CN116210798A - Method for regulating and controlling aggregation of main protein of royal jelly - Google Patents

Method for regulating and controlling aggregation of main protein of royal jelly Download PDF

Info

Publication number
CN116210798A
CN116210798A CN202310502527.3A CN202310502527A CN116210798A CN 116210798 A CN116210798 A CN 116210798A CN 202310502527 A CN202310502527 A CN 202310502527A CN 116210798 A CN116210798 A CN 116210798A
Authority
CN
China
Prior art keywords
aggregation
royal jelly
protein
mrjps
regulating
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
Application number
CN202310502527.3A
Other languages
Chinese (zh)
Other versions
CN116210798B (en
Inventor
彭文君
田文礼
潘飞
李相昕
方小明
王文千
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Institute of Apicultural Research of Chinese Academy of Agricultural Sciences
Original Assignee
Institute of Apicultural Research of Chinese Academy of Agricultural Sciences
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Institute of Apicultural Research of Chinese Academy of Agricultural Sciences filed Critical Institute of Apicultural Research of Chinese Academy of Agricultural Sciences
Priority to CN202310502527.3A priority Critical patent/CN116210798B/en
Publication of CN116210798A publication Critical patent/CN116210798A/en
Application granted granted Critical
Publication of CN116210798B publication Critical patent/CN116210798B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G16B40/20—Supervised data analysis
    • A—HUMAN NECESSITIES
    • A23—FOODS OR FOODSTUFFS; TREATMENT THEREOF, NOT COVERED BY OTHER CLASSES
    • A23J—PROTEIN COMPOSITIONS FOR FOODSTUFFS; WORKING-UP PROTEINS FOR FOODSTUFFS; PHOSPHATIDE COMPOSITIONS FOR FOODSTUFFS
    • A23J1/00—Obtaining protein compositions for foodstuffs; Bulk opening of eggs and separation of yolks from whites
    • A—HUMAN NECESSITIES
    • A23—FOODS OR FOODSTUFFS; TREATMENT THEREOF, NOT COVERED BY OTHER CLASSES
    • A23J—PROTEIN COMPOSITIONS FOR FOODSTUFFS; WORKING-UP PROTEINS FOR FOODSTUFFS; PHOSPHATIDE COMPOSITIONS FOR FOODSTUFFS
    • A23J3/00—Working-up of proteins for foodstuffs
    • A23J3/04—Animal proteins
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/10—Machine learning using kernel methods, e.g. support vector machines [SVM]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/20—Ensemble learning

Landscapes

  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Theoretical Computer Science (AREA)
  • Software Systems (AREA)
  • Medical Informatics (AREA)
  • Data Mining & Analysis (AREA)
  • Physics & Mathematics (AREA)
  • Chemical & Material Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Computation (AREA)
  • General Physics & Mathematics (AREA)
  • Food Science & Technology (AREA)
  • Polymers & Plastics (AREA)
  • Biochemistry (AREA)
  • Mathematical Physics (AREA)
  • General Engineering & Computer Science (AREA)
  • Computing Systems (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Databases & Information Systems (AREA)
  • Evolutionary Biology (AREA)
  • Biotechnology (AREA)
  • Biophysics (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Bioethics (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Epidemiology (AREA)
  • Zoology (AREA)
  • Nutrition Science (AREA)
  • Jellies, Jams, And Syrups (AREA)
  • Peptides Or Proteins (AREA)

Abstract

The invention provides a method for regulating and controlling main protein aggregation of royal jelly, and relates to the field of protein regulation and control. The method for regulating and controlling the aggregation of the main protein of the royal jelly mainly comprises the steps of firstly extracting and purifying MRJPs protein from fresh royal jelly, then carrying out ultrahigh pressure treatment on the extracted and purified MRJPs protein by utilizing high hydrostatic pressure, finally measuring the aggregation index of the MRJPs protein, and constructing an aggregation regulating and controlling model by means of Gradientboosting algorithm. The invention overcomes the defects of the prior art, can directionally guide the high hydrostatic pressure technology to be used in the pretreatment of MRJPs protein, so as to prepare the MRJPs solution with better and target requirements, and is beneficial to improving the digestion, absorption and nutrition utilization of the main protein of the royal jelly and even the royal jelly.

