791 results about "Pig breeding" patented technology

The invention discloses a pig breeding intelligent management and control system based on multi-modal data monitoring, and belongs to the technical field of pig breeding management, and the system comprises a data collection and individual recognition module which comprises an RFID ear tag, an inspection robot, an environment sensor and an intelligent feeder, and is used for determining the identity information of a pig individual based on the data collected by the RFID ear tag and the inspection robot, associating the collected multi-modal data of the live pigs in the pig house, and uploading the multi-modal data to edge computing equipment through an MQTT protocol for preprocessing; the feature extraction module extracts physiological and behavior features of live pigs by using a multi-modal deep learning fusion model; the key breeding index analysis module constructs a live pig health index and an environment quality index; the abnormity early warning module adopts a CUSUM control chart to accumulate index deviation and respond to abnormity; the management regulation and control model constructs a Markov decision process by minimizing energy consumption and maximizing health indexes, intelligently adjusts the rotating speed of a fan and a feeding strategy, and realizes precise environmental control and feeding optimization.

The invention discloses a real-time cost management and control method and system for a pig raising enterprise. The method comprises the following steps: collecting structured data of a whole breeding period of boars, piglets and pork pigs in real time; based on the structured data, real-time cost indexes of the boars, the piglets and the pork pigs are calculated through a preset algorithm; comparing the real-time cost index with a theoretical standard value based on experimental field data; comparing the real-time cost index with a future cost threshold predicted by machine learning; when the real-time cost index exceeds the theoretical standard value or the future cost threshold value, it is judged that the cost is abnormal; and executing a corresponding exception adjustment operation according to the type of the exception cost. According to the invention, the technical problems of fragmentization of data acquisition, lagging of cost accounting, insufficient anomaly detection precision and low manual response efficiency in the prior art are solved.

The invention relates to a pig breeding environment early warning management system and method based on the Internet, and the system comprises a data collection and processing module which is used for collecting the environment data of a pig house, the state data of pigs and the operation data of equipment, and carrying out the data processing; the data transmission and communication module is used for transmitting the data acquired by the data acquisition and processing module and sending early warning information to culture personnel; the model construction module is used for constructing an environment prediction model, a disease prediction model and a risk prediction model, and training the three models in combination with the data acquired by the data acquisition and processing module; the early warning management and analysis module is used for inputting the real-time data acquired by the data acquisition and processing module into the three models of the model construction module, analyzing corresponding early warning conditions and performing early warning management; the method is applied to the system. According to the invention, the overall level of the breeding industry is improved through a mode of adapting to the large-scale and intensive trend of pig breeding based on the Internet.

The invention discloses a black pig breeding disease intelligent monitoring management method based on big data, and relates to the technical field of animal husbandry intelligent management and animal disease monitoring, and the method comprises the following steps: obtaining multi-dimensional data information of pigs in a black pig breeding scene in real time through a sensor network, a video monitoring system and a physiological information collection device; the multi-dimensional data collected in real time is preprocessed and standardized, and the original data quality and the data analysis effectiveness are improved. According to the invention, by introducing an adaptive adjustment mechanism, the problem of pathological data loss caused by excessive elimination of abnormal values in the prior art is solved, and accurate retention and dynamic tracking of early disease signals of pigs are realized. The method integrates multi-dimensional feature extraction and intelligent evaluation, has pathological trend perception and processing strategy adaptive adjustment capabilities, effectively improves the early recognition sensitivity and discrimination accuracy of a disease early warning system, and provides more scientific health management support for farms.

