A Smart Regulation Method for Precision Irrigation and Fertilization in Rice

Abstract

This invention relates to an intelligent regulation method for precise integrated water and fertilizer management in rice cultivation, belonging to the field of rice planting technology. The method includes precision sowing, intelligent high-density transplanting using BeiDou navigation, precise fertilization regulation, precise irrigation regulation, intelligent monitoring and green control of pests, diseases, and weeds, precise mechanical harvesting, and data-driven intelligent decision-making steps. Specifically, precise fertilization regulation combines side-deep fertilization with drone-based leaf-age topdressing; precise irrigation regulation is based on intelligent valves driven by both soil moisture and leaf age factors; pest and disease control constructs an intelligent monitoring and early warning system and a chemical-biological synergistic control system; and intelligent decision-making establishes a production digital model through data collection throughout the entire growth period to continuously optimize planting techniques. This achieves precise sowing and transplanting, intelligent water and fertilizer regulation, green pest and disease control, and standardized harvesting loss reduction, effectively improving nitrogen fertilizer utilization and irrigation water utilization efficiency, and reducing yield losses and chemical pesticide use due to pests, diseases, and weeds.

Description

Technical Field

[0001] This invention relates to the field of rice cultivation technology, specifically to an intelligent control method for precise integrated water and fertilizer management in rice cultivation. Background Technology

[0002] In traditional rice cultivation, water and fertilizer management relies heavily on manual experience, leading to inaccurate control of irrigation timing and volume, resulting in excessive irrigation, water waste, and negatively impacting rice root vitality. Fertilization is primarily done through broadcasting or surface application, resulting in low fertilizer utilization, particularly nitrogen fertilizer, which has a utilization rate of only about 40%. This not only increases planting costs but also contributes to soil and water pollution. Furthermore, traditional sowing methods rely heavily on manual labor or ordinary sowing equipment, leading to low precision in seed quantity control and widespread instances of missed or over-sown seeding. Transplanting operations depend on manual experience, resulting in large errors in plant spacing and a single, uniform planting pattern that cannot be adapted to different plot types. This leads to poor ventilation and light penetration in the field, uneven development of individual rice plants, and difficulty in unlocking the potential for increased yield. In addition, pest and weed control often relies on an experience-based approach of "killing insects and removing weeds as soon as they appear," lacking real-time monitoring and early warning mechanisms. This leads to inappropriate timing of control measures and excessive pesticide use. The large-scale use of chemical pesticides not only increases planting costs but also easily causes pesticide residues, increased pest resistance, and ecological damage. Harvesting relies heavily on manual experience to control timing and machinery parameters, while mechanical harvesting results in a loss rate exceeding 5%, leading to significant yield losses. The combined effect of these problems results in low resource utilization efficiency, high production costs, and increased environmental pressure in rice cultivation, making it difficult to meet the demands of modern agriculture for green, efficient, and sustainable development.

[0003] While existing technologies include precision seeders, Beidou-guided rice transplanters, integrated water and fertilizer systems, IoT monitoring equipment, and digital platforms, these are mostly used independently as single devices. They lack an integrated operational method encompassing precision seeding, navigation-integrated water and fertilizer management, green pest control, and intelligent decision-making. Furthermore, they lack parameterized standards for different rice varieties and plot types, resulting in low matching between water and fertilizer regulation and crop needs. Pest and disease monitoring data is disconnected from control plans, and biological and chemical control are not closely integrated. Digital platforms are only used for data storage and have not established digital models for rice production, hindering in-depth data application and precise decision-making. Therefore, there is an urgent need to construct a comprehensive, precise, and intelligent planting method suitable for large-scale rice cultivation. This method should achieve precision in seeding and transplanting, intelligent water and fertilizer regulation, green pest and weed control, and standardized harvest loss reduction through equipment matching, parameter quantification, intelligent management, and system integration. This will improve the quality of rice plantations, unlock yield potential, and meet the modern development needs of large-scale rice cultivation. Summary of the Invention

[0004] In order to solve the problems of the prior art, the present invention provides an intelligent regulation method for precise water and fertilizer integration in rice.

[0005] To solve the above-mentioned technical problems, the present invention is achieved through the following technical solution: 1. A method for intelligent regulation of precise water and fertilizer integration in rice, comprising precise fertilization regulation, wherein the precise fertilization regulation includes the following steps: S1: Side-deep application of base fertilizer: A side-deep fertilization device is added to the high-speed riding rice transplanter. During transplanting, the slow-release compound fertilizer base fertilizer is accurately applied to the field in one go. The fertilization position is 3-5cm to the side of the seedling and the depth is 5-7cm. The amount of base fertilizer applied accounts for 60%-70% of the total fertilizer amount. S2: Preparation before fertilization: Before fertilization, test the soil fertility of each plot. For plots with high fertility, reduce the amount of base fertilizer applied appropriately, and for plots with poor fertility, increase the amount of base fertilizer applied appropriately. S3: Leaf age diagnosis and determination of topdressing window period: The leaf age of rice in each area is monitored every 3 days to determine the 4th leaf stage from the top of the rice as the window period for topdressing of panicle fertilizer and the 2nd leaf stage from the top of the rice as the window period for topdressing of grain fertilizer; S4: Precision Topdressing with Drones: During the topdressing window, plant protection drones are used for topdressing operations. The drone flight path is planned according to the shape of the plot, and the droplet size is controlled to be 50-80μm with a drift rate of <5%. For panicle fertilizer, a combination of nitrogen and potassium fertilizer is used, and for granular fertilizer, a combination of fast-acting nitrogen fertilizer and zinc and boron micronutrients is used. The amount of topdressing applied accounts for 30%-40% of the total fertilizer amount. S5: Fertilizer effect monitoring: 10 days after topdressing, monitor the growth of rice and apply a small amount of fertilizer to weak seedling plots according to the seedling condition.

