A meat traceability management system and method

Abstract

The present invention discloses a meat traceability management system and method, which belongs to the technical field of traceability management system, including a data library, a production, transportation and marketing information binding module, an information return diagram module, an information group rearrangement module, an information traceability verification module and a traceability analysis module. The present invention can classify various types of data and generate a tree diagram, so that the data is structured and visualized, and it is convenient to quickly find meat that may have the same quality problem and process it in time. By disrupting and reordering multi-step data, generating random numbers and determining reorganized data, the traceability and reliability of the data are enhanced. This random number and finished meat binding method make each finished meat have a unique identification, improve the efficiency of tracing, and trace the source of the finished meat by calculating and verifying the judgment value. The comparison method based on distance and time interval improves the accuracy of discrimination, avoids invalid tracing, and improves the efficiency of tracing.

Description

Technical Field

[0001] The present invention relates to the technical field of traceability management systems, and in particular to a meat traceability management system and method. Background Art

[0002] The meat traceability management system is a management system that uses information technology to integrate information from all aspects of meat production and circulation to achieve product traceability and information sharing. The system aims to ensure the quality and safety of meat products and provide transparent and traceable supply chain management from production to consumption. The role of the meat traceability management system is to improve the quality and safety level of meat products and reduce the occurrence of food safety problems. At the same time, through the transparency of information, consumers' confidence and trust are enhanced. For enterprises, the system also helps to improve production efficiency, optimize resource allocation, and enhance the competitiveness of enterprises.

[0003] At present, meat traceability management generally stays at the retail settlement stage. The lack of data records of the entire process of the food supply chain makes it difficult to form a traceable data chain. In addition, the data string composition pattern bound to the meat supply chain in the existing technology is single and easy to be cracked and forged, resulting in additional traceability burden and affecting traceability efficiency. In addition, the lack of inspection of the source of meat before tracing the problematic meat makes it difficult to avoid invalid traceability, which also affects the traceability efficiency. Summary of the invention

[0004] The purpose of the present invention is to propose a meat traceability management system and method in order to solve the problems in the prior art of lack of inspection on the source of meat and the single composition order of meat data which affects the traceability efficiency.

[0005] The object of the present invention can be achieved by the following technical solutions: a meat traceability management system and method, including a data repository, a production, transportation and marketing information binding module, an information return diagram module, an information group rearrangement module, an information tracing verification module and a tracing analysis module;

[0006] The production, transportation and sales information binding module obtains the relevant data of the current finished meat production process, including feed brand, feed manufacturer, feed production batch, the relevant record data of the transportation process, including the transportation departure date, transportation vehicle, and transportation arrival date, and the relevant record data of the sales process, including the general distributor, secondary distributor, retail point and sales date, and sequentially combines various data in the production, transportation and sales processes to form multi-step data of the finished meat;

[0007] The information-returning diagram module classifies the finished meat according to the multi-step data of the finished meat, and divides the finished meat into a four-layer meat production classification tree diagram by using the feed brand number, feed production factory trademark, and feed production batch as nodes; divides the finished meat into a four-layer meat transportation classification tree diagram by using the transportation dispatch date, transportation vehicle license plate number, and transportation arrival date as nodes; divides the finished meat into a five-layer meat sales classification tree diagram by using the general distributor, secondary distributor, retail location, and sales date as nodes;

[0008] The information group rearrangement module, assuming that the feed brand, feed manufacturer, feed production batch, transportation dispatch date, transportation vehicle, transportation arrival date, general distributor, secondary distributor, retail outlet and sales date are A, B, C, D, E, F, G, H, I and J respectively, then the initial composition of the multi-step data is ABCDEFGHIJ, and each data in the initial composition of the multi-step data is shuffled and reordered to obtain a variety of reorganized data, so that each number from 1 to 3628799 corresponds to a unique permutation and combination sequence, randomly generate a number greater than or equal to 1 and less than or equal to 3628799, and rearrange A, B, C, D, E, F, G, H, I and J according to the reorganized data arrangement corresponding to the number to form the reorganized data of the finished meat, and bind the generated random number to the finished meat;

[0009] The traceability verification module obtains the recombined data and the corresponding random number of each finished meat product that needs to be verified, obtains the arrangement mode of the recombined data corresponding to the random number, splits the recombined data according to the obtained arrangement mode of the recombined data, and rearranges it according to the initial arrangement mode of the multi-step data to obtain its data values, extracts the corresponding label and sales date value of the retail point corresponding to the recombined data and records them as X1 and X2, records the person who provides the finished meat to be inspected as the provider, extracts the corresponding label and sales date value of the retail point orally stated by the provider and records them as X1′ and X2′, extracts the distance Y1 between the inspection point and the retail point corresponding to the recombined data, extracts the interval Y2 between the date the provider hands over the inspection point and the sales date corresponding to the recombined data, and substitutes X1, X2, X1′, X2′, Y1, and Y2 into the formula δ=δ1+δ2, and the verification judgment value δ is obtained, where Y1′ and Y2′ are respectively the preset distance comparison threshold and time interval comparison threshold, k is a preset factor, e is a natural constant, and k must satisfy a value much larger than Y1′ and Y2′. When the verification judgment value δ is less than 2, the corresponding finished meat is judged as non-recorded meat, and the meat source is no longer traced. When the verification judgment value δ is equal to 2, the corresponding finished meat is judged as recorded meat, and it is further traced;

[0010] The traceability analysis module obtains the feed brand, feed manufacturer, feed production batch, transportation dispatch date, transportation vehicle, transportation arrival date, general distributor, secondary distributor, retail outlet and sales date data recorded for the problematic finished meat, assigns values ​​to the nodes in the meat production classification tree diagram, the meat transportation classification tree diagram and the meat sales classification tree diagram, and calculates the total value of the nodes corresponding to the data of each finished meat. A threshold is set, and the total value is compared with the threshold to determine whether the finished meat has quality problems.

