870 results about "Pig farms" patented technology

The invention discloses a pig single-view three-dimensional reconstruction method based on deep learning, and the method is called Magfup. In order to solve the problems that single-view three-dimensional reconstruction viewpoint learning is unstable and training is difficult due to lack of real three-dimensional data, an implicit-explicit combined three-dimensional representation method is adopted, high-dimensional data features subjected to super-resolution optimization are combined, a high-density pig three-dimensional grid can be reconstructed only through a single image, and the problem that training is difficult is solved. And data acquisition cost and equipment requirements are reduced. According to the method, the three-dimensional grid surface is optimized through the Laplacian smoothing method, and the reconstruction quality is improved. According to the invention, the model can learn the general shape and posture characteristics of the pig, predicts the three-dimensional posture, shape and texture information of the specific pig, and more accurately and comprehensively reflects the behavior characteristics of the pig. Therefore, the method can adapt to complex and changeable environments and pig behaviors in a pig farm, and a more comprehensive and accurate data basis is provided for pig behavior analysis.

The invention discloses a pig farm disease risk attribution method and system based on a knowledge graph. The method comprises the following steps: constructing a pig farm biosafety knowledge graph according to a pig industry biosafety application and a pig industry biosafety field knowledge base; secondly, inputting all pig farm events of the pig farm in N days, risks of the pig farm and risk probabilities; factors of pig farm diseases are searched through the pig farm biosafety knowledge map, and the disease text attribution of the pig farm is given according to constraints such as the contribution degree of pig farm problems. The pig farms with medium and high risks are rectified and predicted according to attributed risk items, and the pig farms with low risks or the pig farms without diseases after early warning can be summarized as excellent management experience. Through analysis and reasoning of the atlas, more logical analysis can be provided for pig farm risk attribution tasks, the pig farms are helped to deeply understand characteristics and prevention and control requirements of various diseases, and a scientific basis is provided for formulating targeted prevention and control strategies.

The invention relates to the technical field of data acquisition control, in particular to a breeding environment temperature control system for a pig farm, and the system comprises a temperature acquisition module which collects the temperature data of each monitoring point in the pig farm in real time, and converts the temperature data into a temperature value sequence. According to the method, temperature data of a plurality of monitoring points in a pig farm are collected in real time, a discrete temperature data sequence is converted into basic environment information such as average temperature and temperature difference, and trend and anomaly analysis is carried out on the basis, so that the opportunity and demand of temperature adjustment are determined, the future temperature change trend of the environment is predicted, and a corresponding regulation and control plan is generated; on the basis of prediction, real-time biological feedback information, such as heart rate and body temperature, of pigs is fused, dynamic evaluation is carried out on the comfort level of individual animals, and an environment temperature regulation and control strategy is further optimized by taking the comfort level of the animals as a benchmark, so that the regulation of the environment temperature is more accurately matched with the growth requirements of the pigs, and personalized and intelligent control of the breeding environment is realized.

The present invention relates to the field of intelligent agricultural technology, specifically a remote control system and control method based on a digital twin pig farm, the system includes a behavior monitoring and identification module, a behavior association analysis module, a growth rate analysis module, a digital model construction module, an environmental condition adjustment module, and a pig farm epidemic prevention management module. In the present invention, by real-time monitoring and analyzing the behavior of multiple pigs in a pig farm, combining environmental condition data, analyzing the impact of environmental conditions on pig behavior, achieving targeted environmental adjustment, real-time recording of pig weight and combining environmental data to analyze growth trends, making weight change predictions more accurate, building a digital twin model and simulating the operating status of a pig farm, providing a simulation platform for the adjustment of management measures, enhancing the transparency of pig farm operations and improving the accuracy of decision-making, reducing resource waste and increasing production, optimizing production processes, and achieving cost savings and sustainable development.

