2565 results about "Livestock" patented technology

The invention relates to the technical field of food safety intelligent tracing, and discloses a livestock and poultry product epidemic disease and tracing information quality tracing system based on artificial intelligence. The system comprises a raw material file construction module, an abnormal active prediction module, a multi-modal information fusion module, a tracing knowledge graph construction module and an intelligent tracing decision module. The system generates a raw material archive by collecting livestock and poultry raw material information, and analyzes production monitoring data in real time by using a time sequence model to actively predict abnormal nodes of epidemic diseases. After the abnormity is recognized, multi-link heterogeneous traceability information is synchronously called and fused, an abnormal event panorama is generated, and then a traceability knowledge graph is dynamically constructed in combination with an external knowledge base. And finally, automatically generating an optimized traceability query path according to the knowledge graph, and driving a precise traceability process. According to the invention, the conversion from passive recording to active early warning is realized, and the accuracy and efficiency of epidemic disease tracing are improved through deep fusion and intelligent reasoning of multi-source information.

The invention relates to an agricultural robot, and discloses an animal husbandry pushing robot autonomous navigation method based on a laser radar, which comprises a microsecond-level multi-sensor time synchronization architecture based on an FPGA (Field Programmable Gate Array); in a navigation layer, seamless switching between the GNSS and the laser SLAM is realized by constructing a virtual fusion observation value by utilizing extended Kalman filtering and a self-adaptive dynamic weight algorithm; in the sensing layer, an RGB-I multi-mode model fused with laser reflectivity and a biological micro-motion detection technology are adopted, and feed and biological obstacles are accurately distinguished; and in the execution layer, flexible self-adaptive material pushing is achieved in combination with material groove edge fitting and force-position hybrid control, and the navigation precision, the operation quality and the safety of the material pushing robot in the all-weather and unstructured pasture environment are effectively improved.

The invention provides an uncertainty analysis method and device for a livestock target detection model. The method comprises the following steps: acquiring an RGB image of a livestock target; constructing an uncertainty analysis model of the livestock target detection model, and calling the uncertainty analysis model to detect the livestock target in the RGB image to obtain the category of the livestock target and a detection frame coordinate; and respectively calculating a cognitive uncertainty index and a random uncertainty index of the livestock target detection model according to the category and the coordinates of the detection frame. The method is used for solving the problems that in the prior art, an uncertainty analysis method is not comprehensive enough, uncertainty result attribution is lacked, and the uncertainty evaluation effect is poor.

The invention discloses a dynamic prediction method for the yield of breeding manure, and relates to the technical field of agricultural information.The method comprises the steps that farm real-time data, manure returning historical data and external auxiliary data are synchronously obtained through multi-source data collection and preprocessing, and feature vectors are formed through cleaning and feature engineering; a dynamic prediction model is constructed based on an LSTM neural network and an attention mechanism, the LSTM captures time sequence dependence through a gating mechanism, and the attention mechanism weights and focuses key features; every set period, calculating a prediction error by utilizing newly acquired data, updating model parameters by adopting an incremental gradient descent method and correcting a prediction result; and engineering deployment is realized through edge calculation, data security transmission and performance monitoring, a complete closed loop from data acquisition, model prediction to result correction is formed, and prospective decision support is provided for resource utilization of planting and breeding feces.

The invention discloses intelligent pasture livestock health monitoring equipment. The equipment comprises a vital sign monitoring mechanism worn on the legs of livestock, a behavior monitoring mechanism worn on the neck of the livestock and an environment monitoring mechanism vertically extending and arranged on the pasture ground; the vital sign monitoring mechanism comprises a vital sign monitoring fixing ring, a vital sign monitoring supporting shell with an upward opening is connected to the vital sign monitoring fixing ring, and a plurality of body temperature monitoring sensors are connected into the vital sign monitoring supporting shell; a pulse monitoring through hole penetrating in the radial direction of the physical sign monitoring fixing ring is formed in the side face of the physical sign monitoring fixing ring, and a pulse monitor is arranged at the pulse monitoring through hole; the behavior monitoring mechanism comprises a conventional monitoring camera, a high-speed monitoring camera and an infrared monitoring camera; the equipment can accurately collect various physiological data of livestock, such as body temperature, heart rate, respiratory rate and the like, as well as behavior data, such as activity amount, ingestion time, rumination times and the like, so that the accuracy and reliability of the data are ensured, and an accurate basis is provided for evaluating the health condition of the livestock.

