Intestinal microbial evaluation system and method based on dairy cow diarrhea pathogen analysis

Abstract

The application discloses a dairy cow diarrhea pathogen analysis-based intestinal microbial evaluation system and method, belonging to the field of electronic data processing. The application evaluates the cause of dairy cow diarrhea based on the predicted microbial diet influence and the matching degree of diarrhea time of the diarrhea dairy cow. By comparing the fecal microbial community of the diarrhea and normal dairy cows, potential pathogenic microorganisms related to diarrhea can be identified, so that the cause of diarrhea can be more accurately diagnosed. Combined with the image features and microbial community analysis of the feces, the pathological mechanism of diarrhea can be more comprehensively understood, helping to scientifically guide the development of treatment plans. By analyzing the influence of microorganisms on the feeding habits of dairy cows, the feed formula and feeding conditions of dairy cows can be optimized to prevent the occurrence of diarrhea and improve the health level of dairy cows. Based on the prediction model of microbial diet influence and combined with the matching degree of diarrhea time, the evaluation accuracy of the cause of diarrhea can be improved, providing a scientific basis for clinical veterinarian decision-making.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of electronic data processing, specifically an intestinal microbial evaluation system and method based on dairy cow diarrhea pathogen analysis. BACKGROUND

[0002] Dairy cow diarrhea is a common disease, usually caused by problems in the digestive system. The main causes of dairy cow diarrhea are: pathogenic microorganisms, such as bacteria (e.g. Escherichia coli), viruses (e.g. bovine viral diarrhea virus) or parasites (e.g. coccidia) causing dairy cow diarrhea, which not only affects the health and productivity of dairy cows, but also can lead to a decrease in milk production and quality, therefore, timely diagnosis and treatment is very important, therefore, it is necessary to evaluate the intestinal microorganisms during the process of dairy cow diarrhea to quickly find potential pathogenic microorganisms related to diarrhea, at this time, an intestinal microbial evaluation system based on dairy cow diarrhea pathogen analysis is needed.

[0003] However, the existing intestinal microbial evaluation process of dairy cow diarrhea has a series of problems. During the intestinal microbial evaluation process of dairy cow diarrhea, it is not possible to accurately compare the fecal microbial community of diarrhea and normal dairy cows, identify potential pathogenic microorganisms related to diarrhea, and combine image features and microbial community analysis of feces, resulting in an inability to fully understand the pathogenesis of diarrhea, and an inability to fuse the prediction model of microbial dietary impact with the matching degree of diarrhea time, resulting in low efficiency and accuracy of diarrhea cause evaluation. Most of the existing technologies have the above problems.

[0004] In order to solve the problems raised in the background art, the present application designs an intestinal microbial evaluation system and method based on dairy cow diarrhea pathogen analysis. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application proposes an intestinal microbial evaluation system and method based on dairy cow diarrhea pathogen analysis. The present application evaluates the cause of dairy cow diarrhea based on the matching degree of predicted microbial dietary impact and diarrhea time of dairy cows with diarrhea. By comparing the fecal microbial community of diarrhea and normal dairy cows, potential pathogenic microorganisms related to diarrhea can be identified, thereby more accurately diagnosing the cause of diarrhea. By combining image features and microbial community analysis of feces, the pathogenesis of diarrhea can be more fully understood, helping to scientifically guide the development of treatment plans. By analyzing the impact of microorganisms on dairy cow dietary habits, the feed formula and feeding conditions of dairy cows can be optimized to prevent the occurrence of diarrhea and improve the health level of dairy cows. Based on the prediction model of microbial dietary impact, combined with the matching degree of diarrhea time, the evaluation accuracy of the cause of diarrhea can be improved, providing a scientific basis for clinical veterinary decision-making.

[0006] To achieve the above object, the application provides the following technical scheme: an intestinal microorganism evaluation method based on dairy cow diarrhea pathogen analysis, comprising the following specific steps:

[0007] S1, obtaining various microbial community compositions in the diarrhea cow feces, comparing them with normal cow feces, obtaining potential pathogenic microorganisms, and obtaining fecal image features;

[0008] S2, analyzing the diarrhea cow related microorganism features based on the fecal image features and the potential pathogenic microorganism features;

[0009] S3, analyzing the microorganism diet effect based on the diarrhea cow related microorganism features and the diarrhea cow diet habits;

[0010] S4, evaluating the diarrhea cow diarrhea reason based on the predicted microorganism diet effect and the matching degree of the diarrhea cow diarrhea time.

