6579 results about "Livestock" patented technology

The invention discloses a livestock health state real-time monitoring method and system based on the Internet of Things, and the method comprises the steps: collecting livestock biological data and environment parameters through a biological chip ear tag and an environment sensor, and carrying out the preprocessing, and obtaining a standardized multi-dimensional livestock data flow; in combination with image data provided by a video monitoring system, identifying livestock individuals and analyzing behavior features, and fusing biological data and visual data to generate livestock individualized feature vectors; constructing an individualized health baseline model in combination with historical health records; comparing the deviation degree between the current state and the health baseline through an anomaly detection algorithm, and identifying a potential health problem; early warning is performed according to the abnormity severity level, intervention suggestions are generated, early warning information is pushed to the breeding personnel through multiple channels, and response measures and results are recorded to form closed-loop management. According to the invention, accurate real-time monitoring of the health state of the livestock is realized, the accuracy and timeliness of anomaly detection are improved, the breeding risk is reduced, and the production efficiency of animal husbandry is improved.

The invention provides an agricultural source solid waste pollution reduction and carbon reduction synergistic effect calculation method and system. According to the agricultural solid waste pollution reduction and carbon reduction synergistic effect calculation method, a livestock and poultry manure and straw mixture serves as a treatment object, an environmental parameter set of microbial metabolism intensity is obtained, and then a microbial agent feeding acceleration rate and a flora activity attenuation curve are dynamically matched. In the aerobic fermentation stage, through linkage of pile turning operation and a microbial inoculum adding strategy, activity balance of surface and deep flora is maintained, and a microbial inoculum adding time window is corrected in combination with historical data. And establishing a quantitative model with a carbon-nitrogen ratio imbalance threshold value as a constraint, iteratively optimizing a nonlinear association relationship between the inoculant feeding acceleration rate and the pile turning operation frequency, and outputting a full-period synergistic effect evaluation result. According to the technical scheme, the pollution reduction and carbon reduction synergistic effect of agricultural source solid waste treatment is improved, and the dual purposes of resource utilization and environmental protection are achieved.

The invention discloses a livestock and poultry manure fermentation monitoring method based on digital twinning, and relates to the technical field of livestock and poultry manure treatment. By constructing a high-precision digital twinborn model, fermentation field sensing data are synchronized in real time, the fermentation state is simulated, and the development trend is predicted; setting an intelligent control strategy fusing data relevance and control priority, and dynamically identifying and avoiding rule conflicts; on this basis, control actions such as pile turning, spraying and ventilation are automatically executed, feedback data are recorded, and twin model parameters are continuously optimized based on feedback results; according to the method, intelligent regulation and control and model self-adaptive updating of the fermentation process are realized, and the stability, the energy utilization efficiency and the prediction accuracy of the system are remarkably improved.

The invention discloses a poultry health condition detection method, system and device and a storage medium, and relates to the technical field of poultry health condition detection.The poultry health condition detection method comprises the steps that poultry audio data are collected and preprocessed; based on the time-frequency characteristics of the audio data, constructing an MAE model; and performing pre-training and fine tuning on the MAE model, and evaluating the pre-trained MAE model. Based on a sound spectrum analysis technology, pre-emphasis filtering and Mel-spectrum conversion are combined, the key feature extraction capacity of poultry sound is enhanced, and the method adapts to the complex environment of a livestock farm. An MAE model is adopted, time-frequency characteristics are learned through self-supervised pre-training and a Transform structure, automatic audio acquisition and analysis and real-time health state output are realized, and the labor cost is reduced. The attention visualization technology is introduced, key frequency bands are identified in an auxiliary mode, the model interpretability is enhanced, and the whole scheme has the advantages of automation, high precision and high robustness.