[0011] As a preferred embodiment of the present invention, the specific process of the information-reduction and diagram-analysis module classifying the multi-step data of finished meat and establishing three tree diagrams is as follows:

[0012] S1: extract the feed brand number, feed manufacturer brand number, and feed production batch of all finished meats, summarize the finished meats with the same feed brand number, and form multiple first-level sets of meat products with the same feed brand number. Further divide the finished meats in the first-level set of meat products with the same feed brand number according to the feed manufacturer brand number to form a second-level set of meat products. Further divide the finished meats in the second-level set of meat products from the same feed manufacturer according to the feed production batch to obtain a third-level set of meat products belonging to the same feed production batch. The first-level set of meat products is the first-level node, the second-level set of meat products is the second-level node, and the third-level set of meat products is the third-level node. The second-level nodes are connected and drawn in a manner that the third-level nodes are the child nodes of the first-level nodes and the third-level nodes are the child nodes of the second-level nodes to obtain a meat product classification tree diagram;

[0013] S2: Extract the transportation dispatch date, transportation vehicle license plate number, and transportation arrival date of all finished meats, summarize the finished meats with the same transportation vehicle license plate number, and form multiple first-level meat transportation sets with the same transportation vehicle license plate number. Further divide the finished meats in the first-level meat transportation set with the same transportation vehicle license plate number according to the transportation dispatch date to form a second-level meat transportation set. Further divide the finished meats in the second-level meat transportation set with the same transportation dispatch date according to the transportation arrival date to obtain a third-level meat transportation set with the same transportation arrival date. The first-level meat transportation set is the first-level node, the second-level meat transportation set is the second-level node, and the third-level meat transportation set is the third-level node. The second-level node is the child node of the first-level node, and the third-level node is the child node of the second-level node. Draw lines to obtain a meat transportation classification tree diagram;

[0014] S3: Extract the general distributors, sub-distributors, retail outlets and sales dates of all finished meats, summarize the finished meats with the same general distributor number, and form multiple first-level meat sales sets sold by the same distributor; further divide each finished meat in the first-level set sold by the same distributor according to the sub-distributor number and form a second-level meat sales set; further divide each finished meat in the second-level meat sales set with the same sub-distributor number according to the retail outlet number to obtain a third-level meat sales set with the same retail outlet number; further divide each finished meat in the second-level meat sales set with the same retail outlet number according to the sales date to obtain a fourth-level meat sales set with the same sales date; take the first-level meat sales set as the first-level node, the second-level meat sales set as the second-level node, the third-level meat sales set as the third-level node, and the fourth-level meat sales set as the fourth-level node, and draw lines in the manner of second-level nodes as child nodes of first-level nodes, third-level nodes as child nodes of second-level nodes, and fourth-level nodes as child nodes of third-level nodes to obtain a meat sales classification tree diagram.

[0015] As a preferred embodiment of the present invention, the specific steps of the traceability analysis module to perform value analysis on each finished meat product to determine its quality problems are as follows:

[0016] In the meat production classification tree diagram, meat transportation classification tree diagram and meat sales classification tree diagram, the nodes corresponding to the feed brand, feed manufacturer, feed production batch, transportation dispatch date, transportation vehicle, transportation arrival date, general distributor, secondary distributor, retail outlet and sales date data of the finished meat in question are screened out, and each node is assigned a value according to the node level, where the first-level nodes corresponding to the same data as the finished meat in question are assigned a value of 1, the second-level nodes are assigned a value of 2, the third-level nodes are assigned a value of 3, the fourth-level nodes are assigned a value of 4, and all other nodes different from the finished meat in question are assigned a value of 0. All finished meats are categorized according to the feed brand, feed manufacturer, feed production batch, transportation dispatch date, transportation vehicle, transportation arrival date, general distributor, secondary distributor, retail outlet and sales date data recorded. The data of batch, transport dispatch date, transport vehicle, transport arrival date, general distributor, secondary distributor, retail outlet and sales date are substituted into the nodes in each tree diagram for matching, and the sum of the corresponding node values ​​of each data is calculated and recorded as the evaluation value. A recall threshold is set, and the corresponding evaluation values ​​of all finished meats are compared with the recall threshold. When the corresponding evaluation value is greater than the recall threshold, the finished meat is urgently recalled and destroyed; when the corresponding evaluation value is less than or equal to the recall threshold, it is sampled and tested, and when the sampling test result is normal meat, the traceability is stopped. When the sampling test result is abnormal meat, all meat with an evaluation value greater than 0 is urgently recalled and destroyed.