[0006] Preferably, the NPK ratio of the controlled-release compound fertilizer in step S1 is 15-15-15.

[0007] Preferably, in step S2, the amount of base fertilizer applied to high-fertility plots is reduced by 5%-15%, and the amount applied to low-fertility plots is increased by 5%-15%.

[0008] Preferably, in step S4, the ratio of nitrogen fertilizer to potassium fertilizer in the panicle fertilizer is 2:1, and the ratio of urea, zinc sulfate, mineral-derived boron-magnesium fertilizer or organic chelated boron in the granular fertilizer is 10:1:1.

[0009] Preferably, the method increases the nitrogen fertilizer utilization rate of rice from 40% to over 50%, and the irrigation water utilization coefficient is ≥0.85.

[0010] Preferably, it also includes precise irrigation regulation, which includes the following steps: A1: One soil moisture sensor and one leaf age monitoring point shall be set up for every 100 mu (6.7 hectares). The sensors shall be wirelessly connected to the farm's digital management and control platform to achieve real-time data transmission. A2: Set shallow-wet-dry intermittent irrigation thresholds according to different leaf age stages of rice: maintain a shallow water layer of 3-5cm during the greening stage; alternate between shallow and wet water during the tillering stage, with a water layer of 1-3cm, and replenish water when the soil moisture content drops to 70%-80%; maintain a shallow water layer of 5-7cm during the jointing and booting stage; maintain a shallow water layer of 3-5cm during the heading and flowering stage; alternate between shallow and wet water during the grain filling and grain filling stage; and gradually dry the soil during the yellow ripening stage. A3: The digital management platform automatically opens and closes smart valves in the field based on soil moisture content sensor monitoring data and leaf age monitoring results to achieve precise automatic irrigation; A4: Each irrigation area is assigned a dedicated person to conduct daily inspections and promptly address sensor malfunctions and valve leaks.

[0011] Preferably, the precise automatic irrigation described in step A3 further includes differentiated regulation based on land type: increasing the density of field drainage ditches in low-lying and flood-prone plots, and shortening the drying time in hilly and sandy loam plots; the digital management platform allows remote control via a mobile app, enabling manual intervention in irrigation operations.

[0012] Preferably, it also includes a data-driven intelligent decision-making step: B1: Connect agricultural operation data, seedling data, soil moisture data, pest and disease data, and yield data throughout the entire rice growth period to the farm's digital platform to achieve real-time data collection and storage; B2: Based on the collected multi-dimensional data and combined with the climate and soil conditions of the planting area, a digital model for rice production is established. The model includes the correlation between seedling condition, water and fertilizer, and yield. B3: The rice production digital model enables the transformation of planting decisions from manual experience-based judgment to data-supported decision-making, real-time prediction of field rice yield, and provides data basis for optimizing subsequent rice planting technical solutions.

[0013] Preferably, the yield prediction error of the rice production digital model is less than 5%.

[0014] Preferably, it also includes intelligent monitoring and green prevention and control steps for pests, diseases, and weeds: C1: Set up one IoT monitoring point for every 500 mu, and equip each monitoring point with an insect monitoring lamp, a spore trap and a field camera to monitor the main diseases and pests of rice blast, rice stem borer and rice planthopper in real time; C2: Monitoring data is synchronized to the digital management and control platform in real time. The platform establishes a pest and disease prediction model based on historical data and real-time monitoring data, and automatically generates pest and disease early warning information and precise prevention and control plans. C3: Establish a professional plant protection team, use large plant protection drones and self-propelled sprayers to carry out integrated prevention and control, select green agents according to the prevention and control plan, use kasugamycin or Bacillus subtilis for rice blast, and use Bacillus thuringiensis (Bt.) or spinosad for rice stem borer. C4: Plant 1 mu of flowering plants for every 10 mu around the rice paddies to conserve natural enemies; C5: After transplanting, maintain a shallow water layer of 3-5cm in the field for 7 days to induce weed seed germination. 5-7 days after transplanting, use a pre-emergence herbicide of bensulfuron-methyl and pretilachlor to spray evenly with a plant protection drone, with a droplet size of 40-60μm. During the tillering stage, conduct 1-2 field inspections to manually remove older weeds and clear weeds along field ridges and ditches.

