1573 results about "Livestock breeding" patented technology

The invention provides a livestock breeding risk intelligent assessment method and system based on multi-source data fusion, and the method comprises the steps: collecting livestock individual vital sign data, breeding environment parameters, management behavior data and risk-related historical data through Internet of Things equipment, and carrying out the data preprocessing to form a standardized multi-source data set; extracting risk features of individual, group and environment levels based on the data set, and fusing the risk features to form a multi-dimensional risk feature library; utilizing machine learning to construct a differentiated risk assessment model; analyzing the incidence relation between the risk factor and the actual event through the Bayesian network to calibrate the model; realizing livestock risk grade dynamic division and early warning based on the calibrated risk scoring system; and finally, generating intervention suggestions for risk quantitative evaluation, risk prevention and control decision and loss evaluation. According to the method, accurate evaluation of livestock breeding risks is realized, decision support is provided for breeding safety management, and the method has relatively high application value.

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 discloses an intelligent livestock breeding traceability method and system, and the method comprises the steps: building an overall framework of the intelligent livestock breeding traceability system based on a micro-service architecture, and employing Spring Cloud Al ibaaba as a micro-service technology stack; livestock physiological data and environmental parameters are collected through Internet of Things equipment, and a livestock electronic file is established; an AI intelligent analysis engine is constructed, and livestock health state evaluation, oestrus prediction and abnormal behavior recognition are achieved; the whole life cycle data of livestock from breeding to selling is recorded based on the block chain technology, and a full-chain traceability system is constructed. The method further comprises the functions of integrating a financial service interface, designing a multi-terminal collaborative application platform, constructing a matchmaking transaction platform and the like. According to the invention, the problems of data islanding, incomplete traceability system, low intelligent level, insufficient system expandability and the like in the prior art are solved, and the accuracy, traceability and system stability of livestock breeding are improved.

The invention relates to the cross technical field of computers and livestock breeding, and discloses an intelligent nutrition mode management method and system based on HAP multi-modal data, and the method comprises the steps: obtaining the multi-source heterogeneous HAP data of livestock, and carrying out the feature extraction and feature fusion of the multi-source heterogeneous HAP data; utilizing a controllable generative adversarial network to generate enhanced HAP feature data and an HAP feature data sequence simulating a physiological process; early abnormal signals are detected through an abnormal detection algorithm, and multi-modal attribution analysis is carried out; continuously optimizing the nutrition demand prediction model and the feeding strategy optimization model; according to the method, by effectively utilizing the neglected unstructured information in the past and combining the multi-modal fusion analysis, the early-stage discovery capability of the weak signal for indicating the physiological abnormality or nutritional imbalance of the livestock and poultry is improved.

The invention discloses a cattle manure automatic cleaning device and method for a cattle farm, and relates to the technical field of livestock breeding intelligent equipment.The method comprises the steps that a hexagonal monitoring grid is established based on excretion coordinates, a manure accumulation thermodynamic diagram is established through a three-dimensional space point cloud reconstruction method, and according to thermodynamic value intensity distribution in the manure accumulation thermodynamic diagram, the manure accumulation thermodynamic diagram is obtained; marking a to-be-cleaned area; according to the to-be-cleaned area, dynamically analyzing faeces conductivity characteristics by adopting an electromagnetic eddy current detection method, and generating a cattle faeces viscosity index and a cleaning difficulty coefficient through a multi-physics coupling algorithm in combination with environmental parameters; and according to the excrement viscosity index and the cleaning difficulty coefficient, a control instruction set of the cleaning device is generated through a dynamic adjustment algorithm. According to the invention, by constructing the hexagonal monitoring grid and the excrement accumulation thermodynamic diagram, spatial modeling of excrement distribution and intelligent marking of the cleaning area are realized.