[0017] A meat traceability management method, the specific operating steps of which are as follows:

[0018] Step 1: The information entry module records the brand, manufacturer, and batch of feed fed to the young animals, the date of shipment, transportation vehicle, and arrival date of the meat during transportation, and the general distributor, sub-distributor, retail outlet, and sales date of the finished meat during sales. The feed brand, manufacturer, general distributor, sub-distributor, and retail outlet are numbered respectively, and various data from the production, transportation, and sales processes are sequentially combined to form multi-step data of the finished meat.

[0019] Step 2: When each meat production base starts to purchase or cultivate the animal cubs corresponding to the meat it produces, the signal group rearrangement module generates a random number greater than or equal to 1 and less than or equal to 3628799, and binds the random number to the corresponding meat. At the same time, the random number and the corresponding meat are recorded in the system, and the reorganized data corresponding to the random number are obtained. The data arrangement sequence corresponding to the reorganized data is used as the data frame, and the data values ​​in the multi-step data of the finished meat are rearranged according to the data frame. After filling in the last sales date, the complete reorganized data is affixed to the outer packaging of the finished meat in the form of a digital inkjet label, and recorded in the system data library and bound to the random number at the same time;

[0020] Step 3: The information traceability verification module obtains the reorganized data of each finished meat to be verified and the corresponding random number, finds the corresponding reorganized data arrangement in the information group rearrangement module according to the random number, extracts the reorganized data according to the corresponding arrangement order, extracts the value of each data, and records the corresponding retail point number and sales date value as X1 and X2, the retail point number and sales date value verbally stated by the provider as X1′ and X2′, and substitutes the distance Y1 between the inspection point and the retail point in the reorganized data, and the interval Y2 between the inspection point date and the sales date in the reorganized data into the preset formula δ=δ1+δ2, and the verification judgment value δ is calculated. When the verification judgment value δ is less than 2, the corresponding finished meat is judged as non-recorded meat, and the meat source traceability is no longer performed. When the verification judgment value δ is equal to 2, the corresponding finished meat is judged as recorded meat, and step 4 is performed;

[0021] Step 4: The traceability analysis module marks the meat recorded in step 3 as problematic meat, and obtains the feed brand, feed manufacturer, feed production batch, transport dispatch date, transport vehicle, transport arrival date, general distributor, secondary distributor, retail outlet and sales date data of the problematic meat record, assigns values ​​to the nodes in the meat production classification tree diagram, the meat transportation classification tree diagram and the meat sales classification tree diagram according to the problematic meat data, and assigns values ​​to the data corresponding to each finished meat according to the value of each node and sums them up to obtain the evaluation value of each finished meat, compares the corresponding evaluation values ​​of all finished meats with the recall threshold, and recalls and destroys the finished meat with an evaluation value greater than the recall threshold; when the finished meat with the corresponding evaluation value less than or equal to the recall threshold is sampled and tested, if the sampling test result is normal meat, the tracing is stopped, and when the sampling test result is abnormal meat, all finished meat with an evaluation value greater than 0 is urgently recalled and destroyed.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] 1. The present invention ensures the relative integrity of the meat-related data chain by collecting relevant data in various links such as production, transportation and sales, which is convenient for better tracing and tracing meat with the same problem when quality problems occur in meat. The information return diagram module classifies various types of data and generates a tree diagram to structure and visualize the data, and facilitates and quickly finds meat that may have the same quality problems and processes them in time. The information group rearrangement module enhances the traceability and reliability of the data by disrupting and reordering multi-step data, generating random numbers and determining reorganized data. This binding method of random numbers and finished meat ensures that each finished meat has a unique identification, which improves the efficiency of tracing. The information tracing verification module traces the source of the finished meat by calculating and verifying the judgment value. The comparison method based on distance and time interval improves the accuracy of judgment, avoids invalid tracing, and improves the efficiency of tracing.

[0024] 2. The present invention can record a variety of important data related to meat production, transportation and sales, and divide them by drawing a tree diagram according to the data type, so as to distinguish and summarize meats with different data. When meat has quality problems, the relevant data are first obtained through the reorganized data and the corresponding random numbers, and then the extracted data are substituted into the formula for calculation. The calculated value is used to determine whether the problematic meat matches the recorded meat. If they match, other meats are evaluated and assigned values, and the decision on whether to recall or stop tracing is made based on the evaluation values. This effectively solves the problem in the prior art that meat with problems is difficult to trace and meat that may also have quality problems cannot be recalled, thereby improving the quality assurance of meat operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0026] Figure 1 It is a principle block diagram of the present invention;

[0027] Figure 2 It is a module relationship block diagram of the present invention;

[0028] Figure 3 It is a schematic diagram of the meat sales classification tree diagram of the present invention. DETAILED DESCRIPTION

[0029] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] See also Figure 1 , Figure 2 As shown, a meat traceability management system includes a data library, a production, transportation and sales information binding module, an information classification diagram module, an information group rearrangement module, an information tracing verification module and a tracing analysis module.

[0031] It should be noted that the meat referred to in the present invention is various kinds of meat supplied as the main edible meat in general life, including but not limited to pork, beef, mutton and various poultry, such as chicken, duck and goose, which are purchased by consumers to supplement their protein intake. In the following description, pork will be used as the target finished meat in the meat traceability management system to describe in detail the specific implementation mode of the present invention.

