting supernatant, and performing vacuum freeze drying to obtain the antarctic krill peptide with iron binding activity.
In the step S1, adjusting the pH value to 8.5 by using 0.5-2.0 mol/L NaOH;
in the step S2, the real-time online detection of the near infrared spectrum is to immerse a transflective probe connected to a Matrix-F online Fourier transform near infrared spectrometer into the antarctic krill enzymatic hydrolysate, use air as background reference, adopt a three-dimensional cube corner mirror interference technology, and acquire the near infrared spectrum data of the antarctic krill enzymatic hydrolysate on line in real time through an indium gallium arsenide (InGaAs) detector; the optical path of the transflective probe is 1 mm; the scanning spectrum range is 11500-4000 cm-1The number of scanning times was 64, the scanning speed was 8 times/sec, and the resolution was 8cm-1；
In step S3, cross-validation correlation coefficient (R) of antarctic krill enzymolysis reaction on-line monitoring model2) 0.982, cross-validation Root Mean Square Error (RMSECV) 0.721;
in the step S4, when the hydrolysis degree reaches 19-20%, the enzymolysis liquid shows the highest iron binding activity, then heating at 95-100 ℃ for 8-15 min to inactivate the enzyme and finish the enzymolysis reaction, and performing vacuum freeze drying to obtain the antarctic krill iron binding active peptide.
The online monitoring model for the enzymolysis reaction of the antarctic krill constructed by the invention is used for predicting the hydrolysis degree of the antarctic krill in the enzymolysis reaction process, and the deviation between the predicted value and the measured value is less than 1%.
Compared with the prior art, the invention has the following advantages and technical effects:
1. the invention provides a real-time online monitoring method for an enzymolysis reaction of euphausia superba by utilizing an online Fourier transform near infrared spectrum technology, which can be applied to real-time online monitoring of process parameters on a bioactive peptide enzymolysis preparation production line, and feeds detected data back to a control system in real time, thereby realizing intelligent control of the enzymolysis process, saving production cost and greatly improving production efficiency and quality.
2. Compared with a grating type near infrared spectrum technology, the Fourier transform near infrared spectrum technology adopted by the invention has large luminous flux and high detection sensitivity; high resolution up to 1cm-1(ii) a The scanning speed is high and can reach 8 times/second, and the method is suitable for a production line for preparing the bioactive peptide by enzymolysisReal-time online detection.
3. The euphausia superba enzymolysis reaction on-line monitoring model based on the Fourier transform near infrared spectrum technology is constructed, and correlation coefficients (R) are interactively verified2) 0.982, cross-validation Root Mean Square Error (RMSECV) 0.721; and predicting the hydrolysis degree of the euphausia superba enzymatic hydrolysate by using the established enzymatic hydrolysate model, wherein the deviation between a predicted value and an actual measured value is less than 1%, and the goodness of fit is high.
Drawings
FIG. 1 is a flow chart for constructing an online monitoring model of an enzymolysis reaction of antarctic krill according to the present invention;
FIG. 2 shows the degree of hydrolysis and iron binding activity of the enzymatic hydrolysate of Euphausia superba according to the present invention at different enzymatic times; the abscissa: enzymolysis time (min), left ordinate: iron binding activity (%), right ordinate: degree of hydrolysis (%); the histogram is the iron binding activity of the euphausia superba enzymatic hydrolysate at different enzymatic hydrolysis times; the line graph shows the hydrolysis degree of the euphausia superba enzymatic hydrolysate in different enzymatic hydrolysis times;
FIG. 3 is a near-infrared original spectrum of antarctic krill in the course of enzymolysis reaction; the abscissa: wave number (cm)-1) And the ordinate: absorbance;
FIG. 4 is a graph showing the relationship between the hydrolysis value and the measured value of the enzymolysis reaction of Euphausia superba predicted by the online monitoring model of the enzymolysis reaction of Euphausia superba according to the present invention; the abscissa: measured value of degree of hydrolysis; ordinate: predicting a hydrolysis degree value;
fig. 5 is a flow chart of the real-time online monitoring method for enzymolysis reaction of antarctic krill applied to a production line.
