129 results about "Sheep flock" patented technology

The invention discloses a sheep flock accurate nutrition supply method based on an intelligent feeding algorithm, and the method comprises the following steps: collecting the body type, physiology, movement and environment data of sheep through a multi-modal sensing device, and constructing individual three-dimensional representation based on a neural radiation field model, historical growth data and a real-time health state are analyzed by utilizing an individual nutritional requirement calculation model, an optimal feed distribution strategy is determined by combining an intelligent sheep flock optimization algorithm, a feeding scheme is dynamically adjusted by adopting deep reinforcement learning, and through a cloud-side collaborative calculation architecture, the calculation efficiency is improved and a feeding decision is optimized. A non-intrusive health monitoring technology is combined, a group health evaluation model is constructed, the feed ratio is adjusted in real time, accurate matching of individual and group nutritional requirements is achieved, and through prediction of the individual and group nutritional requirements, self-adaptive adjustment is conducted on feeding parameters, and a dynamic nutrition supply strategy is optimized. The system effectively improves the feeding precision, reduces the feed waste, and optimizes the health management of the sheep flock.

The invention provides an unmanned aerial vehicle multi-target path planning method based on a multi-target sheep flock migration algorithm. The method comprises the following steps: 1, constructing a three-dimensional model of a task environment: 1.1, constructing a grid-based three-dimensional task space model; 1.2, determining collision probability distribution; 2, initializing algorithm parameters and populations; 2.1, initializing multi-target sheep flock migration algorithm parameters; 2.2, randomly generating an initial population in the task area range; 3, performing non-dominated sorting on the population, and selecting head sheep; 3.1, calculating an objective function value of each sheep; 3.2, determining a Pareto optimal solution set by adopting non-dominated sorting; 3.3, selecting the sheep with the largest crowding distance as the head sheep; 4, executing a grazing operator; 5, judging and executing a migration operator or a contraction operator; 5.1, if the optimal solution of the group is updated, executing the migration operator; 5.2, if the optimal solution of the group is not updated, executing a contraction operator; and 5, judging whether the maximum number of iterations is reached or not, if so, outputting an optimal path planning solution, and otherwise, returning to the step 3.

The invention discloses a sheep coccidiosis parasitic ovum accurate detection method based on deep learning, and the method comprises the following steps: automatically collecting a sheep manure sample image, carrying out the noise removal and enhancement of the image, and guaranteeing the image quality; the preprocessed image is input into an automatic sheep coccidiosis parasitic ovum detection model for training, the training process comprises image segmentation, feature extraction and accurate recognition, and a deep learning model is used for automatically recognizing sheep coccidiosis parasitic ovum; performing infection density analysis according to the number of sheep coccidiosis parasitic ova output by the improved deep learning model, and evaluating the infection risk of the sheep flock; the detection result is visually displayed, detailed analysis reports including the number, type distribution and infection density data of sheep coccidiosis parasitic ova are generated, hours or even longer time needed by a traditional method is shortened, and high accuracy of the detection result is ensured.

The invention discloses a large-scale deformation compensation method, device, equipment and medium, and relates to the field of image processing, and the method regards a salient point in an image as a leader in a group, is similar to a leading animal in a migration sheep flock, and plays a key role in guiding the whole registration process. In order to estimate the aggregation manifold, large-scale deformation registration is divided into three parts according to an animal migration mode: route decision based on aggregation quantization, route execution with aggregation maintenance and cascade migration with aggregation inheritance. The three parts are integrated into an aggregation cascade migration (CCM) framework, and large-scale deformation of the image is effectively compensated. According to the method, the registration precision and robustness during large-scale deformation compensation can be greatly improved. The method is a universal method, is not limited to specific feature descriptors or deformation models, and can be easily expanded to other image registration tasks.

The invention belongs to the technical field of molecular markers, and particularly relates to an SNP (Single Nucleotide Polymorphism) molecular marker related to sheep weight traits and application thereof. The invention provides an SNP (Single Nucleotide Polymorphism) molecular marker related to sheep body weight traits, which corresponds to 35074122bp of the 11th chromosome of a sheep genome and has a basic group of C / T. The SNP molecular marker has remarkable correlation with the sheep weight, 6.11% of weight variance variation can be explained, and T is favorable allelic variation of sheep weight traits. The SNP molecular marker provided by the invention can be used for identifying sheep weight traits, distinguishing high-weight sheep from low-weight sheep, selecting a TT genotype for breed conservation during breeding, taking the TT genotype as a breeding sheep during breeding, excluding sheep with C allele during hybridization with other sheep, and performing artificial fertilization by adopting sperm of a TT genotype breeding ram. The breeding efficiency can be greatly improved, and sheep flock with weight advantages can be obtained.