[0011] It should be noted that, as a preferred technical solution of the intestinal microorganism evaluation method based on dairy cow diarrhea pathogen analysis, the obtaining of various microbial community compositions in the diarrhea cow feces, the comparison with normal cow feces, the obtaining of potential pathogenic microorganisms, and the obtaining of fecal image features comprises the following specific contents:

[0012] Obtaining the diarrhea cow fecal sample, obtaining the microbial abundance data and microbial species data in the diarrhea cow fecal sample by gene sequencing, comparing the microbial abundance data and microbial species data in the diarrhea cow fecal sample with the microbial abundance data and microbial species data in the normal cow feces, obtaining the corresponding microbial species with microbial abundance out of the normal range, setting as potential pathogenic microorganisms, and storing the collected data in the storage module;

[0013] Obtaining the color and morphological data of the diarrhea cow fecal image, and obtaining the diet record data of the cow in the period, and storing the collected data in the storage module.

[0014] It should be noted that, as a preferred technical solution of the intestinal microorganism evaluation method based on dairy cow diarrhea pathogen analysis, the analysis of the diarrhea cow related microorganism features based on the fecal image features and the potential pathogenic microorganism features comprises the following specific steps:

[0015] S21, obtaining the color and morphological data of the diarrhea cow fecal image, and obtaining the color and morphological data of the fecal image of the historical identified pathogenic microorganism, wherein the morphological data includes size and shape data, performing fecal similarity analysis, and further obtaining the first probability of pathogenic microorganism;

[0016] Specifically comprising the following steps:

[0017] S211, the color of the diarrhea cow feces image and the color of the feces image of the identified pathogenic microorganism are introduced into a color similarity calculation formula to calculate the color similarity; wherein the color similarity calculation formula can be a Euclidean distance or a cosine similarity calculation method;

[0018] S212, the morphological data of the diarrhea cow feces image and the morphology of the feces image of the identified pathogenic microorganism are introduced into a morphological similarity calculation formula to calculate the morphological similarity, wherein the morphological similarity calculation formula is: the intersection area of the two images divided by the union area of the two images;

[0019] S213, the calculated color similarity and morphological similarity are weighted and summed to obtain the feces similarity, and the feces similarity corresponding to the historical identified pathogenic microorganism is set as the pathogenic microorganism first probability corresponding to the historical identified pathogenic microorganism;

[0020] S22, the corresponding microbial species with an abundance not in the normal range in the diarrhea cow feces is obtained, and the proportion of the abundance of the corresponding microbial species exceeding the normal range and the number of times of causing cow diarrhea of the corresponding microbial species in history are introduced into a pathogenic microorganism second probability calculation formula to calculate the pathogenic microorganism second probability;

[0021] In this step, the second probability of the pathogenic microorganism causing diarrhea is analyzed by the abundance of the microbial species and the number of times of causing cow diarrhea of the corresponding microbial species in history;

[0022] S23, the pathogenic microorganism first probability and the pathogenic microorganism second probability corresponding to the pathogenic microorganism are obtained, and the influence probability of the corresponding pathogenic microorganism is obtained after weighted summation, and the corresponding pathogenic microorganism with an influence probability greater than or equal to a set probability is obtained as the microorganism related to the diarrhea cow.

[0023] It should be noted that as a preferred technical solution of the intestinal microbial evaluation method based on the analysis of the pathogen of the diarrhea cow, the analysis of the diet influence of the microorganism based on the characteristics of the microorganism related to the diarrhea cow and the diet habit of the diarrhea cow includes the following specific steps:

[0024] S31, the abundance of the microbial species related to the diarrhea cow and the detected microbial species content data of various diets in the diet habit of the diarrhea cow are obtained, wherein the diet of the diarrhea cow includes various forages and drinking water;

[0025] S32, the diet influence of various diets on the diarrhea cow is analyzed based on the abundance of the microbial species related to the diarrhea cow and the detected microbial species data of various diets in the diet habit of the diarrhea cow.