The invention discloses a livestock intestinal parasitic disease diagnosis and treatment method based on a visual language large model, which comprises the following steps of: training the visual language large model by utilizing a parasite image-text feature alignment data set, so that the large language model has visual capability on parasites; then, constructing a livestock and poultry parasitic disease diagnosis and treatment dialogue data set, and training the LoRA fine-tuning visual language large model by using the diagnosis and treatment dialogue data set to obtain a diagnosis and treatment dialogue model; utilizing the diagnosis and treatment dialogue model to realize livestock parasitic disease diagnosis and treatment. The diagnosis and treatment efficiency of parasitic diseases of livestock and poultry can be improved, the misdiagnosis rate is reduced, and the diagnosis and treatment process is optimized.

The invention relates to the technical field of livestock health management and early warning, and particularly discloses a livestock health management and early warning method and system for animal husbandry based on the Internet of Things, and the method mainly comprises the steps: obtaining the GPS data and monitoring data of livestock, the GPS data comprising a timestamp and a GPS coordinate; calculating an activity distance of the livestock in a specified time period based on the GPS data; judging whether the activity distance belongs to a preset interval or not, and if yes, identifying the livestock from the monitoring data of the specified time period as the livestock to be monitored; and extracting behavior characteristics of the to-be-monitored livestock from the monitoring data of the specified time period, and judging state information of the behavior characteristics. According to the system, the Internet of Things and the data analysis technology are adopted, intelligent monitoring of the livestock activity state is achieved by obtaining the GPS data and the monitoring data of the livestock in real time, the activity and behavior characteristics of the livestock can be effectively monitored, abnormal conditions can be found in time, early warning is made, the burden of manual monitoring is reduced, and the overall efficiency of pasture management is improved.

The invention belongs to the field of agricultural automation and intelligent equipment, and discloses a portable measuring method and device for pork intramuscular fat content. By screening the characteristic wave bands related to the fat content and selecting the corresponding narrow-band LEDs, the accuracy and effectiveness of the multispectral image are improved. And meanwhile, through multi-modal image fusion analysis, in combination with the RGB image, the black-and-white image and the multi-spectral image, the precision of target segmentation and content prediction is improved. And establishing an end-to-end content prediction model by adopting a mode of combining a CNN and an MLP network. Meanwhile, the FCNN network is used for processing the spectral data, the tedious spectral data preprocessing process is omitted, the advantages of the spectral data and the RGB image are fully played, and a new thought and method are provided for the field of spectral modeling. The technical scheme has the advantages of portability, high efficiency, accuracy and the like, provides powerful support for pork nutrition evaluation, and can provide reference for determination of the fat content of other livestock and poultry meat.

The invention provides a livestock body size measuring point extraction method and system, and belongs to the field of computer vision, and the method comprises the steps: obtaining single-side point cloud data of a plurality of cattle, marking the body size key region of the single-side point cloud of each cattle, and obtaining a labeled point cloud data set; the method comprises the following steps: improving existing PointNet + +, introducing deep separable convolution and residual connection operation, adding a parallelized patch attention sensing module and the like to obtain improved PointNet + +, training the improved PointNet + + through a labeled point cloud data set to obtain a cattle body size key area identification and positioning model CatttlePartNet, and identifying and positioning the cattle body size key area according to the training result of the improved PointNet + + and the training result of the improved PointNet + + and the training result of the improved PointNet + + and the training result of the improved PointNet + +. And inputting the unilateral point cloud data of the to-be-measured cattle into the cattle body size key area identification and positioning model CattlePartNet, identifying different body size key areas of the cattle, and performing calculation according to the point set of the body size key areas to obtain body size parameters. According to the method, the key area and the measuring point of the cattle body can be accurately identified, so that accurate body size parameters are obtained, and the measuring precision and stability are improved.