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 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 discloses a livestock and poultry health state intelligent evaluation method based on multi-sensor fusion and an AI prediction model, and belongs to the technical field of livestock breeding, and the method comprises the following steps: setting multiple types of sensors in a livestock and poultry breeding area, collecting multi-source data such as temperature, humidity, carbon dioxide concentration, ammonia gas concentration, illumination intensity, weight and current, and carrying out the analysis of the data; wherein the weight data is obtained through the weighing platform, and the current data is used for sensing the operation state of drinking, ingestion, ventilation or lighting equipment; various types of sensors such as temperature and humidity sensors, carbon dioxide sensors, ammonia gas sensors, illumination sensors, weight sensors and current sensors are deployed in livestock and poultry breeding areas, all-directional data acquisition of environments and behavior states is realized, and dynamic modeling and feature extraction of key behavior nodes are realized by introducing a deep neural network structure of a gating circulation unit and an attention mechanism.

The invention provides a multi-sensor cooperative stress-free three-dimensional body size measurement method and system for sheep, and belongs to the technical field of livestock breeding, and the method comprises the following steps: collecting the point cloud data of the sheep from multiple perspectives, and carrying out the preprocessing of the collected point cloud data; performing registration and three-dimensional reconstruction according to the preprocessed point cloud data to obtain a sheep three-dimensional point cloud model; performing point cloud repair and attitude correction on the three-dimensional point cloud model of the sheep to obtain a final three-dimensional point cloud model of the sheep; and inputting the three-dimensional point cloud model of the sheep into the trained deep learning model for semantic segmentation and key point detection, and measuring body size parameters of the sheep. According to the multi-sensor cooperative stress-free three-dimensional body size measurement method and system for the sheep, full-life-cycle automatic accurate measurement of body size parameters of the sheep is realized, so that manual intervention is reduced, the stress risk of the sheep is reduced, the measurement precision and efficiency are improved, and technical support is provided for intelligent breeding.

The invention discloses a method for promoting skeletal muscle development and application, and belongs to the technical field of biology. The invention provides a method for promoting skeletal muscle development, an AMPK / p38MAPK pathway is regulated and controlled by activating PPARalpha, the way of activating the PPARalpha is to give a PPARalpha agonist GW7647, and the regulation and control of the AMPK / p38MAPK pathway is shown as reduction of AMPK and P38 phosphorylation levels. Experiments show that the expression of MyoD, MyoG and Pax7 in skeletal muscle can be remarkably improved by activating PPARalpha, the phosphorylation level of AMPK and P38 is inhibited, and therefore muscle fiber proliferation and myoblast proliferation are promoted. The technology can be applied to livestock breeding to improve meat yield or develop drugs for treating skeletal muscle atrophy, and has remarkable economic and clinical values.

The invention relates to the technical field of livestock breeding environment monitoring, regulation and control, and discloses a livestock breeding environment gas dynamic monitoring system. The system comprises a data acquisition module for acquiring data by using a multi-source gas sensor; the gas component analysis module is used for analyzing the data based on a mixed spectrum decomposition algorithm to generate a gas component characteristic matrix; the environment regulation and control decision module inputs the matrix into a multi-mode collaborative decision model to generate a regulation and control instruction; the optimization model construction module is used for constructing a multi-constraint dynamic optimization model to optimize ventilation equipment parameters; and the hierarchical control execution module is used for executing the regulation and control instruction through a hierarchical architecture. The system can comprehensively monitor breeding environment gas, accurately regulate and control ventilation equipment, achieve gas concentration equalization and energy consumption minimization, improve the breeding environment quality, reduce the breeding cost and push intelligent development of the livestock breeding industry.

A temperature control device for livestock raising having a temperature setting function according to one aspect of the present disclosure may comprise: a housing; a first connector disposed on one side of the housing, and to which an input cable connected to an input power source is coupled; a plurality of second connectors provided on one side of the housing and coupled to an output cable connected to the heater assembly to supply electrical power, in which the livestock fence is divided into a plurality of regions and each region is equipped with the temperature sensor and the heater assembly, the heater assembly comprising a plurality of heaters; a third connector which is provided on one side of the housing and to which a plurality of sensor cables respectively connected to the plurality of temperature sensors are coupled; and a temperature controller configured to control electrical power supplied to the plurality of heater assemblies.

