A quantitative pesticide spraying system and method for standardized planting of traditional Chinese medicinal materials

Abstract

The present application relates to the technical field of agricultural intelligent irrigation and precise pesticide application, and discloses a quantitative pesticide spraying system and method for standardized planting of traditional Chinese medicinal materials. A coordinate system and an equidistant sampling grid are established on the surface of a field, a capacitive soil humidity sensor is laid out and calibrated, real-time voltage data is accurately converted into the soil water content of the grid nodes, and four-point bilinear interpolation is used to realize the acquisition of the soil water distribution of the continuous field in the field. Based on the node difference calculation, the water content spatial gradient and the average gradient of the whole field are calculated, the area is divided according to the number of nozzles, the regional boundary is dynamically adjusted to ensure the data validity, and the average gradient of each area is extracted. Combined with the unit area pesticide spraying demand and the coverage area, the basic pesticide spraying volume is obtained, the adjustment factor is generated by linear mapping of the regional gradient and the global extreme value, the pesticide spraying volume is differentiated and controlled, and the boundary clamping is implemented, and finally the opening time is calculated according to the spraying speed, and the controller executes the operation in sequence.

Description

Technical Field

[0001] This invention relates to the field of intelligent irrigation and precision pesticide application technology in agriculture, specifically a quantitative spraying system and method for standardized cultivation of Chinese medicinal herbs. Background Technology

[0002] In modern Chinese medicinal herb cultivation and production, soil moisture conditions directly affect crop growth and development, pest and disease control, and the accumulation of medicinal components. With the development of large-scale and intensive Chinese medicinal herb cultivation, higher demands are placed on the precision and efficiency of spraying operations. Traditional spraying techniques generally employ timed and quantitative methods or manual, experience-based operations, often failing to fully consider the spatial heterogeneity of soil moisture distribution within the field and the dynamic changes in the crop root zone environment. This leads to problems such as low pesticide and water utilization efficiency, uneven crop growth, and environmental pollution.

[0003] Existing spraying systems mostly rely on mechanical quantitative control or simple manual adjustment, lacking the ability to perceive the field's microenvironment in real time and to apply pesticides in a targeted manner. For example, some traditional solutions rely solely on weather stations or single-point soil moisture sensors to obtain regional average data and set the total spray volume accordingly, making it difficult to cope with the subtle but crucial gradient changes in soil moisture along spatial dimensions. While some semi-automatic spraying devices are equipped with basic sensors, they often rely on simple threshold judgments and coarse on / off control, lacking a quantitative control mechanism fully coupled with spatial data, and rarely possessing the ability to independently adjust the spray volume for different spraying zones. Furthermore, when dealing with high-value crops such as medicinal herbs, traditional systems struggle to adapt to the complex needs of multiple varieties, different plots, and variable environments, easily leading to localized over-spraying or under-spraying, which affects the quality of the herbs and exacerbates the pressure on pesticide safety and environmental protection.

[0004] Therefore, this case aims to propose a quantitative spraying system and method for standardized cultivation of Chinese medicinal herbs. The system digitizes the field into a two-dimensional coordinate system, collects soil moisture content at multiple points in real time based on gridded soil moisture sensors, constructs a continuous moisture distribution using interpolation algorithms, and then extracts soil moisture change characteristics through spatial gradient analysis to guide the spraying volume of nozzles in different areas. Summary of the Invention

[0005] This invention provides a quantitative spraying system and method for standardized cultivation of Chinese medicinal herbs, which helps to solve the problems mentioned in the background art.

[0006] This invention provides the following technical solution: a quantitative spraying method for standardized cultivation of Chinese medicinal herbs, comprising:

[0007] Establish a plane rectangular coordinate system on the field surface, construct an equally spaced sampling grid, pre-embed capacitive soil moisture sensors, complete two-point calibration and set feasible upper and lower limits for moisture content, and convert the real-time voltage into the moisture content of each grid node according to the calibration relationship.

[0008] Based on the sensor sampling matrix, four-point bilinear interpolation is performed on any coordinate point according to the grid step to obtain the soil moisture content distribution in the continuous field;

[0009] The horizontal and vertical differences are calculated at each grid node to obtain the spatial gradient components and gradient modulus of water content, and the average gradient modulus of the whole field is obtained.

[0010] Based on the number of nozzles, the field is divided into several rectangular spraying areas. Nodes in each area are collected, and when the nodes are empty, the area boundary is aligned with the grid line and then reprojected to extract the average gradient of each area.

[0011] Obtain the required spray volume per unit area, calculate the coverage area of ​​each nozzle, and obtain the basic spray volume.

[0012] Using the minimum and maximum average gradients of the entire field as endpoints, a linear mapping is performed on the average gradients of each region to generate the spray volume adjustment factor.

[0013] The final spray volume is obtained by multiplying the base volume of each nozzle by the corresponding adjustment factor, and the final spray volume is then bounded.

[0014] The controller obtains the maximum spray speed limit and actual spray speed of each nozzle, calculates the activation time, executes the commands sequentially, and records the basic volume, final volume and activation time according to the nozzle number, generating a spraying report that includes regional gradient, spray volume and execution time.

[0015] Optionally, the step of establishing a planar rectangular coordinate system on the field surface, constructing an equally spaced sampling grid, pre-embedding a capacitive soil moisture sensor, completing two-point calibration and setting feasible upper and lower limits for moisture content, and converting the real-time voltage into the moisture content of each grid node according to the calibration relationship, specifically includes:

[0016] Establish a plane rectangular coordinate system on the surface of the Chinese medicinal herb planting field, with the origin set at any vertex, the horizontal axis along the long side, and the vertical axis along the short side;

[0017] The surface of the medicinal herb planting field is a rectangular area, and the length of the longer side is greater than the length of the shorter side;

[0018] No fewer than two sampling lines are laid out horizontally, and no fewer than two sampling points are laid out vertically on each sampling line. Capacitive soil moisture sensors of equal depth are pre-embedded at all intersections and numbered.

