Food quality intelligent management method and system and medium

Abstract

The invention relates to the technical field of food quality management, and provides a food quality intelligent management method and system and a medium, and the method comprises the steps: obtaining multi-dimensional food quality safety parameters, and extracting food quality safety feature information; constructing a food quality safety feature sequence data set; obtaining a food quality safety coefficient of each dimension according to the food quality safety feature sequence data set; and obtaining a food quality risk index according to the food quality safety coefficient of each dimension, and adjusting monitoring management weights of different processes related to the food quality safety based on the food quality risk index. According to the invention, food quality safety can be comprehensively considered and evaluated from different angles and the whole process of food based on multi-dimensional parameters, intelligent management of food quality safety is realized, the problem that monitoring is not in place when the food quality safety is evaluated and monitored based on single-dimensional data is avoided, and the safety of food quality is improved. And the accuracy of food quality safety monitoring is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of food quality management, and in particular to an intelligent food quality management method, system and medium. Background Art

[0002] Food quality is closely related to food safety. In the existing technology, the detection and monitoring of food quality and safety mostly stays at a single level such as raw materials, production, sealed packaging or cold chain transportation, lacking comprehensive consideration of the quality and safety of the entire food process, and its intelligent management level and efficiency need to be improved.

[0003] In addition, existing food quality and safety control methods, such as the Chinese invention patent "Food safety management system and method thereof" with application number CN202311091758.6, the Chinese invention patent "Hidden Markov model food quality assessment method based on grey correlation analysis" with application number CN201910330705.2, and the Chinese invention patent "Food safety automated diagnosis system and method based on artificial intelligence" with application number "CN202411046097.X", etc., are not based on multi-dimensional parameters and combined with different angles to evaluate food quality and safety, and their accuracy has room for further improvement.

[0004] Therefore, there is an urgent need to develop a management method that can comprehensively consider and evaluate food quality and safety based on multi-dimensional parameters from different angles and the entire food process. Summary of the invention

[0005] In order to solve the problems existing in the prior art, the present invention provides a method, system and medium for intelligent management of food quality, which can obtain multi-dimensional food quality and safety parameters according to different processes related to food quality and safety, extract feature sequences of food quality and safety feature information to construct a food quality and safety feature sequence data set, obtain the food quality and safety coefficient of each dimension and the food quality risk index, and finally adjust the monitoring and management weights of different processes related to food quality and safety based on the food quality risk index, so as to realize intelligent management of food quality and safety. It comprehensively considers and evaluates food quality and safety based on multi-dimensional parameters from different angles and the entire food process, which can improve the intelligence, efficiency and accuracy of food quality management.

[0006] A method for intelligent management of food quality comprises the following steps:

[0007] Acquire multi-dimensional food quality and safety parameters for different processes related to food quality and safety, and extract food quality and safety characteristic information based on the multi-dimensional food quality and safety parameters;

[0008] Preprocessing the food quality and safety characteristic information, and extracting characteristic sequences from the preprocessed food quality and safety characteristic information to construct a food quality and safety characteristic sequence data set;

[0009] Obtaining a food quality safety coefficient for each dimension according to the food quality safety feature sequence data set;

[0010] According to the food quality and safety coefficient of each dimension, a food quality risk index is obtained, and based on the food quality risk index, the monitoring and management weights of different processes related to food quality and safety are adjusted to achieve intelligent management of food quality and safety.

[0011] The intelligent food quality management method extracts food quality and safety characteristic information through multi-dimensional food quality and safety parameters, and then constructs a food quality and safety characteristic sequence data set to obtain the food quality and safety coefficient of each dimension. According to the food quality and safety coefficient of each dimension, a food quality risk index is obtained, and the monitoring and management weights of different processes related to food quality and safety are adjusted based on the food quality risk index. The method can comprehensively consider and evaluate food quality and safety from different angles and the entire food process based on multi-dimensional parameters, realize intelligent management of food quality and safety, avoid the problem of inadequate monitoring of food quality and safety based on single-dimensional data evaluation and monitoring, and improve the accuracy of food quality and safety monitoring.

[0012] Preferably, the specific method for preprocessing the food quality and safety characteristic information comprises the following steps:

[0013] The food quality and safety characteristic information is subjected to data cleaning, weight correction and deviation compensation.

