Breeding management system based on increase of DHA content in eggs

Abstract

The invention relates to the technical field of breeding, in particular to a breeding management system based on increasing the DHA content in eggs, and the system comprises a data collection module which is used for periodically collecting a plurality of related parameters of target laying hens and the actual value of the DHA content in the eggs produced by the target laying hens; a database; the model construction module is used for constructing a DHA related model corresponding to each related parameter and fitting a growth curve and a DHA content change curve of the laying hens; the prediction and comparison module is used for predicting the DHA content value of the eggs produced by the target laying hen in each collection period and determining the abnormal value of the DHA content; the model evaluation module is used for evaluating the relationship between each breeding parameter and the DHA content abnormal value and constructing a DHA abnormity related model; and the parameter adjustment module is used for determining a parameter adjustment mode of each related parameter of the target laying hen. According to the method, the scientificity of breeding management for increasing the DHA content in the eggs can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of aquaculture, and in particular to an aquaculture management system based on improving the DHA content in eggs. Background Art

[0002] DHA, or docosahexaenoic acid, commonly known as "brain gold", is a long-chain polyunsaturated fatty acid belonging to the ω-3 series. A large number of studies have shown that DHA can promote brain development, promote the maturation of retinal photoreceptor cells, reduce cholesterol and triglycerides in the blood, improve the body's immune function, and reduce the level of intracellular reactive oxygen. It is an important nutrient for maintaining human health. The ability to synthesize DHA in the human body is limited, and it needs to be absorbed and supplemented from the outside. Marine fish, fungi and seaweed are its main sources. Eggs and chicken have always been important traditional foods loved by the Chinese people and are also ideal natural foods for humans. Among them, fresh eggs are rich and comprehensive in nutrition. Nutritionists call it a "complete protein model" and are praised as an "ideal nutrient bank". my country's egg production accounts for 36% of the world's total production, and the per capita consumption is 18 kilograms, ranking among the top in the world. With the improvement of people's living standards, consumers not only want to eat enough but also eat well. The requirements for egg quality are increasing, and special groups of people need special eggs. At the same time, eggs and chicken contain a small amount of DHA, which is one of the effective ways to provide DHA for people. However, the DHA content in traditional eggs is relatively low and cannot meet the human body's demand for DHA. Farming feed and breeding conditions have an important impact on the DHA content in eggs. At present, most studies adjust the formula of breeding feed, supplement the DHA intake of laying hens by feeding specific feeds or improve the conversion efficiency of DHA to increase the DHA content in eggs. This method cannot accurately control the DHA content in eggs, the DHA content in eggs is unstable, and the egg production quality of laying hens is unstable. Therefore, there is an urgent need for a method that can scientifically adjust the breeding conditions or parameters in the laying hen breeding process to increase the DHA content in eggs. Summary of the invention

[0003] To this end, the present invention provides a breeding management system based on improving the DHA content in eggs, so as to overcome the problem in the prior art that the breeding conditions or parameters in the laying hen breeding process cannot be scientifically adjusted to improve the DHA content in eggs.

[0004] To achieve the above object, the present invention provides a breeding management system based on increasing the DHA content in eggs, comprising:

[0005] A data acquisition module, which is used to periodically collect several relevant parameters of the target laying hens and the actual value of the DHA content in the eggs produced by the target laying hens, wherein the relevant parameters include the growth parameters of the laying hens and the breeding parameters in the breeding process, wherein the growth parameters include body weight and shank length; the breeding parameters include breeding temperature, breeding density and light intensity;

[0006] A database, which is connected to the data acquisition module and is used to store the relevant parameters of the target laying hens collected by the data acquisition module in each collection cycle and the actual value of the DHA content in the eggs produced, as well as the relevant parameters of the complete life cycle of several laying hens of the same breed and the DHA content values ​​in the eggs produced;

[0007] A model building module, which is connected to the database, and is used to build DHA related models corresponding to the relevant parameters of the complete life cycle of several laying hens of the same breed and the DHA content values ​​in the eggs stored in the database, and to fit the growth curve of the laying hens according to the relevant parameters, and to fit the DHA content change curve according to the DHA content values ​​in the eggs;

[0008] A prediction and comparison module, which is connected to the model building module and the database, respectively, and is used to predict the DHA content value in the eggs produced by the target laying hen in each collection cycle according to each DHA related model, the fitted growth curve of the laying hen and the DHA content change curve, so as to obtain the predicted DHA content value of the target laying hen in each collection cycle, and compare the predicted DHA content value with the actual DHA content value of each collection cycle to determine the abnormal DHA content value;

[0009] A model evaluation module, which is connected to the model construction module and the prediction comparison module respectively, and is used to perform correlation analysis on each of the DHA related models constructed by the model construction module, and evaluate the relationship between each breeding parameter and the abnormal value of DHA content based on the correlation analysis result and the DHA related model corresponding to each breeding parameter, and construct a DHA abnormality related model, wherein the DHA abnormality related model includes a DHA increase model and a DHA decrease model;

[0010] A parameter adjustment module is connected to the model evaluation module and is used to determine the parameter adjustment method of each of the related parameters of the target laying hen according to the evaluation result of the model evaluation module and the DHA abnormality related model.

