Digitalized management system and method for breeding cattle

Abstract

The invention discloses a breeding cattle digital management system and method, and the system comprises a hardware layer which is used for collecting cattle characteristics and environment data in real time based on an intelligent ear tag, an AI body size system and an intelligent base station; the data layer is used for constructing a cattle full life cycle database, storing data information and performing daily automatic backup at the same time; the application layer comprises a basic information management module, a cattle full-life-cycle management module, a frozen semen production full-process management module, an epidemic prevention and environment management module and a report and analysis module; and the user layer is used for realizing access through a PC portal and a mobile terminal APP and supporting operation of various roles. A unified cattle full life cycle database is constructed, a traditional decentralized management mode is broken through, and full-link tracing of data which is marked to the bottom from fence entering to elimination is achieved; the whole frozen semen production process, workflow engine solidified frozen semen production, epidemic prevention management and other processes are digitally controlled, so that manual intervention is reduced, and the error rate of operation is reduced.

Description

Technical Field

[0001] This invention relates to a management system and a method, and more particularly to a digital management system and method for breeding cattle. Background Technology

[0002] In the current breeding cattle and frozen semen production sector, the mainstream management model still relies on manual operation and decentralized management systems. For example, in the breeding cattle management stage, core cattle records such as pedigree information, body size and weight monitoring data, disease prevention records, and breeding records largely depend on paper ledgers or decentralized systems. This data is scattered across different departments such as breeding, propagation, and disease prevention, creating data silos. In the disease prevention management stage, vaccine dispensing and veterinary drug usage are mainly recorded manually by farmhands. This traditional management model has the following shortcomings: First, the scattered storage of breeding cattle records, production data, and disease prevention records, lacking a unified database, results in pedigree tracing taking several hours and is prone to data inconsistencies. Second, the traditional system does not integrate intelligent sensing devices, resulting in low equipment integration. Cattle health monitoring and environmental data collection rely solely on manual labor, leading to poor data timeliness, delayed quality inspection data feedback, and response delays exceeding 24 hours in abnormal situations, resulting in low production process efficiency. Third, the distribution of vaccines and the use of veterinary drugs rely on manual records, and there is no automatic early warning for withdrawal periods. According to statistics, about 30% of farms have lapses in withdrawal period management, resulting in insufficient control of epidemic prevention risks and increased food risks. Fourth, the lack of real-time data statistics and analysis functions resulted in a frozen semen inventory turnover rate that was 25% lower than the industry average. Summary of the Invention

[0003] To address the shortcomings of the aforementioned technologies, this invention provides a digital management system and method for breeding cattle.

[0004] To solve the above technical problems, the technical solution adopted by the present invention is: a digital management system for breeding cattle, including a hardware layer for real-time collection of cattle characteristics and environmental data based on smart ear tags, an AI body scale system and smart base stations; The data layer is used to build a database of the entire life cycle of breeding cattle, store data information, and perform daily automatic backups. The application layer includes a basic information management module for maintaining information on bull stations, personnel, equipment, and breed categories; a cattle lifecycle management module for recording relevant cattle information and linking them together via smart ear tags; a frozen semen production process management module for automating process management through a workflow engine and recording operation logs; a disease prevention and environmental management module for recording feed consumption, pen disinfection, site patrols, and external vehicle information, integrating a disease knowledge base, building a dual-threshold early warning model, and supporting mobile queries; and a reporting and analysis module for generating frozen semen production, sales, and inventory reports, pedigree analysis, and quality inspection summary tables, supporting multi-dimensional filtering, and data visualization through a reporting engine. The user layer is used for access via PC portal and mobile APP, and supports multiple roles for operation.

[0005] Furthermore, the hardware layer collects cattle characteristics and environmental data, specifically including the following steps: Step S1: Collect the cattle's body temperature in real time using smart ear tags, and collect their body weight in real time using the AI ​​body scale system; Step S2: Transmit the real-time body temperature and real-time body size and weight of the cattle collected in step S1 to the smart base station. Step S3: The smart base station pushes the data to the breeding cattle full life cycle database of the data layer via a dedicated data link.

