Intelligent computing platform for animal gene breeding

Abstract

The invention discloses an intelligent computing platform for animal gene breeding, which adopts RFID electronic ear tags or other biological recognition technologies to carry out individual marking and identity authentication on each breeding pig, collects basic information of the breeding pig in real time, and carries out intelligent computing on the basis of a statistical genetics model in combination with a machine learning algorithm. The method comprises the following steps: collecting phenotypic data and genotypic data, carrying out deep analysis on the collected phenotypic data and genotypic data, calculating a breeding value or a genome breeding value of each breeding pig, designing and applying an optimization algorithm according to a genetic evaluation result, formulating an optimal breeding pig mating plan, and realizing automatic monitoring of pig house environment parameters through an Internet of Things technology. The method comprises the steps of performing intelligent analysis on behaviors and postures of pigs in combination with an AI image recognition technology, developing a matched software system, integrating data analysis results, establishing a database based on a cloud computing architecture, constructing a visual platform containing various charts and reports, and converting complex data into visual and understandable information.

Description

Technical Field

[0001] The present invention relates to the field of intelligent computing technology, and in particular to an animal gene breeding intelligent computing platform. Background Art

[0002] Jiayu Smart Cloud Platform is a comprehensive SaaS platform with breeding as its core, Internet thinking as its concept, digital three-dimensional breeding management as its main method, and the use of Internet technology, big data, Internet of Things, artificial intelligence and other advanced technologies as the basis (the main feature of the SaaS platform is in the form of services). While carrying out daily breeding management of breeding pigs, based on traditional BLUP breeding and gene breeding technology, under the strategy of diversified breeding directions and multi-trait breeding goals, it is achieved by building a distributed cluster service with its own powerful computing power. The platform uses a distributed microservice architecture, with domain-driven as the core, and uses a SaaS platform with multiple distributed middleware.

[0003] While collecting data from different dimensions, we will integrate intelligent and automated breeding, improve our ability to collect, manage and analyze data, and combine algorithms, DNA data and germplasm resources to improve breeding results overall.

[0004] Build an interconnected smart breeding platform, lower the technical threshold of whole genome breeding, benefit the industry, promote industrial development, push the pig farming industry towards informatization, digitalization, and intelligence, and realize the ability of digital empowerment.

[0005] 1.1. Currently, most pig environmental controls are based on agreed environmental controls according to region and growth period, and real-time control based on factors such as real-time behavioral characterization of the growth process has not yet been achieved.

[0006] 1.2. The collection of phenotypic information is not timely and accurate enough. In large-scale pig farming, due to the large number of pigs, it is impossible to measure the height, weight, body length and body width of each pig in time. Usually, the measurement is only performed once when the pig is released. In this case, it is unrealistic to increase the manual measurement of pigs. Only by using algorithms to measure pigs can timely and dynamic measurement be achieved.

[0007] 1.3. The automatic health monitoring technology is still immature. There are still some difficulties to be solved in using artificial intelligence technology to monitor pig behavior and temperature to achieve pig health monitoring. For example, the pig house is low and the camera cannot take full pictures, accurate infrared equipment is expensive, there are spider webs in the pig house and image distortion correction is difficult. These problems have led to the current automatic health monitoring technology of pig farms being immature.

[0008] 2.1. Dynamic environmental control based on pig welfare breeding. Automated environmental control is implemented according to the different living environment requirements of different breeds of pigs at different ages. For example, light control is performed during the resting time of pigs to induce them to rest, and temperature and humidity are adjusted to prevent pigs from getting sick while ensuring that they have a better and healthier growth environment.

[0009] 2.2. Precise regulation of individual pig nutrition. Reasonable nutrition matching and feeding should be carried out according to the nutritional needs of different breeds of pigs at different ages. The construction of a precise feeding model for pig farming is the prerequisite for precise nutrition control and is currently a hot research field.

[0010] 2.3. Intelligent health monitoring and early warning. Use technologies such as behavior monitoring, body temperature monitoring, body measurement, weight estimation, and big data analysis to warn sick pigs and sub-healthy pigs to prevent the spread of diseases between pig houses. For example, use infrared cameras to continuously monitor the temperature of pigs. Once the temperature of a pig is abnormal, a warning will be issued and the staff will be notified to isolate the pigs.

