152 results about "Flock" patented technology

The invention discloses a bird repelling method and related equipment for a power distribution iron tower, and the method employs a multi-dimensional sensor for cooperative operation, and collects infrared, sound, images and radar reflection signals in real time. Through multi-dimensional data fusion, the appearance, sound wave and behavior characteristics of the bird flock are deeply mined, the bird flock type is accurately identified, and the problem of insufficient detection of a single sensor is solved. Based on the sensitivity difference of different bird flocks to vision, hearing and ultrasonic waves, bird repelling modes such as strong light stroboflash, sound or ultrasonic waves are dynamically matched from the preset bird repelling strategy library, the adaptability of birds to a single bird repelling means is avoided, and the bird repelling success rate is remarkably increased. And a closed-loop optimization mechanism is formed by iteratively optimizing a strategy library matching rule by using bird repelling effect feedback data, so that the system can adapt to the environment and bird behavior changes, and the long-term bird repelling effect is enhanced. Compared with the prior art, line fault risks caused by bird activities are effectively reduced, and safe and reliable operation of a power system is powerfully guaranteed.

The invention discloses a shortest-time-based bird flock repelling effect evaluation method for an airport intelligent bird repelling system, and the method comprises the steps: S1, collecting the multi-dimensional monitoring data of an airport bird flock repelling process through a biological feature sensing system, and enabling the multi-dimensional monitoring data to comprise a repelling duration parameter, a region clearing index, and bird flock adaptability response data; s2, based on the multi-dimensional monitoring data, analyzing the spatio-temporal behavior characteristics of the bird flock through an intelligent analysis terminal, and constructing a multi-dimensional bird flock expelling effect characteristic matrix; s3, based on the feature matrix, performing dynamic weight optimization of bird flock expelling effect evaluation indexes with the shortest expelling time as a target, and generating a self-adaptive weight coefficient group; and S4, based on the self-adaptive weight coefficient group, performing panoramic evaluation on the bird flock repelling effect by adopting a time sequence perception memory network, and outputting a repelling efficiency analysis result taking the repelling timeliness as a core. While the flight safety is guaranteed, efficient utilization of bird repelling resources is realized.

The invention relates to the technical field of airport safety guarantee, and particularly discloses an airport bird situation monitoring and early warning bird repelling equipment linkage control method comprising the following steps: obtaining bird situation data vectors collected by sensors, calculating fused bird situation data vectors, and obtaining bird flock information; constructing a bird situation risk assessment model based on machine learning, combining the fused bird situation data with an aircraft take-off and landing plan, a runway use state and airport surrounding environment information to form an input feature vector, calculating a risk value through a risk assessment function, and dividing risk levels according to the risk value; according to a risk grade result of the risk assessment module, corresponding bird repelling equipment is controlled to work according to a hierarchical linkage bird repelling strategy; and in the bird repelling process, the risk level is re-evaluated according to the new bird situation data, the parameters of the bird repelling equipment are adjusted, and the bird repelling strategy is optimized by using a reinforcement learning algorithm. According to the invention, the defects of monitoring range and precision of a single sensor are effectively overcome, and the reliability of bird monitoring is greatly improved.

The invention relates to a task allocation and route autonomous planning method for multi-unmanned aerial vehicle cooperative bird repelling. The method comprises the following steps: step 1, digital modeling; 2, collecting information; step 3, task list establishment: adding a bird flock needing to be driven into a task list according to a constraint condition; 4, calculating parameters; step 5, task allocation: using a genetic algorithm to call an objective function to allocate bird repelling tasks to each unmanned aerial vehicle platform, and formulating a bird repelling sequence; 6, flight path planning: unmanned aerial vehicle group flight path autonomous planning based on an artificial field potential method is adopted, an ambush method bird repelling strategy is called to estimate the expected position and speed of each unmanned aerial vehicle, and finally flight path planning is realized; 7, effect evaluation: returning to the step 2 to collect information, evaluating the bird repelling effect, judging whether to continue the step 3 or not, and re-planning the task; the method has the advantages of multi-UAV collaborative bird repelling, bird repelling task allocation optimization, autonomous route planning based on artificial field potential and introduction of path optimization.