The invention discloses a method for fertilizing dry land white slurry soil by coupling liquid fermentation cow dung and straw to return to field. The Baijiang soil fertilizing method provided by the invention comprises the following steps of: throwing crop straws and stubbles into the field in a full amount, then sowing liquid fermented cow dung, and turning over and burying soil; the liquid fermented cow dung dirt is a product obtained by anaerobic fermentation of cow dung, urine and colony house flushing sewage. According to the method, the liquid fermented cow dung and the straws are fully crushed and returned to the field to jointly fertilize the Baijiang soil, so that the cultivated land quality of the Baijiang soil can be remarkably improved, the straw decomposition and nutrient release rate can be accelerated, planting and breeding circulation and livestock and poultry manure resource utilization can be promoted, and the method has important significance on guaranteeing the national food safety.

The invention discloses a livestock identity recognition method and system based on an unmanned aerial vehicle, and relates to the technical field of livestock identity recognition, and the method comprises the steps: constructing an identity information database which comprises the electronic ear tag IDs of all target livestock individuals in a pasture, a visible light feature image, an infrared thermal imaging contour template and a historical motion behavior sequence in a cloud server; initialization of an unmanned aerial vehicle system carrying a visible light camera, an infrared thermal imager, an RFID reader and an edge calculation module is completed, and communication connection between the unmanned aerial vehicle system and a ground control station and between the unmanned aerial vehicle system and a cloud server is established; controlling the unmanned aerial vehicle to enter an inspection area, monitoring a ground target through a visible light camera, synchronously acquiring a visible light image, an infrared thermal image and a radio frequency response signal of a target individual when the livestock is detected to enter an effective identification range, and performing timestamp alignment on the three types of data; a first visual feature vector is extracted from the visible light image and a visual confidence score is generated.

The invention relates to the technical field of pollution treatment of livestock and poultry breeding, in particular to a pollutant emission prediction and management system for a livestock and poultry farm, which comprises a data acquisition and storage unit, a data processing unit, a data processing unit and a data processing unit, and is characterized in that the data acquisition and storage unit is used for acquiring multi-source data of the farm in real time; the influence factor calculation unit obtains key influence factors influencing water quality change and malodorous gas based on production data and facility operation data of the farm; the model prediction analysis unit generates a predicted value of pollutant emission by using a dynamic multi-dimensional pollutant emission prediction model, and key influence factors are introduced in the prediction process for correction; and the management decision-making unit judges the early warning level and generates a control instruction according to the early warning level. According to the system, accurate prediction of emission of malodorous gas and water pollutants is realized by constructing a dynamic multi-dimensional pollutant emission prediction model, and meanwhile, the system not only prevents excessive emission of pollutants in advance, but also is deeply integrated with aquaculture production management to guide actual aquaculture operation.

The invention relates to the technical field of video monitoring, in particular to a livestock farm safety management method and system based on video monitoring, and the method comprises the steps: collecting a monitoring video of a livestock farm, and equally dividing each frame of video image into each CTU block; marking pixel points corresponding to the target object in each frame of video image as salient pixel points, and determining the static saliency of each CTU block; obtaining the motion pixel aggregation degree of each coordinate point in each frame of video image; determining the center-of-mass coordinate and the motion displacement of the target object in each frame of video image, and obtaining the dynamic saliency of each CTU block; and combining the static saliency and the dynamic saliency, determining a saliency weight of each CTU block, distributing a code rate for each CTU block, and carrying out coding compression on the video image for livestock farm safety management. Therefore, the monitoring video quality of the livestock farm is improved, and the safety management effect of the livestock farm is enhanced.