[0019] The voltages of each sensor were collected under two sets of known standard moisture content conditions, and the conversion slope and intercept of each sensor were obtained according to the two-point calibration principle.

[0020] The real-time voltage is converted into water content based on the slope and intercept, and then bounded by a lower and upper bound within the feasible range of zero to 100%, forming a water content sequence for each grid node.

[0021] Optionally, the step of obtaining the soil moisture content distribution of the continuous field by performing four-point bilinear interpolation on any coordinate point according to the grid step size based on the sensor sampling matrix specifically includes:

[0022] Organize the moisture content of all nodes into a two-dimensional sampling matrix by rows and columns;

[0023] The grid spacing is determined based on the total horizontal and vertical length of the field and the number of samples.

[0024] For any coordinate point, locate the bottom left corner grid index of its cell and calculate the normalized relative position coefficients of the point in the horizontal and vertical directions.

[0025] Using the moisture content of the four corner nodes of the unit and the relative position coefficient as weights, four-point bilinear interpolation is performed to obtain the continuous field moisture content of the coordinate point.

[0026] Optionally, the step of calculating the lateral and longitudinal differences at each grid node to obtain the spatial gradient components and gradient modulus of water content, and then calculating the average gradient modulus of the entire field, specifically includes:

[0027] For non-boundary nodes, central difference is applied in both the horizontal and vertical directions to obtain gradient components in two directions;

[0028] One-sided difference is applied to nodes located on the four boundaries to obtain gradient components in two directions;

[0029] The gradient magnitude of each node is obtained using the gradient components in both directions;

[0030] The average gradient magnitude of all nodes is taken to obtain the average gradient magnitude of the entire field.

[0031] Optionally, the process of dividing the field into several rectangular spraying areas based on the number of sprinklers, collecting nodes within each area, aligning the area boundaries with the grid lines when nodes are empty, reprojecting, and extracting the average gradient of each area specifically includes:

[0032] Establish corresponding rectangular spraying areas according to the number of nozzles and number them, and set the horizontal and vertical lower and upper boundaries of each area;

[0033] Collect grid nodes located within the boundaries of each region and count the number of nodes;

[0034] When the number of nodes in a region is zero, align the boundary of the region with the nearest grid line and project it inward or outward until it contains at least one node.

[0035] Calculate the average value of the node gradient magnitude in each region.

[0036] Optionally, obtaining the required spray volume per unit area, calculating the coverage area of ​​each nozzle, and obtaining the basic spray volume specifically includes:

[0037] Obtain the required spray volume per unit area;

[0038] The coverage area is calculated based on the difference in the lateral and longitudinal boundaries of the rectangular area corresponding to each nozzle.

[0039] Multiply the coverage area by the required spray volume per unit area to obtain the basic spray volume for each nozzle.

[0040] Optionally, the step of performing a linear mapping on the average gradient of each region using the minimum and maximum average gradients of the entire field as endpoints to generate a spray volume adjustment factor specifically includes:

[0041] Obtain the minimum and maximum values ​​of the average gradient in each region of the entire field.

[0042] The average gradient of each target region is linearly mapped to its minimum and maximum values ​​to generate the spray volume adjustment factor.

[0043] When the minimum value equals the maximum value, the spray volume adjustment factor for all regions is uniformly set to one.

[0044] Optionally, the step of multiplying the base volume of each nozzle by the corresponding adjustment factor to obtain the final spray volume, and then subjecting the obtained final spray volume to boundary clamping, specifically includes:

[0045] Multiply the base spray volume of each nozzle by the corresponding spray volume adjustment factor to obtain the final spray volume;

[0046] Set the minimum spray volume to 0.8 times the base volume and the maximum spray volume to 1.5 times the base volume for each nozzle.

[0047] The final spray volume is clamped according to the minimum and maximum spray volume to obtain the clamped spray volume.

[0048] Optionally, the process of obtaining the maximum spray speed limit and actual spray speed of each nozzle, calculating the activation duration, and the controller executing these steps sequentially, while recording the basic volume, final volume, and activation duration according to the nozzle number, generates a spraying report containing regional gradient, spray volume, and execution time. Specifically, this includes:

[0049] Obtain the maximum allowable spray speed limit for each nozzle and the actual spray speed selected during execution;

[0050] The opening time of each nozzle is calculated based on the final spray volume and the actual spray speed.

[0051] The controller turns each nozzle on and off sequentially according to its number, and performs the operation according to its respective operating duration.

[0052] Save the basic spray volume, final spray volume, and operation duration records by nozzle number;

[0053] Automatically generate spraying reports, specifying the moisture content gradient of each area, spraying volume, and execution time.

[0054] A system for implementing a quantitative spraying method for standardized cultivation of the aforementioned Chinese medicinal herbs, comprising:

[0055] The field modeling unit performs coordinate establishment and area limitation.

[0056] The sampling and acquisition unit is connected to the capacitive soil moisture sensor to perform two-point calibration and real-time sampling conversion;

[0057] The distribution building unit performs four-point bilinear interpolation and outputs a continuous moisture content distribution.

[0058] The gradient calculation unit performs difference calculations and statistical analysis of the average gradient of the entire field.

[0059] The region is divided into units, spraying areas are established, and boundary alignment and node reprojection are performed.

[0060] The baseline volume calculation unit performs coverage area calculation and basic spray volume generation.

[0061] The response factor calculation unit performs global extremum acquisition and linear mapping.

[0062] The spray volume determination unit performs volume calculation and clamping.

[0063] The execution control unit is connected to the nozzle array and performs spray speed setting and on-time control.

[0064] The information recording unit archives the operation data and generates a spraying report.

[0065] The present invention has the following beneficial effects:

[0066] 1. A Cartesian coordinate system was established on the surface of the medicinal herb planting field. Capacitive soil moisture sensors were then deployed within this coordinate system at equal intervals. Voltage readings were collected at two standard moisture content points to accurately calibrate the sensors and set the upper and lower limits of their effective domain. Deeply integrating the field Cartesian coordinate system with the sensor network ensured the spatial organization of data acquisition and simplified the subsequent interpolation and region division calculation models. Simultaneously, a two-point calibration method was used to correct the conversion relationship between voltage and moisture content, and feasible domain boundaries were set to avoid measurement distortion caused by sensor drift or extreme values.