Detailed Description
The present invention is further illustrated by the following specific examples, but the scope of the invention is not limited thereto. For process parameters not specifically noted, reference may be made to conventional techniques.
Example 1: preparation of iron-binding active peptide by enzymolysis of Antarctic krill
1. Unfreezing Antarctic krill meat flowing water, adding water for homogenizing, preparing Antarctic krill meat homogenate with substrate protein concentration of 20mg/mL, boiling in a boiling water bath for 10min for denaturation pretreatment, and obtaining an Antarctic krill meat enzymolysis substrate solution;
2. cooling the temperature of an enzymolysis substrate solution of the euphausia superba meat to 50 ℃, adjusting the pH to 8.5 by using 1mol/L NaOH, adding alkaline protease (subtilisin CAS 9014-01-1) according to the ratio of 5000U/g substrate protein, and carrying out enzymolysis for 0-4 h under the constant conditions of pH 8.5 and 50 ℃ to obtain an enzymolysis solution of the euphausia superba;
3. calculating the hydrolysis degree of the enzymolysis liquid of the antarctic krill by using a pH-stat titration method to titrate the volume of the consumed standard NaOH solution at 0, 2, 4, 6, 8, 10, 15, 20, 30, 40, 50, 60, 75, 90, 105, 120, 150, 180, 210 and 240min of enzymolysis, and obtaining actual measurement values of the hydrolysis degree of the enzymolysis liquid at different enzymolysis times in the reaction process;
the calculation formula is as follows:
in the formula: DH-degree of hydrolysis,%;
b-volume of base (NaOH) consumed to keep pH constant, mL;
nb-alkali equivalent concentration, mol/L;
mp-total protein in substrate, g;
htottotal number of peptide bonds in the substrate protein, mmol/g, in the present invention htotCalculated as 4.27 mmol/g;
the degree of dissociation of the alpha-amino group during the alpha-hydrolysis is 1.01 in the present invention.
4. While measuring the hydrolysis degree, respectively taking antarctic krill enzymolysis liquid at 10 th, 20 th, 30 th, 60 th, 90 th, 120 th, 180 th and 240 th min of the enzymolysis reaction, carrying out vacuum freeze drying to obtain antarctic krill enzymolysis products, preparing 1mL, 1mg/mL antarctic krill enzymolysis liquid water solution, mixing with 1.35mL ultrapure water and 50 mu L, 2mM FeSO4Mixing the water solutions, performing oscillation reaction for 10min, adding 100 μ L5 mM felodizine water solution, performing oscillation reaction for 10min, and measuring the absorbance (A) of the reaction solution at 562nm with enzyme-labeling instrumentSample (A)) The aqueous solution of antarctic krill zymolyte is replaced by 1mL of ultrapure water to obtainAbsorbance value of blank control (A)Air conditioner) Obtaining the iron binding activity of the enzymatic hydrolysate of the antarctic krill at different enzymolysis times through the following calculation formula;
the calculation formula is as follows:
in the formula:
Asample (A)Absorbance values of the reaction solution
AAir conditioner-absorbance value of blank control
5. And after the enzymolysis is finished, heating at 100 ℃ for 10min to inactivate the enzyme and finish the enzymolysis reaction, then adjusting the pH to 7.0 by using 1mol/LNaOH, centrifuging at 4000r/min for 20min, collecting supernatant, and performing vacuum freeze drying to obtain the antarctic krill iron-binding active peptide.