The invention discloses an ecological planting method for remarkably improving the amino acid content of citrus, which comprises the following steps: (1) mixing and fermenting pruned citrus branches, weed straws, livestock and poultry manure and indigenous probiotic ferment powder to prepare a basic microbial fertilizer, and adding a calcium magnesium phosphate fertilizer and monopotassium phosphate to prepare a special microbial fertilizer for citrus, applying as a base fertilizer in winter; (2) after citrus pruning, in key phenological periods such as a flower bud period, a young fruit period and a fruit swelling period, an indigenous probiotic enzyme diluent with a specific dilution ratio is used for systematic foliage spraying on a tree body. The indigenous probiotic enzyme contains bacillus amyloliquefaciens, saccharomycetes, active enzymes and a plurality of nutrient elements. The method can significantly increase the total amino acid content of citrus fruits, greatly increase the yield, improve the taste of the fruits, enhance the tree body resistance, reduce the use of chemical pesticides, improve soil, and realize quality improvement, yield increase and green sustainable development of citrus planting.

The invention relates to the technical field of material conveying equipment, in particular to a livestock slaughtering automatic feeding device and a feeding method thereof.The livestock slaughtering automatic feeding device comprises a feeding table, the feeding table is provided with a conveying belt with a cutting gap, side plates and limiting frames are arranged on the two sides of the feeding table, and a cutting knife is arranged between the limiting frames; gravity detection assemblies (including pressure detection tables, detection supporting plates and the like) are symmetrically arranged in the feeding table, limiting assemblies (including clamping frames, driving shafts, auxiliary driving belts and the like) are arranged on the inner sides of the side plates, and driving assemblies (including driving equipment, pressure sensors and the like) electrically connected with the gravity detection assemblies are arranged on the outer sides of the side plates; a flow dividing box with a spray head and a cleaning rod is arranged below the feeding table, cleaning of the conveying belt, intermittent discharging of materials to the conveying belt, triggering and limiting when the materials are conveyed to a detection area, starting of weight detection after a pressure sensor reaches the standard, adjustment of the positions of the materials through a driving assembly to guarantee equal-weight cutting, and resetting of a system after completion are achieved. Accurate slitting is achieved, weight deviation is reduced, and production efficiency and product standardization are improved.

The present invention provides a method and a system for monitoring the mobility levels of individual farm animals and accordingly determining their corresponding mobility score. The mobility score may be indicative of the health and / or welfare status of the animals. The present invention processes a 2D video recording obtained from an imaging device to detect the movement of individual animals through a space. The video recording is segmented over a set of individual frames and in each frame the individual instances of the animal appearing in the vide frame are detected. The detected instances of each animal over a number of frames are grouped together. From each detected instance of an individual animal a set of reference points are extracted. The reference points are associated with location on the animal body. The present invention determines the mobility score of each animal by monitoring the relative position between reference points in each frame and the relative position of each reference point across the set of individual frames associated with an animal.

The invention discloses a livestock and poultry product full-chain traceability and slaughter supervision system based on a block chain, and belongs to the technical field of food safety traceability, and the system comprises a multi-source data fusion collection module, a block chain intelligent evidence storage module, an intelligent contract supervision module and a traceability credibility verification module. The multi-source data fusion acquisition module integrates RFID, IoT and video AI technologies to acquire full-dimensional traceability data and evaluate data quality, and the block chain intelligent evidence storage module adopts an alliance chain and an improved Hash algorithm to realize data credible evidence storage and dynamically adjust consensus weight. The intelligent contract supervision module automatically executes compliance check and generates a supervision adjustment instruction to form closed-loop feedback, the traceability credibility verification module adopts deep learning to perform authenticity verification and calculate a comprehensive risk score, and the four modules realize mutual promotion and superimposed synergy through a deep coupling closed-loop cooperation mechanism. And the efficiency and reliability of food safety supervision are obviously improved.