[0006] Furthermore, the breeding cattle digital management system also includes a public support layer, which provides general security services for the application layer, data layer, hardware layer, and user layer to ensure the security and interconnectivity of the entire system.

[0007] Furthermore, the public support layer includes a security technology module, an interface management module, a device interaction module, and an operation log module.

[0008] Furthermore, cattle-related information includes core cattle registration information, body size and weight, breeding cattle training, disease prevention management, prescription management, ultrasound measurement, and pedigree information.

[0009] Furthermore, the application layer also includes a platform service module to support dual-entry login, role-based access control, and operation log auditing, ensuring system security; and a marketing management module, including customer management, supplier management, contract management, and order management units.

[0010] Furthermore, a digital management method for breeding cattle specifically includes the following steps: Step A1: When cattle enter the pen, they wear smart ear tags to establish basic information records; Step A2: Scan the smart ear tag ID with the mobile app, enter the relevant information of the breeding bull, and the system will automatically generate a unique bull number; at the same time, the basic information management module will update the bull station information and breeder files, supporting subsequent data association. Step A3: Conduct growth period monitoring and disease prevention management; regularly collect body measurements automatically through the AI ​​body measurement system and synchronize them to the system for comparison with historical data to generate curves; and build a dual-threshold early warning model based on intelligent early warning algorithms to trigger early warnings in different scenarios; Step A4: The epidemic prevention officer regularly disinfects the pens and enters the disinfection time and disinfectant type through the mobile terminal. The system will link the pen ID and update the record. The system automatically generates vaccination reminders based on the age of the cattle. After vaccination, the vaccine batch number is entered to form a complete epidemic prevention file. Step A5: Conduct frozen semen production and quality inspection; the semen collector makes a semen collection appointment through the system, records the bull ID and semen volume after collection, and the system automatically links the pedigree information of the bull; Step A6: The laboratory generates a task sheet based on the production plan, and the quality inspector conducts a motility test on the frozen semen; unqualified frozen semen is automatically returned, while qualified frozen semen generates an entry QR code. Step A7: The warehouse manager scans the entry QR code to complete the entry process; Step A8: After receiving an order, the sales department initiates an outbound application through the system. After approval by the administrator and re-inspection by the quality inspector, the warehouse scans the barcode and issues the order. The system simultaneously generates a production, sales and inventory report.

[0011] Furthermore, step A3 sets up a dual-threshold early warning model, which specifically includes the following steps: Step A31: Set the basic threshold according to different scenarios; Step A32: Set association conditions based on the actual situation of the scenario; Step A33: When the scenario simultaneously meets the basic threshold and the correlation condition, an early warning for the scenario is triggered.

[0012] Furthermore, in step A6, if a cow fails the vitality test due to a decline in its reproductive capacity, the cow is culled. The breeder enters the reason for culling into the system, and the system automatically connects the genealogy information and frozen semen production data over the years to form a traceability file.

[0013] Furthermore, the application layer utilizes a frozen semen production end-to-end management module to produce frozen semen, specifically including the following steps: Step B1: The semen collector records the semen collection information through the system, and the laboratory generates a task sheet for testing based on the production plan; Step B2: The quality inspection department enters quality inspection data into the system, and unqualified frozen semen will automatically trigger the return process; Step B3: When sperm enters or leaves the warehouse, the warehouse manager scans the QR code for entry and enters the information. The system will automatically update the inventory and trigger threshold warnings as needed.