Description

Method for regulating and controlling aggregation of main protein of royal jelly
Technical Field
The invention relates to the field of protein regulation, in particular to a method for regulating and controlling the aggregation of main proteins of royal jelly.
Background
Royal jelly is one of the most characteristic substances in bee products, and is internationally recognized health food with multiple functions of enhancing immunity, delaying aging and the like for animals and human bodies. China is the first large country of production of royal jelly in the world, and the royal jelly accounts for more than 90% of the total yield in the world. The main dry matter in Lac Regis Apis is protein, wherein Lac Regis Apis main protein (Major royal jelly proteins, MRJPs) is key active component of Lac Regis Apis, and accounts for more than 80% of total protein. The MRJPs can generate electrostatic and hydrophobic interactions in the food processing and storage and transportation processes to spontaneously aggregate to form fibrous aggregates, so that the fibrous aggregates cannot be digested by gastrointestinal tracts, the quality and nutrition absorption of the MRJPs and even the royal jelly are greatly influenced, and the high-value utilization of the royal jelly is restricted. Therefore, how to regulate the aggregation behavior of MRJPs is a difficult goal to develop functional foods based on royal jelly and MRJPs.
Aggregation behavior of food-derived proteins is generally thought to be affected by in vitro environments, resulting in alterations in their native three-dimensional structure and initiation of specific functions. Under appropriate conditions, aggregation behavior of food-borne proteins can be modulated or reversed, as this process does not involve covalent interactions. The most common method of inhibiting protein aggregation is by the addition of exogenous substances, which have been demonstrated by many studies to slow down the aggregation behavior of food-borne proteins during processing (Food Hydrocolloids, 2023, 84, 368-378;Food Hydrocolloids, 2023, 137, 108376; biochemistry, 2009, 48 (46), 11084-11096). However, the introduction of exogenous substances may negatively affect the taste and texture of the food product, limiting its practical use.
In contrast, physical processing provides a more promising approach to regulating protein aggregation, including both thermal and non-thermal processing approaches. However, due to the unique properties of MRJPs, heat treatment accelerates the aggregation behavior of MRJPs. In contrast, non-heat treatment has greater potential in improving the aggregation performance and quality of MRJPs. High hydrostatic pressure is a typical low-pollution non-thermal processing technology, can process proteins at lower temperatures, and can effectively preserve the flavor and nutritional value of foods. However, no research and no patent report has been made so far on whether the high hydrostatic pressure can regulate the aggregation behavior of MRJPs, and furthermore, a further objective is to explore the regulation law of the high hydrostatic pressure on the aggregation behavior of MRJPs.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a method for regulating and controlling the aggregation of main proteins of royal jelly, which can directionally guide a high hydrostatic pressure technology to be used in the pretreatment of MRJPs proteins so as to prepare an MRJPs solution with better and target requirements, thereby being beneficial to improving the digestion, absorption and nutrition utilization of the main proteins of the royal jelly and even the royal jelly.
In order to achieve the above object, the technical scheme of the present invention is realized by the following technical scheme:
a method for regulating and controlling the aggregation of main proteins of royal jelly comprises the following steps:
s1, separating and purifying main proteins (MRJPs) of the royal jelly from the royal jelly;
s2, performing ultrahigh pressure treatment on the extracted and purified MRJPs protein by using high hydrostatic pressure;