[0011] Furthermore, the model building module includes:

[0012] A DHA related model construction submodule is connected to the database and is used to respectively construct DHA related models corresponding to the relevant parameters according to the relevant parameters of the complete life cycle of several laying hens of the same breed and the DHA content values ​​in the eggs stored in the database;

[0013] A growth curve fitting submodule, which is connected to the database and is used to fit the growth curve of laying hens according to the relevant parameters of the complete life cycle of several laying hens of the same breed;

[0014] The DHA content variation curve fitting submodule is connected to the database and is used to fit the DHA content variation curve according to the DHA content values ​​in eggs produced during the complete life cycle of several laying hens of the same breed.

[0015] Furthermore, the prediction and comparison module includes:

[0016] A prediction submodule, which is connected to the model building module, is used to predict the DHA content value in the eggs produced by the target laying hens in each collection cycle according to each DHA related model, the fitted growth curve of the laying hens and the DHA content change curve, so as to obtain the predicted value of the DHA content of the target laying hens in each collection cycle;

[0017] The data comparison submodule is connected to the prediction submodule and the database respectively, and is used to compare the predicted value of DHA content with the actual value of DHA content in each collection cycle to determine the abnormal value of DHA content.

[0018] Furthermore, the model evaluation module includes:

[0019] A correlation analysis submodule, which is connected to the model construction module and is used to perform correlation analysis on each of the DHA correlation models constructed by the model construction module to determine the correlation coefficients between any DHA correlation models;

[0020] A model evaluation submodule, which is connected to the model construction module and the correlation analysis submodule respectively, and is used to evaluate the relationship between each breeding parameter and the abnormal value of DHA content based on the correlation analysis result of the prediction and comparison module and the DHA correlation model corresponding to each breeding parameter;

[0021] The DHA abnormality related model construction submodule is connected to the model evaluation submodule and is used to construct the DHA abnormality related model based on the evaluation result of the model evaluation submodule.

[0022] Furthermore, the parameter adjustment module includes:

[0023] A determination submodule, connected to the model evaluation module, for determining whether each of the related parameters needs to be adjusted based on an evaluation result of the model evaluation module;

[0024] The parameter adjustment submodule is connected to the determination submodule and is used to determine the parameter adjustment method of each of the related parameters of the target laying hen that needs to be adjusted based on the determination result of the determination submodule and the DHA abnormality related model.

[0025] Furthermore, the prediction submodule constructs a DHA content prediction model according to each of the DHA related models, the growth curve of the laying hen and the DHA content change curve.

[0026] Furthermore, the data comparison submodule compares the actual DHA content value of each collection period of the target laying hen with the corresponding predicted DHA content value. If the absolute value of the difference between the actual DHA content value and the corresponding predicted DHA content value is greater than a preset difference, the corresponding actual DHA content value is determined as an abnormal DHA content value.

[0027] Furthermore, the model evaluation submodule determines the key breeding parameters based on the correlation coefficient between the DHA-related model corresponding to any breeding parameter determined by the prediction and comparison module and other DHA-related models, wherein the breeding parameters corresponding to the correlation coefficients between the DHA-related model corresponding to any breeding parameter and other DHA-related models that are greater than the correlation coefficient of the first preset value are determined as key breeding parameters.

[0028] Furthermore, the DHA abnormality correlation model construction submodule determines the DHA abnormality correlation model based on the DHA abnormality correlation model corresponding to the key breeding parameters and the comparison relationship between the actual DHA content value and the corresponding DHA content predicted value, wherein the DHA increase model is determined according to the DHA correlation model corresponding to the key breeding parameters and the abnormal DHA content value greater than the DHA content predicted value, and the DHA decrease model is determined according to the DHA correlation model corresponding to the key breeding parameters and the abnormal DHA content value less than the DHA content predicted value.

[0029] Furthermore, the parameter adjustment submodule adjusts the key breeding parameters based on the DHA abnormality correlation model.