The invention provides a laying hen feeding scheme adjustment method and system based on moulting image recognition, and relates to the technical field of intelligent breeding, and the method comprises the steps: obtaining a multi-angle body surface image sequence synchronously collected by a plurality of laying hen individuals in a target chicken flock under a natural light condition; performing semantic segmentation according to the multi-angle body surface image sequence to obtain a feather contour segmentation map set; performing group feature joint extraction according to the feather contour segmentation map set to obtain a multi-dimensional feature tensor representing individual features and group distribution information at the same time; performing group state collaborative inference according to the multi-dimensional feature tensor to obtain a three-dimensional probability distribution vector; performing group nutrition demand mapping according to the three-dimensional probability distribution vector to obtain an optimal nutrition parameter combination suitable for the whole chicken flock; and generating a feeding scheme according to the optimal nutrition parameter combination to obtain a feeding instruction stream. The accuracy and adaptability of nutrition regulation and control in the moulting period are effectively improved.

The invention relates to the technical field of intelligent agriculture and computer vision, in particular to a small-sample high-density chicken counting framework based on a deep learning Mamba structure, which comprises a feature extraction network, a support-query enhancement module and a decoder. According to the method, a multi-scale feature extraction network based on a residual block (ResNet Block) is introduced, so that local detail information is effectively reserved; and then, a support-query enhancement module is constructed by introducing a Mamba structure, and context interaction between support features and query features is effectively enhanced by utilizing the long sequence modeling capability of linear complexity of the support-query enhancement module, so that the problems of individual overlapping and boundary fuzziness in a high-density chicken flock scene are solved. Experimental results on a PoultryCount real breeding data set show that the mean absolute error (MAE) and the root-mean-square error (RMSE) of the method are reduced compared with those of an existing method, and the chicken counting precision and generalization ability under the condition of a small number of labeled samples are remarkably improved.

The invention discloses a small target bird flock motion monitoring system, and belongs to the technical field of bird identification, and the system specifically comprises the steps: obtaining a millimeter wave radar echo signal, a laser radar point cloud data set and a visible light image of a target region; performing spatial clustering segmentation on the laser radar point cloud to generate target point cloud clusters, acquiring a three-dimensional convex hull vertex set for any target point cloud cluster, and mapping a centroid to a millimeter wave radar coordinate system; performing spectrum analysis on the radar echo signals based on the mapping coordinates to obtain Doppler features, and calculating the three-dimensional position of the spatial extremal region in combination with the three-dimensional convex hull vertex set; and mapping the three-dimensional position to a visible light image to generate a spatial constraint mask, extracting an image feature vector and a spatial feature vector, and finally inputting the two types of feature vectors into a classifier model to obtain a bird recognition result, thereby realizing the type recognition of the small target bird flock in a complex scene.

The invention discloses an AI intelligent bird repelling system and method based on multi-modal perception and dynamic deterrence, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining multi-source historical data of birds in an area, extracting bird activity attribute preferences, and generating an initial thermodynamic diagram of long-term activities of the birds; monitoring a bird activity track, a population category and a behavior mode in real time, and dynamically correcting the bird initial thermodynamic diagram to obtain a dynamically updated bird accurate activity distribution diagram; constructing a virtual simulation bird repelling model, obtaining an optimal bird repelling strategy, and generating a dynamic adaptive multi-mode cooperative deterrent instruction set; according to the dynamic self-adaptive multi-mode cooperative deterrent instruction set, a deterrent unit is issued, the deterrent reaction degree is monitored in real time, if it is displayed that the bird flock is effectively repelled, execution is performed according to the current strategy, if it is displayed that the current strategy is invalid or poor in effect, feedback is performed to the virtual simulation bird repelling model, and a new-generation upgrading strategy instruction is generated. The bird repelling device has the advantages that safe repelling of bird flocks is guaranteed, and the influence on the ecological environment is reduced.