[0011] 2.4. Factory-based intelligent farming. In the future, large-scale, intelligent and intensive pig farming can be achieved by establishing standardized farming specifications and installing various environmental sensors, infrared cameras, automatic feeders and other equipment in the farm area to achieve intelligent pig farming.

[0012] 3.1. Optimize the breeding environment. Effectively connect the intelligent equipment of the farm environment control series to effectively integrate the equipment with the breeding area. Indoor carbon dioxide concentration, air humidity, temperature, etc., send data to the background through sensors, and the system records and executes alarms. Compared with manual operation and management based on experience, it is more refined and achieves the purpose of optimizing the breeding area environment.

[0013] 3.2. Intelligent weight estimation. The collected pig growth information is used to intelligently analyze the average length and width of the pigs through the intelligent engine computing server, and the average weight of the pigs is estimated in combination with the pig density; intelligent weight estimation changes the traditional manual weighing method, reduces labor costs, and improves the efficiency of pig weighing.

[0014] 3.3. Digital management. Through comparative analysis of historical data, objective data feedback is provided for daily situations, and combined with data analysis, it serves as a guide for the formulation and optimization of subsequent breeding plans. Information data is processed to make data basis for adjusting breeding plans and maintain the normal operation of breeding areas.

[0015] Disadvantages of existing technology:

[0016] 1. Digital breeding technology requires a lot of capital and technical support, and has certain requirements on the technical level and financial strength of the breeders. Not all breeders can easily apply it.

[0017] 2. The popularization and promotion of digital breeding technology takes time. The overall digitalization level of the breeding pig industry is not high enough, and there are certain difficulties in promotion.

[0018] 3. Data security and privacy protection issues of digital breeding technology also need to be paid attention to to avoid the risks of data leakage and abuse.

[0019] Therefore, an improved technology is urgently needed to solve this problem existing in the prior art. Summary of the invention

[0020] The purpose of the present invention is to provide a method that can help pig breeders to more accurately evaluate the genetic background and trait performance of pigs, so as to more accurately select excellent pigs for breeding and improve breeding efficiency. Through gene sequencing technology and genetic marker technology, pigs with excellent genetic characteristics can be quickly screened out, the speed of pig breed improvement can be accelerated, and breeding efficiency can be improved. Digital breeding technology can also help pig breeders better understand the genetic background and genetic characteristics of pigs, which is helpful to select excellent breeds suitable for their needs for breeding and promote breed improvement. Through gene editing technology, the genetic information of pigs can be accurately modified to cultivate new breeds that are more adapted to market demand. Digital breeding has brought more accurate and efficient breeding methods to the pig industry, which is helpful to improve breeding efficiency, promote breed improvement, and promote the development of the pig industry. An animal gene breeding intelligent computing platform to solve the problems raised in the above background technology.

[0021] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an animal gene breeding intelligent computing platform, the animal gene breeding intelligent computing platform

[0022] Use RFID electronic ear tags or other biometric technologies to individually mark and authenticate each breeding pig, and collect basic pig information in real time;

[0023] Based on statistical genetics models and combined with machine learning algorithms, the collected phenotypic and genotypic data are deeply analyzed to calculate the breeding value or genomic breeding value of each breeding pig;

[0024] Design and apply optimization algorithms to develop optimal breeding plans for sows based on genetic evaluation results;

[0025] The Internet of Things technology is used to automatically monitor the environmental parameters of the pig house, and AI image recognition technology is used to intelligently analyze the behavior and posture of pigs;

[0026] Develop supporting software systems, integrate data analysis results, and establish databases based on cloud computing architecture;

[0027] Build a visualization platform for various charts and reports to transform complex data into intuitive and easy-to-understand information.

[0028] Preferably, the basic information of pigs on the animal genetic breeding intelligent computing platform includes growth rate, feed conversion rate, and reproductive performance, and the reproductive performance includes genotype data, SNP markers or whole genome sequence information;

[0029] The growth performance indicators include body weight, daily weight gain, feed conversion rate, etc. The health status includes diversified data such as disease records, vaccination status and genotype information. All data are integrated into the central database.