The invention discloses a free-range sheep flock dynamic counting method and system based on multi-view vision, and the method employs multi-view image collection deployment, and devices are installed in different directions, heights and angles of a sheep flock activity area, thereby achieving the complete coverage of the activity range. In the image preprocessing stage, graying, Gaussian filtering, histogram equalization and other operations are applied to improve the image quality. The sheep flock target is accurately detected by means of an improved deep learning model such as YOLOv5 containing a CBAM module. And multi-target tracking association is combined with Kalman filtering and a Hungary algorithm to realize stable tracking of sheep flock targets. The biological feature identification extracts sheep face features and compares the features with a database to identify individuals. And an environmental factor compensation model is constructed to cope with illumination and weather changes. And a parallel computing architecture and an optimized data storage and transmission mode are adopted, so that the processing efficiency is improved, and the dynamic counting of the free-range sheep flock is accurately realized in real time.

The invention discloses a sheep infectious disease number zero individual tracing method and system based on a group interaction network, particularly relates to the technical field of agricultural informatization, and is used for solving the problem of number zero individual misjudgment caused by neglecting group dynamic behaviors in an existing static network model. The method comprises the following steps: dividing a continuous time window to construct a time sequence interaction network by acquiring dynamic contact data and high-risk medium use data of a sheep flock; virtual edges are added to individuals with the use interval smaller than the pathogen survival time of the same high-risk medium; calculating a node behavior mode mutation degree based on a medium using interval variance, and analyzing propagation fluctuation in combination with an input / output propagation flow ratio standard deviation; identifying nodes of which behavior mutation exceeds a threshold value, propagation fluctuation continuously exceeds the threshold value and output propagation flow suddenly drops as an abnormal propagation source; and extracting a first window associated sub-network, and judging the node which has the highest behavior mutation degree and uses a high-risk medium in the sub-network as a zero individual, thereby realizing accurate tracing of the sheep infectious disease source and providing a basis for accurate prevention and control of a farm.

This utility model discloses an intelligent adjustable sheepfold fence device, comprising two first horizontal plates, with second horizontal plates on both sides of each first horizontal plate. Several circular tubes are fixedly connected to the bottom of both the first and second horizontal plates, and circular rods are slidably connected to the inner walls of the circular tubes. A first base plate is fixedly connected to the bottom of the circular rods at the bottom of the first horizontal plates, and a second base plate is fixedly connected to the bottom of the circular rods at the bottom of the second horizontal plates. First fixing plates are fixedly connected to the same side of both the first and second horizontal plates on the same side. A signal transmitter is fixedly connected to one side of the first fixing plate, and second fixing plates are fixedly connected to the same side of both the first and second horizontal plates away from the signal transmitter. This utility model effectively prevents sheep from crossing the fence, ensuring the safety of the flock and the continuity of management. It can respond promptly to changes in sheep behavior, improve the farm's responsiveness, and enhance management flexibility and adaptability.

The invention discloses an intelligent sheep house environment control method and system, and the method comprises the steps: collecting the environment parameters in a sheep house in real time based on a five-dimensional environment sensing array, including temperature, humidity, ammonia concentration, illumination intensity and noise level; performing real-time quantification on the behavior characteristics of the sheep flock by adopting a sheep flock behavior recognition method based on deep learning; constructing a dynamic weight control model based on an LSTM neural network and a reinforcement learning mechanism, and inputting the collected environmental parameters and the quantized behavior characteristics into the dynamic weight control model to realize dynamic coupling of the environmental parameters and the behavior characteristics; and according to an output result of the dynamic weight control model, generating an optimal environment regulation and control instruction, and sending the optimal environment regulation and control instruction to execution equipment to realize intelligent and accurate regulation and control of the sheep house environment. According to the method, the environment regulation response speed can be increased, the lamb survival rate is increased, and the sheep flock health level and production efficiency are remarkably improved.