The invention belongs to the technical field of radar detection, and discloses a bird positioning method of a quantum radar bird detection system, which is characterized in that quantum characteristics such as polarization state and phase of echo photons are accurately analyzed by means of a quantum state demodulation technology, and high-precision measurement of the flight time of the photons is combined, so that the resolution limitation of the traditional radar is broken through from the quantum level; the technical combination not only can capture fine actions such as wing flapping frequency and steering angle of birds, but also can exert remarkable advantages in a dense bird flock scene: by utilizing quantum state differences of echo photons of different birds, overlapping signals are decomposed into independent individual signals through a quantum state separation algorithm; the individual distinguishing problem caused by traditional radar signal aliasing is solved; in high-precision demand scenes such as airports and the like, small bird targets can be accurately locked, flight potential safety hazards caused by misjudgment are greatly reduced, and the system can physically resist copying and deception interference of the outside to quantum signals based on the quantum unclonable principle.

The invention relates to the technical field of bird strike prevention and control, in particular to an airport bird flock timely early warning prevention and control method and system based on radar monitoring, which can scan a monitoring area in real time by using a radar to obtain real-time dynamic data of bird flock activities, integrate the real-time dynamic data into a monitoring data set and send the monitoring data set to a cloud server. Generating spatial mapping data capable of reflecting spatial density distribution of bird flocks in the monitoring area and gathering hot spots, and defining a risk area; if it is judged that the bird flock enters the risk area according to the real-time dynamic data, dynamic adjustment parameters are generated, and a scanning strategy of the radar monitoring system is optimized and adjusted; and generating a real-time updated monitoring report according to the real-time dynamic data, further generating a prevention and control instruction data set, and generating a final response scheme. According to the technical scheme, the target area is monitored based on the radar, the data is accurate, the coverage range is large, the radar scanning strategy is adjusted after the bird flock enters the risk area, the data monitoring precision is improved, and the generated monitoring report is high in precision and timeliness.

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

The invention belongs to the technical field of computer vision and ecological monitoring, and particularly relates to a large-scale bird flock counting system and method based on pure synthetic data training. In a model training stage, a large-scale bird flock composite image and a pixel-level label thereof are used as a unique training set, and end-to-end training is performed on a point prediction deep learning counting network using VGG19-BN as a backbone network to obtain a trained bird flock counting model; in the model training stage, real world bird flock images to be counted are input into the trained bird flock counting model, the model directly outputs predicted bird individual position points, a final counting result of the bird flock is obtained by counting the number of prediction points with high confidence, and a bird flock density distribution diagram can be generated for visualization. The invention provides a method and a system for realizing real scene high-precision counting only through synthetic data training based on a point prediction network aiming at the technical problems of strong dependence of real labeled data and insufficient cross-domain generalization ability of a model in a bird flock counting task.

The invention relates to the technical field of artificial intelligence, and discloses a bird flock detection method and system based on a holographic staring radar, so as to improve the overall performance. The method comprises the following steps of: obtaining coordinate information and initial confidence of a detection frame of a potential bird flock target in each frame of radar distance-Doppler image based on a folov8 network model inserted with an X-CBAM attention mechanism; then identifying a single bird target for each detection frame by using a radar traditional CFAR detection method, fitting a two-dimensional elliptical broadening according to the distribution condition of each identified single bird, and obtaining a confidence correction value of each detection frame based on a ratio value of a short axis to a long axis of a fitted ellipse; and then correcting the initial confidence of each detection frame in each frame of image, which is obtained by the yov8 network model, as a potential bird flock target based on a confidence correction value to obtain the target confidence of each bird flock target in each frame of image.