The invention relates to the technical field of artificial intelligence, in particular to an intelligent pig raising and selling platform data analysis system integrated with a 4G camera, and aims to solve the problems of data semantic segmentation and space-time mismatching of an existing heterogeneous sensing system. The system comprises an intelligent sensing node deployed in a breeding place and a cloud data analysis platform. The intelligent sensing node integrates an individual identification unit, a multi-modal visual acquisition unit and an edge calculation unit, and realizes data source fusion and information extraction; the data analysis platform constructs individual digital twins, and performs multi-dimensional intelligent analysis through growth prediction, health anomaly detection, market transaction decision and other models. According to the scheme, accurate prediction and optimization decision making of the live pig individual full life cycle data are realized, and powerful support is provided for fine breeding management, health early warning and intelligent transaction.

The invention belongs to the technical field of animal breeding, and particularly relates to application of a detection reagent of an SNP (Single Nucleotide Polymorphism) molecular marker related to pork tenderness. An SNP site exists at the 232bp position from the 5'end of the sequence, the polymorphism is G / A, three genotypes of GG, GA and AA are shown, G allele is dominant allele, and the meat tenderness of a GG type individual is obviously higher than that of an AA type individual. The invention further develops a reagent for detecting the SNP molecular marker, the reagent can be used for pig assisted breeding, pig breeding or pork tenderness identification, and a method for identifying the pork tenderness is developed, which is beneficial to accelerating genetic breeding and early-stage seed selection of boars with high-quality meat traits.

The invention belongs to the technical field of feed additives, and particularly relates to slow-release fat powder for pigs and a preparation method of the slow-release fat powder. The slow-release fat powder for pigs comprises an intragastric adhesion-slow release layer, a small intestine forepart bile acid response controlled release layer and a small intestine posterior microbe response controlled release layer. The prepared slow-release fat powder for the pigs is good in stability, accurate release of different nutritional ingredients in different parts of gastrointestinal tracts of the pigs can be achieved, and powerful support is provided for sustainable development of the pig raising industry.

The invention discloses a pig breeding screening method and system based on a body type database, and particularly relates to the technical field of pig breeding screening. The system comprises a multi-modal sign data acquisition and integration module for collecting and standardizing heterogeneous data sources such as phenotypic signs, genomics and environmental parameters of breeding pigs in real time, and a multi-dimensional biological characteristic modeling and analysis module for analyzing a nonlinear action mechanism among genetic markers, phenotypic characteristics and environmental factors, the genetic potential intelligent judgment module is used for quantitatively evaluating spatial expression potential and intergenerational transmission probability of genetic advantages of the breeding pigs through a deep learning algorithm; and the intelligent screening and dynamic monitoring module is used for establishing a multi-dimensional threshold dynamic regulation and control mechanism to realize accurate elimination decision and continuous optimization of a germplasm resource library. According to the method, the screening accuracy is remarkably improved by designing multi-source data fusion and online optimization capability, meanwhile, mistaken elimination is reduced through a redundant superior species temporary storage management module, and collaborative improvement of population genetic diversity and environmental adaptability is ensured.

The invention relates to a primer of an RBP4 gene molecular marker related to pig weak litter number character and application of the primer, and belongs to the technical field of biology. The RBP4 gene molecular marker is located at the 105043789th base of chromosome 14 of a pig reference genome Sscrofa11.1 version, the base is mutated into A or G, and the genotypes are A / A, A / G and G / G. The number of weak piglets of the G / G genotype pigs is lower than that of the A / G and A / A genotype individuals, and the number of weak piglets of the A / G genotype pigs is lower than that of the A / A genotype individuals. According to the present invention, the forward and reverse primer pair is used to amplify the fragment containing the molecular marker site, and the amplification product is subjected to Sanger sequencing so as to rapidly and accurately identify the genotype of the individual; the molecular marker is used as a genetic marker for pig breeding to breed pigs with less weak piglets; the method can efficiently and accurately detect the weak piglet number character, improves the survival rate of healthy piglets of a pig herd, and has an important value for breeding and production of pigs.

