Rice planting method based on shrimp and rice symbiosis intelligent regulation and control

Abstract

The invention discloses a rice planting method based on shrimp and rice symbiosis intelligent regulation and control, and relates to the technical field of agricultural planting. To solve the problem; according to the invention, environment parameters are monitored and analyzed in real time through the intelligent regulation and control equipment, the symbiotic environment state matrix is generated, precise regulation and control of the prawn and rice symbiotic environment are realized, and the symbiotic efficiency is improved. The establishment of the adaptive model optimizes the rice variety selection and shrimp seed putting strategy, enhances the system stability, reduces the production cost through comprehensive management, improves the economic benefits and ecological benefits, effectively promotes the sustainable development of shrimp and rice symbiosis, integrates a wireless transmission network, edge computing nodes and a visual monitoring interface, and improves the management efficiency. Intelligent management of shrimp and rice symbiosis is achieved, manual intervention is reduced, the production cost is reduced, and meanwhile economic benefits and ecological benefits are improved.

Description

Technical Field

[0001] The present invention relates to the field of agricultural planting technology, and in particular to a rice planting method based on intelligent regulation of shrimp-rice symbiosis. Background Art

[0002] With the development of modern agriculture, shrimp-rice symbiosis has been increasingly valued as an ecological planting model. For example, the patent application with publication number CN113826521A discloses a technical method for shrimp-rice symbiosis cultivation, including the following steps: S1, rice field selection; S2, rice field disinfection management; S3, rice variety selection and planting; S4, shrimp seedling selection and release; S5, shrimp seedling release; S6, feeding management; S7, daily management; S8, rice management; S9, rice harvesting and shrimp fishing. This patent application uses a mixture of shrimp and rice to enrich the nutrition of shrimps, which has a large market share for societies that practice ecological farming. At the same time, aquatic plants and rice grow vigorously, and the dissolved oxygen content in the rice field water is high, which is beneficial to the growth of shrimp seedlings and improves the survival rate, reduces the use of chemical fertilizers in rice fields, reduces breeding and planting costs, and improves the yield, specifications and quality of shrimps.

[0003] However, in the shrimp-rice symbiotic cultivation methods in the existing technology, the regulation of key environmental parameters such as water level, water quality, and temperature mainly relies on manual observation and empirical judgment. There are problems such as inaccurate environmental monitoring, unscientific variety selection, and low management efficiency, resulting in poor symbiotic effects and high production costs. Summary of the Invention

[0004] The purpose of the present invention is to provide a rice planting method based on intelligent regulation of shrimp-rice symbiosis, using a multi-parameter sensor group to collect data in real time, screening key indicators through correlation analysis, realizing dynamic threshold regulation of environmental parameters, improving the efficiency of planting and breeding coordination, and significantly improving the yield, quality and ecological benefits of shrimp-rice symbiosis, so as to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] The rice planting method based on intelligent regulation of shrimp-rice symbiosis includes:

[0007] Select a field where shrimp and rice coexist, evenly arrange a multi-parameter sensor group in the field, build an intelligent control device, and establish an adaptation model between the characteristics of rice varieties and the growth cycle of crayfish;

[0008] Based on the adaptation model, the rice variety and the corresponding shrimp seedling release time are determined. Shrimp seedlings that grow at the same time as the selected rice variety are released into the fields. The growth status of the shrimp seedlings is monitored in real time using intelligent control equipment. At the same time, rice seedlings are raised using a factory-based seedling raising method. After the crayfish fishing season ends, the cultivated rice seedlings are transplanted into the fields.

[0009] Based on the real-time collection of key environmental parameters by intelligent control equipment in the field, the monitored key environmental parameters are analyzed to identify the key environmental parameter thresholds that are conducive to shrimp-rice symbiosis and formulate corresponding shrimp-rice symbiosis control strategies;

[0010] According to the shrimp-rice symbiosis regulation strategy, the key environmental parameters monitored in real time are compared and analyzed, and various regulation measures are implemented based on the comparison and analysis results to carry out intelligent regulation of the shrimp-rice symbiotic fields.

[0011] Furthermore, intelligent control equipment is constructed, including:

[0012] In the selected shrimp-rice symbiotic fields, multi-parameter sensor groups were evenly distributed at the intersection of the ring ditch and the field ditch, and in the rice planting area. These included water quality sensors, soil monitoring sensors, infrared behavior monitoring sensors, and micro-meteorological stations.

[0013] The multi-parameter sensor group is connected to the edge computing node based on the wireless transmission network, and the crayfish activity status data and key environmental parameters are correlated and analyzed based on the edge computing node to generate a real-time symbiotic environment status matrix.