The invention relates to the field of livestock and poultry breeding environment control, and particularly discloses a sheep house environment intelligent regulation and control system and method based on multiple sensors. The core of the method is that sheep house environment parameters are collected in real time through a sensor array, and meanwhile sheep flock behavior posture proportion characteristics are continuously extracted through a video analysis module; performing space-time fusion on the environment data and the behavior characteristics, inputting the environment data and the behavior characteristics into a pre-trained behavior-environment coupling model, and calculating a sheep flock discomfort index reflecting a real stress state of the sheep flock; based on the numerical value, the change direction and the rate of the index, a control strategy generator dynamically generates a staged and multi-device cooperative time sequence control instruction sequence to drive ventilation, cooling, heating and other devices to execute combined actions; the system performs effect evaluation according to behavior feedback after regulation and control, and optimizes a subsequent strategy accordingly. The system synchronously realizes accurate decision based on biological feedback, anti-collision control of multi-device cooperation and dynamic regulation and control with early warning capability.

Disclosed are a swab flocking device and a flock blowing and flocking process for a swab. A conveying drag chain transversely penetrates through a flocking box, several swab hangers are arranged on the conveying drag chain at intervals, and the conveying drag chain is connected to a first motor. Several blowers are arranged on an outer side of the conveying drag chain in the flocking box. During flocking, a swab stick is hung on the swab hanger and then is conveyed forwards by the conveying drag chain, and several blowers are configured to blow flocks onto an end head of the swab stick.

The application provides a sheep fattening complete granular feed and a preparation method and a feeding method thereof, relates to the technical field of feed, and the sheep fattening complete granular feed comprises the following components: ginseng stem and leaf, red yeast extract and sheep group basic feeding daily ration. The application solves the technical problems of high total ginsenoside extraction cost, low single stomach animal utilization rate, slow growth during the sheep fattening period and frequent outbreaks of diseases, achieves the technical effects of improving ginsenoside utilization efficiency, synergistically improving sheep immunity and improving the average daily weight gain of sheep during the whole period, and meanwhile, the process is simple, and the cost is low.

The invention relates to the technical field of operation and maintenance inspection, and discloses a factory intelligent operation and maintenance inspection method and a system thereof.The factory intelligent operation and maintenance inspection method comprises the following steps that an inspection area and photovoltaic panel coordinates are set, a first route path is generated, and an unmanned aerial vehicle inspects a photovoltaic panel and a convergence cable according to the first route path; and shooting an inspection area by adopting a site camera, judging that hidden danger behaviors exist in the recorded video, assisting in positioning the coordinates of the hidden danger behaviors through the coordinates of the photovoltaic panel, and planning and generating a second route path according to the inspection area, the coordinates of the photovoltaic panel and the coordinates of the hidden danger behaviors. According to the method, the coordinate position of the sheep flock when the sheep flock eats grass or stays at the bus wire is presumed through the coordinate of the photovoltaic panel, the first route path is modified according to the presumed grass eating or staying coordinate of the sheep flock to generate the second route path, and the grass eating or staying coordinate of the sheep flock is polled through the second route path, so that the cruising efficiency is improved.

The present invention relates to the field of path optimization technology, and in particular to a GIS-based grassland multi-region rotational grazing management optimization method and system. The method first takes into account the positional relationship between non-grazing grassland areas and obstacle areas, and makes a minimum obstacle encirclement for non-grazing grassland areas. The initial grazing preference of each non-grazing grassland area is quantified, and the grazing preference can be obtained by further combining it with the amount of grass for path planning of a single flock of sheep. The grazing paths of different flocks of sheep are combined, and the optimal path combination method can be screened by analyzing the degree of overlap in each path combination method and the grazing suitability of the non-grazing grassland area at the end point. The present invention determines the optimal path combination method through position analysis, path planning, and path combination analysis, which can ensure that the grazing paths of multiple flocks of sheep have a small degree of overlap, and the non-grazing grassland area at the end point of the path can ensure normal grazing of the sheep flock, thereby improving grazing efficiency.