[0067] 2. Based on the calibrated sensor sampling matrix, bilinear interpolation is performed on any field coordinate point according to a pre-set grid step size to obtain a continuous field soil moisture content distribution covering the entire planting area. Discrete point-based moisture content measurements are transformed into a continuous field model that can be used for subsequent gradient calculations, and a bilinear interpolation algorithm is used to smoothly transition between data differences between different sensors. This method solves the problem that existing technologies often use coarse or stepped partitioning in spatial distribution simulation, leading to insufficiently refined decision-making. Through refined grids and interpolation strategies, it can more realistically reflect the spatial variation trend of soil moisture content in the field. Compared with simple neighbor-point assignment or centroid interpolation, this scheme has higher interpolation accuracy and can achieve high-resolution moisture distribution prediction while ensuring real-time performance, providing solid data support for subsequent gradient analysis and spraying decisions.

[0068] 3. By performing central difference and boundary difference operations on the gridded continuous field data in both the horizontal and vertical directions, the gradient component of each grid node is calculated, and the gradient modulus is obtained accordingly. This allows for the statistical calculation of the average gradient across the entire field. Combining continuous field distribution with numerical difference techniques enables both the use of central difference for internal nodes to obtain higher-precision gradient estimation and the flexible application of unilateral difference for boundary nodes to prevent out-of-bounds errors. This design solves the problem of rapidly calculating spatial slope or gradient in large-scale farmland environments, achieving efficient conversion directly from moisture content values ​​to gradient modulus. Compared to traditional methods that only use overall averages or empirical coefficients to process spraying amounts, this scheme can accurately capture the rate of local moisture change, providing a key indicator for precision spraying and improving the responsiveness to differences in moisture gradients during spraying.

[0069] 4. The entire planting area is divided into several rectangular spraying zones based on the number of nozzles. Gradient nodes falling within each zone are aggregated. When some zones are empty, nodes are supplemented by reprojecting along the boundaries and grid lines. Finally, the average gradient modulus of the nodes within each spraying zone is calculated as the representative gradient value for that zone. This one-to-one zone division with each nozzle, along with the dynamic boundary alignment and reprojection strategy in case of insufficient nodes, ensures that all nozzles obtain effective gradient information and solves the problem of some micro-areas being uncountable due to traditional regular grids. Through this design, the system can seamlessly adapt to different numbers and distributions of nozzles in actual operation, without "missed sprays" or "empty zones" affecting accuracy. Compared with existing technologies that use fixed-size grids or ignore areas without measurement points, this solution maximizes the use of available data while ensuring complete spray coverage, thus improving spray uniformity and accuracy.

[0070] 5. Based on the required spray volume per unit area in a given region, the base spray volume for each nozzle is generated by calculating the area of ​​each spraying zone and multiplying it by the required volume per unit area. This directly maps the spray demand from a macroscopic indicator to a volume calculation precisely linked to the area, ensuring that the initial spray volume is strictly proportional to the actual coverage. This solves the problem of over- or under-spraying caused by neglecting micro-area differences in traditional methods, reducing the risk of wasting chemical agents. Compared to existing technologies that typically estimate based on a fixed spray volume or empirical values, this method obtains a more objective and adjustable base volume through precise area calculation, providing an accurate starting point for subsequent adjustments and laying the foundation for differentiated pesticide supply to meet the needs of different crops.

[0071] 6. Simultaneously, calculate the minimum and maximum average gradient values ​​for all sprayed areas. Using these as endpoints, linearly map the average gradient of each area into a spray volume adjustment factor. When the average gradient of all areas is equal, uniformly set the adjustment factor to one. Dynamically adjust the spray volume using the moisture gradient, incorporating the difference between wet and dry conditions into the decision-making system, and forming a directly multiplicative response coefficient through linear mapping. This design effectively solves the drawback of existing technologies that ignore moisture differences, leading to over- or under-spraying; it also ensures stability under conditions of extremely small or large gradients. Compared to traditional methods relying solely on fixed factors or manual adjustments, this scheme's factor generation process is both automated and traceable, reflecting real-time field moisture conditions and improving spray precision and operational consistency.

[0072] 7. Multiply the base spray volume of each nozzle by the corresponding spray volume adjustment factor to obtain the preliminary spray volume. Then, clamp the obtained volume according to preset minimum and maximum percentage boundaries to obtain the final spray volume. This upper and lower limit clamping mechanism prevents over- or under-spraying due to extreme adjustment factors, ensuring the spray volume remains within a reasonable range. Simultaneously, this mechanism, based on proportional definition, ensures flexible adjustment of the spraying strategy while maintaining bottom-line constraints on crop safety and environmental protection. This step addresses the safety and quality risks that may arise from simple mapping. Compared to existing technologies that only map without limiting the range or require manual intervention for remediation, this solution achieves the best balance between automation and safety, exhibiting higher engineering practicality and risk control capabilities.

[0073] 8. Obtain the maximum spray speed limit and actual spray speed of each nozzle, and calculate the operating time based on the final spray volume. The controller sequentially executes the opening and closing operations of each nozzle; simultaneously, it records the basic volume, final volume, spray speed, and operating time according to the nozzle number, and generates a spraying report including the gradient of each area, spray volume, and execution time. This deep integration of execution control and real-time data recording achieves a unified approach to precise control and traceable recording. This design solves the problem of lacking refined execution and closed-loop feedback in large-scale field operations, making the spraying process fully monitorable and auditable. Compared with traditional manual control or simple start-stop methods, this solution, through real-time recording and report generation, enables managers to analyze spraying effects and optimize parameter settings afterward, while simultaneously meeting the dual requirements of agricultural production for quality management and environmental protection. Attached Figure Description

[0074] Figure 1 This is a schematic diagram of the process of the present invention.

[0075] Figure 2 This is a schematic diagram of the rectangular coordinate system of the present invention.

