Low-purine ecological pig circulating breeding system

Abstract

The invention relates to the technical field of agricultural science, and discloses a low-purine ecological pig circulating breeding system which comprises a breeding environment regulation and control module, a low-purine feed management module, an excrement treatment module, a recycling module, a health monitoring module, an intelligent decision-making module, a traceability management module, a water quality purification module and an energy recovery module. The breeding environment regulation and control module monitors in real time and automatically regulates pig house environment parameters through a distributed sensor network; the low-purine feed management module generates a low-purine feed formula based on growth stage recognition and nutritional requirement analysis; the excrement treatment module is used for converting breeding wastes into organic fertilizer raw materials; the cyclic utilization module realizes precise returning of the organic fertilizer to the field according to planting requirements; the health monitoring module evaluates the purine level of the swinery; the intelligent decision-making module integrates the multi-source data to generate a comprehensive optimization scheme; and the traceability management module records whole-process data through a block chain technology. The stability of low-purine culture is guaranteed, and the success rate of low-purine culture is increased.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of agricultural science and technology, in particular to a low purine ecological pig circular breeding system. BACKGROUND

[0002] Agricultural science is a science that studies the natural laws and economic laws of agricultural development, and is comprehensive because it involves various sciences such as agricultural environment, crop and livestock production, agricultural engineering, and agricultural economy. Forestry science and aquaculture science are sometimes included in the broad category of agricultural science.

[0003] At present, due to various technical defects in the traditional pig breeding process, when low purine pig breeding is carried out, the conventional feed formula cannot control the purine content, which may cause the purine level of pork products to exceed the standard, and if the purine metabolism abnormality is not discovered in time, it will cause the product quality to be unqualified and cannot meet the market demand of healthy food.

[0004] Therefore, the low purine ecological pig circular breeding system is proposed to solve the above problems. SUMMARY

[0005] In view of the deficiencies of the prior art, the low purine ecological pig circular breeding system is provided, which solves the problems of the conventional feed formula being unable to control the purine content and being unable to meet the market demand of healthy food as described in the background.

[0006] TECHNICAL SCHEME

[0007] To achieve the above purpose, the present application provides the following technical scheme: the low purine ecological pig circular breeding system comprises:

[0008] The breeding environment control module: the distributed sensor network is used to monitor the pig house environment parameters in real time, the intelligent analysis algorithm is used to generate control instructions, and the variable frequency ventilation system is used to execute environment optimization;

[0009] The low purine feed management module: the growth stage recognition unit and the nutrient demand database are integrated, the formula optimization engine is used to generate a feed formula that meets the purine threshold, and the precise metering feeding device is used to realize differentiated feeding;

[0010] The excrement treatment module: the solid-liquid separation device and the biological fermentation system are provided, and the breeding waste is converted into standardized organic fertilizer raw materials;

[0011] The recycling module: the organic fertilizer nutrients are analyzed by the rapid component detector, the matching scheme is generated by combining the planting demand model, and the intelligent fertilization equipment is used to realize precise field application;

[0012] Health monitoring module: integrated wearable sensing devices and image recognition systems, real-time collection of physiological data of pig groups, evaluation of purine levels through metabolic analysis models and generation of early warning signals;

[0013] Intelligent decision-making module: build a multi-source data fusion platform, use weighted evaluation algorithm to generate a comprehensive solution including environmental regulation, feed optimization and health management;

[0014] Traceability management module: record the whole process data of breeding through blockchain technology, and generate a verifiable product traceability report combined with quality detection results.