s3, determining aggregation indexes of the MRJPs protein, and constructing an aggregation regulation model by means of Gradientboosting algorithm.
Preferably, the main protein of the royal jelly in the S1 is any one of MRJP1, MRJP2, MRJP3, MRJP4, MRJP5, MRJP6, MRJP7, MRJP8, MRJP9 and MRJP10 or any combination or mixture thereof.
Preferably, the high hydrostatic pressure treatment temperature in the step S2 is 4-25 ℃, the treatment time is 0-30 min, and the treatment pressure is 0-600 Mpa.
Preferably, the aggregation index comprises protein particle size, sulfhydryl hydrophobic content, fluorescence intensity, polydispersity, radius of gyration.
Preferably, the aggregation control model is constructed by a mathematical model, wherein the processing parameters are X, and the protein aggregation index is Y.
Preferably, the mathematical model includes, but is not limited to LinearRegression, KNN, SVR, extraTree, randomForest, adaBoost, gradientBoost, etc., and more preferably ExtraTree, adaBoost, gradientBoost is used to construct an aggregate parameter prediction model.
Preferably, the aggregation parameter prediction model is used in the training process
Figure SMS_1
The expression is
Figure SMS_2
I represents an ith sample, m and n respectively represent high-pressure processing intensity and time, the value range of m is 0-600, and the value range of n is 0-30; />
Figure SMS_3
The expression is->
Figure SMS_4
Q, w and e respectively represent the particle size of the protein, the hydrophobic content of sulfhydryl groups and the polydispersity, wherein the particle size of the protein ranges from 5 to 1000, the content of sulfhydryl groups ranges from 0 to 100, and the polydispersity ranges from 0 to 1.
Preferably, the model training process uses leave-one-out cross-validation for verification, followed by model evaluation to pick the best model.
Preferably, the method and step of model evaluation is calculated using the following formula
Figure SMS_5
Figure SMS_6
And->
Figure SMS_7
The predictive power and robustness of the model are evaluated.
Figure SMS_8
In the method, in the process of the invention,
Figure SMS_9
respectively a true value, a predicted value and an average value,SSresis the sum of squares of the residuals, also called the sum of squares of the residuals;SStotis the sum of the total squares;nis the number of samples;MAErepresenting the difference between the true value and the predicted value, the predicted value reflecting the true error by an average of absolute differences to the dataset;MSErepresenting the expected value of the square error;RMSErepresenting the standard deviation of the prediction error.
The invention provides a method for regulating and controlling the aggregation of main proteins of royal jelly, which has the advantages that compared with the prior art:
the high hydrostatic pressure process method used by the invention can effectively regulate and control the aggregation degree of the MRJPs, establishes the relationship between the high hydrostatic pressure processing process and the aggregation behavior of the MRJPs based on a mathematical model, can directionally guide the high hydrostatic pressure technology to be used in the pretreatment of MRJPs protein to prepare the MRJPs solution with better and target requirements, is beneficial to improving the digestion, absorption and nutrition utilization of the main protein of the royal jelly and even the royal jelly, and provides a technical controllable scheme for the development of multi-element special health food taking the royal jelly as a dominant material.
Drawings
FIG. 1 is a graph showing MRJPs particle size distribution at various high hydrostatic pressure process pressures and times;
FIG. 2 shows TEM results of MRJPs solutions at various high hydrostatic treatment pressures and times;
FIG. 3 is a schematic diagram of training using the MRJPs aggregation control model;
FIG. 4 is a schematic diagram showing the results of MRJPs aggregation control model.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions in the embodiments of the present invention will be clearly and completely described in the following in conjunction with the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Examples