[0076] In the diagram: 1 - origin, 2 - Shaft, 3- axis. Detailed Implementation

[0077] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 skilled in the art without creative effort are within the scope of protection of the present invention.

[0078] Example, refer to Figure 1 A quantitative spraying method for standardized cultivation of Chinese medicinal herbs, comprising:

[0079] Establish a plane rectangular coordinate system on the field surface, construct an equally spaced sampling grid, pre-embed capacitive soil moisture sensors, complete two-point calibration and set feasible upper and lower limits for moisture content, and convert the real-time voltage into the moisture content of each grid node according to the calibration relationship.

[0080] Based on the sensor sampling matrix, four-point bilinear interpolation is performed on any coordinate point according to the grid step to obtain the soil moisture content distribution in the continuous field;

[0081] The horizontal and vertical differences are calculated at each grid node to obtain the spatial gradient components and gradient modulus of water content, and the average gradient modulus of the whole field is obtained.

[0082] Based on the number of nozzles, the field is divided into several rectangular spraying areas. Nodes in each area are collected, and when the nodes are empty, the area boundary is aligned with the grid line and then reprojected to extract the average gradient of each area.

[0083] Obtain the required spray volume per unit area, calculate the coverage area of ​​each nozzle, and obtain the basic spray volume.

[0084] Using the minimum and maximum average gradients of the entire field as endpoints, a linear mapping is performed on the average gradients of each region to generate the spray volume adjustment factor.

[0085] The final spray volume is obtained by multiplying the base volume of each nozzle by the corresponding adjustment factor, and the final spray volume is then bounded.

[0086] The controller obtains the maximum spray speed limit and actual spray speed of each nozzle, calculates the activation time, executes the commands sequentially, and records the basic volume, final volume and activation time according to the nozzle number, generating a spraying report that includes regional gradient, spray volume and execution time.

[0087] First, a coordinate system and equally spaced sampling grids are established on the field surface. Capacitive soil moisture sensors are pre-embedded, and after two-point calibration and upper and lower bound settings, the sensor voltage data is converted into soil moisture content for each grid. Then, using these discrete data, an interpolation algorithm is used to obtain the continuous soil moisture distribution at any location within the field. Further, spatial gradients and the average gradient of the entire field are calculated at the grid nodes to reflect the spatial variation characteristics of moisture distribution. The field is then divided into zones based on the number of sprinklers, and data is extracted from each zone. If no valid nodes are available within a zone, the zone boundaries are dynamically adjusted to ensure data availability. For each sprinkler, a basic spray volume is calculated based on the zone area and the unit spray volume requirement. Then, based on the linear relationship between the average gradient of each zone and the overall extreme value, a spray volume adjustment factor is generated to differentiate the spray volume, and boundary clamping is used to prevent extreme spray volumes. Finally, combining the maximum and actual spray rates of each sprinkler, the spray duration is calculated, executed step-by-step by the controller, and all operational data is archived to output a spray report. Through the aforementioned systematic operation across multiple stages, the problems of traditional manual estimation and extensive spraying—namely, their inability to accurately respond to the spatial heterogeneity of field moisture, the instability of spraying operations, and the lack of traceability of spraying data—were solved. The benefits lie in achieving data-driven, differentiated management, and closed-loop recording of field operations, improving the scientific rigor and controllability of spraying operations, and laying the foundation for subsequent digital agricultural management.

[0088] Reference Figure 2 The process of establishing a Cartesian coordinate system on the field surface, constructing an equally spaced sampling grid, pre-embedding capacitive soil moisture sensors, completing two-point calibration and setting feasible upper and lower limits for moisture content, and converting the real-time voltage into the moisture content of each grid node according to the calibration relationship, specifically includes:

[0089] Establish a plane rectangular coordinate system on the surface of the Chinese medicinal herb planting field, with the origin set at any vertex, the horizontal axis along the long side, and the vertical axis along the short side;

[0090] The surface of the medicinal herb planting field is a rectangular area, and the length of the longer side is greater than the length of the shorter side;

[0091] No fewer than two sampling lines are laid out horizontally, and no fewer than two sampling points are laid out vertically on each sampling line. Capacitive soil moisture sensors of equal depth are pre-embedded at all intersections and numbered.

[0092] The voltages of each sensor were collected under two sets of known standard moisture content conditions, and the conversion slope and intercept of each sensor were obtained according to the two-point calibration principle.

[0093] The real-time voltage is converted into water content based on the slope and intercept, and then bounded by a lower and upper bound within the feasible range of zero to 100%, forming a water content sequence for each grid node.

[0094] Further specific implementation steps include:

[0095] Establish a two-dimensional rectangular coordinate system on the surface of the medicinal herb planting field. ,origin Located at any vertex of the field where Chinese medicinal herbs are grown. The axis runs along the length of the long side of the field. The axis is along the shorter side of the field.

[0096] The surface of the medicinal herb planting field is a rectangular area. ;in, , The fields are respectively shaft and The total length in the axial direction, and ;

[0097] Within the surface of the fields where Chinese medicinal herbs are grown, along Equal spacing along the axial direction Sampling line, along Equal spacing along the axial direction There are 1 sampling point, and a capacitive soil moisture sensor is installed at each intersection. The sensor number is [insert sensor number here]. The coordinates are:

[0098] , ;in, For the first line, number Humidity sensor at column position; For row index, For column indexes; For the first Line sensor line coordinate; For the first Column sensor column line Coordinates; and For along Number of sampling lines in the axial direction; For along Number of sampling points along the axial direction;

[0099] The depth at which all sensors are uniformly pre-buried is denoted as... ;

[0100] Voltage values ​​from two sets of humidity sensors were collected under different moisture content conditions. , The corresponding standard moisture content values ​​are respectively and ;in, , For the first The original voltage of sensor No. 1 under two sets of standard moisture content conditions; , Two sets of standard soil moisture contents;

[0101] If and only if and At that time, calculate the humidity sensor The conversion factor is as follows:

[0102] , ;in, and The first Moisture content-voltage slope and linear conversion intercept of sensor number 1;

[0103] At that time At that time, the sensor Real-time output voltage Can be converted to soil moisture content Specifically:

[0104] S101, when season ;

[0105] S102, when season ;

[0106] S103, when season ;

[0107] in, For the first Sensor No. 1 at time The voltage reading; For the first Sensor No. 1 at time Soil moisture content; This is the lower bound of the feasible region. Upper bound of feasible region.