The invention discloses a large-scale pig breeding wastewater purification treatment system, and relates to the technical field of wastewater treatment.The large-scale pig breeding wastewater purification treatment system is characterized in that the ion concentration of anaerobic liquid is monitored through a multi-ion sensing array, and a multi-channel feeding system is controlled to synthesize customized struvite compound fertilizer; the AI prediction control unit predicts the optimal medicament dosage and realizes millisecond-level closed-loop regulation; the multi-dimensional synergistic biochemical treatment module comprises an A / O biochemical treatment unit and an electric field enhanced anaerobic ammonia oxidation reactor, the electric field enhanced anaerobic ammonia oxidation reactor applies a direct-current electric field through an electrode pair, and engineering conductive biochar is used as a carrier to accelerate microbial metabolism; the sludge low-temperature pyrolysis self-consistent circulation module is used for pyrolyzing and converting residual sludge into biochar, biofuel and wood vinegar, and the biochar activation treatment unit is used for preparing engineering conductive biochar and forming a substance closed loop through a self-consistent circulation conveying system; and the digital twinning intelligent management and control platform realizes intelligent management and control of the system.

The invention provides a primer probe combination and a kit for detecting porcine diarrhea related viruses, and belongs to the technical field of virus detection. The combination comprises specific primers and fluorescent probes aiming at a porcine epidemic diarrhea virus (PEDV), a porcine group A rotavirus (PoRV-A), a porcine transmissible gastroenteritis virus (TGEV) and a porcine delta coronavirus (PDCoV). The primer probe combination disclosed by the invention can be used for simultaneously detecting and identifying the four viruses mainly causing porcine diarrhea in one PCR reaction, and has the characteristics of high specificity, high sensitivity, simplicity and convenience in operation, rapidness and high efficiency. Therefore, according to the invention, rapid and accurate detection of porcine diarrhea related viruses can be realized, and disease prevention and control and epidemiological investigation of pig farms can be effectively supported.

The invention relates to the technical field of multi-sensor fusion anomaly detection, in particular to a multi-sensor data fusion pig farm anomaly detection system which comprises the steps that data are continuously collected through sensors, a unique space-time anchor point is bound to an RFID tag, and a particle filter algorithm is utilized to predict the motion trail of a pig in different sensor view fields; local model training is carried out at each node according to own data, then local model parameters are uploaded to a central node for fusion through a gradient aggregation strategy, and a global anomaly detection model is generated; dividing a dynamic sensing network in the hog house, and evaluating the confusion degree and the abnormal possibility of data by calculating entropy values of grid units; a behavior fingerprint database is established for each pig, pig behavior data are monitored in real time, and matching degree calculation is carried out on the behavior fingerprint matching degree. And various types of sensors are widely deployed, so that multi-dimensional information of pigs can be comprehensively acquired, and the condition of the pig farm can be comprehensively sensed.

The invention relates to the technical field of intelligent breeding, in particular to a pig farm sand table modeling and synchronizing method based on digital twinning, which comprises the following steps: constructing a basic model of a digital twinning sand table through a three-dimensional modeling technology according to dynamic topological relation data; in the moving process of the twin body, detecting path conflicts on the moving path of the twin body in real time, and after the conflicts are detected, through virtual elastic deformation modeling processing, adjusting the position and posture of the twin body to avoid the path conflicts; when the physical sand table generates an operation instruction and the state is changed, the related information sends a first synchronization instruction to the digital twin platform through the Internet of Things; and updating the state, namely the topological relation, of the corresponding twinborn body in the digital twinborn sand table according to the correction parameters. According to the method, the dynamic association strength between the devices is calculated by using the topological weight algorithm, the generated dynamic topological relation data accurately reflects the actual relation between the devices, and a solid data basis is provided for subsequent modeling and analysis.