The invention provides a Tibetan chicken intensive breeding health monitoring and early warning method and system, and relates to the technical field of computers, and the method comprises the steps: obtaining the three-dimensional motion and interval time sequence data of a Tibetan chicken flock in a breeding house, and the original chirp audio time sequence data; performing motion mode analysis according to the three-dimensional motion and the interval time sequence data to obtain a vector field sequence; carrying out stress level inference according to the vector field sequence to obtain a group recessive stress index; according to the group implicit stress index and the original chirp audio time sequence data, performing model construction to obtain a chirp-stress association model; acquiring real-time chirp audio data, and inputting the real-time chirp audio data into the chirp-stress correlation model for health state critical point prediction to obtain an instability precursor signal; and performing graded early warning according to the instability precursor signal to obtain a health early warning grade. According to the invention, prediction and early warning of health risks caused by group stress of the Tibetan chickens in an intensive breeding environment are realized.

The invention relates to the technical field of laying hen breeding, and discloses a laying hen breeding accurate feeding adjusting system based on big data cloud-side collaboration. The system comprises an environmental data acquisition module, a cloud edge collaborative analysis module, a multi-dimensional difference evaluation module, an abnormal area positioning module, a feeding strategy adjustment module and an encryption communication link module. The environment data acquisition module acquires chicken flock multi-source data streams through various sensors, and standard chicken flock data is generated after processing; a cloud-edge collaborative analysis module constructs a dynamic feed supply model according to the dynamic feed supply model and outputs theoretical feed demand; the multi-dimensional difference evaluation module performs multi-dimensional comparison on the theoretical value and the actual consumption value to generate a feed difference coefficient matrix; the abnormal area positioning module generates an abnormal feeding probability distribution diagram in combination with farm topological information; the feeding strategy adjusting module generates a self-adaptive feeding control signal based on the graph; the encryption communication link module transmits a control signal to an actuator through a quantum encryption channel. The system realizes accurate adjustment and safety control of feeding for laying hen breeding.

The invention discloses a bird flock oriented repelling path planning method based on a Maklink intelligent airport bird repelling system, and the method comprises the steps: S1, recognizing the surrounding environment of an airport through a radar and photoelectric equipment, carrying out the environment modeling based on a Maklink link diagram theory, and generating a two-dimensional environment model; s2, based on the two-dimensional environment model, planning a repelling path of the airport intelligent bird repelling system by adopting an APF-RRT algorithm, determining path points of bird flock flight, and generating a bird repelling path set; and S3, optimizing the bird repelling path set based on a preset probability function, increasing the probability that the path passes through the safe target area, and generating a guidance repelling path. The guidance bird repelling effect is achieved, it is ensured that the bird flock leaves the airport area according to the expected direction, and therefore the success rate and safety of bird repelling are improved.

The invention discloses a method for rapidly obtaining chicken flocks capable of simultaneously resisting five kinds of subgroup avian leukosis and application, and belongs to the technical field of poultry disease-resistant breeding. The method comprises the following steps: firstly, obtaining primordial germ cells of a donor chicken containing an anti-avian leukosis subgroup genotype I and an anti-avian leukosis subgroup genotype II through in-vitro separation and cultivation, then injecting the primordial germ cells of the chicken into chick embryo blood vessels of a receptor chicken with wild type tvas / s and tvbs / s genotypes, performing incubation and cultivation, performing genetic typing, and finally obtaining the chicken with the anti-avian leukosis subgroup genotype I and the anti-avian leukosis subgroup genotype II. And finally obtaining chicken flocks capable of simultaneously resisting five kinds of subgroup avian leukosis. The method optimizes a chicken primordial reproduction in-vitro efficient culture system, can quickly obtain different chicken flocks capable of simultaneously resisting five kinds of avian leukosis subgroups, can be applied to utilization and preservation of resistance germplasm resources of excellent chicken breeds in China, can be applied to breeding of disease-resistant chickens of different breeds, greatly shortens the period of traditional poultry anti-avian leukosis breeding, and has a wide application prospect. The novel technology has good application value and popularization prospect.