The invention relates to the field of animal husbandry feeding control, in particular to an automatic feeding method and system based on electromagnetic valve flowmeter data, and the method comprises the steps: collecting a historical water pressure time sequence of a drinking water pipeline; static characteristics and dynamic characteristics of all water pressure characteristics of the water pressure time sequence are calculated, and a feeding error is calculated according to the target feeding water quantity and the actual feeding water quantity collected during feeding every time; the water pressure features are clustered, corresponding initial weights are distributed to the static features and the dynamic features in the clustering process, an evaluation function is constructed according to the difference of feeding errors in each cluster after clustering is completed, and when the evaluation function value reaches the minimum value, an optimal clustering result is obtained; according to the optimal clustering result, the water volume during real-time feeding is adjusted so as to complete water drinking management of the livestock. According to the method, the water quantity during real-time feeding is adjusted according to the optimal clustering result, and a more accurate feeding strategy can be formulated according to different conditions.

The invention relates to the technical field of smart agriculture, and discloses a livestock breeding environment real-time monitoring method, which comprises the following steps: an edge computing node deployed in a livestock farm collects a multi-mode sensing signal and executes edge preprocessing; analyzing the preprocessed signal by using a lightweight feature extraction model and constructing a comprehensive health stress index; edge cloud cooperative training based on federal learning is executed, and the cloud server carries out global model aggregation; generating an updated environment regulation and control strategy, and synchronizing the updated environment regulation and control strategy to an edge computing node through an edge network; and the environment regulation and control strategy is combined with the comprehensive health stress index to generate and execute a regulation and control instruction for environment control equipment in the edge Internet of Things. According to the invention, the limitation of one-sided information of a single data source can be broken through, low delay and high reliability of environment regulation and control are guaranteed, and fine management and intelligent decision-making of livestock breeding are realized.

The invention relates to the technical field of intelligent livestock breeding, and discloses an Euler sheep body condition score automatic identification system and method based on machine vision. Comprising an automatic identification system, and the automatic identification system comprises a region division module, an image acquisition module, an image preprocessing module, a feature extraction module, a multi-dimensional body condition scoring model and a data output and decision support module. Through the arrangement of the automatic identification system, non-contact automatic acquisition and analysis of Euler sheep body characteristics can be realized through integration of a computer vision technology, a deep learning algorithm and an image processing technology, and a multi-dimensional body condition scoring model is constructed in combination with physiological characteristics and growth stages of the Euler sheep. The method is used for accurately evaluating the fat condition, the health state and the fattening potential of the Tibetan sheep. The system can be applied to large-scale cultivation management, precise nutrition regulation and control and efficient fattening strategy formulation of Tibetan sheep in plateau pasturing areas, and provides intelligent technical support for improving Tibetan sheep cultivation benefits and meat quality.

The invention discloses a hog house environment regulation and control method based on AI visual analysis, and relates to the technical field of livestock breeding. The defects in the prior art are overcome. The method specifically comprises the following steps: monitoring internal environment parameters of a pig house and behavior postures of pigs in real time; analyzing the current perceptual comfort level of the pig by using a behavior-environment correlation model; and dynamically regulating and controlling the temperature control environment facility in the hog house according to the analysis result, wherein the monitoring mode of the internal environment parameters of the hog house is realized through an Internet of Things sensor network uniformly distributed at each key position in the hog house. The AI vision and the Internet of Things technology are fused, a closed-loop control system of pig behavior posture-environment parameter-growth performance is established, the pig behavior posture serves as a decision-making basis for regulating and controlling the environment in the pig house, the regulation and control response speed is effectively increased, parameters such as the temperature and humidity in the pig house are intelligently adjusted, and the control efficiency is improved. The pigs are in the best state 24 hours a day, and the production benefits are improved.

The invention relates to the technical field of biology, in particular to a primer combination for identifying Leyping spotted pigs and an identification method of the primer combination, six specific SNP molecular markers (SNP1-SNP6) are obtained through whole genome screening, six pairs of specific PCR primers are designed and developed on the basis of the sites, the nucleotide sequences of the primers are shown as SEQ ID NO.1-12, and the primer combination is used for identifying the Leyping spotted pigs. And when the genotypes of the to-be-detected sample at the SNP1-SNP6 sites are CC, TT, TT, AA, CC and GG respectively, the to-be-detected sample can be confirmed as a purebred individual of the Licping spotted pig. Compared with a traditional phenotype identification method, the molecular marker detection system established by the invention has the advantages of high detection efficiency, good accuracy and flux. The technical scheme provided by the invention provides important technical support for genetic resource conservation, variety purity identification and genetic improvement of the Leyping spotted pigs, and has remarkable application value in the field of livestock breeding.