[0015] The beneficial effects of this invention are as follows: 1. This invention achieves precise control of the number of seeds sown through parameterized adjustment of an air-suction precision seeder, reducing seed waste at the source and laying the foundation for cultivating strong seedlings. Building upon this, a Beidou navigation-assisted driving system is added to a high-speed riding rice transplanter, enabling standardized planning and high-precision positioning of the transplanting path. Combined with wide-narrow row planting patterns, row spacing parameters are set according to plot type differences, effectively improving field ventilation and light penetration, optimizing the rice population structure, and balancing individual development with overall population growth. In the fertilization stage, a side-deep fertilization device precisely applies controlled-release compound fertilizer to the root absorption zone on the side of the seedlings, achieving concentrated supply and long-term release of base fertilizer. Combined with soil fertility testing and dynamic adjustment of application rates before topdressing, and precise determination of the topdressing window using leaf age diagnosis technology, topdressing operations are carried out using plant protection drones, forming a precise fertilization process that coordinates base fertilizer and topdressing. In terms of irrigation, by deploying soil moisture sensors and leaf age monitoring points, and based on a shallow-wet-dry intermittent irrigation mode, a digital management platform automatically controls intelligent valves and implements differentiated regulation according to plot type to achieve on-demand water supply. Through the coordinated operation of the above-mentioned sowing, fertilization, and irrigation processes, this invention achieves efficient utilization of fertilizers and water, laying a good foundation for increased rice yield. 2. This invention utilizes IoT monitoring points equipped with insect monitoring lamps, spore traps, and field cameras to achieve real-time monitoring and data synchronization of major pests and diseases. Based on historical and real-time data, it establishes pest and disease prediction models, automatically generating early warning information and precise control plans. At the implementation level, it implements integrated pest management across contiguous areas, combining chemical and biological control. This is achieved by releasing natural enemy insects and planting flowering plants to cultivate natural enemies, thus constructing a natural control system. For weed control, a standardized process combining shallow water trapping, pre-emergence weeding, and manual re-weeding is adopted. Herbicides are adjusted according to the dominant weed species, forming a green control system that integrates chemical and biological control, and complements physical and agricultural control. In terms of loss reduction and quality improvement, a comprehensive lodging control system combining variety selection, cultivation regulation, and chemical regulation is constructed. Measures such as sun-drying the field to control seedling growth, optimizing the nitrogen-potassium ratio, and spraying lodging-resistant regulators enhance the lodging resistance of rice. During harvest, measures such as draining paddy water, adjusting machinery parameters, installing loss rate monitoring devices, conducting real-time inspections by designated personnel, and timely post-harvest drying achieve precise loss reduction. Based on this, this invention integrates agricultural operation data, seedling data, soil moisture data, pest and disease data, and yield data throughout the entire growth cycle into a digital platform, establishing a digital model of rice production containing multi-dimensional correlations. This model enables real-time yield prediction and analysis of the effects of technical measures, forming a closed loop of planting-data-optimization. This transforms planting decisions from experience-based judgments to data-supported, precise decisions, providing a scientific basis for the continuous optimization of subsequent planting plans and achieving iterative improvements in rice planting technology. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the control method of the present invention. Detailed Implementation

[0017] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0018] like Figure 1 This paper presents an intelligent regulation method for precise water and fertilizer integration in rice cultivation.

[0019] I. Intelligent Expansion and Efficiency Enhancement Configuration of High-Standard Farmland (a) Land consolidation and expansion 1. Site Planning Based on the topography of Puyang area, a land consolidation plan was formulated. Scattered small plots of land were consolidated into larger square plots of 10-15 mu (approximately 1.65-1.25 acres), and in this example, they were consolidated into larger square plots of about 12 mu (approximately 1.8 acres). The plan follows the principle of "square fields, straight ridges, interconnected roads, and linked ditches" to ensure a regular farmland layout that facilitates mechanized operations.

[0020] 2. Mechanized land leveling Large-scale land leveling machines were used for field leveling. The flatness error of the leveled plots was less than 3cm; in this embodiment, the flatness error was 2.5cm. Simultaneously, obstacles such as abandoned ridges, miscellaneous trees, and stones were removed to maximize the effective planting area. In this embodiment, land improvement increased the effective planting area by 1500 mu (approximately 100 hectares), improving land utilization by 8%.

[0021] 3. Land title confirmation and digital mapping After land consolidation is completed, satellite positioning technology is used to measure and confirm land rights for each plot, creating digital land maps that label the area, soil fertility, suitable planting varieties, and other information for each plot, which are then incorporated into the farm's digital platform management. In this embodiment, satellite positioning measurement and land rights confirmation are carried out on all the large plots after consolidation, creating digital land maps to achieve digital management and control of farmland.

[0022] (ii) Field facilities 1. Construction of farm roads To support the improved large fields, field roads were constructed, with main roads 4 meters wide and branch roads 3 meters wide. These roads were paved with gravel or cement to ensure smooth passage for large agricultural machinery (seeders, rice transplanters, and harvesters). The field roads covered all planted plots; in this embodiment, the total length of field roads constructed was 80 km, enabling full access for large agricultural machinery.

[0023] 2. Construction of drainage ditch system A three-tiered drainage system consisting of a main ditch, branch ditches, and furrow ditches was constructed. The main ditch is 80cm wide and 60cm deep, the branch ditches are 50cm wide and 40cm deep, and the furrow ditches are 30cm wide and 20cm deep. The drainage system is interconnected, enabling irrigation during droughts and drainage during floods. In this embodiment, the total length of the three-tiered drainage system is 120km, and the interconnected system improves irrigation and drainage efficiency by 50%.

[0024] 3. Repairing the field ridges The ridges of the merged large fields are repaired, with a ridge height of 30-40cm and a width of 20-30cm, ensuring they are firm and preventing water leakage and fertilizer runoff. In this embodiment, the ridges are 35cm high and 25cm wide, compacted with soil and covered with mulch to ensure they are firm and free from water leakage and fertilizer runoff.

[0025] (III) Intelligent System Configuration 1. Intelligent irrigation system configuration Each large plot of land is equipped with an independent intelligent irrigation system, featuring smart valves, integrated water and fertilizer applicators, and soil moisture sensors. The system is interconnected with the farm's digital management platform, enabling remote control via a mobile app and automatic, precise irrigation and fertilization. In this embodiment, over 1600 large plots are each equipped with one intelligent irrigation system, comprising 1600 smart valves, 1600 soil moisture sensors, and 1600 integrated water and fertilizer applicators. The system is interconnected with the farm's digital management platform and can be remotely controlled via a mobile app, increasing the irrigation water utilization coefficient to 0.88.

[0026] 2. Configuration of basic support facilities Power lines and 5G / 4G networks will be constructed to support field IoT monitoring points, smart valves, and drone take-off and landing sites, achieving full power coverage and high-speed data transmission to ensure the normal operation of intelligent equipment. In this embodiment, 50km of power lines will be constructed to achieve full power coverage of the planting area, and 20 5G base stations and 10 4G base stations will be deployed to achieve high-speed data transmission with a transmission latency of <3s.