The invention provides a six-axis inertial data behavior identification universal platform method for cattle, pigs, sheep and other livestock, and is suitable for behavior monitoring and management scenes of various livestock and poultry animals. The method comprises the steps of animal identity and species recognition, corresponding behavior recognition template loading, six-axis data feature extraction, behavior judgment and state recognition, recognition result output, platform interface butt joint and the like. Uniform adaptation and efficient processing of different animal types and sampling strategies (including fixed frequency, intermittent sampling, event triggering and the like) are achieved through a modular structure and a parameterized configuration mode. The platform supports continuous expansion of newly added species and behavior templates, can be deployed on edge equipment or a cloud server, has low power consumption, high compatibility and cross-scene applicability, and is suitable for intelligent management requirements of health monitoring, oestrus recognition, abnormity early warning and the like of livestock such as dairy cattle, beef cattle, live pigs, sheep, goats and the like in a farm.

The invention relates to a nucleic acid aptamer for specifically recognizing tilmicosin as well as screening and application of the nucleic acid aptamer, and belongs to the technical field of food safety detection and biosensing. Aiming at the defects of the existing method for detecting tilmicosin residues in food, the invention provides a high-affinity and high-specificity nucleic acid aptamer obtained by screening based on a graphene oxide index enrichment ligand systematic evolution technology. The aptamer is obtained by multiple rounds of screening from a random single-stranded DNA library through a GO-SELEX technology, and a core sequence Apt-2-1 with the length of 33 nt is finally obtained through sequence analysis and structure optimization. The aptamer shows excellent binding capacity to tilmicosin, the dissociation constant reaches 9.82 nM, and the aptamer has good specificity. The nucleic acid aptamer provided by the invention can be used for constructing a rapid and sensitive tilmicosin residue detection method, and has important application value in monitoring of livestock and poultry products and food safety.

The present invention relates to a modified stem cell and an ex vivo method for preparing defined mature cells from genetic programming of said modified stem cell which can be carried out in absence of certain growth factors, as well as a kit allowing to transform stem cells, and the different uses of the mature cells, for example for in vitro drug screening and toxicology or as cultivated meat. The genetic programming involves a molecular switch between two mutually exclusive programs of stem cell expansion and differentiation. The invention may be used for stem cells or other progenitors cells of any type, from any eukaryotic organism, but finds particular application in pluripotent stem cells from humans and livestock animals.

The invention provides a livestock number identification method and system combining AI vision and multi-target tracking, and the method comprises the steps: collecting a continuous video stream of a livestock activity region, generating a video frame sequence with a timestamp mark, carrying out the dynamic background modeling operation, extracting a contour feature set of a livestock object in each frame image, generating a multi-dimensional motion representation vector, and carrying out the recognition of the number of livestock. The method comprises the following steps: performing adaptive multi-scale feature enhancement on a livestock cluster region, decoupling pixel-level features of the livestock cluster region, outputting a form-motion joint coding sequence of each independent livestock individual, constructing a space-time incidence matrix based on the form-motion joint coding sequence, and extracting topological features of a livestock motion track through a lightweight feature extraction network. And generating a global ID mapping table containing the unique identifier of the individual, carrying out real-time statistics on the number of the livestock based on the global ID mapping table, and carrying out behavior tracing analysis on the individual livestock corresponding to the abnormal movement track to obtain a number statistics result and an abnormal behavior identification result. The precision of livestock quantity statistics can be improved.

The invention discloses a botanical attractant for thrips hawaiiensis in a banana field and application of the botanical attractant. According to the application, alpha-pinene, caryophyllene, DL-limonene, beta-pinene and D-limonene which have a remarkable attracting effect on thrips hawaiiensis are separated and identified from banana flower buds which are host plants of the thrips hawaiiensis, and effective concentrations of the compounds with the attracting effect on the thrips hawaiiensis are screened out; the five compounds are mixed according to a certain volume ratio to prepare the thrips hawaiiensis luring composition. Indoor and outdoor experiments prove that the trapping composition provided by the invention has remarkable trapping activity on thrips hawaiiensis in a banana field. The attractant provided by the invention is derived from plants, is simple to prepare, is environment-friendly, is non-toxic to people and livestock, and has a good popularization and application prospect.