[0030] Compared with the prior art, the beneficial effect of the present invention is that the present invention is provided with a data acquisition module, which can periodically collect various relevant parameters and the actual value of the DHA content in the egg, and provide real-time data for subsequent breeding management. A database is set to store various data in the laying hen breeding process, which can provide data support for subsequent model construction and prediction. A model construction module is set to construct DHA-related models corresponding to various relevant parameters, fit the growth curve of laying hens, and fit the DHA content change curve, which can clarify the influencing factors of the DHA content value in eggs, which is conducive to analyzing the changing trend of the DHA content value in eggs under different breeding conditions, and improving the scientific nature of laying hen breeding management. A prediction and comparison module is set, and by predicting the DHA content value and comparing it with the actual value of the DHA content, the abnormal DHA content value can be accurately determined, providing a theoretical basis for the subsequent analysis of the factors of abnormal DHA content. A model evaluation module is set, and by performing correlation analysis on each DHA-related model, the relevant parameters with correlation to the DHA content can be accurately analyzed, so as to find out the influencing parameters of abnormal DHA content, so as to construct a DHA abnormality-related model, and improve the accuracy of model construction. Setting up a parameter adjustment module and determining the adjustment method of each relevant parameter by combining the evaluation results with the DHA abnormality correlation model can improve the scientificity and accuracy of breeding management for increasing the DHA content in eggs.

[0031] Furthermore, the model construction module of the present invention is provided with a DHA-related model construction submodule, a growth curve fitting submodule and a DHA content change curve fitting submodule, and DHA-related models corresponding to the relevant parameters are respectively constructed according to the relevant parameters of the complete life cycle of several laying hens of the same breed and the DHA content values ​​in the eggs, which can improve the accuracy of the model and provide a theoretical basis for subsequent correlation analysis. By fitting the growth curve of laying hens and the DHA content change curve, the accuracy of subsequent predictions can be improved and the scientific nature of breeding management can be improved.

[0032] Furthermore, the prediction and comparison module of the present invention is provided with a prediction submodule and a data comparison submodule, which comprehensively predicts the DHA content values ​​in the eggs produced by the target laying hens in each collection cycle according to each DHA-related model, the fitted growth curve of the laying hen and the DHA content change curve, thereby improving the accuracy of the prediction of the DHA content in the eggs, and determining the abnormal DHA content value by comparing the predicted DHA content value with the actual DHA content value, thereby improving the accuracy of the determined abnormal DHA content value, thereby improving the scientific nature of the breeding management.

[0033] Furthermore, the model evaluation module of the present invention is provided with a correlation analysis submodule, a model evaluation submodule and a DHA abnormality related model construction submodule. By performing correlation analysis on each DHA related model to evaluate the relationship between each breeding parameter and the abnormal DHA content value, the breeding parameters with a relatively large correlation with the abnormal DHA content value can be quickly determined. The DHA abnormality related model constructed in this way has a relatively high accuracy and can improve the model construction efficiency.

[0034] Furthermore, the parameter adjustment module of the present invention is provided with a determination submodule and a parameter adjustment submodule, and determines whether each of the related parameters needs to be adjusted through the evaluation results of the model evaluation module, and can accurately determine the related parameters that need to be adjusted, and determine the parameter adjustment method of each related parameter of the target laying hen that needs to be adjusted according to the determination results and the DHA abnormality related model, which can improve the scientificity and rationality of laying hen breeding management. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a structural block diagram of a breeding management system based on increasing the DHA content in eggs according to an embodiment of the present invention;

[0036] Figure 2 A logical judgment diagram for determining abnormal values ​​of DHA content in an embodiment of the present invention;

[0037] Figure 3 It is a structural block diagram of the model evaluation module of an embodiment of the present invention. DETAILED DESCRIPTION

[0038] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0039] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0040] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0041] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0042] See also Figure 1 As shown, it is a structural block diagram of a breeding management system based on increasing the DHA content in eggs according to an embodiment of the present invention; the present invention provides a breeding management system based on increasing the DHA content in eggs, comprising:

[0043] A data acquisition module, which is used to periodically collect several relevant parameters of the target laying hens and the actual value of the DHA content in the eggs produced by the target laying hens, wherein the relevant parameters include the growth parameters of the laying hens and the breeding parameters in the breeding process, wherein the growth parameters include body weight and shank length; the breeding parameters include breeding temperature, breeding density and light intensity;