[0108] This method defines how to establish a Cartesian coordinate system on the field surface, construct a sampling grid, pre-embed sensors, complete two-point calibration and upper / lower boundary settings, and convert the collected real-time voltage into moisture content. It employs capacitive soil moisture sensors placed at the intersection of each grid point in the field, precisely positioning each sensor using preset two-dimensional coordinates, with all sensors pre-embedded at a uniform depth. Each sensor collects voltage at two different moisture contents, forming a one-to-one calibration relationship (slope, intercept). During real-time data acquisition, the sensor output voltage is converted into moisture content according to this relationship; values ​​exceeding the upper and lower limits are directly assigned as boundary values, and all results form a spatiotemporal grid. This process solves practical problems such as uneven distribution of field environmental sensors, inconsistent installation depth and positioning, large calibration data errors, and interference from extreme data. The advantages are high consistency, spatial traceability, and automatic anomaly filtering in field moisture measurement data, laying a solid foundation for subsequent accurate interpolation and spraying decisions. Compared with traditional methods, it improves the quality and reliability of sensor data and reduces measurement deviations caused by human factors.

[0109] The method of obtaining the soil moisture content distribution in a continuous field by performing four-point bilinear interpolation on any coordinate point according to the grid step size, based on the sensor sampling matrix, specifically includes:

[0110] Organize the moisture content of all nodes into a two-dimensional sampling matrix by rows and columns;

[0111] The grid spacing is determined based on the total horizontal and vertical length of the field and the number of samples.

[0112] For any coordinate point, locate the bottom left corner grid index of its cell and calculate the normalized relative position coefficients of the point in the horizontal and vertical directions.

[0113] Using the moisture content of the four corner nodes of the unit and the relative position coefficient as weights, four-point bilinear interpolation is performed to obtain the continuous field moisture content of the coordinate point.

[0114] Further specific implementation steps include:

[0115] All sensor sampling results are organized into a two-dimensional matrix. ;in, Let be a matrix function with size . , No. Yuanwei ;

[0116] At any coordinate point Soil moisture content Four-point bilinear interpolation is used, specifically:

[0117] S201, Settings , ,make:

[0118] , Based on this, the index of the lower left corner of the cell is determined as follows: , ;in, , The grid step size; , The coordinates after being bounded by the boundary;

[0119] S202. Calculate the normalized ratio:

[0120] ,

[0121] ;in, , respectively along Axial direction and Normalized relative position along the axis;

[0122] S203, Obtain any point At any moment The continuous field water content is estimated as follows:

[0123] The weighting coefficients are: and satisfy , ;in, These are the bilinear interpolation weight coefficients. This indicates the offset relative to the bottom left node. represent Axial direction, represent Axial direction; For the four corner nodes of the unit At any moment Discrete moisture content.

[0124] All sensor data is organized into a two-dimensional matrix. The relative position of each query point within the grid cell is calculated based on the grid step size. Soil moisture content at any coordinate point in the field is obtained through four-point bilinear interpolation, achieving continuous spatial distribution. By using an interpolation algorithm, the originally discrete data, constrained by sensor layout, is expanded into a soil moisture content distribution covering the entire field. This solves the problem of not being able to obtain target point data when sensor density is insufficient or the spraying path does not coincide with sensor points. Compared to traditional nearest-neighbor assignment or simple averaging, this method effectively smooths spatial variations, eliminates "discontinuities," and improves the spatial integrity and reliability of the field data field. Through this step, spraying decisions can be made accurately at any coordinate point, rather than being limited to the sensor location, propelling digital agricultural operations towards higher precision.

[0125] The process of calculating the lateral and longitudinal differences at each grid node to obtain the spatial gradient components and gradient modulus of water content, and then calculating the average gradient modulus of the entire field, specifically includes:

[0126] For non-boundary nodes, central difference is applied in both the horizontal and vertical directions to obtain gradient components in two directions;

[0127] One-sided difference is applied to nodes located on the four boundaries to obtain gradient components in two directions;

[0128] The gradient magnitude of each node is obtained using the gradient components in both directions;

[0129] The average gradient magnitude of all nodes is taken to obtain the average gradient magnitude of the entire field.

[0130] Further specific implementation steps include:

[0131] For each node Calculation in axis, The gradient components along the axial direction are specifically:

[0132] S301. Non-boundary points use central difference:

[0133] , ;in, , They are nodes At any moment Spatial gradient of water content , Quantity;

[0134] S302, Boundary points use one-sided difference:

[0135] like : ;

[0136] like : ;

[0137] like : ;

[0138] like : ;

[0139] Calculate each node At any moment Moisture gradient modulus Specifically:

[0140] ;

[0141] Calculate at time The average gradient modulus of the entire field Specifically:

[0142] .

[0143] For each node, gradients are calculated laterally and longitudinally using central difference or lateral difference (for boundary nodes). The spatial gradient modulus of each node is then synthesized and averaged over all nodes. This spatial gradient calculation not only reveals the absolute distribution of soil moisture but also the intensity of moisture changes at different locations. Areas with high spatial gradients often indicate significant changes in moisture levels, making them "sensitive" areas for crop growth and key targets for precision management. Compared to existing technologies, traditional spraying focuses primarily on total amount or average value, failing to distinguish between "uniform zones" and "transitional zones" in the field, potentially leading to over-spraying in some areas and under-spraying in others. This method provides a scientific basis for differentiated spraying, helping to improve the utilization efficiency of water, fertilizer, and pesticide inputs while avoiding resource waste and environmental risks caused by uneven application.

