Polyculture method for humpback perches and plectropomus leopardus

Abstract

The invention relates to the technical field of aquaculture, in particular to a polyculture method for humpback perches and plectropomus leopardus. According to the technical scheme, the method comprises the steps of water quality regulation and control to ensure that the water quality is always in a suitable range, pond area division: dividing a culture pond into different areas, and density control: determining reasonable culture density according to the volume of the culture pond and the growth requirement of each kind of fish, feed feeding: the feed feeding amount and time are automatically adjusted according to the body weight, the feeding rule, the feeding amount and the water quality condition of each type of fish to avoid feed waste as much as possible, and water quality fluctuation prediction and adjustment: possible water quality fluctuation is predicted, and corresponding adjustment is made to keep a stable culture environment. Fish behavior collaborative optimization: improving feed utilization efficiency and ensuring optimal allocation of resources in the culture pond. According to the polyculture method, the feed utilization rate is increased, healthy growth of the two kinds of fishes is ensured, efficient utilization of resources is promoted, and the culture benefit of polyculture of the humpback perches and the plectropomus leopardus can be remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of aquaculture, and particularly to a method for polyculture of Cromileptes altivelis and Plectropomus leopardus. Background Art

[0002] With the rapid development of the aquaculture industry, the fish polyculture technology, as an innovative method to improve the aquaculture efficiency and optimize the aquaculture environment, has been widely applied in the production of various aquaculture species. Polyculture can not only improve the utilization efficiency of water resources, but also effectively reduce the risk of disease transmission during aquaculture. However, due to the differences in the ecological requirements, feeding habits, activity patterns and water quality sensitivity of different fish species, polyculturing different fish species in the same aquaculture environment requires special technical strategies and methods to ensure that each fish species can obtain a good growth environment with minimal mutual influence.

[0003] As common freshwater and seawater fish species, Cromileptes altivelis and Plectropomus leopardus have different habitat requirements, feeding habits and behavior patterns. Cromileptes altivelis usually prefers to inhabit the bottom waters and belongs to benthic fish, with strong adaptability to water temperature; while Plectropomus leopardus tends to inhabit the middle and upper waters, with strong gregariousness and high swimming requirements. If the two are to coexist in the same pond or aquaculture space, without appropriate polyculture management measures, problems such as overlapping habitat space and feeding competition may lead to poor growth effects or increased aquaculture risks.

[0004] Existing polyculture technologies often ignore the differences in biological requirements between different fish species, usually adopting extensive regional division and water quality regulation methods, lacking intelligent fish behavior monitoring and collaborative optimization. For fish species with large differences in habitat requirements such as Cromileptes altivelis and Plectropomus leopardus, traditional polyculture technologies are difficult to meet the growth requirements of various fish species while avoiding mutual interference and resource competition between them.

[0005] Therefore, how to reasonably adjust the polyculture density, optimize the allocation of habitat areas, accurately feed the feed, and monitor and adjust the water quality in real time through refined management and technical means has become the key issue for improving the polyculture effect and reducing the aquaculture cost.

[0006] For this reason, we propose a method for polyculture of Cromileptes altivelis and Plectropomus leopardus to solve the existing problems. Summary of the Invention

[0007] The purpose of the present invention is to propose a method for polyculture of Cromileptes altivelis and Plectropomus leopardus for the problems existing in the background art.

[0008] To achieve the above object, the present invention provides the following technical solution: A polyculture method for Cromileptes altivelis and Plectropomus leopardus, comprising the following steps. Step 1 Water quality regulation: Continuously monitor water quality parameters such as water temperature, pH value, dissolved oxygen concentration, and ammonia nitrogen concentration in the culture pond, and automatically adjust the water quality according to the real-time monitoring data to ensure that the water quality is always within the appropriate range to promote the healthy growth of fish. Step 2 Pond area division: According to the different habitat habits and activity requirements of Cromileptes altivelis and Plectropomus leopardus, divide the culture pond into different areas. The bottom area is suitable for the habitat of Cromileptes altivelis, set an area with a relatively low water flow rate, and make the water depth reach 2 meters; the middle and upper areas are suitable for the activities of Plectropomus leopardus, set an area with a relatively high water flow rate, and the water depth is 1 to 2 meters. Step 3 Density control: Determine a reasonable stocking density according to the volume of the culture pond and the growth requirements of each type of fish. Step 4 Feed feeding: Automatically adjust the feed delivery amount and time according to the weight, feeding rules, feed intake of each fish, and water quality conditions. The system ensures accurate and timely feed delivery each time and minimizes feed waste by linking with water quality sensors and behavior analysis systems. Step 5 Water quality fluctuation prediction and adjustment: Use an advanced data prediction model to monitor and predict the water quality fluctuation trend in real time. Through the analysis of historical water quality data, combined with the fish activity cycle and external environmental changes, predict possible water quality fluctuations and make corresponding adjustments to maintain a stable culture environment. Step 6 Fish behavior collaborative optimization: Use sensors to monitor the feeding habits, activity patterns, and schooling behavior of fish. Combining with water quality monitoring data, optimize the timing and placement of feed feeding. When optimizing feed feeding, not only consider the biological needs of different fish species, but also combine the changes in water quality and the activities of fish. Adjust the feeding amount and feeding method through real-time data analysis to improve feed utilization efficiency and ensure the optimal allocation of resources in the culture pond.

[0009] Preferably, the water quality regulation specifically includes controlling the water temperature between 16°C and 20°C, the pH value between 7.5 and 8.5, and the dissolved oxygen concentration between 5 and 8 mg / L. In addition, it is necessary to regularly check the concentration of harmful substances such as ammonia nitrogen to ensure that it is within a safe range. Further, it includes using a temperature control device to adjust the water temperature to ensure that the water temperature is always within the ideal range, using a buffer agent dosing system to adjust the pH value of the water body, and controlling the dissolved oxygen concentration in the water through an aerator to avoid the occurrence of water body hypoxia.

[0010] Preferably, in order to avoid interference between the two types of fish in the pond area division, a transparent partition net or a flexible glass wall can be used to physically isolate different areas. Reasonably configure the size and layout of each area according to the growth space requirements of the fish to ensure that the two types of fish can avoid interfering with each other during activities and achieve the optimal sharing of resources at the same time.

[0011] Preferably, the density control optimizes the density configuration of fish by comprehensively considering the growth space requirements, growth stage and water volume of each fish, ensuring that each fish has enough space to move around in the pond, avoiding fish stress or resource competition caused by excessive density. Density optimization can also reduce water pollution load and improve water quality stability.

[0012] Preferably, the feed feeding step includes adjusting the feeding time according to the peak feeding period of different fish species, especially for humpback seabass, regular and quantitative feeding is implemented in the morning and evening; for leopard gill bass, regular feeding is carried out from noon to afternoon during its peak activity period.

[0013] Preferably, the water quality fluctuation prediction and adjustment step further includes using machine learning algorithms and data analysis models to model historical water quality fluctuation trends, and optimizing predictions in combination with real-time water quality data, to provide early warnings of possible water quality problems, and to adjust the operating strategy of the water quality control system in real time.

[0014] Preferably, the area, water volume and water flow rate of the breeding pond are flexibly adjusted according to different breeding scales to adapt to different water environment conditions and breeding needs, ensuring efficient allocation of resources and healthy growth of fish.

[0015] Preferably, the fish behavior collaborative optimization step further includes real-time monitoring of fish feeding patterns, activity areas and group behaviors through sensor monitoring and data analysis, and optimizing feed feeding strategies based on this information so that feed delivery can more accurately meet the needs of fish and reduce feed waste.

[0016] Compared with the prior art, the present invention has the following beneficial effects:

[0017] Optimize fish habitat and activity area: The present invention scientifically divides the breeding pond into different areas. The bottom area is the habitat of humpback perch, and the upper area is the activity area of leopard gill perch, thus avoiding the overlapping of habitat space and resource competition between the two types of fish. The use of transparent separation nets or flexible glass walls not only ensures the free flow of water, but also effectively avoids direct contact and competition between fish, thus promoting the healthy growth of the two types of fish.

[0018] Intelligent feeding to improve feed utilization efficiency: The present invention adopts an intelligent feeding system, which is precisely controlled based on real-time water quality data, fish feeding behavior and activity patterns. Sensors monitor the feeding status and behavior of fish, and automatically adjust the amount and time of feed to ensure that each type of fish can obtain sufficient nutrition at the right time, avoiding the problems of feed waste and overfeeding in traditional farming. The optimized feeding strategy significantly improves the utilization rate of feed, reduces unnecessary waste of resources, and reduces feed costs;

[0019] Real-time water quality monitoring and adjustment to maintain stable water quality: The present invention adopts an advanced water quality monitoring system to detect key water quality indicators such as water temperature, pH value, dissolved oxygen concentration, and ammonia nitrogen concentration in the aquaculture pond in real time, and automatically adjusts the water quality according to these data to maintain the stability of the water body. Especially in the activity areas of different fish species, the water quality parameters can be finely adjusted according to specific needs, so as to provide an ideal growth environment for each fish species and reduce the impact of water quality fluctuations on fish health;

[0020] Synergistic optimization of fish behavior to reduce interference and competition: The present invention monitors the group behavior and activity patterns of fish through sensors, and combines with water quality change data to optimize the feed feeding strategy in real time. This synergistic optimization based on fish behavior data and water quality information enables the feed placement to accurately match the feeding needs of fish, thus reducing fish competition and stress caused by uneven feed distribution or improper feeding timing;

[0021] Improve the healthy growth of fish and reduce the disease risk: Through refined management, fish can move freely under suitable environmental conditions, avoiding stress reactions caused by overcrowding and resource competition. The combined effects of stable water quality, reasonable density control, and optimized feeding strategy promote the healthy growth of fish, reduce the risk of disease transmission, and thus improve the production efficiency of aquaculture. Description of the Drawings

[0022] Figure 1 It is a schematic flow chart of the present invention. Detailed Embodiments

[0023] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0024] Embodiment 1

[0025] As Figure 1 shown, a method for polyculture of Cromileptes altivelis and Plectropomus leopardus proposed by the present invention includes the following steps:

[0026] Step 1 Water quality regulation:

[0027] Continuously monitor water quality parameters such as water temperature, pH value, dissolved oxygen concentration, and ammonia nitrogen concentration in the aquaculture pond. Automatically adjust the water quality according to the real-time monitoring data to ensure that the water quality is always within the appropriate range to promote the healthy growth of fish. The water quality regulation specifically includes controlling the water temperature between 16°C and 20°C, the pH value between 7.5 and 8.5, and the dissolved oxygen concentration between 5 and 8 mg / L. In addition, it is necessary to regularly check the concentration of harmful substances such as ammonia nitrogen to ensure that it is within a safe range. Further, it includes using a temperature control device to adjust the water temperature to ensure that the water temperature is always within the ideal range, using a buffer agent dosing system to adjust the pH value of the water body, and controlling the dissolved oxygen concentration in the water through an aerator to avoid the occurrence of water body hypoxia. The specific steps are as follows:

[0028] Temperature regulation and monitoring:

[0029] By installing an intelligent temperature control system (a system combining a temperature sensor and a heating device), ensure that the water temperature is maintained between 16 degrees and 20 degrees. This system raises the water temperature through heating pipes in cold seasons or lowers the water temperature through a cooling device in hot weather, thus avoiding the adverse effects of drastic temperature fluctuations on fish growth.

[0030] Temperature change control formula: The adjustment formula for temperature change maintains the target temperature by dynamically adjusting the heating power P:

[0031] P = k T ·(T set - T current )

[0032] Where, T set is the set ideal water temperature, T current is the current water temperature, and k T is the power adjustment coefficient of the heating system.

[0033] pH value adjustment and control: The pH value has a significant impact on the solubility of harmful substances in water, the activity of microorganisms, and the metabolism of fish. For Cromileptes altivelis and Plectropomus leopardus, the ideal pH value range is 7.5 to 8.5. Therefore, an automatic pH adjustment system is adopted to dose an appropriate amount of buffer agent (such as sodium carbonate or sodium dihydrogen phosphate) according to the real-time monitoring results to adjust the pH of the water body.

[0034] pH value adjustment formula: The control system determines the buffer agent dosing amount by calculating the pH deviation ΔpH:

[0035] ΔpH = pH current - pH target

[0036] The amount Q of the buffer agent dosed is proportional to the pH deviation:

[0037] Q = k p ·|ΔpH|

[0038] Among them, k p is an adjustment coefficient, which is dynamically adjusted according to the volume of water in the pond and the water flow velocity.

[0039] Dissolved oxygen regulation: Dissolved oxygen is one of the key factors affecting fish growth. Too low dissolved oxygen will affect the respiration and metabolism of fish, and may even lead to death. The system ensures that the dissolved oxygen concentration in the water body is maintained between 5 - 8 mg / L through an oxygen pump and a water flow regulating device to avoid low oxygen phenomena.

[0040] Dissolved oxygen maintenance formula: The adjustment of the dissolved oxygen concentration DO needs to balance according to the oxygen consumption (determined by the number and activity of fish) and the natural oxygen increment (such as plant photosynthesis):

[0041]

[0042] Among them, O inflow (t) is the external oxygen increment, k do is the dissolved oxygen consumption rate, and DO target is the target dissolved oxygen concentration.

[0043] The water quality change model assumes that the changes of each parameter have hysteresis, and the control system adjusts according to the error. The feedback formula of the control system is:

[0044]

[0045] Among them:

[0046] X i is the i-th water quality parameter (such as temperature, pH, dissolved oxygen, etc.).

[0047] X target is the corresponding target value.

[0048] P i is the control gain, and n is the type of water quality parameters (temperature, pH value, dissolved oxygen, etc.).

[0049] By adjusting the gain coefficient P i , the system can intelligently control each water quality parameter and keep it within the target range.

[0050] Step 2 Pond area division:

[0051] To reduce the mutual competition and interference between the two kinds of groupers, in this embodiment, the aquaculture pond is reasonably partitioned according to the habitat habits of the two kinds of fish. According to the different habitat habits and activity requirements of the humphead grouper and the leopard coral grouper, the aquaculture pond is divided into different areas. The bottom area is suitable for the habitat of the humphead grouper, and an area with a lower water flow velocity is set; the middle and upper areas are suitable for the activities of the leopard coral grouper, and an area with a higher water flow velocity is set;

[0052] To avoid interference between the two fish species in the pond, a transparent partition net or a flexible glass wall can be used to physically isolate different areas. The sizes and layouts of the areas are reasonably configured according to the growth space requirements of the fish, ensuring that the two fish species can avoid interfering with each other during activities while achieving optimal resource sharing.

[0053] Among them, the bottom area design:

[0054] Cromileptes altivelis usually inhabits the bottom layer of the water body, avoiding areas with too fast water flow. The bottom area of the pond is designed as a low-flow area (0.1, 0.3 m / s), and the water depth is about 2 meters;

[0055] The upper and middle area design: Plectropomus leopardus prefers the upper and middle waters. The water flow speed in the designed area is (0.3, 0.5 m / s), and the water depth is 1 - 2 meters, which is suitable for its growth and activities.

[0056] Step 3 Density control:

[0057] According to the volume of the aquaculture pond and the growth requirements of each fish species, a reasonable aquaculture density is determined. Density control optimizes the density configuration of the fish by comprehensively considering the growth space requirements, growth stages, and water volume of each fish species, ensuring that each fish can have enough space to move in the pond and avoiding fish stress or resource competition caused by excessive density. The optimization of density can also reduce the water pollution load and improve the stability of water quality.

[0058] To improve water utilization efficiency and ensure the healthy growth of each fish, a reasonable aquaculture density is calculated.

[0059] Calculation of individual occupied space: According to the weight and growth curve of each fish species, calculate the minimum space required by them in an ideal environment. Assume that the weight of each fish species is related to the growth cycle:

[0060] W i (t) = W0·(1 + r i ·t)

[0061] Among them, W i (t) is the weight of the i-th fish species at time t, W0 is the initial weight, and r i is the growth rate of this fish species.

[0062] The total aquaculture density D is:

[0063]

[0064] Where N is the number of the i-th type of fish in the pond, and V is the ideal water volume. Optimizing the stocking density ensures that the activities of each type of fish in the culture pond are not cramped, and the minimum growth space for each type of fish is estimated based on its growth curve and individual body weight.

[0065] For example, for Cromileptes altivelis, a fish with a body weight of approximately 1.5 kg needs to occupy about 1.5 square meters of the bottom space; while the space requirement of Plectropomus leopardus in the activity area is 1 square meter. Through comparative calculations, it is ensured that the density in each area does not exceed the carrying capacity of that area.

[0066] Step 4 Feed feeding:

[0067] Automatically adjust the feed delivery amount and time according to the body weight, feeding pattern, food intake, and water quality conditions of each type of fish. The system ensures accurate and timely feed delivery each time and minimizes feed waste by linking with the water quality sensor and behavior analysis system. The feed feeding step includes adjusting the feeding timing according to the feeding peak periods of different fish species. Specifically, for Cromileptes altivelis, timed and quantitative feeding is implemented in the morning and evening; for Plectropomus leopardus, timed feeding is carried out from noon to afternoon during its activity peak period.

[0068] Optimization of feeding time:

[0069] Cromileptes altivelis: The feeding peak periods of this fish species mainly concentrate in the morning and evening, and the feeding system automatically conducts quantitative feeding during these two periods.

[0070] Plectropomus leopardus: Due to its all-day feeding habit, the system conducts timed feeding from noon to afternoon during its activity peak period through a fluidized feeding device.

[0071] The feed delivery amount for each type of fish is calculated according to body weight and growth rate:

[0072] F i =W i ·r i

[0073] Where W i is the body weight of the i-th type of fish, r i is the feeding coefficient, and F i is the feed requirement of the i-th type of fish.

[0074] Design the feed formulation according to the nutritional requirements of fish. Each type of fish has different requirements for protein, fat, and carbohydrates, so the formulation needs to be adjusted according to the fish species and growth stage.

[0075] For Cromileptes altivelis, the protein content in the feed needs to be maintained between 45% - 50%; while the protein requirement of Plectropomus leopardus is relatively low, about 35% - 40%.

[0076] The growth of fish is closely related to energy consumption. Let the energy requirement of each fish species be E i , then the relationship between feed energy and fish weight and growth rate can be expressed by the following formula:

[0077] E i = k i ·P i

[0078] where E i is the energy requirement of the fish, P i is the weight of the fish, and k i is the energy consumption coefficient of this fish species.

[0079] Step 5 Water quality fluctuation prediction and adjustment:

[0080] Use an advanced data prediction model to monitor and predict the water quality fluctuation trend in real time. Through the analysis of historical water quality data, combined with the fish activity cycle and external environmental changes, predict possible water quality fluctuations and make corresponding adjustments to maintain a stable aquaculture environment. The water quality fluctuation prediction and adjustment steps further include using machine learning algorithms and data analysis models to model the historical water quality fluctuation trend and optimize the prediction in combination with real-time water quality data, giving early warnings of possible water quality problems, and adjusting the operation strategy of the water quality control system in real time.

[0081] Among them, according to historical data, use the water quality fluctuation analysis model to evaluate the impact of water quality changes and predict future trends. The change of water quality parameters can be described by the following linear differential equation:

[0082]

[0083] where:

[0084] X is the water quality parameter (such as temperature, pH value, etc.),

[0085] k is the water quality self-recovery coefficient (depending on the self-purification ability of the water quality),

[0086] α is the degree of influence of external interference factors on water quality,

[0087] I(t) is the influence of external factors (such as weather, environmental pollution, etc.) on water quality.

[0088] According to this formula, the system can predict the short-term water quality fluctuation and adjust the regulation strategy in advance.

[0089] Step 6 Fish behavior collaborative optimization:

[0090] Sensors are used to monitor the feeding habits, activity patterns and clustering behaviors of fish. Combined with water quality monitoring data, the timing and location of feed feeding are optimized. When optimizing feed feeding, not only the biological needs of different fish species are considered, but also the changes in water quality and the activity of fish. The feeding amount and feeding method are adjusted through real-time data analysis to improve feed utilization efficiency and ensure the optimal allocation of resources in the breeding pond. The fish behavior collaborative optimization step further includes real-time grasp of fish feeding patterns, activity areas and group behaviors through sensor monitoring and data analysis, and optimization of feed feeding strategies based on this information, so that feed delivery can more accurately meet the needs of fish and reduce feed waste.

[0091] The specific expressions are as follows:

[0092] Optimal calculation of feed feeding amount:

[0093] Given a certain time point t, the feed amount F(t) can be calculated by the following formula:

[0094] F(t)=f(S(t),A(t),W(t),P(t))

[0095] in:

[0096] S(t): represents the feeding state of the fish at time t, usually the feeding rate of the fish (which can be measured in real time through sensor data). For example, the feeding state S(t) can take values between 0 (not feeding) and 1 (fully fed);

[0097] A(t): represents the distribution of fish activity areas at time t. The specific activity locations of fish schools in the pond can be detected by sensors. Assume that the activity density of fish schools in area A(t) is ρ(A(t));

[0098] W(t): represents the current water quality conditions, especially water temperature, dissolved oxygen concentration, pH value, etc., which directly affect the feeding behavior of fish. Assuming that the effect of water quality factors on fish feeding is linear, it can be represented by a weighted function;

[0099] P(t): represents the group behavior pattern of fish schools, which usually involves the activity and clustering behavior of fish schools, and depends on the group movement rules of fish schools and the cohesion of clusters.

[0100] Optimization model of feeding strategy:

[0101] In order to ensure that the feeding amount F(t) matches the fish's feeding needs, the feeding amount needs to be adjusted according to different factors. For example, the higher the fish activity area density ρ(A(t)), the stronger the degree of fish aggregation, and the required amount of feed should also increase. Therefore, the adjustment of the feeding amount can be expressed by the following relationship:

[0102]

[0103] in:

[0104] k1 is a constant, which represents the feed requirement coefficient of fish under specific environment;

[0105] W opt It is an ideal water quality standard value (such as the most suitable dissolved oxygen concentration and pH value, etc.) used to regulate the effect of water quality on feed demand;

[0106] P(t) is the weighted coefficient of the group behavior factor, which indicates the degree of activity of the group. For example, if the fish school is active and the group cooperation is high, the feed demand will also increase accordingly.

[0107] Optimization of feeding timing:

[0108] In order to determine the optimal feeding time feed , a predictive model of fish feeding behavior can be used. Assuming that the feeding behavior changes periodically over time t, it can be modeled by a periodic function:

[0109] t feed = argmax t (S(t)·A(t)·cos(ωt+φ))

[0110] in:

[0111] ω is the frequency of fish feeding behavior (depending on the fish species and life cycle);

[0112] φ is the phase, which indicates the time offset of the peak feeding period of fish;

[0113] S(t) and A(t) are the feeding state and activity area defined above.

[0114] By maximizing the above function, the optimal feeding time t can be determined feed That is, feeding should be done during the period when fish are most active in feeding and their activity areas are most concentrated.

[0115] Through the above mathematical formula, the coordinated optimization of fish behavior can be achieved, and adjustments can be made in the following aspects:

[0116] Optimize feeding amount: dynamically adjust feeding amount based on fish feeding status, activity area, group behavior and water quality;

[0117] Optimize feeding time: Determine the best feeding time through periodic functions and fish behavior prediction models;

[0118] Reduce feed waste: Ensure feed delivery matches fish needs and avoid overfeeding.

[0119] The combination of these optimization strategies will help improve the utilization efficiency of feed, ensure the healthy growth of fish, and reduce resource waste at the same time.

[0120] The area, water volume, and water flow rate of the aquaculture pond are flexibly adjusted according to different aquaculture scales to adapt to different water environment conditions and aquaculture needs, ensuring the efficient allocation of resources and the healthy growth of fish.

[0121] The above specific embodiments are merely several preferred embodiments of the present invention. Based on the technical solution of the present invention and the relevant inspirations of the above embodiments, those skilled in the art can make various alternative improvements and combinations to the above specific embodiments.

[0122] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present invention.

Claims

1. A method for polyculture of Cromileptes altivelis and Plectropomus leopardus, comprising the following steps, characterized in that: The step 1 water quality control: continuously monitor the water quality parameters such as water temperature, pH value, dissolved oxygen concentration and ammonia nitrogen concentration in the breeding pond, automatically adjust the water quality according to the real-time monitoring data, ensure that the water quality is always in an appropriate range to promote the healthy growth of fish, the step 2 pond area division: according to the different habitat habits and activity needs of humpback perch and leopard gill perch, the breeding pond is divided into different areas, the bottom area is suitable for the habitat of humpback perch, and an area with a lower water flow velocity is set, and the water depth reaches 2 meters; the middle and upper areas are suitable for the activities of leopard gill perch, and an area with a higher water flow velocity is set, and the water depth is 1 to 2 meters, the step 3 density control: according to the volume of the breeding pond and the growth needs of each fish, a reasonable breeding density is determined, the step 4 feed feeding: according to the weight, feeding habits, food intake and water quality of each fish, the feed delivery amount and time are automatically adjusted, and the system passes By linking with water quality sensors and behavior analysis systems, it is ensured that the amount of feed fed each time is accurate and timely, and feed waste is avoided as much as possible. Step 5: Prediction and adjustment of water quality fluctuations: Use advanced data prediction models to monitor and predict water quality fluctuation trends in real time. Through the analysis of historical water quality data, combined with fish activity cycles and external environmental changes, predict possible water quality fluctuations, and make corresponding adjustments to maintain a stable breeding environment. Step 6: Coordinated optimization of fish behavior: Use sensors to monitor fish feeding habits, activity patterns and clustering behaviors, and combine water quality monitoring data to optimize the timing and location of feed feeding. When optimizing feed feeding, not only the biological needs of different fish species are considered, but also combined with changes in water quality and fish activities. The feeding amount and feeding method are adjusted through real-time data analysis, thereby improving feed utilization efficiency and ensuring the optimal allocation of resources in the breeding pond.

2. The polyculture method of Cromileptes altivelis and Plectropomus leopardus according to claim 1, characterized in that: The water quality control specifically includes controlling the water temperature between 16°C and 20°C, the pH value between 7.5 and 8.5, and the dissolved oxygen concentration between 5 and 8 mg / L. In addition, the concentration of harmful substances such as ammonia nitrogen needs to be checked regularly to ensure that it is within a safe range, further including using a temperature control device to adjust the water temperature to ensure that the water temperature is always within the ideal range, using a buffer delivery system to adjust the pH value of the water body, and controlling the concentration of dissolved oxygen in the water through an aeration pump to avoid the occurrence of hypoxia in the water body.

3. A method for polyculture of Cromileptes altivelis and Plectropomus leopardus according to claim 1, characterized in that: In order to avoid interference between the two types of fish, the area division in the pool can use transparent partition nets or flexible glass walls to physically isolate different areas. The size and layout of each area can be reasonably configured according to the growth space requirements of the fish, ensuring that the two types of fish can avoid interference with each other during activities and achieve optimal sharing of resources.

4. A method for polyculture of Cromileptes altivelis and Plectropomus leopardus according to claim 1, characterized in that: The density control optimizes the density configuration of fish by comprehensively considering the growth space requirements, growth stage and water volume of each fish, ensuring that each fish has enough space to move around in the pond, avoiding fish stress or resource competition caused by excessive density. Density optimization can also reduce water pollution load and improve water quality stability.

5. A method for polyculture of Cromileptes altivelis and Plectropomus leopardus according to claim 1, characterized in that: The feed feeding step comprises adjusting the feeding time according to the feeding peak period of different fish species, especially implementing timed and quantitative feeding of humpback perch in the morning and evening; and feeding of leopard gill perch regularly from noon to afternoon during its activity peak period.

6. A method for polyculture of Cromileptes altivelis and Plectropomus leopardus according to claim 1, characterized in that: The water quality fluctuation prediction and adjustment step further includes using machine learning algorithms and data analysis models to model historical water quality fluctuation trends, and optimizing predictions in combination with real-time water quality data, providing early warnings of possible water quality problems, and adjusting the operating strategy of the water quality control system in real time.

7. A method for polyculture of Cromileptes altivelis and Plectropomus leopardus according to claim 1, characterized in that: The area, water volume and water flow rate of the breeding pond can be flexibly adjusted according to different breeding scales to adapt to different water environment conditions and breeding needs, ensuring efficient allocation of resources and healthy growth of fish.

8. The polyculture method of Cromileptes altivelis and Plectropomus leopardus according to claim 1, characterized in that: The fish behavior collaborative optimization step further includes real-time monitoring of fish feeding patterns, activity areas and group behaviors through sensor monitoring and data analysis, and optimizing feed feeding strategies based on this information so that feed delivery can more accurately meet the needs of fish and reduce feed waste.

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