66 results about "Herd" patented technology

The invention discloses a zero-perception dairy cow behavior observation system based on AI vision, and the system comprises a data collection module which is used for collecting a video image through a monitoring camera; the image preprocessing module is used for generating a standardized image frame sequence; the visual Transform feature extraction module is used for outputting a space-time feature vector; the deep forest behavior classification module is used for behavior classification and label output; the behavior analysis module is used for generating a behavior track and group distribution; the model adaptive training module is used for periodic incremental training; and the abnormity early warning module is used for judging and outputting abnormal behaviors. According to the invention, cow behavior automatic identification and abnormity intelligent early warning based on AI vision are realized, and the management efficiency of a farm and the cow health guarantee level are improved.

The invention discloses a wild boar activity intelligent early warning and grading prevention and control method based on AI and thermal imaging, a sensing system carries out thermal imaging processing and camera shooting monitoring on wild boars in corresponding areas in the air through thermal imaging and camera shooting functions of an unmanned aerial vehicle, and a ground infrared camera array carries out infrared imaging processing on the wild boars around the ground; the sound sensor recognizes the sound of the wild boars, and the ground vibration sensor detects the running of the wild boars and the digging of the ground, and relates to the technical field of early warning, prevention and control of the activities of the wild boars. According to the wild boar activity intelligent early warning and grading prevention and control method based on AI and thermal imaging, a sensing module is arranged in a system, and an unmanned aerial vehicle module, a ground infrared imaging module, a sound recognition processing module and a ground vibration sensing module are matched with one another to perform thermal imaging processing on wild boars so as to obtain specific information of a wild boar group; subsequent driving and marking operations are facilitated while continuous monitoring is carried out, and the danger level of the wild boar herd is analyzed through the analysis module.

An autonomous herding system using a fleet of vehicles to manage and retrieve stray animals, combining technologies from U.S. Patents US 12102060 and US 12153451. The system employs autonomous vehicles equipped with optical-LiDAR sensors, GPS, and machine-learning image recognition to detect and guide strays back to the herd. Vehicles operate in two modes: roundup, for gathering scattered animals, and herding, for maintaining cohesion and directing movement. Positioned in traditional formations (point, swing, flank, drag), they use strategic movements, visual cues, and audio signals to influence herd behavior based on flight zone and point-of-balance principles. A trail boss module coordinates vehicle actions, ensuring efficient herd control. The system includes a battery replacement station for continuous operation, automatically swapping depleted batteries. This integration streamlines livestock management, reducing labor costs while improving animal and handler safety.

The present invention relates miRNA biomarkers from milk. e.g. exosome-derived microRNA from milk, as indicators of welfare in bovines. In particular, the present invention relates to the identification of heat stress in bovines allowing to propose management actions to improve productive animal welfare at the individual or the herd levels.

The present disclosure discloses an intelligent management method and management system of a natural pasture using multi-machine collaboration of UAVs, which belongs to the technical field of UAVs. The method includes: by a UAV group, obtaining pasture environment information, automatically planning a global grazing path, and performing automatic driving and grazing according to a user-defined grazing time, a starting point and an end point; during the process, collecting and analyzing herd activity images, and planning local grazing paths to assist in the automatic driving; and meanwhile, collecting vegetation coverage image data of a grazing area to further assist in the grazing.

Techniques and mechanisms for preventing resource starvation and service throttling during container orchestration system operations are provided. In a Kubernetes-based container orchestration system, pluggable mechanisms are applied to pod and / or associated container creation and operation at the direction of a cluster controller to prevent resource overloading and service throttling during thundering herd problems encountered by components of a Kubernetes cluster. A special-purpose plugin may be provided that causes creation of a pod and / or associated container according to a prescribed order to prevent caching overload and resulting thundering herd problems during pod and / or associated container creation and startup.

The application provides an ecological pasture cow breeding and health management method and system based on meteorological data, and relates to the technical field of cow breeding and health management. The method comprises the following steps: collecting meteorological data and cow breeding basic data in real time; extracting key meteorological factors affecting cow breeding; dividing meteorological suitable threshold corresponding to each breeding stage; realizing weather adaptation of cow herd screening; selecting temperature suitable period for mating operation; formulating meteorological guarantee scheme according to pregnancy stage; quantifying the influence of meteorological conditions on breeding core indicators, and optimizing breeding plan and resource allocation based on the evaluation results. Through the improved cow breeding management process, the application improves the utilization efficiency of breeding resources, provides a traceable and iterative analysis framework for breeding plan optimization, promotes the development of ecological pasture breeding management towards precision and high efficiency, and helps the pasture to reduce costs while realizing the double improvement of population quality and economic benefits.