[0032] The production, transportation and sales information binding module obtains various relevant record data in the current production process, transportation process and sales process of the finished meat, and processes and analyzes them to form a sales data group, among which the relevant data in the production process include feed brand, feed manufacturer and feed production batch; the relevant record data in the transportation process include transportation departure date, transportation vehicle and transportation arrival date; the relevant record data in the sales process include general distributor, secondary distributor, retail outlet and sales date. The feed brand, feed manufacturer, general distributor, secondary distributor and retail outlet are numbered respectively, and the various data in the production, transportation and sales processes are sequentially combined to form the multi-step data of the finished meat. The information return and graphic interpretation module classifies the multi-step data of the finished meat, thereby dividing each finished meat and distinguishing the finished meat by multiple categories.

[0033] It should be noted that finished meat refers to pork that has been raised at the place of origin and reached the final retail point after being slaughtered, cut into pieces, and transported to meet the requirements for pigs to be marketed. Usually, the multi-step data corresponding to the finished meat produced by a pig are the same. The production process of finished meat is mainly the breeding process. When feeding pigs during the breeding process, the feed brand, feed manufacturer, and feed production batch on the feed packaging bag are recorded. The transportation process of finished meat is mainly to transport the finished meat from the place of origin after slaughter and cutting into pieces to the frozen warehouse of the general distributors in each province, and then each general distributor distributes it to the secondary distributors. The transportation process is mostly long-distance cold chain transportation and is transported by the same special vehicle to avoid frequent handling of finished meat during transportation, resulting in changes in temperature and environment, which may cause the quality of the finished meat to deteriorate or mutate. When the finished meat is transported, the time of shipment and the vehicle license plate number are recorded, and when the transportation arrives, the arrival time and vehicle license plate number are recorded. The sales process is mainly that the general distributor refrigerates the finished meat transported by the cold chain after receiving it, and distributes it to each secondary distributor, and the secondary distributor distributes it to the retail outlets, and the retail outlets sell it to consumers and record the sales date.

[0034] The Xingui Graphical Interpretation Module obtains the multi-step data of each finished meat and divides each finished meat into three categories. The specific division steps are as follows:

[0035] S1: Extract all finished meat feed brand A n , Feed production factory trademark number B n , Feed production batch C n , the finished meat of the same feed brand number is summarized to form multiple first-level sets of meat products with the same feed brand number, and each finished meat in the first-level set of meat products with the same feed brand number is further divided according to the feed production factory brand number to form a second-level set of meat products, and each finished meat in the second-level set of meat products belonging to the same feed manufacturer is further divided according to the feed production batch to obtain a third-level set of meat products belonging to the same feed production batch, with the first-level set of meat products as the first-level node, the second-level set of meat products as the second-level node, and the third-level set of meat products as the third-level node, and the second-level node is the child node of the first-level node, and the third-level node is the child node of the second-level node. Lines are drawn to obtain a meat product classification tree diagram;

[0036] S2: Extract the shipping date D for all finished meat n , Transport vehicle license plate number E n , Transportation arrival date F n, the finished meats with the same license plate number of the transport vehicle are summarized to form a first-level meat transport set with the same transport vehicle license plate number, and each finished meat in the first-level meat transport set with the same transport vehicle license plate number is further divided according to the transport dispatch date to form a second-level meat transport set, and each finished meat in the second-level meat transport set with the same transport dispatch date is further divided according to the transport arrival date to obtain a third-level meat transport set with the same transport arrival date, and the first-level meat transport set is used as the first-level node, the second-level meat transport set is used as the second-level node, and the third-level meat transport set is used as the third-level node, and the second-level node is the child node of the first-level node, and the third-level node is the child node of the second-level node, and the meat transportation classification tree diagram is obtained by connecting lines;

[0037] S3: General distributor G that extracts all finished meat n 、Sub-distributor H n 、Retail Location I n and sales date n , the finished meat with the same general distributor number is summarized to form multiple first-level meat sales sets sold by the same distributor; the finished meat in the first-level set sold by the same distributor is further divided according to the secondary distributor number to form a second-level meat sales set; the finished meat in the second-level meat sales set with the same secondary distributor number is further divided according to the retail point number to obtain a third-level meat sales set with the same retail point number; the finished meat in the second-level meat sales set with the same retail point number is further divided according to the sales date to obtain a fourth-level meat sales set with the same sales date; the first-level meat sales set is the first-level node, the second-level meat sales set is the second-level node, the third-level meat sales set is the third-level node, and the fourth-level meat sales set is the fourth-level node, and the second-level node is the child node of the first-level node, the third-level node is the child node of the second-level node, and the fourth-level node is the child node of the third-level node. Draw lines to obtain a meat sales classification tree diagram.

[0038] It should be noted that the reference diagram of the meat production classification tree diagram is as follows Figure 3 As shown, the meat transport classification tree diagram is Figure 3 The difference is that each node corresponds to a different type of data. Figure 3 The difference is that each node corresponds to a different type of data and has one more layer of sub-nodes, so the meat sales classification tree diagram is Figure 3 The tree diagram shown is one level deeper. n , B n , C n , D n 、E n 、F n , G n , H n ,I n and J nIt only indicates the serial number of the corresponding data and has no necessary connection with its label or the data itself. It is only used to distinguish between data of the same type. In the actual process of recording multi-step data, feed brands, feed manufacturers, general distributors, and secondary distributors are numbered separately. The labels can be pure numbers, pure letters, or letters plus symbols, while the retail point labels must be pure numbers.