[0014] Furthermore, a real-time symbiotic environment status matrix is ​​generated, specifically including:

[0015] Establish a wireless transmission network to achieve automatic connection between sensor groups and edge computing nodes;

[0016] The characteristic parameters of each crayfish's behavioral state are extracted based on the infrared thermal imaging data obtained by the infrared behavior monitoring sensor;

[0017] Obtain a set of typical behavior states of crayfish, and define a value range and matching rules of characteristic parameters for each typical behavior state in the set of typical behavior states of crayfish;

[0018] The edge computing node compares the extracted characteristic parameters with the typical behavior state set of crayfish one by one through the wireless transmission network to determine the current behavior state of each crayfish;

[0019] Based on the current behavioral state of each crayfish, the association rules between the behavioral state and key environmental parameters are obtained, and the association rules are analyzed in time series to establish a crayfish behavioral state prediction model;

[0020] A multidimensional matrix is ​​constructed, and the edge computing node fills the matrix elements in real time according to the behavior state prediction model and environmental parameter monitoring data to generate a real-time symbiotic environment state matrix.

[0021] Furthermore, generating a real-time symbiotic environment status matrix also includes: visually displaying the real-time symbiotic environment status matrix to intuitively present the field environmental status information of the shrimp-rice symbiosis.

[0022] Furthermore, an adaptation model between rice variety characteristics and crayfish growth cycle was established, including:

[0023] Determine rice variety characteristic data from sowing to maturity, including growth cycle, morphological characteristics, stress resistance, and nutrient requirements at each stage;

[0024] Obtain data on the crayfish growth cycle, including the growth stages, environmental requirements, and behavioral habits of crayfish from juveniles to adults;

[0025] Calculate the correlation coefficient between each rice variety characteristic index and the crayfish growth cycle index, compare the correlation coefficient with the preset correlation threshold, and screen out the key related indicators with correlation;

[0026] An adaptation model framework is constructed based on key correlation indicators, and the adaptation model framework is trained and iteratively optimized based on historical data to generate a trained adaptation model of rice variety characteristics and crayfish growth cycle.

[0027] Furthermore, the shrimp seedlings that grow at the same time as the selected rice variety are released into the fields, and the process also includes: grading the shrimp seedlings according to their size, and before being released, subjecting the graded shrimp seedlings to temporary adaptation in temporary holding ponds for no less than 24 hours.

[0028] Furthermore, the rice seedling raising method based on the factory-based rice seedling raising method also includes:

[0029] Rice variety screening: Collect information on common rice varieties from multiple regions and establish a preliminary variety library containing variety names and basic biological characteristics. The number of rice varieties collected in the preliminary variety library should be no less than 20;

[0030] Plant all rice varieties in the preliminary variety library under the same planting conditions in the experimental field, simulate the shrimp-rice symbiotic environment, release a certain number of crayfish, and evaluate each rice variety in the preliminary variety library based on growth characteristic evaluation indicators at various stages of rice growth;

[0031] Compare the assessment results with the preset assessment qualification threshold to select rice varieties that meet the growth characteristic assessment index requirements;

[0032] Conduct stress tolerance tests on selected rice varieties. By artificially inoculating pests and diseases, the incidence and resistance of the rice varieties are observed. In the late growth period of rice, severe weather conditions such as strong winds are simulated to evaluate their lodging resistance.

[0033] Based on the verification results, rice varieties with strong stress tolerance were screened out to form a final list of rice varieties suitable for shrimp-rice symbiosis.

[0034] Furthermore, the cultivated rice seedlings are transplanted into the fields, which also includes:

[0035] Stress resistance induction treatment: spray the prepared crayfish metabolic simulation solution evenly when the first leaf of the seedling is fully expanded;

[0036] Water flow disturbance simulation: Use an air pump to simulate the water flow disturbance caused by crayfish activities, and the disturbance treatment lasts for 6 hours every day until 3 days before transplanting;

[0037] Transplanting path planning: Based on the distribution of field furrows and soil nutrient status, a spatial coordination model of crayfish activity paths and densely planted rice areas is established, and the transplanting path is optimized through edge computing nodes;

[0038] Transplanting with rice transplanter: Transplanting is performed using a rice transplanter based on the optimized transplanting path.

[0039] Furthermore, corresponding shrimp-rice symbiosis regulation strategies should be formulated, including:

[0040] Based on the real-time symbiotic environmental state matrix, key environmental parameters corresponding to rice growth stages and crayfish behavioral states were extracted, and the thresholds of key environmental parameters under the coupling of rice growth stages and crayfish behavioral states were determined.