This invention discloses the application of SNP molecular markers based on the STPG1 gene promoter in assessing bull semen quality. The SNP molecular markers include SNP2: g.-1220 T>C, where bulls with the CT genotype have significantly higher sperm motility and a significantly lower sperm abnormality rate than those with the CC genotype. In addition to SNP2, the invention also includes SNP1: g.-1234 G>A and SNP3: g.-1211 C>T. There are six haplotypes among SNPs 1-3. Compared to other haplotype combinations, bulls with H5H2 exhibit the highest sperm motility, while bulls with H3H2 exhibit the lowest sperm abnormality rate. These SNP molecular markers can serve as potential genetic markers for early identification of bull semen quality, which can not only improve breeding efficiency and reduce costs but also significantly enhance the overall reproductive performance of the herd.

Provided, according to one aspect of the present invention, is a method for analyzing incidents in a herd including a plurality of individual animals, the method comprising the steps of: grouping a plurality of individual animals on the basis of at least one criterion and extracting a reference behavior pattern for each group; generating information related to whether a current behavior is abnormal for each group with reference to the reference behavior pattern; and generating information related to an incident on the basis of the information related to whether the current behavior of each group is abnormal.

The invention relates to the field of molecular biology, and discloses a haplotype marker for dairy cow milk production butter-fat percentage character breeding and application of the haplotype marker, the haplotype marker is composed of three SNP sites in a strong linkage imbalance state, and the three SNP sites are located in a Block1 haplotype block region of a 10 # chromosome NC037337.1 of a dairy cow ARS-UCD1.2 genome; the three SNP sites are as follows: SNP1: g.59680573 A > C, SNP2: g.59743173 G > C, and SNP3: g.59743414 C > T; the dominant haplotype of the haplotype marker is H2, and the allele combination of the haplotype marker is SNP1-A, SNP2-G and SNP3-C; the homozygous H2H2 of the dominant haplotype H2 is significantly related to the high milk fat percentage character of milk production of dairy cows. The bottleneck of the traditional technology is solved, and the breeding accuracy is remarkably improved; the screening detection technical scheme is stable and reliable and has a wide application range; the milk production quality of groups is improved, and the industrial economic value is enhanced.

Techniques for measuring greenhouse gas emissions of ruminants after administration of a feed additive include receiving, by a server computer and within a reference period of time during which a cattle farm operates, feed ingredient usage data for each cattle type. The feed ingredient usage data includes an amount of feed provided for each cattle type and an identification of feed additives included in the feed. The feed additive is configured to reduce the emissions of greenhouse gases produced by each cattle in a herd that consumes the feed. The server computer also determines an estimated total amount of controllable greenhouse gas emissions of the cattle farm operation using a total controllable greenhouse gas emission model for the reference time period of the cattle farm operation with the feed ingredient usage data as an input to the model, which can be used to request carbon credits.

In particular, the present invention relates to a method for determining whether an animal and / or a progeny thereof is likely to have an increased heat resistance, an increased resistance to a wall lice, and / or a desired fur texture. It also provides methods for selecting or excluding an animal, one or more cells or embryos; estimating the value of the animal; producing an animal having a desired genotype / phenotype; cloning and breeding animals; and a method of forming a population.

This invention belongs to the field of black pig breeding technology, specifically relating to a method for breeding large-sized, high-quality black pigs. The method involves crossing purebred Songliao black pigs with purebred Berkshire pigs to obtain F1 generation hybrid pigs. The F1 generation hybrid pigs are backcrossed twice with purebred Songliao black pigs to obtain B2 generation hybrid pigs. The B2 generation hybrid pigs are then crossbred to obtain a basic breeding herd of black pigs. This basic breeding herd is then subjected to closed breeding and successive selection for at least six generations to obtain large-sized, high-quality black pigs. The large-sized, high-quality black pigs of this invention have a Berkshire bloodline content of 12.5%, retaining the high fertility and excellent meat quality of Songliao black pigs, while effectively introducing the growth rate and intramuscular fat deposition advantages of Berkshire pigs. The large-sized, high-quality black pigs of this invention have all-black coats, reach 100kg at ≤175 days of age, have a live intramuscular fat content ≥3.5%, and a litter size ≥10.5 piglets, and can be self-breeding.