The invention discloses a pig breeding monitoring and behavior intervention method and system based on improved YOLOv11, and relates to the technical field of intelligent breeding, and the method comprises the steps: collecting video data in a pig house in real time through a camera, carrying out the preprocessing, and extracting a key video frame; an improved YOLOv11 algorithm is adopted to construct a pig behavior detection model, key video frames are input into the model for feature extraction, multi-scale features are fused to enhance the recognition capability, a feature map used for behavior classification is generated, and accurate recognition of pig behaviors is achieved through a detection head; and judging whether a pig fighting behavior occurs in a short period according to the pig microscopic behavior characteristics, if so, triggering fighting early warning, when the pig fighting behavior is detected, triggering an intervention mode, and screening an intervention adjustment method from a management decision library according to the pig behavior state and the environment state. According to the invention, accurate identification and active management of pig behaviors are realized, and the identification capability of pig microscopic behaviors in a complex breeding environment is significantly improved.

The invention provides an ecological pig raising system based on intelligent monitoring and precise feeding, and belongs to the technical field of intelligent monitoring and precise feeding. According to the scheme, multiple types of sensors are deployed in a breeding environment, environment parameters are continuously collected, the collected environment parameters are preprocessed and preliminarily analyzed, and the environment parameters are analyzed to be detected; the processed environment parameters are sent to the central processing unit through the network transmission device, the central processing unit analyzes and evaluates the health state of the pigs, an individualized feeding plan is made according to the health state of the pigs, the behaviors of the pigs are monitored in real time, and abnormal conditions are responded. The problems that the quality of the breeding environment cannot be comprehensively known, and the safety and stability of data transmission cannot be guaranteed are solved.

The invention relates to a primer of a GAREM1 gene molecular marker related to the average daily gain character of pigs and application of the primer, and belongs to the technical field of biology. The GAREM1 gene molecular marker is located at the 116131455th basic group of chromosome 6 of a pig reference genome Sscrofa11.1 version, the basic group is mutated into A, and the genotypes are A / A and A / T. The average daily gain of A / T genotype pigs is higher than that of A / A genotype individuals. According to the present invention, the forward and reverse primer pair is used to amplify the fragment containing the molecular marker site, and the amplification product is subjected to Sanger sequencing so as to rapidly and accurately identify the genotype of the individual; the molecular marker can be used as a genetic marker for pig breeding to breed pigs with proper weight; the method can be used for efficiently and accurately detecting the average daily gain character of the pigs, and has an important value for breeding and production of the pigs.

The utility model relates to the technical field of dam spreading pig breeding, and discloses a pig house comprehensive environment automatic measuring device, which comprises a hanger rail and a breeding inspection machine, and the breeding inspection machine comprises a conveyor running on the hanger rail and an inspection box; an inspection camera, a programmable logic controller, an image analysis module, a sound recognition module, an environment sensing module, a communication module and a power supply module are mounted on the inspection box; the environment sensing module comprises a temperature and humidity sensor, an ammonia gas sensor and a carbon dioxide sensor; the environment parameters, such as temperature, humidity, ammonia gas and carbon dioxide concentration, of the pig house are monitored in real time through the sensors and automatically adjusted according to needs so as to maintain the optimal breeding environment, the breeding environment is optimized, healthy growth of pigs is promoted, diseases are reduced, the breeding quality is improved, an automatic system reduces dependence on manual inspection and management, and the breeding efficiency is improved. And the labor cost is reduced.