[0041] Match the identified key environmental parameter thresholds to the corresponding control rules, and determine the priority of the control rules based on the impact of parameter anomalies on the shrimp-rice symbiosis system;

[0042] Based on the comparison results between the control rules and real-time monitoring data, the control measures are automatically executed to achieve a dynamic balance in the shrimp-rice symbiotic environment, and real-time feedback is provided on the implementation effects of the control measures.

[0043] Furthermore, corresponding shrimp-rice symbiosis regulation strategies are formulated, including: establishing the initial symbiotic environmental balance after transplanting the seedlings, maintaining the water level at a shallow water layer of 3-5 cm within 24 hours after transplanting the seedlings, and guiding crayfish to gather in the ditch area based on the water level difference between the field ditch and the ring ditch; tracking the activity trajectory of crayfish in real time, and when the frequency of a single crayfish entering the main planting area is monitored to be greater than the preset frequency, oxygenating the ring ditch area.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] By constructing intelligent control equipment and a real-time symbiotic environment status matrix, we have achieved precise monitoring and dynamic control of the shrimp-rice symbiotic environment, significantly improved the growth efficiency and quality of rice and crayfish, established an adaptation model between rice variety characteristics and crayfish growth cycle, scientifically screened rice varieties suitable for shrimp-rice symbiosis, optimized the shrimp seedling release time and transplanting strategy, enhanced the stability and sustainability of the symbiotic system, integrated wireless transmission networks, edge computing nodes and visual monitoring interfaces, realized intelligent management of shrimp-rice symbiosis, reduced human intervention, reduced production costs, and at the same time improved economic and ecological benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is a flow chart of the rice planting method based on intelligent regulation of shrimp-rice symbiosis according to the present invention. DETAILED DESCRIPTION

[0047] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0048] In order to solve the technical problems of the traditional shrimp-rice symbiosis model in which environmental regulation relies on manual experience, the efficiency of plant-farming coordination is low, and resource utilization is insufficient, please refer to Figure 1 , this embodiment provides the following technical solutions:

[0049] The rice planting method based on intelligent regulation of shrimp-rice symbiosis includes:

[0050] Select a field where shrimp and rice coexist, evenly arrange a multi-parameter sensor group in the field, build an intelligent control device, and establish an adaptation model between the characteristics of rice varieties and the growth cycle of crayfish;

[0051] Based on the adaptation model, the rice variety and the corresponding shrimp seedling release time are determined. The shrimp seedlings are graded according to their size and, before being released, the graded shrimp seedlings are temporarily adapted in a temporary holding pond for no less than 24 hours to allow them to gradually adapt to the water quality and environment of the field. Shrimp seedlings that grow at the same time as the selected rice variety are released into the field, and the growth status of the shrimp seedlings is monitored in real time based on intelligent control equipment. At the same time, rice seedlings are raised based on a factory-based rice seedling raising method. After the crayfish fishing season ends, the cultivated rice seedlings are transplanted into the field. At the same time, the transplanting density is determined considering the crayfish's activity space and growth needs.

[0052] Intelligent control equipment in the fields collects key environmental parameters in real time, including water quality, soil moisture, temperature, and shrimp activity status. The monitored key environmental parameters are analyzed to identify the key environmental parameter thresholds that are conducive to shrimp-rice symbiosis and formulate corresponding shrimp-rice symbiosis control strategies.

[0053] According to the shrimp-rice symbiosis regulation strategy, the key environmental parameters monitored in real time are compared and analyzed, and various regulation measures are implemented based on the comparison and analysis results to carry out intelligent regulation of the shrimp-rice symbiotic fields.

[0054] In this embodiment, intelligent control equipment is used to monitor and analyze environmental parameters in real time, generate a symbiotic environment state matrix, achieve precise control of the shrimp-rice symbiotic environment, improve symbiotic efficiency, establish an adaptation model to optimize rice variety selection and shrimp seedling release strategy, enhance system stability, and comprehensive management reduces production costs, improves economic and ecological benefits, and effectively promotes the sustainable development of shrimp-rice symbiosis.