The utility model discloses a feeding device for sheep breeding capable of automatically mixing feed, which belongs to the technical field of sheep breeding and comprises a bottom plate, a protective component is connected above the bottom plate, a worker stands outside a breeding farm to pour feed into a feed cylinder, a valve on a discharge pipe is opened, a transverse moving component is started to drive the feed cylinder to transversely move, and the feed cylinder can be automatically mixed. According to the feeding device for sheep breeding, a worker does not need to enter a breeding farm to add feed, time and labor are saved, the risk that sheep flock is infected with diseases is reduced, a protection plate is arranged, the situation that rainwater enters the device can be reduced, the feed quality is prevented from being affected, and the situation that the health of sheep is seriously threatened after the sheep eat the feed is avoided; and by adjusting the connecting assembly, the connecting plate and the protective plate can be detached from the device, so that the connecting plate and the feed cylinder are convenient to maintain or replace, and the practicability is improved.

The present invention relates to the field of image recognition technology, and more particularly to a multi-target recognition method and system based on visual technology, comprising: obtaining the proximity of sheep within a connected domain based on the shape of a connected domain and the distribution value of suspected sheep; obtaining the false detection degree value of each target frame within the connected domain based on the edge distribution of the connected domain between the target frame and other target frames, as well as the sheep segmentation inaccuracy and target probability; obtaining the comprehensive sheep recognition accuracy of the connected domain based on the proximity of the sheep within the connected domain and the false detection degree value of the target frame; obtaining the optimal step size parameter of a convolutional neural network for multi-target recognition of sheep in a pasture based on the comprehensive sheep recognition accuracy; and performing multi-target sheep recognition on a remote sensing image of a sheep flock in a pasture using the convolutional neural network based on the optimal step size. The present invention improves the accuracy of recognizing multi-target sheep in a remote sensing image of a sheep flock.

The invention discloses an SNP (Single Nucleotide Polymorphism) molecular marker related to Hu sheep epididymis weight major quantitative trait sites and application thereof, and belongs to the fields of genetic breeding and molecular biology. The SNP molecular marker is located at the 33127527th basic group of Hu sheep chromosome 9, and polymorphism of two alleles C and T appears at the site. Different genotypes of the SNP site are significantly related to the epididymis weight of Hu sheep, wherein the epididymis weight of a CC genotype individual is significantly lower than that of TC and TT genotypes (Plt; 0.01) of the substrate. The SNP molecular marker is applied to early breeding of high-fecundity stud rams, and has important significance in improving the production capacity of sheep flock and increasing the breeding benefits.

The present application relates to the technical field of sound recognition, and particularly relates to a sound recognition system for sheep feeding behavior. The technical scheme comprises a sound collection module, a voice enhancement module, a voiceprint feature extraction module, a multi-modal classification module, a data fusion unit, the sound collection module is arranged on a wearable device on the neck of a sheep, is provided with an anti-wind-noise directional microphone array, and is used for collecting environmental sound signals in real time; the voice enhancement module is connected with the sound collection module. The present application realizes accurate recognition and analysis of sheep feeding behavior, effectively solves the problems of sound signal processing in a complex environment, individual and group monitoring, privacy protection and energy supply, not only improves the intelligent level and efficiency of pasture management, reduces labor costs, but also can timely find health problems of sheep, protect the health of the sheep, protect the privacy of sheep data, and improve the energy utilization efficiency of equipment.

The present invention discloses an automatic weighing and sheep flock separating device and its usage method, which relates to the technical field of new-type automatic sheep flock separating devices. The present invention includes a flock separating and carrying outer frame, at the top of which is fixedly connected a PLC control cabinet, and at one end of the flock separating and carrying outer frame is fixedly connected an automatic unfolding inlet door. Through the design of the synchronous logarithm automatic marking and recognition structure, the device is convenient for automatically pasting labels again on the bodies of the sheep to be classified and photographing and inputting the data into the cloud, further improving the recognizability after classification and providing convenient support for quantity modularization. And through the design of the adaptive guiding and adjusting plate structure, the device is convenient for completing the driving adjustment of the adaptive slope and angle, so as to adapt to the leg heights of different species and form a better force-bearing support, making the device convenient for better guiding different livestock to use the device.