[0015] Preferably, the breeding environment regulation module comprises:

[0016] Environmental parameter regulation algorithm:

[0017] ;

[0018] wherein, is the normalized environmental regulation coefficient, the threshold range is 0-1, is the real-time temperature monitoring value, unit: ℃, is the optimal temperature, is the temperature normalization reference, is the real-time humidity monitoring value, unit: ℃, is the optimal humidity, is the humidity normalization reference, is the ammonia concentration, unit: ppm, is the safety threshold, is the concentration normalization reference, is the weight distribution coefficient, =0.4, =0.3, =0.3, when >0.6 triggers strong control, 0.3 ≤0.6 triggers weak control, ≤0.3 remains in monitoring state;

[0019] Environmental parameter monitoring unit, equipped with distributed temperature and humidity sensor network, real-time collection of temperature and humidity data in different areas of pig house;

[0020] Air quality analysis unit, using electrochemical sensor array to detect ammonia and hydrogen sulfide concentration, and calculate air quality index;

[0021] Environmental optimization decision unit, based on the preset environmental comfort model, combined with real-time monitoring data to generate ventilation, humidification and cooling instructions;

[0022] The intelligent ventilation system comprises a variable frequency fan unit and an adjustable ventilation window, which dynamically adjusts the ventilation volume and airflow organization mode according to instructions.

[0023] Preferably, the working process of the low-purine feed management module comprises:

[0024] The nutritional requirement analysis unit calculates the upper limit of daily purine intake according to the growth stage, body weight and health status of different pig groups;

[0025] The formula optimization unit screens a low-purine raw material combination based on a raw material database to ensure that the protein content meets the requirements while the purine level is lower than the threshold value;

[0026] The automatic feeding system uses a precise metering device to prepare feed according to the optimized formula, and realizes individual differentiated feeding through RFID identification technology.

[0027] Preferably, the working process of the excrement treatment module is as follows:

[0028] The solid-liquid separation unit uses a spiral extrusion separator to separate the excrement into solid and liquid parts;

[0029] The biological fermentation unit comprises an aerobic fermentation tank and an anaerobic digestion tank, which respectively treat the solid and liquid parts to reduce the content of harmful substances through microbial degradation;

[0030] The conveying pipeline is equipped with a component monitoring probe to detect the moisture content, pH value and nutrient content of the organic fertilizer raw material in real time.

[0031] Preferably, the working process of the recycling module comprises:

[0032] The component detection unit uses near-infrared spectroscopy technology to quickly analyze the nitrogen, phosphorus and potassium content and organic matter proportion of the organic fertilizer raw material;

[0033] The intelligent proportioning unit calculates the optimal fertilization formula and dosage according to the crop demand and soil test results of the planting area;

[0034] The automatic fertilization system comprises a variable rate fertilizer applicator and a drip irrigation device to realize precise application and balanced nutrient supply of organic fertilizer.

[0035] Preferably, the working process of the health monitoring module is as follows:

[0036] The purine metabolism evaluation model is:

[0037] ;

[0038] Wherein, is the standardized purine metabolism index, and the threshold value range is 0-2, is the urine uric acid concentration, unit: mg / dL, is the baseline value, is the blood uric acid content, in mg / dL, is the baseline value, is the individual body weight, in kg, is the body weight normalized baseline, = 0.6, = 0.4 is the metabolic contribution coefficient, + = 1, > 1.2 is determined to be abnormal metabolism, 0.8 ≤ 1.2 needs to be continuously monitored, ≤ 0.8 is determined to be normal metabolism;

[0039] The physical sign acquisition unit includes a wearable device and an image recognition system to acquire pig body temperature, activity level, and feeding behavior data;

[0040] The purine metabolism analysis unit evaluates the individual's purine metabolism efficiency and uric acid level through blood and urine detection devices;

[0041] The abnormality early warning unit establishes a health risk prediction model and generates a graded early warning signal when the detected value deviates from the normal range.

[0042] Preferably, the working process of the intelligent decision module includes:

[0043] The multi-source data fusion unit integrates environmental data, feed data, health data, and recycling data to construct a multi-dimensional feature vector;

[0044] The weight calculation unit uses the analytic hierarchy process to determine the weight coefficients of each influencing factor and generates a comprehensive evaluation score;

[0045] The breeding optimization scheme includes environmental parameter adjustment suggestions, feed formula optimization schemes, and health management measures.