[0144] The process involves dividing the field into several rectangular spraying areas based on the number of sprinklers, collecting node data within each area, aligning the area boundaries with the grid lines when nodes are empty, reprojecting the data, and extracting the average gradient for each area. Specifically, this includes:

[0145] Establish corresponding rectangular spraying areas according to the number of nozzles and number them, and set the horizontal and vertical lower and upper boundaries of each area;

[0146] Collect grid nodes located within the boundaries of each region and count the number of nodes;

[0147] When the number of nodes in a region is zero, align the boundary of the region with the nearest grid line and project it inward or outward until it contains at least one node.

[0148] Calculate the average value of the node gradient magnitude in each region.

[0149] Further specific implementation steps include:

[0150] Set the total number of nozzles to Each nozzle is numbered The rectangular area corresponding to the nozzle and satisfy ;in, Index to nozzles and spray areas; For the first A rectangular area covered by each nozzle; , , , The first The area is , The coordinates of the lower and upper boundaries of the direction;

[0151] Will satisfy , Add the node to the collection In, the total number of nodes is and guarantee If it appears Then The boundaries are aligned with the grid lines and projected:

[0152] ,

[0153] ,

[0154] ,

[0155] ;in, For the position located at the All grid node index pairs within the region A set; For the first The total number of nodes in the region; , , , The first After region alignment , The lower and upper boundaries of the direction;

[0156] Calculate the first Region at time average gradient magnitude .

[0157] The method divides the field into rectangular spraying zones based on the number of sprinklers, collects node data for each zone, and ensures that each zone contains at least one node through boundary alignment and reprojection when a zone lacks a valid node. The average gradient of each zone is then extracted. This approach is beneficial because the actual control unit for spraying is the sprinkler, and each sprinkler corresponds to a specific spatial range. Through zone allocation and adaptive boundary adjustment, the problem of "empty data areas" caused by mismatch between zone division and actual grid location is solved. The reprojection mechanism ensures that each spraying zone is based on real sampled data, avoiding the decision distortion caused by default values ​​due to lack of data in traditional uniform partitioning methods. This method allows for the quantification of differences in the action area of ​​each sprinkler, promoting finer adjustments to spraying operations from "by area" to "by state," making area management more targeted and effective, and improving resource utilization.

[0158] The process of obtaining the required spray volume per unit area, calculating the coverage area of ​​each nozzle, and obtaining the basic spray volume specifically includes:

[0159] Obtain the required spray volume per unit area;

[0160] The coverage area is calculated based on the difference in the lateral and longitudinal boundaries of the rectangular area corresponding to each nozzle.

[0161] Multiply the coverage area by the required spray volume per unit area to obtain the basic spray volume for each nozzle.

[0162] Further specific implementation steps include:

[0163] The required spray volume per unit area is denoted as . The unit is ;

[0164] Calculate the nozzle Area of ​​action ;

[0165] Then you get the nozzle. The basic spray volume is .

[0166] A method for accurately calculating the basic spray volume based on the required spray volume per unit area and the coverage area of ​​each nozzle is proposed. The core of this method is to directly multiply the agronomically standardized application rate (per unit area) by the actual spraying area of ​​each nozzle to obtain the basic spray volume. This method solves the problems of inaccuracy and lack of traceability caused by indirect estimation of spray volume based on experience or nozzle operating time in the past. The advantage of this method is that it directly quantifies and implements agronomic management requirements to the actual field operation unit, ensuring that the actual spray volume is consistent with the theoretical requirement, greatly improving the standardization and normalization of operations, and providing a scientific "baseline" for subsequent differentiated adjustments to the spray volume. Compared with traditional methods, it reduces the problems of pesticide waste or incomplete crop control caused by regional area errors or uneven spraying.

[0167] The process of generating a spray volume adjustment factor by performing a linear mapping on the average gradient of each region using the minimum and maximum average gradients of the entire field as endpoints specifically includes:

[0168] Obtain the minimum and maximum values ​​of the average gradient in each region of the entire field.

[0169] The average gradient of each target region is linearly mapped to its minimum and maximum values ​​to generate the spray volume adjustment factor.

[0170] When the minimum value equals the maximum value, the spray volume adjustment factor for all regions is uniformly set to one.

[0171] Further specific implementation steps include:

[0172] The injection volume adjustment factor is constructed as follows:

[0173] ;in, For the first Region at time The injection volume adjustment factor; For at any time The minimum value of the average gradient across all regions; For at any time The maximum value of the average gradient across all regions.

[0174] This paper describes the steps of generating a spray dosage adjustment factor by performing a linear mapping on the average gradient of each region, using the minimum and maximum average gradients of the entire field as endpoints. This method "normalizes" the spatial gradient intensity of each region to the same standard, making the adjustment factor correspond to the degree of moisture variation within the field. This not only adapts to the spatial heterogeneity variations between different fields or different growth stages within the same field, but also automatically balances spray dosage adjustments under extremely uniform or extremely differentiated conditions, avoiding unreasonable adjustments caused by artificially fixed intervals. Compared with existing technologies, traditional methods are often insensitive to differential responses or use simple threshold divisions, resulting in poor flexibility and adaptability. This method improves the continuity and adaptability of the adjustment mechanism through linear mapping, enabling more scientific allocation of spray dosage to the truly needed areas, improving pesticide utilization efficiency, and reducing environmental pressure.

[0175] The process of multiplying the base volume of each nozzle by its corresponding adjustment factor to obtain the final spray volume, and then subjecting the obtained final spray volume to boundary clamping, specifically includes:

[0176] Multiply the base spray volume of each nozzle by the corresponding spray volume adjustment factor to obtain the final spray volume;

[0177] Set the minimum spray volume to 0.8 times the base volume and the maximum spray volume to 1.5 times the base volume for each nozzle.

[0178] The final spray volume is clamped according to the minimum and maximum spray volume to obtain the clamped spray volume.

[0179] Further specific implementation steps include:

[0180] Calculate the nozzle At any moment The final amount of pesticide sprayed was ;

[0181] Set the first The minimum and maximum spray volume of the nozzle are respectively , ;

[0182] For the nozzle At any moment The final amount of pesticide sprayed is clamped to obtain:

[0183] .

