A detection system for components of monk fruit extract

Abstract

The invention discloses a detection system for components of a monk fruit extract, belonging to the technical field of monk fruit production and processing. The system comprises a sample collection module, a component analysis module and a server. The sample collection module is used for collecting a monk fruit extract sample, establishing a holding pool model, establishing a model coordinate system in the holding pool model, and setting the model coordinate system in proportion in the holding pool and marking it as a physical coordinate system. The system obtains the density of degradation components and the density of monk fruit extract components, illuminates the holding pool, obtains a high-definition image of the extract in the holding pool under illumination, collects the size of the holding pool, establishes a point model, obtains a point coordinate set through the point model, inputs the point coordinate set into the holding pool model, and distinguishes and marks the points. The mutual cooperation between the sample collection module and the extract analysis unit solves the problem of front-end heating in the monk fruit extraction process, and prevents the production and processing of the monk fruit from being affected by temperature problems.

Description

Technical Field

[0001] The invention belongs to the technical field of detection of components of Momordica grosvenori, and in particular is a detection system for components of Momordica grosvenori extract. Background Art

[0002] Existing monk fruit extraction devices usually use soaking, boiling, solvents and other methods to extract components, which require heating during the extraction process. If the temperature is not well controlled, the effective ingredients will often undergo oxidative degradation during the extraction process, causing the monk fruit extract to deteriorate and become ineffective, resulting in a waste of resources; because the other extraction steps in the extraction process are basically unchanged, they will not promote the oxidative degradation of the effective ingredients. The factor that promotes the oxidative degradation of the effective ingredients is temperature. Therefore, by testing the components of the monk fruit extract, it can be determined whether the front-end temperature is reasonable. Summary of the Invention

[0003] In order to solve the problems existing in the above-mentioned solutions, the present invention provides a system for detecting components of Momordica grosvenori extract.

[0004] The purpose of the present invention can be achieved through the following technical solutions:

[0005] A system for detecting components of a monk fruit extract, comprising a sample collection module, a component analysis module, and a server;

[0006] The sample collection module is used to collect samples of the monk fruit extract, establish a holding pool model, establish a model coordinate system in the holding pool model, set the model coordinate system in proportion in the holding pool, and mark it as a physical coordinate system; obtain the density of the degradation component and the density of the monk fruit extract component, illuminate the holding pool, obtain a high-definition image of the extract in the holding pool under illumination, collect the size of the holding pool, establish a point model, obtain a point coordinate set through the point model, input the point coordinate set into the holding pool model, and distinguish and mark it, set a collection interval for the point coordinate set in the holding pool model, sample through a sampling device, set a positioning unit on the sampling device, the positioning unit is used to locate the position of the sampling device in real time, and send the collected position coordinates to the sample collection module, which is displayed in real time in the holding pool model, and when the coordinates sent by the positioning unit are within the collection interval, a collection signal is generated, the movement of the sampling device is stopped, and sample sampling is performed;

[0007] The component analysis module includes an extract analysis unit, which is used to detect and analyze the components of the extract, obtain an extract sample set, which is all samples collected by the sampling device, detect the proportion of each component in the extract sample set, and mark the proportion of the degradation component as Pi, where i = 1, 2, ..., n, where n is a positive integer, according to the formula Calculate the average value Ps of the proportion of degradation components. When Ps>X1 and any N Pi>X2, there is a problem with temperature control and the temperature should be adjusted. Because other extraction steps are basically unchanged during the extraction process, they will not cause the effective ingredients to undergo oxidative degradation. The factor that causes the effective ingredients to undergo oxidative degradation is temperature. When the average proportion of degradation components exceeds the standard and the proportions of multiple degradation components exceed the set value, it can be determined that there is a problem with the temperature control at the front end.

[0008] Furthermore, X1 and X2 are both thresholds, N is a positive integer, and the value range of N is [2, 5].

