Method and system for detecting and evaluating frog virus in aquaculture water based on tangential flow enrichment

Abstract

The invention discloses a method and a system for detecting and evaluating frog viruses in culture water based on tangential flow enrichment, and aims to improve the accuracy and efficiency of virus monitoring in frog culture water. The method comprises the following steps: dividing a culture pond into a plurality of sub-regions, obtaining hydrodynamic parameters of each region, and determining spatial distribution of water flow exchange efficiency; analyzing the growth suitability of the frog virus according to the distribution, and determining the detection position of the virus; detecting viruses in a preset time period by utilizing a tangential flow enrichment technology, and evaluating the change of the virus content; and predicting a virus diffusion trend according to the change data, and providing a corresponding water environment regulation scheme. According to the method, the detection sensitivity and diffusion prediction accuracy of the frog virus can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of tangential flow enrichment, and in particular to a method and system for detecting and evaluating frog viruses in aquaculture water based on tangential flow enrichment. Background Art

[0002] In recent years, with the rapid development of aquaculture, frog farming has gradually become an important farming model. However, the growth process of frogs in the aquatic environment is vulnerable to the threat of a variety of pathogenic microorganisms, especially the spread and spread of frog viruses, which poses a major risk to the health of frogs. Frog virus infection often causes large-scale frog diseases, seriously affecting the breeding benefits and causing huge economic losses. Therefore, how to effectively monitor and control the spread of frog viruses has become a technical problem that needs to be solved urgently in the field of frog farming.

[0003] Traditional frog virus monitoring methods usually rely on manual sampling and laboratory testing, which are long and inefficient, and it is difficult to accurately evaluate the dynamic changes of frog viruses in aquaculture water in real time. In addition, fluid dynamics parameters such as water flow velocity and water flow direction in aquaculture water have an important impact on the spread of frog viruses, but there is currently a lack of systematic methods for comprehensive analysis of these parameters and combined with virus detection.

[0004] In recent years, tangential flow enrichment technology has been widely used in the field of water quality monitoring due to its high efficiency in enriching tiny particles in water bodies. This technology can significantly improve the detection sensitivity of target substances such as microorganisms and viruses in water samples. However, in the prior art, there is no frog virus detection scheme based on tangential flow enrichment technology that can combine the spatial distribution of water flow exchange efficiency to predict the virus diffusion trend and formulate an effective aquaculture water environment regulation scheme.

[0005] Therefore, there is an urgent need for a comprehensive method that combines tangential flow enrichment technology and fluid dynamics analysis to enable real-time monitoring, diffusion prediction, and environmental regulation of frog viruses in aquaculture water, so as to improve the safety and production efficiency of frog farming. Summary of the invention

[0006] In order to solve at least one of the above technical problems, the present invention proposes a method and system for detecting and evaluating frog viruses in aquaculture water based on tangential flow enrichment.

[0007] The first aspect of the present invention provides a method for detecting and evaluating frog viruses in aquaculture water based on tangential flow enrichment, comprising:

[0008] Divide the target frog breeding pond into N breeding water body sub-areas, obtain the fluid dynamics parameters of each sub-area, and determine the spatial distribution of water flow exchange efficiency of the target frog breeding pond according to the fluid dynamics parameters;

[0009] Analyzing the growth suitability of the frog virus in the target frog breeding pond according to the spatial distribution of the water exchange efficiency, and determining the detection position of the frog virus according to the growth suitability of the frog virus;

[0010] Based on the tangential flow enrichment technology, the frog virus at the detection position in the preset time period is detected, and the change of the frog virus content at the detection position in the preset time period is evaluated to obtain the frog virus content change data;

[0011] Predicting the spread trend of the frog virus in the target frog breeding pond according to the frog virus content change data to obtain a prediction result;

[0012] A plan for regulating the aquaculture water environment of the target frog breeding pond is determined based on the prediction results.

[0013] In this scheme, the target frog breeding pond is divided into N breeding water sub-areas, the fluid dynamics parameters of each sub-area are obtained, and the spatial distribution of the water flow exchange efficiency of the target frog breeding pond is determined according to the fluid dynamics parameters, specifically:

[0014] Acquire geometric shape data of a target frog breeding pond, construct a three-dimensional model of the target frog breeding pond according to the geometric shape data, and divide the target frog breeding pond into N breeding water body sub-areas according to the three-dimensional model;

[0015] Acquire fluid dynamics parameters and position coordinate information of each sub-area based on a flow velocity sensor, wherein the fluid dynamics parameters include water flow velocity and water flow direction of each sub-area;

[0016] The fluid dynamics parameters are converted into numerical expressions, and the fluid dynamics parameters in the numerical expressions and the position coordinate information are normalized based on a Z-score normalization method to obtain normalized fluid dynamics parameters and position coordinate information;

[0017] An OPTICS clustering algorithm is introduced, and a clustering operation is performed on the standardized fluid dynamics parameters and position coordinate information according to the OPTICS clustering algorithm to obtain a clustering result;

[0018] Extracting the clusters output by the clustering result, obtaining the sub-regions contained in each cluster, dividing the target frog breeding pond into cluster regions according to the sub-regions contained in each cluster, and obtaining the cluster regions represented by each cluster;

[0019] Calculate the average water flow velocity of each cluster area according to the water flow velocity of the sub-areas contained in each cluster;

[0020] Determine the water flow exchange efficiency of each cluster area according to the average water flow velocity of each cluster area, map the water flow exchange efficiency of each cluster area into the three-dimensional model, and draw a spatial distribution map of the water flow exchange efficiency in the target frog breeding pond;

[0021] The spatial distribution of water exchange efficiency in the target frog breeding pond is determined according to the water exchange efficiency spatial distribution map.

[0022] In this solution, the standardized fluid dynamics parameters and position coordinate information are clustered according to the OPTICS clustering algorithm to obtain a clustering result, which is specifically:

[0023] Converting the standardized fluid dynamics parameters and position coordinate information into feature vectors to obtain a feature vector data set for each sub-region;

[0024] Setting the basic parameters of the OPTICS clustering algorithm, wherein the basic parameters include the maximum distance threshold ε between two data points and the minimum number of data points MinPts in each cluster;

[0025] Marking each data point in the feature vector data set as an unvisited state, visiting each data point in the feature vector data set in turn, and marking the data point that enters the visited state as an visited state data point;

[0026] Obtain data points in the ε neighborhood of the access status data point. If the number of data points in the ε neighborhood is not less than MinPts, mark the access status data point as a core point. If the number of data points in the ε neighborhood is less than MinPts, mark the access status data point as a noise point. Calculate the Manhattan distance from the core point to the MinPts-th nearest point in the ε neighborhood to obtain the core distance of the core point.