The invention provides a saline-alkali soil multi-source carbon sequestration synergistic wheat yield-increasing and quality-improving fertilization method, and belongs to the technical field of crop cultivation. The fertilizing method comprises the following steps: applying a base fertilizer to wheat, wherein the base fertilizer comprises decomposed livestock and poultry manure and biochar; the base fertilizer contains 4-6t / hm < 2 > of organic carbon, and the organic carbon input ratio of the decomposed livestock and poultry manure to the biochar is (1-3): (1-3). The soil carbon sequestration capacity is improved through the synergistic effect of the multi-source carbon sequestration materials, the wheat yield and the grain zinc content are remarkably improved by combining precise nutrient regulation and control, meanwhile, the content of organic matter in saline-alkali soil is improved, and the method is suitable for wheat cultivation in saline-alkali soil with the pH being 8-9 and the salt content being smaller than or equal to 0.3%.

The invention provides a local livestock and poultry variety identification method based on an SNP marker, and relates to the field of variety identification, and the method comprises the following steps: S1, genotype data acquisition, S2, genotype data quality control, S3, variety identification standard library establishment, and S4, bloodline content evaluation. According to the method, on the basis of a standardized molecular identification analysis process of genomic SNP marker bloodline content evaluation, genotype information of a core SNP site is analyzed, so that whole analysis process processing from original genotyping data to variety identity judgment is realized; the method can provide standardized, convenient and efficient molecular detection technical support for protection and utilization of genetic resources of local livestock and poultry in China, germplasm innovation and industrial development.

The invention relates to a traditional Chinese medicine composition with functions of tonifying qi and nourishing blood for livestock. The traditional Chinese medicine composition comprises the following components in parts by weight: 10-30 parts of astragalus membranaceus, 10-40 parts of spina gleditsiae, 10-20 parts of angelica sinensis, 10-20 parts of codonopsis pilosula, 10-30 parts of uniflower swisscentaury root, 10-30 parts of ligusticum wallichii, 10-20 parts of cowherb seed, 10-20 parts of fruit of liquidambar formosana hance and 1-10 parts of iron sucrose. The traditional Chinese medicine composition is scientific and reasonable in component, free of toxic and side effects and medicine residue, convenient to take and low in cost, has the functions of tonifying qi and nourishing blood, stimulating the menstrual flow and prompting lactation, and is capable of effectively treating diseases of postpartum hypogalactia, breast milk stoppage and the like which are normal in livestock.

The invention discloses a cold-season grassland grazing monitoring method based on time sequence remote sensing. The method comprises the steps that a spectrum change sequence is obtained through continuous remote sensing images, signals are enhanced through multi-time-difference differential calculation, a surface reflectance curve is extracted, and an abnormal point set of a potential grazing event is determined in combination with texture analysis. And tracking the spatial connectivity of the abnormal points, generating continuous trajectory path data by using time sequence filtering, and matching the continuous trajectory path data with frozen soil period signals to obtain a grazing trajectory set. Enabling the track set to correspond to remote sensing image space coordinates, generating a preliminary grazing mode map, extracting livestock moving path features, confirming an effective grazing event, and finally refining the boundary through texture analysis, thereby achieving the precise monitoring of the grazing activity of the cold-season grassland. According to the method, the automatic identification precision and efficiency of the grazing trajectory are remarkably improved, and a scientific basis is provided for grassland ecological monitoring and management.