[0009] Furthermore, the component analysis module further includes an additive analysis unit, which is used to detect and analyze the components of the additives; the specific method includes:

[0010] Collect several additional product samples, detect the components and corresponding component proportions in the additional product samples, calculate the average proportion of each component, establish a detailed list of additional products, classify them according to the components, mark the categories with an average proportion lower than the threshold X3 as low-quantity categories, mark the categories with an average proportion higher than the threshold X4 as high-quantity categories, and mark the rest as normal categories;

[0011] According to the number of additional product samples, threshold X3 and threshold X4, the corresponding output of low-volume classification, high-volume classification and normal classification in the production process of one day is estimated; according to the additional product detailed list, the usage direction, production process and construction cost of the corresponding additional products are collected from the Internet, and the collected usage direction, production process, construction cost, corresponding proportion classification information and additional product detailed list are sent to the user, and the user manually selects the usable additional products and marks them as reused components; a reused component document library is established, and corresponding documents are matched in the reused component document library according to the reused components, and the matched documents are sent to the user.

[0012] Furthermore, the method for establishing a reuse component document library includes:

[0013] Obtain documents on reused components from the Internet to form a document set, obtain subject words related to reused components, and mark them as reuse subject words; collect the weight values ​​of the reuse subject words contained in each document in the document set, map the documents to the vector space and construct a MeSH space matrix;

[0014] Calculate the weight W of the reused subject word g in the MeSH space matrix of the subject word document set A An ; According to the weight value of all reused keywords in the keyword document set A, the vector formula of the keyword document set A is constructed: W A=(w A1 , w A2 ,…,w Am ); Calculate the cosine similarity between subject word document set A and subject word document set B in the MeSH space matrix;

[0015]

[0016] A storage unit is established, and the subject word document set B that meets the similarity requirements is stored in the storage unit, and the storage unit is marked as a reuse component document set library.

[0017] Furthermore, f refers to the total number of documents containing the subject word A; n Aj is the number of MeSH subject terms corresponding to the jth article in the articles related to subject term A; e j is the number of times the jth document is cited; k is the number of documents in f that contain the reuse keyword g, 1≤g≤m, m is the total number of reuse topics; e i is the number of times the i-th document is cited; f' is the number of intersections between the document set corresponding to subject word B and the document set corresponding to subject word A; subject word B is the subject word in subject word document set B, and subject word document set B is the subject word document set set through retrieval, which is used to supplement the reuse component document set library, q g is the number of articles containing the reuse keyword g.

[0018] Furthermore, W Bg is the weight value of the reused subject word g in the subject word document set B and the MeSH space matrix.

[0019] Furthermore, the method of mapping the literature into the vector space to construct the MeSH space matrix includes:

[0020] Extract the reused subject words of each document in the document collection, extract all the reused subject words in the document collection, and form a subject word set with all the reused subject words;

[0021] When there is a reused subject word in the subject word set in the document, the reused subject word is marked with 1, otherwise it is marked with 0; the vector result corresponding to the document

[0022] When all the reused subject terms of the documents in the subject document set are marked with 1 or 0, a document and reused subject term matrix is ​​formed using all the marked documents; the weight value of the reused subject term marked as 1 in the document is calculated, and the document is mapped to the vector space according to the weight value of all the reused subject terms marked as 1 in the same document: di = (Wi1, Wi2, ..., Wix), and all the documents mapped to the vector space are used to form a MeSH space matrix.

[0023] Furthermore, di is the i-th document in the subject document set d; Wix is ​​the weight value of di and the reuse subject term x it contains, and x is the total number of reuse subject terms in di.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] The cooperation between the sample collection module and the extract analysis unit solves the problem of front-end heating during the extraction process of Monk Fruit, thus preventing the production and processing of Monk Fruit from being affected by temperature problems. The cooperation between the holding pool model and the sampling device allows the sampling personnel to intuitively understand the sampling process, making the sampling more accurate and avoiding the problem of inaccurate sampling caused by the flow of liquid, which may cause the sampling device to deviate from the sampling point, and the sampling personnel may not be able to detect it due to visibility problems, as in conventional sampling.