[0046] Preferably, the working process of the traceability management module is:

[0047] The identification recognition unit uses ear tags and subcutaneous chips to record pig individual identity information and growth cycle data;

[0048] The blockchain storage unit stores breeding environmental parameters, feed feeding records, health monitoring data, and organic fertilizer usage on the chain;

[0049] The visual display unit generates a quality certificate containing purine content detection reports, breeding environment evaluation, and organic certification information.

[0050] Preferably, it further includes:

[0051] Water purification module: The aquaculture wastewater is treated through a multi-layer filtration unit, residual nutrients are removed by a plant absorption unit, and recycled water is output after ultraviolet disinfection unit treatment;

[0052] Energy recovery module: biogas generated during the fermentation process is recovered through a biogas collection system, and converted into heat and electricity by a combined heat and power device for system use.

[0053] Preferably, it also includes:

[0054] Environmental intelligent control subsystem, containing a distributed temperature and humidity sensor array, an ammonia gas concentration detector and an environmental regulation actuator, for real-time monitoring and automatic adjustment of pig house environmental parameters;

[0055] Precise nutrition supply subsystem, integrated with a growth stage recognition unit, a purine metabolism characteristic database and an automatic batching device, for formulating low purine feed according to different growth stage requirements;

[0056] Waste recycling treatment subsystem, equipped with a solid-liquid separation device, an aerobic fermentation tank and an anaerobic digestion tank, for converting breeding waste into organic fertilizer;

[0057] Organic fertilizer precise application subsystem, containing a component detector, a proportioning regulator and a variable rate fertilizer applicator, for applying the treated organic fertilizer precisely to the matching planting area;

[0058] Health monitoring and early warning subsystem, integrated with wearable devices, image recognition systems and biosensors, for real-time monitoring of pig health status and purine metabolism level;

[0059] Intelligent decision support subsystem, with a multi-source data fusion unit and an optimization algorithm engine, for generating a comprehensive breeding optimization scheme;

[0060] Product traceability and certification subsystem, containing a blockchain storage module and a quality detection device, for recording full-process data and generating a quality certification report.

[0061] Advantages

[0062] Compared with the prior art, the present application provides a low purine ecological pig circular breeding system, which has the following advantages:

[0063] 1. In the present application, by establishing an environmental parameter standard model and setting differential control standards for different growth stages, the accuracy of pig house environmental control is ensured, and the temperature and humidity and harmful gas concentration are monitored in real time, and the ventilation and temperature control equipment is automatically adjusted, which can avoid the stress reaction of pigs caused by environmental factors, ensure the stability of low purine breeding, and reduce the adverse effects of environmental factors on purine metabolism.

[0064] 2. In the present application, by calculating the purine metabolic demand of each growth stage, the proportion of nutritional ingredients in the feed formula is adjusted in real time, so that the system can accurately control the purine intake of each pig, and when purine metabolism is detected, it can be corrected in time by adjusting the feed formula, ensuring that the overall purine level of the pig population is within the safe threshold range, and improving the success rate of low purine breeding.

[0065] 3. In the present application, by automatically monitoring the conversion efficiency of the fermentation process, the treatment parameters are adjusted in real time, which can efficiently convert excrement into high-quality organic fertilizer, and at the same time, through the fertilization system, the organic fertilizer is used back to the supporting planting area, realizing the full utilization of breeding waste, improving the resource recycling rate, and solving the environmental pollution problem of traditional farms.