The invention provides a heat stress activation state threshold regulation and control method and system based on poultry group behavior feedback, and relates to the technical field of intelligent management and control of livestock and poultry breeding environment, and the method comprises the steps: recognizing the number of poultry heads in a heat wheezing state and the total number of the poultry heads based on poultry head images, and obtaining the real-time heat wheezing proportion of poultry groups; based on a distributed environment real-time acquisition network, obtaining an in-cage environment temperature and humidity index; aiming at each region, integrating data pairs synchronized by a time window, fitting a piecewise linear regression relationship of the real-time heat wheezing proportion of the poultry group along with the change of the temperature and humidity index of the environment in the cage, dynamically generating a heat stress grading threshold value of the region based on a characteristic turning point, generating a house-level regulation and control instruction and a region-level regulation and control instruction, and carrying out region-level regulation and control on the region-level regulation and control instruction. The local environment of the corresponding area is adjusted and alarmed, and a heat stress activation state threshold regulation and control result is obtained. The problems that poultry group heat stress is difficult to accurately and dynamically assess and poultry house environment is difficult to finely and hierarchically control in different production scenes are solved.

The invention discloses a configurable low-power-consumption six-axis inertial sensor sampling method suitable for livestock and poultry, and belongs to the technical field of animal behavior recognition and intelligent breeding. According to the method, by setting an intermittent sampling strategy and combining low-frequency period awakening and a short-time high-frequency data sampling window, behavior recognition data collection of the six-axis inertial sensor under the low-power-consumption condition is achieved. Meanwhile, a sampling template mechanism based on a behavior target is introduced, various sampling parameters can be configured according to the growth stage of the animal, the monitoring requirement and the variety difference, and multi-scene switching application such as oestrus recognition, parturient monitoring and night energy-saving guarding is supported. In addition, the system has an edge recognition capability, and can automatically trigger temporary recollection when detecting that the attitude angle is abnormal, so that the integrity of key behavior data is guaranteed. The method has the advantages of low power consumption, accurate recognition, flexible configuration, high adaptability and the like, and is widely applied to behavior monitoring scenes of bred animals such as dairy cows, pigs, sheep, chickens, ducks, geese and the like.

The invention discloses an intelligent livestock and poultry ear tag device based on edge calculation and lightweight reasoning, and the device comprises a dynamic sampling module which collects the motion behavior data of livestock and poultry through a three-axis acceleration sensor based on a low-power-consumption sampling mechanism. The local processing module carries out local real-time processing on the collected data by adopting feature screening and a light-weight behavior recognition algorithm based on a TinyML model, and the low-power-consumption transmission module processes the collected data based on a bitmap compression coding form to carry out internal communication transmission, so that wireless data transmission is carried out by a low-power-consumption transmission mechanism based on AI edge calculation; according to the method, a low-power-consumption sampling mechanism and a lightweight algorithm based on a TinyML model are matched with feature screening, so that the power consumption and the calculation amount can be greatly reduced; an AI edge computing architecture is utilized, only key events and features are uploaded, the wireless transmission frequency is reduced, the communication power consumption is reduced, and local intelligent operation in a network disconnection scene is supported.

The invention discloses a special organic fertilizer for soybeans and a preparation method thereof, and belongs to the technical field of organic fertilizers. The special organic fertilizer for soybeans is prepared from the following raw materials in parts by weight: 8-10 parts of fish protein modified charcoal, 40-50 parts of decomposed soybean meal, 20-25 parts of decomposed livestock and poultry manure, 15-20 parts of humic acid, 10-15 parts of plant ash, 3-5 parts of a seaweed extract and 0.1-0.3 part of ammonium molybdate. According to the organic fertilizer, the soybean meal fermented by the trichoderma reesei and the aspergillus awamori and the fish protein modified biochar are added, the two components are compounded with the cooked livestock and poultry manure, the humic acid, the plant ash, the seaweed extract and the ammonium molybdate to form the organic fertilizer, the nitrogen fixation capacity of the soybeans is effectively improved through the synergistic effect of various substances, and the growth and development of the soybeans are remarkably promoted; the soybean yield and quality are improved. In addition, the whole organic fertilizer preparation process is free of strong acid and strong alkali treatment, the environmental pollution risk is reduced, and the standard of organic agriculture is met.