A livestock management system for detecting, tracking, and responding to livestock location and physical parameters, and for determining livestock behavior and physical conditions correlated thereto. The system generally includes a plurality of tags and sensors attached to and implanted in a plurality of livestock, one or more local sensors, a management platform, and a remote computer system. Each tag receives, processes and maintains data regarding the location, activity and physical parameters of a livestock to which it is attached and locally determines the behavior and physical conditions of the livestock. The tags communicate with other nearby tags and sensors locally via dynamic mesh networks and with the management platform and remote computer system via longer range wireless networks. The management platform processes the tag data and produces herd-related data. The remote computer uses the tag data to generate and update livestock behavior and condition models for download to the tags.

This invention discloses an industrial park optimization scheduling method based on the wild horse herd algorithm, comprising: establishing a multi-energy resource model of the park and an objective function oriented towards minimizing the overall expected operating cost of the industrial park; constructing a multivariate joint probability distribution model of wind power, photovoltaic power, and load using the R-Teng Copula method to quantify source-load uncertainty and generate multiple typical scenarios; establishing a two-layer optimization model, with the upper layer taking the minimization of the overall expected operating cost of the industrial park as the global optimization objective, and the lower layer dividing the park into several aggregation units with the minimization of the operating cost of each unit as the local optimization objective; performing sub-problem optimization for each aggregation unit based on the wild horse herd algorithm and ADMM; and achieving optimized scheduling based on the charging and discharging power of energy storage units, the demand response reduction power of flexible units, and the output value of distributed units in each aggregation unit obtained through optimization.

The invention discloses a grass and livestock integrated intelligent management system and method with cooperation of grass original ecology protection and production. The system integrates a space-air-ground integrated monitoring network, a hybrid communication network, a cloud platform and an intelligent analysis model, and realizes comprehensive acquisition, transmission, analysis and decision of grassland environment, pasture growth and livestock behavior data; a scientific grazing scheme and graded early warning are generated through dynamic grassland bearing capacity evaluation, a livestock group optimization grazing strategy and a grass and livestock balance early warning model, and decision making, feedback collection and continuous model optimization are performed by means of an intelligent mobile terminal and an intelligent electronic fence system; according to the invention, the problems of disjunction of monitoring and execution, imbalance of grass and livestock and the like in traditional grassland management are solved, and intelligent cooperation and dynamic balance of ecological protection and animal husbandry production are realized.

The invention discloses a system for calculating the number of calves and the total value of calves in different sperm freezing schemes in a dairy farm, and relates to the technical field of animal husbandry production cost control, and the system comprises an input module, a calculation module and a display module. The input module is used for inputting group indexes, price indexes and different semen freezing schemes of a target dairy farm; the calculation module is used for respectively calculating the calf income except the surplus milk female calf quantity and the sperm freezing cost of the target dairy farm under different sperm freezing schemes based on the group index, the price index and the different sperm freezing schemes of the target dairy farm; wherein the calf income except for the frozen semen cost does not contain the calf income of the milk female calf; and the display module is used for displaying the calf income except the excessive milk female calf quantity and the sperm freezing cost of the target dairy farm under different sperm freezing schemes. The accuracy and the calculation efficiency of calculation of the calf number and the calf total value of different sperm freezing schemes are improved.

Provided is a dynamics prediction system that can predict the dynamics of a livestock group, which is a herd of livestock, in a form reflecting differences between individuals. The dynamics prediction system comprises: a storage unit that stores livestock group information including individual information of livestock constituting the livestock group, which is a herd of livestock, the number of individuals constituting the livestock group, health condition information of the individuals constituting the livestock group, and life-cycle information of the livestock; and a dynamics prediction unit that predicts the dynamics of the livestock group, including a change in the number of individuals, on the basis of the livestock group information stored in the storage unit. At least a portion of the number of individuals and the health condition information is managed on the basis of data acquired via sensors in the environment of the livestock.