The invention provides a cattle and sheep feed trough residual feed monitoring method based on vision, and relates to the technical field of intelligent livestock breeding, and the method comprises the following six steps: intelligent triggering and multi-modal image acquisition, image preprocessing and fusion, time sequence image segmentation and feature extraction, density adaptive volume calculation, online learning and residual feed estimation, and decision analysis and early warning. According to the method, RGB and near-infrared images are synchronously collected through infrared triggering, after perspective correction and illumination adaptive fusion, an LSTM-U-Net time sequence segmentation model is adopted to solve the dynamic shielding problem, a residual feed area is accurately extracted, the feed type is recognized, density adaptive volume measurement is achieved in combination with monocular depth estimation and texture feature analysis, and the method is suitable for large-scale industrial production. Weight estimation is carried out through a support vector regression model, model parameters are optimized on line based on manual correction data, intelligent early warning of the residual material amount is finally achieved through a cloud platform, and the limitation of a traditional method in the aspects of shielding processing, density adaptation and environment anti-interference is effectively overcome.

The invention provides functional compound feed for sows in the perinatal period as well as a preparation method and application of the functional compound feed, and relates to the technical field of livestock breeding. The functional compound feed for the sows in the perinatal period is prepared from the following raw materials in parts by mass: 55 to 60 parts of corn, 13 to 15 parts of soybean meal, 1 to 5 parts of fish meal, 6 to 8 parts of extruded soybeans, 2 to 8 parts of barley bran, 0.5 to 1.5 parts of soybean oil, 0.5 to 1.5 parts of glucose, 2 to 8 parts of wheat bran, 1 to 1.5 parts of dicalcium phosphate, 0.5 to 1.5 parts of calcium carbonate, 0.2 to 0.6 part of table salt, 0.05 to 0.2 part of baking soda, 0.05 to 0.2 part of 50 percent choline chloride and 2 to 5 parts of premix. 0.1 to 0.5 part of a composite additive; the compound additive is prepared from the following raw materials in parts by mass: 0.5 to 1 part of ligustrazine, 1 to 5 parts of aloe-emodin glycoside, 0.5 to 2 parts of magnolol and 3 to 5 parts of probiotic microcapsules. Aiming at the perinatal syndrome of the sows, by adjusting the composition and proportion of the raw materials of the compound feed and the preparation method of important raw materials, many problems caused by the perinatal syndrome of the sows are solved, and the compound feed has a good industrial application prospect.

The invention discloses lactobacillus plantarum OBM7 and application thereof, and belongs to the technical field of biology. The strain is preserved in the Guangdong Microbial Culture Collection Center (GDMCC) on November 12, 2025, the preservation address is the 5th floor of the building 59, No.100 Courtyard, Xianlie Middle Road, Guangzhou, and the preservation number is GDMCC NO. 67282; and the probiotic preparation does not contain antibiotics or drug residues, and meets the development requirements of green and healthy breeding. The probiotic preparation can specifically prevent and control lamb diarrhea, significantly reduce the fatality rate of lamb diarrhea, effectively improve the survival rate of lambs, and provide targeted protection for lamb intestinal health; the lamb feed can regulate lamb gastrointestinal tract micro-ecological balance, improve digestion and absorption functions, significantly improve feed intake and feed conversion efficiency, and promote lamb growth performance improvement. Reliable technical support is provided for efficient, green and healthy breeding of lambs, high practicability and wide industrial application prospects are achieved, and the method has great significance in promoting green transformation of the livestock breeding industry.

The invention relates to the technical field of livestock breeding, in particular to mutton sheep breeding manure dehydration type treatment equipment which comprises a mixing barrel, a trapezoidal box is fixedly connected to the rear side of the top end of a manure dehydration box, a conveying barrel is fixedly connected to the interior of the front end of the manure dehydration box, and a power auger is arranged in the conveying barrel; the right end of the conveying cylinder is fixedly connected with a dewatering cylinder, the right end of the dewatering cylinder is fixedly connected with a dewatering extrusion cylinder, the outer end of the dewatering extrusion cylinder is provided with an extrusion assembly, the trapezoidal box is internally provided with a sliding assembly, the extrusion assembly and the sliding assembly are used for extruding and dewatering excrement, and the bottom end of the excrement dewatering box is fixedly connected with a supporting leg frame. A manure water tank and a manure tank are arranged on the right side of the manure dewatering tank; the manure tank is positioned on the right side of the manure water tank. As the excrement is dehydrated for three times, the excrement is dehydrated more thoroughly, and the dehydration efficiency is improved.