The invention relates to the field of breeding duck breeding monitoring, in particular to a breeding environment intelligent monitoring method and system for breeding duck breeding. According to the system, firstly, concentration data of different gases at different monitoring points of a breeding duck farm and temperature data, humidity data and noise intensity of the monitoring points are obtained in real time; according to the temperature data and the humidity data of the monitoring points at the current moment, the distribution of the noise intensity of each monitoring point at the current moment and the distribution of the noise intensity of the monitoring points in the reference time period, the duck group activity density of each monitoring point at the current moment is obtained, and the airflow intensity and the airflow direction of each monitoring point at the current moment are analyzed; and in combination with the concentration data of various gases at each monitoring point at the current moment, an environmental pollution accumulation coefficient at the current moment is obtained, and real-time early warning is carried out on the environment of the breeding duck farm. According to the invention, the local accumulation phenomenon of harmful gas in the breeding duck farm can be effectively monitored, and the accuracy of breeding duck breeding environment monitoring is improved.

Techniques are disclosed for systems and methods to provide wildlife feeding flock detection using a remote sensing imagery system. A remote sensing imagery system includes a radar assembly mounted to a mobile structure and a coupled logic device. The logic device is configured to receive radar returns corresponding to a detected target, determine a radial velocity spectrum associated with the detected target based, at least in part, on the received radar returns, and determine a probability the detected target includes a feeding flock based, at least in part, on the determined radial velocity spectrum. The logic device may generate radar image data based on the received radar returns, the determined radial velocity spectrum, and / or the probability the detected target includes the feeding flock. Subsequent user input and / or the sensor data may be used to adjust a steering actuator, a propulsion system thrust, and / or other operational systems of the mobile structure.

The invention relates to the technical field of ecological monitoring and computer vision, and particularly discloses a large-scale bird flock automatic labeling synthetic data generation method and system. The technical problem to be solved is to overcome the defects that in the prior art, the acquisition cost of large-scale bird flock counting task annotation data is high, the quality is difficult to guarantee, and the authenticity and scale of synthetic data are limited. According to the technical scheme, the method comprises the following steps: based on acquired real small-scale bird flock three-dimensional trajectory data, performing group scale expansion by using a collective motion model such as an inertial spin model, and generating a large-scale bird flock three-dimensional motion trajectory; a pre-established three-dimensional bird model and a flight animation are endowed with the motion trail, rendering is performed in a virtual rendering engine, and an initial synthetic image and a corresponding pixel-level precise labeling mask including a binary mask of the whole bird flock and an instance segmentation mask of each individual are generated; and performing visual reality enhancement processing on the initial synthetic image, migrating the real bird texture to the synthetic bird through style migration, and fusing the mask and the real background image to generate a final synthetic image with high reality, and strictly maintaining the integrity of the annotated mask at the same time. The method is mainly used for automatically generating precisely labeled and highly realistic large-scale bird flock images, provides efficient data support for bird flock automatic counting model training, and can be applied to ecological monitoring and protection.

The invention relates to the technical field of clothes treatment, in particular to a control method of clothes treatment equipment, the clothes treatment equipment and a control device, and aims to solve the problem that the clothes treatment equipment in the prior art is high in flock cleaning energy consumption. In order to achieve the purpose, the control method for clothes treatment comprises the steps that the amount of soft flocks is obtained; when the flock amount is larger than or equal to a first flock set value, the water inlet valve is controlled to be opened; controlling the circulating pump to start; when the soft flock amount is smaller than a second soft flock set value, the circulating pump is controlled to be closed; and the water inlet valve is controlled to be closed. According to the control method, when the quantity of soft flocks exceeds a set value, the circulating pump is controlled to pump out the liquid in the treatment cavity and circulate in the circulating loop, and the inner wall of the treatment cylinder is flushed while the liquid circulates, so that the soft flocks are removed; the flocks can be quickly cleaned under the common cleaning action of the liquid in the processing cylinder and the liquid driven by the circulating pump to circulate, so that the cleaning efficiency of the flocks is improved while the energy consumption is reduced.