1. The aggregation degree of the main protein of the royal jelly is regulated and controlled:
(1) The method for separating and purifying the main protein MRJPs of the royal jelly from the royal jelly comprises the following specific steps:
400 g of fresh royal jelly sample (selected royal jelly is derived from the institute of honey of the national academy of agricultural sciences, bee variety is Italian bee) is weighed and dissolved in 4000 ml of ultrapure water to prepare a mixed solution;
placing the mixed solution into a box containing ice cubes, stirring with an electromagnetic stirrer at 600 r/min for 1 hour, centrifuging the supernatant on a high-speed centrifuge at 12000 rpm for 15min, and allowing the supernatant in each centrifuge tube to pass through a 0.45 μm microporous filter membrane; combining the filtrate with the filtrate to obtain a main protein solution of the royal jelly;
detecting a main protein solution of the royal jelly, wherein the main protein solution consists of MRJP1-9, and the relative contents of MRJP1-3 and MRJP5 are 31%, 16%, 26% and 9% respectively; MRJP4, MRJP7 and MRJP9 account for 4.8%, 0.33% and 0.05%, respectively; whereas the MRJP6 and MRJP8 contents are both lower than 0.01%.
(2) Carrying out ultrahigh pressure treatment on the extracted and purified MRJPs protein by utilizing high hydrostatic pressure;
(3) Determining the protein particle size, the sulfhydryl hydrophobic content and the polydispersity of MRJPs protein, adopting ExtraTree, adaBoost, gradientBoost mathematical model, and constructing aggregation regulation model by Gradientboosting algorithm, wherein the processing parameters are used as
Figure SMS_10
Protein aggregation index as +.>
Figure SMS_11
；
During the training process
Figure SMS_12
The expression is->
Figure SMS_13
I represents an ith sample, m and n respectively represent high-pressure processing intensity and time, the value range of m is 0-600, and the value range of n is 0-30; />
Figure SMS_14
The expression is
Figure SMS_15
Q, w and e respectively represent the size of protein particles, the hydrophobic content of sulfhydryl groups and the polydispersity index, wherein the size of the protein particles ranges from 5 to 1000, the content of sulfhydryl groups ranges from 0 to 100, the polydispersity index ranges from 0 to 1, and the method of one-step cross validation is used for inspection in the model training process, and then model evaluation is carried out to select the optimal model.
Calculation using the following formula
Figure SMS_16
Figure SMS_17
And->
Figure SMS_18
The predictive power and robustness of the model are evaluated. />
Figure SMS_19
In the method, in the process of the invention,
Figure SMS_20
the true value, the predicted value and the average value are respectively. SSres is the sum of squares of the residuals, also called sum of squares of the residuals; SStot is the sum of the total squares; n is the number of samples; MAE represents the difference between the true value and the predicted value, which reflects the true error by averaging the absolute differences of the data sets; MSE represents the expected value of the square error; RMSE represents the standard deviation of the prediction error.
2. For step (2), the influence of different high hydrostatic pressure treatment pressures and times on the aggregation behavior of MRJPs is measured at normal temperature, and the specific effects are shown in the following table 1:
table 1: MRJPs aggregation degree parameter under different high hydrostatic pressure treatment pressures and times
Figure SMS_21
/>
Figure SMS_22