[0027] 3. Configuration of agricultural machinery and supporting agricultural facilities The plan is to construct one large agricultural machinery warehouse and one rice drying center for every 5,000 mu of planting area, and one centralized dry seedling raising base for every 1,000 mu. Each area will also have at least one drone landing point to meet the agricultural needs of large-scale, mechanized rice cultivation. In this embodiment, four large agricultural machinery warehouses, four rice drying centers, 20 centralized dry seedling raising bases, and 20 drone landing points will be constructed to meet the needs of large-scale, mechanized rice cultivation on 20,000 mu of land.

[0028] 4. System integration and maintenance After all intelligent facilities were installed, a full system commissioning was conducted to ensure normal equipment operation and smooth data transmission. A regular maintenance system was established, with monthly inspections and maintenance of the intelligent equipment and field facilities to promptly address any malfunctions. In this example, after all facilities were installed, a full system commissioning was conducted, ensuring normal equipment operation and smooth data transmission. A maintenance system was established, with 20 professional personnel assigned to conduct monthly inspections and maintenance of the facilities, promptly addressing any equipment malfunctions.

[0029] II. Pre-sowing preparation and precision sowing (a) Preparations before sowing Japonica rice was selected as the planting variety. Before sowing, the seed suction nozzle of the air-suction precision seeder was adjusted, and a standard seed quantity of 5-6 seeds per hill was set. At the same time, a centralized dry seedling raising base was constructed, using a uniform seedling raising substrate (in this example, well-rotted rice husk substrate was used), and a three-layer film covering technology was adopted to control the temperature inside the seedling raising shed at 25-28℃ and the humidity at 70%-80% to cultivate strong seedlings.

[0030] (ii) Precision seeding A calibrated air-suction precision seeder was used for sowing operations at the dry seedling nursery. Within 24 hours of sowing, the missed sowing rate and over-sowing rate were measured in the field. In this example, the missed sowing rate was 0.8% and the over-sowing rate was 1.5%, meeting the standards of <1% and <2% for both. Unqualified areas were promptly re-sowed to ensure sowing quality.

[0031] III. BeiDou Navigation Debugging and Intelligent High-Density Rice Transplanting (I) BeiDou Navigation Debugging A Beidou navigation-assisted driving system was added to the high-speed riding rice transplanter, and the system was debugged to achieve a positioning accuracy of ≤1cm. In this embodiment, the positioning accuracy after debugging is 0.8cm. An electronic map of all plots in the planting area was imported, and standardized operation paths were planned according to the shape of the plots. In this embodiment, a round-trip operation path was planned for rectangular plots to ensure that the rice transplanting operation is not repeated or missed.

[0032] (II) Intelligent dense rice transplanting Rice seedlings are transplanted into the field when they reach a height of 15-20cm and have 3.5-4.5 leaves. In this embodiment, transplanting is carried out when the seedlings reach a height of 18cm and have 4 leaves, with the transplanting depth controlled at 1.8cm. The row spacing error is controlled by the Beidou navigation-assisted driving system to ensure it is less than 2cm; in this embodiment, the row spacing error is 1.5cm.

[0033] Rice seedlings are transplanted using a wide-narrow row planting pattern. In this example, the planting plot is a high-fertility plot, using a 30cm×15cm wide-narrow row dense planting pattern, with 5-7 seedlings per hole. The row spacing can be adjusted according to different plot types: for low-lying and high-fertility plots, the row spacing is slightly adjusted to 30cm×15cm; for hilly and poor-fertility plots, the row spacing is slightly adjusted to 30cm×17cm; the basic row spacing is 30cm×16cm.

[0034] (III) Post-transplanting inspection and replanting Within 72 hours of transplanting, the uniformity of seedling distribution per hill was checked in each plot, and drifting seedlings were removed. Deeply planted or missing seedlings were promptly replanted. In this example, the drifting seedling rate was 0.3% after 48 hours of transplanting. Missing seedlings were promptly replanted to ensure a uniform distribution of basic seedlings in the field.

[0035] IV. Precision Water and Fertilizer Integration Intelligent Regulation (I) Precision fertilization regulation 1. Apply base fertilizer by deep side application A side-deep fertilization device is added to the high-speed riding rice transplanter to precisely apply slow-release compound fertilizer as base fertilizer to the field in one go during transplanting. In this embodiment, the base fertilizer is a slow-release compound fertilizer with NPK=15-15-15, combined with commercial organic fertilizer and mineral-derived silicon fertilizer. The fertilization position is 3-5cm to the side of the seedling and 5-7cm deep, specifically 4cm to the side and 6cm deep. The base fertilizer accounts for 60%-70% of the total fertilizer amount. In this embodiment, the slow-release compound fertilizer accounts for 65% of the total fertilizer amount, the organic fertilizer application rate is 120 kg / mu, and the silicon fertilizer (calculated as SiO2) application rate is 8 kg / mu.

[0036] 2. Preparation and dynamic adjustment before fertilization Before fertilization, soil fertility was tested on a plot-by-plot basis, and the amount of base fertilizer applied was adjusted according to the test results. In this example, the amount of base fertilizer applied to highly fertile plots was reduced by 10%, and that to infertile plots was increased by 10%. The specific adjustment range was 5%-15%, and the adjustment ratio was determined based on the actual soil fertility test results.