[0026] In this step, the impact of the diet is predicted by the similarity of the microbial content of the diet and the microorganisms associated with the diarrhea cow;

[0027] It should be noted that, as a preferred technical solution of the intestinal microbial evaluation method based on the analysis of the pathogen of the diarrhea of the dairy cow, the evaluation of the cause of the diarrhea of the dairy cow based on the predicted impact of the microorganism of the diet and the matching degree of the diarrhea time of the diarrhea cow includes the following specific contents: S41, obtaining the feeding time, diet type and diarrhea time of the dairy cow in the period, obtaining the matching degree of the diarrhea time and the diet type based on the feeding time, diet type and diarrhea time of the dairy cow, i.e. time impact probability;

[0028] S42, obtaining the matching degree of the diarrhea time and the diet type calculated and the diet impact of various diets on the diarrhea cow, and obtaining the total impact of the corresponding diet type on the diarrhea after weighted summation;

[0029] S43, obtaining the total impact of the corresponding diet type on the diarrhea in descending order, obtaining a plurality of corresponding diet types in the front as the diet cause of the diarrhea of the dairy cow, and sending to the client, and the client replaces the diet.

[0030] It should be noted that the acquisition method of each weighting weight in the present application is as follows: the data of the historical diarrhea cow is substituted into each step of the present application to analyze the total impact of the corresponding diet type on the diarrhea, and the inspection results of the abnormal diet type by the staff are obtained, and the inspection results and the total impact of the corresponding diet type on the diarrhea obtained by analysis are introduced into the fitting software for continuous fitting iteration of data, and the values of each weighting weight in the present application meeting the maximum inspection accuracy are output.

[0031] The intestinal microbial evaluation system based on the analysis of the pathogen of the diarrhea of the dairy cow is realized based on the above-mentioned intestinal microbial evaluation method based on the analysis of the pathogen of the diarrhea of the dairy cow, and specifically includes the following modules:

[0032] Acquisition module: comparing various microbial community compositions in the feces of the diarrhea cow with the feces of the normal dairy cow, obtaining potential pathogenic microorganisms, and obtaining feces image features;

[0033] Microbial feature analysis module: analyzing the microbial features associated with the diarrhea cow based on the feces image features and the potential pathogenic microbial features;

[0034] Diet impact prediction module: analyzing the diet impact of the microorganism based on the microbial features associated with the diarrhea cow and the diet habit of the diarrhea cow;

[0035] Diarrhea cause evaluation module: evaluating the cause of the diarrhea of the dairy cow based on the predicted impact of the microorganism of the diet and the matching degree of the diarrhea time of the diarrhea cow.

[0036] An electronic device comprises: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0037] The processor executes the above-mentioned intestinal microorganism assessment method based on dairy cow diarrhea pathogen analysis by calling the computer program stored in the memory.

[0038] A computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the intestinal microorganism assessment method based on the analysis of pathogens of dairy cow diarrhea as described above.

[0039] Compared with the prior art, the present invention has the following advantages:

[0040] The present application obtains the composition of various microbial communities in the feces of diarrheal cows, compares it with the feces of normal cows, obtains potential pathogenic microorganisms therein, and simultaneously obtains fecal image features. Based on the fecal image features and the potential pathogenic microorganism features, the microbial characteristics associated with diarrheal cows are analyzed. The dietary impact of microorganisms is predicted based on the analysis of the microbial characteristics associated with diarrheal cows and the dietary habits of diarrheal cows. The cause of diarrhea in cows is assessed based on the predicted microbial dietary impact and the degree of matching between the diarrheal cows and the diarrheal cows. By comparing the fecal microbial communities of diarrheal and normal cows, potential pathogenic microorganisms associated with diarrhea can be identified, thereby more accurately diagnosing the cause of diarrhea. Combining fecal image features and microbial community analysis can provide a more comprehensive understanding of the pathological mechanism of diarrhea and help scientifically guide the formulation of treatment plans. By analyzing the impact of microorganisms on the dietary habits of dairy cows, the feed formula and breeding conditions of dairy cows can be optimized, the occurrence of diarrhea can be prevented, and the health level of dairy cows can be improved. The predictive model based on the microbial dietary impact, combined with the degree of matching between diarrheal times, can improve the accuracy of the assessment of the cause of diarrhea and provide a scientific basis for clinical veterinary decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a schematic diagram of the overall process of an embodiment of the present application method;

[0042] Figure 2 This is a flow chart of step S2 of the method embodiment of the present application;

[0043] Figure 3 This is a flow chart of step S4 of the method embodiment of the present application;

[0044] Figure 4 This is a flow chart of step S21 of an embodiment of the method of the present application;

[0045] Figure 5 This is a schematic diagram of the overall framework of the system embodiment of this application. DETAILED DESCRIPTION

