496 results about "Beef cattle" patented technology

The invention discloses a feed regulation and control method and system for beef cattle breeding, and relates to the technical field of feed regulation and control, and the method comprises the steps: carrying out grouping management according to individual differences of beef cattle, and collecting feed component data, growth stage data and climate environment data of beef cattle breeding in each group in real time; on the basis of the feeding and defecation amount of the beef cattle, the nutrient substance digestion and metabolism capacity of the beef cattle is evaluated, a dynamic feeding model driven by multi-modal data is constructed, and a feeding mode and an optimal feed ratio are matched; the optimal feed proportion is converted into a control instruction, and equipment is driven to execute feed blending and feeding; beef cattle growth condition data are monitored in real time, and the feed ratio is optimized according to actual deviation feedback. According to the method, the cattle in different physiological states are finely distinguished, multi-dimensional data such as environmental parameters and metabolic capability evaluation are combined, a dynamic feeding model is constructed, the feed conversion efficiency and the stability of growth performance are remarkably improved, and healthy growth of the beef cattle is guaranteed through effective feeding management.

The invention discloses an intelligent beef cattle breeding monitoring management system based on whole industry chain data. The system comprises a data acquisition module which is used for deploying sensors and data acquisition terminals in each link of a beef cattle whole industry chain for data acquisition; the data transmission and integration module is used for transmitting data acquired in each link to a cloud data center for processing by using a wireless communication technology; the intelligent analysis module is used for mining the integrated data and adjusting breeding processes such as seed selection and matching, a nutrition formula and a management strategy; the monitoring and early warning module is used for setting a key index threshold value, and when the key index exceeds the threshold value, the system automatically sends out early warning information to a mobile phone terminal or a computer client of a culture worker; and the breeding decision support module is used for providing guidance for the breeding direction according to long-term accumulated data and analysis results and screening out good beef cattle individuals and families thereof. The system has the advantages of high breeding efficiency, high beef cattle variety improvement speed and the like.

The invention belongs to the technical field of bioinformatics, particularly relates to a computer simulation and regulation method and system for beef cattle fat metabolism, and aims to solve the problems of excessive fat deposition, low feed conversion efficiency, difficulty in multi-objective optimization and the like in existing beef cattle breeding. A multi-scale biological network model is constructed, a computer simulation and prediction engine is developed, an intelligent intervention strategy optimization engine is designed, and implementation and feedback optimization are carried out. By reducing unnecessary fat deposition, improving the feed conversion efficiency and improving the beef quality, the economic benefit of beef cattle breeding is remarkably improved, the requirements of consumers for high-quality and safe beef products are met, and the method has important value for promoting intelligent upgrading and sustainable development of the beef cattle industry.

The invention relates to the technical field of cattle body measurement, in particular to a beef cattle body size measuring system based on image recognition. According to the technical scheme, the system comprises a multi-modal data acquisition module, a model construction and measurement module, a dynamic attitude estimation and compensation module, a multi-source data fusion module and a visual interaction module. According to the invention, a data basis is provided for subsequent processing through multi-modal data fusion, the attitude estimation accuracy is improved through the attitude estimation sub-module, and the accuracy of a body size measurement result is further improved through an improved ICP registration algorithm. The system can estimate and compensate the gestures of the beef cattle when the beef cattle are in various natural gestures through the dynamic posture estimation and compensation module, so that the accuracy of body size measurement is ensured, in addition, the visualization effect and interactivity of data are enhanced through the visualization interaction module, a user can conveniently find the abnormal gestures of the beef cattle in time, and the user experience is improved. A scientific decision basis is provided for the user, and the user is helped to better manage the breeding process of beef cattle.

The invention relates to the technical field of intelligent breeding, and discloses a beef cattle identification method based on multi-scale segmentation optimization and multi-modal data fusion, which comprises the following steps: acquiring beef cattle multi-modal image data, carrying out time-space synchronization and fusion to construct a fusion image, carrying out preprocessing of illumination invariant transformation and multi-scale pyramid construction, and carrying out multi-scale segmentation optimization and multi-modal data fusion on the fusion image; generating an enhanced image, inputting the enhanced image into a depth-guided attention segmentation network to extract double-branch foreground features, generating an initial segmentation probability graph, optimizing a segmentation mask in combination with a conditional random field model and a motion consistency constraint, finally extracting multi-dimensional features from the mask, inputting the multi-dimensional features into a multi-classification support vector machine to perform individual classification reasoning, and obtaining a final segmentation result. And obtaining a beef cattle individual identification result. Therefore, the foreground and background segmentation method applied to the intelligent breeding scene for beef cattle individual recognition is provided, the beef cattle individual recognition precision is improved, and meanwhile the management requirements of commercial breeding for high precision, high stability and multi-scene adaptability are met.