[0044] It is understandable that body weight is one of the important indicators to measure the growth condition of laying hens. The weight of laying hens will be different during the brooding period, rearing period and egg-laying period. Tibia length is an important parameter to measure the bone development of laying hens, and it is of great significance for predicting the DHA content in the eggs produced by laying hens. Feeding temperature has an important impact on the production performance of laying hens and the quality of eggs. Appropriate feeding temperature can ensure the health and production efficiency of laying hens, thereby affecting the DHA content in eggs. Too high or too low temperature may cause stress to laying hens, affecting the absorption and conversion efficiency of DHA; appropriate feeding density can reduce competition between chickens, reduce stress, improve welfare, and affect the conversion efficiency of DHA in feed by laying hens, thereby affecting the DHA content in eggs; light intensity has a direct impact on the egg-laying performance of laying hens. When the light intensity is below 20lx, egg production increases with the increase of light intensity; between 20lx and 40lx, egg production does not change significantly; exceeding 40lx, the mortality rate of chickens increases. Light intensity will affect the deposition of DHA in eggs produced by laying hens. Appropriate light intensity can promote the health of laying hens and help increase the DHA content in eggs.

[0045] It should be noted that those skilled in the art know that any method and equipment in the prior art that can collect growth parameters (weight and shank length) and breeding parameters (breeding temperature, breeding density and light intensity) of laying hens fall within the scope of protection of the present invention and will not be described in detail here.

[0046] During implementation, the data acquisition module periodically collects several relevant parameters of the target laying hens and the actual value of the DHA content in the eggs produced by the target laying hens. The actual implementers can set the collection period according to the actual situation or the laying cycle of the laying hens. Preferably, the collection period value range is set to 0.5 days to 1 day.

[0047] A database, which is connected to the data acquisition module and is used to store the relevant parameters of the target laying hens collected by the data acquisition module in each collection cycle and the actual value of the DHA content in the eggs produced, as well as the relevant parameters of the complete life cycle of several laying hens of the same breed and the DHA content values ​​in the eggs produced;

[0048] It is understandable that the complete life cycle of laying hens is from hatching to culling. By analyzing the relevant parameters and DHA content values ​​of the complete life cycle of laying hens of the same breed as the target laying hens, data support can be provided for the breeding management of the target laying hens.

[0049] A model building module, which is connected to the database, and is used to build DHA related models corresponding to the relevant parameters of the complete life cycle of several laying hens of the same breed and the DHA content values ​​in the eggs stored in the database, and to fit the growth curve of the laying hens according to the relevant parameters, and to fit the DHA content change curve according to the DHA content values ​​in the eggs;

[0050] Specifically, the model building module includes:

[0051] A DHA related model construction submodule is connected to the database and is used to respectively construct DHA related models corresponding to the relevant parameters according to the relevant parameters of the complete life cycle of several laying hens of the same breed and the DHA content values ​​in the eggs stored in the database;

[0052] It should be noted that those skilled in the art know that any method in the prior art that can perform data fitting on the relevant parameters of the complete life cycle of several laying hens of the same breed and the DHA content values ​​in the eggs to construct a DHA correlation model corresponding to each relevant parameter falls within the scope of protection of the present invention and will not be described in detail herein.

[0053] During implementation, data fitting is performed based on the body weight data of several laying hens of the same breed during their entire life cycle and the DHA content values ​​in the eggs produced, so as to construct a DHA correlation model corresponding to the body weight; data fitting is performed based on the tibia length data of several laying hens of the same breed during their entire life cycle and the DHA content values ​​in the eggs produced, so as to construct a DHA correlation model corresponding to the tibia length; data fitting is performed based on the feeding temperature data of several laying hens of the same breed during their entire life cycle and the DHA content values ​​in the eggs produced, so as to construct a DHA correlation model corresponding to the feeding temperature; data fitting is performed based on the feeding density data of several laying hens of the same breed during their entire life cycle and the DHA content values ​​in the eggs produced, so as to construct a DHA correlation model corresponding to the feeding density; data fitting is performed based on the light intensity data of several laying hens of the same breed during their entire life cycle and the DHA content values ​​in the eggs produced, so as to construct a DHA correlation model corresponding to the light intensity.

[0054] A growth curve fitting submodule, which is connected to the database and is used to fit the growth curve of laying hens according to the relevant parameters of the complete life cycle of several laying hens of the same breed;

[0055] It should be noted that those skilled in the art know that any method in the prior art that can fit the growth curve of laying hens falls within the protection scope of the present invention, such as Logistic model, Gompertz model, nonlinear regression analysis, etc., which will not be repeated here.

[0056] The DHA content variation curve fitting submodule is connected to the database and is used to fit the DHA content variation curve according to the DHA content values ​​in eggs produced during the complete life cycle of several laying hens of the same breed.

[0057] It should be noted that those skilled in the art are aware that any method in the prior art that can fit the DHA content change curve falls within the protection scope of the present invention and will not be described in detail herein.