The experimental results are as follows: carrying out enzymolysis on euphausia superba meat by using alkaline protease, wherein the hydrolysis degree and iron binding activity of the euphausia superba enzymolysis liquid are gradually increased along with the prolonging of the enzymolysis time; when the hydrolysis degree reaches 19.88%, the antarctic krill enzymolysis product has the highest iron binding activity; when the degree of hydrolysis is greater than 20%, the iron binding activity of the enzymatic hydrolysate of antarctic krill shows a decreasing trend (fig. 2). Therefore, the antarctic krill iron-conjugated active peptide can be prepared by enzymolysis under the condition that the hydrolysis degree is controlled to be 19-20%.
Example 2: online near infrared spectrum acquisition and online monitoring model establishment in antarctic krill enzymolysis reaction process
1. The method comprises the following steps of (1) adopting a Matrix-F online Fourier transform near-infrared spectrometer to online acquire near-infrared spectrum data in the enzymolysis reaction process of the antarctic krill in real time (which is carried out simultaneously with the operation of measuring the hydrolysis degree in the example 1); immersing a transflective probe with an optical path of 1mm into the antarctic krill enzymolysis liquid, taking air as a background reference, and scanning in a transflective mode, wherein the scanning spectral range is 11500-4000 cm-1The number of scanning times was 64, the scanning speed was 8 times/sec, and the resolution was 8cm-1(ii) a Adopting three-dimensional cube corner mirror interference technique, and real-time online collecting by indium gallium arsenide (InGaAs) detectorAnd (3) near-infrared original spectrum of the euphausia superba enzymatic hydrolysate.
2. Preprocessing absorbance data of collected near infrared spectrum data of antarctic krill enzymatic hydrolysate at different wavelengths by using OPUS software and a chemometric method, wherein the chemometric method comprises 9 methods of first-order derivative, minimum-maximum normalization, vector normalization, multivariate scattering correction, subtraction of a straight line, first-order derivative + vector normalization, first-order derivative + multivariate scattering correction, first-order derivative + subtraction of a straight line, second-order derivative and the like; establishing correlation between absorbance data at different wavelengths in near infrared spectrum number of enzymatic hydrolysate of Antarctic krill and hydrolysis degree of enzymatic hydrolysis reaction by partial least square method to interactively verify correlation coefficient (R)2) And establishing an online monitoring model of the enzymolysis reaction of the antarctic krill by taking the Root Mean Square Error (RMSECV) of the cross validation as an evaluation index.
The experimental results are as follows: in this example, a Matrix-F online fourier transform near-infrared spectrometer was used to collect near-infrared raw spectra (20 curves in fig. 3) of 60 samples (spectra collected at different enzymolysis times and three independent parallel experiments of enzymolysis reaction) from an enzymolysis reaction process of antarctic krill. Pre-processing the near-infrared original spectrum with R2RMSECV is used as an evaluation index and ranges from 11500 cm to 4000cm-1The range analysis compares the influence of the preprocessing method on the prediction model established by the partial least squares method, and the result is shown in table 2. The pretreatment of different spectrums has obvious difference on the effect of establishing an online monitoring model of the enzymolysis reaction of the antarctic krill. 9 spectrum pretreatment methods are compared, the pretreatment with the best first derivative is carried out, the spectrum after the treatment, the predicted value of the partial least square method model of the hydrolysis degree of the enzymolysis reaction of the antarctic krill and the R of the truth value are established2The RMSECV is 0.982 and 0.721 (fig. 4), which shows that the first derivative is a superior spectral pretreatment method suitable for the online monitoring model of the enzymolysis reaction of the antarctic krill. Therefore, the near infrared spectrum after the first derivative pretreatment is 9400-7496 cm-1、6104～5448cm-1The model established by the partial least square method in the spectral region is used as an online monitoring model of the enzymolysis reaction of the antarctic krill (figure 4).