The invention provides a cattle behavior recognition method based on a three-axis attitude angle, and belongs to the technical field of intelligent animal husbandry management. According to the method, three-axis attitude angle signals such as the yaw angle (Yaw), the pitch angle (Pitch) and the roll angle (Roll) of the head of a cattle are collected in real time through a gyroscope sensor arranged in wearable equipment such as a cattle ear tag. The method does not depend on images, accelerometers, microphones or other modalities, only based on attitude angle signals, multiple algorithms such as a time sequence sliding window, frequency domain analysis, weighted scoring, sudden change detection and state transition modeling are utilized, and multiple typical behaviors such as ingestion, rumination, water drinking, bed lying, limping, licking, fright jumping and low activity are recognized. The method is suitable for multiple cattle breeds such as dairy cattle, beef cattle and buffalo, has the advantages of low power consumption, lightweight calculation, low deployment cost, accurate identification and the like, and is convenient for realizing behavior monitoring and health management of large-scale cattle individuals. The algorithm path can be flexibly selected, but a core input signal is only limited to attitude angle data, so that the technical boundary of the patent protection of the method is formed.

The invention discloses a beef cattle whole industry chain management method and device based on digital twinning and a medium, and the method comprises the steps: collecting physiological data in real time through an intelligent wearable device worn on a beef cattle individual, and collecting environment parameters of a farm, a transport vehicle and a processing line through an environment sensor; the physiological data and the environmental parameters are transmitted to a cloud end to construct a digital twinborn model of the beef cattle individuals, the beef cattle variety, genetic information and real-time physiological data are fused through the digital twinborn model, and the weight gain curve and health risk of the beef cattle individuals are dynamically predicted; dynamically optimizing the industry decision instruction of the beef cattle individual through a reinforcement learning algorithm based on the weight gain curve and the health risk; and adjusting an actual production flow based on the optimized industry decision instruction, recording whole industry chain data of the beef cattle individuals based on a block chain technology, and generating a corresponding traceability chain for querying a whole life cycle file of the beef cattle individuals.

The invention relates to the technical field of behavior feature recognition, in particular to a beef cattle oestrus state monitoring method based on dynamic gait analysis. According to the method, multi-source data acquisition, such as dynamic gait video and body temperature data, video preprocessing, such as frame extraction, denoising, abnormal frame recognition and restoration, target tracking, dynamic gait characteristic parameter extraction, such as step length, step frequency, step speed, joint angle change and body gravity center offset, and life data acquisition, such as diet, body weight change and drinking water. A large oestrus monitoring and recognition model integrating attitude analysis, behavior analysis, living state analysis and an integration module is constructed, and after training and iterative optimization, accurate judgment of oestrus, non-oestrus and wig oestrus states of beef cattle is achieved in combination with ear tag identity recognition. By monitoring the dynamic gaits and behavior modes of the beef cattle and combining daily life data of the beef cattle, the problem of misjudgment caused by wig oestrus is greatly avoided, and the monitoring accuracy is improved.

The invention belongs to the technical field of animal breeding, and particularly relates to a molecular marker closely linked with beef quality characters, a primer pair, a detection reagent and application. The nucleotide sequence of the molecular marker is shown as SEQ ID NO.1, the nucleotide shown as SEQ ID NO.1 has G / A polymorphism at the 831th bp, when the genotype of the 831th site from the 5'end of the molecular marker is GG, the meat color brightness and intramuscular fat content of an individual are higher than those of a GA genotype individual, and the cooking loss of the individual is lower than that of the GA genotype individual, and the molecular marker can be used for selective breeding of high-quality beef cattle.

The invention relates to the technical field of biological fermentation devices, and particularly discloses an efficient fermentation device for beef cattle feed processing, the efficient fermentation device comprises a fermentation tank, the upper end of the fermentation tank is fixedly connected with a feeding pipe, the upper end of the fermentation tank is provided with a pressure stabilizing assembly for exhausting, and the inner surface of the fermentation tank is fixedly connected with a guide seat; the pressure stabilizing assembly comprises a fixing cover fixedly connected with the outer surface of the upper end of the fermentation tank, notches are symmetrically formed in the outer surface of the fixing cover, and a sealing plate is slidably connected to the inner surface of the fixing cover. By arranging the pressure stabilizing assembly, the gas in the fermentation tank can be discharged in time according to the pressure change of the gas in the fermentation tank, so that the pressure in the fermentation tank can be maintained in a proper range, the risk that the fermentation tank is burst by pressure can be reduced, and meanwhile, the stability of the fermentation tank in the working process can be improved; furthermore, the fermentation quality of the cattle feed can be ensured, and the workload of manual exhaust of workers can be reduced.