The invention relates to the technical field of livestock and poultry epidemic disease management, and particularly discloses an intelligent livestock and poultry epidemic disease early warning and partitioned prevention and control management system and method, and the method comprises the steps: laying an integrated intelligent sensor network in a livestock and poultry farm, and collecting environment parameters, feeding management data and animal health data in real time through a low-power-consumption Internet of Things technology; transmitting the collected multi-dimensional data to a cloud platform by utilizing an edge computing technology; based on multi-dimensional data, a deep learning and multi-source data fusion analysis technology is adopted, a dynamic disease risk prediction model is constructed, and generalization ability of an adversarial generative network optimization model in a complex environment is introduced; by arranging the integrated intelligent sensor network, environmental parameters, feeding management data and animal health data in the livestock and poultry farm are comprehensively collected in real time, the early monitoring capability of epidemic diseases is remarkably improved, potential epidemic disease risks are found in time, and precious time is won for subsequent prevention and control work.

This invention presents a comprehensive system and method for treating and remineralizing both solid and liquid biowaste derived from animal husbandry operations including aquaculture and livestock. Key components include a settling tank with optional coagulant addition, two anaerobic digestion tanks, a gas collection tank, a sequential batch reactor featuring aeration supply for oxygen addition, a solids collection tank, and a filtration tank for removing and filtering supernatant. The innovation addresses the technical problem of efficient biowaste management by providing a holistic solution that optimizes digestion, waste revalorization through biogas production, and filtration processes to optimize two types of fertilizer production with the option to alternate between a solid fertilizer and a neutralized liquid effluent safe for environmental discharge or both a solid fertilizer and liquid fertilizer effluent. The principal use of this invention lies in its ability to convert biowaste into valuable resources while minimizing environmental impact.

The invention relates to the technical field of odor emission reduction, in particular to an odor emission reduction control system and method for livestock and poultry manure compositing. According to the system and the method, concentration changes of ammonia gas, hydrogen sulfide and volatile organic compounds and temperature and humidity data in a composting environment are accurately obtained through real-time performance and multi-parameter association of gas monitoring in the composting process; the method comprises the following steps of: calculating a diffusion path, a speed and a coverage area of gas in a compost body through finite element analysis, quantifying the distribution characteristics of gas concentration in space, optimizing the wind speed, the wind quantity and the layout of a ventilation system, and improving the ventilation efficiency. Pattern recognition is performed on compost environment gas emission data through the convolutional neural network, the turning frequency and the compost microenvironment are dynamically adjusted in combination with the gas concentration, a gas emission high-value area and a main guide source are accurately positioned, accurate control over compost fermentation odor emission is achieved, and the systematicness and refinement level of compost odor treatment is improved.

The invention discloses a livestock and poultry precise feeding method, system and device based on image recognition, relates to the technical field of livestock and poultry breeding management, and aims to solve the technical problem that an existing livestock and poultry feeding method is low in efficiency. The method comprises the following steps: acquiring image data of a target livestock and poultry pen; based on the image data of the target livestock and poultry circle, obtaining individual information of each livestock and poultry; on the basis of the image data of the target livestock and poultry circle, carrying out feeding tracking on each livestock and poultry individual, judging whether the feeding amount of each livestock and poultry individual meets a feeding amount threshold value or not, and sending alarm information to a feeder on the basis of a judgment result; based on the image data of the target livestock and poultry pen, judging the feed allowance in each feed trough in the target livestock and poultry pen; adding the feed remaining amounts in all the feed troughs, and judging whether the total feed remaining amount is smaller than a remaining amount threshold value or not; if not, no processing is carried out; if yes, the feed adding amount in the feed trough is calculated based on the feed remaining amount in the feed trough.