[0039] The information group rearrangement module obtains multi-step data. Suppose the feed brand, feed manufacturer, feed production batch, transportation dispatch date, transportation vehicle, transportation arrival date, general distributor, secondary distributor, retail location and sales date are A, B, C, D, E, F, G, H, I and J respectively. The initial composition of the multi-step data is ABCDEFGHIJ. By shuffling and reordering the data in the initial composition of the multi-step data, a variety of reorganized data can be obtained. The total number of reorganized data types is There are 3628799 sorting methods of the reorganized data, and each number from 1 to 3628799 corresponds to a permutation and combination sequence. The arrangement order of each data in the reorganized data corresponding to each permutation and combination sequence is different. That is to say, each number from 1 to 3628799, including 1 and 3628799, corresponds to an arrangement method of the reorganized data. A number greater than or equal to 1 and less than or equal to 3628799 is randomly generated, and each data is rearranged to form the reorganized data of the finished meat according to the reorganized data arrangement method corresponding to the number, and the generated random number is bound to the finished meat.

[0040] It should be noted that the multi-step data is arranged and combined in a specific order to correspond to each finished meat product. The value of each data is clear and understandable, which is convenient for subsequent extraction of various data for analysis and processing and traceability management. However, the order setting also means that it is easier to be cracked and forged. A variety of reorganized data can replace the multi-step data and bind it to the finished meat, thereby protecting the various production, transportation and sales data of the finished meat from being easily cracked and forged. Although the signal group rearrangement module randomly reorganizes the multi-step data so that the reorganized data composition is not easy to crack, there is still the possibility of counterfeiting using the generated reorganized data. Therefore, it is necessary to verify the finished meat before tracing it to ensure that the finished meat that needs to be traced is the finished meat recorded by the system, thereby saving time, reducing the workload of traceability management, and improving the overall operation efficiency of the system.

[0041] In addition, the data character lengths corresponding to feed brands, feed manufacturers, feed production batches, transport dispatch dates, transport vehicles, transport arrival dates, general distributors, secondary distributors, retail outlets and sales dates should remain consistent, so that even after reorganization, they can be extracted according to the arrangement order. The specific extraction method is: let the unified character length of each data be i, and the total length of the reorganized data be j, then j=10i, and the reorganized data is divided into i as a unit length to obtain 10 data with a unit length of i arranged in sequence, then the data values ​​corresponding to the reorganized data are these 10 data values, and according to the arrangement method of each group of data in the reorganized data, the 10 data values ​​are extracted in order to obtain the values ​​corresponding to each data.

[0042] The traceability verification module obtains the recombined data and corresponding random numbers of each finished meat product that needs to be verified, obtains the arrangement of the recombined data corresponding to the random number, splits the recombined data according to the obtained arrangement of the recombined data, and rearranges it according to the initial arrangement of the multi-step data, obtains the recorded feed brand, feed manufacturer, feed production batch, transportation date, transportation vehicle, transportation arrival date, general distributor, secondary distributor, retail point and sales date, the sales date is composed of pure digits of year, month and day, extracts the corresponding number and sales date value of the retail point corresponding to the recombined data and records them as X1 and X2, records the person who provides the finished meat to be inspected as the provider, extracts the corresponding number and sales date value of the retail point orally stated by the provider and records them as X1′ and X2′, extracts the distance Y1 between the inspection point and the retail point corresponding to the recombined data, extracts the interval Y2 between the date the provider hands it over to the inspection point and the sales date corresponding to the recombined data, and substitutes X1, X2, X1′, X2′, Y1, and Y2 into the formula δ=δ1+δ2 to obtain the verification judgment value δ, wherein Y1′ and Y2′ are respectively the preset distance comparison threshold and time interval comparison threshold, k is a preset factor, e is a natural constant, and k must satisfy a value much larger than Y1′ and Y2′. When the verification judgment value δ is less than 2, the corresponding finished meat is judged as non-recorded meat, and the meat source is no longer traced. When the verification judgment value δ is equal to 2, the corresponding finished meat is judged as recorded meat, and further traced.

[0043] The traceability analysis module obtains the feed brand, feed manufacturer, feed production batch, transportation dispatch date, transportation vehicle, transportation arrival date, general distributor, secondary distributor, retail outlet and sales date data recorded for the problematic finished meat, and finds the nodes corresponding to the feed brand, feed manufacturer, feed production batch, transportation dispatch date, transportation vehicle, transportation arrival date, general distributor, secondary distributor, retail outlet and sales date data of the problematic finished meat in the meat production classification tree diagram, meat transportation classification tree diagram and meat sales classification tree diagram, and assigns a value to each node according to the node level, where the first-level nodes corresponding to the problematic finished meat data are assigned a value of 1, the second-level nodes are assigned a value of 2, the third-level nodes are assigned a value of 3, the fourth-level nodes are assigned a value of 4, and all other nodes that are not related to the problematic finished meat data are assigned a value of 5. The same node is assigned a value of 0, and the feed brand, feed manufacturer, feed production batch, transportation dispatch date, transportation vehicle, transportation arrival date, general distributor, secondary distributor, retail outlet and sales date data recorded in all finished meat are compared with the nodes in each tree diagram one by one, and the sum of the node values ​​corresponding to each data is calculated and recorded as the evaluation value. A recall threshold is set, and the corresponding evaluation values ​​of all finished meats are compared with the recall threshold. When the corresponding evaluation value is greater than the recall threshold, the finished meat is urgently recalled and destroyed; when the corresponding evaluation value is less than or equal to the recall threshold, it is sampled and tested, and when the sampling test result is normal meat, the tracing is stopped, and when the sampling test result is abnormal meat, all meat with an evaluation value greater than 0 is urgently recalled and destroyed.

