Industrial chain tracing method, device and system for large-scale cattle breeding

Abstract

The invention relates to the technical field of data processing, and provides an industrial chain tracing method, device and system for large-scale cattle breeding, and the method comprises the steps: screening all bred cattle in all breeding stages based on individual health index values, and obtaining all unhealthy bred cattle and healthy bred cattle; obtaining a health data prediction value of each dimension of each unhealthy bred cattle in different breeding stages; obtaining a health data prediction deviation degree of each unhealthy bred cattle by analyzing a difference condition between the health data of each dimension of each unhealthy bred cattle in different breeding stages and a health data prediction value; according to the health data, predicting the deviation degree and the individual health index values of each unhealthy bred cattle in different breeding stages, and obtaining the industry traceability necessity of each unhealthy bred cattle; and carrying out block chain hierarchical storage on the health data of all bred cattle based on industrial traceability necessity. According to the invention, the industrial chain tracing efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to an industrial chain tracing method, device and system for large-scale cattle breeding. Background Art

[0002] The traceability of the industrial chain in large-scale cattle farming involves the entire process from breeding, feeding, processing to sales. It adopts advanced technologies such as the Internet of Things, blockchain, and big data to ensure the safety, transparency, and quality of products, enhance market trust, and help optimize production management. Blockchain technology is a decentralized, distributed database technology with core features such as immutability, decentralization, and transparency. Therefore, in order to achieve accurate traceability, blockchain technology is usually used to index the database. In order to achieve the purpose of large-scale industrial chain traceability of cattle, each farmed cattle is monitored and its health data is collected at different breeding stages. The health data is transmitted via radio waves and recorded in the data blockchain. In the process of blockchain traceability, due to problems with the breeding environment, the health data of farmed cattle tends to be abnormal, which in turn leads to abnormalities in the necessity of industrial chain traceability, and ultimately reduces the efficiency of industrial chain traceability. Summary of the invention

[0003] The present invention provides an industrial chain traceability method, device and system for large-scale cattle breeding, so as to solve the problem that the health data of cattle breeding tends to be abnormal due to the breeding environment, which in turn leads to the necessity of industrial chain traceability being abnormal, and finally reduces the traceability efficiency of the industrial chain. The technical solutions adopted are as follows: The present invention proposes an industrial chain tracing method for large-scale cattle breeding, which includes the following steps: Obtaining health data of all cattle in the farm; the health data of cattle includes health data of several dimensions of cattle at different breeding stages; According to the outliers of health data of different dimensions of each breeding cattle at each breeding stage, the individual health index value of each breeding cattle at each breeding stage is obtained; All farmed cattle in all breeding stages are screened based on individual health index values ​​to obtain all unhealthy farmed cattle and healthy farmed cattle; the predicted health data value of each unhealthy farmed cattle in each dimension at different breeding stages is obtained; the predicted health data deviation of each unhealthy farmed cattle is obtained by analyzing the difference between the health data and the predicted health data value of each dimension at different breeding stages; the necessity of industrial traceability of each unhealthy farmed cattle is obtained based on the predicted health data deviation and the individual health index value of each unhealthy farmed cattle at different breeding stages; Based on the necessity of industry traceability, the health data of all farmed cattle are stored in a layered manner on blockchain.

[0004] Preferably, the specific method of obtaining the individual health index value of each breeding cattle at each breeding stage according to the outliers of the health data of different dimensions of each breeding cattle at each breeding stage includes: All the cattle in the farm will be The first stage of breeding The sequence of health data of the dimensions is recorded as the number of The next breeding stage health data series of dimensions; The next breeding stage The health data sequence of the dimensions is input into the LOF outlier detection algorithm to obtain the outlier value of each breeding cow in the first The next breeding stage Outliers in health data of various dimensions; Get the Only cattle are raised in Outlier differences in health data at each breeding stage; The first Only cattle are raised in The reciprocal of the mean of the outliers of the health data of all dimensions in the breeding stage is Only cattle are raised in The normalized value of the product of the outlier differences in health data under the breeding stage is taken as the Only cattle are raised in Individual health index values ​​at each breeding stage.