The invention relates to the technical field of data tracking, in particular to a livestock breeding tracking and tracing method and system based on data integration analysis. The method comprises the following steps: obtaining a livestock breeding related parameter universal set and a traceability objective function set, performing layered screening on the livestock breeding parameter universal set to obtain a key breeding parameter set, and generating a dynamic constraint rule; constructing a multi-level agent analysis model based on the key breeding parameter set and the traceability target function set, and establishing a multi-target traceability evaluation standard to obtain a fitness evaluation standard; therefore, a complete calculation chain integrating data dimension reduction, proxy modeling, parallel evolution and multi-objective decision is constructed, so that the optimization problems that the traditional livestock breeding tracking and tracing scheme design depends on artificial experience, the efficiency is low and multiple competition objectives are difficult to consider are solved; and the scientificity, the automation degree and the overall performance benefit of the traceability system configuration are improved.

The invention belongs to the field of biotechnology and livestock breeding, and relates to an SNP (Single Nucleotide Polymorphism) molecular marker closely related to sheep weight traits, a primer group, a kit and application. The nucleotide sequence of the SNP molecular marker is as shown in SEQ ID NO.4, and Ggt exists at the 46th bp position of the sequence as shown in SEQ ID NO.4; c mutation. According to the method, the sheep population with excellent genetic resources can be rapidly established by rapidly and accurately detecting the SNP marker related to the weight character of the sheep genetic resource population of the'Auodur Lake ', so that the marker-assisted selection breeding process of the weight character of the sheep is accelerated.

The utility model relates to the technical field of feed production, in particular to a livestock feed screening device for livestock breeding, and adopts the technical scheme that the livestock feed screening device comprises a placement frame, a screening hopper is movably mounted at the top of the placement frame, and a feeding hopper is movably mounted at the top of the screening hopper; the placing frame comprises a bottom frame, a top frame is movably installed on the top of the bottom frame, the front end of the bottom of the top frame is rotatably installed with the front end of the top of the bottom frame through a hinge, and the rear ends of the two sides of the top frame are movably installed with the bottom frame through first adjusting frames. A reserved groove is formed in the rear end of the bottom of the feeding hopper, a movable frame is movably installed at the position, at the bottom of the reserved groove, of the bottom of the feeding hopper, the rear end of the feeding hopper is rotationally connected with the rear end of the top of the screening hopper through a hinge, second adjusting frames are movably installed on the two sides of the feeding hopper respectively, and the feeding hopper and the screening hopper are movably installed through the second adjusting frames. The problem that in the prior art, the feed falling speed is uncontrollable, and consequently the screening accuracy is reduced is solved.

The feed trough comprises a feeding trough and a feed feeding device, the feed feeding device comprises a feed box arranged above the feed trough, a discharge port is formed in the lower end of the side, close to the feed trough, of the feed box, and a feed outlet is formed in the lower end of the side, close to the feed trough, of the feed box. A feed supply mechanism used for controlling the feed in the feed box to be discharged through the discharge port is arranged at the discharge port, a pressure sensor is installed at the bottom of the feed box and used for detecting the weight of the feed in the feed trough, and when the feed is poured into the feed box, the pressure sensor detects the weight of the feed in the feed box; when the feed in the feed box reaches a certain weight, the controller controls the feed supply mechanism to discharge the feed in the feed box through the discharge port, and the driving mechanism drives the feed box to move back and forth in the length direction of the feeding trough, so that the feed is uniformly put into all positions of the feed trough, local accumulation of the feed in the feed trough is avoided, and the feed feeding efficiency is improved. The beef cattle can conveniently eat.