The invention discloses a pig farm abortion attribution diagnosis method based on a porcine reproductive and respiratory syndrome risk propagation knowledge graph, and relates to the technical field of artificial intelligence, and the method comprises the steps: constructing a pig farm porcine reproductive and respiratory syndrome attribution knowledge graph, pre-defining a risk propagation mode according to a porcine reproductive and respiratory syndrome risk propagation mechanism, searching a path according with the risk propagation mode through graph mode matching, and carrying out the diagnosis of the abortion attribution of a pig farm. Integrating into a risk sub-graph; performing representation learning on the risk sub-graphs by adopting a graph attention network fused with PRRS risk propagation knowledge, and quantifying the contribution degree of each risk sub-graph to the abortion rate of the pig farm in combination with context representation learning and a time difference attenuation mechanism; and based on the contribution proportion of each risk event in the attention score decomposition risk sub-graph, generating a quantitative attribution result, and outputting a diagnosis result including risk event identification, a risk propagation link and a quantitative attribution contribution degree. Risk attribution of the porcine reproductive and respiratory syndrome in the pig farm is realized, and contribution of specific attribution risk points to the abortion rate of the pig farm is quantified.

The invention discloses an intelligent detection and traceability system and method for pig farm breeding data, relates to the technical field of pig farm monitoring, and aims to solve the technical problems that breeding risks are difficult to estimate and hidden dangers exist in pork quality safety due to the lack of a traceability method and a management system in current pig farm breeding. Comprising a multi-type sensor network, a video monitoring system, a wireless communication network, and data encryption and secure transmission. According to the invention, a traceability system for live pigs from breeding to slaughtering can be established, a convenient traceability query function is provided for consumers through a block chain traceability system and a decision support system, and targeted breeding decision support is provided for farmers. According to the invention, pig farm breeding data can be collected and analyzed comprehensively, accurately and intelligently, and stored and inquired through the block chain traceability platform; and real-time early warning and decision support can be provided for live pig production and breeding of farmers. According to the invention, the modernization and intelligence level of the pig breeding industry can be effectively improved.

The invention belongs to the technical field of molecular biotechnology and molecular markers, and particularly relates to an SNP (Single Nucleotide Polymorphism) site related to pig intramuscular fat content, a related molecular marker and application of the SNP site. The SNP site corresponds to the 151330919bp site of a No.6 chromosome of an international pig reference genome version 11.1, the polymorphism of a base of the site affects the intramuscular fat content of the pig, the related index of a TT genotype is greater than that of a pig individual with TG and GG genotypes, and the related index of the TG genotype is greater than that of a pig individual with GG genotype. According to the invention, a molecular breeding means is utilized to solve the problem of improving the character expression of the intramuscular fat content of the pig, and by optimizing the dominant alleles of the SNP, the frequency of the dominant alleles can be increased generation by generation, the intramuscular fat content of the pig can be improved, the pork quality can be improved, the genetic modification breeding of the pig can be accelerated, and the economic benefit of a pig farm can be improved.

The invention relates to the technical field of management systems, in particular to a pig behavior and pigsty environment integrated management system based on digital twinning, which comprises a digital twinning system, and the digital twinning system comprises an Internet of Things module used for data acquisition and transmission between a physical pig farm and a digital twinning model; the environmental parameter acquisition module is used for acquiring environmental data in the pig farm in real time by installing various sensors in the pig farm; the animal behavior data acquisition module is used for monitoring and identifying pig behaviors, including motion behaviors, feeding behaviors, land laying behaviors and climbing attack behaviors. In the invention, aiming at the problem of weak capabilities of capturing, analyzing and predicting pig behaviors in the prior art, the animal behavior data acquisition module is used for comprehensively monitoring the behaviors such as movement, feeding, land laying, climbing attack and the like of the pigs, so that the dynamic change and interaction relationship between the environment and the behaviors can be effectively captured, and the accuracy of a prediction result is improved.

The invention discloses a pig farm manure processing method and system based on image analysis, and belongs to the field of image analysis. Acquired environment change data in a pig farm is imported into an environment change abnormity analysis strategy for environment change abnormity analysis; the method comprises the following steps: acquiring a pig farm manure change abnormity analysis result and an environment change abnormity analysis result to predict the manure deterioration time, analyzing the abnormal change in a storage process through historical change data in the manure storage process, and accurately extracting and analyzing characteristics influencing the manure deterioration time. Therefore, the deterioration time of the feces is accurately estimated, the ability of mastering the deterioration time of the feces is improved, and efficient treatment of the feces is facilitated.