This invention discloses a method for breeding a new dual-purpose (meat and milk) sheep breed. The method involves crossbreeding East Friesian sheep as the sire and Lowland sheep as the dam to obtain the East F1 generation; crossbreeding the East F1 generation with Lowland sheep as the dam to obtain the East F2 generation; crossbreeding the East F1 generation with East Friesian sheep as the dam to obtain the East F2 generation flock; and crossbreeding the East F2 generation with East F1 generation as the dam and Lowland sheep as the dam to obtain the East F3 generation flock. Superior rams and ewes from the East F3 generation flock are selected for self-pollination to establish a zero-generation dual-purpose sheep flock. Through crossbreeding fixation, generational selection, and breeding expansion, a new dual-purpose sheep breed is developed. The new breed developed by this invention has advantages such as good meat performance, excellent milk production performance, high fertility, good maternal instincts, and strong adaptability.

The invention relates to the technical field of path optimization, in particular to a grassland multi-region rotation grazing management optimization method and system based on a GIS (Geographic Information System). According to the method, firstly, the position relation between an unpainted grassland area and an obstacle area is considered, and a minimum obstacle encirclement circle of the unpainted grassland area is made; and the initial grazing optimization degree of each non-grazing grassland area is quantified, and the grazing optimization degree can be obtained by further combining the grazing amount so as to be used for path planning of a single sheep flock. The grazing road strength of different sheep flocks is combined, and the optimal path combination mode can be screened out by analyzing the coincidence degree in each path combination mode and the appropriate grazing degree of the end point non-grazing grassland area. According to the method, the optimal path combination mode is determined through position analysis, path planning and path combination analysis, it can be guaranteed that the coincidence degree of the grazing paths of multiple sheep flocks is small, normal grazing of the sheep flocks can be guaranteed in the non-grazing grassland area of the path end point, and the grazing efficiency is improved.

This invention discloses an integrated fermentation pen for sheep farming. It relates to the field of livestock farming technology and includes: a sheep pen comprising pillars and a roof; the base of the pillars is fixed to the ground, and the roof is mounted on the pillars at an angle to the ground, with ventilation louvers on the roof; a slatted floor is located below the roof, and a manure storage space is located below the slatted floor; a support platform is movably positioned between the manure storage space and the slatted floor via a walking mechanism; the bottom of the support platform has a spray pipe, a feeding pipe, and a storage bin; the end of the spray pipe away from the storage bin has an atomizing nozzle, and an auger conveyor is located inside the storage bin corresponding to the feeding pipe; a manure cleaning device includes a scraper and a high-pressure pneumatic cleaning assembly, with the scraper rotatably connected to the bottom of the support platform. This integrated fermentation pen for sheep farming solves the problems of manure residue during cleaning, delayed ammonia control, and air pollution in underground spaces in existing technologies.

The invention discloses a YOLOv13 model-based improved high-density low-pixel sheep detection method under an unmanned aerial vehicle visual angle, and the method comprises the following steps: 1, collecting an original picture of a sheep flock, and carrying out the marking of a target sheep through a marking tool; 2, carrying out the structural innovation of a YOLOv13 model, providing a TokenC3 module, and introducing a high-resolution P2 detection branch and a modular sparse pruning strategy; 3, training the improved model to obtain a high-precision and real-time detection result, and generating a visual detection picture; 4, carrying out an ablation experiment, and gradually verifying the effectiveness of each innovative module; and step 5, realizing deployment of the model on an embedded platform, and visually displaying the application effect of the method. According to the whole method, the detection precision, speed and generalization ability of the sheep target in the unmanned aerial vehicle scene are greatly improved, and the method has remarkable practical application value.

The utility model discloses a sheep farm medicated bath spraying device, which relates to the field of livestock breeding, and comprises a base, the top of the base is provided with an annular wall, the top of the base is provided with a support seat at the center of the annular wall, the inside of the support seat is rotatably connected with a delivery pipe, and the outer side of the delivery pipe is provided with dispersion pipes in an annular array. According to the sheep medicated bath device, the motor drives the conveying pipe to rotate, the dispersing pipe and the nozzles are driven to evenly spray liquid medicine, so that sheep flock can be fully subjected to medicated bath treatment in the annular enclosing wall, and the sheep flock can be uniformly dispersed in the annular enclosing wall. Liquid medicine can comprehensively and evenly cover the sheep body, the medicated bath efficiency and effect are improved, the gradient of the top of the base is gradually reduced from the center to the periphery, redundant liquid medicine can naturally flow to the periphery of the base, and accumulation of the liquid medicine on the top of the base is reduced.