[0014] Preferably, the specific method for cleaning, weight correction and deviation compensation of the food quality and safety characteristic information comprises the following steps:

[0015] Cleaning the food quality and safety characteristic information;

[0016] Obtaining the real-time attention degree and the trend value within a preset time period of the food quality and safety characteristic information after cleaning, and performing weight correction according to the real-time attention degree, the trend value and the preset correction strategy;

[0017] Obtain error parameters that affect the food quality and safety characteristic information, and perform deviation compensation on the food quality and safety characteristic information based on the error parameters.

[0018] Preferably, the specific method for obtaining the real-time attention degree of the food quality and safety characteristic information after cleaning and the trend value within a preset time period comprises the following steps:

[0019] Obtaining the popularity of preset keywords in the food quality and safety feature information through a search engine, and obtaining the real-time attention degree according to the popularity of the preset keywords;

[0020] The average value of the change trend of the search volume of preset keywords in the food quality and safety characteristic information within a preset time period is obtained through a search engine, and the trend value is obtained according to the average value of the change trend.

[0021] The present invention provides an intelligent food quality management system, which comprises:

[0022] A characteristic information acquisition module, used to acquire multi-dimensional food quality and safety parameters for different processes related to food quality and safety, and extract food quality and safety characteristic information based on the multi-dimensional food quality and safety parameters;

[0023] A preprocessing module, used for preprocessing the food quality and safety characteristic information;

[0024] A sequence data set construction module is used to extract feature sequences from the food quality and safety feature information after preprocessing to construct a food quality and safety feature sequence data set;

[0025] A safety factor acquisition module, used to obtain the food quality safety factor of each dimension according to the food quality safety feature sequence data set;

[0026] The intelligent monitoring module is used to obtain a food quality risk index according to the food quality safety coefficient of each dimension, and adjust the monitoring and management weights of different processes related to food quality and safety based on the food quality risk index to achieve intelligent management of food quality and safety.

[0027] Preferably, the preprocessing module comprises:

[0028] A data cleaning unit, used for cleaning the food quality and safety characteristic information;

[0029] A weight correction unit, used to perform weight correction on the food quality and safety characteristic information after data cleaning;

[0030] The deviation compensation unit is used to compensate for the deviation of the food quality and safety characteristic information after weight correction.

[0031] Preferably, the weight correction unit obtains the real-time attention degree and the trend value in a preset time period of the food quality and safety feature information after cleaning, and performs weight correction according to the real-time attention degree, the trend value and the preset correction strategy.

[0032] Preferably, the food quality intelligent management system further includes:

[0033] The resource dispatching center is used to dispatch monitoring resources in the process of intelligent management of food quality and safety.

[0034] The present invention also provides a computer-readable storage medium storing a computer program, which implements the intelligent food quality management method when the computer program is executed. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The present invention can be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily drawn to scale, but the emphasis is placed on illustrating the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0036] Figure 1 It is a schematic diagram of the overall process of an intelligent food quality management method in one embodiment of the present invention;

[0037] Figure 2 It is a flowchart of a specific method for preprocessing food quality and safety characteristic information in one embodiment of the present invention;

[0038] Figure 3 It is a flowchart of a specific method for obtaining real-time attention and trend values ​​in one embodiment of the present invention. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with its embodiments. It should be understood that the specific implementation methods described herein are only used to explain the present invention and do not limit the protection scope of the present invention.

[0042] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only and do not represent the only implementation method.

[0043] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0044] The “first” and “second” mentioned in the present invention do not represent specific quantities and orders, but are merely used to distinguish names.

[0045] like Figure 1 As shown, a method for intelligent management of food quality comprises the following steps:

[0046] S1, for different processes related to food quality and safety, obtain multi-dimensional food quality and safety parameters, and extract food quality and safety characteristic information based on the multi-dimensional food quality and safety parameters.

[0047] The different processes related to food quality and safety include but are not limited to the raw material acquisition and pre-processing stage, the production stage such as cleaning, disinfection, cooking, quality inspection, packaging, warehousing, and the pre-sale stage such as freezing, loading and transportation. It is understood that the different processes include all processes from the raw material end to the user end.

[0048] The multi-dimensional food quality and safety parameters include but are not limited to environmental parameters, operating parameters and food parameters at each stage of food production and processing. The extracted food quality and safety characteristic information is related to food quality and safety, such as temperature and humidity and oxygen concentration in the processing workshop, processing temperature and pH, freezer temperature, shelf life of raw materials, color and smell of raw materials, pesticide residues and heavy metal content of raw materials, cooking time and temperature values, quality inspection pass rate, transportation time and packaging vacuum degree.