The invention discloses a pig farm environment control method and system, and mainly relates to the technical field of environment control. Comprising the steps that fans are arranged in a target pig farm in advance, and a fan set and an effective coverage area set are determined; traversing the effective coverage area set to arrange gas sensors, and extracting monitoring data of the arranged gas sensor set according to a preset monitoring frequency after the feeding nodes to obtain a harmful gas concentration monitoring sequence set; performing time sequence trend analysis on the harmful gas concentration monitoring sequence set to obtain a first control influence factor set; determining a second control influence factor set; determining a risk area set; and acquiring a ventilation circulation path of the target pig farm, and regulating and controlling the fan set in combination with the risk area set and the area concentration prediction result set. The pig farm environment control method has the beneficial effects that the technical problems of lack of dynamic analysis and low control reliability of pig farm environment control in the prior art are solved, and the technical effect of improving the control reliability is achieved.

The utility model discloses a feces collection and discharge device for a pig farm in a Poyang Lake region. The feces collection and discharge device for the pig farm in the Poyang Lake region comprises a film covering collection system and a pollutant treatment efficient degradation system. The covering film collecting system comprises a primary settling zone, an intermediate settling zone and an ultimate settling zone which are arranged in sequence. The efficient degradation system for pollutant treatment adopts an S-shaped treatment mode and specifically comprises three parts, namely a head section, a middle section and a tail section. According to the excrement collecting and discharging device for the pig farm in the Poyang Lake area, an anaerobic method is adopted for removing COD and SS, the primary removal effect is determined by the anaerobic depth and time, the sediment amount in the primary sedimentation area is the largest, solid sediment can be discharged in time by arranging the sediment discharging port, the effective excrement treatment capacity of the device is guaranteed, and the economic benefit is improved. Pollutants can be promoted to be degraded layer by layer, and finally the emission standard is achieved.

The utility model provides a pig farm reclaimed water recycling system with multiple application scenes, which comprises a pretreatment device, a reverse osmosis device, a first recycling device, a disinfection device and a second recycling device which are connected in sequence, the pretreatment device comprises a full-automatic multi-medium filter and an ultrafilter which are connected in sequence; the reverse osmosis device comprises a scale inhibitor, a precision filter and a reverse osmosis membrane assembly which are connected in sequence, and the ultrafilter is connected with the scale inhibitor; the first recycling device comprises a first water storage tank, and the first water storage tank is connected with the reverse osmosis membrane assembly. The utility model overcomes the key core problem of hindering the reuse of reclaimed water in a large-scale farm, provides a feasible technical scheme for the industry, and not only can relieve the water pressure of the pig farm, but also can save clean water resources.

The invention discloses a method for predicting and judging the diarrhea risk grade of suckling piglets, and belongs to the technical field of piglet epidemic disease prevention and control. Aiming at the problems that traditional piglet diarrhea prediction depends on manual observation, multi-dimensional data relevance is insufficient, early warning lags and the like, a multi-parameter monitoring device is arranged in a piglet breeding environment to collect environment data in real time, and an excretion behavior detection module is used for triggering an excrement image collection device to obtain a high-quality image; and inputting multi-source data into a random forest model for risk level prediction by combining regular weight measurement and blood detection in a specific time period after environment adjustment. The system dynamically adjusts pig environment parameters according to a prediction result, after spraying, heating compensation is started to maintain humidity and control ammonia concentration, and closed-loop feedback regulation is formed. According to the method, through multi-modal data fusion and model iterative optimization, early-stage accurate early warning of diarrhea risks is realized, the method is suitable for intelligent management of a large-scale pig farm, the diarrhea occurrence rate can be effectively reduced, and the breeding benefits are improved.