The invention relates to the technical field of intelligent breeding and logistics optimization control, and solves the technical problems of high energy consumption, unstable efficiency, unbalanced distribution, lack of an intelligent scheduling mechanism and the like in feed conveying of a multi-storey pig farm. The method comprises the following steps: acquiring static parameters (physical characteristics of feed, physical attributes of a conveying system and a pig house structure) and dynamic parameters (real-time feeding requirements, equipment and material states and external environment factors); establishing a multi-objective optimization model of a collaborative optimization energy consumption model E (x), a time model T (x) and a conveying balance degree model U (x); solving by adopting a genetic algorithm with a special design crossover and mutation operator to obtain an optimal scheduling scheme; in the execution process, a closed-loop self-learning calibration mechanism is started, actual power is measured through a current sensor, and when the deviation between predicted energy consumption and actual energy consumption exceeds a preset threshold value, efficiency parameters in the energy consumption model are reversely corrected through a gradient descent method; the weight coefficients of the three models are dynamically adjusted according to the real-time electricity price and the inventory state. The system adopts a three-layer architecture of a perception and data acquisition layer, a decision and control core layer and an execution layer. According to the method, multi-target collaborative optimization and intelligent adaptive scheduling are realized, the total energy consumption is effectively reduced, the transmission time is shortened, the distribution balance degree is improved, and the energy consumption prediction accuracy is remarkably improved.

The utility model discloses a feed mixing and stirring device for pig breeding. The feed mixing and stirring device comprises a mixing assembly, the stirring assembly comprises a hollow annular groove, a rotating disc, a gear ring, a driven gear, a supporting shaft, a driving gear, a rotating shaft, a rotating motor, a first stirring rod and a second stirring rod, the hollow annular groove is formed in the outer side of the bottom end of the cover plate, the rotating disc is rotationally connected to the inner position of the hollow annular groove, and the gear ring is fixedly connected to the bottom end of the rotating disc. The driven gear is meshed with the inner side of the gear ring. A stirring assembly is arranged, a rotating motor drives a rotating shaft to rotate, the rotating shaft drives a driving gear to rotate, the driving gear drives a gear ring to rotate reversely through a driven gear, and a second stirring rod at the bottom end of the driving gear and a first stirring rod at the bottom end of the gear ring rotate forwards and backwards in a feed barrel correspondingly; the feed is prevented from rotating along with the first stirring rod, and the stirring efficiency of the feed is improved.

The invention discloses a future pork pig group weight estimation method and system based on multi-model fusion, and the method comprises the steps: obtaining a historical structural data set of a pork pig breeding complete period, and employing a multi-modal fusion evaluation method of field priori knowledge weighted evaluation, data-driven feature importance calculation and an automatic code analysis tool. Extracting a key factor set influencing the weight of the pork pig, then based on the historical structured data set and the key factor set, respectively constructing an expert rule reasoning model, a data-driven prediction model and a code generation type dynamic model to predict the weight of the pork pig, inputting each model based on real-time data, and outputting a prediction value; weights are dynamically distributed according to historical errors, results are fused, abnormal values are removed in combination with discrete degree detection, and a final fusion prediction value is generated. The technical problem of improving the weight estimation accuracy of the pork pig group in the prior art is solved.

The invention discloses automatic manure cleaning and harmful gas detection equipment and method for a pig house, and relates to the field of pig breeding. The equipment comprises a robot, a control system, a manure cleaning device, a visible light camera, a multispectral camera and a harmful gas monitoring module, the visible light camera and the multispectral camera respectively obtain a visible light image and a multispectral image of the ground of the hog house unit; the control system identifies excrement based on the visible light image, plans an excrement cleaning path through deep reinforcement learning, and controls the excrement cleaning device to clean the identified excrement according to the excrement cleaning path; meanwhile, based on the visible light image and the multispectral image of the ground of the hog house unit, the health monitoring result of the hog in the hog house unit is output through a support vector machine. The harmful gas monitoring module monitors the concentration of harmful gas in the hog house unit in real time; the control system gives an alarm when the harmful gas concentration monitored in real time is larger than a concentration threshold value. The automation degree of hog house management can be improved, and the labor cost is reduced.