[0049] S2, preprocessing the food quality and safety characteristic information, and extracting the characteristic sequence of the preprocessed food quality and safety characteristic information to construct a food quality and safety characteristic sequence data set; the preprocessing mainly includes but is not limited to data cleaning of the food quality and safety characteristic information to eliminate useless, repeated and abnormal information and improve the quality of the food quality and safety characteristic information.

[0050] The food quality and safety feature sequence data set can be understood as a feature sequence of food quality and safety feature information and a feature data set between time, operation sequence, or production process. By constructing a food quality and safety feature sequence data set, the consistency and integrity of the data can be maintained, the analysis and mining of food quality and safety feature information can be facilitated, and the calculation efficiency of the food quality and safety coefficient in each dimension can be improved.

[0051] S3, obtaining the food quality safety coefficient of each dimension according to the food quality safety feature sequence data set.

[0052] Preferably, the food quality safety factor of each dimension is S = 1 / e λ1*Δt×λ2*f. Among them, Δt represents the total time that the food quality and safety characteristic information exceeds the corresponding safety characteristic warning value, f represents the total number of times that the food quality and safety characteristic information exceeds the corresponding safety characteristic warning value within the preset time period, and λ1 and λ2 represent the total time weight coefficient and the total number of weight coefficients, which can be set by technical personnel.

[0053] S4, according to the food quality and safety coefficient of each dimension, obtain the food quality risk index, and adjust the monitoring and management weights of different processes related to food quality and safety based on the food quality risk index to achieve intelligent management of food quality and safety.

[0054] Preferably, the food quality risk index for each process Where n represents the number of dimensions of food quality and safety parameters under this process, S i represents the food quality safety factor in the i-th dimension of the process, α i represents the proportional adjustment factor of the food quality safety factor in the i-th dimension of the process, and e represents a natural constant. By calculating the food quality risk index of each process The corresponding food production monitoring can be carried out for each process respectively. The food quality risk index is obtained based on the comprehensive analysis of the multi-dimensional food quality and safety parameters of the production process, which can comprehensively and accurately reflect the safety status of the food quality in the process.

[0055] Based on the food quality risk index, the monitoring and management weights of different processes related to food quality and safety are adjusted. The larger the food quality risk index, the larger the corresponding monitoring and management weight, and more monitoring resources are deployed, such as testing personnel, monitoring cameras, server memory, food quality testing equipment, etc. In this way, the monitoring and management weight in each production process is proportional to the food quality risk index, and targeted quality monitoring can be carried out on different production processes, thereby improving the intelligence level of food quality and safety monitoring.

[0056] To sum up, the intelligent food quality management method extracts food quality and safety characteristic information through multi-dimensional food quality and safety parameters, and then constructs a food quality and safety characteristic sequence data set to obtain the food quality and safety coefficient of each dimension. According to the food quality and safety coefficient of each dimension, the food quality risk index is obtained, and the monitoring and management weights of different processes related to food quality and safety are adjusted based on the food quality risk index. It can comprehensively consider and evaluate food quality and safety from different angles and the entire food process based on multi-dimensional parameters, realize intelligent management of food quality and safety, avoid the problem of inadequate monitoring of food quality and safety based on single-dimensional data evaluation and monitoring, and improve the accuracy of food quality and safety monitoring.

[0057] As a preferred technical solution, a specific method for preprocessing the food quality and safety characteristic information includes the following steps: data cleaning, weight correction and deviation compensation for the food quality and safety characteristic information.

[0058] The purpose of data cleaning is to remove duplicate, invalid and abnormal data and improve the quality of data. Weight correction includes weight correction of the total time weight coefficient and the total number of weight coefficients. The technicians can first preset a total time weight coefficient and a total number of weight coefficients, and then obtain the real-time attention of the food quality and safety characteristic information after cleaning and the trend value within the preset time period, and finally perform weight correction according to the real-time attention, trend value and preset correction strategy.

[0059] like Figure 2 As shown, the specific method for cleaning, weight correction and deviation compensation of the food quality and safety characteristic information includes the following steps:

[0060] S20, cleaning the food quality and safety characteristic information.

[0061] S21, obtaining the real-time attention degree and the trend value in a preset time period of the food quality and safety characteristic information after cleaning, and performing weight correction according to the real-time attention degree, the trend value and the preset correction strategy.