At lower pressure, a medium time treatment (10-15 min) resulted in an increase in the average particle size and polydispersity of the MRJPs, indicating that the solution presented a polydisperse system, helping to form larger particles. When the treatment time is increased to 20 min, the average particle size of the MRJPs is obviously reduced, but the polydispersity coefficient reaches the maximum value, which shows that the extension of the treatment time is favorable for the depolymerization of the MRJPs to form smaller particles; the particle size of the MRJPs solution gradually becomes smaller along with the increase of the treatment pressure (50-200 MPa) and reaches the minimum particle size under the condition that the treatment time is 15min, and when the treatment pressure is further increased (200-600 MPa), smaller particle size and polydispersity can be obtained under the lower treatment time (5 min), and the results show that the aggregation degree of the MRJPs can be better regulated and controlled when the medium-pressure treatment is medium-time and the high-pressure treatment is low.
FIG. 1 shows MRJPs particle size distribution plots at different high hydrostatic pressure process pressures and times; the result shows that the high hydrostatic pressure can obviously change the particle size distribution of the MRJPs solution, especially the particle size distribution is more uniform along with the increase of the treatment pressure (50-200 MPa), wherein the maximum peak appears in the particle size distribution when the treatment time is 15 min. When the treatment pressure is further increased, a more uniform particle size distribution peak can be obtained with a lower treatment time, and the increase of the treatment time leads to the occurrence of a plurality of peaks of the particle size distribution, particularly distribution peaks located at 500-1000 nm and above 3000 nm. In summary, the high hydrostatic pressure treatment parameters of 200 MPa-15 min and 600 MPa-5 min have better effect on improving the aggregation particle size of MRJPs.
FIG. 2 shows TEM results of MRJPs solutions at different high hydrostatic pressure treatment pressures and times (where g 1-g 20 are the same as the treatment pressures and times of A1-A20, respectively, in Table 1 above). While MRJPs solution without high hydrostatic pressure treatment shows fiber aggregate structure, the use of high hydrostatic pressure treatment can significantly improve MRJPs fiber aggregate, breaking it into smaller aggregates. Under the treatment of 50-200 MPa, the aggregation degree of the MRJPs is obviously improved along with the increase of the treatment time (5-15 min), and especially under the condition of 15min of 200MPa treatment, the MRJPs solution is mainly composed of small aggregates and small protein particles; with further increase of the treatment pressure (> 200 MPa), the particles of the MRJPs solution become smaller and uniform gradually under the condition of 5min of treatment time, and the best treatment pressure is achieved under 600 MPa; as the treatment time further increases, small aggregates in the MRJPs solution re-aggregate to form larger protein particles.
3. The data set is divided by using a leave-one-out method, and training is carried out by combining with ensemble learning, the specific result is shown in fig. 3, which is a training schematic diagram of an MRJPs aggregation regulation model, and the MRJPs aggregation regulation model under high hydrostatic pressure constructed by combining the three models ExtraTree, adaBoost, gradientBoost with the leave-one-out method through cross verification is shown in the following table 2:
TABLE 2
Figure SMS_23
As can be seen from Table 2, gradientBoosting has the best predicted results on average particle size and polydispersity, with the minimum MAE and RMSE. And AdaBoost has the best predicted result in the prediction of thiol content.
The MRJPs aggregation regulation parameters under high hydrostatic pressure predicted by the optimal model are shown in figure 4, the optimal model has good prediction capability on aggregation indexes such as average particle size, mercapto content, polydispersity coefficient and the like, the fitting coefficient R2 of the predicted value and the true value exceeds 0.92, and MAE and RMSE values are smaller. In the important contribution degree, the influence of high-voltage strength on the aggregation behavior of the MRJPs is the greatest, and the weight of the MRJPs exceeds 74%.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (9)