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 the technical field of organic fertilizers, and discloses an agricultural waste two-stage fermentation bio-organic fertilizer and a preparation method thereof.The bio-organic fertilizer comprises 70%-80% of a mixture of livestock and poultry manure and straw subjected to anaerobic fermentation and aerobic fermentation two-stage treatment, 5%-10% of auxiliary organic matter, 3%-5% of a soil improvement material, 2%-4% of a functional additive and 1%-3% of a microbial preparation. The preparation method comprises the following steps: mixing the livestock and poultry manure and the straw according to a carbon-nitrogen ratio of 30: 1, and performing pretreatment; carrying out anaerobic fermentation for 7 days, and collecting biogas; performing solid-liquid separation to obtain a solid material and biogas slurry; concentrating the biogas slurry to prepare a leaf fertilizer; adding a microbial preparation into the solid material, and carrying out aerobic fermentation for 10-15 days; after fermentation is completed, drying, functional component adding, granulating, screening and packaging are conducted, a finished product is obtained, collaborative integration of anaerobic-aerobic fermentation and full-quantitative utilization of agricultural waste are achieved, and the method has the remarkable advantages of being short in fermentation period, small in nutrient loss, high in functionality and the like.

The invention relates to the technical field of image data processing, in particular to an infrared thermal imaging-based body temperature anomaly detection method, which comprises the following steps of: firstly, performing enhancement processing on an initial image according to different block sizes by using a CLAHE algorithm; then, calculating the direction consistency degree of each pixel point in the enhanced image under each block size, and quantifying the noise confidence weight of each pixel point through the information entropy of the pixel points in the neighbor range; then, calculating an average value of products of noise confidence weights and direction consistency degrees of all pixel points in the same enhanced image to obtain a feasible degree of the size of each block; and finally, according to a weight coefficient of feasible degree conversion, carrying out weighted fusion on gray values of the same pixel position in the enhanced images under all block sizes so as to realize abnormal temperature detection based on the generated target enhanced image. According to the invention, the image enhancement process can be optimized, and the abnormal temperature of the livestock and poultry body surface can be accurately detected.

The invention relates to the technical field of ecological cycle, in particular to an ecological cycle management method based on agricultural and pastoral integration. A data mining technology is adopted, soil sensor data, meteorological data, crop growth data and livestock health data are integrated, and a dynamically coupled nutrient management model is constructed; the nutrient requirements of crops and soil are predicted in real time by using algorithms such as deep learning, and a fertilization strategy is adjusted according to a prediction result, so that the limitation of static management is overcome, and precise fertilization is realized; the real-time monitoring technology is combined, and real-time adjustment is carried out according to the actual environment and crop requirements; nutrient supply is continuously optimized through a feedback mechanism system, the problem of lag in an existing management scheme is avoided, and it is guaranteed that crops obtain a proper amount of nutrients in different growth stages; historical data are deeply analyzed by using a data mining technology, key factors influencing nutrient supply and demand are mined, a scientific fertilization strategy is formulated, the utilization rate of data is remarkably improved, and uncertainty in management decision is reduced.

The invention discloses a compound microbial fertilizer and application thereof in field planting. The survival rate of the paenibacillus mucilaginosus HX-02 disclosed by the invention can be up to 62.8% after 170d under the condition of 38% of nitrogen, phosphorus and potassium. The strain is organically combined with bacillus velezensis RKN1111 and a nitrogen-phosphorus-potassium inorganic fertilizer (N + P2O5 + K2O = 38%), the compound microbial fertilizer is developed, the viable count of effective bacteria is not less than 1.5 billion / g, and the viable count of paenibacillus mucilaginosus is not less than 0.5 billion / g. The compound microbial fertilizer taking the strain as a main functional bacterium is applied to field corn planting, can replace part of chemical fertilizers and increase soil fertility, can reduce the use amount of the chemical fertilizers by 15.56%, and achieves the effects of promoting the growth of field crops and increasing the yield by 10.2%. The paenibacillus mucilaginosus HX-02 is separated from soil, is harmless to human, livestock and environment, and meets the requirements of green plant protection and agricultural sustainable development.