Table 2: near-infrared original spectrum pretreatment result of antarctic krill enzymolysis liquid sample
Example 3: prediction of degree of hydrolysis in antarctic krill enzymolysis reaction process
1. Unfreezing Antarctic krill meat flowing water, adding water for homogenizing, preparing Antarctic krill meat homogenate with substrate protein concentration of 40mg/mL, boiling in a boiling water bath for 10min for denaturation pretreatment to obtain an Antarctic krill meat enzymolysis substrate solution, cooling to 50 ℃, and adjusting pH to 8.5 by using 1mol/L NaOH;
2. immersing a transflective probe and a pH meter connected to a Matrix-F online Fourier transform near-infrared spectrometer into an euphausia superba enzymatic hydrolysate, adding novacin alkaline protease (Alcalase 2.4L) according to the proportion of 5000U/g substrate protein, carrying out enzymatic hydrolysis under the constant conditions of pH 8.5 and 50 ℃, and collecting a near-infrared spectrum in real time; meanwhile, recording the volume of the consumed standard NaOH solution in real time, and obtaining an actual value of the hydrolysis degree of the antarctic krill in the enzymolysis reaction process by a pH-stat titration method;
3. the method comprises the steps of utilizing OPUS software and a first derivative method to conduct near infrared spectrum pretreatment, converting real-time absorbance data of different wavelengths of near infrared spectrum into real-time enzymolysis reaction hydrolysis degree through the antarctic krill enzymolysis reaction on-line monitoring model constructed in the embodiment 2, predicting the hydrolysis degree in the antarctic krill enzymolysis reaction process, and comparing a predicted value with an actual measurement value.
The experimental results are as follows: table 3 shows that the predicted value and the measured value of the hydrolysis degree in the enzymolysis reaction process of the antarctic krill, the absolute value of the deviation is less than 1%, and the coincidence degree of the predicted value and the measured value is high, which indicates that the online monitoring model established by the invention can well predict the enzymolysis reaction process of the antarctic krill.
Table 3: prediction result of degree of hydrolysis in enzymolysis reaction process of Antarctic krill
Example 4: real-time online monitoring of antarctic krill iron-binding active peptide enzymolysis preparation
The real-time online monitoring method for the enzymolysis preparation of the iron-bonded active peptide of the antarctic krill is shown in fig. 5, the flowing water of the antarctic krill is unfrozen, after the water is added for homogenization, the homogenate of the antarctic krill meat with the substrate protein concentration of 20mg/mL is prepared, the antarctic krill meat homogenate is boiled in a boiling water bath for 10min for denaturation pretreatment, an enzymolysis substrate solution of the antarctic krill meat is obtained, the temperature is cooled to 50 ℃, the pH is adjusted to 8.5, and the enzymolysis system in fig. 5 is obtained; immersing a transflective probe connected to a Matrix-F online Fourier transform near-infrared spectrometer into an antarctic krill enzymatic hydrolysate, adding alkaline protease according to the proportion of 5000U/g substrate protein, carrying out enzymolysis under the constant conditions of pH 8.5 and 50 ℃, adopting a three-dimensional cube corner mirror interference technology, collecting near infrared spectrum data in an enzymolysis reaction process in real time on line by an indium gallium arsenide (InGaAs) detector, carrying out spectrum pretreatment by using OPUS software and a first derivative method, converting absorbance data at different wavelengths of the real-time near infrared spectrum into real-time enzymolysis reaction hydrolysis by calling an enzymolysis reaction online monitoring model, judging whether an enzyme end point is reached, and continuing to carry out enzyme if the enzyme end point is not reached; and (3) stopping enzymolysis when the enzymolysis end point (the hydrolysis degree reaches 19-20%) is reached, heating at 100 ℃ for 10min to inactivate enzyme, finishing enzymolysis reaction, adjusting the pH value to 7.0, centrifuging at 4000r/min for 20min, collecting supernatant, and performing vacuum freeze drying to obtain the antarctic krill iron-conjugated active peptide.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be able to cover the technical solutions and the inventive concepts of the present invention within the technical scope of the present invention.