The invention provides paracoccus pantotrophus, a deodorant composed of the paracoccus pantotrophus and application of the deodorant, and belongs to the technical field of microbial agents. According to the invention, a paracoccus pantotrophus strain is screened from biogas residues of a pig farm, is named as Paracoccus pantotrophus SZZ1 and is preserved in the China Center for Type Culture Collection, the preservation address is Wuhan University, Wuhan, China, and the biological preservation number is CCTCC M20242509. The SZZ1 strain is used for animal manure fermentation, and results show that the microbial inoculum can effectively reduce odor generated during manure fermentation, and especially has a significant inhibition effect on release of hydrogen sulfide. Therefore, the method not only enriches the types of existing deodorization strains, but also has an excellent removal effect on hydrogen sulfide and a stable and lasting deodorization effect, and is suitable for popularization and application.

The invention discloses a pig farm breeding system based on digital twinning, the system is realized by adopting a front and rear end separation mode and combining Unity to generate WebGL, and the system specifically comprises a user management module, a pig management module, an equipment management module, a video monitoring module, an alarm module, an information large screen module and a pig farm twinning module. The system adopts a front-end and rear-end separated framework, the rear end and the front end can be independently deployed, and maintenance and upgrading can be more flexibly carried out. Based on the digital twinning technology, the management level of the pig farm can be comprehensively improved, and the pig raising industry can be more efficient and sustainable in development.

The utility model discloses a pig farm breeding and breeding vehicle which comprises a frame formed by welding square pipes, the frame is provided with an operation layer, a first storage layer and a second storage layer from top to bottom, a side plate of the operation layer is fixedly provided with a fixing plate through a five-star handle, and the fixing plate is provided with a tail breaking device. And a castrating bracket mounted on the other side plate of the operation layer is arranged in front of the tail cutter. The tail cutting device and the castration support are arranged, tail cutting and castration can be achieved on one device, convenience and rapidness are achieved, various nursing behaviors can be completed at a time, meanwhile, tools and operation space used for immune behaviors are provided, rework is avoided, the manual workload is reduced, and artificial counterfeiting is eradicated.

The invention provides a classical swine fever virus subunit vaccine and a preparation method thereof, the classical swine fever virus subunit vaccine is based on an E2 protein gene and a GP67 signal peptide gene of a CSFV 1.1 strain, a recombinant expression vector is constructed through gene cloning, a classical swine fever virus E2 recombinant protein is obtained through expression of an insect baculovirus system, and the classical swine fever virus subunit vaccine is obtained. And the recombinant protein is combined with a colloidal manganese adjuvant to prepare the swine fever virus subunit vaccine. The hog cholera virus E2 recombinant protein is close to natural E2 protein in structural function, high in reduction degree, high in expression quantity and suitable for vaccine production and application; the vaccine can generate specific humoral immunity and relatively strong cellular immunity, and is beneficial to removal of CSFV in an animal body; meanwhile, the vaccine can be distinguished from attenuated vaccine strain immunization or wild strain infection at the nucleic acid level, can be used for preventing and purifying classical swine fever in an intensive pig farm, and has a considerable application prospect.

The invention discloses a pig segmentation and posture detection method, device and equipment, and the method comprises the steps: obtaining pig farm image data, and carrying out the marking of a bounding box, a segmentation mask and a posture key point for each pig instance in each pig farm image data, so as to construct training data; a multi-task network model based on the YOLOv8 framework is constructed, and the network architecture of the multi-task network model comprises a backbone network, a neck feature fusion module, a detection head, a segmentation head and a key nodding head, and the detection head, the segmentation head and the key nodding head are arranged in parallel; inputting the training data into the multi-task network model, and training based on a preset loss function to obtain a trained pig segmentation and posture detection model; and inputting an acquired to-be-detected image into the pig segmentation and posture detection model for reasoning to obtain a segmentation and posture detection result corresponding to each pig. According to the method, the processing efficiency is remarkably improved, and the requirement of a real-time monitoring scene of a large-scale pig farm for low delay can be met.