[0062] Preferably, in step S21, Figure 3 As shown, the specific method for obtaining the real-time attention degree of the food quality and safety characteristic information after cleaning and the trend value within a preset time period includes the following steps:

[0063] S210, obtaining the popularity of preset keywords in the food quality and safety feature information through a search engine, and obtaining the real-time attention according to the popularity of the preset keywords;

[0064] S211, obtaining, through a search engine, an average value of the change trend of the search volume of preset keywords in the food quality and safety characteristic information within a preset time period, and obtaining the trend value according to the average value of the change trend.

[0065] Specifically, the real-time attention degree can be obtained by obtaining the popularity of preset keywords in the food quality and safety feature information through a search engine, that is, the real-time attention degree is proportional to the popularity of the preset keywords, or the average popularity of multiple preset keywords is expressed as the real-time attention degree. The trend value can be obtained by obtaining the average value of the change trend of the search volume of the preset keywords in the food quality and safety feature information within a preset time period through a search engine. The preset correction strategy can be understood as weight correction of the total time weight coefficient and the total number of weight coefficients according to the real-time attention degree and the trend value within the preset time period, for example, according to the size of the real-time attention degree and the trend value, the total time weight coefficient and the total number of weight coefficients are adjusted in a corresponding proportional proportion.

[0066] S22, obtaining error parameters that affect the food quality and safety characteristic information, and performing deviation compensation on the food quality and safety characteristic information based on the error parameters.

[0067] The error parameter can be understood as the error value caused by changes in environmental parameters within a preset time period of the data acquisition unit that collects food quality and safety characteristic information, such as temperature drift of the temperature sensor caused by temperature and humidity, electromagnetic interference, etc., and food surface defect errors identified based on visual recognition technology due to aging and light changes.

[0068] Specifically, the mean value of the real-time environmental parameters within a preset time period can be calculated first, and then the ratio value between the real-time environmental parameters and the preset environmental alarm parameters can be calculated, and the weighted average value of the ratio value greater than the preset alarm threshold can be calculated, and then the food quality and safety characteristic information can be compensated for the deviation according to the weighted average value. For example, if the initial value of the food quality and safety characteristic information is C0 and the weighted average value is C1, then the food quality and safety characteristic information after deviation compensation is C2 = C0 + C1 * A. A represents the deviation compensation coefficient, which is set by the technical staff.

[0069] In this way, by cleaning, weighting and bias compensating the food quality and safety characteristic information, and comprehensively considering the impact of different factors on the accurate value of the food quality and safety characteristic information, the accuracy of the food quality and safety characteristic information can be improved, so that intelligent monitoring of food quality and safety can be achieved more accurately based on the method.

[0070] The present invention provides an intelligent food quality management system, which comprises a feature information acquisition module, a preprocessing module, a sequence data set construction module, a safety factor acquisition module and an intelligent monitoring module.

[0071] The characteristic information acquisition module is used to obtain multi-dimensional food quality and safety parameters for different processes related to food quality and safety, and to extract food quality and safety characteristic information based on the multi-dimensional food quality and safety parameters; the preprocessing module is used to preprocess the food quality and safety characteristic information.

[0072] The multi-dimensional food quality and safety parameters include but are not limited to environmental parameters, operating parameters and food parameters at each stage of food production and processing. The extracted food quality and safety characteristic information is related to food quality and safety, such as temperature and humidity and oxygen concentration in the processing workshop, processing temperature and pH, freezer temperature, shelf life of raw materials, color and smell of raw materials, pesticide residues and heavy metal content of raw materials, cooking time and temperature values, quality inspection pass rate, transportation time and packaging vacuum degree.

[0073] The food quality and safety feature sequence data set can be understood as a feature sequence of food quality and safety feature information and a feature data set between time, operation sequence, or production process. By constructing a food quality and safety feature sequence data set, the consistency and integrity of the data can be maintained, the analysis and mining of food quality and safety feature information can be facilitated, and the calculation efficiency of the food quality and safety coefficient in each dimension can be improved.

[0074] Preferably, the preprocessing module includes a data cleaning unit, a weight correction unit and a deviation compensation unit.

[0075] The data cleaning unit is used to perform data cleaning on the food quality and safety characteristic information; the weight correction unit is used to perform weight correction on the food quality and safety characteristic information after data cleaning.

[0076] The purpose of data cleaning is to remove duplicate, invalid and abnormal data and improve the quality of data. Weight correction includes weight correction of total time weight coefficient and total number of weight coefficient. The technicians can first preset a total time weight coefficient and a total number of weight coefficient, and then obtain the real-time attention of the food quality and safety characteristic information after cleaning and the trend value within the preset time period, and finally perform weight correction according to the real-time attention, trend value and preset correction strategy.