[0066] 4. In the present application, by recording the whole process data from the breeding environment, feed feeding to health monitoring through blockchain technology, a real and reliable purine content detection report can be provided to ensure the traceability of low purine pork products, improve the market recognition and added value of the products, and provide technical support for health food certification. BRIEF DESCRIPTION OF DRAWINGS

[0067] Figure 1 The figure is a schematic diagram of the framework of the low purine ecological pig circular breeding system of the present application. DETAILED DESCRIPTION

[0068] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0069] Please refer to Figure 1 The specific implementation of the low purine ecological pig circular breeding system is as follows, including:

[0070] Breeding environment control module: real-time monitoring of pig house environmental parameters through distributed sensor network, generating control instructions using intelligent analysis algorithm, and executing environmental optimization through variable frequency ventilation system;

[0071] Low purine feed management module: integrating growth stage recognition unit and nutrient demand database, generating feed formula meeting purine threshold through formula optimization engine, and realizing differentiated feeding using precise metering feeding device;

[0072] Excrement treatment module: equipped with solid-liquid separation device and biological fermentation system, converting breeding waste into standardized organic fertilizer raw material;

[0073] Recycling module: Analyze the nutrients of organic fertilizer through rapid component detector, generate matching scheme combined with planting demand model, and realize precise returning to field by intelligent fertilization equipment;

[0074] Health monitoring module: Integrate wearable sensing devices and image recognition systems to collect real-time physiological data of pig groups, evaluate purine levels through metabolic analysis model, and generate early warning signals;

[0075] Intelligent decision-making module: Build a multi-source data fusion platform, and generate a comprehensive solution including environmental regulation, feed optimization and health management by using weighted evaluation algorithm;

[0076] Traceability management module: Record the whole process data of breeding through blockchain technology, and generate verifiable product traceability report combined with quality detection results;

[0077] The breeding environment regulation module includes:

[0078] Environmental parameter regulation algorithm:

[0079] ;

[0080] Among them, is the normalized environment regulation coefficient, the threshold range is 0-1, is the real-time temperature monitoring value, unit: ℃, is the optimal temperature, is the temperature normalization reference, is the real-time humidity monitoring value, unit: ℃, is the optimal humidity, is the humidity normalization reference, is the ammonia concentration, unit: ppm, is the safety threshold, is the concentration normalization reference, is the weight distribution coefficient, =0.4, =0.3, =0.3, when >0.6 triggers strong control, 0.3 ≤0.6 triggers weak control, ≤0.3 remains in monitoring state;

[0081] The environmental parameter monitoring unit is configured with a distributed temperature and humidity sensor network to collect real-time temperature and humidity data in different areas of the pig house;

[0082] The air quality analysis unit uses an electrochemical sensor array to detect ammonia and hydrogen sulfide concentrations and calculate the air quality index;

[0083] An environmental optimization decision unit generates ventilation, humidification, and cooling instructions based on a preset environmental comfort model and real-time monitoring data.

[0084] An intelligent ventilation system includes a variable frequency fan unit and an adjustable ventilation window, which dynamically adjusts the ventilation volume and airflow organization mode according to the instructions.

[0085] The working process of the low-purine feed management module includes:

[0086] A nutritional requirement analysis unit calculates the upper limit of daily purine intake according to the growth stage, body weight, and health status of different pig groups.

[0087] A formula optimization unit selects a low-purine raw material combination based on a raw material database to ensure that the protein content meets the requirements while the purine level is below the threshold value. The formula optimization algorithm is:

[0088] ;

[0089] wherein, is the normalized feed score, and the threshold value is 0-2, is the i-th nutritional weight, =1, is the nutritional standardized value, is the requirement reference, with a unit of g / kg, is the purine standardized value, =500mg / kg is the safety threshold value, is the cost proportion, =5 yuan / kg is the upper limit, is the cost adjustment factor, ranging from 0.1 to 0.3, >1.5 is a high-quality formula, 1.0-1.5 needs optimization, and less than 1.0 is eliminated;

[0090] An automatic feeding system uses a precise metering device to prepare feed according to the optimized formula and realizes individual differentiated feeding through RFID identification technology.

[0091] The working process of the excrement treatment module is as follows:

[0092] A solid-liquid separation unit uses a spiral extrusion separator to separate excrement into solid and liquid parts.