[0026] The additive analysis unit detects and analyzes the components of additives, recommends reasonable professional literature, and helps users rationally plan the production and reuse of additives. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0028] Figure 1 This is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0029] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0030] like Figure 1As shown, a system for detecting components of Luo Han Guo extract includes a sample collection module, a component analysis module and a server;

[0031] The sample collection module is used to collect samples of the Momordica grosvenori extract. When the temperature is not well controlled, the effective ingredients often undergo oxidative degradation during the extraction process. There are degraded components in the Momordica grosvenori extract. However, since the amount of the Momordica grosvenori extract is large, and the proportion of degraded components is small, if the collection method is unreasonable and incomplete, some of the effective ingredients may undergo oxidative degradation. If the degraded components are not collected, the original control temperature will still be used, affecting the extraction of the Momordica grosvenori. Therefore, the sample collection module is used to solve this problem. The specific method includes:

[0032] A three-dimensional model of the storage tank for the monk fruit extract is established and marked as the storage tank model. A spatial coordinate system is established in the storage tank model. The origin and direction of the spatial coordinate system are not fixed and can be adjusted according to actual needs. For example, the center, inflection point, etc. of the storage tank model are used as the origin and marked as the model coordinate system. The model coordinate system is set proportionally in the storage tank, which is equivalent to setting out; it is marked as the physical coordinate system.

[0033] Obtain the density of the degradation components and the density of the monk fruit extract components, illuminate the holding pool, and use visible light, blue light, red light and other light. The specific light used can be freely adjusted according to the components to be detected. Obtain a high-definition image of the extract in the holding pool under illumination, collect the size of the holding pool, and establish a point model. The point model is used to generate a set of point coordinates that need to be sampled based on the input data. The point model is implemented based on a DNN network or a CNN network, and the real coordinate system, the high-definition image of the extract, the size of the holding pool, and the degradation components are combined into a point model. The density and density of the components of the monk fruit extract are integrated and marked as point input data, the point input data is input into the point model to obtain a point coordinate set, the point coordinate set is input into the holding pool model, and is distinguished and marked. The distinguished marking is to make the point coordinate set intuitively visible in the holding pool model, and different colors can be used for marking; a collection interval is set for the point coordinate set in the holding pool model, that is, a spherical collection interval is established with the point coordinate as the center, and the radius of the collection interval is set according to the collection accuracy requirements and the density of the point coordinates;

[0034] Sampling is carried out through a sampling device. The sampling device can use an existing sampling device. A positioning unit is set on the sampling device. The positioning unit is used to locate the position of the sampling device in real time and send the collected position coordinates to the sample collection module. The collected coordinates use the real coordinate system and are displayed in real time in the holding pool model. When the coordinates sent by the positioning unit are within the collection interval, a collection signal is generated, the movement of the sampling device is stopped, and sample sampling is carried out.

[0035] The component analysis module is used to detect the components of the collected sample, including an extract analysis unit and an additive analysis unit. The extract analysis unit is used to detect and analyze the components of the extract. The specific method includes:

[0036] Obtain an extract sample set, detect the proportion of each component in the extract sample set, and mark the proportion of the degradation component as Pi, where i = 1, 2, ..., n, and n is a positive integer; according to the formula Calculate the average value Ps of the degradation component ratio. When Ps>X1 and any N Pi>X2, there is a problem with temperature control and the temperature should be adjusted. X1 and X2 are both thresholds, and N is a positive integer in the range of [2, 5].

[0037] The additive analysis unit is used to detect and analyze the components of the additives; because a large number of additives are produced during the extraction process of Monk Fruit, such as protein, dietary fiber, flavonoids, polyphenols, etc. in Monk Fruit, if the additives can be fully utilized, it will bring considerable economic benefits to the enterprise and increase the utilization rate of resources. The specific methods include:

[0038] Several additional product samples are collected, the components and corresponding component proportions in the additional product samples are detected, the average proportion of each component is calculated, and an additional product detailed list is established. The additional products are classified according to the components, and the categories with an average proportion lower than a threshold value X3 are marked as low-quantity categories, the categories with an average proportion higher than a threshold value X4 are marked as high-quantity categories, and the remaining categories are marked as normal categories; the corresponding output of low-quantity categories, high-quantity categories, and normal categories in a day's production process is estimated based on the number of additional product samples, thresholds X3, and thresholds X4; the usage direction, production process, and construction cost of the corresponding products are collected from the Internet based on the additional product detailed list, and the collected usage direction, production process, construction cost, corresponding proportion classification information, and the additional product detailed list are sent to the user, and the corresponding proportion classification information indicates whether the corresponding component belongs to the low-quantity category, high-quantity category, or normal category; as well as the corresponding estimated daily output; the user manually selects the usable additional products and marks them as reused components; a reused component literature library is established, and corresponding documents are matched in the reused component literature library based on the reused components, and the matched documents are sent to the user.