Claims (7)
1. A real-time online monitoring method for an enzymolysis reaction of antarctic krill comprises the following steps:
s1, adding water into the euphausia superba meat for homogenizing, and preparing euphausia superba meat homogenate liquid with the substrate protein concentration of 20-40 mg/mL; boiling in a water bath for 5-15 min to perform denaturation pretreatment, so as to obtain an enzymolysis substrate solution of the euphausia superba meat; after the solution is cooled to 40-60 ℃, adjusting the pH to 8.5, adding alkaline protease according to the proportion of 5000U/g substrate protein, and carrying out enzymolysis at the conditions of pH 8.5 and 40-60 ℃;
s2, determining the hydrolysis degree of the euphausia superba enzymatic hydrolysate with different enzymatic hydrolysis times by a pH-stat titration method in the enzymatic hydrolysis process of the euphausia superba meat enzymatic hydrolysis substrate solution in the step S1;
measuring the degree of hydrolysis, and simultaneously mixing 1mg/mL antarctic krill enzymolysis liquid with 2mM FeSO4Mixing the aqueous solutions, carrying out oscillation reaction for 10-20 min, adding 5mM felazine aqueous solution, carrying out oscillation reaction for 10-20 min, measuring absorbance at 562nm by using an enzyme-labeling instrument to obtain the iron binding activity of the euphausia superba enzymatic hydrolysate in different enzymolysis times, and determining the corresponding hydrolysis degree range as the optimal hydrolysis degree when the enzymatic hydrolysate has the highest iron binding activity;
performing near infrared spectrum real-time online detection on the antarctic krill enzymatic hydrolysate while determining the degree of hydrolysis to obtain near infrared spectra of the antarctic krill enzymatic hydrolysate at different enzymolysis times;
s3, performing spectrum pretreatment on the absorbance data of the near infrared spectrum obtained in the step S2 at different wavelengths by using OPUS software and a first derivative method, wherein the absorbance data is 9400-7496 cm-1、6104～5448cm-1The spectrum region adopts a partial least square method to construct the correlation between the absorbance data at different wavelengths in the near infrared spectrum of the Antarctic krill and the hydrolysis degree of the enzymolysis reaction so as to interactively verify the correlation coefficient (R)2) Establishing an online monitoring model of the enzymolysis reaction of the antarctic krill by taking a Root Mean Square Error (RMSECV) as an evaluation index through interactive verification;
s4, adding water into the euphausia superba meat for homogenizing, and preparing euphausia superba meat homogenate liquid with the protein concentration of 20-40 mg/mL; boiling in a water bath for 5-10 min to perform denaturation pretreatment, and obtaining an enzymolysis substrate solution of the euphausia superba meat; after the temperature of an enzymolysis substrate solution of the euphausia superba meat is cooled to 40-60 ℃, adjusting the pH to 8.5, adding alkaline protease according to the ratio of 5000U/g substrate protein, and starting enzymolysis under the conditions of pH 8.5 and 40-60 ℃; in the enzymolysis process, performing near infrared spectrum real-time online detection on enzymolysis liquid, performing spectrum pretreatment by using OPUS software and a first derivative method, converting absorbance data at different wavelengths of a real-time near infrared spectrum into a real-time enzymolysis reaction hydrolysis degree through an antarctic krill enzymolysis reaction online monitoring model constructed in the step S3, finishing the reaction when the hydrolysis degree reaches the optimal hydrolysis degree in the step S2, heating to inactivate enzymes, adjusting the pH to 7.0, centrifuging, collecting supernatant, and performing vacuum freeze drying to obtain the antarctic krill peptide with iron binding activity.
2. The real-time on-line monitoring method for enzymolysis reaction of antarctic krill as claimed in claim 1, wherein: in step S1, the pH is adjusted to 8.5 with 0.5-2.0 mol/L NaOH.