[0005] Preferably, the obtaining Only cattle are raised in The outlier differences in health data at each breeding stage include: The first Only cattle are raised in The next breeding stage Outliers in health data of dimensions Only cattle are raised in The next breeding stage The absolute value of the difference between the outliers of the health data in the dimension is recorded as Only cattle are raised in The next breeding stage The outlier difference of health data in the dimension Only cattle are raised in The sum of the outlier differences of health data in all dimensions under the breeding stage is recorded as Only cattle are raised in The outlier differences in health data at different breeding stages.

[0006] Preferably, the method of screening all the farmed cattle in all breeding stages based on the individual health index values ​​to obtain all the unhealthy farmed cattle and healthy farmed cattle includes the following specific methods: Preset a health threshold parameter , for the Only raising cattle, if Only the individual health index value of cattle in any breeding stage is less than or equal to the health threshold parameter , will Only breeding cattle are recorded as unhealthy breeding cattle; The individual health index values ​​of cattle in any breeding stage are greater than the health threshold parameters , will Only breeding cattle are recorded as healthy breeding cattle.

[0007] Preferably, the specific method of obtaining the predicted value of health data of each dimension of each unhealthy breeding cow at different breeding stages includes: The first Only unhealthy cattle are farmed at all stages of production The sequence of health data of dimensions is recorded as Only unhealthy cattle breeding health data series of dimensions; Only unhealthy cattle breeding The health data series of dimensions is input into the ARIMA prediction model algorithm to obtain the Only unhealthy cattle are farmed at each stage of breeding Predicted value of health data in various dimensions.

[0008] Preferably, the health data prediction deviation of each unhealthy farmed cattle is obtained by analyzing the difference between the health data and the health data prediction value of each dimension of each unhealthy farmed cattle at different breeding stages, and the specific method includes: The first Only unhealthy cattle breeding The first stage of breeding The predicted value of health data in the first dimension is Only unhealthy cattle breeding The first stage of breeding The absolute value of the difference between the health data of the first dimension is recorded as Only unhealthy cattle breeding The first stage of breeding The predicted difference value of the dimension The mean of the predicted difference values ​​of all dimensions of unhealthy farmed cattle in all breeding stages is taken as the The predicted deviation of health data of unhealthy farmed cattle.

[0009] Preferably, the necessity of industrial traceability of each unhealthy farmed cattle is obtained based on the predicted deviation of health data and the individual health index value of each unhealthy farmed cattle at different breeding stages, including the specific method of: The first The reciprocal of the mean of the individual health index values ​​of unhealthy farmed cattle at all breeding stages is The normalized value of the product of the predicted deviations of the health data of the unhealthy cattle is taken as the first The necessity of industry traceability for unhealthy cattle farming.

[0010] Preferably, the health data of all farmed cattle are stored in a blockchain layered manner based on the necessity of industry traceability, including the following specific methods: Preset a stratification threshold parameter , The necessity of industrial traceability of unhealthy cattle is greater than or equal to the stratification threshold parameter , will The health data of unhealthy cattle is stored in the front layer of the blockchain; if The necessity of industrial traceability of unhealthy cattle is less than the threshold parameter of stratification , will Only the health data of unhealthy farmed cattle are stored in the middle area of ​​the blockchain; the health data of all healthy farmed cattle are stored in the back area of ​​the blockchain.

[0011] The present invention also proposes an industrial chain traceability system for large-scale cattle farming, which includes a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of the above method are implemented.

[0012] The present invention also proposes an industrial chain traceability device for large-scale cattle breeding, which includes: A health data collection module, an industry traceability necessity acquisition module and a blockchain hierarchical storage module. The health data collection module is used to obtain the health data of all farmed cattle in the farm. The industry traceability necessity acquisition module implements the steps of the above method by calling a computer program to obtain the industry traceability necessity of each unhealthy farmed cattle. The blockchain hierarchical storage module performs blockchain hierarchical storage on the health data of all farmed cattle based on the industry traceability necessity.