[0046] In order to make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the following will be combined with the accompanying drawings for the embodiments of the present application to make a clear and complete description of the technical solutions in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0047] It should also be noted that the relative terms such as first and second in the specification are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment. Without more limitations, the element defined by the statement "including a" does not exclude the presence of another identical element in the process, method, article or equipment including the element. Embodiment 1

[0048] To solve the technical problems raised in the background art, the present application provides a preferred embodiment: as shown in the following table, a method for evaluating intestinal microorganisms based on dairy cow diarrhea pathogen analysis, which comprises the following specific steps: Figures 1-4

[0049] S1, obtaining the composition of various microbial communities in the feces of a diarrhea dairy cow, comparing it with the feces of a normal dairy cow, obtaining potential pathogenic microorganisms therein, and obtaining feces image features;

[0050] In the embodiment, obtaining the composition of various microbial communities in the feces of a diarrhea dairy cow, comparing it with the feces of a normal dairy cow, obtaining potential pathogenic microorganisms therein, and obtaining feces image features comprises the following specific contents:

[0051] Obtaining a diarrhea dairy cow feces sample, obtaining the microbial abundance data and microbial species data in the diarrhea dairy cow feces sample by gene sequencing, comparing the microbial abundance data and microbial species data in the diarrhea dairy cow feces sample with the microbial abundance data and microbial species data in the normal dairy cow feces, obtaining the corresponding microbial species whose microbial abundance is not within the normal range, and setting it as a potential pathogenic microorganism, and storing the collected data in a storage module;

[0052] ​Color and morphological data of the diarrhea cow fecal image are acquired, and dietary record data in the cycle of the cow are acquired, and the collected data are stored in a storage module;

[0053] S2, based on the fecal image features and the potential pathogenic microorganism features, analyze the diarrhea cow related microorganism features;

[0054] In this embodiment, based on the fecal image features and the potential pathogenic microorganism features, analyzing the diarrhea cow related microorganism features includes the following specific steps:

[0055] S21, color and morphological data of the diarrhea cow fecal image are acquired, and color and morphological data of the fecal image of the identified pathogenic microorganism are acquired, wherein the morphological data includes size and shape data, fecal similarity analysis is performed, and then pathogenic microorganism first probability is acquired;

[0056] Specifically includes the following steps:

[0057] S211, the color of the diarrhea cow fecal image and the color of the identified pathogenic microorganism fecal image are introduced into a color similarity calculation formula to calculate the color similarity; wherein the color similarity calculation formula can be a Euclidean distance or a cosine similarity calculation method, if the Euclidean distance method is used to calculate the color similarity, the calculation steps are: first, the fecal image of the diarrhea cow and the fecal image of the known pathogenic microorganism are collected; the images are preprocessed, including adjusting the size, gray scale (if only considering the gray scale information) or extracting the color channel (if considering the color information); color features are extracted from the processed images, which usually involves converting the color value (such as RGB value) of each pixel in the image into coordinates in the color space, such as RGB, HSV or Lab color space, the color feature vector of the whole image can be represented by using the average value, weighted average value or other statistical methods; Color feature vector: using RGB color space, for each fecal image, a vector containing R (red), G (green) and B (blue) values will be obtained; Calculate the Euclidean distance: the vector is substituted into the Euclidean distance calculation formula to calculate the Euclidean distance of the image;

[0058] S212, the morphological data of the diarrhea cow fecal image and the morphological data of the identified pathogenic microorganism fecal image are introduced into a morphological similarity calculation formula to calculate the morphological similarity, wherein the morphological similarity calculation formula is: the intersection area of two images divided by the union area of two images;

[0059] S213, obtain the calculated color similarity and the shape similarity, and obtain the fecal similarity by weighted summation, set the fecal similarity of the fecal image corresponding to the historical identified pathogenic microorganism as the pathogenic microorganism first probability corresponding to the historical identified pathogenic microorganism;

[0060] S22, obtain the corresponding microbial species with the abundance not in the normal range in the diarrhea cow feces, and introduce the proportion of the abundance of the corresponding microbial species exceeding the normal range and the number of times of causing cow diarrhea of the corresponding microbial species history into the pathogenic microorganism second probability calculation formula to calculate the pathogenic microorganism second probability, wherein the i-th pathogenic microorganism second probability calculation formula is:

[0061] , wherein n is the number of microbial species in the diarrhea cow feces, fi is the number of times of causing cow diarrhea of the i-th microbial species in the corresponding period, exp() is the number of times of the natural constant e, ki is the abundance of the i-th microbial species, and kim is the maximum value of the normal range of the abundance of the i-th microbial species;

[0062] In this step, the second probability of the pathogenic microorganism causing diarrhea is analyzed by the abundance of the microbial species and the number of times of causing cow diarrhea of the corresponding microbial species history;

[0063] S23, obtain the pathogenic microorganism first probability and the pathogenic microorganism second probability corresponding to the pathogenic microorganism, and obtain the influence probability of the corresponding pathogenic microorganism by weighted summation, and obtain the corresponding pathogenic microorganism with the influence probability greater than or equal to the set probability as the diarrhea cow related microorganism;

[0064] S3, analyze the diet influence of the microorganism based on the characteristics of the diarrhea cow related microorganism and the diet habit of the diarrhea cow;

[0065] In this embodiment, the diet influence of the microorganism is predicted based on the analysis of the characteristics of the diarrhea cow related microorganism and the diet habit of the diarrhea cow, which includes the following specific steps:

[0066] S31, obtain the abundance of the diarrhea cow related microbial species and the detected microbial species content data of various diets in the diet habit of the diarrhea cow, wherein the diet of the diarrhea cow includes various forages and drinking water;

[0067] S32, analyze the diet influence of various diets on the diarrhea cow based on the abundance of the diarrhea cow related microbial species and the detected microbial species data of various diets in the diet habit of the diarrhea cow, wherein the diet influence calculation formula of the j-th diet on the diarrhea cow is:

[0068] wherein M is the number of detected diarrhea cow related microorganism species of the jth diet, Tc is the content of the cth detected diarrhea cow related microorganism species of the jth diet, Tm is the content standard value, and Jc is the influence probability of the cth diarrhea cow related microorganism species.

[0069] In this step, the influence of the diet is predicted by the similarity of the microbial content of the diet and the diarrhea cow related microorganism;

[0070] S4, based on the predicted microbial diet influence and the matching degree of the diarrhea time of the diarrhea cow, the diarrhea cause of the cow is evaluated;

[0071] In this embodiment, the evaluation of the diarrhea cause of the cow based on the predicted microbial diet influence and the matching degree of the diarrhea time of the diarrhea cow includes the following specific contents: S41, the feeding time, diet type and diarrhea time of the cow in the period are obtained, and the matching degree of the diarrhea time and the diet type, i.e. the time influence probability, is obtained based on the feeding time, diet type and diarrhea time of the cow, wherein the calculation formula of the matching degree of the diarrhea time and the jth diet type is:

[0072] wherein Vj is the number of times of the jth diet type in the period, Uv is the diarrhea times of the vth time of drinking the jth diet type in the period, is the total amount of diarrhea of the vth time of drinking the jth diet type in the period, is the amount of diet of the vth time of drinking the jth diet type in the period, and tm is the standard time length of diarrhea, is the time length between the uth diarrhea after the vth time of drinking the jth diet type in the period; in this formula, the abnormal diet is quickly found by analyzing the matching degree of the diet and the diarrhea in time;

[0073] S42, the matching degree of the diarrhea time and the diet type and the diet influence of various diets on the diarrhea cow are obtained, and the total influence of the corresponding diet type on the diarrhea is obtained after weighted summation;

[0074] S43, the total influence of the corresponding diet type on the diarrhea is arranged in descending order, and the several corresponding diet types arranged in front are set as the diet reason of the diarrhea of the cow, and are sent to the client, and the client replaces the diet.

[0075] The benefits of the present embodiment over the prior art are: obtaining the composition of various microbial communities in the feces of diarrhea cows, comparing it with the feces of normal cows, obtaining potential pathogenic microorganisms, obtaining fecal image features, analyzing diarrhea cow-related microbial features based on fecal image features and potential pathogenic microorganism features, predicting the dietary impact of microorganisms based on the analysis of diarrhea cow-related microbial features and the dietary habits of diarrhea cows, predicting the dietary impact of microorganisms based on the matching degree of the predicted dietary impact of microorganisms and the diarrhea time of diarrhea cows, and evaluating the cause of diarrhea in cows. By comparing the fecal microbial communities of diarrhea and normal cows, potential pathogenic microorganisms related to diarrhea can be identified, thereby more accurately diagnosing the cause of diarrhea. Combining image features and microbial community analysis of feces can provide a more comprehensive understanding of the pathological mechanism of diarrhea, helping to scientifically guide the development of treatment plans. By analyzing the impact of microorganisms on the dietary habits of cows, the feed formula and feeding conditions of cows can be optimized to prevent the occurrence of diarrhea and improve the health level of cows. Based on the prediction model of the dietary impact of microorganisms and the matching degree of the diarrhea time, the accuracy of the evaluation of the cause of diarrhea can be improved, providing a scientific basis for clinical veterinary decision-making. Embodiment 2