The invention relates to the field of electromagnetic interference defense, and discloses a configuration method of an electromagnetic haze bomb filling material and an electromagnetic interference method.The method comprises the steps that current bird distribution information in an airport no-fly zone is obtained, and the current bird distribution information comprises a plurality of bird flock activity areas and a center point corresponding to each bird flock activity area; acquiring current meteorological data (wind speed and wind direction) of an airport and an electromagnetic haze elastic energy parameter (effective diffusion time), and determining an effective diffusion distance after the electromagnetic haze bomb is released; according to the center point, the wind direction and the effective diffusion distance corresponding to each bird flock activity area, determining an optimal release point and generating a launching instruction; and the optimal release point and the launching instruction are sent to an electromagnetic haze bomb launching control end, so that the electromagnetic haze bomb launching control end executes the electromagnetic haze bomb launching operation, and the filling material of the electromagnetic haze bomb is configured through the configuration method in the claim 1. Therefore, safe operation of aviation equipment is guaranteed.

The invention discloses a close following control method and system for a spherical airship robot under strong airflow disturbance. The method comprises the steps that a close following three-dimensional kinematics model is established; establishing a bird flock-imitating close following aerodynamic influence model; establishing a spherical airship space dynamic equation; establishing collision detection auxiliary control based on a touch sensor; and constructing a model prediction close following control equation. According to the method, a bird flock formation strategy is used for reference, a dynamic model fused with aerodynamic characteristics, touch sensor collision detection auxiliary control and an accurate model prediction control algorithm are constructed, and the technical defects that a traditional control method cannot effectively establish aerodynamic interaction between airships and the problem of tight flight collision is caused by missing positioning data are overcome; stable airship close following control is achieved, and technical support is provided for a multi-airship cooperative task in a small-space complex scene.

This invention relates to the field of migratory bird distribution detection technology, specifically disclosing a method for detecting migratory bird distribution in wetland protected areas based on image sensors, including the following steps: Step S1: Divide the protected area into several sub-regions, set up image acquisition points in each sub-region, acquire migratory bird images in real time, identify the instantaneous number of migratory birds in the images, and simultaneously record the acquisition timestamp and acquisition coordinates; Step S2: Construct a spatiotemporal counting matrix based on the number of migratory birds at different times at each acquisition point, with acquisition coordinates as rows and time as columns, and obtain several basic spatiotemporal patterns and the corresponding linear weights of each pattern through matrix decomposition; Step S3: Based on the change of the linear weights of each basic spatiotemporal pattern over time, identify the migration events of migratory bird flocks between sub-regions, combine the migration events with the spatial distribution preference vectors of each pattern, determine the migratory bird flock gathering areas and migration channels, and generate the final distribution detection results.

The invention relates to a GPNMB gene molecular marker related to pigeon chest breadth character and application of the GPNMB gene molecular marker, and belongs to the technical field of biology. According to the GPNMB gene molecular marker related to the pigeon chest width character, the nucleotide sequences of SNP primers corresponding to the molecular marker are shown as SEQ ID NO: 1 and SEQ ID NO: 2, the site of the molecular marker is located at the 129265233rd base of a chromosome 2 of a pigeon reference genome ClivNAU1.0 version, and the base is mutated into C or T. By eliminating C / C and C / T genotype individuals and retaining T / T genotype individuals, the molecular marker has the beneficial effects that the molecular marker is used as a genetic marker for breeding pigeons, and the pigeons with wide and uniform chest width are bred; the pigeon breast width character can be efficiently and rapidly identified, the uniformity of the pigeon breast width is improved, a scientific basis is provided for early breeding of pigeons, and pigeon breeding is better served.

This invention discloses a method and system for analyzing the health status behavior of poultry flocks from images, relating to the fields of computer vision and smart farming technology. The method includes: firstly, acquiring monitoring images and extracting the poultry's location coordinates; secondly, dividing the poultry into an active first target set and an inactive second target set based on displacement features; thirdly, constructing a discrete topological network using the first target set to generate candidate spatial gap regions and identifying edge targets; fourthly, generating a biological rejection intensity index based on the head orientation vector of the edge targets, and determining stable rejection regions based on temporal stability; and fifthly, outputting a health anomaly warning when the center of the stable rejection region and the coordinates of the second target set satisfy spatial matching conditions. This invention effectively solves the problem of distinguishing between physiological quiescence and pathological stagnation in high-density farming by analyzing the group's biological rejection behavior to pinpoint abnormal individuals, thus improving monitoring accuracy.