[0013] The beneficial effects of the present invention are as follows: the present invention screens all farmed cattle in all breeding stages based on individual health index values ​​to obtain all unhealthy farmed cattle and healthy farmed cattle; obtains the predicted health data value of each unhealthy farmed cattle in different breeding stages; obtains the predicted health data deviation of each unhealthy farmed cattle by analyzing the difference between the health data and the predicted health data value of each unhealthy farmed cattle in different breeding stages; obtains the necessity of industrial traceability of each unhealthy farmed cattle according to the predicted health data deviation and the individual health index value of each unhealthy farmed cattle in different breeding stages; performs blockchain hierarchical storage of the health data of all farmed cattle based on the necessity of industrial traceability; thereby improving the traceability efficiency of the industrial chain. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0015] Figure 1 This is a flowchart of the steps of an industrial chain traceability method for large-scale cattle breeding according to the present invention; Figure 2 This is a characteristic relationship flow chart of an industrial chain traceability method for large-scale cattle breeding according to the present invention. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not 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.

[0017] See also Figure 1 , which shows a flow chart of an industrial chain traceability method for large-scale cattle breeding provided by an embodiment of the present invention, the method comprising the following steps: Step S001, obtaining health data of all cattle in a breeding farm; the health data of cattle includes health data of several dimensions of cattle at different breeding stages.

[0018] It should be noted that in the process of large-scale cattle breeding, the purpose of industrial chain traceability is to track various data of cattle production, processing, circulation and other links to ensure the quality, safety and source traceability of the products; by tracing the entire life cycle of cattle, industrial traceability can quickly locate potential food safety hazards and ensure product safety; for example, if harmful substances are found in a batch of beef, it can be quickly traced back to the source of breeding and processing to deal with the problem. By collecting the health data of cattle during the breeding process, it can more accurately control the breeding environment, feeding process, health management and other aspects, thereby improving production efficiency and product quality.

[0019] Preferably, in some implementations of the embodiments of the present invention, the specific method for obtaining health data of several dimensions of all cattle in the farm at different breeding stages is: All the cattle in the farm are numbered, and a temperature sensor and a motion sensor are installed on any of the cattle in the farm to monitor and collect the health data of the cattle in real time. Every other week is a breeding stage, and the temperature sensor and the motion sensor are used to collect the health data of each cattle in three dimensions, namely, temperature data, exercise data and heart rate data, for a total of 12 weeks.

[0020] At this point, health data of several dimensions of all cattle in the farm at different breeding stages have been obtained.

[0021] Step S002: Obtain the individual health index value of each farmed cattle at each breeding stage according to the outliers of the health data of different dimensions of each farmed cattle at each breeding stage.

[0022] It should be noted that in the process of recording the health data of farmed cattle in the data blockchain, in order to meet the purpose of high efficiency of block traceability, the recorded health data needs to be layered on the blockchain, and the health data of farmed cattle at the top level has a higher possibility of traceability; generally, the ultimate goal of industrial chain traceability is to check whether a certain farmed cattle has certain abnormal conditions after being slaughtered and entering the market, and have the ability to track and trace the source; for example, if food health problems occur during consumer consumption, then at this time, through the blockchain non-tampering traceability method, the relevant breeders can be checked and traced to prevent the market circulation of such meat products; then compared with other individual farmed cattle, farmed cattle with the above health problems are more likely to be traced; so in the process of storing them in the data blockchain, this embodiment assigns them to a higher priority level, which is the initial layering logic.

[0023] It should be further explained that for the health data of farmed cattle transmitted to the data blockchain at any breeding stage, in order to ensure the traceability of its stratification results, it is first necessary to analyze the health data of farmed cattle in different dimensions at any breeding stage, and then combine the individual health index values ​​of each farmed cattle reflected in multiple breeding stages, and then store them in layers on the data blockchain.