[0039] Methods for establishing a collection of reused content documents include:

[0040] Obtain literature on recycled ingredients from the Internet, which refers to technical solutions for the production and reuse of recycled ingredients; form a literature collection, obtain subject terms related to recycled ingredients, and mark them as recycled subject terms; take dietary fiber as an example, dietary fiber has many reuse uses, and dietary fiber has a strong ability to absorb water or bind with water. This effect can increase the volume of feces in the intestine, speed up its transportation speed, and reduce the time that harmful substances in it contact the intestinal wall; some dietary fibers have strong viscosity and can form mucus-type solutions, including pectin, gum, seaweed polysaccharides, etc.; dietary fiber has the function of binding bile acid and cholesterol; dietary fiber can bind to inorganic salts such as potassium, sodium, iron and other cations in the gastrointestinal tract to form dietary fiber complexes, affecting their absorption; collect the weight values ​​of the recycled subject terms contained in each document in the literature collection, map the documents to the vector space to construct a MeSH space matrix;

[0041] Calculate the weight W of the reused subject word g in the MeSH space matrix of the subject word document set A An ; Wherein the subject word document set A is a reused subject word document set A produced from historical documents related to the enterprise through the above steps;

[0042] Among them, f refers to the total number of documents containing the subject word A; n Aj is the number of MeSH subject terms corresponding to the jth article in the articles related to subject term A; e j is the number of times the jth document is cited; k is the number of documents in f that contain the reuse keyword g, 1≤g≤m, m is the total number of reuse topics; e i is the number of times the i-th document is cited; f' is the number of intersections between the document set corresponding to subject word B and the document set corresponding to subject word A; subject word B is the subject word in subject word document set B, and subject word document set B is the subject word document set set through retrieval, which is used to supplement the reuse component document set library, q g is the number of articles containing the reuse keyword g;

[0043] According to the weight value of all reused keywords in the keyword document set A, the vector formula of the keyword document set A is constructed: W A =(w A1 , w A2 ,…,w Am ); Calculate the cosine similarity between subject word document set A and subject word document set B in the MeSH space matrix;

[0044] Among them, W Bgis the weight value of the subject word document set B and the reused subject word g in the MeSH space matrix; a storage unit is established, the subject word document set B that meets the similarity requirements is stored in the storage unit, and the storage unit is marked as a reused component document set library.

[0045] Methods for mapping documents into vector space and constructing MeSH space matrix include:

[0046] Extract the reused subject words of each document in the document collection, extract all the reused subject words in the document collection, and form a subject word set with all the reused subject words; when a reused subject word in the subject word set exists in the document, the reused subject word is marked with 1, otherwise it is marked with 0; the vector result corresponding to the document Where 1 represents that the document contains the MeSH term at the corresponding position, and 0 represents that the document does not contain the MeSH term; when the reuse subject terms of all documents in the subject document set are marked with 1 or 0, all the marked documents are used to form a document and reuse subject term matrix; the weight value of the reuse subject term marked as 1 in the document is calculated, and the document is mapped to the vector space according to the weight value of all the reuse subject terms marked as 1 in the same document: di = (Wi1, Wi2, ..., Wix), where di is the i-th document in the subject document set d; Wix is ​​the weight value of di and the reuse subject term x it contains, and x is the total number of reuse subject terms in di; all documents mapped to the vector space are used to form a MeSH space matrix.

[0047] The above formulas are all calculated by removing dimensions and taking their numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technicians in this field according to actual conditions or obtained by simulating a large amount of data.

[0048] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A system for detecting components of Momordica grosvenori extract, characterized in that: Including sample collection module, component analysis module and server; The sample collection module is used to collect samples of the monk fruit extract, establish a holding pool model, establish a model coordinate system in the holding pool model, set the model coordinate system in proportion in the holding pool, and mark it as a physical coordinate system; obtain the density of the degradation component and the density of the monk fruit extract component, illuminate the holding pool, obtain a high-definition image of the extract in the holding pool under illumination, collect the size of the holding pool, establish a point model, obtain a point coordinate set through the point model, input the point coordinate set into the holding pool model, and distinguish and mark it, set a collection interval for the point coordinate set in the holding pool model, sample through a sampling device, set a positioning unit on the sampling device, the positioning unit is used to locate the position of the sampling device in real time, and send the collected position coordinates to the sample collection module, which is displayed in real time in the holding pool model, and when the coordinates sent by the positioning unit are within the collection interval, a collection signal is generated, the movement of the sampling device is stopped, and sample sampling is performed; The component analysis module includes an extract analysis unit, which is used to detect and analyze the components of the extract, obtain an extract sample set, detect the proportion of each component in the extract sample set, mark the proportion of the degradation component as Pi, and calculate the ratio according to the formula Calculate the average value Ps of the degradation component ratio. When Ps>X1 and any N Pi>X2, there is a problem with temperature control and the temperature should be adjusted. X1 and X2 are both thresholds, N is a positive integer, and the value range of N is [2, 5].