[0037] 3. Leaf age diagnosis and determination of the topdressing window period A professional leaf age diagnosis team was established to monitor the leaf age of rice in each area every 3 days. In this example, the period from the top 4 leaves was determined to be June 20-25 (the window period for topdressing with panicle fertilizer), and the period from the top 2 leaves was determined to be July 15-20 (the window period for topdressing with grain fertilizer). The diagnosis results were uploaded to the digital management and control platform in real time.

[0038] 4. Precision fertilization by drone Topdressing operations were carried out using agricultural drones during the fertilization window. The drone flight path was planned according to the shape of the plot; in this embodiment, a checkerboard flight path was used. The droplet size was controlled to be 50-80 μm and the drift rate to be <5%; in this embodiment, the droplet size was 60 μm and the drift rate was 3%.

[0039] For the panicle fertilizer, a combination of nitrogen and potassium fertilizer is used. In this example, urea and potassium chloride are mixed in a 2:1 ratio. For the granulation fertilizer, a combination of fast-acting nitrogen fertilizer and zinc and boron micronutrients is used. In this example, urea, zinc sulfate, and mineral-derived boron-magnesium fertilizer are mixed in a 10:1:1 ratio.

[0040] Topdressing accounts for 30%-40% of the total fertilizer application; in this example, topdressing accounts for 35% of the total fertilizer application.

[0041] 5. Fertilizer effect monitoring and supplemental fertilization Ten days after topdressing, the growth of rice was monitored, and small amounts of fertilizer were applied to weak seedlings. In this example, ten days after topdressing, the rice seedlings were found to be healthy, with weak seedlings accounting for less than 2%. Small amounts of fertilizer were then applied to these weak seedlings to ensure uniform growth.

[0042] In this embodiment, the nitrogen fertilizer utilization rate was increased to 52%, which is 12 percentage points higher than that of traditional fertilization.

[0043] (II) Precision Irrigation Regulation 1. Deployment of monitoring equipment In rice paddies, one soil moisture sensor and one leaf age monitoring point are deployed for every 100 mu (approximately 6.7 hectares). In this embodiment, 10 soil moisture sensors and 10 leaf age monitoring points are deployed in 1000 mu (approximately 67 hectares) of rice paddies. The sensors are wirelessly connected to the farm's digital management platform to achieve real-time data transmission with a data transmission delay of less than 5 seconds.

[0044] 2. Irrigation threshold setting Set shallow-wet-dry intermittent irrigation thresholds based on different leaf age stages of rice: During the greening period: maintain a shallow water layer of 3-5cm; in this example, the water layer is 4cm. Tillering stage: alternating between shallow and wet conditions, with a water layer of 1-3cm. Water should be added when the soil moisture content reaches 70%-80%. In this example, water should be added when the water layer is 2cm and the soil moisture content is 75%. During the jointing and heading stage: maintain a shallow water layer of 5-7cm; in this example, the water layer is 6cm. During the heading and flowering stage: maintain a shallow water layer of 3-5cm, and in this embodiment, the water layer is 4cm; Grouting and setting period: alternating between shallow and wet conditions; Yellow ripening stage: Gradually dry.

[0045] 3. Intelligent irrigation execution The digital management platform automatically switches on and off smart valves in the field based on soil moisture content sensor data and leaf age monitoring results, achieving precise and automatic irrigation. Simultaneously, differentiated adjustments are made according to plot type: drainage ditches are densified in low-lying, flood-prone plots; in this embodiment, drainage ditches are densified to one every 5 meters in low-lying plots; drying time is shortened in hilly and sandy loam plots; in this embodiment, drying time in hilly plots is shortened from 7 days to 5 days.

[0046] The digital management platform allows remote control via a mobile app, enabling staff to monitor irrigation status in real time and manually intervene in irrigation operations during extreme weather.

[0047] 4. Irrigation Inspection Each irrigation area is assigned a dedicated person for daily inspections to promptly address issues such as sensor malfunctions and valve leaks. In this example, five inspectors are assigned, each responsible for a 200-mu (approximately 33 hectares) area. They inspect sensors and valves daily, promptly addressing one valve leak issue to ensure accurate implementation of irrigation commands.

[0048] In this embodiment, the irrigation water utilization rate is increased to over 0.85, saving 30% of water resources.

[0049] V. Intelligent Monitoring and Green Control of Diseases, Pests, and Weeds (I) Intelligent monitoring and early warning 1. Monitoring point deployment In large-scale rice planting areas, one IoT monitoring point is set up for every 500 mu (approximately 33 hectares). In this embodiment, 10 IoT monitoring points are set up in a 5,000 mu (approximately 333 hectares) planting area. Each monitoring point is equipped with an insect monitoring lamp, a spore trap, and a high-definition field camera to achieve real-time monitoring of major pests and diseases such as rice blast, rice stem borer, and rice planthopper around the clock.

[0050] 2. Data transmission and model establishment Monitoring data is synchronized to the digital management and control platform in real time via a 5G network; in this embodiment, the transmission latency is less than 3 seconds. The platform establishes a pest and disease prediction model based on historical pest and disease data from the past five years and real-time monitoring data.

[0051] 3. Intelligent Early Warning and Solution Generation The digital management platform automatically generates pest and disease early warning information and precise control plans through pest and disease prediction models. In this example, the platform detected a sharp increase in the number of adult rice stem borers in mid-June, automatically issued a rice stem borer early warning information, and generated a control plan: spray with chlorantraniliprole at a dilution of 1500 times from June 20th to June 22nd, use plant protection drones for large-scale control, and push the plan to the 10 area control leaders.

[0052] (II) Green Control of Diseases and Pests 1. Organizations for unified defense and control A professional plant protection team was formed, and large-scale plant protection drones and self-propelled sprayers were used for integrated pest management. In this embodiment, a professional plant protection team of 5 people was formed, equipped with 3 large-scale plant protection drones and 2 self-propelled sprayers.