[0027] For each data point in the ε neighborhood of the accessed state data point, if the neighborhood data point has not been visited, the reachable distance between the neighborhood data point and the core point is calculated, and each unvisited neighborhood data point is inserted into the priority queue, ending the access state of the accessed state data point;

[0028] Sequentially taking out the smallest reachable distance points from the priority queue as access status data points for access, and updating the priority queue until all data points in the priority queue are accessed, thereby obtaining a clustering sequence table;

[0029] A reachable distance graph is generated according to the clustering sequence table, clusters of the standardized fluid dynamics parameters and position coordinate information are identified according to the reachable distance graph, and the clusters are output to obtain clustering results.

[0030] In this scheme, the growth suitability of the frog virus in the target frog breeding pond is analyzed according to the spatial distribution of the water exchange efficiency, and the detection position of the frog virus is determined according to the growth suitability of the frog virus, specifically:

[0031] According to the spatial distribution of the water exchange efficiency, a high water exchange area, a low water exchange area, and a water flow stop area in the target frog breeding pond are identified to obtain water exchange partitions;

[0032] Obtain water impurity content data of each sub-area in the target frog breeding pond and water purification capacity data of each water flow exchange partition, and analyze the accumulation of water impurities in each sub-area over a preset time length according to the water impurity content data and the water purification capacity data of each water flow exchange partition;

[0033] Performing water quality assessment on each sub-area according to the accumulation of impurities in the water body to obtain a water quality assessment result;

[0034] Acquire suitable water quality condition data for frog virus, determine the suitability of frog virus growth in each sub-area according to the suitable water quality condition data and the water quality assessment result, and determine the frog virus growth risk in each sub-area according to the frog virus growth suitability;

[0035] The detection position of the frog virus is determined according to the frog virus growth risk.

[0036] In this scheme, the tangential flow enrichment technology is used to detect the frog virus at the detection position in a preset time period, and the frog virus content change at the detection position in the preset time period is evaluated to obtain the frog virus content change data, specifically:

[0037] Acquire water samples at the detection location in a preset time period according to a preset detection time period, analyze the water impurity content of the water samples, and if the water impurity content is greater than a preset content, perform an impurity filtering operation on the water samples;

[0038] Acquire frog virus size data, determine the filter membrane pore size for tangential flow enrichment according to the frog virus size data, and perform frog virus enrichment operation on the water sample after impurity filtration operation based on the tangential flow enrichment technology according to the filter membrane pore size to obtain an enriched sample;

[0039] Performing frog virus detection on the enriched sample to determine the frog virus content of the enriched sample to obtain a detection result;

[0040] The detection results are sorted according to the time series to obtain the frog virus content change data of the detection position in the preset time period.

[0041] In this scheme, the spread trend of the frog virus in the target frog breeding pond is predicted according to the frog virus content change data to obtain the prediction results, which are specifically:

[0042] Performing a stability test on the frog virus content change data based on the ADF test, if the stability of the frog virus content change data is lower than a preset stability value, performing a differential operation on the frog virus content change data to obtain stable frog virus content change data;

[0043] Constructing a frog virus content prediction model based on the ARIMA algorithm, constructing an autocorrelation function graph and a partial autocorrelation function graph based on the stable data of frog virus content changes, and determining the autoregressive order and moving average order of the frog virus content prediction model according to the autocorrelation function graph and the partial autocorrelation function graph;

[0044] The parameters of the frog virus content prediction model are set according to the autoregressive order and the moving average order, the stable data of frog virus content change is imported into the frog virus content prediction model for training, and the model parameters are optimized based on the maximum likelihood estimation method;

[0045] Based on the tangential flow enrichment technology, real-time data on the change in the amount of frog virus at each frog virus detection position in the current preset time period are obtained in real time, and the real-time data on the change in the amount of frog virus is imported into a frog virus content prediction model to predict the amount of frog virus at each frog virus detection position in the future preset time period, thereby obtaining frog virus content prediction data;

[0046] The frog virus diffusion trend of the target frog breeding pond is predicted according to the frog virus content prediction data to obtain a prediction result, which includes the change in the number of frog viruses and the location and diffusion of the frog viruses.

[0047] In this scheme, the aquaculture water environment adjustment scheme of the target frog breeding pond is determined according to the prediction results, specifically:

[0048] According to the prediction results, the risk of frogs in the target frog breeding pond being infected with frog virus in a preset time period in the future is evaluated to obtain a frog virus infection risk evaluation result;

[0049] Obtaining a frog virus infection risk control threshold in a target breeding pond, comparing the frog virus infection risk assessment result with the frog virus infection risk control threshold, marking a time period in a future preset time period when the frog virus infection risk in the target frog breeding pond is higher than the frog virus infection risk control threshold, and obtaining a marked time period;

[0050] Acquire the controllable range data of the inflow and outflow of the target frog breeding pond, and determine the inflow and outflow control parameters of the target frog breeding pond in the marked time period according to the controllable range data of the inflow and outflow and the predicted data of the frog virus content in the marked time period;

[0051] Constructing a dynamic regulation scheme for the aquaculture water environment of the target frog aquaculture pond according to the water inlet and outlet control parameters of the marked time period;

[0052] Acquire the inlet and outlet position information of the target frog breeding pond, construct a water flow simulation model of the target frog breeding pond according to the inlet and outlet position information, perform inlet and outlet simulation operations on the breeding water environment dynamic adjustment scheme based on the water flow simulation model, and determine the water quality update status of the target frog breeding pond;

[0053] The purification effect of the frog virus is evaluated according to the water quality update situation, and the frog virus infection risk of the marked time period is re-evaluated according to the purification effect. If the frog virus infection risk of the marked time period is still higher than the frog virus infection risk control threshold, the time period still higher than the frog virus infection risk control threshold is marked as a time period to be optimized for the second time;

[0054] Determine the maximum water flow renewal amount of the target frog breeding pond according to the controllable range data of the water inflow and outflow of the target frog breeding pond;

[0055] The time advance of adjusting the inlet and outlet water volume of the target frog breeding pond is calculated according to the maximum water flow update amount and the predicted data of the frog virus content in the time period to be optimized for the second time, and the dynamic adjustment plan of the breeding water environment is optimized according to the time advance to obtain the breeding water environment adjustment plan of the target frog breeding pond.