The invention belongs to the technical field of animal molecular markers, and particularly relates to an SNP molecular marker for beef cattle flavor character breeding and application of the SNP molecular marker. The invention proposes that genotype polymorphism of 84181318bp and 84181699bp on chromosome 3 of an international bovine reference genome AR-UCD1.2 version is related to the character of the content of the beef arachidonic acid for the first time, the genotype polymorphism can be used for evaluating the content of the beef arachidonic acid, and beef cattle with specific genotypes at the two sites has relatively high content of the beef arachidonic acid. The site can be used as a molecular marker for evaluating the content of the arachidonic acid in the beef cattle, early prediction and auxiliary screening of beef cattle individuals with excellent meat quality and flavor characters, and a theoretical basis and a technical support are provided for breeding of the beef cattle with high content of the arachidonic acid in the beef cattle.

The invention relates to the technical field of beef cattle breeding, and particularly provides a beef cattle meat percentage prediction method and system based on dynamic physiology and AI three-dimensional body size fusion, and the method comprises the following steps: obtaining the real-time three-dimensional body size data of a target beef cattle, inputting a pre-training AI weight estimation model to obtain the real-time weight data, and carrying out the timestamp association; acquiring dynamic physiological data, and integrating the dynamic physiological data with the body size and weight data associated with the time sequence into a multi-source time sequence data set; multi-source data space-time alignment is completed through a time sequence attention fusion model, time sequence causal association of body weight, physiology and body size changes is mined through an attention mechanism, and a fusion association feature set is generated; and inputting the feature set into a meat percentage prediction model, and outputting a result containing a meat percentage prediction value and a causal association basis. The method breaks through the limitation of traditional static prediction, dynamic high-precision prediction is realized, the causal basis can support the breeding decision, and the precise breeding level and breeding benefits are improved.

The invention provides a six-axis inertial data behavior identification universal platform method for cattle, pigs, sheep and other livestock, and is suitable for behavior monitoring and management scenes of various livestock and poultry animals. The method comprises the steps of animal identity and species recognition, corresponding behavior recognition template loading, six-axis data feature extraction, behavior judgment and state recognition, recognition result output, platform interface butt joint and the like. Uniform adaptation and efficient processing of different animal types and sampling strategies (including fixed frequency, intermittent sampling, event triggering and the like) are achieved through a modular structure and a parameterized configuration mode. The platform supports continuous expansion of newly added species and behavior templates, can be deployed on edge equipment or a cloud server, has low power consumption, high compatibility and cross-scene applicability, and is suitable for intelligent management requirements of health monitoring, oestrus recognition, abnormity early warning and the like of livestock such as dairy cattle, beef cattle, live pigs, sheep, goats and the like in a farm.

The invention discloses a beef cattle behavior recognition method driven by a multi-modal data fusion model. The method comprises the following steps: constructing a beef cattle behavior recognition video data set and a nine-axis acceleration text data set; constructing a comparative learning behavior recognition network and performing data processing to obtain fusion features; network training; constructing a time sequence dynamic pyramid contrast learning behavior recognition network, and performing data processing to obtain time sequence dynamic multi-modal fusion features; and beef cattle behavior identification is carried out by using the double-identification network. According to the embodiment of the invention, by introducing the comparative learning behavior recognition network and the time sequence dynamic pyramid comparative learning behavior recognition network, high-precision behavior recognition is realized in a real breeding environment, low calculation burden is also considered, and the system can flexibly and efficiently adapt to complex task requirements of various breeding scenes through combination of the two; according to the invention, both precision and efficiency are considered, the accuracy and robustness of identification are improved, and an efficient and stable behavior identification solution is provided.

