Breeding environment regulation method and system for penaeus vannamei based on reproductive quality evaluation

Abstract

The application discloses a kind of based on breeding quality evaluation's south American white prawn breeding environmental regulation method and system.The method collects the environmental parameters of breeding pool multi-node and the survival rate of larva hatching, larva metamorphosis synchronization rate, calculates the spatial distribution of reproductive quality;Using DBSCAN algorithm clustering analysis, construct water quality-reproductive force coupling distribution characteristics;According to the difference, the density of circulating water branch pipe and the inclination of microporous aeration device are laid out, and the partition control layout is formed.The cooperative change of dissolved oxygen pulse frequency and calcium ion fluctuation amplitude is monitored during operation, and the lag coefficient of reproductive quality improvement is calculated to quantify the control response.When the lag coefficient is over the threshold value, call LSTM model to predict future environmental parameters and output correction amount, generate adaptive instruction set.The application solves the problem of strong space uniformity and response lag in traditional control, significantly improves the survival rate of south American white prawn hatching and larva metamorphosis synchronization rate.

Description

Technical Field

[0001] This invention relates to the field of aquaculture technology, and in particular to a method and system for controlling the breeding environment of Litopenaeus vannamei based on reproductive quality assessment. Background Technology

[0002] Litopenaeus vannamei has become the dominant species in my country's marine aquaculture due to its rapid growth and strong disease resistance. As the starting point of the industry chain, the precision of environmental control in the breeding stage directly determines the survival rate of juvenile shrimp hatching and the synchronization rate of metamorphosis in offspring. Currently, traditional breeding pond environmental control mostly adopts a "global homogenization" model, that is, maintaining the stability of overall water quality indicators (such as dissolved oxygen and temperature) through evenly distributed aeration pipes and circulating water systems at the bottom of the pond. However, due to the existence of dead zones in the pond and uneven lighting, the physicochemical environment exhibits significant spatial heterogeneity, resulting in huge differences in reproductive quality in different areas.

[0003] Existing technologies suffer from the following drawbacks: First, they lack spatial resolution sensing capabilities, failing to identify the "high-fertility core zone" and "low-fertility edge zone" within the pond, leading to wasted regulatory resources. Second, regulatory methods are singular and passive, typically relying on threshold values ​​for a single parameter for feedback adjustment, neglecting the synergistic effects of key factors such as dissolved oxygen pulses and calcium ion fluctuations on shrimp molting and metamorphosis, resulting in significant response lag. Finally, existing methods lack a dynamic coupling model between water quality parameters and reproductive quality, making proactive intervention based on real-time reproductive status difficult. Therefore, there is an urgent need for a method capable of quantifying the spatial distribution of reproductive quality, analyzing the water quality-fertility coupling mechanism, and achieving zoned differentiated adaptive regulation to address the current problems of low breeding efficiency and poor larval synchronization. Summary of the Invention

[0004] To address at least one of the aforementioned technical problems, this invention proposes a method and system for controlling the breeding environment of Litopenaeus vannamei based on reproductive quality assessment.

[0005] The first aspect of this invention provides a method for controlling the breeding environment of Litopenaeus vannamei based on reproductive quality assessment, comprising: Multidimensional environmental parameters of multiple monitoring nodes in the breeding pond of Litopenaeus vannamei are obtained, along with data on the hatching survival rate of juvenile shrimp and the metamorphosis synchronization rate of larvae within a preset time period. Based on the hatching survival rate of juvenile shrimp and the metamorphosis synchronization rate of larvae, the reproductive quality of the corresponding area of ​​each monitoring node is calculated, and preliminary evaluation data of the spatial distribution of reproductive quality are obtained. The DBSCAN clustering algorithm was used to cluster the preliminary evaluation data of the spatial distribution of reproductive quality, identify the regional characteristics of reproductive quality in the breeding pond, and construct the water quality-reproductive capacity coupled distribution characteristics by combining multidimensional environmental parameters. Based on the water quality-reproductive capacity coupling distribution characteristics, the layout density of the circulating water branch pipes and the tilt angle of the microporous aeration device in the breeding pond of Litopenaeus vannamei are determined, and a layout scheme for the zoned differentiated environmental control unit is constructed. The environmental control unit operates according to the layout scheme, and monitors in real time the coordinated change data of dissolved oxygen pulse frequency and calcium ion fluctuation amplitude in the same reproductive quality characteristic area within a preset time period. Based on the coordinated change data, the reproductive quality improvement lag coefficient is calculated to obtain the environmental control response characteristics. The operating parameters of the differentiated environmental control unit are dynamically adjusted according to the environmental control response characteristics. When the lag coefficient for improving reproductive quality is greater than the preset threshold, the short-term environmental parameter prediction model based on the LSTM network outputs the environmental parameter correction amount for the preset adjustment period in the future, thus obtaining an adaptive control instruction set.

[0006] In this scheme, the acquisition of multidimensional environmental parameters from multiple monitoring nodes within the Litopenaeus vannamei breeding pond, along with data on juvenile shrimp hatching survival rates and metamorphosis synchronization rates over a preset time period, and the calculation of reproductive quality for the corresponding area of ​​each monitoring node based on the juvenile shrimp hatching survival data and metamorphosis synchronization rates, yields preliminary spatial distribution data for reproductive quality. Specifically: Based on multiple monitoring nodes deployed in the breeding pond, multidimensional environmental parameters such as water temperature, dissolved oxygen concentration, pH value, ammonia nitrogen content, nitrite content and calcium ion concentration are collected synchronously within the coverage area of ​​each node. The hatching survival rate of juvenile shrimp is obtained by calculating the ratio of the total number of juvenile shrimp that have completed hatching within a preset time period in the coverage area of ​​each monitoring node to the total number of initial eggs laid by Litopenaeus vannamei. The metamorphosis synchronization rate of juvenile shrimp is obtained by calculating the ratio of the number of individuals in the same batch of juvenile shrimp that have completed metamorphosis from zoea larvae to mysid larvae within a set interval to the total number of juvenile shrimp in the coverage area of ​​each monitoring node. The data on the survival rate of juvenile shrimp hatching and the synchronization rate of larval shrimp metamorphosis are weighted and fused. The weighted fusion result is used as the quantitative value of reproductive quality for the corresponding monitoring node coverage area. The quantitative values ​​of reproductive quality corresponding to all monitoring nodes are registered and mapped according to the spatial coordinates of each monitoring node in the breeding pond to construct the preliminary evaluation data of the spatial distribution of reproductive quality with spatial location identifier.

[0007] In this scheme, the initial evaluation data of the spatial distribution of reproductive quality is clustered using the DBSCAN clustering algorithm to identify the regional characteristics of reproductive quality within the breeding pond. This is combined with multidimensional environmental parameters to construct a water quality-reproductive capacity coupled distribution characteristic. Specifically: Extract the spatial coordinates and quantitative values ​​of reproductive quality corresponding to each monitoring node from the preliminary evaluation data of spatial distribution of reproductive quality. Construct a dataset to be clustered using the spatial coordinates as the location parameters of the sample points and the quantitative values ​​of reproductive quality as the attribute parameters of the sample points. Set the neighborhood radius and minimum neighborhood sample number for the DBSCAN clustering algorithm. Iterate through all sample points in the dataset to be clustered. Mark the sample points whose neighborhood contains a number of sample points not less than the minimum neighborhood sample number as core points. Mark the sample points located in the neighborhood of core points but not meeting the core point determination criteria as boundary points. Mark the sample points that do not belong to any core point neighborhood as noise points. Divide the interconnected core points and the boundary points belonging to their neighborhoods into the same cluster. Each cluster corresponds to a reproductive quality characteristic region in the breeding pool. The level of the corresponding reproductive quality feature region is determined based on the mean of the reproductive quality quantification values ​​of all sample points within each cluster. The area ratio of the corresponding reproductive quality feature region is calculated based on the spatial range covered by each cluster, resulting in reproductive quality region features that include spatial boundaries, quality level, and area ratio. The multidimensional environmental parameters of each monitoring node are correlated and matched with the reproductive quality characteristic area to which they belong according to spatial coordinates. The average values ​​of water temperature, dissolved oxygen concentration, pH value, ammonia nitrogen content, nitrite content and calcium ion concentration of all monitoring nodes in the same reproductive quality characteristic area are calculated to obtain the average water quality parameter set corresponding to each reproductive quality characteristic area. Based on the spatial boundary of the reproductive quality characteristic area, the average water quality parameter set is spatially superimposed and mapped with the grade and area ratio of the corresponding reproductive quality characteristic area to construct a water quality-reproductive capacity coupled distribution feature carrying the correspondence between water quality parameters and reproductive quality grade.

[0008] In this scheme, the layout scheme of the zoned differentiated environmental control unit is constructed by determining the layout density of the circulating water branch pipes and the tilt angle of the microporous aeration device in the breeding pond of Litopenaeus vannamei based on the water quality-reproductive capacity coupling distribution characteristics. Specifically: Based on the spatial boundaries, quality grades, area proportions, and average water quality parameter sets of each reproductive quality characteristic region in the water quality-reproductive capacity coupling distribution characteristics, the spatial gradients of dissolved oxygen concentration, calcium ion concentration, ammonia nitrogen content, and nitrite content between adjacent reproductive quality characteristic regions are calculated, and a water quality exchange demand matrix for each reproductive quality characteristic region is constructed. Calculate the water quality compensation direction and water exchange contribution value at the boundary of each reproductive quality characteristic area based on the water quality exchange demand matrix. Determine the unit area coverage requirement of the circulating water branch pipe in the corresponding area based on the area ratio, spatial boundary length and water exchange contribution value of each reproductive quality characteristic area. Map the unit area coverage requirement of each reproductive quality characteristic area to the spatial coordinates of the breeding pond to determine the layout density of the circulating water branch pipe corresponding to each reproductive quality characteristic area. Based on the average dissolved oxygen concentration, average calcium ion concentration, and corresponding circulating water branch pipe layout density of each reproductive quality characteristic area, the local water flow direction formed by the water outlet of each circulating water branch pipe is calculated. Combined with the water quality compensation direction between each reproductive quality characteristic area and adjacent reproductive quality characteristic areas, the target water flow synthesis direction of each area is determined. Based on the target water flow synthesis direction, the angle relationship between the rising trajectory of the bubbles released by the microporous aeration device and the target water flow synthesis direction is calculated, and the tilt angle of the microporous aeration device corresponding to each reproductive quality characteristic area is determined. The density of circulating water branch pipes and the tilt angle of microporous aeration devices corresponding to each reproductive quality characteristic area are matched according to the corresponding spatial boundaries to generate a layout scheme of zoned differentiated environmental control units that connect each reproductive quality characteristic area.

[0009] In this scheme, the environmental control unit operating according to the layout scheme monitors in real time the coordinated change data of dissolved oxygen pulse frequency and calcium ion fluctuation amplitude in the same reproductive quality characteristic area within a preset time period. Based on the coordinated change data, the reproductive quality improvement lag coefficient is calculated to obtain the environmental control response characteristics, specifically: According to the layout scheme, the density of circulating water branch pipes and the tilt angle of microporous aeration devices are determined for each reproductive quality characteristic area. The corresponding zone-specific environmental control unit is driven to operate, and all reproductive quality characteristic areas with the same quality level are screened in the breeding pond to form a set of characteristic areas. In each reproductive quality feature region within the same feature region set, time-series data of dissolved oxygen concentration and calcium ion concentration are obtained. The dissolved oxygen concentration time-series data is counted by a sliding window to obtain the dissolved oxygen pulse frequency per unit time. The calcium ion concentration time-series data is subjected to Hilbert transform to extract the instantaneous amplitude envelope. The variance of the instantaneous amplitude envelope is calculated and the square root is taken to obtain the calcium ion fluctuation amplitude. The dissolved oxygen pulse frequency and calcium ion fluctuation amplitude of all reproductive quality characteristic regions within the same characteristic region set are subjected to pairwise difference operations to construct cross-regional dissolved oxygen pulse frequency difference matrix and cross-regional calcium ion fluctuation amplitude difference matrix. The mean of the absolute values ​​of all elements in the cross-regional dissolved oxygen pulse frequency difference matrix is ​​calculated as the dissolved oxygen pulse dispersion, and the mean of the absolute values ​​of all elements in the cross-regional calcium ion fluctuation amplitude difference matrix is ​​calculated as the calcium ion fluctuation dispersion. For each reproductive quality feature region within the same feature region set, the quantitative value of reproductive quality of that region before environmental regulation is extracted as the initial reproductive quality benchmark value. After the environmental regulation operation reaches the preset time period, the quantitative value of reproductive quality of that region is recalculated as the reproductive quality value after regulation. The difference between the reproductive quality value after regulation and the initial reproductive quality benchmark value is calculated to obtain the reproductive quality improvement amount of a single region. The standard deviation of the improvement in reproductive quality of all single regions within the set of regions with the same characteristics is calculated as the dispersion of cross-regional reproductive quality improvement. The dispersion of dissolved oxygen pulses and the dispersion of calcium ion fluctuations are used to determine the deviation of the coordinated response. The ratio of the dispersion of cross-regional reproductive quality improvement to the deviation of the coordinated response is used as the lag coefficient of reproductive quality improvement corresponding to the set of regions with the same characteristics. This yields the environmental regulation response characteristics that characterize the inconsistency of regulation among regions with the same reproductive quality characteristics.

[0010] In this scheme, the operating parameters of the zoned differentiated environmental control unit are dynamically adjusted according to the environmental control response characteristics. When the lag coefficient for improving reproductive quality is greater than a preset threshold, the short-term environmental parameter prediction model based on the LSTM network outputs the environmental parameter correction amount for a future preset adjustment period, thus obtaining an adaptive control instruction set, specifically: Extract the lag coefficient for reproductive quality improvement corresponding to each set of regions with the same characteristics in the environmental regulation response features, screen the set of regions with the same characteristics to be optimized that are greater than the preset threshold, retrieve the average water quality parameter set, circulating water branch pipe layout density and microporous aeration device tilt angle of each reproductive quality feature region in the set, and simultaneously extract the time series data of dissolved oxygen concentration, calcium ion concentration, water temperature and the corresponding reproductive quality quantitative value sequence during the regulation operation period, and align and splice them according to the timestamp to construct a training sample set; Using environmental parameters from consecutive historical time steps as input and reproductive quality quantification values ​​lagged by one time step as supervision labels, the short-term environmental parameter prediction model of the LSTM network is trained until convergence. The current dissolved oxygen concentration time series data, calcium ion concentration time series data, and water temperature time series data of the same feature region to be optimized are input into the trained model, and the predicted values ​​of dissolved oxygen concentration, calcium ion concentration, and reproductive quality quantification values ​​are output for each time step within the preset adjustment period in the future. Calculate the cumulative increment of the predicted value of the quantitative value of reproductive quality within the preset adjustment period in the future, compare the cumulative increment with the preset target value of reproductive quality improvement, and when the cumulative increment is less than the preset target value of reproductive quality improvement, take the predicted value of the quantitative value of reproductive quality reaching the preset target value of reproductive quality improvement as the optimization target, determine the required amount of dissolved oxygen concentration correction and calcium ion concentration correction for each time step, and combine the water quality exchange demand matrix of the corresponding reproductive quality characteristic area to calculate the adjustment amount of the circulating water branch flow and the adjustment amount of the aeration intensity of the microporous aeration device. The dissolved oxygen concentration correction, calcium ion concentration correction, circulating water branch pipe flow adjustment, and microporous aeration intensity adjustment are mapped according to the spatial boundaries of the corresponding reproductive quality characteristic regions to generate an adaptive control instruction set carrying spatial coordinate identifiers. This sets drive the corresponding zone-specific environmental control units to adjust their operating parameters according to the instructions. At the same time, the predicted value of the quantitative reproductive quality is fed back to the LSTM network model to update the model parameters online to adapt to the dynamic changes in the breeding pond environment.

[0011] A second aspect of the present invention also provides a breeding environment control system for Litopenaeus vannamei based on reproductive quality assessment. The system includes a memory and a processor. The memory includes a program for a breeding environment control method for Litopenaeus vannamei based on reproductive quality assessment. When the processor executes the program for the breeding environment control method for Litopenaeus vannamei based on reproductive quality assessment, it implements the steps of the breeding environment control method for Litopenaeus vannamei based on reproductive quality assessment as described in any of the above claims.

[0012] This invention discloses a method and system for environmental regulation in Litopenaeus vannamei breeding based on reproductive quality assessment. The method collects environmental parameters from multiple nodes in the breeding pond, as well as the hatching survival rate of juvenile shrimp and the metamorphosis synchronization rate of offspring, to calculate the spatial distribution of reproductive quality. Using the DBSCAN algorithm for cluster analysis, it constructs the water quality-reproductive capacity coupled distribution characteristics. Based on this, it differentiates the density of circulating water branch pipes and the inclination angle of microporous aeration devices to form a zoned regulation layout. During operation, it monitors the coordinated changes in dissolved oxygen pulse frequency and calcium ion fluctuation amplitude, calculating the lag coefficient for improving reproductive quality to quantify the regulatory response. When the lag coefficient exceeds a threshold, it calls an LSTM model to predict future environmental parameters and outputs correction values, generating an adaptive instruction set. This invention solves the problems of strong spatial uniformity and lag in traditional regulation methods, significantly improving the hatching survival rate and metamorphosis synchronization rate of Litopenaeus vannamei. Attached Figure Description

[0013] Figure 1 The flowchart of a method for controlling the breeding environment of Litopenaeus vannamei based on reproductive quality assessment according to the present invention is shown; Figure 2 The flowchart illustrating the water quality-reproductive force coupled distribution characteristics constructed according to the present invention is shown. Figure 3 A flowchart illustrating the layout scheme of the partitioned differentiated environment control unit of the present invention is shown; Figure 4 A block diagram of a breeding environment control system for Litopenaeus vannamei based on reproductive quality assessment is shown. Detailed Implementation

[0014] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0015] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0016] Figure 1 The flowchart of a method for controlling the breeding environment of Litopenaeus vannamei based on reproductive quality assessment according to the present invention is shown.

[0017] like Figure 1 As shown, the first aspect of this invention provides a method for controlling the breeding environment of Litopenaeus vannamei based on reproductive quality assessment, comprising: Multidimensional environmental parameters of multiple monitoring nodes in the breeding pond of Litopenaeus vannamei are obtained, along with data on the hatching survival rate of juvenile shrimp and the metamorphosis synchronization rate of larvae within a preset time period. Based on the hatching survival rate of juvenile shrimp and the metamorphosis synchronization rate of larvae, the reproductive quality of the corresponding area of ​​each monitoring node is calculated, and preliminary evaluation data of the spatial distribution of reproductive quality are obtained. The DBSCAN clustering algorithm was used to cluster the preliminary evaluation data of the spatial distribution of reproductive quality, identify the regional characteristics of reproductive quality in the breeding pond, and construct the water quality-reproductive capacity coupled distribution characteristics by combining multidimensional environmental parameters. Based on the water quality-reproductive capacity coupling distribution characteristics, the layout density of the circulating water branch pipes and the tilt angle of the microporous aeration device in the breeding pond of Litopenaeus vannamei are determined, and a layout scheme for the zoned differentiated environmental control unit is constructed. The environmental control unit operates according to the layout scheme, and monitors in real time the coordinated change data of dissolved oxygen pulse frequency and calcium ion fluctuation amplitude in the same reproductive quality characteristic area within a preset time period. Based on the coordinated change data, the reproductive quality improvement lag coefficient is calculated to obtain the environmental control response characteristics. The operating parameters of the differentiated environmental control unit are dynamically adjusted according to the environmental control response characteristics. When the lag coefficient for improving reproductive quality is greater than the preset threshold, the short-term environmental parameter prediction model based on the LSTM network outputs the environmental parameter correction amount for the preset adjustment period in the future, thus obtaining an adaptive control instruction set.

[0018] It should be noted that by introducing juvenile shrimp hatching survival rate and postlarval metamorphosis synchronization rate as core evaluation dimensions, biological reproductive performance is transformed into quantifiable spatial distribution data. This breaks through the limitations of traditional water quality assessment based solely on physicochemical parameters, achieving a precise initial assessment of reproductive quality in the spatial dimension. The DBSCAN density clustering algorithm effectively eliminates abnormal noise points and automatically identifies continuous areas with similar reproductive characteristics within the pond, thus accurately delineating high, medium, and low reproductive capacity blocks and their boundaries. Based on this, the established water quality-reproductive capacity coupled distribution characteristics reveal the intrinsic mapping relationship between specific environmental factor combinations and reproductive performance, providing a data foundation for precise regulation. Differentiated configuration of circulating water branch pipe density and microporous aeration device tilt angle based on these coupling characteristics can specifically alter local flow patterns. By analyzing field structure and material transport pathways, a stable environment is maintained in high-fertility areas while enhancing hydraulic disturbance and water-air exchange in low-fertility areas, effectively eliminating water quality dead zones and promoting balanced ion diffusion. By monitoring the coordinated changes in dissolved oxygen pulse frequency and calcium ion fluctuation amplitude to calculate the lag coefficient for improving reproductive quality, the system can keenly capture the spatiotemporal delay effect and regional inconsistencies between environmental intervention and biological physiological responses, thereby quantifying the actual effectiveness of control measures. Finally, by combining the powerful time series prediction capabilities of LSTM networks, the system can predict environmental evolution trends in advance and output forward-looking parameter corrections when the lag coefficient exceeds the standard, realizing the transformation from passive feedback to active intervention, ensuring that the breeding environment is always in optimal dynamic equilibrium, and significantly improving the overall vitality and developmental synchronicity of juvenile shrimp.

[0019] According to an embodiment of the present invention, the acquisition of multidimensional environmental parameters of multiple monitoring nodes in the breeding pond of Litopenaeus vannamei and the hatching survival rate data of juvenile shrimp and the metamorphosis synchronization rate of larvae within a preset time period, and the calculation of the reproductive quality of the corresponding area of ​​each monitoring node based on the hatching survival rate data of juvenile shrimp and the metamorphosis synchronization rate of larvae to obtain preliminary evaluation data of the spatial distribution of reproductive quality, specifically includes: Based on multiple monitoring nodes deployed in the breeding pond, multidimensional environmental parameters such as water temperature, dissolved oxygen concentration, pH value, ammonia nitrogen content, nitrite content and calcium ion concentration are collected synchronously within the coverage area of ​​each node. The hatching survival rate of juvenile shrimp is obtained by calculating the ratio of the total number of juvenile shrimp that have completed hatching within a preset time period in the coverage area of ​​each monitoring node to the total number of initial eggs laid by Litopenaeus vannamei. The metamorphosis synchronization rate of juvenile shrimp is obtained by calculating the ratio of the number of individuals in the same batch of juvenile shrimp that have completed metamorphosis from zoea larvae to mysid larvae within a set interval to the total number of juvenile shrimp in the coverage area of ​​each monitoring node. The data on the survival rate of juvenile shrimp hatching and the synchronization rate of larval shrimp metamorphosis are weighted and fused. The weighted fusion result is used as the quantitative value of reproductive quality for the corresponding monitoring node coverage area. The quantitative values ​​of reproductive quality corresponding to all monitoring nodes are registered and mapped according to the spatial coordinates of each monitoring node in the breeding pond to construct the preliminary evaluation data of the spatial distribution of reproductive quality with spatial location identifier.

[0020] It should be noted that due to factors such as the location of inlet and outlet, light obstruction, differences in bottom sediment, and equipment disturbance within the breeding ponds of Litopenaeus vannamei, key environmental factors such as water temperature, dissolved oxygen, and calcium ions exhibit significant non-uniform distribution. This leads to substantial differences in spawning rates, larval hatching survival rates, and metamorphosis rates among broodstock in different physical locations. Traditional breeding management often overlooks this spatial heterogeneity, employing a uniform control strategy across the entire pond. This not only excessively disturbs the high-fertility environment in high-fertility areas but also prevents targeted improvement of limiting factors in low-fertility areas, resulting in overall low reproductive efficiency and inconsistent larval size. Therefore, by simultaneously collecting multi-dimensional environmental parameters across multiple coverage areas and weighting and fusing the two core biological indicators—larval hatching survival rate and larval metamorphosis synchronization rate—we can construct preliminary assessment data on the spatial distribution of reproductive quality with precise spatial location identifiers. This allows for accurate insight into the true pattern of reproductive potential within the pond, identifying micro-environmental shortcomings that constrain production, and providing indispensable spatial decision-making basis for subsequent differentiated regional control.

[0021] Figure 2 The flowchart illustrating the water quality-reproductive capacity coupled distribution characteristics constructed according to the present invention is shown.

[0022] According to an embodiment of the present invention, the initial assessment data of the spatial distribution of reproductive quality is clustered using the DBSCAN clustering algorithm to identify the regional characteristics of reproductive quality within the breeding pond, and water quality-reproductive capacity coupled distribution characteristics are constructed by combining multidimensional environmental parameters, specifically as follows: Extract the spatial coordinates and quantitative values ​​of reproductive quality corresponding to each monitoring node from the preliminary evaluation data of spatial distribution of reproductive quality. Construct a dataset to be clustered using the spatial coordinates as the location parameters of the sample points and the quantitative values ​​of reproductive quality as the attribute parameters of the sample points. Set the neighborhood radius and minimum neighborhood sample number for the DBSCAN clustering algorithm. Iterate through all sample points in the dataset to be clustered. Mark the sample points whose neighborhood contains a number of sample points not less than the minimum neighborhood sample number as core points. Mark the sample points located in the neighborhood of core points but not meeting the core point determination criteria as boundary points. Mark the sample points that do not belong to any core point neighborhood as noise points. Divide the interconnected core points and the boundary points belonging to their neighborhoods into the same cluster. Each cluster corresponds to a reproductive quality characteristic region in the breeding pool. The level of the corresponding reproductive quality feature region is determined based on the mean of the reproductive quality quantification values ​​of all sample points within each cluster. The area ratio of the corresponding reproductive quality feature region is calculated based on the spatial range covered by each cluster, resulting in reproductive quality region features that include spatial boundaries, quality level, and area ratio. The multidimensional environmental parameters of each monitoring node are correlated and matched with the reproductive quality characteristic area to which they belong according to spatial coordinates. The average values ​​of water temperature, dissolved oxygen concentration, pH value, ammonia nitrogen content, nitrite content and calcium ion concentration of all monitoring nodes in the same reproductive quality characteristic area are calculated to obtain the average water quality parameter set corresponding to each reproductive quality characteristic area. Based on the spatial boundary of the reproductive quality characteristic area, the average water quality parameter set is spatially superimposed and mapped with the grade and area ratio of the corresponding reproductive quality characteristic area to construct a water quality-reproductive capacity coupled distribution feature carrying the correspondence between water quality parameters and reproductive quality grade.

[0023] It should be noted that the DBSCAN density clustering algorithm effectively overcomes the shortcomings of sparse and uneven data from monitoring nodes in the breeding pond, which are susceptible to interference from transient outliers. By constructing the dataset to be clustered based on dual parameters of spatial coordinates and quantitative reproductive quality values, the algorithm can automatically identify and filter out noise points caused by sensor drift or local biological aggregation, retaining only statistically significant core data. This accurately delineates the true physical boundaries of high, medium, and low reproductive capacity regions within the breeding pond, avoiding the boundary rigidity problem caused by artificial grid division. By grouping connected core points and boundary points into the same cluster, it not only clarifies the regions with different reproductive quality characteristics, but also... The spatial outline and area proportion were analyzed, and an objective quality level was established based on the mean of data within the cluster, revealing the macroscopic reproductive pattern hidden behind discrete data points. Furthermore, the mean of multidimensional environmental parameters within the same cluster was fused to construct a water quality-reproductive capacity coupled distribution feature, successfully establishing a strong correlation mapping between specific combinations of water quality parameters and specific reproductive quality levels. This revealed the specific contribution of high dissolved oxygen pulse frequency combined with appropriate calcium ion fluctuation amplitude to improving reproductive quality. This in-depth mining from spatial clustering to water quality attribution provides high-confidence data support for analyzing the cumulative effect of environmental factors on the reproductive physiology of Litopenaeus vannamei.

[0024] Figure 3 A flowchart illustrating the layout scheme of the partitioned differentiated environment control unit of the present invention is shown.

[0025] According to an embodiment of the present invention, the step of determining the layout density of the circulating water branch pipes and the tilt angle of the microporous aeration device in the breeding pond of Litopenaeus vannamei based on the water quality-reproductive capacity coupling distribution characteristics, and constructing a layout scheme for the zoned differentiated environmental control unit, specifically includes: Based on the spatial boundaries, quality grades, area proportions, and average water quality parameter sets of each reproductive quality characteristic region in the water quality-reproductive capacity coupling distribution characteristics, the spatial gradients of dissolved oxygen concentration, calcium ion concentration, ammonia nitrogen content, and nitrite content between adjacent reproductive quality characteristic regions are calculated, and a water quality exchange demand matrix for each reproductive quality characteristic region is constructed. Calculate the water quality compensation direction and water exchange contribution value at the boundary of each reproductive quality characteristic area based on the water quality exchange demand matrix. Determine the unit area coverage requirement of the circulating water branch pipe in the corresponding area based on the area ratio, spatial boundary length and water exchange contribution value of each reproductive quality characteristic area. Map the unit area coverage requirement of each reproductive quality characteristic area to the spatial coordinates of the breeding pond to determine the layout density of the circulating water branch pipe corresponding to each reproductive quality characteristic area. Based on the average dissolved oxygen concentration, average calcium ion concentration, and corresponding circulating water branch pipe layout density of each reproductive quality characteristic area, the local water flow direction formed by the water outlet of each circulating water branch pipe is calculated. Combined with the water quality compensation direction between each reproductive quality characteristic area and adjacent reproductive quality characteristic areas, the target water flow synthesis direction of each area is determined. Based on the target water flow synthesis direction, the angle relationship between the rising trajectory of the bubbles released by the microporous aeration device and the target water flow synthesis direction is calculated, and the tilt angle of the microporous aeration device corresponding to each reproductive quality characteristic area is determined. The density of circulating water branch pipes and the tilt angle of microporous aeration devices corresponding to each reproductive quality characteristic area are matched according to the corresponding spatial boundaries to generate a layout scheme of zoned differentiated environmental control units that connect each reproductive quality characteristic area.

[0026] It should be noted that, based on the coupled distribution characteristics of water quality and reproductive capacity, the spatial gradient is quantified by calculating the ratio of the concentration difference of key water quality indicators between adjacent reproductive quality characteristic areas to the distance of the regional boundary. Specifically, the direction pointing from high reproductive capacity areas to low reproductive capacity areas is defined as the positive vector of water quality compensation, and its magnitude is jointly determined by the degree of deficit of dissolved oxygen and calcium ions and the surplus of ammonia nitrogen and nitrite. This constructs a water quality exchange demand matrix that covers the direction and urgency of compensation, which directly reflects the physical driving force of water exchange between different areas. Subsequently, the water quality compensation direction at the boundary of each area is analyzed based on this matrix, and the water exchange contribution value is calculated by combining the area ratio of the area and the boundary length. This is then used to inversely deduce the unit area coverage density of circulating water branch pipes required to meet the compensation demand, realizing the spatial difference in deployment density. The system first calculates the radial water flow vector formed by the water outlet of each branch pipe based on the determined layout density when determining the tilt angle of the microporous aeration device. Then, it superimposes this vector with the aforementioned water quality compensation direction vector to obtain the target water flow synthesis direction, which aims to promote the directional transport of beneficial ions and inhibit the accumulation of harmful metabolites. Since the bubbles generated by microporous aeration will be dragged by the horizontal water flow during their ascent and change their trajectory, the optimal tilt angle required by the microporous aeration device is derived by calculating the angle between the rising trajectory of the bubbles and the target water flow synthesis direction. This allows the rising power of the bubbles to be converted into the kinetic energy that propels the water to flow along the target direction to the greatest extent. Finally, the density parameters and angle parameters are registered according to the spatial boundary to form a physically executable and hydraulically highly coordinated zoned differentiated environmental control unit layout scheme.

[0027] According to an embodiment of the present invention, the environmental control unit operating according to the layout scheme monitors in real time the coordinated change data of dissolved oxygen pulse frequency and calcium ion fluctuation amplitude in the same reproductive quality characteristic area within a preset time period, calculates the reproductive quality improvement lag coefficient based on the coordinated change data, and obtains the environmental control response characteristics, specifically as follows: According to the layout scheme, the density of circulating water branch pipes and the tilt angle of microporous aeration devices are determined for each reproductive quality characteristic area. The corresponding zone-specific environmental control unit is driven to operate, and all reproductive quality characteristic areas with the same quality level are screened in the breeding pond to form a set of characteristic areas. In each reproductive quality feature region within the same feature region set, time-series data of dissolved oxygen concentration and calcium ion concentration are obtained. The dissolved oxygen concentration time-series data is counted by a sliding window to obtain the dissolved oxygen pulse frequency per unit time. The calcium ion concentration time-series data is subjected to Hilbert transform to extract the instantaneous amplitude envelope. The variance of the instantaneous amplitude envelope is calculated and the square root is taken to obtain the calcium ion fluctuation amplitude. The dissolved oxygen pulse frequency and calcium ion fluctuation amplitude of all reproductive quality characteristic regions within the same characteristic region set are subjected to pairwise difference operations to construct cross-regional dissolved oxygen pulse frequency difference matrix and cross-regional calcium ion fluctuation amplitude difference matrix. The mean of the absolute values ​​of all elements in the cross-regional dissolved oxygen pulse frequency difference matrix is ​​calculated as the dissolved oxygen pulse dispersion, and the mean of the absolute values ​​of all elements in the cross-regional calcium ion fluctuation amplitude difference matrix is ​​calculated as the calcium ion fluctuation dispersion. For each reproductive quality feature region within the same feature region set, the quantitative value of reproductive quality of that region before environmental regulation is extracted as the initial reproductive quality benchmark value. After the environmental regulation operation reaches the preset time period, the quantitative value of reproductive quality of that region is recalculated as the reproductive quality value after regulation. The difference between the reproductive quality value after regulation and the initial reproductive quality benchmark value is calculated to obtain the reproductive quality improvement amount of a single region. The standard deviation of the improvement in reproductive quality of all single regions within the set of regions with the same characteristics is calculated as the dispersion of cross-regional reproductive quality improvement. The dispersion of dissolved oxygen pulses and the dispersion of calcium ion fluctuations are used to determine the deviation of the coordinated response. The ratio of the dispersion of cross-regional reproductive quality improvement to the deviation of the coordinated response is used as the lag coefficient of reproductive quality improvement corresponding to the set of regions with the same characteristics. This yields the environmental regulation response characteristics that characterize the inconsistency of regulation among regions with the same reproductive quality characteristics.

[0028] It should be noted that even when breeding ponds are divided into zones with the same reproductive quality characteristics, uneven hydraulic retention times can occur due to bottom micro-topography, local shading differences, or the accumulation of residual bioflocs. This leads to variations in the sensitivity of different locations to dissolved oxygen pulses and calcium ion fluctuations under uniform zonal control, resulting in asynchronous improvement in reproductive quality in originally homogeneous areas after the same control duration, thus masking the actual effectiveness of the control measures. Therefore, by introducing Hilbert transform to accurately extract the instantaneous amplitude envelope of calcium ion fluctuations to quantify the amplitude, and combining it with sliding window peak counting to capture the dissolved oxygen pulse frequency, the interference of environmental noise on biological physiological rhythm signals is effectively eliminated. Then, by constructing a cross-regional difference matrix to calculate pulse dispersion and fluctuation dispersion, the degree of coordinated deviation of environmental disturbances within the same characteristic area is accurately quantified. At the same time, the standard deviation of cross-regional reproductive quality improvement is used as a discrete characterization of biological response. Finally, the reproductive quality improvement lag coefficient, defined by the ratio of the two, can keenly identify control blind spots caused by water flow short-circuiting or diffusion obstruction, revealing the nonlinear lag relationship between environmental physical disturbances and biological reproductive response.

[0029] According to an embodiment of the present invention, the step of dynamically adjusting the operating parameters of the zone-differentiated environmental control unit based on the environmental control response characteristics, when the lag coefficient for improving reproductive quality is greater than a preset threshold, outputs the environmental parameter correction amount for a future preset adjustment time period based on the short-term environmental parameter prediction model of the LSTM network, to obtain an adaptive control instruction set, specifically as follows: Extract the lag coefficient for reproductive quality improvement corresponding to each set of regions with the same characteristics in the environmental regulation response features, screen the set of regions with the same characteristics to be optimized that are greater than the preset threshold, retrieve the average water quality parameter set, circulating water branch pipe layout density and microporous aeration device tilt angle of each reproductive quality feature region in the set, and simultaneously extract the time series data of dissolved oxygen concentration, calcium ion concentration, water temperature and the corresponding reproductive quality quantitative value sequence during the regulation operation period, and align and splice them according to the timestamp to construct a training sample set; Using environmental parameters from consecutive historical time steps as input and reproductive quality quantification values ​​lagged by one time step as supervision labels, the short-term environmental parameter prediction model of the LSTM network is trained until convergence. The current dissolved oxygen concentration time series data, calcium ion concentration time series data, and water temperature time series data of the same feature region to be optimized are input into the trained model, and the predicted values ​​of dissolved oxygen concentration, calcium ion concentration, and reproductive quality quantification values ​​are output for each time step within the preset adjustment period in the future. Calculate the cumulative increment of the predicted value of the quantitative value of reproductive quality within the preset adjustment period in the future, compare the cumulative increment with the preset target value of reproductive quality improvement, and when the cumulative increment is less than the preset target value of reproductive quality improvement, take the predicted value of the quantitative value of reproductive quality reaching the preset target value of reproductive quality improvement as the optimization target, determine the required amount of dissolved oxygen concentration correction and calcium ion concentration correction for each time step, and combine the water quality exchange demand matrix of the corresponding reproductive quality characteristic area to calculate the adjustment amount of the circulating water branch flow and the adjustment amount of the aeration intensity of the microporous aeration device. The dissolved oxygen concentration correction, calcium ion concentration correction, circulating water branch pipe flow adjustment, and microporous aeration intensity adjustment are mapped according to the spatial boundaries of the corresponding reproductive quality characteristic regions to generate an adaptive control instruction set carrying spatial coordinate identifiers. This sets drive the corresponding zone-specific environmental control units to adjust their operating parameters according to the instructions. At the same time, the predicted value of the quantitative reproductive quality is fed back to the LSTM network model to update the model parameters online to adapt to the dynamic changes in the breeding pond environment.

[0030] This approach requires constructing a multi-dimensional training sample set aligned to timestamps and utilizing an LSTM network to uncover the deep temporal dependencies between environmental parameters such as dissolved oxygen, calcium ions, and water temperature and the quantitative values ​​of reproductive quality. This effectively overcomes the overshoot or under-adjustment problems caused by traditional control methods neglecting the lag in biological growth, enabling the model to accurately predict environmental evolution trends and reproductive quality response trajectories in the short term. By dynamically comparing the predicted cumulative increase in reproductive quality with the target value and using the goal of bridging the gap between the predicted and target values ​​as the reverse optimization objective, a shift from simple parameter feedback control to closed-loop optimal control based on biological growth targets is achieved, ensuring the foresight and purposefulness of the control commands. Simultaneously, By coupling environmental parameter corrections with the water quality exchange demand matrix, the system converts them into specific adjustments to the flow rate of circulating water branches and the intensity of micropore aeration. This ensures the physical feasibility of the control actions at the hydraulic and dynamic level. The generated adaptive instruction set, carrying spatial coordinate identifiers, can precisely drive the hardware to perform differentiated fine-tuning, avoiding global disturbances. Furthermore, by continuously feeding the latest quantitative prediction results of reproductive quality back to the model for online updates, the system possesses a self-learning ability that evolves with the progress of the breeding cycle. It can adapt to the dynamic changes in the ecological structure within the pond, thereby minimizing the time lag for improving reproductive quality while reducing energy consumption and equipment wear, and significantly improving the stability and production efficiency of Litopenaeus vannamei breeding.

[0031] Figure 4 A block diagram of a breeding environment control system for Litopenaeus vannamei based on reproductive quality assessment is shown.

[0032] A second aspect of the present invention also provides a breeding environment control system for Litopenaeus vannamei based on reproductive quality assessment. The system includes: a memory 401, a processor 402, and a communication interface 403. The memory includes a program for a breeding environment control method for Litopenaeus vannamei based on reproductive quality assessment. The communication interface is used for data connection and communication between the memory and the processor. When the program for a breeding environment control method for Litopenaeus vannamei based on reproductive quality assessment is executed by the processor, the steps of the breeding environment control method for Litopenaeus vannamei based on reproductive quality assessment as described in any of the above claims are implemented.

[0033] This invention discloses a method and system for environmental regulation in Litopenaeus vannamei breeding based on reproductive quality assessment. The method collects environmental parameters from multiple nodes in the breeding pond, as well as the hatching survival rate of juvenile shrimp and the metamorphosis synchronization rate of offspring, to calculate the spatial distribution of reproductive quality. Using the DBSCAN algorithm for cluster analysis, it constructs the water quality-reproductive capacity coupled distribution characteristics. Based on this, it differentiates the density of circulating water branch pipes and the inclination angle of microporous aeration devices to form a zoned regulation layout. During operation, it monitors the coordinated changes in dissolved oxygen pulse frequency and calcium ion fluctuation amplitude, calculating the lag coefficient for improving reproductive quality to quantify the regulatory response. When the lag coefficient exceeds a threshold, it calls an LSTM model to predict future environmental parameters and outputs correction values, generating an adaptive instruction set. This invention solves the problems of strong spatial uniformity and lag in traditional regulation methods, significantly improving the hatching survival rate and metamorphosis synchronization rate of Litopenaeus vannamei.

[0034] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0035] Alternatively, if the integrated units of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0036] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for environmental control in Litopenaeus vannamei breeding based on reproductive quality assessment, characterized in that, Includes the following steps: Multidimensional environmental parameters of multiple monitoring nodes in the breeding pond of Litopenaeus vannamei are obtained, along with data on the hatching survival rate of juvenile shrimp and the metamorphosis synchronization rate of larvae within a preset time period. Based on the hatching survival rate of juvenile shrimp and the metamorphosis synchronization rate of larvae, the reproductive quality of the corresponding area of ​​each monitoring node is calculated, and preliminary evaluation data of the spatial distribution of reproductive quality are obtained. The DBSCAN clustering algorithm was used to cluster the preliminary evaluation data of the spatial distribution of reproductive quality, identify the regional characteristics of reproductive quality in the breeding pond, and construct the water quality-reproductive capacity coupled distribution characteristics by combining multidimensional environmental parameters. Based on the water quality-reproductive capacity coupling distribution characteristics, the layout density of the circulating water branch pipes and the tilt angle of the microporous aeration device in the breeding pond of Litopenaeus vannamei are determined, and a layout scheme for the zoned differentiated environmental control unit is constructed. The environmental control unit operates according to the layout scheme, and monitors in real time the coordinated change data of dissolved oxygen pulse frequency and calcium ion fluctuation amplitude in the same reproductive quality characteristic area within a preset time period. Based on the coordinated change data, the reproductive quality improvement lag coefficient is calculated to obtain the environmental control response characteristics. The operating parameters of the differentiated environmental control unit are dynamically adjusted according to the environmental control response characteristics. When the lag coefficient for improving reproductive quality is greater than the preset threshold, the short-term environmental parameter prediction model based on the LSTM network outputs the environmental parameter correction amount for the preset adjustment period in the future, thus obtaining an adaptive control instruction set.

2. The method for environmental control in Litopenaeus vannamei breeding based on reproductive quality assessment according to claim 1, characterized in that, The process involves acquiring multidimensional environmental parameters from multiple monitoring nodes within the Litopenaeus vannamei breeding pond, along with juvenile shrimp hatching survival rate data and postlarval metamorphosis synchronization rate data within a preset time period. Based on these data, the reproductive quality of the corresponding area for each monitoring node is calculated, yielding preliminary spatial distribution data for reproductive quality. Specifically: Based on multiple monitoring nodes deployed in the breeding pond, multidimensional environmental parameters such as water temperature, dissolved oxygen concentration, pH value, ammonia nitrogen content, nitrite content and calcium ion concentration are collected synchronously within the coverage area of ​​each node. The hatching survival rate of juvenile shrimp is obtained by calculating the ratio of the total number of juvenile shrimp that have completed hatching within a preset time period in the coverage area of ​​each monitoring node to the total number of initial eggs laid by Litopenaeus vannamei. The metamorphosis synchronization rate of juvenile shrimp is obtained by calculating the ratio of the number of individuals in the same batch of juvenile shrimp that have completed metamorphosis from zoea larvae to mysid larvae within a set interval to the total number of juvenile shrimp in the coverage area of ​​each monitoring node. The data on the survival rate of juvenile shrimp hatching and the synchronization rate of larval shrimp metamorphosis are weighted and fused. The weighted fusion result is used as the quantitative value of reproductive quality for the corresponding monitoring node coverage area. The quantitative values ​​of reproductive quality corresponding to all monitoring nodes are registered and mapped according to the spatial coordinates of each monitoring node in the breeding pond to construct the preliminary evaluation data of the spatial distribution of reproductive quality with spatial location identifier.

3. The method for environmental control in Litopenaeus vannamei breeding based on reproductive quality assessment according to claim 1, characterized in that, The DBSCAN clustering algorithm is used to cluster the initial spatial distribution assessment data of reproductive quality to identify the regional characteristics of reproductive quality within the breeding pond. This is combined with multidimensional environmental parameters to construct a water quality-reproductive capacity coupled distribution characteristic. Specifically: Extract the spatial coordinates and quantitative values ​​of reproductive quality corresponding to each monitoring node from the preliminary evaluation data of spatial distribution of reproductive quality. Construct a dataset to be clustered using the spatial coordinates as the location parameters of the sample points and the quantitative values ​​of reproductive quality as the attribute parameters of the sample points. Set the neighborhood radius and minimum neighborhood sample number for the DBSCAN clustering algorithm. Iterate through all sample points in the dataset to be clustered. Mark the sample points whose neighborhood contains a number of sample points not less than the minimum neighborhood sample number as core points. Mark the sample points located in the neighborhood of core points but not meeting the core point determination criteria as boundary points. Mark the sample points that do not belong to any core point neighborhood as noise points. Divide the interconnected core points and the boundary points belonging to their neighborhoods into the same cluster. Each cluster corresponds to a reproductive quality characteristic region in the breeding pool. The level of the corresponding reproductive quality feature region is determined based on the mean of the reproductive quality quantification values ​​of all sample points within each cluster. The area ratio of the corresponding reproductive quality feature region is calculated based on the spatial range covered by each cluster, resulting in reproductive quality region features that include spatial boundaries, quality level, and area ratio. The multidimensional environmental parameters of each monitoring node are correlated and matched with the reproductive quality characteristic area to which they belong according to spatial coordinates. The average values ​​of water temperature, dissolved oxygen concentration, pH value, ammonia nitrogen content, nitrite content and calcium ion concentration of all monitoring nodes in the same reproductive quality characteristic area are calculated to obtain the average water quality parameter set corresponding to each reproductive quality characteristic area. Based on the spatial boundary of the reproductive quality characteristic area, the average water quality parameter set is spatially superimposed and mapped with the grade and area ratio of the corresponding reproductive quality characteristic area to construct a water quality-reproductive capacity coupled distribution feature carrying the correspondence between water quality parameters and reproductive quality grade.

4. The method for environmental control in Litopenaeus vannamei breeding based on reproductive quality assessment according to claim 1, characterized in that, The layout scheme of the zoned differentiated environmental control unit is constructed by determining the layout density of the circulating water branch pipes and the tilt angle of the microporous aeration device in the breeding pond of Litopenaeus vannamei based on the water quality-reproductive capacity coupling distribution characteristics. Specifically: Based on the spatial boundaries, quality grades, area proportions, and average water quality parameter sets of each reproductive quality characteristic region in the water quality-reproductive capacity coupling distribution characteristics, the spatial gradients of dissolved oxygen concentration, calcium ion concentration, ammonia nitrogen content, and nitrite content between adjacent reproductive quality characteristic regions are calculated, and a water quality exchange demand matrix for each reproductive quality characteristic region is constructed. Calculate the water quality compensation direction and water exchange contribution value at the boundary of each reproductive quality characteristic area based on the water quality exchange demand matrix. Determine the unit area coverage requirement of the circulating water branch pipe in the corresponding area based on the area ratio, spatial boundary length and water exchange contribution value of each reproductive quality characteristic area. Map the unit area coverage requirement of each reproductive quality characteristic area to the spatial coordinates of the breeding pond to determine the layout density of the circulating water branch pipe corresponding to each reproductive quality characteristic area. Based on the average dissolved oxygen concentration, average calcium ion concentration, and corresponding circulating water branch pipe layout density of each reproductive quality characteristic area, the local water flow direction formed by the water outlet of each circulating water branch pipe is calculated. Combined with the water quality compensation direction between each reproductive quality characteristic area and adjacent reproductive quality characteristic areas, the target water flow synthesis direction of each area is determined. Based on the target water flow synthesis direction, the angle relationship between the rising trajectory of the bubbles released by the microporous aeration device and the target water flow synthesis direction is calculated, and the tilt angle of the microporous aeration device corresponding to each reproductive quality characteristic area is determined. The density of circulating water branch pipes and the tilt angle of microporous aeration devices corresponding to each reproductive quality characteristic area are matched according to the corresponding spatial boundaries to generate a layout scheme of zoned differentiated environmental control units that connect each reproductive quality characteristic area.

5. The method for environmental control in Litopenaeus vannamei breeding based on reproductive quality assessment according to claim 1, characterized in that, The environmental control unit operating according to the layout scheme monitors in real time the coordinated changes in dissolved oxygen pulse frequency and calcium ion fluctuation amplitude in regions with the same reproductive quality characteristics within a preset time period. Based on the coordinated change data, it calculates the reproductive quality improvement lag coefficient to obtain the environmental control response characteristics, specifically: According to the layout scheme, the density of circulating water branch pipes and the tilt angle of microporous aeration devices are determined for each reproductive quality characteristic area. The corresponding zone-specific environmental control unit is driven to operate, and all reproductive quality characteristic areas with the same quality level are screened in the breeding pond to form a set of characteristic areas. In each reproductive quality feature region within the same feature region set, time-series data of dissolved oxygen concentration and calcium ion concentration are obtained. The dissolved oxygen concentration time-series data is counted by a sliding window to obtain the dissolved oxygen pulse frequency per unit time. The calcium ion concentration time-series data is subjected to Hilbert transform to extract the instantaneous amplitude envelope. The variance of the instantaneous amplitude envelope is calculated and the square root is taken to obtain the calcium ion fluctuation amplitude. The dissolved oxygen pulse frequency and calcium ion fluctuation amplitude of all reproductive quality characteristic regions within the same characteristic region set are subjected to pairwise difference operations to construct cross-regional dissolved oxygen pulse frequency difference matrix and cross-regional calcium ion fluctuation amplitude difference matrix. The mean of the absolute values ​​of all elements in the cross-regional dissolved oxygen pulse frequency difference matrix is ​​calculated as the dissolved oxygen pulse dispersion, and the mean of the absolute values ​​of all elements in the cross-regional calcium ion fluctuation amplitude difference matrix is ​​calculated as the calcium ion fluctuation dispersion. For each reproductive quality feature region within the same feature region set, the quantitative value of reproductive quality of that region before environmental regulation is extracted as the initial reproductive quality benchmark value. After the environmental regulation operation reaches the preset time period, the quantitative value of reproductive quality of that region is recalculated as the reproductive quality value after regulation. The difference between the reproductive quality value after regulation and the initial reproductive quality benchmark value is calculated to obtain the reproductive quality improvement amount of a single region. The standard deviation of the improvement in reproductive quality of all single regions within the set of regions with the same characteristics is calculated as the dispersion of cross-regional reproductive quality improvement. The dispersion of dissolved oxygen pulses and the dispersion of calcium ion fluctuations are used to determine the deviation of the coordinated response. The ratio of the dispersion of cross-regional reproductive quality improvement to the deviation of the coordinated response is used as the lag coefficient of reproductive quality improvement corresponding to the set of regions with the same characteristics. This yields the environmental regulation response characteristics that characterize the inconsistency of regulation among regions with the same reproductive quality characteristics.

6. The method for environmental control in Litopenaeus vannamei breeding based on reproductive quality assessment according to claim 1, characterized in that, The process involves dynamically adjusting the operating parameters of the differentiated environmental control unit based on the environmental control response characteristics. When the lag coefficient for improving reproductive quality exceeds a preset threshold, the short-term environmental parameter prediction model based on the LSTM network outputs the environmental parameter correction amount for a future preset adjustment period, thus obtaining an adaptive control instruction set. Specifically: Extract the lag coefficient for reproductive quality improvement corresponding to each set of regions with the same characteristics in the environmental regulation response features, screen the set of regions with the same characteristics to be optimized that are greater than the preset threshold, retrieve the average water quality parameter set, circulating water branch pipe layout density and microporous aeration device tilt angle of each reproductive quality feature region in the set, and simultaneously extract the time series data of dissolved oxygen concentration, calcium ion concentration, water temperature and the corresponding reproductive quality quantitative value sequence during the regulation operation period, and align and splice them according to the timestamp to construct a training sample set; Using environmental parameters from consecutive historical time steps as input and reproductive quality quantification values ​​lagged by one time step as supervision labels, the short-term environmental parameter prediction model of the LSTM network is trained until convergence. The current dissolved oxygen concentration time series data, calcium ion concentration time series data, and water temperature time series data of the same feature region to be optimized are input into the trained model, and the predicted values ​​of dissolved oxygen concentration, calcium ion concentration, and reproductive quality quantification values ​​are output for each time step within the preset adjustment period in the future. Calculate the cumulative increment of the predicted value of the quantitative value of reproductive quality within the preset adjustment period in the future, compare the cumulative increment with the preset target value of reproductive quality improvement, and when the cumulative increment is less than the preset target value of reproductive quality improvement, take the predicted value of the quantitative value of reproductive quality reaching the preset target value of reproductive quality improvement as the optimization target, determine the required amount of dissolved oxygen concentration correction and calcium ion concentration correction for each time step, and combine the water quality exchange demand matrix of the corresponding reproductive quality characteristic area to calculate the adjustment amount of the circulating water branch flow and the adjustment amount of the aeration intensity of the microporous aeration device. The dissolved oxygen concentration correction, calcium ion concentration correction, circulating water branch pipe flow adjustment, and microporous aeration intensity adjustment are mapped according to the spatial boundaries of the corresponding reproductive quality characteristic regions to generate an adaptive control instruction set carrying spatial coordinate identifiers. This sets drive the corresponding zone-specific environmental control units to adjust their operating parameters according to the instructions. At the same time, the predicted value of the quantitative reproductive quality is fed back to the LSTM network model to update the model parameters online to adapt to the dynamic changes in the breeding pond environment.

7. A breeding environment control system for Litopenaeus vannamei based on reproductive quality assessment, characterized in that, The Litopenaeus vannamei breeding environment control system based on reproductive quality assessment includes a memory and a processor. The memory includes a Litopenaeus vannamei breeding environment control method program based on reproductive quality assessment. When the Litopenaeus vannamei breeding environment control method program based on reproductive quality assessment is executed by the processor, it implements the steps of the Litopenaeus vannamei breeding environment control method based on reproductive quality assessment as described in any one of claims 1 to 6.

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