[0077] Preferably, the weight correction unit obtains the real-time attention degree and the trend value in a preset time period of the food quality and safety feature information after cleaning, and performs weight correction according to the real-time attention degree, the trend value and the preset correction strategy.

[0078] Specifically, the real-time attention degree can be obtained by obtaining the popularity of preset keywords in the food quality and safety feature information through a search engine, that is, the real-time attention degree is proportional to the popularity of the preset keywords, or the average popularity of multiple preset keywords is expressed as the real-time attention degree. The trend value can be obtained by obtaining the average value of the change trend of the search volume of the preset keywords in the food quality and safety feature information within a preset time period through a search engine. The preset correction strategy can be understood as weight correction of the total time weight coefficient and the total number of weight coefficients according to the real-time attention degree and the trend value within the preset time period, for example, according to the size of the real-time attention degree and the trend value, the total time weight coefficient and the total number of weight coefficients are adjusted in a corresponding proportional proportion.

[0079] The deviation compensation unit is used to perform deviation compensation on the food quality and safety characteristic information after weight correction.

[0080] First, calculate the mean value of the real-time environmental parameters within the preset time period, then calculate the ratio value between the real-time environmental parameters and the preset environmental alarm parameters, calculate the weighted average value of the ratio value greater than the preset alarm threshold, and then compensate the deviation of the food quality and safety characteristic information according to the weighted average value. For example, if the initial value of the food quality and safety characteristic information is C0 and the weighted average value is C1, then the food quality and safety characteristic information after deviation compensation is C2 = C0 + C1 * A. A represents the deviation compensation coefficient, which is set by the technical staff.

[0081] In this way, by cleaning, weighting and bias compensating the food quality and safety characteristic information, and comprehensively considering the impact of different factors on the accurate value of the food quality and safety characteristic information, the accuracy of the food quality and safety characteristic information can be improved, so that intelligent monitoring of food quality and safety can be achieved more accurately based on the method.

[0082] The sequence data set construction module is used to extract the feature sequence of the food quality and safety feature information after preprocessing and construct a food quality and safety feature sequence data set; the safety factor acquisition module is used to obtain the food quality safety factor of each dimension based on the food quality and safety feature sequence data set.

[0083] The intelligent monitoring module is used to obtain the food quality risk index according to the food quality and safety coefficient of each dimension, and adjust the monitoring and management weights of different processes related to food quality and safety based on the food quality risk index to achieve intelligent management of food quality and safety.

[0084] Food quality safety factor in each dimension Among them, Δt represents the total time that the food quality and safety characteristic information exceeds the corresponding safety characteristic warning value, f represents the total number of times that the food quality and safety characteristic information exceeds the corresponding safety characteristic warning value within the preset time period, λ1 and λ2 represent the total time weight coefficient and the total number of weight coefficients, which can be set by technical personnel.

[0085] Food quality risk index for each process Where n represents the number of dimensions of food quality and safety parameters under this process, S i represents the food quality safety factor in the i-th dimension of the process, α i represents the proportional adjustment factor of the food quality safety factor in the i-th dimension of the process, and e represents a natural constant. By calculating the food quality risk index of each process The corresponding food production monitoring can be carried out for each process respectively. The food quality risk index is obtained based on the comprehensive analysis of the multi-dimensional food quality and safety parameters of the production process, which can comprehensively and accurately reflect the safety status of the food quality in the process.

[0086] Based on the food quality risk index, the monitoring and management weights of different processes related to food quality and safety are adjusted. The larger the food quality risk index, the larger the corresponding monitoring and management weight, and more monitoring resources are deployed, such as testing personnel, monitoring cameras, server memory, food quality testing equipment, etc. In this way, the monitoring and management weight in each production process is proportional to the food quality risk index, and targeted quality monitoring can be carried out on different production processes, thereby improving the intelligence level of food quality and safety monitoring.

[0087] Preferably, the intelligent food quality management system further includes a resource scheduling center, which is used to schedule monitoring resources in the intelligent management process of food quality and safety. After the intelligent monitoring module adjusts the monitoring management weights of different processes related to food quality and safety based on the food quality risk index, the resource scheduling center schedules the monitoring resources of each process according to the adjusted monitoring management weights of different processes to achieve intelligent management of food quality and safety.