The invention discloses a western China cattle parameter-free Bayesian genome selection method. The method comprises the following steps: step 1, constructing a reference group and measuring important classification characters; step 2, collecting blood from the western China cattle, preserving, extracting DNA, and performing genetic typing to obtain the genotype of each SNP site; step 3, for the individual Chinese western cattle, using plink2 software to associate the genotype file and the phenotype file to obtain summarized statistical data; partitioning each SNP site according to the position of a chromosome to obtain an LD reference file; 4, the summarized statistical data and the LD reference file serve as input files of a parameter-free Bayesian model, and an effect value of the SNP site is obtained through calculation; and multiplying the genotype vector of the candidate individual by the locus effect value vector to obtain a genome estimation breeding value. The invention aims to establish a breeding method for classification characters of the Huaxi cattle based on a parameter-free Bayesian genome selection technology, and provides a molecular breeding method for breeding high-quality Huaxi cattle so as to promote rapid development of beef cattle breeding industry.

The invention discloses a beef cattle straw feed preparation method based on compound strain synergistic fermentation, and relates to the technical field of feed processing, and the beef cattle straw feed preparation method comprises the following steps: screening bacillus, lactic acid bacteria and the like to construct an initial compound strain, and screening a high-degradation-ability strain combination through a directed evolution system (30-45 DEG C, pH 4.0-7.0, and lignocellulose 5-15g / L); the straw lignocellulose structure is destroyed through microwave-assisted pretreatment (the power is 200-800 W, and the time is 1-5 min); high-efficiency fermentation is realized through double-stage fermentation (the pH is reduced at 30-35 DEG C for 12-24 hours in the first stage, and stubborn components are degraded at 35-40 DEG C for 36-60 hours in the second stage) and intelligent regulation and control. According to the method, the content of crude protein in the straw is increased to 15.2%, the content of crude fibers is reduced to 19.8%, the degradation rate of lignocellulose reaches 62%, the quality of the feed is remarkably improved, and a new path is provided for recycling of agricultural wastes.

The invention provides a beef cattle multi-target tracking method driven by a dual-detection and pseudo-depth motion model. The method comprises the following steps: S1, constructing a beef cattle detection and multi-target tracking data set; s2, realizing a high-precision context sensing target detection teacher network (HP-CAOD-TN); step S3, training a high-precision context awareness target detection teacher network (HP-CAOD-TN); step S4, realizing an efficient context awareness target detection student network EC-CAOD-SN; step S5, carrying out model distillation; step S6, realizing a pseudo depth enhanced Kalman filter P-DEKF; and step S7, based on the target dual-detection network obtained in the step S5, using the pseudo depth enhanced Kalman filter P-DEKF in the step S6 to simulate the state of the target so as to perform pseudo depth motion model driving, and using a Hungary algorithm to perform frame-by-frame data association so as to jointly realize multi-target tracking. According to the invention, by introducing the high-precision context-aware target detection teacher network HP-CAOD-TN and the efficient context-aware target detection student network EC-CAOD-SN, high-precision target detection is realized in multi-target tracking, and low calculation burden is also considered.

The utility model relates to the technical field of beef cattle breeding devices, and provides a quantitative dosing device for beef cattle breeding disease prevention and control, which comprises a rack, and a notch is formed in the middle of the left side of the rack; a worker firstly drives beef cattle into the rack, then the worker starts a third motor to drive two sets of supporting blocks to synchronously move, so that a supporting plate can be driven to drive the beef cattle to ascend and descend, then the worker can start a first motor to drive two sets of limiting plates to play a role in clamping the two sides of the beef cattle, and the two limiting plates are combined to clamp the beef cattle; according to the technical scheme, the clamping device can clamp beef cattle of different sizes, the situation that the beef cattle are prone to being stimulated to be not matched during treatment is prevented, then a worker can start a constant delivery pump, medicine mixed with water can be pumped to an atomization spray head and then sprayed out, and therefore the effect of treating the beef cattle is achieved. The beef cattle can synchronously breathe atomized medicine when eating in the feeding trough, so that the utilization rate of the medicine is higher, and the waste of the medicine is reduced.

The invention discloses a method for preparing bovine MSTN gene editing cells by using CRISPR / Cas12i, and belongs to the technical field of biology. According to the invention, an sgRNA expression vector aiming at the bovine MSTN gene is constructed, and a CRISPR / Cas12i system is utilized to carry out precise gene editing on a specific target area of a first exon of the bovine primary fibroblast MSTN gene, so that mRNA of the MSTN gene cannot be normally transcribed, and MSTN gene deleted cells are obtained. Compared with other gene editing tools, the Cas12i system shows higher specificity and editing efficiency (improved by 3%-5%), and the off-target effect risk is effectively reduced. The prepared MSTN gene deleted bovine recombinant cell line is stable and efficient in editing efficiency, the cell expression level is not affected, the MSTN gene deleted bovine recombinant cell line can be widely applied to somatic cell cloning and microinjection preparation of double-muscle-hip beef cattle, and a new strategy is provided for beef cattle breeding.