[0014] This invention discloses a digital management system and method for breeding cattle, which has the following beneficial effects: I. By constructing a unified database covering the entire life cycle of breeding cattle, cattle files, pedigree data, production data, and disease prevention records are linked through smart ear tag IDs, breaking through the traditional decentralized management model and realizing full-chain data traceability from entry into the pen to culling. Second, by implementing digital management of the entire frozen semen production process, automating data collection and flow, and using intelligent ear tags to collect body temperature in real time, intelligent base stations to transmit data, and an AI body measurement system to automatically measure body size parameters, the efficiency of data collection has been improved. The workflow engine solidifies processes such as frozen semen production and disease prevention management, reducing manual intervention, lowering the error rate of operations, and saving labor costs. By integrating various IoT devices and system platforms, real-time monitoring of cattle characteristics and pen environment is achieved, shortening the response time to anomalies, and thus improving the efficiency of the production process. Third, through the epidemic prevention and environmental management module, an early warning model is built based on multi-dimensional data to realize automated early warning of vaccine use, withdrawal period, and abnormal cattle health, thereby strengthening epidemic prevention risk control and reducing the risk of disease. Fourth, by providing real-time multi-dimensional data reports and analysis functions, an early warning model is built based on multi-dimensional data. Combined with report analysis functions, data support is provided for breeding, production, and sales decisions, improving the turnover rate of frozen semen inventory and increasing the speed of decision response. Attached Figure Description

[0015] Figure 1 This is a system architecture diagram of the present invention.

[0016] Figure 2 This is a management flowchart for the present invention. Detailed Implementation

[0017] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0018] like Figure 1 and 2The illustrated digital management system for breeding cattle includes a hardware layer, a data layer, an application layer, and a user layer. The hardware layer is used to collect real-time data on cattle characteristics and the environment. The hardware layer includes smart ear tags, an AI body measurement system, a smart base station, and multimedia information. The hardware layer transmits real-time data such as cattle body temperature, body size, weight, and pen environment to the smart base station via ultra-high frequency radio frequency communication through the smart ear tags. The smart base station then pushes this data to the breeding cattle's full life-cycle database in the data layer via Ethernet or a dedicated data link. The smart ear tags upload body temperature data every 10 minutes, which is then aggregated by the smart base station and written into the cattle health data table in the database, achieving real-time storage of raw data. In this embodiment, the smart ear tags upload body temperature every ten minutes, the AI ​​body measurement system automatically measures body size, and the smart base station achieves real-time data transmission within a 150-meter range, avoiding data accumulation or loss at the device end.

[0019] The data layer is used to construct a full lifecycle database for breeding cattle, enabling data storage. This data includes cattle records, production data, quality inspection data, and disease prevention records, and is automatically backed up daily, maintaining seven backup versions. Data cleaning is also performed to improve data quality, laying a solid foundation for end-to-end traceability. The breeding cattle full lifecycle database uses MySQL 5.7. The data layer provides data support to various modules in the application layer through the breeding cattle full lifecycle database interface. In this embodiment, when the cattle full lifecycle management module in the application layer needs to query the pedigree information of a specific cattle, it uses the smart ear tag ID as the association key. Data is retrieved from the disease prevention record table in the pedigree table of the breeding cattle full lifecycle database. When the frozen semen production full-process management module generates a production plan, it needs to read data from the inventory table in the collection record table for calculation. Simultaneously, the operation results of the application layer, such as quality inspection data entry and inventory updates, are written back to the data layer to ensure real-time data synchronization. By constructing a unified database covering the entire life cycle of breeding cattle, cattle files, pedigree data, production data, and disease prevention records are linked through smart ear tag IDs. This breaks through the traditional decentralized management model and enables full-chain data traceability from entry into the pen to culling, reducing pedigree query time to the second level. This shortens the entire frozen semen production process and automatically links the entire life cycle of cattle, allowing for full data retrieval by scanning a code, thus improving pedigree query efficiency.