[0030] Preferably, the animal genetic breeding intelligent computing platform uses methods such as PCA (principal component analysis) and BLUP optimal linear unbiased prediction to guide the selection and matching process based on statistical genetics models, and displays the data input, processing, and output processes in the form of a flow chart.

[0031] Preferably, the animal gene breeding intelligent computing platform uses optimization algorithms based on genetic evaluation including genetic algorithms and simulated annealing algorithms.

[0032] Preferably, the pig house environmental parameters automatically monitored by the animal gene breeding intelligent computing platform based on the Internet of Things technology include temperature, humidity, and ammonia concentration.

[0033] Preferably, the animal gene breeding intelligent computing platform cleans, integrates and deeply analyzes the massive amount of data collected, realizes the full information management of individual breeding pigs from birth, feeding, selection to elimination, and uses machine learning algorithms to explore the correlation between the genetic performance, health status and production performance of breeding pigs.

[0034] Preferably, the visualization platform on the animal gene breeding intelligent computing platform draws a genetic improvement process diagram of breeding pigs, a core group structure diagram, etc., and uses a time series diagram to show the changing trends of various performance indicators of breeding pigs over time.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] (1) The animal genetic breeding intelligent computing platform uses the Internet of Things technology to automatically monitor the environmental parameters of the pig house, and combines AI image recognition technology to intelligently analyze the behavior and body shape of pigs, to provide early warning of disease risks and safeguard the health of the pig herd;

[0037] (2) Apply advanced statistical models and algorithms to conduct genetic evaluation of sows based on genomic information, predict the performance and genetic potential of their offspring, and use intelligent decision support systems to select the best sows for breeding based on the results of genetic evaluation;

[0038] (3) Use IoT technology to monitor pig house environmental parameters and animal behavior characteristics. These data can help optimize feeding conditions and health management. Install smart cameras, sensors and other equipment to assist in estrus detection, estrus identification and early disease warning.

[0039] (4) The digital breeding technology of the animal genetic breeding intelligent computing platform can help pig farmers more accurately evaluate the genetic background and trait performance of pigs, so as to more accurately select excellent pigs for breeding and improve breeding efficiency. Through gene sequencing technology and genetic marker technology, pigs with excellent genetic characteristics can be quickly screened out, the speed of pig breed improvement can be accelerated, and breeding efficiency can be improved. Digital breeding technology can also help pig farmers better understand the genetic background and genetic characteristics of pigs, which helps to select excellent breeds that suit their needs for breeding and promote breed improvement. Through gene editing technology, the genetic information of pigs can be accurately modified to cultivate new breeds that are more adapted to market demand. Digital breeding has brought more accurate and efficient breeding methods to the pig industry, which helps to improve breeding efficiency, promote breed improvement, and promote the development of the pig industry. DETAILED DESCRIPTION

[0040] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] The present invention provides a technical solution: an animal gene breeding intelligent computing platform, the animal gene breeding intelligent computing platform

[0042] Use RFID electronic ear tags or other biometric technologies to individually mark and authenticate each breeding pig, and collect basic pig information in real time;

[0043] Based on statistical genetics models and combined with machine learning algorithms, the collected phenotypic and genotypic data are deeply analyzed to calculate the breeding value or genomic breeding value of each breeding pig;

[0044] Design and apply optimization algorithms to develop optimal breeding plans for sows based on genetic evaluation results;

[0045] The Internet of Things technology is used to automatically monitor the environmental parameters of the pig house, and AI image recognition technology is used to intelligently analyze the behavior and posture of pigs;

[0046] Develop supporting software systems, integrate data analysis results, and establish databases based on cloud computing architecture;

[0047] Build a visualization platform for various charts and reports to transform complex data into intuitive and easy-to-understand information.

[0048] The basic information of pigs on the animal genetic breeding intelligent computing platform includes growth rate, feed conversion rate, and reproductive performance, and the reproductive performance includes genotype data, SNP markers or whole genome sequence information.