The invention discloses a livestock feed proportioning method based on livestock growth, and relates to the technical field of feed proportioning, and the livestock feed proportioning method comprises the following steps: collecting the body temperature and motion track data and environmental temperature and humidity data of livestock individuals, monitoring the concentration of amino acids in digestive tracts, preprocessing the collected data, and generating a standardized biological data set; analyzing the compensation amount of vitamins and trace elements according to the metabolic fingerprint spectrum, and constructing a multi-objective optimization function in combination with an individual growth curve; solving the multi-objective optimization function through a quantum annealing algorithm, and matching local raw material inventory data of block chain evidence storage to generate an optimization strategy; and executing the optimization strategy and detecting the mixing uniformity, and when the mixing uniformity index exceeds a preset mixing uniformity threshold, starting the compensation device to adjust the optimization strategy. According to the invention, through a cooperation mechanism of dynamic nutritional requirement identification and multi-constraint optimization, the precise regulation and control capability of livestock breeding is significantly improved.

The invention discloses a traditional Chinese medicine residue treatment method and application of a fermented traditional Chinese medicine residue preparation prepared through the traditional Chinese medicine residue treatment method in feed, and belongs to the technical field of waste resource recycling. The lactobacillus plantarum is used for fermenting the traditional Chinese medicine residues, and the prepared fermented traditional Chinese medicine residue preparation improves the content of phenolic substances and the activity of flavonoid substances; finally, the fermented traditional Chinese medicine residue preparation prepared by the treatment method of the traditional Chinese medicine residues is applied to preparation of feed, so that the growth performance of the Rongchang pigs can be improved, the diarrhea rate can be reduced, the immune function can be enhanced, resource utilization and reduction treatment of the traditional Chinese medicine residues can be realized, and a high-quality feed additive can be provided for livestock and poultry breeding; the sustainable development of animal husbandry is promoted.

The invention relates to the technical field of intelligent ventilation adjustment, in particular to an intelligent ventilation adjustment method and system for livestock breeding. The method comprises the following steps: carrying out all-weather gas state monitoring on a livestock and poultry farm through a sensor, and obtaining gas temperature and humidity and ammonia / carbon dioxide concentration time sequence change data; then, gas deposition adsorption effect quantification is carried out, and deposition thermal entropy increase effect data are obtained through deposition thermal entropy increase effect simulation calculation; and then, designing ventilation logic of the livestock and poultry farm based on the deposition heat entropy increase effect data, and generating ventilation logic data of the livestock and poultry farm. And finally, intelligent adjustment firmware design is carried out by utilizing the ventilation logic data of the livestock and poultry farm, the firmware is uploaded to the cloud platform, and intelligent ventilation adjustment is executed. The intelligent ventilation adjusting technology is optimized, so that the intelligent ventilation adjusting technology is more perfect.

The invention relates to the technical field of artificial intelligence, and discloses a method and a system for dynamically predicting the risk of harm of feed mycotoxin to livestock and poultry. The method comprises the following steps: constructing a metabolic digital twin model based on a multi-organ coupling dynamics mechanism, connecting a gastrointestinal tract, a liver and a kidney through blood flow parameters to form a closed loop topology network, establishing a toxin migration rate equation, and verifying bioavailability; collecting feed toxin concentration and livestock and poultry physiological data in real time; after distributing the initial toxin load, iteratively generating target organ dynamic concentration distribution by adopting a Runge-Kutta method; an organ exposure index is calculated based on an organ specific hazard threshold, key organs are positioned, and low / high risk levels and toxin accumulation paths are output. The method solves the problems that a traditional static model is low in efficiency and poor in organ difference adaptability when being used for dynamically predicting the risk of harm to livestock and poultry caused by feed mycotoxin.

The invention discloses a microbial compound feed additive, which is prepared from the following ingredients in parts by weight: 35 to 45 parts of traditional Chinese medicine residues, 25 to 35 parts of soybean meal, 15 to 25 parts of bran, 8 to 12 parts of corn flour, 0.3 to 0.7 part of selenium-enriched yeast, 8 to 12 parts of aspergillus niger spore powder, 10 to 15 parts of bacillus subtilis, 6 to 9 parts of lactobacillus plantarum and 5 to 8 parts of candida utilis. The invention relates to the technical field of feed additives, through the synergistic effect of the aspergillus niger, the bacillus subtilis, the lactobacillus plantarum and the candida utilis, the aspergillus niger can generate various enzymes, and decomposition of raw materials and release of nutritional ingredients are facilitated; the bacillus subtilis can enhance the immunity of livestock and poultry and inhibit the growth of harmful bacteria; lactobacillus plantarum can regulate intestinal microecological balance and promote digestion and absorption; candida utilis is rich in protein and vitamins and provides nutrition for livestock and poultry, the four components cooperate with each other, the function limitation of a single strain is broken through, and the health level and production performance of livestock and poultry are comprehensively improved.