[0024] Preferably, in some implementations of the embodiments of the present invention, for any farmed cattle at any breeding stage, if the outlier of a certain dimension of the health data of the farmed cattle is higher, it means that the health index of the farmed cattle deviates from the health index of the general farmed cattle, and the individual health index value of the farmed cattle is lower; and the individual attributes of the farmed cattle are different, and the corresponding health data of different dimensions will be different; then simply performing outlier analysis on the health data of a single dimension at a breeding stage, the resulting hierarchical storage result of the blockchain is inaccurate; it is necessary to conduct a comprehensive analysis in combination with the health data of different dimensions, then according to the outlier situation of the health data of different dimensions of each farmed cattle at each breeding stage, the specific method for obtaining the individual health index value of each farmed cattle at each breeding stage is: All the cattle in the farm will be The first stage of breeding The sequence of health data of the dimensions is recorded as the number of The next breeding stage health data series of dimensions; The next breeding stage The health data sequence of the dimensions is input into the LOF outlier detection algorithm to obtain the outlier value of each breeding cow in the first The next breeding stage Outliers in health data of various dimensions; The first Only cattle are raised in The next breeding stage Outliers in health data of dimensions Only cattle are raised in The next breeding stage The absolute value of the difference between the outliers of the health data in the dimension is recorded as Only cattle are raised in The next breeding stage The outlier difference of health data in the dimension Only cattle are raised in The sum of the outlier differences of health data in all dimensions under the breeding stage is recorded as Only cattle are raised in Outlier differences in health data at each breeding stage; The first Only cattle are raised in The reciprocal of the mean of the outliers of the health data of all dimensions in the breeding stage is Only cattle are raised in The normalized value of the product of the outlier differences in health data under the breeding stage is taken as the Only cattle are raised in Individual health index values ​​at each breeding stage; The specific formula is: In the formula, Indicates Only cattle are raised in Individual health index values ​​at each breeding stage; Indicates Only cattle are raised in The mean of outliers in all dimensions of health data at each breeding stage; Represents the health data types of all dimensions of farmed cattle; Indicates Only cattle are raised in The next breeding stage Outliers in health data of various dimensions; Indicates Only cattle are raised in The next breeding stage Outliers in health data of various dimensions; Indicates taking the absolute value; represents the linear normalization function; Represents the preset hyperparameters. This implementation presets , used to prevent the denominator from being 0.

[0025] It should be noted that The larger the Only cattle are raised in The comprehensive health data of the first breeding stage is significantly different from that of other breeding cattle. Only cattle are raised in The smaller the individual health index value at each breeding stage; The smaller it is, the higher the correlation between dimensional outliers is. Only cattle are raised in When the amount of exercise in the first breeding stage increases, it always corresponds to the increase of body temperature. At this time, the outliers between the two dimensions are high, so the health data shows high outliers in different dimensions. If the outlier difference is larger at this time, it means that the first Only cattle are raised in The smaller the individual health index value in each breeding stage; the LOF outlier detection algorithm is a prior art and will not be described in detail in this embodiment.

[0026] At this point, the individual health index value of each breeding cattle in each breeding stage is obtained.

[0027] Step S003: Screen all farmed cattle in all breeding stages based on individual health index values ​​to obtain all unhealthy farmed cattle and healthy farmed cattle; obtain the predicted health data value of each unhealthy farmed cattle in each dimension at different breeding stages; obtain the predicted health data deviation of each unhealthy farmed cattle by analyzing the difference between the health data and the predicted health data value of each unhealthy farmed cattle in different breeding stages; obtain the necessity of industrial traceability of each unhealthy farmed cattle based on the predicted health data deviation and the individual health index value of each unhealthy farmed cattle in different breeding stages.

[0028] It should be noted that due to the non-tamperability of data in the traceability record process, the individual health index values ​​of the same farmed cattle at different breeding stages reflect different levels of health and are recorded in different stratified results. This will also cause traceability difficulties because it is necessary to benchmark the individual health index values ​​of different breeding stages; so in order to further improve the traceability efficiency, more specific health index results of each farmed cattle are analyzed, and corresponding evaluations are made for the health index values ​​of each farmed cattle at different breeding stages. Based on the health index value as a means of division, they are stored in different blockchain stratified record domains to improve the traceability efficiency; in order to achieve this goal, farmed cattle with lower individual health index values ​​at each breeding stage are selected, and by analyzing their health results at different breeding stages, the necessity of industrial chain traceability for each farmed cattle is determined, that is, under long-term monitoring, the objective health index value of each farmed cattle is analyzed, and it is used as a reference result for the necessity of industrial chain traceability.