[0053] 2. Chemical control According to the control plan, green pesticides were selected: for rice blast, kasugamycin or Bacillus subtilis were used; for rice stem borer, Bacillus thuringiensis (Bt.) or spinosad were used. Strict control of pesticide concentration and frequency was maintained to avoid indiscriminate application. In this example, Bacillus thuringiensis (8000 IU / µL) at 200 ml / acre was used for spraying, requiring only one application throughout the entire treatment.

[0054] 3. Biological control Planting flowering plants around rice paddies helps to cultivate natural enemies, with 1 mu (approximately 0.067 hectares) of flowering plants planted for every 10 mu (approximately 0.67 hectares) of rice paddy. In this example, cosmos and sesame are planted to cultivate natural enemies such as frogs, spiders, and parasitic wasps, thus constructing a natural control system.

[0055] 4. Monitoring the effectiveness of prevention and control Seven days after treatment, the efficacy of pest and disease control was monitored in each area. Areas with an efficacy rate below 85% were promptly treated with supplementary measures. In this example, monitoring seven days after treatment showed that the efficacy against rice stem borer reached 92%, requiring no supplementary treatment. The efficacy against rice blast, rice planthopper, and other pests and diseases throughout the entire growth period was ≥88%.

[0056] (III) Green control of weeds 1. Shallow water trapping After rice transplanting, the paddy field is kept at a shallow water level of 3-5 cm for 7 days to induce weed seed germination. In this example, the water level was kept at 4 cm for 7 days after transplanting, and the weed seed germination rate reached over 90%.

[0057] 2. Pre-emergence weed control Five to seven days after transplanting, a pre-emergence herbicide mixture of bensulfuron-methyl and pretilachlor is applied and sprayed evenly using a plant protection drone for soil sealing. The drone's droplet size is 40-60 μm, ensuring uniform spraying without any blind spots. In this example, pre-emergence weeding is performed six days after transplanting, with a droplet size of 50 μm, ensuring uniform spraying without any blind spots.

[0058] 3. Manual repair During the rice tillering stage, conduct 1-2 field inspections, manually remove any older weeds that have been missed, and clear weeds along field ridges and ditches to cut off the source of weed spread. In this example, two field inspections are conducted during the tillering stage, with 20 staff members manually removing older weeds and clearing weeds along field ridges and ditches.

[0059] 4. Differentiated weed control Based on the dominant weed species in the paddy fields of the planting area, the type of pre-emergent herbicide is appropriately adjusted to avoid the development of herbicide resistance in weeds. In this example, for some plots where barnyard grass is the dominant weed, the herbicide is adjusted to bensulfuron-methyl + cyhalofop-butyl, achieving a weed control effect of over 95%.

[0060] In this embodiment, the yield loss rate caused by rice diseases, pests and weeds was controlled at 2.5%, which is 4 percentage points lower than traditional control methods, and the amount of chemical pesticides used was reduced by 30%.

[0061] VI. Loss Reduction and Quality Improvement and Intelligent Decision-Making (I) Loss Reduction, Quality Improvement, and Prevention 1. Selection of lodging-resistant varieties Lodging-resistant rice varieties suitable for the soil and climate conditions of the planting area were selected, characterized by robust stems, short internodes, well-developed root systems, and moderate plant height. In this example, a lodging-resistant japonica rice variety with robust stems and short internodes was selected.

[0062] 2. Cultivation regulation to prevent lodging At the end of the rice tillering stage, when the number of seedlings reaches 80% of the expected number of panicles, the field is dried to control seedling growth. The field is dried until the surface cracks and white roots are exposed, which lasts for 7-10 days. In this example, the drying and seedling control lasts for 8 days.

[0063] During fertilization, nitrogen fertilizer application should be controlled while potassium fertilizer application should be increased, accounting for 20%-30% of the total fertilizer application. This promotes lignification of rice stems and enhances lodging resistance. In this example, potassium fertilizer accounts for 25% of the total fertilizer application.

[0064] 3. Chemical regulation to prevent lodging During the jointing stage of rice, paclobutrazol or uniconazole lodging regulators are sprayed according to the field seedling condition at a concentration of 150-200 mg / L to control rice plant height and shorten the length of basal internodes. In this example, paclobutrazol lodging regulator at a concentration of 180 mg / L was sprayed, resulting in a 10 cm reduction in rice plant height and a 2 cm shortening of basal internodes after spraying.

[0065] 4. Seedling condition monitoring Rice seedling growth was monitored every 5 days, and control measures were adjusted promptly to ensure robust rice growth. In this example, seedling growth was monitored every 5 days, and the rice grew vigorously without lodging.

[0066] (ii) Precision mechanical harvesting 1. Pre-harvest preparations Ten to fifteen days before rice harvest, the paddy fields are drained to ensure a firm surface and prevent harvesters from getting stuck or crushing the rice plants. In this example, the fields are drained 12 days before harvest, achieving a surface firmness of over 80%. Obstacles such as stones and wooden stakes are checked in advance, and harvester paths are planned according to the shape of the plots. In this example, a reciprocating path is planned for rectangular plots.

[0067] 2. Mechanical debugging and harvest High-performance combine harvesters (such as Kubota and Yanmar series) were selected, and loss rate monitoring devices were installed on the harvesters. Before harvesting, the machinery was adjusted, controlling the header height to 5-10 cm and the operating speed to 2-3 km / h. The threshing drum speed was adjusted according to the characteristics of the rice variety to ensure thorough threshing and no grain breakage. In this example, 20 Kubota high-performance combine harvesters were selected, each equipped with a loss rate monitoring device. During harvesting, the header height was 7 cm, the operating speed was 2.5 km / h, and the threshing drum speed was 800 r / min.