[0044] A meat traceability management method, the specific operating steps of which are as follows:

[0045] Step 1: The information entry module records the brand, manufacturer and batch of feed fed to young animals; the date of shipment, vehicle and arrival of meat during transportation; the general distributor, sub-distributor, retail outlet and sales date of finished meat during sales; and labels the brand, manufacturer, general distributor, sub-distributor and retail outlet respectively. It combines various data in the production, transportation and sales processes in sequence to form multi-step data of the finished meat.

[0046] Step 2: When each meat production base starts to purchase or cultivate the animal cubs corresponding to the meat it produces, the signal group rearrangement module generates a random number greater than or equal to 1 and less than or equal to 3628799, and binds the random number to the corresponding meat. At the same time, the random number and the corresponding meat are recorded in the system, and the reorganized data corresponding to the random number are obtained. The data arrangement sequence corresponding to the reorganized data is used as the data frame, and the data values ​​in the multi-step data of the finished meat are rearranged according to the data frame. After filling in the last sales date, the complete reorganized data is affixed to the outer packaging of the finished meat in the form of a digital inkjet label, and recorded in the system data library and bound to the random number. In other words, each finished meat corresponds to a reorganized data and a random number.

[0047] In a specific embodiment, the generated random number is 78, and the arrangement of each data in the corresponding reorganized data is specifically FAJBCEGDHI. In the process of recording data to form the reorganized data, the recorded feed brand, feed manufacturer, feed production batch, transportation dispatch date, transportation vehicle, transportation arrival date, general distributor, secondary distributor, retail outlet and sales date are arranged in the following order: transportation arrival date, feed brand, sales date, feed manufacturer, feed production batch, transportation vehicle, general distributor, transportation dispatch date, secondary distributor, retail outlet, to form the reorganized data corresponding to various finished meats produced by the batch of animal seedlings. The reorganized data is affixed to the outer packaging of the finished meat in the form of a digital inkjet label, and is recorded in the system data library and bound to the random number. When the corresponding reorganized data of the finished meat is input, the random number corresponding to the reorganized data can be obtained, and then the arrangement order of each data in the reorganized data is obtained, and each data is extracted and arranged according to the multi-step data initial arrangement method, so that each data can be analyzed separately.

[0048] Step 3: The information traceability verification module obtains the reorganized data of each finished meat to be verified and the corresponding random number, finds the corresponding reorganized data arrangement in the information group rearrangement module according to the random number, extracts the reorganized data according to the corresponding arrangement order, extracts the value of each data, and records the corresponding retail point number and sales date value as X1 and X2, the retail point number and sales date value verbally stated by the provider as X1′ and X2′, and substitutes the distance Y1 between the inspection point and the retail point in the reorganized data, and the interval Y2 between the inspection point date and the sales date in the reorganized data into the preset formula Calculation is performed in δ=δ1+δ2 to obtain the verification judgment value δ. When the verification judgment value δ is less than 2, the corresponding finished meat is judged as non-recorded meat, and meat source traceability is no longer performed. When the verification judgment value δ is equal to 2, the corresponding finished meat is judged as recorded meat, and step four is performed.

[0049] Step 4: The traceability analysis module marks the meat recorded in step 3 as problematic meat, and obtains the feed brand, feed manufacturer, feed production batch, transport dispatch date, transport vehicle, transport arrival date, general distributor, secondary distributor, retail outlet and sales date data of the problematic meat record, assigns values ​​to the nodes in the meat production classification tree diagram, the meat transportation classification tree diagram and the meat sales classification tree diagram according to the problematic meat data, and assigns values ​​to the data corresponding to each finished meat according to the value of each node and sums them up to obtain the evaluation value of each finished meat, compares the corresponding evaluation values ​​of all finished meats with the recall threshold, and recalls and destroys the finished meat with an evaluation value greater than the recall threshold; when the finished meat with the corresponding evaluation value less than or equal to the recall threshold is sampled and tested, if the sampling test result is normal meat, the tracing is stopped, and when the sampling test result is abnormal meat, all finished meat with an evaluation value greater than 0 is urgently recalled and destroyed.