[0020] The application layer includes a basic information management module for maintaining information on bull stations, personnel, equipment files, and breed categories, and supports batch import and export of Excel data; and a cattle lifecycle management module for recording core cattle registration information, body size and weight, breeding cattle training, disease prevention management, prescription management, ultrasound measurements, and pedigree information. It also automatically collects body temperature data via smart ear tags and triggers alerts when abnormalities occur. Core cattle registration information includes cattle number, breed, and status, and is linked to cattle files, disease prevention records, and pedigree information via smart ear tag IDs, enabling end-to-end data traceability throughout the entire lifecycle. The digital management method for breeding cattle is implemented through the cattle lifecycle management module, specifically including the following steps: Step A1: Basic information is established when cattle enter the pen. Cattle are fitted with smart ear tags upon entry. For breeding cattle, this implementation uses 3-month-old Simmental calves; the handler applies ultra-high frequency smart ear tags to them. Step A2: Scan the ear tag ID using the mobile app, enter information such as the breed, date of birth, and origin of the breeding cattle, and the system will automatically generate a unique cattle number; at the same time, the basic information management module will update the bull station information and breeder files synchronously, and support subsequent data association; Step A3: Conduct growth period monitoring and disease prevention management; automatically collect body height, chest circumference, and other data monthly through the AI ​​body measurement system, synchronize them to the system, and compare them with historical data to generate a growth curve; regularly collect body size and weight data through the AI ​​body measurement system, and upload the data to the cattle in real time using smart ear tags. In case of abnormalities, a health warning temperature is triggered based on an intelligent early warning algorithm. In this embodiment, a notification is sent to the veterinarian when the cattle's body temperature is detected to be greater than 39.5℃; in this embodiment, a dual-threshold early warning model is constructed based on the intelligent early warning algorithm. Using basic thresholds and correlation conditions as the core, combined with real-time collected data and historical baselines, early warnings are triggered for different scenarios; the dual-threshold early warning model provides early warnings, specifically including the following steps: Step A31: Set the basic threshold according to different scenarios; Step A32: Set association conditions based on the actual situation of the scenario; Step A33: When the scenario simultaneously meets both the basic threshold and the associated condition, an alert for that scenario is triggered. For example, in the inventory alert model of the dual threshold alert system, the basic threshold is set to 500 units, and the associated condition is that the expected sales in the next 7 days are greater than 300 units. Therefore, when the inventory is less than 500 units and the expected sales exceed 300 units, an emergency replenishment alert is triggered. In the health alert model of the dual threshold alert system, the basic threshold is a body temperature greater than 39°C, and the associated condition is a sudden decrease in activity level. Therefore, when both the basic threshold and the associated condition are met, the system determines that the person is in a health abnormality. It should be noted that in this embodiment, body temperature is measured every 2 hours. If the body temperature exceeds 39°C for 3 consecutive times, and the activity level decreases by no less than 50% compared to the average of the previous 24 hours, a health alert is triggered. Warning; Among them, the activity level is collected by the built-in accelerometer of the smart ear tag, and the unit is the number of daily activities; the smart ear tag data of the cow with the number XM-2025-002 shows that the body temperature was 39.2℃ at 10:00, 39.3℃ at 12:00, and 39.5℃ at 14:00. The body temperature was above 39℃ for three consecutive times, and the activity level was 80 times on that day. The average activity level in the previous 24 hours was 200 times. The activity level on that day decreased by 60% compared with the previous day, which is more than 50%. Therefore, the conditions are met, and the system judges it as an abnormal health condition. It needs to be pushed to the veterinarian's mobile terminal immediately and linked to the most recent immunization record for auxiliary diagnosis.

[0021] Step A4: After the sanitation worker regularly disinfects the pens, he enters the disinfection time and disinfectant type through the mobile terminal. The system links the pen ID and updates the record. When foot-and-mouth disease vaccination is required, the system automatically generates a vaccination reminder based on the age of the cattle. After vaccination, the vaccine batch number is entered to form a complete sanitation file. Step A5: Conduct frozen semen production and quality inspection; the semen collector makes a semen collection appointment through the system, records the bull ID and semen volume after collection, and the system automatically links the pedigree information of the bull, its sire number and maternal number; Step A6: The laboratory generates a task sheet based on the production plan. The quality inspector performs a motility test on the frozen semen, and the pass standard is not less than 0.3. After the data is entered into the system, the unqualified frozen semen will automatically trigger the return process, while the qualified frozen semen will generate an entry QR code. Step A7: The warehouse manager scans the entry QR code to complete the entry. The system automatically updates the inventory and will automatically send a replenishment warning to the sales department when the inventory is below 500 units. Step A8: After receiving an order, the sales department initiates an outbound application through the system. After approval by the administrator and re-inspection by the quality inspector, the warehouse scans the barcode for outbound delivery, and the system simultaneously generates a production, sales, and inventory report. The re-inspection condition is that the frozen sperm motility must be no less than 0.25. Step A9: When cattle are culled due to declining reproductive capacity, the breeder enters the reason for culling into the system. The system automatically links the genealogy information and frozen semen production data over the years to form a traceability file, supporting subsequent traceability analysis by breeders. In this example, a 10-year-old bull with the number XM-2025-001 had a sperm motility that was consistently less than 0.2 and was culled due to declining reproductive capacity.