The invention discloses bacillus subtilis, a method for preparing yellow corn silage feed under a strong alkali condition and a product thereof, and belongs to the technical field of microorganisms. The technical problem to be solved is that the survival rate of the existing bacillus subtilis is lower than 30% under the strong alkali condition of pH 9-11, and the existing bacillus subtilis cannot normally grow and propagate. The preparation of the yellow corn silage feed under a strong alkali condition needs additional pH adjustment, the process is complex and the cost is high; the crude protein content of the existing yellow corn silage feed is only 3-5%, and the requirements of livestock cannot be met. According to the technical scheme, the strong-alkali-resistant bacillus subtilis is provided, the preservation number is CGMCC No.36677, the survival rate of the strain is larger than or equal to 80% under the condition that the pH is 9-11, the straw degradation rate is larger than or equal to 25%, no waste water is generated when the strain is used for preparing the yellow silage feed, the cost is reduced compared with an existing technology, the protein content is increased by 50%-80%, palatability is good, and the method is suitable for large-scale straw resource utilization and feed protein production.

The invention discloses an organic fertilizer and a preparation method thereof, and belongs to the technical field of agricultural waste resource utilization and fertilizer preparation. The preparation method of the organic fertilizer comprises the following steps: mixing the livestock and poultry manure with the straw powder, adding the biological compound enzyme for enzymolysis, and fermenting by using the compound bacteria liquid and the nitrogen-retaining agent to obtain the organic fertilizer. The problems that existing organic fertilizers are low in fermentation efficiency, large in nitrogen loss, poor in nutrient effectiveness and low in raw material utilization rate are solved. Through the integrated agricultural waste treatment technology of enzymolysis pretreatment, compound bacteria synergistic fermentation and adsorption, slow release and nitrogen conservation, agricultural waste resource utilization is achieved, the organic matter content of the prepared organic fertilizer is larger than or equal to 68%, the nitrogen retention rate is larger than or equal to 92%, the total nutrient is larger than or equal to 8.2%, the nutrient effectiveness is high, and the organic fertilizer is suitable for planting of various crops.

The invention relates to the technical field of livestock and poultry breeding environment control, and discloses a meat duck shed energy-saving ventilation system and method based on air purification and reuse, and the method comprises the steps: carrying out the time-sharing collection of the temperature, humidity and ammonia gas, carbon dioxide and dust concentration of each ventilation region in a meat duck shed, and recognizing the abnormal air flow and pollution accumulation points; air is guided in a partitioned mode according to the pollution type and the flow direction, dust-containing air is separated in the mode that gravity settling and primary filtering are combined, wet air is subjected to circulating condensation treatment, and high-concentration ammonia gas flow is subjected to adsorption or chemical neutralization treatment; a multi-stage closed-loop circulation is formed through the opening-degree-variable air valve and the multi-speed circulating fan; in the backflow process, the recycled air and the fresh air are mixed in proportion through an adjustable air mixing pipeline; and the ventilation paths, the filtering units and the air partition conditions are analyzed regularly, and the cleaning period, the flow dividing proportion and the circulating fan operation mode are adjusted. The device has the advantage of improving the purification efficiency.

The invention belongs to the technical field of livestock and poultry breeding waste treatment, and discloses a pig farm waste comprehensive treatment and cyclic utilization system which comprises the steps of obtaining various wastes of a pig farm, collecting multi-dimensional data, matching an optimal working condition mode in combination with three-dimensional situation evaluation, and generating a global collaborative instruction set; performing cross-unit predictive collaboration through a causal-parameter chain, performing waste grading treatment and resource preliminary conversion to obtain a treatment intermediate product and a resource primary product, and generating operation feedback data; performing efficiency-income two-dimensional evaluation, when the efficiency does not reach the standard, calling a historical recovery file to generate an adaptive recovery strategy, and generating an update state report; scheduling operation is executed through resource-load dynamic matching logic, reverse traceability optimization processing parameters are carried out, resource products are obtained, and a circulation benefit report is generated; and fusing the multi-cycle cyclic benefit report and the operation feedback data, generating a three-dimensional optimization suggestion, updating the core rule base, and forming a closed-loop link.