[0056] The second aspect of the present invention also provides a frog virus detection and evaluation system in aquaculture water based on tangential flow enrichment, the system comprising: a memory, a processor, the memory comprising a frog virus detection and evaluation method program in aquaculture water based on tangential flow enrichment, the frog virus detection and evaluation method program in aquaculture water based on tangential flow enrichment being executed by the processor to implement the following steps:

[0057] Divide the target frog breeding pond into N breeding water body sub-areas, obtain the fluid dynamics parameters of each sub-area, and determine the spatial distribution of water flow exchange efficiency of the target frog breeding pond according to the fluid dynamics parameters;

[0058] Analyzing the growth suitability of the frog virus in the target frog breeding pond according to the spatial distribution of the water exchange efficiency, and determining the detection position of the frog virus according to the growth suitability of the frog virus;

[0059] Based on the tangential flow enrichment technology, the frog virus at the detection position in the preset time period is detected, and the change of the frog virus content at the detection position in the preset time period is evaluated to obtain the frog virus content change data;

[0060] Predicting the spread trend of the frog virus in the target frog breeding pond according to the frog virus content change data to obtain a prediction result;

[0061] A plan for regulating the aquaculture water environment of the target frog breeding pond is determined based on the prediction results.

[0062] The present invention discloses a method and system for detecting and evaluating frog viruses in aquaculture water based on tangential flow enrichment, aiming to improve the accuracy and efficiency of virus monitoring in frog aquaculture water. The method includes: dividing the aquaculture pond into multiple sub-areas, obtaining the fluid dynamics parameters of each area, and determining the spatial distribution of water flow exchange efficiency; analyzing the growth suitability of frog viruses based on the distribution, and determining the detection position of the virus; using tangential flow enrichment technology to detect viruses within a preset time period and evaluate changes in virus content; predicting the virus diffusion trend based on the change data, and proposing corresponding water environment adjustment plans. This method can effectively improve the detection sensitivity and diffusion prediction accuracy of frog viruses. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 A flow chart showing a method for detecting and evaluating frog viruses in aquaculture water based on tangential flow enrichment according to the present invention is shown;

[0064] Figure 2 A flow chart of determining the detection position of a ranavirus according to the present invention is shown;

[0065] Figure 3 The flow chart of obtaining the data of change of the content of frog virus in the present invention is shown;

[0066] Figure 4 A block diagram of a frog virus detection and evaluation system in aquaculture water based on tangential flow enrichment according to the present invention is shown. DETAILED DESCRIPTION

[0067] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0068] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0069] Figure 1 The present invention shows a flow chart of a method for detecting and evaluating frog viruses in aquaculture water based on tangential flow enrichment.

[0070] like Figure 1 As shown, the first aspect of the present invention provides a method for detecting and evaluating frog viruses in aquaculture water based on tangential flow enrichment, comprising:

[0071] S102, dividing the target frog breeding pond into N breeding water body sub-areas, obtaining fluid dynamics parameters of each sub-area, and determining the spatial distribution of water flow exchange efficiency of the target frog breeding pond according to the fluid dynamics parameters;

[0072] S104, analyzing the growth suitability of the frog virus in the target frog breeding pond according to the spatial distribution of the water exchange efficiency, and determining the detection position of the frog virus according to the growth suitability of the frog virus;

[0073] S106, detecting the ranavirus at the detection position in a preset time period based on the tangential flow enrichment technology, evaluating the change of the ranavirus content at the detection position in the preset time period, and obtaining the ranavirus content change data;

[0074] S108, predicting the spread trend of the frog virus in the target frog breeding pond according to the frog virus content change data to obtain a prediction result;

[0075] S110, determining a plan for regulating the aquaculture water environment of the target frog aquaculture pond according to the prediction result.

[0076] It should be noted that by dividing the breeding pond into multiple sub-areas and obtaining fluid dynamic parameters such as water flow velocity and direction, the water flow characteristics of the entire breeding pond can be analyzed in detail. The spatial distribution of water flow exchange efficiency can help identify the water quality renewal capacity of different areas; by analyzing the spatial distribution of water flow exchange efficiency, the high-efficiency water flow exchange area and the low-efficiency water flow exchange area can be determined, and combined with the growth characteristics of frog viruses, the areas where the virus growth is more suitable can be identified; the tangential flow enrichment technology can efficiently enrich the frog virus particles in the water body and improve the detection sensitivity; by analyzing the data on the change of frog virus content, the spread trend of the virus in the breeding pond can be accurately predicted, including the direction and speed of virus spread and the future infection risk, and by discovering potential high-risk areas in advance, the spread of the virus can be warned, thereby reducing the threat of the virus to frogs; according to the predicted virus spread trend, a water environment adjustment plan can be formulated to effectively control the spread of frog viruses, optimize water circulation and water quality management, and improve the health level of frogs. By reasonably adjusting the inlet and outlet water volume or water flow velocity, the risk of virus accumulation and transmission can be reduced, the water environment of the frog breeding pond can be accurately controlled, and the breeding efficiency and yield can be improved.

[0077] According to an embodiment of the present invention, the target frog breeding pond is divided into N breeding water body sub-areas, the fluid dynamics parameters of each sub-area are obtained, and the spatial distribution of the water flow exchange efficiency of the target frog breeding pond is determined according to the fluid dynamics parameters, specifically:

[0078] Acquire geometric shape data of a target frog breeding pond, construct a three-dimensional model of the target frog breeding pond according to the geometric shape data, and divide the target frog breeding pond into N breeding water body sub-areas according to the three-dimensional model;

[0079] Acquire fluid dynamics parameters and position coordinate information of each sub-area based on a flow velocity sensor, wherein the fluid dynamics parameters include water flow velocity and water flow direction of each sub-area;

[0080] The fluid dynamics parameters are converted into numerical expressions, and the fluid dynamics parameters in the numerical expressions and the position coordinate information are normalized based on a Z-score normalization method to obtain normalized fluid dynamics parameters and position coordinate information;

[0081] Introducing the OPTICS clustering algorithm, performing clustering operations on the standardized fluid dynamics parameters and position coordinate information according to the OPTICS clustering algorithm to obtain clustering results;

[0082] Extracting the clusters output by the clustering result, obtaining the sub-regions contained in each cluster, dividing the target frog breeding pond into cluster regions according to the sub-regions contained in each cluster, and obtaining the cluster regions represented by each cluster;

[0083] Calculate the average water flow velocity of each cluster area according to the water flow velocity of the sub-areas contained in each cluster;

[0084] Determine the water flow exchange efficiency of each cluster area according to the average water flow velocity of each cluster area, map the water flow exchange efficiency of each cluster area into the three-dimensional model, and draw a spatial distribution map of the water flow exchange efficiency in the target frog breeding pond;

[0085] The spatial distribution of water exchange efficiency in the target frog breeding pond is determined according to the water exchange efficiency spatial distribution map.

[0086] It should be noted that after the fluid dynamics parameters of different regions are standardized by Z-score, the parameters can be compared under the same standard. This process eliminates the differences in the numerical ranges of different parameters, so that the fluid dynamics characteristics of each sub-region can be balanced during clustering, and the parameters with larger values ​​are prevented from dominating the clustering results; the OPTICS (Ordering Points To Identify the Clustering Structure) clustering algorithm can divide the aquaculture pond into multiple clusters with similar water flow characteristics according to the fluid dynamics parameters (such as water flow velocity and water flow direction) and their position coordinate information. Through OPTICS clustering, sub-regions with similar water flow velocity and direction can be classified into the same cluster, thereby effectively distinguishing areas with large differences in water flow dynamics in the aquaculture pond. Each cluster in the clustering result represents an area with similar flow characteristics in the aquaculture pond. Based on the water flow velocity in each cluster, the average water flow velocity of the area can be calculated. Water flow velocity is an important parameter for measuring water flow exchange efficiency. The faster the water flow, the higher the exchange efficiency. After OPTICS clustering, the average water flow velocity and exchange efficiency of each area can be intuitively presented in the form of a spatial distribution map. Based on the generated spatial distribution map of water exchange efficiency, areas with low water exchange efficiency can be intuitively found. Inefficient water flow areas may cause water quality deterioration or accumulation of frog viruses in these areas, affecting the overall aquaculture health.

[0087] According to an embodiment of the present invention, the standardized fluid dynamics parameters and position coordinate information are clustered according to the OPTICS clustering algorithm to obtain a clustering result, which is specifically:

[0088] Converting the standardized fluid dynamics parameters and position coordinate information into feature vectors to obtain a feature vector data set for each sub-region;

[0089] Setting the basic parameters of the OPTICS clustering algorithm, wherein the basic parameters include the maximum distance threshold ε between two data points and the minimum number of data points MinPts in each cluster;

[0090] Marking each data point in the feature vector data set as an unvisited state, visiting each data point in the feature vector data set in turn, and marking the data point that enters the visited state as an visited state data point;

[0091] Obtain data points in the ε neighborhood of the access status data point. If the number of data points in the ε neighborhood is not less than MinPts, mark the access status data point as a core point. If the number of data points in the ε neighborhood is less than MinPts, mark the access status data point as a noise point. Calculate the Manhattan distance from the core point to the MinPts-th nearest point in the ε neighborhood to obtain the core distance of the core point.

[0092] For each data point in the ε neighborhood of the accessed state data point, if the neighborhood data point has not been visited, the reachable distance between the neighborhood data point and the core point is calculated, and each unvisited neighborhood data point is inserted into the priority queue, ending the access state of the accessed state data point;

[0093] Sequentially taking out the smallest reachable distance points from the priority queue as access status data points for access, and updating the priority queue until all data points in the priority queue are accessed, thereby obtaining a clustering sequence table;

[0094] A reachable distance graph is generated according to the clustering sequence table, clusters of the standardized fluid dynamics parameters and position coordinate information are identified according to the reachable distance graph, and the clusters are output to obtain clustering results.

[0095] It should be noted that in the OPTICS clustering process, by setting the maximum distance threshold (ε) and the minimum number of data points (MinPts), the sub-region data points can be divided into core points and noise points. A core point refers to a point whose number of data points in its ε neighborhood is greater than or equal to MinPts, representing a high-density area. By gradually calculating the distance between data points, the density change of the data is identified, thereby dividing clusters of different densities. This density sensitivity is very suitable for analyzing water flow distribution, because water flow may have different flow velocities and flow patterns in different areas. By calculating the core distance of the core point and the reachable distance of the neighborhood point, OPTICS can accurately divide the areas with high and low water flow exchange efficiency according to the change of water flow density, thereby helping to identify different flow patterns. By generating a reachable distance map to show the density change between data points, different clusters can be intuitively identified based on this map. The trough in the reachable distance map represents a high-density area (i.e., the core area), while the peak represents a sparse area (or noise point). This visualization method can not only help identify different clusters, but also reveal the density structure differences between clusters. By clustering clusters, it is possible to identify areas in the aquaculture pond with higher water flow speed and stronger exchange efficiency, as well as areas with slower water flow and weaker exchange efficiency. Based on this information, it is possible to further analyze the spatial distribution of water flow exchange efficiency, build a three-dimensional model of the aquaculture pond, and draw a spatial distribution map of water flow exchange efficiency; the clustering results cluster sub-areas with similar water flow speed and direction, and these clustered sub-areas can be connected in position to form a cluster.

[0096] Figure 2 The flowchart of the present invention for determining the detection position of the ranavirus is shown.

[0097] According to an embodiment of the present invention, the growth suitability of the frog virus in the target frog breeding pond is analyzed according to the spatial distribution of the water flow exchange efficiency, and the detection position of the frog virus is determined according to the growth suitability of the frog virus, specifically:

[0098] S202, identifying a high water flow exchange area, a low water flow exchange area, and a water flow stop area in the target frog breeding pond according to the spatial distribution of the water flow exchange efficiency, and obtaining a water flow exchange partition;

[0099] S204, obtaining water impurity content data of each sub-area in the target frog breeding pond and water purification capacity data of each water flow exchange partition, and analyzing the accumulation of water impurities in each sub-area over a preset time length according to the water impurity content data and the water purification capacity data of each water flow exchange partition;

[0100] S206, performing water quality assessment on each sub-region according to the accumulation of impurities in the water body to obtain a water quality assessment result;

[0101] S208, obtaining suitable water quality condition data for frog virus, determining the suitability of frog virus growth in each sub-area according to the suitable water quality condition data and the water quality assessment result, and determining the frog virus growth risk in each sub-area according to the frog virus growth suitability;

[0102] S210, determining a detection position of the frog virus according to the frog virus growth risk.

[0103] It should be noted that by analyzing the spatial distribution of water flow exchange efficiency, high water flow exchange areas, low water flow exchange areas and water flow cessation areas in the breeding pond can be effectively identified. Generally, areas with low water flow exchange efficiency are more likely to become hotbeds for virus accumulation, while areas with water flow cessation may become key high-risk areas for the breeding of frog viruses. The growth suitability of frog viruses is closely related to the accumulation of water impurities. By obtaining the water impurity content data and water purification capacity data of each sub-area, and combining the analysis of the preset time length, the accumulation of impurities in each area can be accurately estimated. Inefficient water flow exchange or stopped water flow areas are often prone to the accumulation of water impurities, such as organic matter, waste, and potential virus carriers; according to the accumulation of water impurities, water quality assessment of each sub-area can obtain an accurate analysis of water quality conditions. The quality of water directly affects the growth conditions of frog viruses; by evaluating the water flow exchange efficiency, water quality conditions and impurity accumulation in each sub-area, combined with the suitable conditions of frog viruses, high-risk areas for the growth of frog viruses can be accurately identified. These areas are often places where viruses are more likely to reproduce or spread. By concentrating virus detection in these high-risk areas, the accuracy of virus detection can be significantly improved and waste of resources can be avoided. The detection location is to perform frog virus detection in places where the risk of frog virus growth is greater than a preset value.

[0104] Figure 3 The flowchart of the present invention for obtaining the data of changes in the content of frog virus is shown.

[0105] According to an embodiment of the present invention, the tangential flow enrichment technology is used to detect the frog virus at the detection position in a preset time period, and the frog virus content change at the detection position in the preset time period is evaluated to obtain the frog virus content change data, specifically:

[0106] S302, obtaining water samples at the detection location in a preset time period according to a preset detection time period, analyzing the water impurity content of the water samples, and if the water impurity content is greater than a preset content, performing an impurity filtering operation on the water samples;

[0107] S304, obtaining frog virus size data, determining the filter membrane pore size for tangential flow enrichment according to the frog virus size data, and performing frog virus enrichment operation on the water sample after impurity filtration operation based on the tangential flow enrichment technology according to the filter membrane pore size to obtain an enriched sample;

[0108] S306, performing frog virus detection on the enriched sample to determine the frog virus content of the enriched sample to obtain a detection result;

[0109] S308, sorting the detection results according to the time series to obtain the frog virus content change data of the detection position in the preset time period.

[0110] It should be noted that the tangential flow enrichment technology can effectively concentrate frog viruses in water by allowing water samples to flow along the surface of the filter membrane. The core of this method is that it can reduce membrane fouling while ensuring water flow. By reasonably selecting the pore size of the filter membrane, the tangential flow enrichment technology can effectively remove impurities and improve the detection rate of viruses while maintaining the virus in the water sample. The presence of impurities in water samples may interfere with the detection of frog viruses. By analyzing the impurity content in the water body, the sample can be filtered for impurities. When the impurity content exceeds the preset value, filtering can significantly reduce the impact of impurities on subsequent virus detection. This pretreatment step ensures the purity of the enriched sample and improves the reliability of virus detection.

[0111] According to an embodiment of the present invention, the spread trend of the frog virus in the target frog breeding pond is predicted based on the frog virus content change data to obtain a prediction result, which is specifically:

[0112] Performing a stability test on the frog virus content change data based on the ADF test, if the stability of the frog virus content change data is lower than a preset stability value, performing a differential operation on the frog virus content change data to obtain stable frog virus content change data;

[0113] Constructing a frog virus content prediction model based on the ARIMA algorithm, constructing an autocorrelation function graph and a partial autocorrelation function graph based on the stable data of frog virus content changes, and determining the autoregressive order and moving average order of the frog virus content prediction model according to the autocorrelation function graph and the partial autocorrelation function graph;

[0114] The parameters of the frog virus content prediction model are set according to the autoregressive order and the moving average order, the stable data of frog virus content change is imported into the frog virus content prediction model for training, and the model parameters are optimized based on the maximum likelihood estimation method;

[0115] Based on the tangential flow enrichment technology, real-time data on the change in the amount of frog virus at each frog virus detection position in the current preset time period are obtained in real time, and the real-time data on the change in the amount of frog virus is imported into a frog virus content prediction model to predict the amount of frog virus at each frog virus detection position in the future preset time period, thereby obtaining frog virus content prediction data;

[0116] The frog virus diffusion trend of the target frog breeding pond is predicted according to the frog virus content prediction data to obtain a prediction result, which includes the change in the number of frog viruses and the location and diffusion of the frog viruses.

[0117] It should be noted that the use of ADF (Augmented Dickey-Fuller) test for stationarity detection can ensure that the data used is suitable for time series analysis. If the data stationarity is lower than the preset value, the difference operation is used to obtain stationary data, making the model more stable, reducing the prediction error caused by non-stationary data, and improving the reliability of the prediction results; ARIMA (autoregressive integrated moving average) model, as a time series prediction method, can effectively capture the autocorrelation and trend of data; by analyzing historical and real-time data, the model can identify the spread pattern of frog viruses in the breeding pond. By predicting the potential trend of virus spread in advance, the farm can take preventive measures in advance to avoid large-scale losses caused by virus spread, thereby reducing overall operating costs and improving economic benefits.

[0118] According to an embodiment of the present invention, the aquaculture water environment adjustment scheme of the target frog breeding pond is determined according to the prediction result, specifically:

[0119] According to the prediction results, the risk of frogs in the target frog breeding pond being infected with frog virus in a preset time period in the future is evaluated to obtain a frog virus infection risk evaluation result;

[0120] Obtaining a frog virus infection risk control threshold in a target breeding pond, comparing the frog virus infection risk assessment result with the frog virus infection risk control threshold, marking a time period in a future preset time period when the frog virus infection risk in the target frog breeding pond is higher than the frog virus infection risk control threshold, and obtaining a marked time period;

[0121] Acquire the controllable range data of the inflow and outflow of the target frog breeding pond, and determine the inflow and outflow control parameters of the target frog breeding pond in the marked time period according to the controllable range data of the inflow and outflow and the predicted data of the frog virus content in the marked time period;

[0122] Constructing a dynamic regulation scheme for the aquaculture water environment of the target frog aquaculture pond according to the water inlet and outlet control parameters of the marked time period;

[0123] It should be noted that the frogs in the target frog breeding pond have a certain self-resistance to frog viruses. Under a certain frog virus content, the risk of frog virus infection is controllable. Therefore, the risk of frog virus infection in the preset time period in the future is evaluated through the prediction results, and the time period above the frog virus infection risk control threshold is marked. The marked time period indicates that the risk of frog virus infection is high and epidemic prevention operations are required; by adjusting the inlet and outlet water volume of the target frog breeding pond, the concentration of frog virus in the water body can be effectively adjusted, thereby reducing the risk of infection, and by accurately controlling the inlet and outlet water volume, the waste of water resources can be effectively reduced.

[0124] Acquire the inlet and outlet position information of the target frog breeding pond, construct a water flow simulation model of the target frog breeding pond according to the inlet and outlet position information, perform water inlet and outlet simulation operations on the dynamic regulation scheme of the breeding water environment based on the water flow simulation model, and determine the optimization of the water flow exchange efficiency of the target frog breeding pond according to the spatial distribution of the water flow exchange efficiency;

[0125] It should be noted that the water flow simulation model is constructed through the finite element method to simulate the inlet and outlet water operations of the dynamic regulation scheme of the aquaculture water environment. The water flow simulation model uses the inlet and outlet water of the dynamic regulation scheme of the aquaculture water environment as input conditions to determine the water flow conditions in each sub-area and then determine the optimization of the water flow exchange efficiency of the target frog breeding pond in the spatial distribution of the water flow exchange efficiency.

[0126] Determine the water quality update of each sub-area in the target frog breeding pond according to the water flow exchange efficiency optimization;

[0127] The purification effect of the frog virus is evaluated according to the water quality update situation, and the frog virus infection risk of the marked time period is re-evaluated according to the purification effect. If the frog virus infection risk of the marked time period is still higher than the frog virus infection risk control threshold, the time period still higher than the frog virus infection risk control threshold is marked as a time period to be optimized for the second time;

[0128] It should be noted that by simulating the dynamic adjustment plan for the aquaculture water environment and conducting a secondary assessment of the risk of frog virus infection in the marked time period, after simulating the implementation of the dynamic adjustment plan for the aquaculture water environment, if the risk of frog virus infection in the marked time period is still higher than the frog virus infection risk control threshold, it means that even if the inlet and outlet water volume is adjusted to maximum power in the target frog breeding pond, the risk of frog virus infection in the target frog breeding pond cannot be controlled within the control threshold. At this time, the time period that is still higher than the frog virus infection risk control threshold needs to be marked as the time period to be optimized twice, and secondary optimization is performed in this time period.

[0129] Determine the maximum water flow renewal amount of the target frog breeding pond according to the controllable range data of the water inflow and outflow of the target frog breeding pond;

[0130] The time advance of adjusting the inlet and outlet water volume of the target frog breeding pond is calculated according to the maximum water flow update amount and the predicted data of the frog virus content in the time period to be optimized for the second time, and the dynamic adjustment plan of the breeding water environment is optimized according to the time advance to obtain the breeding water environment adjustment plan of the target frog breeding pond.

[0131] It should be noted that the dynamic adjustment plan for the aquaculture water environment is to perform water treatment only when the risk of frog virus infection is higher than the risk control threshold of frog virus infection. When the concentration of frog virus is too high, water treatment is delayed and it takes time to improve water quality. Simply performing water treatment immediately after the risk is detected may not be able to significantly reduce the concentration of frog virus in a short period of time. Therefore, by adjusting the water quality in advance, it is ensured that the safe water quality standards are met before the peak of the infection risk, thereby effectively reducing the risk of frog virus infection. In the process of water quality treatment, the water inlet and outlet are reasonably adjusted, which not only reduces the cost of water quality treatment, but also improves the efficiency of water resource utilization and realizes the improvement of economic benefits.

[0132] Figure 4 A block diagram of a frog virus detection and evaluation system in aquaculture water based on tangential flow enrichment according to the present invention is shown.

[0133] The second aspect of the present invention also provides a frog virus detection and evaluation system 4 in aquaculture water based on tangential flow enrichment, the system comprising: a memory 41, a processor 42, the memory comprising a frog virus detection and evaluation method program in aquaculture water based on tangential flow enrichment, the frog virus detection and evaluation method program in aquaculture water based on tangential flow enrichment being executed by the processor to implement the following steps:

[0134] Divide the target frog breeding pond into N breeding water body sub-areas, obtain the fluid dynamics parameters of each sub-area, and determine the spatial distribution of water flow exchange efficiency of the target frog breeding pond according to the fluid dynamics parameters;

[0135] Analyzing the growth suitability of the frog virus in the target frog breeding pond according to the spatial distribution of the water exchange efficiency, and determining the detection position of the frog virus according to the growth suitability of the frog virus;

[0136] Based on the tangential flow enrichment technology, the frog virus at the detection position in the preset time period is detected, and the change of the frog virus content at the detection position in the preset time period is evaluated to obtain the frog virus content change data;

[0137] Predicting the spread trend of the frog virus in the target frog breeding pond according to the frog virus content change data to obtain a prediction result;

[0138] A plan for regulating the aquaculture water environment of the target frog breeding pond is determined based on the prediction results.

[0139] The present invention discloses a method and system for detecting and evaluating frog viruses in aquaculture water based on tangential flow enrichment, aiming to improve the accuracy and efficiency of virus monitoring in frog aquaculture water. The method includes: dividing the aquaculture pond into multiple sub-areas, obtaining the fluid dynamics parameters of each area, and determining the spatial distribution of water flow exchange efficiency; analyzing the growth suitability of frog viruses based on the distribution, and determining the detection position of the virus; using tangential flow enrichment technology to detect viruses within a preset time period and evaluate changes in virus content; predicting the virus diffusion trend based on the change data, and proposing corresponding water environment adjustment plans. This method can effectively improve the detection sensitivity and diffusion prediction accuracy of frog viruses.

[0140] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0141] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0142] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0143] Those skilled in the art can understand that: all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), disks or optical disks, and other media that can store program codes.

[0144] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0145] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for detecting and evaluating frog viruses in aquaculture water based on tangential flow enrichment, characterized in that: The following steps are involved: Divide the target frog breeding pond into N breeding water body sub-areas, obtain the fluid dynamics parameters of each sub-area, and determine the spatial distribution of water flow exchange efficiency of the target frog breeding pond according to the fluid dynamics parameters; Analyzing the growth suitability of the frog virus in the target frog breeding pond according to the spatial distribution of the water exchange efficiency, and determining the detection position of the frog virus according to the growth suitability of the frog virus; Based on the tangential flow enrichment technology, the frog virus at the detection position in the preset time period is detected, and the change of the frog virus content at the detection position in the preset time period is evaluated to obtain the frog virus content change data; Predicting the spread trend of the frog virus in the target frog breeding pond according to the frog virus content change data to obtain a prediction result; A plan for regulating the aquaculture water environment of the target frog breeding pond is determined based on the prediction results.

2. The method for detecting and evaluating frog viruses in aquaculture water based on tangential flow enrichment according to claim 1, characterized in that: The target frog breeding pond is divided into N breeding water body sub-areas, the fluid dynamics parameters of each sub-area are obtained, and the spatial distribution of the water flow exchange efficiency of the target frog breeding pond is determined according to the fluid dynamics parameters, specifically: Acquire geometric shape data of a target frog breeding pond, construct a three-dimensional model of the target frog breeding pond according to the geometric shape data, and divide the target frog breeding pond into N breeding water body sub-areas according to the three-dimensional model; Acquire fluid dynamics parameters and position coordinate information of each sub-area based on a flow velocity sensor, wherein the fluid dynamics parameters include water flow velocity and water flow direction of each sub-area; The fluid dynamics parameters are converted into numerical expressions, and the fluid dynamics parameters in the numerical expressions and the position coordinate information are normalized based on a Z-score normalization method to obtain normalized fluid dynamics parameters and position coordinate information; An OPTICS clustering algorithm is introduced, and a clustering operation is performed on the standardized fluid dynamics parameters and position coordinate information according to the OPTICS clustering algorithm to obtain a clustering result; Extracting the clusters output by the clustering result, obtaining the sub-regions contained in each cluster, dividing the target frog breeding pond into cluster regions according to the sub-regions contained in each cluster, and obtaining the cluster regions represented by each cluster; Calculate the average water flow velocity of each cluster area according to the water flow velocity of the sub-areas contained in each cluster; Determine the water flow exchange efficiency of each cluster area according to the average water flow velocity of each cluster area, map the water flow exchange efficiency of each cluster area into the three-dimensional model, and draw a spatial distribution map of the water flow exchange efficiency in the target frog breeding pond; The spatial distribution of water exchange efficiency in the target frog breeding pond is determined according to the water exchange efficiency spatial distribution map.

3. The method for detecting and evaluating frog viruses in aquaculture water based on tangential flow enrichment according to claim 2, characterized in that: The standardized fluid dynamics parameters and position coordinate information are clustered according to the OPTICS clustering algorithm to obtain a clustering result, which is specifically: Converting the standardized fluid dynamics parameters and position coordinate information into feature vectors to obtain a feature vector data set for each sub-region; Setting the basic parameters of the OPTICS clustering algorithm, wherein the basic parameters include the maximum distance threshold ε between two data points and the minimum number of data points MinPts in each cluster; Marking each data point in the feature vector data set as an unvisited state, visiting each data point in the feature vector data set in turn, and marking the data point that enters the visited state as an visited state data point; Obtain data points in the ε neighborhood of the access status data point. If the number of data points in the ε neighborhood is not less than MinPts, mark the access status data point as a core point. If the number of data points in the ε neighborhood is less than MinPts, mark the access status data point as a noise point. Calculate the Manhattan distance from the core point to the MinPts-th nearest point in the ε neighborhood to obtain the core distance of the core point. For each data point in the ε neighborhood of the accessed state data point, if the neighborhood data point has not been visited, the reachable distance between the neighborhood data point and the core point is calculated, and each unvisited neighborhood data point is inserted into the priority queue, ending the access state of the accessed state data point; Sequentially taking out the smallest reachable distance points from the priority queue as access status data points for access, and updating the priority queue until all data points in the priority queue are accessed, thereby obtaining a clustering sequence table; A reachable distance graph is generated according to the clustering sequence table, clusters of the standardized fluid dynamics parameters and position coordinate information are identified according to the reachable distance graph, and the clusters are output to obtain clustering results.

4. The method for detecting and evaluating frog viruses in aquaculture water based on tangential flow enrichment according to claim 1, characterized in that: The method of analyzing the growth suitability of the frog virus in the target frog breeding pond according to the spatial distribution of the water flow exchange efficiency and determining the detection position of the frog virus according to the growth suitability of the frog virus is specifically as follows: According to the spatial distribution of the water exchange efficiency, a high water exchange area, a low water exchange area, and a water flow stop area in the target frog breeding pond are identified to obtain water exchange partitions; Obtain water impurity content data of each sub-area in the target frog breeding pond and water purification capacity data of each water flow exchange partition, and analyze the accumulation of water impurities in each sub-area over a preset time length according to the water impurity content data and the water purification capacity data of each water flow exchange partition; Performing water quality assessment on each sub-area according to the accumulation of impurities in the water body to obtain a water quality assessment result; Acquire suitable water quality condition data for frog virus, determine the suitability of frog virus growth in each sub-area according to the suitable water quality condition data and the water quality assessment result, and determine the frog virus growth risk in each sub-area according to the frog virus growth suitability; The detection position of the frog virus is determined according to the frog virus growth risk.

5. The method for detecting and evaluating frog viruses in aquaculture water based on tangential flow enrichment according to claim 1, characterized in that: The tangential flow enrichment technology is used to detect the frog virus at the detection position in a preset time period, and the frog virus content change at the detection position in the preset time period is evaluated to obtain the frog virus content change data, specifically: Acquire water samples at the detection location in a preset time period according to a preset detection time period, analyze the water impurity content of the water samples, and if the water impurity content is greater than a preset content, perform an impurity filtering operation on the water samples; Acquire frog virus size data, determine the filter membrane pore size for tangential flow enrichment according to the frog virus size data, and perform frog virus enrichment operation on the water sample after impurity filtration operation based on the tangential flow enrichment technology according to the filter membrane pore size to obtain an enriched sample; Performing frog virus detection on the enriched sample to determine the frog virus content of the enriched sample to obtain a detection result; The detection results are sorted according to the time series to obtain the frog virus content change data of the detection position in the preset time period.

6. The method for detecting and evaluating frog viruses in aquaculture water based on tangential flow enrichment according to claim 1, characterized in that: The prediction result is obtained by predicting the spread trend of the frog virus in the target frog breeding pond according to the frog virus content change data, specifically: Performing a stability test on the frog virus content change data based on the ADF test, if the stability of the frog virus content change data is lower than a preset stability value, performing a differential operation on the frog virus content change data to obtain stable frog virus content change data; Constructing a frog virus content prediction model based on the ARIMA algorithm, constructing an autocorrelation function graph and a partial autocorrelation function graph based on the stable data of frog virus content changes, and determining the autoregressive order and moving average order of the frog virus content prediction model according to the autocorrelation function graph and the partial autocorrelation function graph; The parameters of the frog virus content prediction model are set according to the autoregressive order and the moving average order, the stable data of frog virus content change is imported into the frog virus content prediction model for training, and the model parameters are optimized based on the maximum likelihood estimation method; Based on the tangential flow enrichment technology, real-time data on the change in the amount of frog virus at each frog virus detection position in the current preset time period are obtained in real time, and the real-time data on the change in the amount of frog virus is imported into a frog virus content prediction model to predict the amount of frog virus at each frog virus detection position in the future preset time period, thereby obtaining frog virus content prediction data; The frog virus diffusion trend of the target frog breeding pond is predicted according to the frog virus content prediction data to obtain a prediction result, which includes the change in the number of frog viruses and the location and diffusion of the frog viruses.

7. The method for detecting and evaluating frog viruses in aquaculture water based on tangential flow enrichment according to claim 1, characterized in that: The aquaculture water environment adjustment scheme of the target frog breeding pond is determined according to the prediction results, specifically: According to the prediction results, the risk of frogs in the target frog breeding pond being infected with frog virus in a preset time period in the future is evaluated to obtain a frog virus infection risk evaluation result; Obtaining a frog virus infection risk control threshold in a target breeding pond, comparing the frog virus infection risk assessment result with the frog virus infection risk control threshold, marking a time period in a future preset time period when the frog virus infection risk in the target frog breeding pond is higher than the frog virus infection risk control threshold, and obtaining a marked time period; Acquire the controllable range data of the inflow and outflow of the target frog breeding pond, and determine the inflow and outflow control parameters of the target frog breeding pond in the marked time period according to the controllable range data of the inflow and outflow and the predicted data of the frog virus content in the marked time period; Constructing a dynamic regulation scheme for the aquaculture water environment of the target frog aquaculture pond according to the water inlet and outlet control parameters of the marked time period; Acquire the inlet and outlet position information of the target frog breeding pond, construct a water flow simulation model of the target frog breeding pond according to the inlet and outlet position information, perform inlet and outlet simulation operations on the breeding water environment dynamic adjustment scheme based on the water flow simulation model, and determine the water quality update status of the target frog breeding pond; The purification effect of the frog virus is evaluated according to the water quality update situation, and the frog virus infection risk of the marked time period is re-evaluated according to the purification effect. If the frog virus infection risk of the marked time period is still higher than the frog virus infection risk control threshold, the time period still higher than the frog virus infection risk control threshold is marked as a time period to be optimized for the second time; Determine the maximum water flow renewal amount of the target frog breeding pond according to the controllable range data of the water inflow and outflow of the target frog breeding pond; The time advance of adjusting the inlet and outlet water volume of the target frog breeding pond is calculated according to the maximum water flow update amount and the predicted data of the frog virus content in the time period to be optimized for the second time, and the dynamic adjustment plan of the breeding water environment is optimized according to the time advance to obtain the breeding water environment adjustment plan of the target frog breeding pond.

8. A frog virus detection and evaluation system in aquaculture water based on tangential flow enrichment, characterized in that: The system for detecting and evaluating frog viruses in aquaculture water based on tangential flow enrichment comprises a storage device and a processor, wherein the storage device comprises a method program for detecting and evaluating frog viruses in aquaculture water based on tangential flow enrichment, and when the method program for detecting and evaluating frog viruses in aquaculture water based on tangential flow enrichment is executed by the processor, the following steps are implemented: Divide the target frog breeding pond into N breeding water body sub-areas, obtain the fluid dynamics parameters of each sub-area, and determine the spatial distribution of water flow exchange efficiency of the target frog breeding pond according to the fluid dynamics parameters; Analyzing the growth suitability of the frog virus in the target frog breeding pond according to the spatial distribution of the water exchange efficiency, and determining the detection position of the frog virus according to the growth suitability of the frog virus; Based on the tangential flow enrichment technology, the frog virus at the detection position in the preset time period is detected, and the change of the frog virus content at the detection position in the preset time period is evaluated to obtain the frog virus content change data; Predicting the spread trend of the frog virus in the target frog breeding pond according to the frog virus content change data to obtain a prediction result; A plan for regulating the aquaculture water environment of the target frog breeding pond is determined based on the prediction results.

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