[0049] RFID electronic ear tags or other biometric technologies are used to individually mark and authenticate each breeding pig, and real-time collection of basic pig information, such as date of birth, parent information, growth performance indicators including weight, daily weight gain, feed conversion rate, etc., health status including disease records, vaccination status, genotype information and other diversified data. All data are integrated into a central database and efficiently managed and analyzed through cloud storage and cloud computing.

[0050] Based on statistical genetic models and combined with machine learning algorithms, the collected phenotypic and genotypic data are deeply analyzed to calculate the breeding value or genomic breeding value of each breeding pig to guide breeding and matching work. This process may require the use of methods such as PCA (principal component analysis) and BLUP (best linear unbiased prediction), and the process of data input, processing, and output is displayed in the form of a flow chart.

[0051] The animal genetic breeding intelligent computing platform formulates the optimal breeding pig mating plan based on the application optimization algorithm of genetic evaluation, including genetic algorithm and simulated annealing algorithm, to improve the genetic improvement efficiency and economic benefits of the offspring group. The application optimization algorithm of genetic evaluation can demonstrate how the genetic evaluation module, matching optimization module and decision support module interact through the system device.

[0052] The animal gene breeding intelligent computing platform automatically monitors the pig house environmental parameters including temperature, humidity, and ammonia concentration based on the Internet of Things technology. The animal gene breeding intelligent computing platform uses the Internet of Things technology to realize automatic monitoring of pig house environmental parameters, and combines AI image recognition technology to conduct intelligent analysis of pig behavior and body shape, to provide early warning of disease risks and safeguard the health of the pig herd.

[0053] The animal genetic breeding intelligent computing platform cleans, integrates and deeply analyzes the massive amount of collected data, realizes the full information management of individual breeding pigs from birth, feeding, selection to elimination, and uses machine learning algorithms to explore the correlation between the genetic performance, health status and production performance of breeding pigs.

[0054] The visualization platform on the animal gene breeding intelligent computing platform draws the genetic improvement process diagram of breeding pigs, the core group structure diagram, etc., and uses a time series diagram to show the changing trends of various performance indicators of breeding pigs over time. The intelligent computing platform builds a visualization platform that includes various charts and reports, which converts complex data into intuitive and easy-to-understand information, and provides managers with a basis for scientific decision-making. For example, it draws the genetic improvement process diagram of breeding pigs, the core group structure diagram, etc., and uses a time series diagram to show the changing trends of various performance indicators of breeding pigs over time.

[0055] Embodiment 1,

[0056] Using electronic ear tags, RFID and other technologies, we can track and record important indicators such as the growth and development, reproductive performance, health status, feed conversion rate, etc. of each breeding pig in real time, and obtain the breeding pig's genomic SNP markers or whole genome sequence information through high-throughput sequencing or chip detection technology.

[0057] Establish a breeding database system for breeding pigs, integrate and store all collected data, ensure the accuracy and completeness of the data, and develop specialized breeding management software to realize functions such as breeding pig pedigree tracing, mating plan formulation, and genetic evaluation.

[0058] Apply advanced statistical models and algorithms (such as BLUP, GBLUP, etc.) to conduct genetic evaluation of breeding pigs based on genomic information, predict the trait performance and genetic potential of their offspring, and use intelligent decision support systems to select the best breeding pigs for breeding based on the results of genetic evaluation.

[0059] The Internet of Things technology is used to monitor the environmental parameters of the pig house (temperature, humidity, ammonia concentration, etc.) and animal behavioral characteristics. These data help optimize feeding conditions and health management. Smart cameras, sensors and other equipment are installed to assist in estrus detection, estrus identification and early warning of diseases.

[0060] Build a cross-enterprise and cross-regional big data sharing platform for breeding pig genetic resources, promote cooperative breeding among enterprises in the industry, jointly improve the quality of breeding pigs, implement molecular marker-assisted selection (MAS) or genomic selection (GS), and promote the use of genetic materials of selected breeding pigs in the industry.