The invention provides a novel Klebsiella aerogenes strain, which is Klebsiella aerogenes N1, and the preservation number of the novel Klebsiella aerogenes strain is CGMCC (China General Microbiological Culture Collection Center) NO.30271. The invention further provides a preparation method of the novel Klebsiella aerogenes strain. The invention also provides a microbial inoculum prepared from the klebsiella aerogenes N1, and the microbial inoculum is a bacterial liquid cultured to a logarithmic phase. In addition, the invention also provides an application of the klebsiella aerogenes N1 in degradation of VOCs in livestock and poultry farms. The klebsiella aerogenes N1 provided by the invention is a new strain capable of degrading VOCs in livestock and poultry farms. According to the present invention, the bacterial liquid prepared from the klebsiella aerogenes N1 is added into the blistered manure to treat, such that the VOCs in the pig farm can be effectively degraded, the degradation rate is up to 85.37%, and the bacterial liquid has different degrees of degradation effects on odor, ammonia gas and hydrogen sulfide in the livestock and poultry farm so as to provide good application prospects.

The invention relates to the field of microorganisms, and discloses a P.megaterium and an application thereof in pig farm manure treatment, the P.megaterium is preserved in China Center for Type Culture Collection on December 13, 2022, the preservation address is Wuhan, China, the classification name of the P.megaterium is Pristia megaterium 3144, and the preservation number is CCTCC NO: M20221962. The content of pollutants such as total nitrogen, chemical oxygen demand and the like in pig farm feces is reduced by secreting various degrading enzymes such as protease, lipase and the like through the provided Priestia megaterium 3144 strain, and meanwhile, fecal coliforms and roundworm eggs are killed by the strain through metabolism heat production and antibacterial substance secretion.

The invention relates to the technical field of breeding facilities, in particular to a dynamic feeding device capable of improving pig feed utilization rate, which comprises a feeding table, fences are mounted on the front side, the left side and the right side of the feeding table, an opening allowing only one pig to pass through is formed in the rear side of each fence, and a trough monitoring wagon balance and a weight monitoring wagon balance are mounted on the upper surface of the feeding table. A feeding trough is placed above the feeding trough monitoring wagon balance, an automatic feed supply device, a camera, a driving device and an individual recognition device are installed around the upper portion of the feeding trough, and the feeding trough monitoring wagon balance, the body weight monitoring wagon balance, the camera and the individual recognition device input data signals to the control center in a one-way mode. The control center inputs control signals to the automatic feed supply device and the driving device in a one-way mode. By improving the feed utilization rate and the pig growth efficiency, the production cost is directly reduced, and the overall economic benefit of a pig farm is improved.

The invention relates to the technical field of intelligent breeding and logistics optimization control, and solves the technical problems of high energy consumption, unstable efficiency, unbalanced distribution, lack of an intelligent scheduling mechanism and the like in feed conveying of a multi-storey pig farm. The method comprises the following steps: acquiring static parameters (physical characteristics of feed, physical attributes of a conveying system and a pig house structure) and dynamic parameters (real-time feeding requirements, equipment and material states and external environment factors); establishing a multi-objective optimization model of a collaborative optimization energy consumption model E (x), a time model T (x) and a conveying balance degree model U (x); solving by adopting a genetic algorithm with a special design crossover and mutation operator to obtain an optimal scheduling scheme; in the execution process, a closed-loop self-learning calibration mechanism is started, actual power is measured through a current sensor, and when the deviation between predicted energy consumption and actual energy consumption exceeds a preset threshold value, efficiency parameters in the energy consumption model are reversely corrected through a gradient descent method; the weight coefficients of the three models are dynamically adjusted according to the real-time electricity price and the inventory state. The system adopts a three-layer architecture of a perception and data acquisition layer, a decision and control core layer and an execution layer. According to the method, multi-target collaborative optimization and intelligent adaptive scheduling are realized, the total energy consumption is effectively reduced, the transmission time is shortened, the distribution balance degree is improved, and the energy consumption prediction accuracy is remarkably improved.