[0050] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A meat traceability management system, comprising a database, characterized in that: It also includes a production, transportation and marketing information binding module, an information grouping and diagramming module, an information grouping and rearrangement module, an information tracing and verification module and a tracing and analysis module; The production, transportation and sales information binding module obtains the relevant data of the current finished meat production process, including feed brand, feed manufacturer, feed production batch, the relevant record data of the transportation process, including the transportation departure date, transportation vehicle, and transportation arrival date, and the relevant record data of the sales process, including the general distributor, secondary distributor, retail point and sales date, and sequentially combines various data in the production, transportation and sales processes to form multi-step data of the finished meat; The information-returning diagram module classifies the finished meat according to the multi-step data of the finished meat, and divides the finished meat into a four-layer meat production classification tree diagram by using the feed brand number, feed production factory trademark, and feed production batch as nodes; divides the finished meat into a four-layer meat transportation classification tree diagram by using the transportation dispatch date, transportation vehicle license plate number, and transportation arrival date as nodes; divides the finished meat into a five-layer meat sales classification tree diagram by using the general distributor, secondary distributor, retail location, and sales date as nodes; The information group rearrangement module, assuming that the feed brand, feed manufacturer, feed production batch, transportation dispatch date, transportation vehicle, transportation arrival date, general distributor, secondary distributor, retail outlet and sales date are A, B, C, D, E, F, G, H, I and J respectively, then the initial composition of the multi-step data is ABCDEFGHIJ, and each data in the initial composition of the multi-step data is shuffled and reordered to obtain a variety of reorganized data, so that each number from 1 to 3628799 corresponds to a unique permutation and combination sequence, randomly generate a number greater than or equal to 1 and less than or equal to 3628799, and rearrange A, B, C, D, E, F, G, H, I and J according to the reorganized data arrangement corresponding to the number to form the reorganized data of the finished meat, and bind the generated random number to the finished meat; The traceability verification module obtains the recombined data and corresponding random numbers of each finished meat product that needs to be verified, obtains the arrangement of the recombined data corresponding to the random number, splits the recombined data according to the obtained arrangement of the recombined data, and rearranges it according to the initial arrangement of the multi-step data to obtain its data values, extracts the corresponding label and sales date value of the retail point corresponding to the recombined data and records them as X1 and X2, records the person who provides the finished meat to be inspected as the provider, extracts the corresponding label and sales date value of the retail point orally stated by the provider and records them as X1′ and X2′, extracts the distance Y1 between the inspection point and the retail point corresponding to the recombined data, extracts the interval Y2 between the date the provider hands it over to the inspection point and the sales date corresponding to the recombined data, and substitutes X1, X2, X1′, X2′, Y1, and Y2 into the formula δ=δ1+δ2, and the verification judgment value δ is obtained, where Y1′ and Y2′ are respectively the preset distance comparison threshold and time interval comparison threshold, k is a preset factor, e is a natural constant, and k must satisfy a value much larger than Y1′ and Y2′. When the verification judgment value δ is less than 2, the corresponding finished meat is judged as non-recorded meat, and the meat source is no longer traced. When the verification judgment value δ is equal to 2, the corresponding finished meat is judged as recorded meat, and it is further traced; The traceability analysis module obtains the feed brand, feed manufacturer, feed production batch, transportation dispatch date, transportation vehicle, transportation arrival date, general distributor, secondary distributor, retail outlet and sales date data recorded for the problematic finished meat, assigns values ​​to the nodes in the meat production classification tree diagram, the meat transportation classification tree diagram and the meat sales classification tree diagram, and calculates the total value of the nodes corresponding to the data of each finished meat. A threshold is set, and the total value of the assigned values ​​is compared with the threshold to determine whether the source of each finished meat overlaps with the problematic finished meat.

2. A meat traceability management system according to claim 1, characterized in that: The specific process of the information-reduction and diagram-analysis module classifying the multi-step data of finished meat and establishing three tree diagrams is as follows: S1: extract the feed brand number, feed manufacturer brand number, and feed production batch of all finished meats, summarize the finished meats with the same feed brand number, and form multiple first-level sets of meat products with the same feed brand number. Further divide the finished meats in the first-level set of meat products with the same feed brand number according to the feed manufacturer brand number to form a second-level set of meat products. Further divide the finished meats in the second-level set of meat products from the same feed manufacturer according to the feed production batch to obtain a third-level set of meat products belonging to the same feed production batch. The first-level set of meat products is the first-level node, the second-level set of meat products is the second-level node, and the third-level set of meat products is the third-level node. The second-level nodes are connected and drawn in a manner that the third-level nodes are the child nodes of the first-level nodes and the third-level nodes are the child nodes of the second-level nodes to obtain a meat product classification tree diagram; S2: Extract the transportation dispatch date, transportation vehicle license plate number, and transportation arrival date of all finished meats, summarize the finished meats with the same transportation vehicle license plate number, and form multiple first-level meat transportation sets with the same transportation vehicle license plate number. Further divide the finished meats in the first-level meat transportation set with the same transportation vehicle license plate number according to the transportation dispatch date to form a second-level meat transportation set. Further divide the finished meats in the second-level meat transportation set with the same transportation dispatch date according to the transportation arrival date to obtain a third-level meat transportation set with the same transportation arrival date. The first-level meat transportation set is the first-level node, the second-level meat transportation set is the second-level node, and the third-level meat transportation set is the third-level node. The second-level node is the child node of the first-level node, and the third-level node is the child node of the second-level node. Draw lines to obtain a meat transportation classification tree diagram; S3: Extract the general distributors, sub-distributors, retail outlets and sales dates of all finished meats, summarize the finished meats with the same general distributor number, and form multiple first-level meat sales sets sold by the same distributor; further divide each finished meat in the first-level set sold by the same distributor according to the sub-distributor number and form a second-level meat sales set; further divide each finished meat in the second-level meat sales set with the same sub-distributor number according to the retail outlet number to obtain a third-level meat sales set with the same retail outlet number; further divide each finished meat in the second-level meat sales set with the same retail outlet number according to the sales date to obtain a fourth-level meat sales set with the same sales date; take the first-level meat sales set as the first-level node, the second-level meat sales set as the second-level node, the third-level meat sales set as the third-level node, and the fourth-level meat sales set as the fourth-level node, and draw lines in the manner of second-level nodes as child nodes of first-level nodes, third-level nodes as child nodes of second-level nodes, and fourth-level nodes as child nodes of third-level nodes to obtain a meat sales classification tree diagram.