[0093] A biological fermentation unit includes an aerobic fermentation tank and an anaerobic digestion tank, which respectively treat solid and liquid parts, reduce the content of harmful substances through microbial degradation, and the fermentation efficiency evaluation model is:

[0094] ;

[0095] wherein, is the normalized conversion rate, 0-1, >0.8, is a time coefficient, is a reference time, is a temperature coefficient, optimal temperature, when trigger temperature and time adjustment when <0.6;

[0096] The conveying pipeline is equipped with a component monitoring probe to detect the moisture content, pH value and nutrient content of the organic fertilizer raw material in real time.

[0097] The working process of the recycling module includes:

[0098] The fertilizer application amount calculation formula is:

[0099] ;

[0100] wherein, is a fertilizer application amount coefficient, , is a soil deficiency ratio, is a critical value, is a fertilizer efficiency concentration ratio, is an organic matter standard, is a utilization ratio, is a reference value, is a soil correction factor, ranging from 0.9 to 1.1, >1.2 needs to be applied in several times, less than 0.8 needs to be supplemented;

[0101] The component detection unit uses near-infrared spectroscopy technology to quickly analyze the nitrogen, phosphorus and potassium content and organic matter proportion of the organic fertilizer raw material.

[0102] The intelligent proportioning unit calculates the optimal fertilizer formula and dosage according to the crop demand of the planting area and the soil test results.

[0103] The automatic fertilizer application system includes a variable fertilizer application machine and a drip irrigation device to realize precise application of organic fertilizer and balanced supply of nutrients.

[0104] The working process of the health monitoring module is:

[0105] The purine metabolism evaluation model is:

[0106] ;

[0107] wherein, is a standardized purine metabolism index, with a threshold range of 0-2, is a urine uric acid concentration, in mg / dL, is a reference value, is a blood uric acid content, in mg / dL, is a reference value, is the individual body weight, in kg, is the body weight normalized reference, = 0.6, = 0.4 is the metabolic contribution coefficient, = 1, > 1.2 is determined to be abnormal metabolism, 0.8 ≤ 1.2 needs to be continuously monitored, ≤ 0.8 is determined to be normal metabolism; the physical sign acquisition unit includes a wearable device and an image recognition system, which acquires pig body temperature, activity amount and feeding behavior data;

[0108] The purine metabolism analysis unit evaluates the individual purine metabolism efficiency and uric acid level through blood and urine detection devices;

[0109] The abnormality early warning unit establishes a health risk prediction model and generates a graded early warning signal when the detection value deviates from the normal range;

[0110] The working process of the intelligent decision module includes:

[0111] The multi-objective optimization function is:

[0112] ;

[0113] wherein, is the comprehensive index, ranging from 0 to 1.5, > 1.2 is optimal, is the growth rate ratio, = 0.8 kg / d is the reference, is the health score, ranging from 0 to 1, > 0.7 is up to standard, is the environmental load, ranging from 0 to 1, <0.3 is up to standard, is the cost efficiency ratio, = 15 yuan / kg is the standard;

[0114] The multi-source data fusion unit integrates environmental data, feed data, health data and recycling data to construct a multi-dimensional feature vector;

[0115] The weight calculation unit uses the analytic hierarchy process to determine the weight coefficients of each influencing factor and generates a comprehensive evaluation score;

[0116] The breeding optimization scheme includes environmental parameter adjustment suggestions, feed formula optimization schemes and health management measures;

[0117] The working process of the traceability management module is:

[0118] ​The identification recognition unit adopts ear tags and subcutaneous chips to record the individual identity information and growth cycle data of pigs;

[0119] The blockchain storage unit stores the breeding environment parameters, feed feeding records, health monitoring data, and organic fertilizer usage on the chain;

[0120] The visual display unit generates quality certificates containing purine content detection reports, breeding environment assessments, and organic certification information;

[0121] It also includes:

[0122] The water purification module: through the multi-layer filtration unit to process the breeding wastewater, use the plant absorption unit to remove residual nutrients, and output the recycled water through the ultraviolet disinfection unit;

[0123] The energy recovery module: through the biogas collection system to recover the biogas produced in the fermentation process, and use the combined heat and power device to convert it into heat and electricity for system use, the energy conversion efficiency model is:

[0124] ;

[0125] Where, is the efficiency ratio, =0.8 design benchmark, is the energy production ratio, =20m³ / d design value, when <0.9, maintenance warning is triggered;

[0126] It also includes:

[0127] The environmental intelligent control subsystem includes a distributed temperature and humidity sensor array, an ammonia concentration detector, and an environmental regulation actuator, which is used to monitor and automatically adjust the environmental parameters of the pig house in real time;

[0128] The precise nutrition supply subsystem integrates a growth stage recognition unit, a purine metabolism characteristic database, and an automatic batching device, which is used to prepare low-purine feed according to the needs of different growth stages;

[0129] The waste recycling processing subsystem is equipped with a solid-liquid separation device, an aerobic fermentation tank, and an anaerobic digestion tank, which is used to convert breeding waste into organic fertilizer;

[0130] The organic fertilizer precise application subsystem includes a component detector, a proportioning regulator, and a variable rate fertilizer applicator, which is used to apply the treated organic fertilizer precisely to the matching planting area;

[0131] The health monitoring and early warning subsystem integrates wearable devices, image recognition systems, and biosensors, which is used to monitor the health status of the pig population and the purine metabolism level in real time;

[0132] An intelligent decision support subsystem with a multi-source data fusion unit and an optimization algorithm engine for generating comprehensive breeding optimization schemes;

[0133] A product traceability certification subsystem containing a blockchain storage module and a quality detection device for recording full-process data and generating quality certification reports.

[0134] The operation steps of the low-purine ecological pig circular breeding system are as follows:

[0135] Step one, environmental regulation stage

[0136] The system first collects real-time environmental parameter data such as temperature, humidity, and ammonia concentration through a sensor network distributed in various areas of the pig house, compares and analyzes the collected data with the preset optimal breeding environment standard, and automatically starts the adjustment device of the ventilation system and temperature control equipment when the environmental parameters deviate from the standard range, maintaining a stable and suitable breeding environment and reducing the impact of environmental stress on purine metabolism in pigs.

[0137] Step two, feed preparation stage

[0138] The system selects high-quality low-purine feed raw materials from the raw material database according to the nutritional needs of pigs at different growth stages, and prepares special feed that meets purine control requirements through metering and automatic mixing equipment. During feeding, the system realizes differentiated feeding through individual identification technology to ensure that each pig receives the right amount of daily ration with controllable purine content.

[0139] Step three, health monitoring stage

[0140] The system uses wearable devices and image recognition technology to continuously monitor the physiological indicators and behavioral characteristics of pigs, assess individual health status by analyzing data such as food intake and activity frequency, and pay special attention to purine metabolism-related indicators. When abnormal conditions are found, timely warnings are given, and feeding management measures are automatically adjusted.

[0141] Step four, waste treatment stage

[0142] Excreta produced during breeding are first treated by a solid-liquid separation device, with the solid part entering an aerobic fermentation system and the liquid part entering an anaerobic digestion tank. The system efficiently converts waste into stable organic fertilizer by controlling parameters such as fermentation temperature, humidity, and time.

[0143] Step five, resource recycling stage

[0144] After the treated organic fertilizer is detected for its composition, the system calculates the optimal fertilization scheme based on the soil conditions and crop requirements of the supporting planting area, and uses intelligent fertilization equipment to achieve precise field application, completing the ecological cycle of breeding-planting.

[0145] Step six, quality control stage

[0146] The system records the whole process data from environmental regulation, feed feeding to health monitoring through blockchain technology, generates product traceability report containing purine content detection results, and provides real and reliable product quality information for consumers.

[0147] Step seven, intelligent optimization phase

[0148] The system comprehensively analyzes environmental data, feed data, health data and resource utilization data, continuously optimizes the operation parameters of each link through machine learning algorithm, and continuously improves the breeding efficiency and environmental friendliness of the system.