[0076] As shown in Figure 5 , the intestinal microbial evaluation system based on cow diarrhea pathogen analysis is implemented based on the above-mentioned intestinal microbial evaluation method based on cow diarrhea pathogen analysis, and specifically includes: an acquisition module that acquires the composition of various microbial communities in the feces of diarrhea cows, compares it with the feces of normal cows, and acquires potential pathogenic microorganisms, while acquiring fecal image features; a microbial feature analysis module that analyzes diarrhea cow-related microbial features based on fecal image features and potential pathogenic microorganism features; a dietary impact prediction module that predicts the dietary impact of microorganisms based on the analysis of diarrhea cow-related microbial features and the dietary habits of diarrhea cows; and a diarrhea cause evaluation module that evaluates the cause of diarrhea in cows based on the predicted dietary impact of microorganisms and the matching degree of the diarrhea time of diarrhea cows. Embodiment 3

[0077] The present embodiment provides an electronic device, comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0078] The processor executes the above-mentioned intestinal microbial evaluation method based on cow diarrhea pathogen analysis by calling the computer program stored in the memory.

[0079] The electronic device can have a large difference due to different configurations or performances, and can include one or more processors and one or more memories in which at least one computer program is stored, the computer program being loaded and executed by the processor to implement the method of evaluating intestinal microorganisms based on analysis of a dairy cow diarrhea pathogen provided by the above-mentioned method embodiment. The electronic device can also include other components for implementing device functions, for example, the electronic device can also have a wired or wireless network interface and an input and output interface, and the like, so as to perform input and output of data. This embodiment will not be described here. Embodiment 4

[0080] The embodiment provides a computer readable storage medium, which stores an erasable computer program.

[0081] When the computer program is run on the computer device, the computer device is caused to execute the method of evaluating intestinal microorganisms based on analysis of a dairy cow diarrhea pathogen described above.

[0082] For example, the computer readable storage medium can be a read-only memory, a random access memory, a read-only optical disc, a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0083] The above-mentioned embodiments can be realized by software, hardware, firmware or any combination thereof, in whole or in part. When realized by software, the above-mentioned embodiments can be realized in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the flow or function according to the embodiments of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable device. The computer instructions can be stored in a computer readable storage medium or transferred from one computer readable storage medium to another, for example, the computer instructions can be transferred from one website, computer, server or data center to another website, computer, server or data center through a wired network or / and a wireless network. The computer readable storage medium can be any available medium accessible by a computer or a data storage device such as a server, data center and the like containing one or more available medium sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD) or a semiconductor medium. The semiconductor medium can be a solid state disk.