The invention relates to the technical field of beef cattle information management, in particular to a beef cattle individual information management system. According to the technical scheme, the system comprises a data acquisition layer, a data transmission layer, a data processing and storage layer and an application layer, wherein the data acquisition layer is used for acquiring biological characteristics, physiological indexes, behavior information and breeding environment information of beef cattle; the data transmission layer is responsible for transmitting the data acquired by the data acquisition layer to the data processing and storage layer; the data processing and storage layer is used for cleaning, fusing, analyzing and storing the data transmitted by the data transmission layer; and the application layer is based on the processing result of the data processing and storage layer. Through accurate and comprehensive information acquisition, strong data processing capability, abundant intelligent application functions and guarantee of data safety and stability, fine management and scientific decision of beef cattle breeding are realized, breeding benefits and market competitiveness are improved, and development of the beef cattle breeding industry is promoted.

The present invention discloses the application of the MYLK gene and the CPSF2 gene in regulating beef intramuscular fat deposition, belonging to the field of genetic engineering technology. By studying the APA mechanism during cattle intramuscular fat deposition, the present invention found that during the IMF deposition process, the 3′UTR of the MYLK gene shortened and the expression level of the MYLK gene increased. During the shortening process, the miRNA involved in IMF deposition was lost, thereby regulating the reduction of IMF deposition; after the 3′UTR of the CPSF2 gene was shortened, its expression was also upregulated, regulating the reduction of IMF deposition. The research results of the present invention provide new theoretical support and technical guidance for the prediction of beef quality and the breeding of high-quality beef cattle, which is of great significance to promoting the development of animal husbandry and improving the production efficiency of animal husbandry.

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

The invention belongs to the technical field of image processing, and provides a cattle herd density abnormity early warning method based on multi-camera data fusion, which utilizes a multi-camera data fusion technology to convert cattle herd pixel data into two-dimensional coordinates in a unified coordinate system to form a beef cattle global movement track, and meanwhile, divides a field area according to grid units to form a beef cattle density abnormity early warning system. Calculating the density of each grid, delimiting the degree of congestion according to the density, calculating the characteristic values of the grids, introducing a logistic regression model, monitoring and labeling the grids with high characteristic values, combining the grid data and the global motion track, calculating the risk probability, making early warning arrangement according to the level of the risk probability, and counting the false alarm and missing alarm conditions. And retraining the model to complete closed-loop iteration.

The invention discloses a beef cattle multi-variety genome data analysis and management method and system, and the method comprises the following steps: data collection and integration: obtaining beef cattle original genome sequence data, building a genome data storage library, and adding a unique identification label for the data of each variety; performing data preprocessing and standardization: detecting variation points, performing standardization processing on the detected variation points, and meanwhile, performing encoding processing on genotype data of the variation points; multi-variety genome feature analysis: identifying beef cattle varieties with rich genetic diversity and relatively deficient beef cattle varieties, obtaining potential variety subgroups or variety combinations with similar genetic backgrounds, and mining character associated sites ubiquitous in different varieties or specific to specific varieties; and performing data visualization and report generation: performing visual display on a result obtained by analysis. According to the method, comprehensive, systematic and efficient analysis and management of beef cattle multi-variety genome data can be realized, and powerful support is provided for beef cattle genetic breeding.

The invention provides a compound feed for promoting beef cattle growth and improving meat quality and a production method thereof, and belongs to the technical field of feed preparation. The compound feed comprises the following components in parts by weight: 100 parts of basal feed, 7-10 parts of a functional additive and 0.3-0.5 part of disodium inosinate, and the functional additive comprises a postbiotic compound, a fatty acid regulating agent, a bacterium enzyme synergist and trace elements, wherein the metagen complex comprises a lactobacillus plantarum metagen extract and a bacillus coagulans metagen extract, the fatty acid regulating agent comprises conjugated linoleic acid glyceride and medium-chain fatty acid, and the bacterial enzyme synergist comprises beta-mannase and bacillus subtilis. According to the compound feed, the growth performance and the meat quality can be synchronously improved, and a reliable processing technical guarantee is provided for improving the growth performance and the meat quality of beef cattle.