[0029] Preferably, in some implementations of the embodiments of the present invention, all farmed cattle in all breeding stages are screened based on individual health index values, and the specific method for obtaining all unhealthy farmed cattle and healthy farmed cattle is: Preset a health threshold parameter , wherein this embodiment is based on This example is described as an example, and this embodiment is not specifically limited. Depends on the specific implementation situation; For Only raising cattle, if Only the individual health index value of cattle in any breeding stage is less than or equal to the health threshold parameter , will Only breeding cattle are recorded as unhealthy breeding cattle; The individual health index values ​​of cattle in any breeding stage are greater than the health threshold parameters , will Only breeding cattle are recorded as healthy breeding cattle.

[0030] Preferably, in some implementations of the embodiments of the present invention, the specific method for obtaining the predicted value of health data of each dimension of each unhealthy breeding cow at different breeding stages is: The first Only unhealthy cattle are farmed at all stages of production The sequence of health data of dimensions is recorded as Only unhealthy cattle breeding health data series of dimensions; Only unhealthy cattle breeding The health data series of dimensions is input into the ARIMA prediction model algorithm to obtain the Only unhealthy cattle are farmed at each stage of breeding Predicted value of health data in various dimensions.

[0031] Among them, the ARIMA forecasting model algorithm is a prior art and will not be described in detail in this embodiment.

[0032] Preferably, in some implementations of the embodiments of the present invention, by analyzing the difference between the health data and the predicted value of the health data of each dimension of each unhealthy farmed cow at different breeding stages, the specific method for obtaining the predicted deviation of the health data of each unhealthy farmed cow is: The first Only unhealthy cattle breeding The first stage of breeding The predicted value of health data in the first dimension is Only unhealthy cattle breeding The first stage of breeding The absolute value of the difference between the health data of the first dimension is recorded as Only unhealthy cattle breeding The first stage of breeding The predicted difference value of the dimension The mean of the predicted difference values ​​of all dimensions of unhealthy farmed cattle in all breeding stages is taken as the The predicted deviation of health data of unhealthy farmed cattle; The specific formula is: In the formula, Indicates The predicted deviation of health data of unhealthy farmed cattle; Represents the health data types of all dimensions of farmed cattle; Indicates the number of all breeding stages; Indicates Only unhealthy cattle breeding The first stage of breeding Health data of various dimensions; Indicates Only unhealthy cattle breeding The first stage of breeding Predictive value of health data in various dimensions; Indicates taking the absolute value.

[0033] Preferably, in some implementations of the embodiments of the present invention, based on the predicted deviation of health data and the individual health index value of each unhealthy farmed cattle at different breeding stages, the specific method for obtaining the necessity of industrial traceability of each unhealthy farmed cattle is: The first The reciprocal of the mean of the individual health index values ​​of unhealthy farmed cattle at all breeding stages is The normalized value of the product of the predicted deviations of the health data of the unhealthy cattle is taken as the first The necessity of tracing the origin of the unhealthy cattle industry; The specific formula is: In the formula, Indicates The necessity of tracing the origin of the unhealthy cattle industry; Indicates The predicted deviation of health data of unhealthy farmed cattle; Indicates The mean of individual health index values ​​of unhealthy farmed cattle at all breeding stages; represents the linear normalization function.

[0034] At this point, it is necessary to obtain industry traceability for every unhealthy farmed cattle.

[0035] Step S004: Based on the necessity of industry traceability, the health data of all farmed cattle are stored in a layered manner on the blockchain.