2. A detection system for components of Momordica grosvenori extract according to claim 1, characterized in that: The component analysis module further includes an additive analysis unit, which is used to detect and analyze the components of the additives. The specific method includes: Collect several additional product samples, detect the components and corresponding component proportions in the additional product samples, calculate the average proportion of each component, establish a detailed list of additional products, classify them according to the components, mark the categories with an average proportion lower than the threshold X3 as low-quantity categories, mark the categories with an average proportion higher than the threshold X4 as high-quantity categories, and mark the rest as normal categories; According to the number of additional product samples, threshold X3 and threshold X4, the corresponding output of low-volume classification, high-volume classification and normal classification in the production process of one day is estimated; according to the additional product detailed list, the usage direction, production process and construction cost of the corresponding product are collected from the Internet, and the collected usage direction, production process, construction cost, corresponding proportion classification information and additional product detailed list are sent to the user, and the user manually selects the usable additional products and marks them as reused components; a reused component document library is established, and corresponding documents are matched in the reused component document library according to the reused components, and the matched documents are sent to the user.

3. A detection system for components of Momordica grosvenori extract according to claim 2, characterized in that: Methods for establishing a collection of reused content documents include: Obtain documents on reused components from the Internet to form a document set, obtain subject words related to reused components, and mark them as reuse subject words; collect the weight values ​​of the reuse subject words contained in each document in the document set, map the documents to the vector space and construct a MeSH space matrix; Calculate the weight W of the reused subject word g in the MeSH space matrix of the subject word document set A An ; , according to the weight value of all reused keywords in the keyword document set A, construct the vector formula of the keyword document set A: W A =(w A1 , w A2 ,…,w Am ); Calculate the cosine similarity between subject word document set A and subject word document set B in the MeSH space matrix; ; Establish a storage unit, store the subject word document set B that meets the similarity requirement in the storage unit, and mark the storage unit as a reuse component document set library; f refers to the total number of documents containing the subject word A; n Aj is the number of MeSH subject terms corresponding to the jth article in the articles related to subject term A; e j is the number of times the jth document is cited; k is the number of documents in f that contain the reuse keyword g, 1≤g≤m, m is the total number of reuse topics; e i is the number of times the i-th document is cited; f' is the number of intersections between the document set corresponding to subject word B and the document set corresponding to subject word A; subject word B is the subject word in subject word document set B, and subject word document set B is the subject word document set set through retrieval, which is used to supplement the reuse component document set library, q g is the number of articles containing the reuse keyword g; W Bg is the weight value of the reused subject word g in the subject word document set B and the MeSH space matrix.

4. A detection system for components of Momordica grosvenori extract according to claim 3, characterized in that: Methods for mapping documents into vector space and constructing MeSH space matrix include: Extract the reused subject words of each document in the document collection, extract all the reused subject words in the document collection, and form a subject word set with all the reused subject words; When there is a reused subject word in the subject word set in the document, the reused subject word is marked with 1, otherwise it is marked with 0; the vector result corresponding to the document ; After all reused subject terms in the subject document set are marked with 1 or 0, a document and reused subject term matrix is ​​formed using all marked documents; the weight value of the reused subject term marked as 1 in the document is calculated, and the document is mapped to a vector space according to the weight values ​​of all reused subject terms marked as 1 in the same document: di = (Wi1, Wi2, ..., Wix), and a MeSH space matrix is ​​formed using all documents mapped to the vector space; di is the i-th document in the subject document set d; Wix is ​​the weight value of di and the reuse subject term x it contains, and x is the total number of reuse subject terms in di.

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