Claims

1. An intestinal microbial evaluation system based on the pathogen analysis of dairy cow diarrhea, characterized by: Specifically include: Acquisition module: obtains the composition of various microbial communities in the feces of diarrheal cows, compares it with the feces of normal cows, obtains potential pathogenic microorganisms, and obtains fecal image features; Microbial feature analysis module: Analyzes microbial features related to diarrheal cows based on fecal image features and potential pathogenic microbial features; Dietary impact prediction module: This module predicts the dietary impact of microorganisms based on the analysis of microbial characteristics related to diarrheal cows and their dietary habits; Diarrhea Cause Assessment Module: This module assesses the cause of diarrhea in dairy cows based on the predicted microbial diet impact and the degree of matching between the diarrheal cows and the diarrheal cows. Analyzing the microbial characteristics associated with diarrheal cows includes the following specific steps: S21, obtaining color and morphological data of feces images of diarrheal cows, and simultaneously obtaining color and morphological data of feces images of previously identified pathogenic microorganisms, performing feces similarity analysis, and then obtaining a first probability of the pathogenic microorganisms; S22. Obtain the corresponding microbial species whose abundance in the feces of the diarrheal cow is not within the normal range, and introduce the proportion of the corresponding microbial species whose abundance exceeds the normal range and the number of times the corresponding microbial species has caused diarrhea in the cow into the second probability calculation formula of the pathogenic microorganism to calculate the second probability of the pathogenic microorganism, wherein the calculation formula for the second probability of the i-th pathogenic microorganism is: , where n is the number of microbial species in the feces of diarrheal dairy cows, fi is the number of times the i-th microbial species causes diarrhea in the corresponding period, exp() is the power of the natural constant e, ki is the abundance of the i-th microbial species, and kim is the maximum value of the normal range of abundance of the i-th microbial species; S23, obtaining a first probability of the pathogenic microorganism and a second probability of the pathogenic microorganism for the corresponding pathogenic microorganism, performing weighted summation to obtain an influence probability of the corresponding pathogenic microorganism, and obtaining the corresponding pathogenic microorganism with an influence probability greater than or equal to the set probability as the microorganism associated with diarrheal cows; The method for predicting the dietary effects on microorganisms includes the following specific steps: S31. Obtaining data on the abundance of microbial species associated with dairy cows with diarrhea and the content of microbial species detected in various diets of dairy cows with diarrhea, wherein the diet of dairy cows with diarrhea includes various feeds and drinking water; S32. Analyze the dietary effects of various diets on diarrhea cows based on the abundance of microbial species associated with diarrhea cows and the microbial species detected in the dietary habits of diarrhea cows. The formula for calculating the dietary effect of the jth diet on diarrhea cows is: , where M is the number of microbial species related to diarrheal cows detected in the jth diet, Tc is the content of the cth microbial species related to diarrheal cows detected in the jth diet, Tm is the standard value of the content, and Jc is the influence probability of the cth microbial species related to diarrheal cows; The cow diarrhea cause assessment includes the following specific contents: S41, obtaining the cow's eating time, diet type, and diarrhea time within a cycle, and obtaining the matching degree between the diarrhea time and diet type based on the cow's eating time, diet type, and diarrhea time; S42. Obtaining the calculated matching degree between diarrhea time and diet type and the dietary effects of various diets on dairy cows with diarrhea, and performing weighted summation to obtain the total effect of the corresponding diet type on diarrhea; S43. Obtain the total effects of corresponding diet types on diarrhea and arrange them in descending order. Obtain several corresponding diet types that are ranked first and set them as the dietary causes of diarrhea in dairy cows. Send the results to the client, and the client changes the diet.

2. The intestinal microbial evaluation system based on the pathogen analysis of dairy cow diarrhea according to claim 1, characterized in that: The acquisition of the first probability of the pathogenic microorganism specifically includes the following steps: S211, obtaining the color of the diarrhea cow feces image and the color of the feces image of the identified pathogenic microorganisms, and inputting them into a color similarity calculation formula to calculate the color similarity; S212, obtaining morphological data of the diarrhea cow feces image and the morphological data of the feces image of the identified pathogenic microorganisms, and inputting the data into a morphological similarity calculation formula to calculate morphological similarity, wherein the morphological similarity calculation formula is: the intersection area of ​​the two images divided by the union area of ​​the two images; S213. Obtain the calculated color similarity and morphological similarity, perform weighted summation on them to obtain a stool similarity, and set the stool similarity of the stool image corresponding to the historically identified pathogenic microorganism as the first probability of the pathogenic microorganism corresponding to the historically identified pathogenic microorganism.

3. The intestinal microorganism evaluation system based on the pathogen analysis of dairy cow diarrhea according to claim 2, characterized in that: The method of obtaining the composition of various microbial communities in the feces of diarrheal cows and comparing it with the feces of normal cows to obtain potential pathogenic microorganisms therein and obtaining fecal image features includes the following specific contents: Obtain fecal samples from diarrheal cows, obtain the abundance data and microbial species data of each microorganism in the fecal samples of diarrheal cows through gene sequencing, and compare the abundance data and microbial species data of each microorganism in the feces of normal dairy cows to obtain the corresponding microbial species whose microbial abundance is not within the normal range, set them as potential pathogenic microorganisms, and store the collected data in a storage module; The color and morphological data of the feces image of the diarrheal cow are obtained, and the diet record data of the cow during the cycle is obtained, and the collected data is stored in the storage module.

4. The intestinal microbial evaluation system based on the pathogen analysis of dairy cow diarrhea according to claim 3, characterized in that: The color similarity calculation formula is a Euclidean distance or cosine similarity calculation method.

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