The invention belongs to the technical field of livestock breeding, and discloses a livestock breeding odor deodorization and purification device and method. The odor deodorization and purification device for livestock breeding comprises a filter box and flow guide covers at the two ends of the filter box, a supporting baffle and a slidable screen frame are arranged in the filter box, an activated carbon filter structure is arranged in the screen frame, and an adsorption sealing assembly is arranged in the filter box; the adsorption sealing assembly comprises a shielding guide plate, a magnetic coupling structure, a dynamic sealing structure, a self-cleaning structure and a gas flowing channel; the device has the beneficial effects that the shielding blocking plate is synchronously driven to precisely slide to and block the opening of the box body through magnetic adsorption, and the effect of'sealing before opening 'or'sealing while opening' is achieved in the process; the inevitable waste gas leakage window period in a traditional replacement mode is physically eradicated.

The invention discloses an animal nutrition and feed course resource sharing cloud platform and a knowledge graph construction method. The method comprises the steps of obtaining feeding knowledge resource data of different animal types and constructing a feeding knowledge meta-database; performing multi-granularity entity recognition and analysis on the feeding knowledge resources in the feeding knowledge meta-database to generate four types of entity sets, constructing an entity interaction graph, performing entity relationship reasoning to obtain a triple set, and constructing a feeding resource knowledge graph by using the triple set; constructing a personalized recommendation engine, carrying out user question answering and demand knowledge recommendation through the personalized recommendation engine, and carrying out interest resource recommendation based on user use behaviors; and building an animal nutrition and feed course resource sharing cloud platform by utilizing a micro-service architecture technology based on the personalized recommendation engine, the feeding knowledge meta-database and the feeding resource knowledge graph. Therefore, accurate, real-time and multi-dimensional knowledge service and help are provided for animal husbandry practitioners or interests and amateurs.

The invention discloses a pork safety traceability quality nondestructive testing method and system for livestock breeding. The method comprises the following steps: constructing a stable detection environment by utilizing a constant temperature and humidity device, a dynamic environment monitoring unit and an optical shielding material; a Fourier transform infrared spectrometer is adopted to collect spectral data, and a non-contact texture detection device is combined to measure physical parameters; denoising, standardization processing and feature fusion are carried out on the collected data, and key variables are extracted through principal component analysis; grouping the samples by using a K-means algorithm, and verifying sample classification by using linear discriminant analysis; quantitative prediction and classification of pork quality are realized based on partial least squares regression and a support vector machine model; the model is applied to an actual scene, real-time processing and visual display are achieved through online data collection, and a data sample library is continuously expanded. The method has the advantages of high detection speed, high precision, wide application range and the like, and can be widely applied to the fields of meat quality detection and food safety.

The invention relates to a cattle stomach momentum anomaly identification method based on machine learning, and belongs to the field of animal husbandry digitization. The method comprises the following steps of S1, data acquisition, S2, data preprocessing, S3, feature construction, S4, stomach momentum state label construction, S5, sample imbalance processing, S6, model construction and training, and S7, model evaluation and parameter adjustment. The method not only makes obvious breakthrough in theoretical modeling precision and practical deployment efficiency, but also realizes substantive crossing of experience-driven cattle stomach momentum management to data-driven cattle stomach momentum management through experimental verification, and provides powerful technical support for health early warning and asset management in an intelligent animal husbandry scene.

The invention discloses a livestock monitoring method and device based on multi-sensor fusion, and relates to the technical field of livestock breeding. Comprising the following steps: firstly, collecting boundary information of a livestock place, determining a motion range and establishing a plane-coordinate system; motion data, including motion coordinates, acceleration and timestamps, is obtained by a motion monitoring unit carried by the livestock. And converting the acceleration into displacement by using a double-integral method, aligning a motion track by using a dynamic time migration algorithm, and outputting fusion data. And based on the motion fusion data, setting a monitoring time window, and extracting motion features and physiological parameters. And generating a comprehensive health judgment coefficient in a weighted coupling mode, and dynamically correcting a health judgment threshold value according to the environment temperature to obtain a self-adaptive health judgment threshold value. And comparing the comprehensive health judgment coefficient with a self-adaptive health judgment threshold value to obtain a health monitoring result. And comprehensive and accurate monitoring and evaluation of the health state of the livestock are realized.