[0088] To sum up, the food quality intelligent management system extracts food quality and safety characteristic information through multi-dimensional food quality and safety parameters, and then constructs a food quality and safety characteristic sequence data set to obtain the food quality and safety coefficient of each dimension. According to the food quality and safety coefficient of each dimension, the food quality risk index is obtained, and the monitoring and management weights of different processes related to food quality and safety are adjusted based on the food quality risk index. It can comprehensively consider and evaluate food quality and safety from different angles and the entire food process based on multi-dimensional parameters, realize intelligent management of food quality and safety, avoid the problem of inadequate monitoring of food quality and safety based on single-dimensional data evaluation and monitoring, and improve the accuracy of food quality and safety monitoring.

[0089] The present invention also provides a computer-readable storage medium storing a computer program, which implements the intelligent food quality management method when the computer program is executed.

[0090] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0091] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A method for intelligent management of food quality, characterized in that: The food quality intelligent management method comprises the following steps: Acquire multi-dimensional food quality and safety parameters for different processes related to food quality and safety, and extract food quality and safety characteristic information based on the multi-dimensional food quality and safety parameters; Preprocessing the food quality and safety characteristic information, and extracting characteristic sequences from the preprocessed food quality and safety characteristic information to construct a food quality and safety characteristic sequence data set; Obtaining a food quality safety coefficient for each dimension according to the food quality safety feature sequence data set; According to the food quality and safety coefficient of each dimension, a food quality risk index is obtained, and based on the food quality risk index, the monitoring and management weights of different processes related to food quality and safety are adjusted to achieve intelligent management of food quality and safety.

2. A method for intelligent management of food quality according to claim 1, characterized in that: The specific method for preprocessing the food quality and safety characteristic information comprises the following steps: The food quality and safety characteristic information is subjected to data cleaning, weight correction and deviation compensation.

3. A method for intelligent management of food quality as claimed in claim 2, characterized in that: The specific method for cleaning, weighting and compensating the food quality and safety characteristic information comprises the following steps: Cleaning the food quality and safety characteristic information; Obtaining the real-time attention degree and the trend value within a preset time period of the food quality and safety characteristic information after cleaning, and performing weight correction according to the real-time attention degree, the trend value and the preset correction strategy; Obtain error parameters that affect the food quality and safety characteristic information, and perform deviation compensation on the food quality and safety characteristic information based on the error parameters.

4. A method for intelligent management of food quality as claimed in claim 3, characterized in that: The specific method for obtaining the real-time attention degree of the food quality and safety characteristic information after cleaning and the trend value within a preset time period comprises the following steps: Obtaining the popularity of preset keywords in the food quality and safety feature information through a search engine, and obtaining the real-time attention degree according to the popularity of the preset keywords; The average value of the change trend of the search volume of preset keywords in the food quality and safety characteristic information within a preset time period is obtained through a search engine, and the trend value is obtained according to the average value of the change trend.

5. An intelligent food quality management system, used to implement the intelligent food quality management system according to any one of claims 1 to 4, characterized in that: The food quality intelligent management system comprises: A characteristic information acquisition module, used to acquire multi-dimensional food quality and safety parameters for different processes related to food quality and safety, and extract food quality and safety characteristic information based on the multi-dimensional food quality and safety parameters; A preprocessing module, used for preprocessing the food quality and safety characteristic information; A sequence data set construction module is used to extract feature sequences from the food quality and safety feature information after preprocessing to construct a food quality and safety feature sequence data set; A safety factor acquisition module, used to obtain the food quality safety factor of each dimension according to the food quality safety feature sequence data set; The intelligent monitoring module is used to obtain a food quality risk index according to the food quality safety coefficient of each dimension, and adjust the monitoring and management weights of different processes related to food quality and safety based on the food quality risk index to achieve intelligent management of food quality and safety.

6. An intelligent food quality management system as claimed in claim 5, characterized in that: The preprocessing module comprises: A data cleaning unit, used for cleaning the food quality and safety characteristic information; A weight correction unit, used to perform weight correction on the food quality and safety characteristic information after data cleaning; The deviation compensation unit is used to compensate for the deviation of the food quality and safety characteristic information after weight correction.

7. An intelligent food quality management system as claimed in claim 6, characterized in that: The weight correction unit obtains the real-time attention degree and the trend value in a preset time period of the food quality and safety feature information after cleaning, and performs weight correction according to the real-time attention degree, the trend value and the preset correction strategy.

8. An intelligent food quality management system as claimed in claim 7, characterized in that: The food quality intelligent management system also includes: The resource dispatching center is used to dispatch monitoring resources in the process of intelligent management of food quality and safety.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed, implements the intelligent food quality management method according to any one of claims 1 to 4.

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