The invention relates to the technical field of livestock and poultry breeding, in particular to an intelligent duck farm environment management optimization method and system, and the method comprises the steps: collecting real-time growth state information of breeding duck growth, employing a sensor to optimally collect environment influence factors concerning a breeding duck farm, and executing association to obtain the growth state information after information synchronization; filtering high-weight environment influence factors based on growth attributes in the growth state information blocks, and setting key environment influence factors of a plurality of growth scenes based on the high-weight environment influence factors; environment influence factor collection of a plurality of growth scenes is executed, a matching environment log of healthy growth of the breeding ducks is configured to execute semantic processing, and the similarity with the matching environment log is collected; and optimizing the breeding duck growth scene based on the similarity to obtain priority optimization entries, and optimizing the environment of the concerned duck farm. According to the method, the optimal value can be judged according to the duck breeding state data of the intelligent duck farm and the mixed breeding state of the breeding ducks, and the utilization efficiency and the output result of the duck farm are effectively improved.

An ice auger for drilling holes in ice includes a cylindrical tubular bit with a cutting edge having a plurality of teeth on the bottom end, and a center shaft extending vertically through the tubular bit. The center shaft has a pointed tip extending below the teeth and a top end extending above the tubular bit for coupling to a rotary powerhead. The tubular bit may include tangential slots for drainage and ice removal. The pointed tip of the center shaft prevents lateral movement of the auger during initial cutting. The ice auger drills holes faster and easier than conventional augers by cutting a circular groove and removing only the perimeter ice. The ice auger is well-suited for ice fishing and livestock watering applications.

The invention discloses a method for preparing an organic fertilizer from livestock and poultry manure, which comprises the following steps: mixing cow dung and plant ash, pig manure and edible mushroom waste, chicken manure and vegetable waste, and duck manure and corn bran or mushroom stick residue, inoculating a corresponding mixed inoculant, fermenting and decomposing by using a trough type aerobic fermentation process, crushing, and screening to obtain the organic fertilizer. The cow dung bio-organic fertilizer, the pig manure bio-organic fertilizer, the chicken manure bio-organic fertilizer and the duck manure bio-organic fertilizer are obtained. According to the invention, rapid decomposition in 28 days in winter and 18 days in summer can be realized, meanwhile, the decomposition degree is remarkably improved, the killing rate of harmful germs reaches 98.93%, the humus content is greater than or equal to 58%, and the product is rich in microbial beneficial bacteria, rich in organic matters, mild in fertilizer efficiency and free of root burning.

The utility model relates to the technical field of harmless treatment, in particular to harmless treatment complete equipment for animals died of illness, which comprises a supporting mechanism, a fragmentation sterilization mechanism, a transmission mechanism and a separation incineration mechanism, fragmentation operation is carried out through fragmentation stirring blades, and the mechanical fragmentation mode is time-saving, labor-saving and high in efficiency. Meanwhile, harmful substances of the animals died of diseases can be fully eliminated, and the safety of harmless treatment of the animals died of diseases is improved. A solid-liquid mixture obtained after fragmentation treatment is injected into a feeding port of the incineration treatment box from a conveying end through a pump machine of the conveying mechanism, solid-liquid separation and drying and low-oxygen combustion treatment are achieved through a solid-liquid separation bin in the incineration treatment box, smoke dust is input into a smoke dust purifier through a smoke dust discharging pipe through a smoke sucker to be treated and discharged, and the environment is protected. According to the separation and incineration mechanism, the material volume is reduced, livestock and poultry molecules are decomposed, the harmless treatment effect is achieved, and the environment-friendly and energy-saving benefits of the equipment are improved.