The invention belongs to the technical field of animal breeding, and particularly relates to application of a detection reagent of an SNP (Single Nucleotide Polymorphism) molecular marker related to pork quality traits. Basic groups at 208bp and 217bp from the 5'end of the sequence have synchronous C / T mutation, the sequence shows three genotypes of CC, CT or TT, T allele is dominant allele, and the intramuscular fat content of the TT type pig is greater than that of the CC type pig. The invention further develops a reagent for detecting the SNP molecular marker, the reagent can be used for pig assisted breeding, pig breeding, pork quality character identification or pork quality character screening, and a method for identifying the intramuscular fat content of pork and screening pork with rich intramuscular fat is developed.

The invention provides application of a pig STR molecular marker combination in pig individual identification, a kit and an identification method, relates to the technical field of biology, and develops an STR molecular marker combination for accurate identification of pig individual identification by applying a whole genome association analysis method for 18 wild boar varieties and 42 domestic pig varieties. By detecting the combination, individual identification and genetic identification can be accurately and efficiently carried out on a to-be-detected pig sample, and when the minimum set number of the selected STR marker is 6, individual distinguishing can be carried out. According to the scheme provided by the invention, by comprehensively analyzing the STR typing result, the parent-child margin determination and individual identification of the pig can be effectively carried out, so that the pedigree accuracy in pig breeding work can be improved, the breeding process is accelerated, and the method has good application prospects and economic values.

The invention belongs to the technical field of intelligent breeding and robots, and particularly relates to a pig house robot health monitoring and early warning system for a pig raising platform. The system aims to solve the problem of early warning lag caused by discontinuity of existing monitoring data. The system comprises a static sentinel node subsystem which is used for continuously collecting data at high frequency, generating an abnormal score and sending a triage request; the mobile diagnosis and service unit subsystem is used for performing autonomous diagnosis after receiving the request, acquiring individual accurate data and generating a report; and the central control and prediction subsystem is used for fusing data, constructing a space-time atlas model, predicting epidemic disease transmission and generating prospective early warning. By means of the system, 7 * 24-hour uninterrupted monitoring of swinery is achieved, data faults are solved, common screening-fine diagnosis cooperation is formed, a space-time diagram neural network is used for providing prospective early warning, and an epidemic disease prevention and control gateway is remarkably advanced.

The application relates to the technical field of ecological pig breeding, and through the structural setting of a breeding component, ecological pig breeding work is facilitated; a third control motor controls the rotation of a conducting belt, ecological pigs can move, stains are transmitted through the conducting belt, can be guided to the guide and discharge pipe and the grid guide and discharge seat for guiding and discharging, a pressurizing control seat controls the extension and retraction adjustment of a scraper through a hydraulic connection seat, so that the scraper can contact the conducting belt to clean the surface of the conducting belt, and an electric control hydraulic telescopic rod changes the height of a support rack through extension and retraction, so that the support rack drives the bottom supporting plate to move, so that the conducting belt, the fixed side block and the third control motor can move in coordination, facilitating maintenance work; through the structural setting of a massage processing component, ecological pig massage work is facilitated; a massage sleeve rod rotates on a bearing seat through a rotating control rod, can contact the ecological pigs to massage the ecological pigs.

The invention provides a multi-robot cooperative manure cleaning method and system and electronic equipment. The system comprises a communication server subsystem, a driving robot subsystem, an inspection robot subsystem, a manure cleaning robot subsystem, a main controller system, an environment monitoring robot subsystem, a two-dimensional code positioning subsystem and a disinfection robot subsystem. The method comprises the following steps: acquiring environment information in a live pig breeding area and position information of at least one excrement through an inspection robot; acquiring a cleaning path of the excrement cleaning robot according to the environment information and the position information of the at least one excrement, wherein the cleaning path passes through the position of the excrement; and finally, the manure cleaning robot is controlled to clean manure in the pig breeding area based on the cleaning path. The excrement in the breeding area is automatically cleaned, so that the breeding convenience is improved, the working efficiency is improved, and the labor cost of breeding is reduced.