3. The real-time on-line monitoring method for enzymolysis reaction of antarctic krill as claimed in claim 1, wherein: in the step S2, the near infrared spectrum real-time online detection is to immerse a transflective probe connected to a Matrix-F online Fourier transform near infrared spectrometer into the antarctic krill enzymatic hydrolysate, use air as background reference, adopt a three-dimensional cube corner mirror interference technology, and acquire the near infrared spectrum data of the antarctic krill enzymatic hydrolysate on line in real time through an indium gallium arsenic detector.
4. The real-time on-line monitoring method for enzymolysis reaction of antarctic krill as claimed in claim 3, wherein: the optical path of the transflective probe is 1 mm; the scanning spectrum range is 11500-4000 cm-1The number of scanning times was 64, the scanning speed was 8 times/sec, and the resolution was 8cm-1。
5.The real-time on-line monitoring method for enzymolysis reaction of antarctic krill as claimed in claim 1, wherein: in step S3, cross-validation correlation coefficient R of antarctic krill enzymolysis reaction on-line monitoring model2At 0.982, the cross-validation root mean square error RMSECV was 0.721.
6. The real-time on-line monitoring method for enzymolysis reaction of antarctic krill as claimed in claim 1, wherein: in step S4, when the hydrolysis degree reaches 19-20%, the enzymolysis liquid shows the highest iron binding activity; and then heating at 95-100 ℃ for 8-15 min to inactivate enzyme and finish enzymolysis reaction, adjusting the pH to 7.0, centrifuging and collecting supernatant, and performing vacuum freeze drying to obtain the antarctic krill iron-bonded active peptide.
7. The real-time on-line monitoring method for enzymolysis reaction of antarctic krill as claimed in claim 1, wherein: and predicting the hydrolysis degree of the antarctic krill in the enzymolysis reaction process by using the constructed antarctic krill enzymolysis reaction on-line monitoring model, wherein the deviation between the predicted value and the measured value is less than 1%.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110520644.3A CN113189043B (en) | 2021-05-13 | 2021-05-13 | Real-time online monitoring method for euphausia superba enzymolysis reaction |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110520644.3A CN113189043B (en) | 2021-05-13 | 2021-05-13 | Real-time online monitoring method for euphausia superba enzymolysis reaction |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113189043A true CN113189043A (en) | 2021-07-30 |
| CN113189043B CN113189043B (en) | 2023-06-06 |
Family
ID=76981399
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110520644.3A Active CN113189043B (en) | 2021-05-13 | 2021-05-13 | Real-time online monitoring method for euphausia superba enzymolysis reaction |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113189043B (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105628644A (en) * | 2015-12-21 | 2016-06-01 | 江苏大学 | Device and method for on-line monitoring of protein enzymolysis process based on in-situ real-time spectrum |
| CN107190040A (en) * | 2017-06-05 | 2017-09-22 | 浙江国际海运职业技术学院 | A kind of ring shrimp anti-oxidation peptide and preparation method thereof |
| CN108107018A (en) * | 2017-11-13 | 2018-06-01 | 江苏大学 | A kind of macromolecular polypeptides based on gastro-intestinal digestion prepare INSITU REAL TIME |
| WO2019091472A1 (en) * | 2017-11-13 | 2019-05-16 | 江苏大学 | Ultrasound-assisted simulated digestion method of milk protein active peptide and application thereof in health foods |
-
2021
- 2021-05-13 CN CN202110520644.3A patent/CN113189043B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105628644A (en) * | 2015-12-21 | 2016-06-01 | 江苏大学 | Device and method for on-line monitoring of protein enzymolysis process based on in-situ real-time spectrum |
| CN107190040A (en) * | 2017-06-05 | 2017-09-22 | 浙江国际海运职业技术学院 | A kind of ring shrimp anti-oxidation peptide and preparation method thereof |