The invention relates to the field of preparation of amino acid water-soluble fertilizers, and discloses a method for preparing an amino acid-containing water-soluble fertilizer by using slaughtering blood of bred livestock and poultry, which comprises the following steps: collecting the blood of the bred livestock and poultry in a slaughter house through a blood collection container, and adding an anticoagulant to obtain an anticoagulant raw material; the preparation method comprises the following steps: heating and disinfecting an anticoagulant raw material, and then adding bacillus subtilis and monopotassium phosphate to carry out enzymolysis treatment, so as to obtain a feed liquid after enzymolysis; then filtering, complexing treatment, ultraviolet sterilization treatment and sterilization are carried out in sequence; carrying out amino acid detection on the sterilized material liquid subjected to enzymolysis, and adding other nutrients to form an organic liquid fertilizer containing amino acid; and finally, carrying out preservative treatment, packaging and warehousing, and storing in a shade place to complete the preparation process of the amino acid water-soluble fertilizer. The invention solves the problems that the existing amino acid water-soluble fertilizer preparation raw materials are less, the amino acid water-soluble fertilizer preparation process is longer, and the environment is polluted due to the discharge of livestock and poultry slaughtering blood waste.

The invention provides a picea flower monochamus alternatus attractant and a use method thereof.The attractant comprises plant source pheromone and insect pheromone, the chemical components are mixed according to a certain dosage and proportion and then dropwise added to slow-release carriers such as a slow-release bottle, a slow-release bag and a capillary tube, and a picea flower monochamus alternatus lure is prepared; the insecticidal composition can be used for trapping a large number of black longhorn beetles of picea flowers and has the characteristics of remarkable trapping effect and longer lasting period. The attractant is simple to prepare, good in attraction effect and not prone to generating resistance, the formula is a combination of host plant volatile matter and insect pheromone, the attractant is harmless to people and livestock and free of pollution to the environment, a practical pollution-free monitoring and prevention technical means is provided for large-scale trapping and killing of the black longhorn beetles in forests, forest resources are protected, and the economic benefits are increased. The ecological balance is maintained, the application value is very good, and the sustainable development of forestry is promoted.

The invention belongs to the technical field of livestock and poultry breeding environment intelligent control, and particularly relates to a meat duck breeding environment temperature regulation and control method and system integrating quantile regression prediction and reinforcement learning. The method comprises the following steps: collecting multi-dimensional data of a breeding environment and operation state information of environment regulation and control equipment, and performing feature construction to obtain a feature vector; using the multi-source data set to predict in-house temperature based on quantile regression to obtain predicted temperatures under different quantiles; modeling a breeding environment temperature regulation problem into a Markov decision process, and dynamically adjusting fan power and a wet curtain equipment state; and setting an online updating model step threshold, and performing actual deployment and application on the reinforcement learning decision model obtained by training and fusing quantile regression information. According to the method, the problems that the meat duck breeding environment temperature regulation and control technology still faces insufficient predictability, regulation and control lag, control strategy static performance, multi-target optimization deficiency and the like are solved.

Provided in the present application are a livestock sorting method, a livestock sorting system, and a related apparatus. The method comprises: when target livestock enters a detection area, acquiring a livestock image of the target livestock; acquiring livestock information of the target livestock according to the livestock image; on the basis of the livestock information, acquiring sorting information corresponding to the target livestock; and sorting the target livestock to a sorting area corresponding to the sorting information. The present application can solve the problem of livestock sorting quality being relatively poor due to the fact that sorting is only performed according to the weight of livestock, and the influence of factors such as the age, gender, development conditions and health conditions of the livestock on the livestock cannot be comprehensively considered.