[0036] Preferably, in some implementations of the embodiments of the present invention, the specific method for storing the health data of all farmed cattle in a blockchain layered manner based on the necessity of industry traceability is: Preset a stratification threshold parameter , wherein this embodiment is based on This example is described as an example, and this embodiment is not specifically limited. Depends on the specific implementation situation; Jordi The necessity of industrial traceability of unhealthy cattle is greater than or equal to the stratification threshold parameter , will The health data of unhealthy cattle is stored in the front layer of the blockchain; if The necessity of industrial traceability of unhealthy cattle is less than the threshold parameter of stratification , will Only the health data of unhealthy farmed cattle are stored in the middle area of ​​the blockchain; the health data of all healthy farmed cattle are stored in the back area of ​​the blockchain.

[0037] Among them, the necessity of industrial traceability for each healthy farmed cattle is assumed to be 0.

[0038] See also Figure 2 , which shows a characteristic relationship flow chart of an industrial chain traceability method for large-scale cattle breeding; At this point, this embodiment is completed.

[0039] Another embodiment of the present invention provides an industrial chain traceability system for large-scale cattle farming, the system comprising a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the above method steps S001 to S004 are implemented.

[0040] Another embodiment of the present invention provides an industrial chain traceability device for large-scale cattle breeding, the device comprising: A health data collection module, an industry traceability necessity acquisition module and a blockchain hierarchical storage module. The health data collection module is used to obtain the health data of all farmed cattle in the farm. The industry traceability necessity acquisition module implements the above method steps S001 to S004 by calling a computer program to obtain the industry traceability necessity of each unhealthy farmed cattle. The blockchain hierarchical storage module performs blockchain hierarchical storage on the health data of all farmed cattle based on the industry traceability necessity.

[0041] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for tracing the industrial chain of large-scale cattle breeding, characterized in that: The method comprises the following steps: Obtaining health data of all cattle in the farm; the health data of cattle includes health data of several dimensions of cattle at different breeding stages; According to the outliers of health data of different dimensions of each breeding cattle at each breeding stage, the individual health index value of each breeding cattle at each breeding stage is obtained; All farmed cattle in all breeding stages are screened based on individual health index values ​​to obtain all unhealthy farmed cattle and healthy farmed cattle; the predicted health data value of each unhealthy farmed cattle in each dimension at different breeding stages is obtained; the predicted health data deviation of each unhealthy farmed cattle is obtained by analyzing the difference between the health data and the predicted health data value of each dimension at different breeding stages; the necessity of industrial traceability of each unhealthy farmed cattle is obtained based on the predicted health data deviation and the individual health index value of each unhealthy farmed cattle at different breeding stages; Based on the necessity of industry traceability, the health data of all farmed cattle are stored in a layered manner on blockchain.

2. The industrial chain tracing method for large-scale cattle breeding according to claim 1 is characterized in that: The specific method for obtaining the individual health index value of each breeding cattle at each breeding stage according to the outliers of the health data of different dimensions of each breeding cattle at each breeding stage is as follows: All the cattle in the farm will be The first stage of breeding The sequence of health data of the dimensions is recorded as the number of The next breeding stage health data series of dimensions; The next breeding stage The health data sequence of the dimensions is input into the LOF outlier detection algorithm to obtain the outlier value of each breeding cow in the first The next breeding stage Outliers in health data of various dimensions; Get the Only cattle are raised in Outlier differences in health data at each breeding stage; The first Only cattle are raised in The reciprocal of the mean of the outliers of the health data of all dimensions in the breeding stage is Only cattle are raised in The normalized value of the product of the outlier differences in health data under the breeding stage is taken as the Only cattle are raised in Individual health index values ​​at each breeding stage.

3. The industrial chain tracing method for large-scale cattle breeding according to claim 2 is characterized in that: The acquisition Only cattle are raised in The outlier differences in health data at each breeding stage include: The first Only cattle are raised in The next breeding stage Outliers in health data of dimensions Only cattle are raised in The next breeding stage The absolute value of the difference between the outliers of the health data in the dimension is recorded as Only cattle are raised in The next breeding stage The outlier difference of health data in the dimension Only cattle are raised in The sum of the outlier differences of health data in all dimensions under the breeding stage is recorded as Only cattle are raised in The outlier differences in health data at different breeding stages.