[0184] This paper proposes a method to calculate the final spray volume by multiplying the base spray volume by an adjustment factor, and sets strict upper and lower limits on the result to prevent excessively high or low spray volumes due to extreme adjustments. Specifically, the final spray volume for each nozzle must not be lower than 0.8 times or higher than 1.5 times the base spray volume. The beneficial effect of this approach is that while ensuring the heterogeneity of moisture in the response area, it establishes a reasonable range for spraying operations, preventing over- or under-spraying due to local extreme conditions or algorithm errors. This mechanism retains the flexibility of differentiated management while also considering the safety of actual operations and the rigor of agronomic standards. Compared with existing technologies, it reduces operational instability caused by improper selection of adjustment parameters, and improves the controllability and consistency of actual field operations.

[0185] The process involves obtaining the maximum and actual spray speed of each nozzle, calculating the activation duration, and the controller executing these steps sequentially. It also records the base volume, final volume, and activation duration according to the nozzle number, generating a spraying report that includes the regional gradient, spray volume, and execution time. Specifically, this includes:

[0186] Obtain the maximum allowable spray speed limit for each nozzle and the actual spray speed selected during execution;

[0187] The opening time of each nozzle is calculated based on the final spray volume and the actual spray speed.

[0188] The controller turns each nozzle on and off sequentially according to its number, and performs the operation according to its respective operating duration.

[0189] Save the basic spray volume, final spray volume, and operation duration records by nozzle number;

[0190] Automatically generate spraying reports, specifying the moisture content gradient of each area, spraying volume, and execution time.

[0191] Further specific implementation steps include:

[0192] Get the The maximum allowable spray speed of the nozzle is denoted as . ;

[0193] Get the The actual spray speed selected by the nozzle during operation is denoted as . ;

[0194] Calculate the first nozzle on-time ;

[0195] The controller sequentially executes the activation duration for each nozzle for the following durations. ;

[0196] Record and archive the following data according to the nozzle number: ;in, For the first A set of operation record entries for the sprinkler head;

[0197] The system automatically generates a spraying report, including the water content gradient, spray volume, and execution time for each area.

[0198] The process clearly defines how to calculate the spraying time by combining the maximum and actual spraying speed of the nozzles, and then execute the spraying sequentially via a controller. Detailed data such as the basic volume, final volume, and spraying time of each nozzle are recorded, and a spraying report is generated. This step, through data archiving, achieves full-process digitalization and traceability management of the spraying process, solving problems such as omissions, incomplete data, and difficulty in reviewing operations in traditional manual recording. The spraying report not only includes operational parameters but also reflects the water content gradient and actual pesticide application in each area, providing solid data support for field management, operational quality analysis, and subsequent scientific decision-making. Compared with traditional manual recording or methods relying entirely on experience, this improves the transparency and intelligence of agricultural operations, contributing to the refinement and data-driven management of farms.

[0199] This embodiment also provides a system for a quantitative spraying method for standardized cultivation of Chinese medicinal herbs, including:

[0200] The field modeling unit performs coordinate establishment and area limitation.

[0201] The sampling and acquisition unit is connected to the capacitive soil moisture sensor to perform two-point calibration and real-time sampling conversion;

[0202] The distribution building unit performs four-point bilinear interpolation and outputs a continuous moisture content distribution.

[0203] The gradient calculation unit performs difference calculations and statistical analysis of the average gradient of the entire field.

[0204] The region is divided into units, spraying areas are established, and boundary alignment and node reprojection are performed.

[0205] The baseline volume calculation unit performs coverage area calculation and basic spray volume generation.

[0206] The response factor calculation unit performs global extremum acquisition and linear mapping.

[0207] The spray volume determination unit performs volume calculation and clamping.

[0208] The execution control unit is connected to the nozzle array and performs spray speed setting and on-time control.

[0209] The information recording unit archives the operation data and generates a spraying report.

[0210] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0211] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A quantitative spraying method for standardized cultivation of Chinese medicinal herbs, characterized in that, include: Establish a plane rectangular coordinate system on the field surface, construct an equally spaced sampling grid, pre-embed capacitive soil moisture sensors, complete two-point calibration and set feasible upper and lower limits for moisture content, and convert the real-time voltage into the moisture content of each grid node according to the calibration relationship. Based on the sensor sampling matrix, four-point bilinear interpolation is performed on any coordinate point according to the grid step to obtain the soil moisture content distribution in the continuous field; The horizontal and vertical differences are calculated at each grid node to obtain the spatial gradient components and gradient modulus of water content, and the average gradient modulus of the whole field is obtained. Based on the number of nozzles, the field is divided into several rectangular spraying areas. Nodes in each area are collected, and when the nodes are empty, the area boundary is aligned with the grid line and then reprojected to extract the average gradient of each area. Obtain the required spray volume per unit area, calculate the coverage area of ​​each nozzle, and obtain the basic spray volume. Using the minimum and maximum average gradients of the entire field as endpoints, a linear mapping is performed on the average gradients of each region to generate the spray volume adjustment factor. The final spray volume is obtained by multiplying the base volume of each nozzle by the corresponding adjustment factor, and the final spray volume is then bounded. The controller obtains the maximum spray speed limit and actual spray speed of each nozzle, calculates the activation time, executes the commands sequentially, and records the basic volume, final volume and activation time according to the nozzle number, generating a spraying report that includes regional gradient, spray volume and execution time.

2. The quantitative spraying method for standardized cultivation of Chinese medicinal herbs according to claim 1, characterized in that, The process of establishing a Cartesian coordinate system on the field surface, constructing an equally spaced sampling grid, pre-embedding capacitive soil moisture sensors, completing two-point calibration and setting feasible upper and lower limits for moisture content, and converting real-time voltage into moisture content for each grid node according to the calibration relationship, specifically includes: Establish a plane rectangular coordinate system on the surface of the Chinese medicinal herb planting field, with the origin set at any vertex, the horizontal axis along the long side, and the vertical axis along the short side; The surface of the medicinal herb planting field is a rectangular area, and the length of the longer side is greater than the length of the shorter side; No fewer than two sampling lines are laid out horizontally, and no fewer than two sampling points are laid out vertically on each sampling line. Capacitive soil moisture sensors of equal depth are pre-embedded at all intersections and numbered. The voltages of each sensor were collected under two sets of known standard moisture content conditions, and the conversion slope and intercept of each sensor were obtained according to the two-point calibration principle. The real-time voltage is converted into water content based on the slope and intercept, and then bounded by a lower and upper bound within the feasible range of zero to 100%, forming a water content sequence for each grid node.