[0055] In this embodiment, building an intelligent control device specifically includes:

[0056] Select fields with good water sources, strong water retention capacity, and flat terrain suitable for shrimp-rice symbiosis. Circular ditches were excavated around the fields for crayfish habitat and activity. Cross-shaped or well-shaped field ditches were excavated inside the fields to assist crayfish activity and water circulation. Within the selected shrimp-rice symbiotic fields, multi-parameter sensor groups were evenly deployed at the intersection of the circular ditch and the field ditch, as well as in the rice planting area. These included water quality sensors (monitoring dissolved oxygen, ammonia nitrogen, nitrite, and water temperature, with an accuracy of ±2%), soil monitoring sensors (monitoring moisture content, EC value, and pH value, with a depth of 0-30 cm in the tillage layer), infrared behavioral monitoring sensors (installed at intervals of 10 m, using thermal imaging to identify crayfish clustering activity, molting, and other behavioral states, with a resolution of ≥640×480), and micro-meteorological stations (monitoring light intensity, air temperature and humidity, and wind speed, with a data update frequency of ≤10 seconds).

[0057] In this example, a clay or loam field with a water retention capacity of ≥60% and a pH value of 6.5-7.5 was selected. A circular ditch was excavated along the inner side of the field ridge, occupying 12%-15% of the field area. A bionic perch made of bamboo or wood was set in the ditch for crayfish to hide. The perches were spaced 1.5 meters apart. A "well"-shaped field ditch (0.8 m wide and 0.5 m deep) was excavated at intervals of 20 meters in the middle of the field. The ditch walls were paved with biodegradable fiber mesh to prevent collapse.

[0058] The multi-parameter sensor group is connected to the edge computing node based on the wireless transmission network. The crayfish activity status data and key environmental parameters are correlated and analyzed based on the edge computing node to generate a real-time symbiotic environment status matrix. Specifically, it includes:

[0059] Establish a wireless transmission network to achieve automatic connection between sensor groups and edge computing nodes;

[0060] The characteristic parameters of each crayfish's behavioral state are extracted based on the infrared thermal imaging data obtained by the infrared behavior monitoring sensor;

[0061] In this embodiment, for the static state, the crayfish's contour area, center of mass position and other features are extracted; for the feeding state, the interaction features between the crayfish and the food area, such as distance and overlapping area, are extracted; for the molting state, morphological operations (such as expansion and corrosion) are used to extract the change characteristics of the individual crayfish's surface area, and the surrounding water temperature change data is obtained through a temperature sensor. For the stress state, the optical flow method is used to calculate the crayfish's movement speed and direction, and the ammonia nitrogen concentration change data is obtained in combination with the water quality sensor;

[0062] Obtain a set of typical crayfish behavioral states, including resting, feeding, cruising, molting, stress, etc., and define the value range and matching rules of characteristic parameters for each typical behavioral state in the set;

[0063] The edge computing node compares the extracted characteristic parameters with the typical behavior state set of crayfish one by one through the wireless transmission network to determine the current behavior state of each crayfish;

[0064] Based on the current behavioral state of each crayfish, association rules between behavioral state and key environmental parameters were obtained. For example, in the molting state, the individual surface area increases by 30%-40%, and the surrounding water temperature drops by 0.5-1°C (due to heat dissipation from the water body due to oxygen consumption during molting). In the stress state, the group movement speed is greater than 10 cm / s, the directional consistency is greater than 80%, and the ammonia nitrogen concentration increases by ≥0.3 mg / L. The association rules are then analyzed in time series to establish a prediction model for the crayfish's behavioral state.

[0065] Construct a multi-dimensional matrix. The edge computing node fills the matrix elements in real time based on the behavior state prediction model and environmental parameter monitoring data to generate a real-time symbiotic environment state matrix, including key environmental parameters and state indicators.

[0066] The real-time symbiotic environment status matrix is ​​visualized, using charts and color coding to intuitively present the environmental status information of the shrimp-rice symbiotic field, providing a basis for decision-making on intelligent shrimp-rice symbiosis regulation, such as adjusting water levels, increasing oxygen, and applying fertilizers.

[0067] In this embodiment, the row dimension of the multidimensional matrix represents the rice growth stage (such as the seedling raising period, tillering period, heading period, filling period, and maturity period), the column dimension represents the crayfish behavioral state (such as resting, feeding, cruising, molting, and stress), and the matrix elements represent key environmental parameters (such as dissolved oxygen, ammonia nitrogen concentration, water temperature, soil moisture content, light intensity, etc.) and status indicators (such as the probability of occurrence of behavioral states, the degree of abnormality of environmental parameters, etc.).

[0068] In this embodiment, the structured design of the circular ditch and the field ditch provides a suitable habitat and activity space for crayfish, reducing their disturbance to the rice root system. At the same time, the water circulation design of the field ditch improves the uniformity of dissolved oxygen in the water body, and the survival rate of crayfish is greatly improved compared with the traditional model. The collaborative work of the multi-parameter sensor group and the edge computing node realizes real-time monitoring of various key parameters, generates a real-time symbiotic environment status matrix, and realizes the precise coupling analysis of the crayfish behavioral status and the rice growth stage.