[0061] Use artificial intelligence algorithms to optimize mating schemes, breeding plans and feeding strategies, achieve precision breeding, predict market trends, dynamically adjust breeding goals and directions based on market demand, and establish a series of standardized and intelligent production management processes from introduction, feeding, testing, selection to elimination to ensure that breeding work is carried out efficiently and orderly.

[0062] Strengthen the training of professional talents, improve the information technology level and data analysis ability of practitioners, continuously develop and improve breeding-related technologies, and keep pace with the international advanced level. Through the above implementation methods, digital breeding can significantly improve the scientificity and efficiency of pig breeding, and help the sustainable development of the pig industry.

[0063] The digital breeding technology of this animal genetic breeding intelligent computing platform can help pig farmers more accurately evaluate the genetic background and trait performance of pigs, so as to more accurately select excellent pigs for breeding and improve breeding efficiency. Through gene sequencing technology and genetic marker technology, pigs with excellent genetic characteristics can be quickly screened out, the speed of pig breed improvement can be accelerated, and breeding efficiency can be improved. Digital breeding technology can also help pig farmers better understand the genetic background and genetic characteristics of pigs, which is helpful to select excellent breeds suitable for their needs for breeding and promote breed improvement. Through gene editing technology, the genetic information of pigs can be accurately modified to cultivate new breeds that are more adapted to market demand. Digital breeding has brought more accurate and efficient breeding methods to the pig industry, which helps to improve breeding efficiency, promote breed improvement, and promote the development of the pig industry.

[0064] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An animal gene breeding intelligent computing platform, characterized by: The animal gene breeding intelligent computing platform Use RFID electronic ear tags or other biometric technologies to individually mark and authenticate each breeding pig, and collect basic pig information in real time; Based on statistical genetics models and combined with machine learning algorithms, the collected phenotypic and genotypic data are deeply analyzed to calculate the breeding value or genomic breeding value of each breeding pig; Design and apply optimization algorithms to develop optimal breeding plans for sows based on genetic evaluation results; The Internet of Things technology is used to automatically monitor the environmental parameters of the pig house, and AI image recognition technology is used to intelligently analyze the behavior and posture of pigs; Develop supporting software systems, integrate data analysis results, and establish databases based on cloud computing architecture; Build a visualization platform for various charts and reports to transform complex data into intuitive and easy-to-understand information.

2. The animal gene breeding intelligent computing platform according to claim 1, characterized in that: The basic information of pigs on the animal genetic breeding intelligent computing platform includes growth rate, feed conversion rate, and reproductive performance, and the reproductive performance includes genotype data, SNP markers or whole genome sequence information; The growth performance indicators include body weight, daily weight gain, feed conversion rate, etc. The health status includes diversified data such as disease records, vaccination status and genotype information. All data are integrated into the central database.

3. The animal gene breeding intelligent computing platform according to claim 1, characterized in that: The animal gene breeding intelligent computing platform uses methods such as PCA (principal component analysis) and BLUP optimal linear unbiased prediction to guide the selection and matching process based on statistical genetics models, and displays the data input, processing, and output processes in the form of a flow chart.

4. The animal gene breeding intelligent computing platform according to claim 1, characterized in that: The animal gene breeding intelligent computing platform uses optimization algorithms based on genetic evaluation, including genetic algorithms and simulated annealing algorithms.

5. The animal gene breeding intelligent computing platform according to claim 1, characterized in that: The animal gene breeding intelligent computing platform automatically monitors the pig house environmental parameters including temperature, humidity and ammonia concentration based on the Internet of Things technology.

6. The animal gene breeding intelligent computing platform according to claim 1, characterized in that: The animal genetic breeding intelligent computing platform cleans, integrates and deeply analyzes the massive amount of data collected, realizes the full information management of individual breeding pigs from birth, feeding, selection to elimination, and uses machine learning algorithms to explore the correlation between the genetic performance, health status and production performance of breeding pigs.

7. The animal gene breeding intelligent computing platform according to claim 1, characterized in that: The visualization platform on the animal gene breeding intelligent computing platform draws a genetic improvement process diagram of breeding pigs, a core group structure diagram, etc., and uses a time series diagram to show the changing trends of various performance indicators of breeding pigs over time.