The invention belongs to the technical field of molecular biotechnology and molecular markers, and particularly relates to an SNP molecular marker located on a pig RBFOX1 gene locus and related to ingestion behavior characters and application of the SNP molecular marker. An SNP site of the SNP molecular marker corresponds to the 35094559 Ggt on a chromosome 3 of a reference sequence of an international pig reference genome version 11.1; t mutation. By optimizing the dominant alleles of the molecular marker, the frequency of the dominant alleles can be increased generation by generation, the average daily ingestion times of pigs can be reduced, the average ingestion time of each time can be increased, and the feed conversion efficiency of the pigs can be improved. The breeding of the excellent boars with the characters is beneficial to accelerating the progress of genetic improvement of the boars and improving the economic benefits of pig breeding.

The invention relates to an application of an FOS gene in pig breeding for increasing pig spine number and rib number. The pig capable of increasing the number of spines and the number of ribs is an FOS gene knockout gene editing pig, the number of the FOS gene in an enmbl genome database is ENSSSCG00000002383, the preparation method of the gene editing pig comprises the steps that FOS gene knockout pig fibroblasts are prepared through a CRISPR-Cas9 technology, then the FOS gene knockout pig is produced through a somatic cell cloning technology, and the FOS gene knockout pig is obtained. And finally, selecting pigs with increased spine number and rib number from the FOS gene knockout pigs through phenotype identification. According to the method, the individual proportion of cloned pig fetuses with increased thoracolumbar vertebra number obtained by knocking out the FOS gene is 60%, it is proved that the FOS gene is a key gene influencing the thoracolumbar vertebra number on pig genetic breeding, and a gene edited pig with increased spine number and rib number can be obtained by knocking out the FOS gene, especially knocking out a second exon of the FOS gene.

The invention discloses an SNP (Single Nucleotide Polymorphism) molecular marker positioned on a No.15 chromosome of a sow and related to the lactation ability of the sow. The SNP site of the SNP molecular marker corresponds to the Agt at the 31884611bp position on the No.15 chromosome of an international pig reference genome version 11.1; g mutation; the genotype of the gene is AA, AG or GG. The SNP molecular marker provided by the invention is remarkably related to the sow lactation ability character, the identification of the sow lactation ability character can be realized by identifying the single nucleotide polymorphism of the SNP molecular marker and / or the genotype of the SNP molecular marker, and the dominant allele frequency can be increased generation by generation and the sow lactation ability can be improved by preferably selecting the dominant allele G of the SNP provided by the invention. The pig genetic improvement progress is accelerated, so that the economic benefit of breeding pig breeding is effectively improved.

The invention discloses a method for preparing live pig feed through mixed solid-state fermentation of feed rape and rapeseed meal. The method specifically comprises the following steps: harvesting feed rape from a full-bloom stage to a final bloom stage, adding rapeseed dregs, and uniformly mixing to obtain a fermentation substrate with the water content of 55-65%; spraying the compound enzyme bacterium preparation on the fermentation substrate, uniformly stirring, finally compacting by using a packer, sealing, packing and storing, and fermenting for 45 days; the compound enzyme bacterial preparation comprises a bacterial agent and an enzyme agent; the fungicide comprises lactobacillus plantarum, bacillus subtilis, saccharomyces cerevisiae and aspergillus niger; the enzyme agent is prepared from phytase, cellulase, hemicellulase, pectinase, tannase, xylanase and alpha-galactosidase. The feed rape and the rapeseed meal are subjected to mixed solid fermentation, so that the content of phytic acid, glucosinolate and crude fiber is greatly reduced, the content of crude protein is increased, and the nutritional quality of the feed is remarkably improved. The fermented feed is used for replacing part of corn, soybean meal and wheat bran, and the use amount of concentrated feed in live pig breeding is reduced.