1. The method for regulating and controlling the aggregation of the main protein of the royal jelly is characterized in that the regulation and control of the aggregation of the main protein of the royal jelly is realized by directionally controlling the aggregation degree of the main protein of the royal jelly through a processing technology, and the specific method comprises the following steps:
s1, separating and purifying main proteins (MRJPs) of the royal jelly from the royal jelly;
s2, performing ultrahigh pressure treatment on the extracted and purified MRJPs protein by using high hydrostatic pressure;
s3, determining aggregation indexes of the MRJPs protein, and constructing an aggregation regulation model by means of Gradientboosting algorithm.
2. The method for regulating and controlling the aggregation of main proteins of royal jelly according to claim 1, which is characterized in that: the main protein of Lac Regis Apis in S1 is selected from MRJP1, MRJP2, MRJP3, MRJP4, MRJP5, MRJP6, MRJP7, MRJP8, MRJP9, MRJP10, or their mixture.
3. The method for regulating and controlling the aggregation of main proteins of royal jelly according to claim 1, which is characterized in that: the high hydrostatic pressure treatment temperature in the step S2 is 4-25 ℃, the treatment time is 0-30 min, and the treatment pressure is 0-600 Mpa.
4. The method for regulating and controlling the aggregation of main proteins of royal jelly according to claim 1, which is characterized in that: the aggregation index comprises the particle size of protein, the hydrophobic content of sulfhydryl, fluorescence intensity, polydisperse coefficient and radius of gyration.
5. The method for regulating and controlling the aggregation of main proteins of royal jelly according to claim 4, which is characterized in that: the aggregation regulation model is constructed by a mathematical model, wherein the processing parameters are used as X, and the protein aggregation index is used as Y.
6. The method for regulating and controlling the aggregation of main proteins of royal jelly according to claim 5, which is characterized in that: the mathematical model is to construct an aggregate parameter prediction model using ExtraTree, adaBoost, gradientBoost.
7. The method for regulating and controlling the aggregation of main proteins of royal jelly according to claim 6, which is characterized in that: the aggregation parameter prediction model is in the training process
Figure QLYQS_1
The expression is->
Figure QLYQS_2
I represents an ith sample, m and n respectively represent high-pressure processing intensity and time, the value range of m is 0-600, and the value range of n is 0-30; />
Figure QLYQS_3
The expression is
Figure QLYQS_4
Q, w and e respectively represent the particle size of the protein, the hydrophobic content of sulfhydryl groups and the polydispersity, wherein the particle size of the protein ranges from 5 to 1000, the content of sulfhydryl groups ranges from 0 to 100, and the polydispersity ranges from 0 to 1.
8. The method for regulating and controlling the aggregation of main proteins of royal jelly according to claim 7, which is characterized in that: the model training process uses leave-one-out cross-validation for verification, and then model evaluation is performed to select the best model.
9. The method for regulating and controlling the aggregation of main proteins of royal jelly according to claim 8, wherein the method and the step of model evaluation are as follows:
calculation using the following formula
Figure QLYQS_5
And->
Figure QLYQS_6
Evaluating the predictive power and robustness of the model;
Figure QLYQS_7
；
in the method, in the process of the invention,
Figure QLYQS_8
respectively a true value, a predicted value and an average value,SSresis the sum of squares of the residuals, also called the sum of squares of the residuals;SStotis the sum of the total squares;nis the number of samples;MAErepresenting the difference between the true value and the predicted value, the predicted value reflecting the true error by an average of absolute differences to the dataset;MSErepresenting the expected value of the square error;RMSErepresenting the standard deviation of the prediction error. />
CN202310502527.3A 2023-05-06 2023-05-06 Method for regulating and controlling aggregation of main protein of royal jelly Active CN116210798B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310502527.3A CN116210798B (en) 2023-05-06 2023-05-06 Method for regulating and controlling aggregation of main protein of royal jelly