[0149] It should be noted that in this paper, relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between the entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment. Without more limitations, the element defined by the statement "including a" does not exclude the existence of other identical elements in the process, method, article or equipment including the element.

[0150] Although the embodiments of the present application have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A low purine ecological pig circular breeding system, characterized in that: The application relates to a pig breeding system based on low-purine feed and organic fertilizer recycling. The system comprises the following modules: a breeding environment regulation module: real-time monitoring of pig house environmental parameters through a distributed sensor network, generation of regulation instructions using intelligent analysis algorithms, and execution of environmental optimization through a variable frequency ventilation system; a low-purine feed management module: integration of a growth stage recognition unit and a nutrient requirement database, generation of a feed formula meeting the purine threshold through a formula optimization engine, and realization of differentiated feeding using a precise metering feeding device; a manure treatment module: equipped with a solid-liquid separation device and a biological fermentation system, converting breeding waste into standardized organic fertilizer raw materials; a recycling module: analysis of organic fertilizer nutrients through a rapid component detector, generation of a matching scheme in combination with a planting demand model, and realization of precise field application using an intelligent fertilization device; a health monitoring module: integration of wearable sensing devices and image recognition systems, real-time collection of pig group physiological data, evaluation of purine levels through a metabolic analysis model, and generation of early warning signals; an intelligent decision-making module: construction of a multi-source data fusion platform, generation of a comprehensive scheme including environmental regulation, feed optimization, and health management using a weighted evaluation algorithm; 2. The low purine eco-pig circular breeding system according to claim 1, characterized in that: a traceability management module: recording of breeding process data through blockchain technology, and generation of a verifiable product traceability report in combination with quality detection results. The breeding environment regulation module comprises: ； wherein, is the normalized environmental control coefficient, threshold range 0-1, is the real-time temperature monitoring value, unit ℃, is the optimum temperature, is the temperature normalization reference, is the real-time humidity monitoring value, unit ℃, is the optimum humidity, is the humidity normalization reference, is the ammonia concentration, unit ppm, is the safety threshold, is the concentration normalization reference, is the weight distribution coefficient, =0.4, =0.3, =0.3, when >0.6 triggers strong control, 0.3 ≤0.6 triggers weak control, ≤0.3 remains in monitoring state; an environmental parameter regulation algorithm: an environmental parameter monitoring unit equipped with a distributed temperature and humidity sensor network, real-time collection of temperature and humidity data in different areas of the pig house; an air quality analysis unit using an electrochemical sensor array to detect ammonia and hydrogen sulfide concentrations and calculate an air quality index; an environmental optimization decision unit generating ventilation, humidification, and cooling instructions based on a pre-set environmental comfort model and in combination with real-time monitoring data; 3. The low purine eco-pig circular breeding system according to claim 1, characterized in that: an intelligent ventilation system including a variable frequency fan unit and adjustable ventilation windows, dynamically adjusting ventilation volume and air flow organization according to the instructions. The working process of the low-purine feed management module comprises: a nutrient requirement analysis unit calculating the daily purine intake upper limit according to the growth stage, body weight, and health status of different pig groups; a formula optimization unit screening low-purine raw material combinations based on a raw material database, ensuring that the protein content meets the requirements while the purine level is below the threshold; 4. The low purine eco-pig circular breeding system according to claim 1, characterized in that: an automatic feeding system using a precise metering device to prepare feed according to the optimized formula and realizing individual differentiated feeding through RFID identification technology. The working process of the manure treatment module is as follows: a solid-liquid separation unit using a spiral extrusion separator to separate manure into solid and liquid parts; a biological fermentation unit including an aerobic fermentation tank and an anaerobic digestion tank, respectively processing the solid and liquid parts, and reducing the content of harmful substances through microbial degradation; 5. The low purine eco-pig circular breeding system according to claim 1, characterized in that: a conveying pipeline equipped with a component monitoring probe, real-time detecting the moisture content, pH value, and nutrient content of the organic fertilizer raw materials. The working process of the recycling module comprises: a component detection unit using near-infrared spectroscopy technology to rapidly analyze the nitrogen, phosphorus, and potassium contents and the organic matter proportion of the organic fertilizer raw materials; an intelligent matching unit calculating the optimal fertilization formula and dosage according to the crop requirements and soil detection results in the planting area; 6. The low purine eco-pig circular breeding system according to claim 1, characterized in that: an automatic fertilization system including a variable rate fertilizer applicator and a drip irrigation device, realizing precise application and nutrient balanced supply of the organic fertilizer. The working process of the health monitoring module is as follows: Purine metabolism evaluation model: ； wherein, is the standardized purine metabolism index, threshold range 0-2, is the urine uric acid concentration in mg / dL, is the baseline value, is the blood uric acid content in mg / dL, is the baseline value, is the individual body weight in kg, is the body weight normalized baseline, = 0.6, = 0.4 is the metabolic contribution coefficient, + = 1, > 1.2 is determined to be a metabolic abnormality, 0.8 ≤ 1.2 requires continuous monitoring, ≤ 0.8 is determined to be a normal metabolism; The physical data acquisition unit includes a wearable device and an image recognition system to collect data on pig body temperature, activity level, and feeding behavior; The purine metabolism analysis unit assesses the individual's purine metabolism efficiency and uric acid level through blood and urine testing devices; The abnormality early warning unit establishes a health risk prediction model and generates a graded warning signal when the detected value deviates from the normal range.