[0058] The model construction module of the present invention is provided with a DHA-related model construction submodule, a growth curve fitting submodule and a DHA content change curve fitting submodule, and DHA-related models corresponding to the relevant parameters are respectively constructed according to the relevant parameters of the complete life cycle of several laying hens of the same breed and the DHA content values ​​in the eggs, so that the accuracy of the model can be improved, and a theoretical basis can be provided for subsequent correlation analysis. By fitting the growth curve of laying hens and the DHA content change curve, the accuracy of subsequent predictions can be improved, and the scientific nature of breeding management can be improved.

[0059] A prediction and comparison module, which is connected to the model building module and the database, respectively, and is used to predict the DHA content value in the eggs produced by the target laying hen in each collection cycle according to each DHA related model, the fitted growth curve of the laying hen and the DHA content change curve, so as to obtain the predicted DHA content value of the target laying hen in each collection cycle, and compare the predicted DHA content value with the actual DHA content value of each collection cycle to determine the abnormal DHA content value;

[0060] See also Figure 2 As shown, it is a logical judgment diagram for determining abnormal values ​​of DHA content in an embodiment of the present invention; specifically, the prediction and comparison module includes:

[0061] A prediction submodule, which is connected to the model building module, is used to predict the DHA content value in the eggs produced by the target laying hens in each collection cycle according to each DHA related model, the fitted growth curve of the laying hens and the DHA content change curve, so as to obtain the predicted value of the DHA content of the target laying hens in each collection cycle;

[0062] Specifically, the prediction submodule constructs a DHA content prediction model according to the DHA-related models, the growth curve of the laying hen and the DHA content change curve, and inputs the relevant parameters of the target laying hens collected periodically and the actual value of the DHA content in the eggs produced by the target laying hens into the DHA content prediction model to obtain the predicted value of the DHA content in the eggs produced by the target laying hens during their entire life cycle output by the DHA content prediction model.

[0063] It should be noted that those skilled in the art are aware that any prediction model in the prior art that can predict the DHA content in eggs falls within the protection scope of the present invention and will not be described in detail here.

[0064] The data comparison submodule is connected to the prediction submodule and the database respectively, and is used to compare the predicted value of DHA content with the actual value of DHA content in each collection cycle to determine the abnormal value of DHA content.

[0065] Specifically, the data comparison submodule compares the actual DHA content value of each collection period of the target laying hen with the corresponding predicted DHA content value. If the absolute value of the difference between the actual DHA content value and the corresponding predicted DHA content value is greater than a preset difference, the corresponding actual DHA content value is determined as an abnormal DHA content value.

[0066] In implementation, actual implementers can set the preset difference according to actual conditions or based on an expert system. Preferably, the preset difference value range is set to 20 mg / 100 g to 50 mg / 100 g.

[0067] The prediction and comparison module of the present invention is provided with a prediction submodule and a data comparison submodule, and the DHA content value in the eggs produced by the target laying hen in each collection cycle is comprehensively predicted according to each DHA related model, the fitted growth curve of the laying hen and the DHA content change curve, so that the accuracy of the prediction of the DHA content in the eggs can be improved, and the abnormal value of the DHA content can be determined by comparing the predicted value of the DHA content with the actual value of the DHA content, so that the accuracy of the determined abnormal value of the DHA content can be improved, thereby improving the scientific nature of the breeding management.

[0068] A model evaluation module, which is connected to the model construction module and the prediction comparison module respectively, and is used to perform correlation analysis on each of the DHA related models constructed by the model construction module, and evaluate the relationship between each breeding parameter and the abnormal value of DHA content based on the correlation analysis result and the DHA related model corresponding to each breeding parameter, and construct a DHA abnormality related model, wherein the DHA abnormality related model includes a DHA increase model and a DHA decrease model;

[0069] See also Figure 3 As shown, it is a structural block diagram of a model evaluation module according to an embodiment of the present invention; specifically, the model evaluation module includes:

[0070] A correlation analysis submodule, which is connected to the model construction module and is used to perform correlation analysis on each of the DHA correlation models constructed by the model construction module to determine the correlation coefficients between any DHA correlation models;

[0071] It should be noted that those skilled in the art are aware that any method in the prior art that can perform correlation analysis on various DHA correlation models, such as: Pearson correlation coefficient, Spearman rank correlation coefficient, Kendale correlation coefficient, etc., all fall within the scope of protection of the present invention and will not be described in detail herein.

[0072] In a specific embodiment, correlation analysis is performed on any two DHA correlation models to determine their correlation coefficient, which indicates the degree of correlation between the two corresponding DHA correlation models. The larger the correlation coefficient, the greater the degree of correlation.