4. The industrial chain tracing method for large-scale cattle breeding according to claim 1 is characterized in that: The specific method of screening all the breeding cattle in all breeding stages based on the individual health index values ​​to obtain all the unhealthy breeding cattle and healthy breeding cattle includes: Preset a health threshold parameter , for the Only raising cattle, if Only the individual health index value of cattle in any breeding stage is less than or equal to the health threshold parameter , will Only breeding cattle is recorded as unhealthy breeding cattle; Jordi The individual health index values ​​of cattle in any breeding stage are greater than the health threshold parameters , will Only breeding cattle are recorded as healthy breeding cattle.

5. The industrial chain tracing method for large-scale cattle breeding according to claim 1 is characterized in that: The specific method for obtaining the predicted health data value of each dimension of each unhealthy breeding cow at different breeding stages includes: The first Only unhealthy cattle are farmed at all stages of production The sequence of health data of dimensions is recorded as Only unhealthy cattle breeding health data series of dimensions; Only unhealthy cattle breeding The health data series of dimensions is input into the ARIMA prediction model algorithm to obtain the Only unhealthy cattle are farmed at each stage of breeding Predicted value of health data in various dimensions.

6. The industrial chain tracing method for large-scale cattle breeding according to claim 1 is characterized in that: The method of obtaining the predicted health data deviation of each unhealthy farmed cow by analyzing the difference between the health data of each dimension of each unhealthy farmed cow at different breeding stages and the predicted health data includes the following specific methods: The first Only unhealthy cattle breeding The first stage of breeding The predicted value of health data in the first dimension is Only unhealthy cattle breeding The first stage of breeding The absolute value of the difference between the health data of the first dimension is recorded as Only unhealthy cattle breeding The first stage of breeding The predicted difference value of the dimension The mean of the predicted difference values ​​of all dimensions of unhealthy farmed cattle in all breeding stages is taken as the The predicted deviation of health data of unhealthy farmed cattle.

7. The industrial chain tracing method for large-scale cattle breeding according to claim 1 is characterized in that: The necessity of obtaining the industrial traceability of each unhealthy farmed cattle based on the predicted deviation of health data and the individual health index value of each unhealthy farmed cattle at different breeding stages includes the following specific methods: The first The reciprocal of the mean of the individual health index values ​​of unhealthy farmed cattle at all breeding stages is The normalized value of the product of the predicted deviations of the health data of the unhealthy cattle is taken as the first The necessity of industry traceability for unhealthy cattle farming.

8. The industrial chain tracing method for large-scale cattle breeding according to claim 1 is characterized in that: The specific method of storing the health data of all farmed cattle in a layered manner on blockchain based on the necessity of industry traceability is as follows: Preset a stratification threshold parameter , The necessity of industrial traceability of unhealthy cattle is greater than or equal to the stratification threshold parameter , will Only the health data of unhealthy farmed cattle is stored in the front layer area of ​​the blockchain; Jordi The necessity of industrial traceability of unhealthy cattle is less than the threshold parameter of stratification , will Only the health data of unhealthy farmed cattle is stored in the middle area of ​​the blockchain; The health data of all healthy farmed cattle are stored in the back-layer area of ​​the blockchain.

9. An industrial chain traceability system for large-scale cattle farming, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the industrial chain traceability method for large-scale cattle breeding are implemented as described in any one of claims 1-8.

10. An industrial chain traceability device for large-scale cattle breeding, characterized in that: The device includes: A health data collection module, an industrial traceability necessity acquisition module and a blockchain hierarchical storage module. The health data collection module is used to obtain the health data of all farmed cattle in the farm. The industrial traceability necessity acquisition module implements the steps of an industrial chain traceability method for large-scale cattle breeding as described in any one of claims 1 to 8 by calling a computer program to obtain the necessity of industrial traceability for each unhealthy farmed cattle. The blockchain hierarchical storage module performs blockchain hierarchical storage on the health data of all farmed cattle based on the necessity of industrial traceability.

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