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310502527.3A CN116210798B (en) 2023-05-06 2023-05-06 Method for regulating and controlling aggregation of main protein of royal jelly

Publications (2)

Publication Number Publication Date
CN116210798A true CN116210798A (en) 2023-06-06
CN116210798B CN116210798B (en) 2023-07-18

Family

ID=86580906

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310502527.3A Active CN116210798B (en) 2023-05-06 2023-05-06 Method for regulating and controlling aggregation of main protein of royal jelly

Country Status (1)

Country Link
CN (1) CN116210798B (en)

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050020818A1 (en) * 1999-10-25 2005-01-27 Robinson Anne Skaja Use of hydrostatic pressure to inhibit and reverse protein aggregation and facilitate protein refolding
US20080161242A1 (en) * 2006-09-15 2008-07-03 Randolph Theodore W High pressure treatment of proteins for reduced immunogenicity
CN104849232A (en) * 2015-04-27 2015-08-19 中国农业科学院蜜蜂研究所 Method for rapid detection of contents of water and protein in royal jelly

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050020818A1 (en) * 1999-10-25 2005-01-27 Robinson Anne Skaja Use of hydrostatic pressure to inhibit and reverse protein aggregation and facilitate protein refolding
US20080161242A1 (en) * 2006-09-15 2008-07-03 Randolph Theodore W High pressure treatment of proteins for reduced immunogenicity
CN104849232A (en) * 2015-04-27 2015-08-19 中国农业科学院蜜蜂研究所 Method for rapid detection of contents of water and protein in royal jelly

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
JIANYING GUO等: "Royal Jelly Protected against Dextran-Sulfate-Sodium-Induced Colitis by Improving the Colonic Mucosal Barrier and Gut Microbiota", NUTRIENTS, vol. 14, no. 10 *
周一鸣: "高静水压和热处理对荞麦蛋白功能性质的影响", 食品科学, vol. 42, no. 05 *
王晨笑等: "高静压处理对植物蛋白消化性的影响", 保鲜与加工, vol. 20, no. 04 *

Also Published As

Publication number Publication date
CN116210798B (en) 2023-07-18

Similar Documents

Publication Publication Date Title
Lorente et al. Steam explosion and vibrating membrane filtration to improve the processing cost of microalgae cell disruption and fractionation
Youwei et al. Grape Preservation Using Chitosan Combined with β‐Cyclodextrin
Derossi et al. From biorefinery of microalgal biomass to vacuum impregnation of fruit. A multidisciplinary strategy to develop innovative food with increased nutritional properties
Cao et al. Nondestructive determination of the total mold colony count in green tea by hyperspectral imaging technology
CN116210798B (en) Method for regulating and controlling aggregation of main protein of royal jelly
Bao et al. Green alternative methods for pretreatment of whole jujube before the drying process
Wu et al. Prediction of pork storage time using Fourier transform near infrared spectroscopy and Adaboost‐ULDA
Meda et al. Optimization of microwave-vacuum drying processing parameters on the physical properties of dried Saskatoon berries
Jiang et al. Rapid identification of fermentation stages of bioethanol solid-state fermentation (SSF) using FT-NIR spectroscopy: comparisons of linear and non-linear algorithms for multiple classification issues
Sun et al. Optimization method of microwave drying process parameters for rice
Zou et al. Research on peanut variety classification based on hyperspectral image
Popa et al. Influence of convective and vacuum-type drying on quality, microstructural, antioxidant and thermal properties of pretreated Boletus edulis mushrooms
Xing et al. Physiological alterations and nondestructive test methods of crop seed vigor: A comprehensive review
Zhang et al. Identification of multiple raisins by feature fusion combined with NIR spectroscopy
Dumitru Veleșcu et al. Research on the process of convective drying of apples and apricots using an original drying installation
CN106338488A (en) Method for fast undamaged determination of transgenic soybean milk powder
CN111154666B (en) Leuconostoc citreum with starch agglutination activity
Ye et al. Freeze-thawing treatment as a simple way to tune the gel property and digestibility of minced meat from red swamp crayfish (Procambarus clarkiix)
Yang et al. Quantitative proteomics analysis on the meat quality of processed pale, soft, and exudative (PSE)-like broiler pectoralis major by different heating methods
Yoosa et al. The Effect Moisture Residue in Oil Palm Fruits with Microwave Technique: Quantifying the Significant Factor of Residual Moisture as the Process Parameter for Commercial Sterilization
Mehta et al. A statistical and neural network-assisted sustainable integrated process-based on ‘zero solid waste’for the extraction of polyphenols, dietary fiber and xylooligosaccharide from de-oiled rice and corn bran
Joardder et al. Retaining Quality When Drying Food: Challenges and Solutions
CN109765197A (en) A kind of method for quick identification of chilled atlantic salmon and freeze thawing atlantic salmon
Unluturk et al. Process neural network method: case study I: discrimination of sweet red peppers prepared by different methods
Cazón Díaz et al. Rapid authentication and composition determination of cellulose films by UV-VIS-NIR spectroscopy

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