The invention relates to the technical field of livestock measurement, in particular to a beef cattle body size intelligent measurement device and method, in the beef cattle body size intelligent measurement device and method, hoof joint point pixel coordinates are converted and angle differences are calculated in combination with a lexicographical sequence block reordering algorithm, identity binding codes are accurately generated, uniqueness and stability of beef cattle individual recognition are ensured, and the accuracy of beef cattle body size measurement is improved. The method effectively reduces the identification confusion risk when multiple beef cattle are measured at the same time, generates a simulation sample through local pixel block rendering and generative adversarial network, screens a sample according with a threshold according to authenticity scores, improves the sample richness, optimizes the coverage of a model training set, extracts body size fields and position coding values, and calculates correlation coefficients between fields. Low-correlation field pairs are removed, only high-correlation fields are reserved for cross combination, a modeling sample pool is constructed, the representativeness of samples and variable combination diversity are enhanced, and the fitting precision and popularization capability of a body size estimation model are improved.

The embodiment of the utility model provides an accurate feed feeding device, and relates to the technical field of feed feeding. The accurate feed feeding device comprises fixing frames, a plurality of connected feed storage boxes are installed between the fixing frames, a supporting plate is arranged on one side of each feed storage box, a movable plate is movably installed in each supporting plate, a discharging box is arranged on one side of each movable plate, symmetrical adjusting plates are arranged in each discharging box in a sliding mode, and baffles are arranged on the upper sides of the adjusting plates. According to the feeding device, the moving plate drives the discharging box to move to the lower side of the storage box for feeding through pushing of the first air cylinder, the two adjusting plates and the baffle are moved to the proper positions indicated by the proper scale marks according to the feed amount needed in the beef cattle breeding stage, and therefore feed can only enter the position between the two adjusting plates, quantitative and accurate feeding is achieved, and the feeding efficiency is improved. When the first air cylinder pushes the discharging box to move to the upper side of the feeding trough, the two sealing plates are far away from each other, then feed enters the feeding trough, and the feeding quality is effectively improved.

The invention relates to the technical field of image analysis, in particular to a beef cattle feed intake intelligent monitoring and analysis method based on a video stream, which comprises the following steps of: converting a single-frame beef cattle house RGB image in the video stream into a logarithmic chroma space; according to the method, the chromaticity space conversion is performed on the single-frame cowshed RGB image and the illumination and reflection components are separated, so that the shadow interference can be suppressed, the feeding trough area is more stable in the image, the shadow suppression feeding trough image is divided into overlapped blocks, and local structure features and visual saliency features are calculated to generate a priority matrix; the local enhancement process can be adjusted according to actual feature distribution instead of a single global index, the flexibility and accuracy of the local area in contrast adjustment are improved, the self-adaptive contrast limit amplitude is set for different blocks in combination with the enhancement priority matrix, the distinction degree of the feed area and the background is improved, and the contrast adjustment accuracy is improved. And the texture and boundary features in the region are more prominent.

The invention belongs to the technical field of animal breeding, and particularly relates to a molecular marker closely linked with beef intramuscular fat traits, a primer pair, a kit and application. Nucleotide sequences of the molecular marker are shown as SEQ ID NO.1 and SEQ ID NO.2, the molecular marker has T / C polymorphism from the 76th basic group of the 5'end, and when the genotype of the locus is TC, the intramuscular fat content of beef of an individual is higher than that of the individual with the genotype of TT. The beef cattle with the high intramuscular fat content character can be screened or cultivated by utilizing the molecular marker.

The invention discloses excrement collection and treatment integrated equipment for a beef cattle farm, and relates to the technical field of excrement treatment, the excrement collection and treatment integrated equipment comprises a fermentation bin, the top of the fermentation bin fixedly communicates with a separation bin, one side of the fermentation bin and one side of the separation bin fixedly communicate with a filter pressing bin, and the bottom end of the side, away from the filter pressing bin, of the fermentation bin fixedly communicates with a drainage pipeline; the multi-separation assembly comprises a filter plate which is connected to the top end of the inner wall of the separation bin in a sliding manner; through the arrangement of the fermentation bin, the separation bin and the filter pressing bin, excrement generated in the beef cattle breeding process is treated step by step, the excrement is divided into solid matter and excrement water to be collected separately, and the follow-up resource utilization efficiency of the solid matter and the excrement water is conveniently improved; meanwhile, moisture contained in solids in the feces is completely removed, subsequent storage, transportation and reprocessing of the solids are facilitated, the separated liquid feces can also be directly used as crop irrigation objects, and the resource utilization rate is increased.