[0073] A model evaluation submodule, which is connected to the model construction module and the correlation analysis submodule respectively, and is used to evaluate the relationship between each breeding parameter and the abnormal value of DHA content based on the correlation analysis result of the prediction and comparison module and the DHA correlation model corresponding to each breeding parameter;

[0074] Specifically, the model evaluation submodule determines the key breeding parameters based on the correlation coefficient between the DHA-related model corresponding to any breeding parameter determined by the prediction and comparison module and other DHA-related models, wherein the breeding parameters corresponding to the correlation coefficients between the DHA-related model corresponding to any breeding parameter and other DHA-related models that are greater than the correlation coefficient of the first preset value are determined as key breeding parameters.

[0075] In a specific embodiment, for example, if the correlation coefficient between the DHA correlation model corresponding to the feeding temperature and the DHA correlation model corresponding to the body weight is a first coefficient, the correlation coefficient between the DHA correlation model corresponding to the feeding temperature and the DHA correlation model corresponding to the tibia length is a second coefficient, the correlation coefficient between the DHA correlation model corresponding to the feeding temperature and the DHA correlation model corresponding to the feeding density is a third coefficient, and the correlation coefficient between the DHA correlation model corresponding to the feeding temperature and the DHA correlation model corresponding to the light intensity is a fourth coefficient, wherein the first coefficient, the second coefficient, the third coefficient and the fourth coefficient are all greater than the first preset value, then the feeding temperature is determined as the key breeding parameter.

[0076] It is understandable that the actual implementer may determine the first preset value according to the actual situation or based on the minimum value of the correlation coefficient that passes the qualification test in the historical data. Preferably, the first preset value is taken in the range of 0.5 to 0.7.

[0077] The DHA abnormality related model construction submodule is connected to the model evaluation submodule and is used to construct the DHA abnormality related model based on the evaluation result of the model evaluation submodule.

[0078] Specifically, the DHA abnormality correlation model construction submodule determines the DHA abnormality correlation model based on the DHA abnormality correlation model corresponding to the key breeding parameters and the comparison relationship between the actual DHA content value and the corresponding DHA content predicted value, wherein the DHA increase model is determined according to the DHA correlation model corresponding to the key breeding parameters and the abnormal DHA content value greater than the DHA content predicted value, and the DHA decrease model is determined according to the DHA correlation model corresponding to the key breeding parameters and the abnormal DHA content value less than the DHA content predicted value.

[0079] It can be understood that several abnormal DHA content values ​​can be determined based on the actual DHA content value and the predicted DHA content value. If the actual DHA content value is greater than the predicted DHA content value, it indicates that the corresponding DHA content is abnormally increased, and the abnormal DHA content increase value can be obtained; if the actual DHA content value is less than the predicted DHA content value, it indicates that the corresponding DHA content is abnormally decreased, and the abnormal DHA content decrease value can be obtained. The DHA correlation model corresponding to the key breeding parameters and the DHA correlation model corresponding to other related parameters are highly correlated. According to the DHA correlation model corresponding to the key breeding parameters and the corresponding abnormal DHA content increase value / DHA content decrease value, the DHA increase model / DHA decrease model can be determined.

[0080] It should be noted that those skilled in the art know that any method in the prior art that can determine the DHA increase model / DHA decrease model based on the DHA correlation model and the abnormal value of DHA content (abnormal value of increased DHA content / abnormal value of decreased DHA content) falls within the scope of protection of the present invention and will not be described in detail here.

[0081] The model evaluation module of the present invention is provided with a correlation analysis submodule, a model evaluation submodule and a DHA abnormality related model construction submodule. By performing correlation analysis on each DHA related model to evaluate the relationship between each breeding parameter and the abnormal DHA content value, the breeding parameters with a relatively large correlation with the abnormal DHA content value can be quickly determined. The DHA abnormality related model constructed in this way has a relatively high accuracy and can improve the model construction efficiency.

[0082] A parameter adjustment module is connected to the model evaluation module and is used to determine the parameter adjustment method of each of the related parameters of the target laying hen according to the evaluation result of the model evaluation module and the DHA abnormality related model.

[0083] Specifically, the parameter adjustment module includes:

[0084] A determination submodule, connected to the model evaluation module, for determining whether each of the related parameters needs to be adjusted based on an evaluation result of the model evaluation module;

[0085] In practice, if there are abnormal values ​​of key breeding parameters and DHA content, it is determined that the key breeding parameters need to be adjusted.

[0086] The parameter adjustment submodule is connected to the determination submodule and is used to determine the parameter adjustment method of each of the related parameters of the target laying hen that needs to be adjusted based on the determination result of the determination submodule and the DHA abnormality related model.