An intelligent feed waste collection vehicle based on vision detection, belonging to the field of livestock machinery technology, includes a mobile chassis capable of moving along a preset path on the ground; a collection mechanism including a collection frame, a rolling main brush, a bidirectional auger, and a collection motor, wherein the collection frame is located at the front end of the mobile chassis, and the rolling main brush is rotatably mounted in the collection frame for brushing away feed waste on the ground; a conveying mechanism, one end of which is connected to the collection frame and is inclined upward behind the bidirectional auger; a storage bin, which is mounted on the mobile chassis, with the inlet of the storage bin corresponding to the output end of the conveying mechanism; and a feed waste detection module, including an image acquisition module and an image processing module. This collection vehicle firstly avoids manual operation, can know the feed waste status in different areas of the pen after the dairy cows have eaten, and accurately record it, which is beneficial for assessing the palatability of TMR formula, dairy cow feeding behavior, and even the health status of the herd.

The invention discloses a method and a system for improving functions of household alpine grassland. Investigating the current situation of the grassland by taking a family as a unit, and dividing the grassland into seven succession states according to an alpine grassland passive-active degradation succession theory; the grassland is improved by adopting rotation grazing, grazing reduction, interval pasturing, pasture population nutrition regulation, grass felt surface layer cracking and manual intervention recovery technologies; according to the annual grassland productivity, the number and structure of livestock groups are adjusted, and a function improvement technical system is constructed by combining family economy and grassland income dynamics. The method has the advantages that quantitative diagnosis of the degradation stage is realized by means of multi-parameter indexes and clustering analysis; through a long-term control test, screening effective technical combinations in each degradation stage; a family pasture ecological economic evaluation model is introduced, and an ecological target and herdsman income increase are both considered; a complete technical chain of diagnosis, testing, optimization and decision making is formed, dynamic adjustment can be achieved, and technology popularization standardization and adaptability unification are achieved.

The invention discloses a livestock group identity authentication method based on deep learning and target tracking, and relates to the field of modern intelligent livestock breeding, and the method comprises the following steps: obtaining livestock group image data, carrying out the preprocessing, and generating a labeled data set; training a target detection model, and outputting a detection result containing the position of the detection frame of the livestock group individual, the category confidence and the apparent feature vector; inputting a detection result into a target tracking model, continuously tracking the livestock group individuals, and outputting a unique identity identifier of each tracked individual and detection frame information corresponding to the unique identity identifier; individual areas are extracted from the original image sequence, and identity authentication of livestock group individuals is realized in combination with a pre-trained feature extraction network; and performing performance evaluation, and outputting an identification accuracy rate, a recall rate and an average precision index. According to the method, automatic and accurate identity authentication of the livestock group individuals is realized, and the efficiency and reliability of livestock group identity management in an actual scene are remarkably improved.

The present application relates to the technical field of intelligent collars, in particular to a distributed intelligent collar for monitoring the activity range of sheep herds. The intelligent collar comprises an intelligent terminal, a first fixing band and a second fixing band fixedly connected to the two sides of the intelligent terminal, an adjusting buckle fixedly connected to one end of the second fixing band, a collar band arranged in the adjusting buckle, and a buckling mechanism arranged between the collar band and the first fixing band. The buckling mechanism comprises a first connecting plate and a second connecting plate rotatably connected to one end of the first connecting plate. The buckling mechanism can distinguish between the instantaneous impact caused by the daily activities of sheep and the continuous pulling force caused by the hooking of foreign objects on the collar. When the sheep is firmly hooked by foreign objects and struggles to break free, the buckling mechanism actively disassembles to separate the collar from the sheep's neck, thereby avoiding suffocation and death caused by the tightening of the collar and reducing the economic losses of the breeder. The separation of the buckling mechanism is a mechanical unlocking, which can reduce the damage of the collar during the pulling process.

The utility model relates to the technical field of breeding equipment discloses a kind of guiding weighing pass devices for sheep, including base, the middle part of base top end is fixedly connected with protection frame, the left and right ends of protection frame are fixedly connected with protective fence, the inward one end of protective fence is fixedly connected with rotating seat, the inner wall of rotating seat is rotatably connected with rotating rod, the inward one end of rotating rod is fixedly connected with first fence gate, the top end of base is provided with first drive component in four corners, the left and right ends of protection frame are connected with second fence gate by second drive component, the inner wall of base top end is provided with weighing platform. In the utility model, first fence gate and second fence gate on both sides are closed and opened alternately, can be separated to sheep, and can guide sheep herd with protective fence, so that sheep can be sequentially and continuously weighed on the weighing platform inside the protection frame, without repeatedly pulling by artificial to avoid sheep running due to fright.