[0069] In this embodiment, an adaptation model between rice variety characteristics and crayfish growth cycle is established, including:

[0070] Determine rice variety characteristics from sowing to maturity, including:

[0071] The growth cycle of each stage: such as the specific duration of the germination period, tillering period, jointing period, booting period, heading period, flowering period, grain filling period and maturity period;

[0072] Morphological characteristics: including plant height, stem diameter, leaf length, leaf width, and root system development, with particular attention paid to characteristics that may interact with crayfish activity, such as plant height during the tillering stage, internode length below the ear, and stem hardness during the waxy stage.

[0073] Stress resistance: Collect data on rice's resistance to stresses such as pests and diseases, drought, flooding, high and low temperatures;

[0074] Nutrient requirements: Understand the demand patterns of rice for major nutrients such as nitrogen, phosphorus, potassium, and various trace elements at different growth stages;

[0075] Obtain crayfish growth cycle data, including:

[0076] The growth stages of crayfish from juvenile to adult, such as juvenile stage, rapid growth stage, molting stage, and maturity stage, are recorded, with the duration of each stage recorded;

[0077] Environmental requirements: including the effects of environmental factors such as water temperature, water quality (dissolved oxygen, pH, ammonia nitrogen content, etc.), bottom sediment, and light on the growth of crayfish, as well as the suitable range of these environmental factors for crayfish at different growth stages;

[0078] Behavioral habits: observe the crayfish's activity patterns, feeding habits, habitat preferences and other behavioral characteristics;

[0079] Calculate the correlation coefficient between each rice variety characteristic indicator and the crayfish growth cycle indicator. For example, analyze the correlation between rice plant height during the tillering stage and the growth rate of crayfish during the juvenile stage, and the correlation between rice stem hardness during the waxy stage and the survival rate of crayfish during the molting stage. Compare the correlation coefficient with the preset correlation threshold to screen out key related indicators with correlation.

[0080] An adaptation model framework is constructed based on key correlation indicators, and the adaptation model framework is trained and iteratively optimized based on historical data to generate a trained adaptation model of rice variety characteristics and crayfish growth cycle.

[0081] In this embodiment, the rice variety screening index effectively avoids the risk of crayfish climbing and breaking stems, establishes an adaptation model between rice variety characteristics and crayfish growth cycle, and achieves precise matching of the planting and breeding cycle from variety screening to shrimp seedling release, so that the rice filling period is synchronized with the crayfish maturity period, which facilitates centralized management and reduces conflicts in planting and breeding cycles.

[0082] In this embodiment, the rice seedling raising method based on the factory-based rice seedling raising method further includes:

[0083] Rice variety screening: Collect information on common rice varieties from multiple regions and establish a preliminary variety library containing variety names and basic biological characteristics (such as plant height, growth period, and stress resistance). The number of rice varieties collected in the preliminary variety library should be no less than 20;

[0084] All rice varieties in the preliminary variety library were planted under the same planting conditions in the experimental field, and a certain number of crayfish were released to simulate the shrimp-rice symbiotic environment. At each stage of rice growth, the rice varieties in the preliminary variety library were evaluated based on the growth characteristic evaluation indicators. The amount of crayfish seedlings released was calculated using the following formula:

[0085]

[0086] Where N is the amount of shrimp seedlings released per mu (tails), S is the area of ​​the ditch (m 2 ), C1 represents the water capacity of the field furrow during the rice jointing period (m 3 / mu), C2 represents the buffer space required for the molting period of crayfish, which is 0.002m 3 / tail, V represents the minimum active volume of a single shrimp fry (m 3 ), take 0.002m 3 / tail;

[0087] Compare the assessment results with the preset qualification thresholds to select rice varieties that meet the growth characteristic assessment index requirements; for example, use statistical methods to calculate the mean and standard deviation of each indicator for each variety to assess its stability and adaptability;

[0088] The selected rice varieties are tested for stress tolerance, including disease and insect pest resistance and lodging resistance. By artificially inoculating pests and diseases, the incidence and resistance of the rice varieties are observed. In the late growth stage of the rice, severe weather conditions such as strong winds are simulated to evaluate their lodging resistance.