3. The quantitative spraying method for standardized cultivation of Chinese medicinal herbs according to claim 2, characterized in that, The method of obtaining the soil moisture content distribution in a continuous field by performing four-point bilinear interpolation on any coordinate point according to the grid step size, based on the sensor sampling matrix, specifically includes: Organize the moisture content of all nodes into a two-dimensional sampling matrix by rows and columns; The grid spacing is determined based on the total horizontal and vertical length of the field and the number of samples. For any coordinate point, locate the bottom left corner grid index of its cell and calculate the normalized relative position coefficients of the point in the horizontal and vertical directions. Using the moisture content of the four corner nodes of the unit and the relative position coefficient as weights, four-point bilinear interpolation is performed to obtain the continuous field moisture content of the coordinate point.

4. The quantitative spraying method for standardized cultivation of Chinese medicinal herbs according to claim 3, characterized in that, The process of calculating the lateral and longitudinal differences at each grid node to obtain the spatial gradient components and gradient modulus of water content, and then calculating the average gradient modulus of the entire field, specifically includes: For non-boundary nodes, central difference is applied in both the horizontal and vertical directions to obtain gradient components in two directions; One-sided difference is applied to nodes located on the four boundaries to obtain gradient components in two directions; The gradient magnitude of each node is obtained using the gradient components in both directions; The average gradient magnitude of all nodes is taken to obtain the average gradient magnitude of the entire field.

5. The quantitative spraying method for standardized cultivation of Chinese medicinal herbs according to claim 4, characterized in that, The process involves dividing the field into several rectangular spraying areas based on the number of sprinklers, collecting node data within each area, aligning the area boundaries with the grid lines when nodes are empty, reprojecting the data, and extracting the average gradient for each area. Specifically, this includes: Establish corresponding rectangular spraying areas according to the number of nozzles and number them, and set the horizontal and vertical lower and upper boundaries of each area; Collect grid nodes located within the boundaries of each region and count the number of nodes; When the number of nodes in a region is zero, align the boundary of the region with the nearest grid line and project it inward or outward until it contains at least one node. Calculate the average value of the node gradient magnitude in each region.

6. The quantitative spraying method for standardized cultivation of Chinese medicinal herbs according to claim 5, characterized in that, The process of obtaining the required spray volume per unit area, calculating the coverage area of ​​each nozzle, and obtaining the basic spray volume specifically includes: Obtain the required spray volume per unit area; The coverage area is calculated based on the difference in the lateral and longitudinal boundaries of the rectangular area corresponding to each nozzle. Multiply the coverage area by the required spray volume per unit area to obtain the basic spray volume for each nozzle.

7. A quantitative spraying method for standardized cultivation of Chinese medicinal herbs according to claim 6, characterized in that, The process of generating a spray volume adjustment factor by performing a linear mapping on the average gradient of each region using the minimum and maximum average gradients of the entire field as endpoints specifically includes: Obtain the minimum and maximum values ​​of the average gradient in each region of the entire field. The average gradient of each target region is linearly mapped to its minimum and maximum values ​​to generate the spray volume adjustment factor. When the minimum value equals the maximum value, the spray volume adjustment factor for all regions is uniformly set to one.

8. The quantitative spraying method for standardized cultivation of Chinese medicinal herbs according to claim 7, characterized in that, The process of multiplying the base volume of each nozzle by its corresponding adjustment factor to obtain the final spray volume, and then subjecting the obtained final spray volume to boundary clamping, specifically includes: Multiply the base spray volume of each nozzle by the corresponding spray volume adjustment factor to obtain the final spray volume; Set the minimum spray volume to 0.8 times the base volume and the maximum spray volume to 1.5 times the base volume for each nozzle. The final spray volume is clamped according to the minimum and maximum spray volume to obtain the clamped spray volume.

9. A quantitative spraying method for standardized cultivation of Chinese medicinal herbs according to claim 8, characterized in that, The process involves obtaining the maximum and actual spray speed of each nozzle, calculating the activation duration, and the controller executing these steps sequentially. It also records the base volume, final volume, and activation duration according to the nozzle number, generating a spraying report that includes the regional gradient, spray volume, and execution time. Specifically, this includes: Obtain the maximum allowable spray speed limit for each nozzle and the actual spray speed selected during execution; The opening time of each nozzle is calculated based on the final spray volume and the actual spray speed. The controller turns each nozzle on and off sequentially according to its number, and performs the operation according to its respective operating duration. Save the basic spray volume, final spray volume, and operation duration records by nozzle number; Automatically generate spraying reports, specifying the moisture content gradient of each area, spraying volume, and execution time.

10. A system employing the quantitative spraying method for standardized cultivation of Chinese medicinal herbs as described in claim 9, characterized in that, include: The field modeling unit performs coordinate establishment and area limitation. The sampling and acquisition unit is connected to the capacitive soil moisture sensor to perform two-point calibration and real-time sampling conversion; The distribution building unit performs four-point bilinear interpolation and outputs a continuous moisture content distribution. The gradient calculation unit performs difference calculations and statistical analysis of the average gradient of the entire field. The region is divided into units, spraying areas are established, and boundary alignment and node reprojection are performed. The baseline volume calculation unit performs coverage area calculation and basic spray volume generation. The response factor calculation unit performs global extremum acquisition and linear mapping. The spray volume determination unit performs volume calculation and clamping. The execution control unit is connected to the nozzle array and performs spray speed setting and on-time control. The information recording unit archives the operation data and generates a spraying report.

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