The utility model discloses pig wet feed processing equipment. The pig wet feed processing equipment comprises a crusher, a plurality of bins, a batching scale, a mixer, a cooking pot and a feeding pot, the crusher is communicated with the stock bin through a pipeline, the stock bin is connected with the batching scale through a pipeline, the batching scale is communicated with the mixer, the mixer is communicated with the cooking pot through a pipeline, and the cooking pot is communicated with the feeding pot through a pipeline; the cooking pot comprises a pot body, a heater is arranged on the inner wall of the pot body, a steam inlet and a steam outlet are formed outside the heater, a stirring motor, a pressure release valve and a feed port are arranged at the top of the pot body, an output shaft of the stirring motor is in transmission connection with a stirring rod, and the feed port is communicated with the mixing machine; a discharge hole is formed in the bottom of the tank body and is communicated with the feeding tank. According to the utility model, the traditional pig raising wet feed scheme can be simulated, meanwhile, the aspects of automation, safety and the like are considered in the process engineering, and the process skips the granulating process of the pig feed, so that the feeding cost of farmers is reduced while the pig raising effect is considered.

The invention belongs to the technical field of precise environment control for pig breeding, and particularly relates to a method and system for pig breeding environment-behavior correlation modeling and cooperative regulation and control. The method comprises the following steps: S1, modeling an association mechanism of a multi-element environment factor and a pig abnormal behavior: fully mining the association between the multi-element environment factor and the pig abnormal behavior in an existing knowledge base by introducing a pre-trained large language model LLM, and modeling; s2, construction of an environment-behavior collaborative decision-making system guided by the large language model: constructing a multi-source real-time data acquisition system, synchronously acquiring and fusing environment and pig behavior data, and constructing the environment-behavior collaborative decision-making system based on the fine-tuned large language model for realizing multi-factor collaborative attribution and intelligent regulation and control. According to the method, the pre-trained large language model and the multi-source perception data are fused, and the method has the advantages that the processing efficiency can be guaranteed, and meanwhile accurate modeling and analysis of the complex environment-behavior relation can be achieved.

The invention relates to the technical field of live pig breeding, and discloses a live pig feeding device capable of feeding at fixed time, the live pig feeding device comprises an n-shaped main body frame, the bottom of the inner cavity of the n-shaped main body frame is provided with a driving wheel, the outer wall of the n-shaped main body frame is provided with a control computer, and the top of the driving wheel is provided with a feeding cleaning assembly. Through the arrangement of the sealing plug, when the sealing plug is in contact with the downpipe, water in the sealing shell can enter the feed adjusting pipe through the water inlet pipe to be mixed with dry feed and then enter the trough, when the sealing plug is in contact with the water inlet pipe, the dry feed can independently flow in the feed adjusting pipe, and the water flows in the downpipe; the feed and water separately flow into the trough, so that the problem that the feed and the water are mixed and then fed into the trough after being stirred in the trough by the nose and mouth of the pig due to the fact that half of the feed and half of the water are fed into the trough in the existing live pig feeding equipment after feeding, and the dry feed and the water cannot enter the trough after being mixed is solved.

The invention belongs to the technical field of animal genetic breeding, and provides an application of an SNP molecular marker related to a pig backfat thickness character. The nucleotide sequence of the molecular marker is as shown in SEQ ID NO: 7, wherein the polymorphism of the eleventh basic group is C / T. The key gene SLC26A3 related to the backfat thickness of the large white pig is identified through whole genome deep sequencing, the genotype of the backfat thickness character of the large white pig is further detected through an SLC26A3 gene molecular marker, and the backfat thickness of the CC genotype large white pig is obviously higher than that of a CT / TT genotype pig. Therefore, the breeding of the CT / TT genotype individuals is beneficial to meeting the continuous demand of large-scale production on high-efficiency utilization of feed energy. The detection method provided by the invention is simple and easy to operate, can efficiently and quickly identify the back fat thickness character of the large white pig, improves the uniformity of the back fat thickness of the pig, and provides a scientific basis for early breeding of the pig.