The hog house flushing device comprises a supporting rod, a sliding groove, a sliding block, a moving mechanism, a limiting mechanism, an adjusting mechanism, a spray head and a driving mechanism, the sliding groove is formed in the lower end of the supporting rod, the sliding block is inserted into the sliding groove, the moving mechanism is installed in the middle of the inner side of the sliding groove, and the spray head is arranged on the sliding groove. Limiting mechanisms are installed on the front side and the rear side in the sliding groove, an adjusting mechanism used for controlling longitudinal angle adjustment of the nozzle is installed at the lower end of the sliding block, a driving mechanism used for controlling transverse angle adjustment of the nozzle is installed in the middle of the lower end of the sliding block, and the nozzle is installed at the lower end of the adjusting mechanism. The animal house cleaning device has the advantages that an operator can flexibly adjust the spraying angle of the spray head according to the specific structure and shape in an animal house, and therefore the more comprehensive and deep cleaning effect is achieved, and the cleaning process is more efficient.

The invention discloses a method for identifying an early performance behavior of a pig epidemic disease based on a three-axis attitude angle, and belongs to the technical field of intelligent breeding and livestock and poultry health monitoring. According to the method, a wearable device integrated with a gyroscope is worn on the head of a pig, and three-axis attitude angle signals such as a yaw angle (Yaw), a pitch angle (Pitch) and a roll angle (Roll) of the pig are collected in real time. And carrying out sliding processing on the continuous attitude angle data according to a set time window, extracting behavior characteristic parameters, and carrying out comprehensive identification on behavior performance in the early stage of the suspected epidemic disease in combination with behavior chain pattern identification, individual-group comparative analysis, continuous trend monitoring and an abnormal scoring mechanism. The method does not depend on other sensors such as an accelerometer, an image, a sound or a body temperature sensor, only takes the attitude angle as a unique input signal source, has the advantages of low power consumption, light model weight, convenient deployment and suitability for edge recognition, can quickly find out an individual with abnormal behavior in the early stage of epidemic diseases, realizes intelligent early warning earlier than definite diagnosis, and has a good application prospect. The method is suitable for epidemic disease prevention and control and fine management of various large-scale pig farms.

The invention discloses a breeding data acquisition device and method for a smart pig farm, belongs to the technical field of pig farms, and solves the problem that the sensible temperature of pigs cannot be accurately acquired through a single infrared camera in an existing smart pig farm. Stable pig ear temperature data can be obtained through the ear temperature collector, the accuracy of the collected data is improved, multiple pigs evenly distributed in a pig farm are marked through a marking method to serve as marked pigs, the number of used temperature collecting assemblies is reduced, the cost is reduced, and the pig ear temperature collecting device is suitable for being popularized and applied. And the pig body temperature data of all pigs in the marked pig area are corrected through the accurate ear temperature data of each marked pig, and all pig body temperature data, humidity data and wind speed data in the corresponding position area are obtained by using the track inspection robot, so that the sensible temperature of the pigs in each area in the whole pig farm can be accurately obtained.

The invention belongs to the technical field of biology, and particularly relates to a porcine epidemic diarrhea virus broad-spectrum neutralizing antibody and application thereof. A porcine epidemic diarrhea virus broad-spectrum neutralizing antibody 6G2 is screened, the virus neutralizing activity of the antibody is evaluated through a cell model, and it is found that the antibody can effectively block infection of G1a, G1b, G2a, G2b, G2c and S-INDEL (porcine epidemic diarrhea virus) gene subtype strains with high epidemic rate on cells. Further, animal infection experiments of pigs prove that the neutralizing antibody provided by the invention has good prevention and treatment effects on the porcine epidemic diarrhea virus, and has important significance on improving the capability of preventing and controlling porcine epidemic diarrhea in a pig farm.