[0022] Simultaneously, it also includes a frozen semen production full-process management module, covering semen collection process, production planning, quality inspection management, warehousing management, and frozen semen production summary. The workflow engine automates the process. Quality inspection management includes routine quality inspection and inbound / outbound viability testing. Based on the workflow engine configuration approval process, frozen semen outbound requires four steps: sales department application, administrator approval, quality inspector confirmation, and warehouse outbound. Each step is automatically recorded in the log. The workflow engine solidifies frozen semen production and epidemic prevention management processes, reducing manual intervention and lowering the error rate. It sets unified data entry standards and process specifications, and digitizes information such as feed consumption ledgers. Intelligent equipment replaces manual monitoring, shortening inventory counting time, reducing the need for dedicated record keepers, and saving labor costs. Through digital control of the entire frozen semen production process, automated data collection and flow are achieved. Real-time temperature collection via smart ear tags, data transmission within 150 meters via smart base stations, and automatic measurement of body size parameters by an AI body size system improve data collection efficiency, reducing batch processing time to less than 1.5 hours, thereby improving production process efficiency. The disease prevention and environmental management module records information on feed consumption, pen disinfection, site patrols, and disinfection of external vehicles. It integrates a disease knowledge base, constructs a dual-threshold early warning model, and supports mobile queries. Through this module, an early warning model is built based on multi-dimensional data to automatically warn of vaccine issuance, withdrawal periods, and abnormal cattle health, thereby strengthening disease prevention risk control and reducing disease risk. In other words, intelligent early warning reduces the oversight rate of withdrawal period management, lowers disease risk, reduces the failure rate of frozen semen quality inspection, and improves product quality. The reporting and analysis module generates frozen semen production, sales, and inventory reports, pedigree analysis reports, and quality inspection summary tables. It supports multi-dimensional filtering by time, breed, and customer, and enables data visualization through a reporting engine. By providing real-time multi-dimensional data reports and analysis functions, it builds early warning models based on multi-dimensional data. Combined with report analysis functions, it provides data support for breeding, production, and sales decisions, improving frozen semen inventory turnover and decision-making speed. Specifically, based on production, sales, and inventory data trend analysis, it improves frozen semen inventory turnover, reduces capital occupation, and increases the efficiency of selecting superior breeding cattle by improving the accuracy of breeding analysis. The platform service module supports dual-entry login, role-based access control, and operation log auditing, thereby ensuring system security. Dual-entry login includes user login and data center administrator login. Roles include data center administrator, production department, and quality inspection department, etc. The data center administrator can monitor the data flow of each module in real time through the data center, and simultaneously assign permissions according to roles. Operation logs are automatically audited to prevent unauthorized operations. The marketing management module includes customer management, supplier management, contract management, and order management units.The application layer exposes functional interfaces to the user layer through Web services (PC portal) and mobile APIs (mobile apps). Operation requests from different user roles, such as feeders entering cattle information and quality inspectors submitting quality inspection reports, are processed by the platform service module of the application layer after permission verification, and the results are fed back to the user through a visual interface. In this embodiment, when the veterinarian receives a health alert through the mobile app, the cattle life cycle module of the application layer retrieves and formats the body temperature data and cattle information associated with the alert from the data layer.

[0023] The user layer is accessed via a PC portal and a mobile app, supporting multiple roles such as breeders, breeders, and quality inspectors. By assigning permissions according to roles, it supports collaborative operations among breeders, the quality inspection department, and the sales department, improving the efficiency of information transmission.