[0068] 3. Harvesting process control Dedicated personnel were assigned to patrol the harvesters and monitor the harvest loss rate in real time. If the loss rate exceeded 3%, the machine was immediately stopped and the mechanical parameters were adjusted. In this example, 40 patrol personnel were assigned, each accompanying one harvester to monitor the loss rate in real time. If the loss rate of one harvester reached 3.2%, it was immediately stopped and the parameters were adjusted. After adjustment, the loss rate was reduced to 2.8%.

[0069] 4. Postpartum care and protection Within 24 hours of harvest, the rice is threshed and cleaned, and the moisture content is reduced to 13%-14% using a dryer or natural sun-drying to prevent mold and sprouting, thus reducing post-harvest losses. In this embodiment, threshing and cleaning are completed within 20 hours of harvest, and the moisture content of the rice is reduced to 13.5% using a dryer, with no mold or sprouting occurring.

[0070] In this embodiment, the loss rate of rice harvesting by machinery is controlled at 2.7%, which is 2.5 percentage points lower than that of traditional harvesting.

[0071] (III) Data-driven intelligent decision-making 1. Data collection throughout the entire reproductive period Throughout the entire rice growing season, including sowing, transplanting, irrigation, fertilization, pest control, and harvesting, all agricultural operation data, seedling condition data, soil moisture data, pest and disease data, and yield data are integrated into the farm's digital platform for real-time data collection and storage. In this embodiment, over 20 data items, including seed quantity, transplanting row spacing, irrigation water volume, fertilizer application, pest and disease control measures, and harvest loss rate, are collected and integrated into the farm's digital platform, achieving 100% data collection coverage.

[0072] 2. Establishment of a digital model for rice production Based on the collected multi-dimensional data and combined with the climate and soil conditions of the planting area, a digital model for rice production is established. In this embodiment, the model includes the correlation between seedling condition, water and fertilizer, and yield, as well as the correlation between pest and disease occurrence, control, and losses, enabling multi-dimensional data correlation analysis.

[0073] 3. Intelligent decision-making and technology optimization By using a digital model for rice production, planting decisions are shifted from manual experience-based judgment to data-driven support, enabling real-time prediction of rice yield per unit area. Simultaneously, the yield-increasing and loss-reducing efficiencies of various cultivation techniques are analyzed, providing data support for optimizing subsequent rice planting techniques and forming a closed loop of "planting-data-optimization." In this embodiment, the digital model predicts rice yield per unit area in real time with a prediction error of <5%. Analysis of the effects of various techniques reveals that the 30cm×15cm wide-narrow row dense planting pattern has a significant yield-increasing effect and has been identified as the primary dense planting pattern for the following year. Furthermore, the application rate of potassium fertilizer has been optimized, determining the optimal application rate to be 26% of the total fertilizer amount.

[0074] The following technical effects were achieved through the implementation of the above embodiments: Farmland expansion and efficiency improvement: Small plots of land are merged into larger plots of about 12 mu (approximately 1.8 hectares), increasing the effective planting area by 8% and improving field operation efficiency by 60%; Improved sowing precision: The missed sowing rate is 0.8% and the over-sowing rate is 1.5%, significantly improving sowing precision and reducing seed waste; Standardized rice transplanting: Beidou navigation positioning accuracy is 0.8cm, row spacing error is 1.5cm, achieving standardization of rice transplanting operations; Fertilizer utilization rate improved: Nitrogen fertilizer utilization rate increased from 40% to 52%, an increase of 12 percentage points; Water conservation: Irrigation water utilization rate increased to over 0.85, saving 30% of water resources; Significant effects in the control of diseases, pests, and weeds: disease and pest control efficacy ≥88%, weed control efficacy ≥95%, yield loss rate controlled at 2.5%, and chemical pesticide use reduced by 30%; Harvest loss reduction: The mechanical harvesting loss rate is controlled at 2.7%, which is 2.5 percentage points lower than that of traditional harvesting; Intelligent decision-making: The yield prediction error is less than 5%, and the technical solution is continuously optimized. It is expected that the yield of rice per unit area will increase by more than 8% in the next year.

[0075] This embodiment fully demonstrates that the intelligent expansion and efficiency enhancement configuration method and supporting planting technology for high-standard rice farmland provided by the present invention realizes the integrated configuration of "field, water, road, forest, machinery, electricity and intelligence", laying a hardware foundation for large-scale, precise and intelligent rice planting, effectively improving water and fertilizer utilization efficiency, reducing losses from pests and weeds, reducing the use of chemical pesticides, realizing green and efficient rice planting, and adapting to the needs of large-scale rice planting.

[0076] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for intelligent regulation of precise water and fertilizer integration in rice cultivation, characterized in that, This includes precise fertilization regulation, which comprises the following steps: S1: Side-deep application of base fertilizer: A side-deep fertilization device is added to the high-speed riding rice transplanter. During transplanting, the slow-release compound fertilizer base fertilizer is accurately applied to the field in one go. The fertilization position is 3-5cm to the side of the seedling and the depth is 5-7cm. The amount of base fertilizer applied accounts for 60%-70% of the total fertilizer amount. S2: Preparation before fertilization: Before fertilization, test the soil fertility of each plot. For plots with high fertility, reduce the amount of base fertilizer applied appropriately, and for plots with poor fertility, increase the amount of base fertilizer applied appropriately. S3: Leaf age diagnosis and determination of topdressing window period: The leaf age of rice in each area is monitored every 3 days to determine the 4th leaf stage from the top of the rice as the window period for topdressing of panicle fertilizer and the 2nd leaf stage from the top of the rice as the window period for topdressing of grain fertilizer; S4: Precision Topdressing with Drones: During the topdressing window, plant protection drones are used for topdressing operations. The drone flight path is planned according to the shape of the plot, and the droplet size is controlled to be 50-80μm with a drift rate of <5%. For panicle fertilizer, a combination of nitrogen and potassium fertilizer is used, and for granular fertilizer, a combination of fast-acting nitrogen fertilizer and zinc and boron micronutrients is used. The amount of topdressing applied accounts for 30%-40% of the total fertilizer amount. S5: Fertilizer effect monitoring: 10 days after topdressing, monitor the growth of rice and apply a small amount of fertilizer to weak seedling plots according to the seedling condition.