7. The low purine eco-pig circular breeding system according to claim 1, characterized in that: The working process of the intelligent decision-making module includes: The multi-source data fusion unit integrates environmental data, feed data, health data, and recycling data to construct a multi-dimensional feature vector; The weight calculation unit uses the analytic hierarchy process to determine the weight coefficients of each influencing factor and generates a comprehensive evaluation score; The breeding optimization scheme includes environmental parameter adjustment recommendations, feed formula optimization schemes, and health management measures.

8. The low purine eco-pig circular breeding system according to claim 1, characterized in that: The working process of the traceability management module is as follows: The identification recognition unit uses ear tags and subcutaneous chips to record pig individual identity information and growth cycle data; The blockchain storage unit stores breeding environmental parameters, feed feeding records, health monitoring data, and organic fertilizer usage on the chain; The visualization display unit generates a quality certificate containing purine content detection reports, breeding environment evaluation, and organic certification information.

9. The low purine eco-pig circular breeding system according to claim 1, characterized in that: It also includes: Water purification module: The multi-layer filtration unit processes breeding wastewater, the plant absorption unit removes residual nutrients, and the ultraviolet disinfection unit outputs recycled water; Energy recovery module: The biogas collection system recovers biogas generated during fermentation, and the combined heat and power device converts it into heat and electricity for system use.

10. The low purine eco-pig circular breeding system according to any one of claims 1-9, characterized in that: It also includes: Environmental intelligent control subsystem, including distributed temperature and humidity sensor array, ammonia concentration detector and environmental regulation actuator, for real-time monitoring and automatic adjustment of pig house environmental parameters; Precise nutrition supply subsystem, integrated with growth stage recognition unit, purine metabolism feature database and automatic batching device, for preparing low purine feed according to different growth stage needs; Waste recycling treatment subsystem, equipped with solid-liquid separation device, aerobic fermentation tank and anaerobic digestion tank, for converting breeding waste into organic fertilizer; Organic fertilizer precise application subsystem, including component detector, proportioning regulator and variable rate fertilizer applicator, for precise application of treated organic fertilizer to supporting planting area; Health monitoring and early warning subsystem, integrated with wearable device, image recognition system and biosensor, for real-time monitoring of pig health status and purine metabolism level; Intelligent decision support subsystem with multi-source data fusion unit and optimization algorithm engine for generating comprehensive breeding optimization scheme; Product traceability certification subsystem, including blockchain storage module and quality detection device, for recording whole process data and generating quality certification report.

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