[0089] Based on the verification results, rice varieties with strong stress tolerance were screened to form a final list of rice varieties suitable for shrimp-rice symbiosis;

[0090] In this embodiment, the plant height at the tillering stage is ≤80 cm, the internode length below the spike is ≥25 cm (to prevent crayfish from climbing and breaking the stem), and the stem hardness at the waxy stage is ≥15 N / mm. 2 The growth period of varieties (such as the same type of stress-resistant variety "Liangyou 287") overlaps with the crayfish breeding cycle by ≥80%. Based on factors such as the area of ​​the ring ditch, the water capacity of the field ditch during the rice jointing period, and the buffer space required for the crayfish molting period, the amount of shrimp seedlings released per mu is accurately calculated, ensuring the growth environment and living space of the crayfish, improving the survival rate and yield of the crayfish, reducing the planting cost of breeding, and improving the yield and quality of rice and crayfish.

[0091] In this embodiment, the method of transplanting the cultivated rice seedlings into the field also includes:

[0092] Stress-resistance induction treatment: When the first leaf of the seedlings is fully expanded (approximately 10-12 days after sowing), evenly spray the prepared crayfish metabolic simulation solution (containing 0.5 mg / L ammonia nitrogen, 10 mg / L organic carbon, and adjusted to a pH of 6.5-7.5) to induce stress-resistance gene expression and metabolite accumulation;

[0093] Water flow disturbance simulation: An air pump was used to simulate the water flow disturbance caused by crayfish activity (frequency 0.5 Hz, duration 6 hours / day). The disturbance treatment was continued for 6 hours every day until 3 days before transplanting to enhance the toughness of the seedling stems.

[0094] Transplanting path planning: Based on the distribution of field furrows and soil nutrient status, a spatial coordination model of crayfish activity paths and densely planted rice areas is established. The transplanting path is optimized through edge computing nodes. Specifically:

[0095] Obtain field ditch coordinate data, and divide the field into 5m×5m grid cells based on the ditch edge and the field ditch centerline. Build a three-dimensional spatial model, defining the 1m area around the ditch as the "core crayfish activity area," the 0.5m area on both sides of the field ditch as the "secondary activity area," and the remaining area as the "main rice planting area." In the "core crayfish activity area," the distance is expanded to 20cm to form a light-proof channel ≥1m wide for crayfish. No tillering fertilizer is applied in the channel to reduce competitive pressure from rice.

[0096] When the EC value of the grid unit is ≥1.2mS / cm, it indicates nutrient enrichment. In the nutrient-enriched area, the planting density is increased by 5%-10% to form a nutrient circulation channel from "crayfish activity path to rice dense planting area";

[0097] Transplanting with rice transplanter: Based on the optimized transplanting path, transplanting is performed using a Beidou navigation rice transplanter, with row-plant spacing error ≤±1cm, the basic number of seedlings per hole being 2-3, and the uniformity variation coefficient ≤8%.

[0098] In this embodiment, stress resistance induction and transplanting planning based on factory-based seedling cultivation are used to improve the adaptability of seedlings to the symbiotic environment and the efficiency of space resource utilization, thereby increasing the tolerance of seedlings to ammonia nitrogen stress after transplanting. At the same time, water flow disturbance simulation is used to enhance stem toughness, and grid-based transplanting path planning is used to form a synergistic gradient between the crayfish activity space and the rice planting area, thereby ensuring the crayfish's need for shelter from light and improving the utilization rate of nitrogen, phosphorus and potassium, thereby reducing fertilizer input.

[0099] In this embodiment, a corresponding shrimp-rice symbiosis regulation strategy is formulated, specifically including:

[0100] Based on the real-time symbiotic environmental state matrix, key environmental parameters corresponding to rice growth stages (seedling raising, tillering, and booting) and crayfish behavioral states (resting, molting, and stress) were extracted, including dissolved oxygen, ammonia nitrogen concentration, water temperature, soil moisture, and light intensity. The thresholds of key environmental parameters under the coupling of rice growth stages and crayfish behavioral states were determined.

[0101] In this example, the dissolved oxygen threshold during the molting period of crayfish is set at 5.0-5.5 mg / L (based on the dissolved oxygen distribution during successful molting in historical data), and the soil moisture threshold during the rice booting period is set at 65%-75% (combined with the root water demand model at this stage and the upper limit of the moisture content for the benthic activities of crayfish);

[0102] The identified key environmental parameter thresholds are matched to the corresponding control rules, and the control rule priorities are determined based on the degree of impact of parameter abnormalities on the shrimp-rice symbiosis system. The table is as follows:

[0103] Table 1 Regulation strategies for shrimp-rice symbiosis

[0104]

[0105] Based on the comparison results of the control rules and real-time monitoring data, control measures such as water level adjustment, oxygenation, and fertilization are automatically implemented to achieve a dynamic balance in the shrimp-rice symbiotic environment. Real-time feedback on the implementation effect of the control measures is provided. In combination with new monitoring data, the control strategy is iteratively optimized to improve the adaptability of the shrimp-rice symbiotic system.