2. The intelligent regulation method for precise water and fertilizer integration in rice according to claim 1, characterized in that, The NPK ratio of the controlled-release compound fertilizer mentioned in step S1 is 15-15-15.

3. The intelligent regulation method for precise water and fertilizer integration in rice according to claim 1, characterized in that, In step S2, the amount of base fertilizer applied to high-fertility plots is reduced by 5%-15%, while that applied to low-fertility plots is increased by 5%-15%.

4. The intelligent regulation method for precise water and fertilizer integration in rice according to claim 1, characterized in that, In step S4, the ratio of nitrogen fertilizer to potassium fertilizer in the panicle fertilizer is 2:1, and the ratio of urea, zinc sulfate, mineral-derived boron-magnesium fertilizer or organic chelated boron in the granular fertilizer is 10:1:

1.

5. The intelligent regulation method for precise water and fertilizer integration in rice according to claim 1, characterized in that, The method improves the nitrogen fertilizer utilization rate of rice from 40% to over 50%, and the irrigation water utilization coefficient is ≥0.

85.

6. The intelligent regulation method for precise water and fertilizer integration in rice according to claim 1, characterized in that: It also includes precision irrigation regulation, which includes the following steps: A1: One soil moisture sensor and one leaf age monitoring point shall be set up for every 100 mu (6.7 hectares). The sensors shall be wirelessly connected to the farm's digital management and control platform to achieve real-time data transmission. A2: Set shallow-wet-dry intermittent irrigation thresholds according to different leaf age stages of rice: maintain a shallow water layer of 3-5cm during the greening stage; alternate between shallow and wet water during the tillering stage, with a water layer of 1-3cm, and replenish water when the soil moisture content drops to 70%-80%; maintain a shallow water layer of 5-7cm during the jointing and booting stage; maintain a shallow water layer of 3-5cm during the heading and flowering stage; alternate between shallow and wet water during the grain filling and grain filling stage; and gradually dry the soil during the yellow ripening stage. A3: The digital management platform automatically opens and closes smart valves in the field based on soil moisture content sensor monitoring data and leaf age monitoring results to achieve precise automatic irrigation; A4: Each irrigation area is assigned a dedicated person to conduct daily inspections and promptly address sensor malfunctions and valve leaks.

7. The intelligent regulation method for precise water and fertilizer integration in rice according to claim 6, characterized in that: Step A3: The precision automatic irrigation also includes differentiated regulation based on land type: increasing the density of field drainage ditches in low-lying and flood-prone plots, and shortening the drying time in hilly and sandy loam plots; The digital management platform allows remote control via a mobile app, enabling manual intervention in irrigation operations.

8. A method for intelligent regulation of precise water and fertilizer integration in rice according to claim 1 or 6, characterized in that: It also includes data-driven intelligent decision-making steps: B1: Connect agricultural operation data, seedling data, soil moisture data, pest and disease data, and yield data throughout the entire rice growth period to the farm's digital platform to achieve real-time data collection and storage; B2: Based on the collected multi-dimensional data and combined with the climate and soil conditions of the planting area, a digital model for rice production is established. The model includes the correlation between seedling condition, water and fertilizer, and yield. B3: The rice production digital model enables the transformation of planting decisions from manual experience-based judgment to data-supported decision-making, real-time prediction of field rice yield, and provides data basis for optimizing subsequent rice planting technical solutions.

9. The intelligent regulation method for precise water and fertilizer integration in rice according to claim 8, characterized in that: The yield prediction error of the digital model for rice production is less than 5%.

10. A method for intelligent regulation of precise water and fertilizer integration in rice according to claim 1 or 6, characterized in that: It also includes intelligent monitoring and green prevention and control measures for pests, diseases, and weeds: C1: Set up one IoT monitoring point for every 500 mu, and equip each monitoring point with an insect monitoring lamp, a spore trap and a field camera to monitor the main diseases and pests of rice blast, rice stem borer and rice planthopper in real time; C2: Monitoring data is synchronized to the digital management and control platform in real time. The platform establishes a pest and disease prediction model based on historical data and real-time monitoring data, and automatically generates pest and disease early warning information and precise prevention and control plans. C3: Establish a professional plant protection team, use large plant protection drones and self-propelled sprayers to carry out integrated prevention and control, select green agents according to the prevention and control plan, use kasugamycin or Bacillus subtilis for rice blast, and use Bacillus thuringiensis (Bt.) or spinosad for rice stem borer. C4: Plant 1 mu of flowering plants for every 10 mu around the rice paddies to conserve natural enemies; C5: After transplanting, maintain a shallow water layer of 3-5cm in the field for 7 days to induce weed seed germination. 5-7 days after transplanting, use a pre-emergence herbicide of bensulfuron-methyl and pretilachlor to spray evenly with a plant protection drone, with a droplet size of 40-60μm. During the tillering stage, conduct 1-2 field inspections to manually remove older weeds and clear weeds along field ridges and ditches.

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