This invention provides a molecular marker associated with sheep weight traits and its application. Primers were designed based on the TNNT1 gene sequence to extract DNA from sheep blood. Through PCR amplification, DNA sequencing, and sequence analysis, a G / C polymorphism site was found at 176 bp of the amplified fragment. Further analysis using AQP primers detected the polymorphism site in 918 Hu sheep and established a least-squares model to analyze the association between genotype and weight traits. Ultimately, the TNNT1 gene fragment amplified by this invention was determined to serve as a molecular marker associated with sheep weight traits. By detecting the genotype of this molecular marker, this invention allows for the selection of GG homozygous sheep for breeding in the core herd, which can improve sheep weight and contribute to increased economic benefits.

A livestock management system for detecting, tracking, and responding to livestock location and physical parameters, and for determining livestock behavior and physical conditions correlated thereto. The system generally includes a plurality of tags and sensors attached to and implanted in a plurality of livestock, one or more local sensors, a management platform, and a remote computer system. Each tag receives, processes and maintains data regarding the location, activity and physical parameters of a livestock to which it is attached and locally determines the behavior and physical conditions of the livestock. The tags communicate with other nearby tags and sensors locally via dynamic mesh networks and with the management platform and remote computer system via longer range wireless networks. The management platform processes the tag data and produces herd-related data. The remote computer uses the tag data to generate and update livestock behavior and condition models for download to the tags.

Individual animals in a herd are identified using a first camera (140) that registers 3D image data (Dimg) of a back portion of a preselected individual (130). A database (160) stores reference data records, which each is associated with the identity of a parti- cular individual. The 3D image data (Dimg) is processed to extract data (Dext) describing anatomy / topology of the back portion of the individual (130); the extracted data (Dext) are matched against the reference data records; and an identity is assigned to the prese- lected individual (130) in response to a match between the extrac- ted data (Dext) and one of the reference data records, where the assigned identity is the identity associated with the matching re- ference data record. The reference data record for an individual is updated repeatedly if the 3D image data (Dimg) is obtained toge- ther with an independent identification (ID) the individual (130). However, such updating occurs if and only if at least one updating criterion is fulfilled, which relates to a physiology parameter (P), a behavioral parameter (B), a reproductive-cycle parameter (R) and / or a lactation-cycle-related parameter (L) for the individual (130) in question.

The utility model discloses a multifunctional neck clamp device for sheep, which belongs to the technical field of sheep breeding and comprises a cross rod, a vertical plate arranged on the lower side of the cross rod, a base arranged on the lower side of the vertical plate, a side plate arranged on the upper side of the base, a positioning plate arranged on the upper side of the base and a first limiting plate arranged on the upper side of the base. The inner side of the adjusting groove is connected with a second limiting plate in a sliding mode, a plurality of fixing grooves are formed in the inner side of the adjusting groove, fixing pieces used for fixing the second limiting plate are arranged in the fixing grooves, one side of the first limiting plate and one side of the second limiting plate are provided with limiting parts, and the limiting parts are used for limiting the sheep neck. And the neck clamp is not easy to properly adjust according to the sheep flock.

The present invention relates miRNA biomarkers from a bulk milk sample, e.g. exosome-derived microRNA, as indicators of welfare in bovines. In particular, the present invention relates to the identification of heat stress in bovines allowing to propose management actions to improve productive animal welfare at the herd level.

This application relates to the field of data monitoring technology, specifically to an environmental monitoring method, system, and medium for intelligent livestock farms. The method includes: collecting temperature and humidity data for each cattle shed at various times; pre-setting a time window and obtaining a temperature anomaly value based on the correlation between temperature and humidity data; obtaining a herd thermal activity index based on the fluctuation characteristics of temperature and humidity data within the time window for each cattle shed; obtaining an average temperature level based on the distance between each cattle shed and other cattle sheds, combined with the temperature data; obtaining a representative temperature value based on the difference between the temperature data for each cattle shed at various times and the corresponding average temperature level; and obtaining the monitoring results of the temperature data at the corresponding time. This application aims to improve the accuracy of environmental data monitoring in cattle farming.