[0024] It also includes a common support layer, which provides general protection services for the application layer, data layer, hardware layer, and user layer to ensure the security and interconnectivity of the entire system. This layer includes security technology modules, interface management modules, device interaction modules, and operation log modules. Frozen sperm production is managed using an application-layer frozen sperm production end-to-end management module, specifically including the following steps: Step B1: The semen collector records the semen collection information through the system, and the laboratory generates a task sheet for testing based on the production plan; Step B2: The quality inspection department enters quality inspection data into the system. Unqualified frozen semen will automatically trigger the return process. The quality inspection data includes motility and density, etc. Step B3: When entering or leaving the warehouse, the warehouse manager scans the QR code for entry and enters the information. The system automatically updates the inventory and triggers a threshold warning as needed. In this embodiment, the sales department is notified when the inventory is below 500 units.

[0025] By integrating various IoT devices and system platforms, real-time monitoring of cattle characteristics and pen environment can be achieved, reducing the anomaly response time to within 30 minutes.

[0026] This embodiment provides the key links, technologies, and data flow for cattle from entry to culling, specifically including the following steps: Step C1: Leaders set annual target requirements, technicians screen and find cattle to purchase based on the targets, and purchasing staff purchase liquid nitrogen, disinfection equipment, vaccines, veterinary drugs and feed according to the purchase contracts and customer management. Step C2: The technician will track and breed the purchased three-month-old calves, and regularly monitor the calves' body fat index and collect data during this breeding process; Step C3: Place the calves in the breeding farm for further development. The breeding farm requires regular environmental disinfection, and records of disinfection and external vehicle visits must be maintained. The breeding process specifically includes the following steps: Step C31: File and register the March-aged calves in the breeding cattle warehouse; the breeding cattle warehouse includes basic information about the breeding cattle and various test results. Step C32: Regularly monitor the physical characteristics of breeding cattle, including weight and body length; Step C33: Train the replacement calves; Step C34: Conduct sperm collection management; This involves technicians managing sperm collection according to the production plan, specifically including the following steps: Step C34-1: The technician collects sperm. If any unexpected events occur during the collection process, the events are recorded. Step C34-2: Send to the laboratory and add diluent; Step C34-3: Perform sperm motility testing; Step C34-4: Perform frozen sperm monitoring; Step C34-5: After testing, qualified sperm are stored in the bank and managed as sperm storage.

[0027] Step C35: Select or cull older breeding cattle for breeding purposes; Step C36: The marketing center sells high-quality sperm, which needs to be processed for release from the breeding cattle warehouse before it can be sold.

[0028] The above embodiments are not intended to limit the present invention, and the present invention is not limited to the examples given above. Any changes, modifications, additions or substitutions made by those skilled in the art within the scope of the technical solution of the present invention are also within the protection scope of the present invention.

Claims

1. A digital management system for breeding cattle, characterized in that, This includes a hardware layer for real-time collection of cattle characteristics and environmental data based on smart ear tags, AI body scale systems, and smart base stations; The data layer is used to build a database of the entire life cycle of breeding cattle, store data information, and perform daily automatic backups. The application layer includes a basic information management module for maintaining information on bull stations, personnel, instruments, and breed categories; a cattle lifecycle management module for recording relevant cattle information and linking them together via smart ear tags; and a frozen semen production process management module for automating process management through a workflow engine and recording operation logs. The epidemic prevention and environmental management module is used to record information on fodder consumption, pen disinfection, site patrols, and external vehicles. It integrates an epidemic knowledge base, builds a dual-threshold early warning model, and supports mobile queries. The reporting and analysis module is used to generate frozen semen production, sales and inventory reports, pedigree analysis and quality inspection summary tables. It supports filtering by multiple dimensions and realizes data visualization through the reporting engine. The user layer is used for access via PC portal and mobile APP, and supports multiple roles for operation.

2. The digital management system for breeding cattle according to claim 1, characterized in that: The hardware layer performs cattle characteristic and environmental data collection, specifically including the following steps: Step S1: Collect the cattle's body temperature in real time using smart ear tags, and collect their body weight in real time using the AI ​​body scale system; Step S2: Transmit the real-time body temperature and real-time body size and weight of the cattle collected in step S1 to the smart base station. Step S3: The smart base station pushes the data to the breeding cattle full life cycle database of the data layer via a dedicated data link.