[0106] Establish the initial symbiotic environmental balance after transplanting the seedlings. Maintain the water level at a shallow water layer of 3-5 cm within 24 hours after transplanting the seedlings. Guide the crayfish to gather in the ditch area based on the water level difference between the field ditch and the ring ditch to reduce the climbing disturbance to the seedlings. Track the activity trajectory of the crayfish in real time. When the frequency of a single crayfish entering the main planting area is greater than the preset frequency, such as more than 3 times per hour, increase the oxygen in the ring ditch area and increase the dissolved oxygen to 6-7 mg / L to attract the crayfish back to the ditch area.

[0107] In this embodiment, a shrimp-rice symbiotic regulation strategy was formulated and implemented, achieving a dynamic balance of environmental parameters and coordinated optimization of the breeding system, improving the pertinence of regulatory measures, and implementing hierarchical regulation rules and effect feedback mechanisms, which significantly enhanced the system's anti-interference ability, improved the efficiency of crayfish stress response processing, reduced the incidence of rice diseases and pests, and established a low-carbon cycle symbiotic model.

[0108] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A rice planting method based on intelligent regulation of shrimp-rice symbiosis, characterized in that: include: Select a field where shrimp and rice coexist, evenly arrange a multi-parameter sensor group in the field, build an intelligent control device, and establish an adaptation model between the characteristics of rice varieties and the growth cycle of crayfish; Based on the adaptation model, the rice variety and the corresponding shrimp seedling release time are determined. Shrimp seedlings that grow at the same time as the selected rice variety are released into the fields. The growth status of the shrimp seedlings is monitored in real time using intelligent control equipment. At the same time, rice seedlings are raised using a factory-based seedling raising method. After the crayfish fishing season ends, the cultivated rice seedlings are transplanted into the fields. Based on the real-time collection of key environmental parameters by intelligent control equipment in the field, the monitored key environmental parameters are analyzed to identify the key environmental parameter thresholds that are conducive to shrimp-rice symbiosis and formulate corresponding shrimp-rice symbiosis control strategies; According to the shrimp-rice symbiosis regulation strategy, the key environmental parameters monitored in real time are compared and analyzed, and various regulation measures are implemented based on the comparison and analysis results to carry out intelligent regulation of the shrimp-rice symbiotic fields.

2. The rice planting method based on intelligent regulation of shrimp-rice symbiosis according to claim 1, characterized in that: Build intelligent control equipment, including: In the selected shrimp-rice symbiotic fields, multi-parameter sensor groups were evenly distributed at the intersection of the ring ditch and the field ditch, and in the rice planting area. These included water quality sensors, soil monitoring sensors, infrared behavior monitoring sensors, and micro-meteorological stations. The multi-parameter sensor group is connected to the edge computing node based on the wireless transmission network, and the crayfish activity status data and key environmental parameters are correlated and analyzed based on the edge computing node to generate a real-time symbiotic environment status matrix.

3. The rice planting method based on intelligent regulation of shrimp-rice symbiosis according to claim 2, characterized in that: Generate a real-time symbiotic environment status matrix, including: Establish a wireless transmission network to achieve automatic connection between sensor groups and edge computing nodes; The characteristic parameters of each crayfish's behavioral state are extracted based on the infrared thermal imaging data obtained by the infrared behavior monitoring sensor; Obtain a set of typical behavior states of crayfish, and define a value range and matching rules of characteristic parameters for each typical behavior state in the set of typical behavior states of crayfish; The edge computing node compares the extracted characteristic parameters with the typical behavior state set of crayfish one by one through the wireless transmission network to determine the current behavior state of each crayfish; Based on the current behavioral state of each crayfish, the association rules between the behavioral state and key environmental parameters are obtained, and the association rules are analyzed in time series to establish a crayfish behavioral state prediction model; A multidimensional matrix is ​​constructed, and the edge computing node fills the matrix elements in real time according to the behavior state prediction model and environmental parameter monitoring data to generate a real-time symbiotic environment state matrix.

4. The rice planting method based on intelligent regulation of shrimp-rice symbiosis according to claim 3, characterized in that: Generating a real-time symbiotic environment status matrix also includes: visually displaying the real-time symbiotic environment status matrix to intuitively present the field environmental status information of the shrimp-rice symbiosis.