[0087] Specifically, the parameter adjustment submodule adjusts the key breeding parameters based on the DHA abnormality correlation model.

[0088] It is understandable that the DHA correlation model corresponding to the key breeding parameters is compared with the DHA abnormality correlation model to determine the adjustment amount of the key breeding parameters.

[0089] In implementation, the model difference between the DHA-related model and the DHA abnormality-related model can be obtained based on a machine learning method, and a first intermediate value is determined by the difference between the model difference and a preset difference. A second intermediate value is determined based on the ratio of the first intermediate value to the preset difference. The adjustment amount of the key breeding parameters of each sampling period is determined based on the product of the second intermediate value and the key breeding parameters of each sampling period.

[0090] It is understandable that the actual implementer can set the preset difference according to the actual situation or based on the average of the differences between the DHA-related model and the DHA abnormality-related model that have passed the qualification test in historical data. Preferably, the preset difference value range is set to 0.7-0.9.

[0091] The parameter adjustment module of the present invention is provided with a determination submodule and a parameter adjustment submodule, and determines whether each of the related parameters needs to be adjusted through the evaluation results of the model evaluation module, and can accurately determine the related parameters that need to be adjusted, and determine the parameter adjustment method of each related parameter of the target laying hen that needs to be adjusted according to the determination result and the DHA abnormality related model, which can improve the scientificity and rationality of laying hen breeding management.

[0092] The present invention is provided with a data acquisition module, which can periodically collect various relevant parameters and the actual value of the DHA content in the egg, and provide real-time data for subsequent breeding management. A database is set to store various data in the laying hen breeding process, which can provide data support for subsequent model construction and prediction. A model construction module is set to construct DHA-related models corresponding to various relevant parameters, fit the growth curve of laying hens, and fit the DHA content change curve, which can clarify the influencing factors of the DHA content value in the egg, which is conducive to analyzing the changing trend of the DHA content value in the egg under different breeding conditions, and improving the scientific nature of laying hen breeding management. A prediction and comparison module is set, which can accurately determine the abnormal value of the DHA content by predicting the DHA content value and comparing it with the actual value of the DHA content, and provide a theoretical basis for the subsequent analysis of the factors of abnormal DHA content. A model evaluation module is set, which can accurately analyze the relevant parameters that have a correlation with the influence of the DHA content by performing correlation analysis on each DHA-related model, so as to find out the influencing parameters of abnormal DHA content, so as to construct a DHA abnormality-related model, and improve the accuracy of model construction. Setting up a parameter adjustment module and determining the adjustment method of each relevant parameter by combining the evaluation results with the DHA abnormality correlation model can improve the scientificity and accuracy of breeding management for increasing the DHA content in eggs.

[0093] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. A breeding management system based on increasing the DHA content in eggs, characterized in that: include: A data acquisition module, which is used to periodically collect several relevant parameters of the target laying hens and the actual value of the DHA content in the eggs produced by the target laying hens, wherein the relevant parameters include the growth parameters of the laying hens and the breeding parameters in the breeding process, wherein the growth parameters include body weight and shank length, and the breeding parameters include breeding temperature, breeding density and light intensity; A database, which is connected to the data acquisition module and is used to store the relevant parameters of the target laying hens collected by the data acquisition module in each collection cycle and the actual value of the DHA content in the eggs produced, as well as the relevant parameters of the complete life cycle of several laying hens of the same breed and the DHA content values ​​in the eggs produced; A model building module, which is connected to the database, and is used to build DHA related models corresponding to the relevant parameters of the complete life cycle of several laying hens of the same breed and the DHA content values ​​in the eggs stored in the database, and to fit the growth curve of the laying hens according to the relevant parameters, and to fit the DHA content change curve according to the DHA content values ​​in the eggs; A prediction and comparison module, which is connected to the model building module and the database, respectively, and is used to predict the DHA content value in the eggs produced by the target laying hen in each collection cycle according to each DHA related model, the fitted growth curve of the laying hen and the DHA content change curve, so as to obtain the predicted DHA content value of the target laying hen in each collection cycle, and compare the predicted DHA content value with the actual DHA content value of each collection cycle to determine the abnormal DHA content value; A model evaluation module, which is connected to the model construction module and the prediction comparison module respectively, and is used to perform correlation analysis on each of the DHA related models constructed by the model construction module, and evaluate the relationship between each breeding parameter and the abnormal value of DHA content based on the correlation analysis result and the DHA related model corresponding to each breeding parameter, and construct a DHA abnormality related model, wherein the DHA abnormality related model includes a DHA increase model and a DHA decrease model; A parameter adjustment module is connected to the model evaluation module and is used to determine the parameter adjustment method of each of the related parameters of the target laying hen according to the evaluation result of the model evaluation module and the DHA abnormality related model.