3. The digital management system for breeding cattle according to claim 1, characterized in that: The breeding cattle digital management system also includes a common support layer, which provides general security services for the application layer, data layer, hardware layer and user layer to ensure the security and interconnectivity of the entire system.

4. The digital management system for breeding cattle according to claim 3, characterized in that: The common support layer includes a security technology module, an interface management module, a device interaction module, and an operation log module.

5. The digital management system for breeding cattle according to claim 1, characterized in that: The relevant information about the cattle includes core information on cattle registration, body size and weight, training of breeding cattle, disease prevention and control, prescription management, ultrasound measurement and pedigree information.

6. The digital management system for breeding cattle according to claim 1, characterized in that: The application layer also includes a platform service module to support dual-entry login, role-based access control, and operation log auditing, ensuring system security; and a marketing management module, including a customer management unit, a supplier management unit, a contract management unit, and an order management unit.

7. A method for digital management of breeding cattle, applied to the digital management system for breeding cattle as described in any one of claims 1-6, characterized in that, Specifically, the following steps are included: Step A1: When cattle enter the pen, they wear smart ear tags to establish basic information records; Step A2: Scan the smart ear tag ID with the mobile app, enter the relevant information of the breeding bull, and the system will automatically generate a unique bull number; at the same time, the basic information management module will update the bull station information and breeder files, supporting subsequent data association. Step A3: Conduct growth period monitoring and disease prevention management; regularly collect body measurements automatically through the AI ​​body measurement system and synchronize them to the system for comparison with historical data to generate curves; and build a dual-threshold early warning model based on intelligent early warning algorithms to trigger early warnings in different scenarios; Step A4: The epidemic prevention officer regularly disinfects the pens and enters the disinfection time and disinfectant type through the mobile terminal. The system will link the pen ID and update the record. The system automatically generates vaccination reminders based on the age of the cattle. After vaccination, the vaccine batch number is entered to form a complete epidemic prevention file. Step A5: Conduct frozen semen production and quality inspection; the semen collector makes a semen collection appointment through the system, records the bull ID and semen volume after collection, and the system automatically links the pedigree information of the bull; Step A6: The laboratory generates a task sheet based on the production plan, and the quality inspector conducts a motility test on the frozen semen; unqualified frozen semen is automatically returned, while qualified frozen semen generates an entry QR code. Step A7: The warehouse manager scans the entry QR code to complete the entry process; Step A8: After receiving an order, the sales department initiates an outbound application through the system. After approval by the administrator and re-inspection by the quality inspector, the warehouse scans the barcode and issues the order. The system simultaneously generates a production, sales and inventory report.

8. The method for digital management of breeding cattle according to claim 7, characterized in that: Step A3, which sets up the dual-threshold early warning model, specifically includes the following steps: Step A31: Set the basic threshold according to different scenarios; Step A32: Set association conditions based on the actual situation of the scenario; Step A33: When the scenario simultaneously meets the basic threshold and the correlation condition, an early warning for the scenario is triggered.

9. The method for digital management of breeding cattle according to claim 7, characterized in that: In step A6, if a cow fails the vitality test due to a decline in its reproductive capacity, the cow is culled. The breeder enters the reason for culling into the system, and the system automatically links the genealogy information and frozen semen production data over the years to form a traceability file.

10. The method for digital management of breeding cattle according to claim 7, characterized in that: The application layer utilizes a frozen semen production process management module to produce frozen semen, specifically including the following steps: Step B1: The semen collector records the semen collection information through the system, and the laboratory generates a task sheet for testing based on the production plan; Step B2: The quality inspection department enters quality inspection data into the system, and unqualified frozen semen will automatically trigger the return process; Step B3: When sperm enters or leaves the warehouse, the warehouse manager scans the QR code for entry and enters the information. The system will automatically update the inventory and trigger threshold warnings as needed.

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