The invention provides a breed selection method for selecting chicken combining ability based on a family heterosis rate, and belongs to the technical field of breeding, the breed selection method comprises the following steps: constructing a pure line subculture group, a progeny determination group and a combining ability determination group by using a commercial line variety with more than two lines; constructing a family heterosis rate by using the average value of the sum of the descendant measured average weight of the combining ability measuring paternal line and the descendant measured average weight of the combining ability measuring maternal line and the average weight of the combining ability measuring group, and selecting seeds according to the family heterosis rate. The invention provides a determination scheme for determining the combining ability of the pure-line individuals, creates a method for quantifying the combining ability and evaluation indexes, establishes a new method for improving the combining ability of the pure-line chicken flocks through breeding, eliminates the influence of the self weight difference of the pure-line individuals on a combining ability determination result, and enables the combining ability of the pure-line groups to be compared in the same dimension.

The invention discloses a breeding method of high-yield laying hens, and belongs to the technical field of chicken breeding. The method comprises the following steps: S1, environment monitoring and comfort calculation; s2, individual feeding amount calculation and feeding; s3, chicken flock behavior monitoring and welfare optimization; s4, regulating and controlling flavor and taste; s5, health and safety monitoring; s6, performing digital twin closed-loop optimization; and S7, carrying out actual breeding according to a breeding strategy generated by the digital twin system. According to the method, the environment, feeding, behaviors, welfare, flavor and health are dynamically predicted and regulated through the digital twin chicken flock model, closed-loop optimization of the whole breeding process is achieved, the chicken flock is always in the physiological and environmental state close to the optimal state, and therefore the laying rate is remarkably increased, and the breeding cost is reduced. The phenomenon of egg laying reduction caused by environmental fluctuation, insufficient nutrition or stress reaction is reduced.

The application discloses an intelligent inspection management system and method for large-scale chicken breeding, and relates to the technical field of breeding management. In the process of artificial one-by-one inspection of chicken flocks, the inspection results of each type are recorded, and the high-spectrum image of the tail feather of the chicken and the call recording of the chicken are synchronously collected; the high-spectrum image features of the tail feather of the chicken and the audio features of the call recording of the chicken under the inspection results of each type are classified and extracted; the correlation calculation is performed, and the high-spectrum image feature range of the tail feather and the audio feature range of the call recording corresponding to the inspection results of each type are classified; the high-spectrum image of the tail feather and the call recording of the chicken in the breeding farm are batch-collected and the features are extracted, the high-spectrum image feature range of the tail feather and the audio feature range of the call recording corresponding to the inspection results of each type are compared, and the inspection results of the chicken are batch-obtained. The application realizes batch intelligent detection management of the chicken for large-scale breeding.

The invention discloses electric driving type fluff extraction equipment, which belongs to the technical field of wormwood processing, and comprises a machine body assembly, a fluff extraction device, a fluff extraction device and a control device, the electric driving assembly is assembled on the machine body assembly and provides electric driving force; the electric driving assembly comprises a rotary driving assembly, a power driving assembly and a lifting assembly, the rotary driving assembly and the power driving assembly are assembled on the machine body assembly, and the power driving assembly is partially assembled on the rotary driving assembly and drives the rotary driving assembly to rotate; the lifting assembly is driven to lift back and forth; the down lifting assembly is assembled on the machine body assembly, and the lifting assembly is assembled on the down lifting assembly and drives the down lifting assembly to lift down in a reciprocating mode; compared with the prior art, the flock extraction speed of the flock extraction head is uniform, and the flock extraction quality of folium artemisiae argyi can be improved.