2. The breeding management system based on increasing the DHA content in eggs according to claim 1, characterized in that: The model building module includes: A DHA related model construction submodule is connected to the database and is used to respectively construct DHA related models corresponding to the relevant parameters according to the relevant parameters of the complete life cycle of several laying hens of the same breed and the DHA content values ​​in the eggs stored in the database; A growth curve fitting submodule, which is connected to the database and is used to fit the growth curve of laying hens according to the relevant parameters of the complete life cycle of several laying hens of the same breed; The DHA content variation curve fitting submodule is connected to the database and is used to fit the DHA content variation curve according to the DHA content values ​​in eggs produced during the complete life cycle of several laying hens of the same breed.

3. The breeding management system based on increasing the DHA content in eggs according to claim 2, characterized in that: The prediction and comparison module comprises: A prediction submodule, which is connected to the model building module, is used to predict the DHA content value in the eggs produced by the target laying hens in each collection cycle according to each DHA related model, the fitted growth curve of the laying hens and the DHA content change curve, so as to obtain the predicted value of the DHA content of the target laying hens in each collection cycle; The data comparison submodule is connected to the prediction submodule and the database respectively, and is used to compare the predicted value of DHA content with the actual value of DHA content in each collection cycle to determine the abnormal value of DHA content.

4. The breeding management system based on increasing the DHA content in eggs according to claim 3, characterized in that: The model evaluation module includes: A correlation analysis submodule, which is connected to the model construction module and is used to perform correlation analysis on each of the DHA correlation models constructed by the model construction module to determine the correlation coefficients between any DHA correlation models; A model evaluation submodule, which is connected to the model construction module and the correlation analysis submodule respectively, and is used to evaluate the relationship between each breeding parameter and the abnormal value of DHA content based on the correlation analysis result of the prediction and comparison module and the DHA correlation model corresponding to each breeding parameter; The DHA abnormality related model construction submodule is connected to the model evaluation submodule and is used to construct the DHA abnormality related model based on the evaluation result of the model evaluation submodule.

5. The breeding management system based on increasing the DHA content in eggs according to claim 4, characterized in that: The parameter adjustment module comprises: A determination submodule, connected to the model evaluation module, for determining whether each of the related parameters needs to be adjusted based on an evaluation result of the model evaluation module; The parameter adjustment submodule is connected to the determination submodule and is used to determine the parameter adjustment method of each of the related parameters of the target laying hen that needs to be adjusted based on the determination result of the determination submodule and the DHA abnormality related model.

6. The breeding management system based on increasing the DHA content in eggs according to claim 5, characterized in that: The prediction submodule constructs a DHA content prediction model according to each of the DHA related models, the growth curve of the laying hen and the DHA content change curve.

7. The breeding management system based on increasing the DHA content in eggs according to claim 6, characterized in that: The data comparison submodule compares the actual DHA content value of each collection period of the target laying hen with the corresponding predicted DHA content value. If the absolute value of the difference between the actual DHA content value and the corresponding predicted DHA content value is greater than a preset difference, the corresponding actual DHA content value is determined as an abnormal DHA content value.

8. The breeding management system based on increasing the DHA content in eggs according to claim 7, characterized in that: The model evaluation submodule determines the key breeding parameters based on the correlation coefficient between the DHA correlation model corresponding to any breeding parameter determined by the prediction and comparison module and other DHA correlation models, wherein the breeding parameters corresponding to the correlation coefficients between the DHA correlation model corresponding to any breeding parameter and other DHA correlation models that are greater than the correlation coefficient of the first preset value are determined as key breeding parameters.

9. The breeding management system based on increasing the DHA content in eggs according to claim 8, characterized in that: The DHA abnormality correlation model construction submodule determines the DHA abnormality correlation model based on the DHA abnormality correlation model corresponding to the key breeding parameters and the comparison relationship between the actual DHA content value and the corresponding DHA content predicted value, wherein the DHA increase model is determined according to the DHA correlation model corresponding to the key breeding parameters and the DHA content abnormal value greater than the DHA content predicted value, and the DHA decrease model is determined according to the DHA correlation model corresponding to the key breeding parameters and the DHA content abnormal value less than the DHA content predicted value.

10. The breeding management system based on increasing the DHA content in eggs according to claim 9, characterized in that: The parameter adjustment submodule adjusts the key breeding parameters based on the DHA abnormality correlation model.

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