3. A meat traceability management system according to claim 1, characterized in that: The specific steps of the traceability analysis module to perform value analysis on each finished meat product to determine its quality problems are as follows: In the meat production classification tree diagram, meat transportation classification tree diagram and meat sales classification tree diagram, the nodes corresponding to the feed brand, feed manufacturer, feed production batch, transportation dispatch date, transportation vehicle, transportation arrival date, general distributor, secondary distributor, retail outlet and sales date data of the finished meat in question are screened out, and each node is assigned a value according to the node level, where the first-level nodes corresponding to the same data as the finished meat in question are assigned a value of 1, the second-level nodes are assigned a value of 2, the third-level nodes are assigned a value of 3, the fourth-level nodes are assigned a value of 4, and all other nodes different from the finished meat in question are assigned a value of 0. All finished meats are categorized according to the feed brand, feed manufacturer, feed production batch, transportation dispatch date, transportation vehicle, transportation arrival date, general distributor, secondary distributor, retail outlet and sales date data recorded. The data of batch, transport dispatch date, transport vehicle, transport arrival date, general distributor, secondary distributor, retail outlet and sales date are substituted into the nodes in each tree diagram for matching, and the sum of the corresponding node values ​​of each data is calculated and recorded as the evaluation value. A recall threshold is set, and the corresponding evaluation values ​​of all finished meats are compared with the recall threshold. When the corresponding evaluation value is greater than the recall threshold, the finished meat is urgently recalled and destroyed; when the corresponding evaluation value is less than or equal to the recall threshold, it is sampled and tested, and when the sampling test result is normal meat, the traceability is stopped. When the sampling test result is abnormal meat, all meat with an evaluation value greater than 0 is urgently recalled and destroyed.

4. A meat traceability management method, characterized in that: The specific operation steps are as follows: Step 1: The information entry module records the brand, manufacturer, and batch of feed fed to the young animals, the date of shipment, transportation vehicle, and arrival date of the meat during transportation, and the general distributor, sub-distributor, retail outlet, and sales date of the finished meat during sales. The feed brand, manufacturer, general distributor, sub-distributor, and retail outlet are numbered respectively, and various data from the production, transportation, and sales processes are sequentially combined to form multi-step data of the finished meat. Step 2: When each meat production base starts to purchase or cultivate the animal cubs corresponding to the meat it produces, the signal group rearrangement module generates a random number greater than or equal to 1 and less than or equal to 3628799, and binds the random number to the corresponding meat. At the same time, the random number and the corresponding meat are recorded in the system, and the reorganized data corresponding to the random number are obtained. The data arrangement sequence corresponding to the reorganized data is used as the data frame, and the data values ​​in the multi-step data of the finished meat are rearranged according to the data frame. After filling in the last sales date, the complete reorganized data is affixed to the outer packaging of the finished meat in the form of a digital inkjet label, and recorded in the system data library and bound to the random number at the same time; Step 3: The information traceability verification module obtains the reorganized data of each finished meat to be verified and the corresponding random number, finds the corresponding reorganized data arrangement in the information group rearrangement module according to the random number, extracts the reorganized data according to the corresponding arrangement order, extracts the value of each data, and records the corresponding retail point number and sales date value as X1 and X2, the retail point number and sales date value verbally stated by the provider as X1′ and X2′, and substitutes the distance Y1 between the inspection point and the retail point in the reorganized data, and the interval Y2 between the inspection point date and the sales date in the reorganized data into the preset formula δ=δ1+δ2, and the verification judgment value δ is calculated. When the verification judgment value δ is less than 2, the corresponding finished meat is judged as non-recorded meat, and the meat source traceability is no longer performed. When the verification judgment value δ is equal to 2, the corresponding finished meat is judged as recorded meat, and step 4 is performed; Step 4: The traceability analysis module marks the meat recorded in step 3 as problematic meat, and obtains the feed brand, feed manufacturer, feed production batch, transport dispatch date, transport vehicle, transport arrival date, general distributor, secondary distributor, retail outlet and sales date data of the problematic meat record, assigns values ​​to the nodes in the meat production classification tree diagram, the meat transportation classification tree diagram and the meat sales classification tree diagram according to the problematic meat data, and assigns values ​​to the data corresponding to each finished meat according to the value of each node and sums them up to obtain the evaluation value of each finished meat, compares the corresponding evaluation values ​​of all finished meats with the recall threshold, and recalls and destroys the finished meat with an evaluation value greater than the recall threshold; when the finished meat with the corresponding evaluation value less than or equal to the recall threshold is sampled and tested, if the sampling test result is normal meat, the tracing is stopped, and when the sampling test result is abnormal meat, all finished meat with an evaluation value greater than 0 is urgently recalled and destroyed.

Images