| CN108107018A (en) * | 2017-11-13 | 2018-06-01 | 江苏大学 | A kind of macromolecular polypeptides based on gastro-intestinal digestion prepare INSITU REAL TIME |
| WO2019091472A1 (en) * | 2017-11-13 | 2019-05-16 | 江苏大学 | Ultrasound-assisted simulated digestion method of milk protein active peptide and application thereof in health foods |
Non-Patent Citations (2)
| Title |
|---|
| 杨雪 等: "酪蛋白酶解反应过程的近红外光谱在线监测技术研究", 中国食品学报 * |
| 郑景如 等: "优选南极磷虾蛋白肽抗氧化活性组分", 食品安全质量检测学报 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113189043B (en) | 2023-06-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| WO2017107278A1 (en) | In-situ real-time spectrum based on-line protein enzymatic hydrolysis monitoring method and device | |
| Hu et al. | Rapid detection of three quality parameters and classification of wine based on Vis-NIR spectroscopy with wavelength selection by ACO and CARS algorithms | |
| Cuadrado et al. | Comparison and joint use of near infrared spectroscopy and Fourier transform mid infrared spectroscopy for the determination of wine parameters | |
| TW201945534A (en) | Multivariate spectral analysis and monitoring for biomanufacturing | |
| CN109765196A (en) | A kind of method for quick identification of atlantic salmon and rainbow trout | |
| Ye et al. | Application of FT-NIR spectroscopy to apple wine for rapid simultaneous determination of soluble solids content, pH, total acidity, and total ester content | |
| CN106701846B (en) | Method for producing sodium gluconate by on-line monitoring and optimizing aspergillus niger fermentation | |
| Xie et al. | Application of time series hyperspectral imaging (TS-HSI) for determining water content within tea leaves during drying | |
| Jiang et al. | Detecting total acid content quickly and accurately by combining hyperspectral imaging and an optimized algorithm method | |
| Cheng et al. | Development of a novel quantitative function between spectral value and metmyoglobin content in Tan mutton | |
| Yan et al. | Development of an on-line Raman spectral analytical method for monitoring and endpoint determination of the Cornu Caprae Hircus hydrolysis process | |
| Kafle et al. | Fourier-transform infrared spectroscopy for characterization of liquid protein solutions: A comparison of two sampling techniques | |
| CN113189043A (en) | Real-time online monitoring method for enzymolysis reaction of euphausia superba | |
| CN108107018B (en) | In-situ real-time monitoring method for macromolecular polypeptide preparation based on gastrointestinal digestion | |
| CN110865046A (en) | Method for rapidly detecting content of trans-fatty acid isomer of edible oil | |
| Joshi et al. | Quantitative analysis of glycerol concentration in red wine using Fourier transform infrared spectroscopy and chemometrics analysis | |
| CN113504208A (en) | Method for detecting urea in milk based on pH sensitive carbon dots and urease | |
| Luo et al. | In situ and real-time monitoring of an ultrasonic-assisted enzymatic hydrolysis process of corn gluten meal by a miniature near infrared spectrometer | |
| CN110108647A (en) | A kind of discrimination method and identification system of meat kind | |
| Shen et al. | Evaluation of near‐infrared and mid‐infrared spectroscopy for the determination of routine parameters in Chinese rice wine | |
| Gao et al. | Analysis of protein denaturation, and chemical visualisation, of frozen grass carp surimi containing soluble soybean polysaccharides | |
| Marinoni et al. | Quantification of casein fractions and of some of their genetic variants in phosphate buffer by near infrared spectroscopy | |
| Xie et al. | Band Selection Method of Absorption Peak Perturbance for the FTIR/ATR Spectrum Analysis | |
| Guan et al. | The qualitative and quantitative analysis of aromatic vinegar produced during different seasons by near infrared spectroscopy | |
| Verma et al. | Perspectives of Infrared Spectroscopy in Quantitative Estimation of Proteins |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |