Freshwater shrimp and crab multi-nutrition hierarchy system aquatic plant dynamic rotation method based on intelligent regulation and control

Abstract

The invention relates to the technical field of ecological breeding, in particular to a freshwater shrimp and crab multi-nutrition hierarchy system aquatic plant dynamic crop rotation method based on intelligent regulation and control, and solves the problems that during ecological breeding of freshwater shrimps and crabs, management is extensive and depends on experience, plant configuration and crop rotation mainly depend on artificial experience, and the survival rate is low. The dynamic change of water quality and the real-time requirements of shrimps and crabs cannot be accurately responded, so that the breeding income is low. Comprising the following steps: S1, building an aquatic plant function database and a dynamic rotation knowledge base; s2, deploying a sensor network in the breeding area, and monitoring water quality parameters in the range of the breeding area in real time. According to the system, a cooperative system composed of an intelligent control center, a sensor network and an ecological execution module is constructed, accurate management and dynamic adjustment of aquatic plant communities are achieved, the service function of the ecological system always keeps optimal matching with the breeding requirement, and therefore the breeding income is increased.

Description

Technical Field

[0001] This invention relates to the field of ecological aquaculture technology, specifically to a dynamic crop rotation method for aquatic plants in a multi-trophic level freshwater shrimp and crab system based on intelligent regulation. Background Technology

[0002] Ecological aquaculture is a farming method based on the principle of symbiosis and complementarity. It utilizes the natural material cycle system and employs technology and management measures within a specific farming space to enable different organisms to grow together, maintain ecological balance, and improve farming profits. This method uses unpolluted waters or ecological technologies to improve water quality and the ecological environment, and produces pollution-free food. The core of ecological aquaculture lies in following ecological principles to build a resource-recycling, environmentally friendly, and sustainable agricultural production system. Its core elements can be summarized as follows: resource recycling and multi-level utilization of materials, ecological balance and system coordination, environmental friendliness and pollution control, and technology-driven and refined management.

[0003] In the ecological aquaculture of freshwater shrimp and crabs, the extensive management, reliance on experience, and the manual experience-based plant configuration and rotation methods make it difficult to accurately respond to dynamic changes in water quality and the real-time needs of shrimp and crabs, resulting in low aquaculture returns. Therefore, this method does not meet the current needs. To address this, we propose a dynamic aquatic plant rotation method for a multi-trophic level freshwater shrimp and crab system based on intelligent regulation. Summary of the Invention

[0004] The purpose of this invention is to provide a dynamic rotation method for aquatic plants in a multi-trophic level freshwater shrimp and crab system based on intelligent regulation, in order to solve the problems mentioned in the background art, such as extensive management, reliance on experience, and plant configuration and rotation mainly based on human experience when ecologically aquaculture of freshwater shrimp and crabs, which cannot accurately respond to dynamic changes in water quality and the real-time needs of shrimp and crabs, resulting in low aquaculture benefits.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for dynamic crop rotation of aquatic plants in a freshwater shrimp and crab multi-trophic level system based on intelligent regulation, comprising the following steps: S1: Establish a functional database of aquatic plants and a dynamic crop rotation knowledge base; S2: Deploy a sensor network in the aquaculture area to monitor water quality parameters in real time within the aquaculture area; S3: The data analysis and control terminal receives water quality parameters, analyzes the water quality parameters and compares them with the crop rotation knowledge base and plant function database to generate comparative data, and generates plant management decisions based on the comparative data. S4: The ecological execution module executes the plant management decisions generated in S3 to dynamically adjust the distribution of aquatic plant communities.

[0006] Preferably, the aquatic plant functional database contains quantitative indicators of various aquatic plants in four dimensions: ecological purification, ecological services, economic output, and growth characteristics.

[0007] Preferably, aquatic plants include submerged plants (Elodea nuttallii, Potamogeton crispus), sessile plants (Vallisneria natans, Hydrilla verticillata), floating plants (Water spinach, Water spinach), water purifiers (Water hyacinth, Water chestnut), and emergent plants (Water bamboo, Water celery).

[0008] Preferably, the dynamic crop rotation knowledge base includes crop rotation patterns associated with seasons, water quality data, and shrimp and crab growth stages, and the crop rotation patterns include at least spring, summer, and autumn patterns.

[0009] Preferably, the sensor network includes multiple water quality monitoring sensors, which collect data at a set frequency, such as once every hour. The water quality monitoring sensors transmit the data to a data analysis and control terminal via wireless transmission technology.

[0010] Preferably, the data analysis and control terminal includes hardware facilities and software devices. The hardware facilities include cloud servers and local servers, and the software devices include an aquatic plant dynamic management algorithm. The aquatic plant dynamic management algorithm is used for data fusion, status diagnosis, and decision generation to realize closed-loop control logic.

[0011] Preferably, the decision generation triggers at least one control scenario, including dynamic coverage adjustment, precise activation of emergency purification, and predictive mode switching, based on real-time water quality data and preset thresholds.

[0012] Preferably, the dynamic coverage adjustment scenario is as follows: when the sensor detects that the dissolved oxygen is continuously below 5 mg / L and the turbidity increases, the system determines that the submerged plants may be too dense or aging and rotting, and outputs a decision to harvest some of the submerged plants and turn on more aerators. The precise activation of the emergency purification scenario is as follows: when a sharp rise in ammonia nitrogen concentration is detected and the water temperature is suitable, the system determines that the feed has been over-fed and adds floating plants. The predictive mode switching scenario is as follows: when the system predicts a sustained high temperature based on historical data and weather forecasts, it outputs a decision to move in purifying plants and prepare to harvest floating plants.

[0013] Preferably, the ecological execution module includes a user interface, manual and automated devices, for receiving and executing instructions issued by the data analysis and control terminal.

[0014] Preferably, the automated equipment includes one or more of an automatic harvester, an aerator, a feeder, and a float valve adjustment device.

[0015] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention can dynamically adjust plant management strategies according to real-time changes in water quality, achieving precise ecological regulation and preventing problems before they occur. When water quality changes and affects the growth of freshwater shrimp and crabs, the aquaculture strategy is adjusted immediately. Through precise matching, it ensures that the various functions of aquatic plants are used efficiently when the system needs them most, while reducing labor costs and resource waste, and improving the overall benefits brought by ecological aquaculture. 2. This invention enables precise management and dynamic adjustment of aquatic plant communities through real-time data-driven approaches, ensuring that ecosystem service functions are always optimally matched with aquaculture needs. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the dynamic crop rotation method of the present invention; Figure 2 This is a schematic diagram of the structure of the float valve adjustment device of the present invention; Figure 3 This is a schematic diagram of the structure of the bio-floating valve of the present invention.

[0017] In the diagram: 1. Aquaculture pond; 2. Biological flotation valve; 3. Adjusting motor; 4. Adjusting crossbar; 5. Moving motor; 6. Adjusting screw; 7. Electric telescopic rod; 8. L-shaped support plate; 9. Battery; 10. Moving slider; 11. Contact groove. Detailed Implementation

[0018] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0019] like Figure 1 The method for dynamic crop rotation of aquatic plants in a freshwater shrimp and crab multi-trophic level system based on intelligent regulation, as shown, includes the following steps: S1: Establish a functional database of aquatic plants and a knowledge base for dynamic crop rotation.

[0020] As the preferred option for this implementation, the aquatic plant functional database contains quantitative indicators of various aquatic plants in four dimensions: ecological purification, ecosystem services, economic output, and growth characteristics.

[0021] Among them, aquatic plants include submerged plants (Elodea nuttallii, Potamogeton crispus), sessile plants (Vallisneria natans, Hydrilla verticillata), floating plants (Water spinach, Water spinach), water purifiers (Water hyacinth, Water chestnut), and emergent plants (Water bamboo, Water celery).

[0022] The dynamic crop rotation knowledge base includes crop rotation patterns associated with seasons, water quality data, and shrimp and crab growth stages. The crop rotation patterns include at least spring, summer, and autumn patterns.

[0023] Spring Mode (March-June): Centered on low-temperature tolerant submerged plants (Elodea nuttallii, Potamogeton crispus) and paired with sessile plants (Vallisneria natans, Hydrilla verticillata), the goal is to create an underwater forest for the early growth and critical molting of shrimp and crabs.

[0024] Summer mode (July-September): Centered on high-efficiency and economical floating plants (water spinach, water spinach), and paired with strong purification plants (water hyacinth - controllable isolation, water chestnut), the goal is to cope with high temperature and fertilization, and achieve economic benefits on the water surface.

[0025] Autumn Mode (October to February of the following year): Centered on submerged autumn and winter plants (Potamogeton crispus), supplemented by emergent plants (Water chestnut, Water celery), the goal is to consolidate the system, fatten up for overwintering, and diversify production. S2: Deploy a sensor network in the aquaculture area to monitor water quality parameters in real time within the aquaculture area.

[0026] As a preferred embodiment, the sensor network includes multiple water quality monitoring sensors. The water quality monitoring sensors collect data at a set frequency, such as once per hour. The water quality monitoring sensors transmit the data to a data analysis and control terminal via wireless transmission technology for real-time acquisition of at least one parameter among water temperature, pH value, dissolved oxygen, ammonia nitrogen, and nitrite.

[0027] S3: The data analysis and control terminal receives water quality parameters, analyzes the water quality parameters and compares them with the crop rotation knowledge base and the plant function database to generate comparative data, and generates plant management decisions based on the comparative data.

[0028] As a preferred embodiment, the data analysis and control terminal includes hardware facilities and software equipment. The hardware facilities include cloud servers and local servers, and the software equipment includes an aquatic plant dynamic management algorithm. The aquatic plant dynamic management algorithm is used for data fusion, status diagnosis and decision generation to realize closed-loop control logic.

[0029] Among them, the decision generation triggers at least one control scenario, including dynamic coverage adjustment, precise activation of emergency purification, and predictive mode switching, based on real-time water quality data and preset thresholds. The dynamic coverage adjustment scenario is as follows: when the sensor detects that the dissolved oxygen is consistently below 5 mg / L and the turbidity increases, the system determines that the submerged plants may be too dense or aging and decaying, and outputs a decision to harvest some of the submerged plants and turn on more aerators. The precise activation of the emergency purification scenario is as follows: when a sharp increase in ammonia nitrogen concentration (0.5 mg / L) is detected and the water temperature is suitable, the system judges that the feed has been over-fed and adds floating plants. The predictive mode switching scenario is as follows: when the system predicts a sustained period of high temperatures based on historical data and weather forecasts, it outputs a decision to move in purifying plants and prepare to harvest floating plants.

[0030] S4: The ecological execution module executes the plant management decisions generated in S3 to dynamically adjust the distribution of aquatic plant communities.

[0031] As a preferred embodiment, the ecological execution module includes a user interface, manual and automated devices for receiving and executing instructions issued by the data analysis and control terminal.

[0032] The automated equipment includes one or more of the following: automatic harvesters, aerators, feeders, and float valve adjustment equipment.

[0033] Example of a core intelligent control scenario: Scenario 1, Dynamic Coverage Adjustment: When the sensor detects that the dissolved oxygen is consistently below 5 mg / L and the turbidity is increasing, the system determines that the submerged plants may be too dense or aging and decaying. Its decision output is: "Warning: Dissolved oxygen is low, submerged plants may be too dense. Recommendation: Immediately harvest 20% of the Elodea and turn on more aerators."

[0034] Scenario 2, Precise Activation of Emergency Purification: When a sharp increase in ammonia nitrogen concentration (>0.5mg / L) is detected and the water temperature is suitable, the system determines that the feed has been over-fed, and its decision output is: "Warning: Ammonia nitrogen exceeds the standard. Recommendation: Activate 'Emergency Water Purification Mode' to quickly replenish water spinach rafts on the empty water surface, increasing the target coverage rate by 10%."

[0035] Scenario 3, Predictive Mode Switching: Based on historical data and weather forecasts, the system predicts that high temperatures will continue for the next week. Its decision output is: "Forecast: High temperatures for the next week. Recommendation: Move the water hyacinth isolation area into the core breeding area in advance to enhance shading and purification capabilities, and prepare for harvesting water spinach next week."

[0036] Command execution and feedback: The generated decision commands are pushed to farmers through the user interface (mobile APP / computer software) of the control center. For manual and integrated automated equipment, such as automatic harvesters, aerators, feeders and float valve adjustments, the system can send commands for direct execution and receive execution feedback to form a complete closed loop.

[0037] like Figure 2 and Figure 3As shown, the float valve adjustment device includes an aquaculture tank 1. Two movable motors 5 are fixed on both sides of the aquaculture tank 1. The output shaft of the movable motor 5 is connected to an adjusting screw 6. The end of the adjusting screw 6 is connected to the aquaculture tank 1 through a ball bearing support. A movable slider 10 is connected to the outside of the adjusting screw 6 through a thread. An L-shaped support plate 8 is fixed to the bottom of the movable slider 10. A battery 9 is fixed to the surface of the L-shaped support plate 8. An electric telescopic rod 7 is fixed to the outside of the movable slider 10. The movable slider 10 supplies power to the electric telescopic rod 7 through a wire.

[0038] A biological flotation valve 2 is slidably installed above the aquaculture pond 1. Both ends of the biological flotation valve 2 are provided with contact grooves 11. Two regulating motors 3 are also fixed on both sides of the aquaculture pond 1. An regulating cross 4 is fixed on the outside of the output shaft of the regulating motor 3. Each of the four ends of the regulating cross 4 is provided with a U-shaped structure. The two ends of the U-shaped structure are curved outward in an arc shape.

[0039] When adjusting the bio-floating valve, the electric telescopic rod 7 is energized to lift the bio-floating valve 2. Then, the moving motor 5 starts and drives the adjusting screw 6 to rotate, so that the adjusting screw 6 moves the moving slider 10 towards the adjusting motor 3 through thread transmission. The moving slider 10 drives the electric telescopic rod 7 to move the bio-floating valve 2 to the vicinity of the adjusting motor 3. At this time, the adjusting motor 3 is energized and drives the adjusting cross 4 to rotate counterclockwise or clockwise. The end of the rotating adjusting cross 4 is engaged with the inside of the contact groove 11, and the rotating adjusting cross 4 lifts the bio-floating valve 2 and moves it from one side of the aquaculture pond 1 to the other side, thereby adjusting the position of the bio-floating valve 2. This allows for the adjustment of the number of bio-floating valves 2 on both sides of the aquaculture pond 1, which is used to change the number of bio-floating valves for planting water spinach.

[0040] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for dynamic crop rotation of aquatic plants in a freshwater shrimp and crab multi-trophic level system based on intelligent regulation, characterized in that: Includes the following steps: S1: Establish a functional database of aquatic plants and a dynamic crop rotation knowledge base; S2: Deploy a sensor network in the aquaculture area to monitor water quality parameters in real time within the aquaculture area; S3: The data analysis and control terminal receives water quality parameters, analyzes the water quality parameters and compares them with the crop rotation knowledge base and plant function database to generate comparative data, and generates plant management decisions based on the comparative data. S4: The ecological execution module executes the plant management decisions generated in S3 to dynamically adjust the distribution of aquatic plant communities.

2. The method for dynamic crop rotation of aquatic plants in a freshwater shrimp and crab multi-trophic level system based on intelligent regulation according to claim 1, characterized in that: The aquatic plant functional database contains quantitative indicators for various aquatic plants in four dimensions: ecological purification, ecosystem services, economic output, and growth characteristics.

3. The method for dynamic crop rotation of aquatic plants in a freshwater shrimp and crab multi-trophic level system based on intelligent regulation according to claim 2, characterized in that: Aquatic plants include submerged plants (Elodea nuttallii, Potamogeton crispus), sessile plants (Vallisneria natans, Hydrilla verticillata), floating plants (Water spinach, Water spinach), water purifiers (Water hyacinth, Water chestnut), and emergent plants (Water bamboo, Water celery).

4. The method for dynamic crop rotation of aquatic plants in a freshwater shrimp and crab multi-trophic level system based on intelligent regulation according to claim 1, characterized in that: The dynamic crop rotation knowledge base includes crop rotation patterns associated with seasons, water quality data, and shrimp and crab growth stages, and the crop rotation patterns include at least spring, summer, and autumn patterns.

5. The method for dynamic crop rotation of aquatic plants in a freshwater shrimp and crab multi-trophic level system based on intelligent control according to claim 1, characterized in that: The sensor network includes multiple water quality monitoring sensors, which collect data at a set frequency, such as once every hour. The water quality monitoring sensors transmit the data to a data analysis and control terminal via wireless transmission technology. It is used to collect at least one of the following parameters in real time: water temperature, pH value, dissolved oxygen, ammonia nitrogen, and nitrite.

6. The method for dynamic crop rotation of aquatic plants in a freshwater shrimp and crab multi-trophic level system based on intelligent regulation according to claim 3, characterized in that: The data analysis and control terminal includes hardware facilities and software equipment. The hardware facilities include cloud servers and local servers, and the software equipment includes an aquatic plant dynamic management algorithm. The aquatic plant dynamic management algorithm is used for data fusion, status diagnosis and decision generation to realize closed-loop control logic.

7. A method for dynamic crop rotation of aquatic plants in a freshwater shrimp and crab multi-trophic level system based on intelligent regulation, as described in claim 6, is characterized in that: The decision generation triggers at least one control scenario, including dynamic coverage adjustment, precise activation of emergency purification, and predictive mode switching, based on real-time water quality data and preset thresholds.

8. A method for dynamic crop rotation of aquatic plants in a freshwater shrimp and crab multi-trophic level system based on intelligent regulation, as described in claim 7, is characterized in that: The dynamic coverage adjustment scenario is as follows: when the sensor detects that the dissolved oxygen is consistently below 5 mg / L and the turbidity increases, the system determines that the submerged plants may be too dense or aging and decaying, and outputs a decision to harvest some of the submerged plants and turn on more aerators. The precise activation of the emergency purification scenario is as follows: when a sharp rise in ammonia nitrogen concentration is detected and the water temperature is suitable, the system determines that the feed has been over-fed and adds floating plants. The predictive mode switching scenario is as follows: when the system predicts a sustained high temperature based on historical data and weather forecasts, it outputs a decision to move in purifying plants and prepare to harvest floating plants.

9. A method for dynamic crop rotation of aquatic plants in a freshwater shrimp and crab multi-trophic level system based on intelligent regulation, as described in claim 6, is characterized in that: The ecological execution module includes a user interface, manual and automated devices, used to receive and execute instructions issued by the data analysis and control terminal.

10. A method for dynamic crop rotation of aquatic plants in a freshwater shrimp and crab multi-trophic level system based on intelligent regulation, as described in claim 9, is characterized in that: The automated equipment includes one or more of the following: automatic harvester, aerator, feeder, and float valve adjustment device.

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