This utility model relates to the field of sheep farming technology, specifically to a sheep feed mixing and stirring device. It includes a cylinder, with an internal feeding chamber and a stirring chamber equipped with a stirring assembly. Several internally and externally connected feeding hoppers are annularly installed on the side wall of the feeding chamber. The stirring assembly includes a stirring shaft and several multi-layered stirring blades fixedly installed on the outer wall of the stirring shaft. The stirring assembly also includes a stirring motor installed outside the bottom of the cylinder. A hollow sprinkler ring is arranged concentrically around the outside of the cylinder. A discharge pipe is connected to the side wall near the bottom of the cylinder. A filter plate is fixedly connected to the end of the discharge pipe that connects to the side wall of the cylinder. A butterfly valve is fixedly installed on the discharge pipe. This utility model uses a sprinkler to adjust the humidity during the feed mixing process to meet the needs of different sheep flocks. Furthermore, the sprinkler sprays water into the inner cavity of the cylinder, and the stirring blades create a vortex to clean the inner wall of the cylinder, ensuring cleanliness.

The invention relates to the technical field of livestock breeding, and discloses a sheep variety breeding method combining phenotype data and gene information, and the method comprises the steps: building a data collection module, a data analysis module, a seed selection and reproduction module, a monitoring module, a genetic stability evaluation module and a feedback adjustment module; the data analysis module is used for analyzing data of the data acquisition module, calculating and evaluating growth, gene conditions and environmental correlation and providing a basis for breeding, a seed selection strategy is formulated in the seed selection and reproduction module, the monitoring module records multi-generation genetic data, and the genetic stability evaluation module is used for evaluating the genetic stability of the sheep flock subjected to multi-generation breeding. And comparing and analyzing the change conditions of gene frequencies and genotype distribution genetic parameters before and after multi-generation breeding, calculating a historical genetic stability coefficient As according to the gene frequencies before and after multi-generation breeding, evaluating a breeding effect and finding a problem improvement direction, and adjusting seed selection by a feedback adjustment module according to an evaluation result of a genetic stability evaluation module.

The application discloses a screening method and application of a SNP molecular marker of a PDGF gene related to the number of lambing of a Tianhua mutton sheep flock. F ST The signal is detected, and a molecular marker affecting the number of lambing of the Tianhua mutton sheep flock is screened in combination with gene annotation and site annotation. The molecular marker is located at 3850004 bp of a PDGFD gene of a chromosome 15 of a sheep reference genome (ARS-UI_Ramb_v2.0), and the base mutation is T or C. The molecular marker has a significant influence on the number of lambing of the Tianhua mutton sheep flock, can be applied to the molecular marker for detecting the number of lambing of the Tianhua mutton sheep flock, accelerates the breeding process of the Tianhua mutton sheep, and has the advantages of simple operation, high speed, high sensitivity and the like.

An impact protecting device includes flocked energy absorbing material (FEAM) impact force absorbing (IFA) segments. Each segment includes a double-sided flock section; a segment cover disposed covering the double-sided flock section and an outer elastic cover enclosing the plurality of FEAM IFA segments including stitching to keep the segments adjacent to adjoining segments but separated. The device further includes overlapped segments to provide extra head protection for the forehead and frontal head areas.

The invention relates to the technical field of livestock breeding intellectualization, and discloses an intelligent breeding system and method for full-barn feeding cashmere goats. The method comprises the following steps: collecting position coordinates and attitude information of down producing goats in a breeding house, and collecting environmental parameters of a plurality of position points; identifying a sheep flock subset with a local aggregation situation according to the position coordinates, and synchronously obtaining environmental parameters associated with the geographic position of the subset; deducing an expected behavior evolution trend of the sheep flock subset under the action of the environmental parameters in combination with the attitude information and the associated environmental parameters; judging whether the distribution of the whole cashmere goats needs to be subjected to global intervention or not according to the trend; when it is judged that intervention is needed, the movement guiding priority of each cashmere goat is calculated; and generating a differentiated path guide strategy for each goat based on the priority and executing the strategy to adjust the distribution state of the down producing goats in the shed. According to the invention, active prediction and personalized accurate guidance of sheep flock behaviors are realized, and the intelligent level of breeding management and animal welfare are improved.