5. The rice planting method based on intelligent regulation of shrimp-rice symbiosis according to claim 1, characterized in that: Establish an adaptation model between rice variety characteristics and crayfish growth cycle, including: Determine rice variety characteristics from sowing to maturity, including growth cycle, morphological characteristics, stress resistance, and nutrient requirements at each stage; Obtain data on the crayfish growth cycle, including the growth stages, environmental requirements, and behavioral habits of crayfish from juveniles to adults; Calculate the correlation coefficient between each rice variety characteristic index and the crayfish growth cycle index, compare the correlation coefficient with the preset correlation threshold, and screen out the key related indicators with correlation; An adaptation model framework is constructed based on key correlation indicators, and the adaptation model framework is trained and iteratively optimized based on historical data to generate a trained adaptation model of rice variety characteristics and crayfish growth cycle.

6. The rice planting method based on intelligent regulation of shrimp-rice symbiosis according to claim 1, characterized in that: The shrimp seedlings that grow at the same time as the selected rice variety are released into the fields, and the process also includes: grading the shrimp seedlings according to their size, and acclimatizing the graded shrimp seedlings in temporary holding ponds before release, with the acclimatization period being no less than 24 hours.

7. The rice planting method based on intelligent regulation of shrimp-rice symbiosis according to claim 1, characterized in that: Rice seedling cultivation based on factory-based rice seedling cultivation also includes: Rice variety screening: Collect information on common rice varieties from multiple regions and establish a preliminary variety library containing variety names and basic biological characteristics. The number of rice varieties collected in the preliminary variety library should be no less than 20; Plant all rice varieties in the preliminary variety library under the same planting conditions in the experimental field, simulate the shrimp-rice symbiotic environment, release a certain number of crayfish, and evaluate each rice variety in the preliminary variety library based on growth characteristic evaluation indicators at various stages of rice growth; Compare the assessment results with the preset assessment qualification threshold to select rice varieties that meet the growth characteristic assessment index requirements; Conduct stress tolerance tests on selected rice varieties. By artificially inoculating pests and diseases, the incidence and resistance of the rice varieties are observed. In the late growth period of rice, severe weather conditions such as strong winds are simulated to evaluate their lodging resistance. Based on the verification results, rice varieties with strong stress tolerance were screened out to form a final list of rice varieties suitable for shrimp-rice symbiosis.

8. The rice planting method based on intelligent regulation of shrimp-rice symbiosis according to claim 1, characterized in that: Transplanting the cultivated rice seedlings into the fields, including: Stress resistance induction treatment: spray the prepared crayfish metabolic simulation solution evenly when the first leaf of the seedling is fully expanded; Water flow disturbance simulation: Use an air pump to simulate the water flow disturbance caused by crayfish activities, and the disturbance treatment lasts for 6 hours every day until 3 days before transplanting; Transplanting path planning: Based on the distribution of field furrows and soil nutrient status, a spatial coordination model of crayfish activity paths and rice dense planting areas is established, and the transplanting path is optimized through edge computing nodes; Transplanting with rice transplanter: Transplanting is performed using a rice transplanter based on the optimized transplanting path.

9. The rice planting method based on intelligent regulation of shrimp-rice symbiosis according to claim 1, characterized in that: Develop corresponding shrimp-rice symbiotic regulation strategies, including: Based on the real-time symbiotic environmental state matrix, key environmental parameters corresponding to rice growth stages and crayfish behavioral states were extracted, and the thresholds of key environmental parameters under the coupling of rice growth stages and crayfish behavioral states were determined. Match the identified key environmental parameter thresholds to the corresponding control rules, and determine the priority of the control rules based on the impact of parameter anomalies on the shrimp-rice symbiosis system; Based on the comparison results between the control rules and real-time monitoring data, the control measures are automatically executed to achieve a dynamic balance in the shrimp-rice symbiotic environment, and real-time feedback is provided on the implementation effects of the control measures.

10. The rice planting method based on intelligent regulation of shrimp-rice symbiosis according to claim 9, characterized in that: Formulate corresponding shrimp-rice symbiotic regulation strategies, which also include: establishing the initial symbiotic environmental balance after transplanting the seedlings, maintaining the water level at a shallow water layer of 3-5 cm within 24 hours after transplanting the seedlings, and guiding crayfish to gather in the ditch area based on the water level difference between the field ditch and the ring ditch; tracking the activity trajectory of crayfish in real time, and when the frequency of a single crayfish entering the main planting area is greater than the preset frequency, oxygenating the ring ditch area.

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