A precision fertilization method and system based on real-time monitoring of paddy field nutrients

Abstract

This invention relates to the field of agricultural fertilization technology, specifically to a precision fertilization method and system based on real-time monitoring of paddy field nutrients. The method includes the following steps: acquiring map data of the paddy field; dividing the paddy field into multiple uniform regions using random sampling and expansion algorithms; acquiring soil and nutrient data of the paddy field; constructing a comprehensive assessment model for paddy field regions to comprehensively evaluate differences in nutrient and soil characteristics; classifying the uniform regions according to differences in nutrient and soil characteristics to obtain classified regions; constructing a nutrient demand analysis model for paddy fields; constructing a precision fertilization model for paddy fields; and determining the fertilization amount to achieve precise graded fertilization. This invention comprehensively assesses paddy field nutrients and soil characteristics by region, determines fertilization priority, and precisely matches the nutrient requirements of each region to specific fertilizers and fertilization amounts, ensuring close alignment between region, nutrient, fertilizer type, and fertilization amount, thus achieving precision fertilization management.

Description

Technical Field

[0001] This invention relates to the field of agricultural fertilization technology, specifically to a precision fertilization method and system based on real-time monitoring of nutrient content in paddy fields. Background Technology

[0002] As a crucial base for food crop production, the nutrient management of paddy fields has a vital impact on crop yield and quality. However, traditional paddy field nutrient management methods often rely on experience-based judgment and periodic manual testing. This approach is not only time-consuming and labor-intensive but also fails to accurately reflect real-time changes in paddy field nutrients. With the development of modern agricultural technology, real-time monitoring of paddy field nutrients and precise fertilization based on this information have become important means to improve agricultural production efficiency and sustainability.

[0003] Although some paddy field nutrient monitoring technologies exist, these technologies still have many shortcomings in practical applications. First, most existing technologies can only provide limited nutrient data, making it difficult to comprehensively reflect the nutrient status of paddy fields. Second, the regional division methods of existing technologies are often too simplistic, failing to achieve precise regional division of paddy fields, leading to uneven nutrient management. Third, existing fertilization models are often based on static data, lacking the ability to dynamically adjust and accurately predict and respond to real-time changes in paddy field nutrient requirements. Fourth, the impact of soil characteristics on nutrients is not considered during fertilization, resulting in insufficient precision in fertilization site location. These problems limit the effectiveness of existing technologies in precision fertilization, leading to low fertilizer utilization, severe nutrient loss, and increased environmental pollution.

[0004] To address the shortcomings of existing technologies, this invention proposes a precision fertilization method based on real-time monitoring of paddy field nutrients. This method utilizes random sampling and expansion algorithms, combined with paddy field map data, to achieve uniform division of paddy field areas, significantly improving the precision and efficiency of paddy field management. By constructing a comprehensive evaluation model for paddy field areas, it comprehensively assesses the differences in paddy field nutrients and soil characteristics, providing a scientific basis for precision fertilization. Furthermore, by constructing a paddy field nutrient demand analysis model and a precision fertilization model, it achieves accurate quantification of paddy field nutrient requirements and precise fertilization. Therefore, this invention has achieved significant innovative results in real-time monitoring and precision fertilization of paddy field nutrients, possessing broad application prospects and significant social value. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a precision fertilization method and system based on real-time monitoring of paddy field nutrients.

[0006] In a first aspect, the present invention provides a precision fertilization method based on real-time monitoring of paddy field nutrients, comprising the following steps: acquiring map data of the paddy field, the map data including coordinate data and area data; dividing the paddy field into multiple uniform regions based on the map data using a random sampling algorithm and an expansion algorithm; acquiring soil data and nutrient data of the paddy field according to the uniform regions; the soil data including data on soil texture, water content, pH, and electrical conductivity, and the nutrient data including data on nitrogen, phosphorus, potassium, and organic matter; constructing a comprehensive assessment model for paddy field regions based on the soil data and the nutrient data to comprehensively evaluate the differences in nutrient and soil characteristics of paddy field regions; classifying the uniform regions according to the differences in nutrient and soil characteristics according to the comprehensive assessment model for paddy field regions and obtaining classified regions; constructing a paddy field nutrient demand analysis model based on the classified regions; constructing a precision fertilization model for paddy fields based on the paddy field nutrient demand analysis model; and determining the fertilization amount through the precision fertilization model for paddy fields to achieve precise graded fertilization. This invention utilizes random sampling and expansion algorithms, combined with paddy field map data, to uniformly divide paddy field areas, effectively improving the precision and efficiency of paddy field management and ensuring the accuracy of nutrient requirement analysis. By constructing a comprehensive assessment model for paddy field areas, it comprehensively evaluates the differences in nutrient content and soil characteristics, providing a scientific basis for precision fertilization. By constructing and utilizing the paddy field nutrient requirement analysis model and the paddy field precision fertilization model for precise graded fertilization, it not only significantly improves fertilizer utilization and reduces nutrient loss and environmental pollution, but also promotes sustainable paddy field production, providing strong support for green agricultural development.

[0007] Optionally, dividing the paddy field into multiple uniform regions based on the map data using a random sampling algorithm and an expansion algorithm includes: constructing a dynamic equilibrium region division model based on the map data using a random sampling algorithm and an expansion algorithm; and dividing the paddy field into multiple uniform regions using the dynamic equilibrium region division model. This invention, by utilizing a random sampling algorithm and an expansion algorithm to construct a dynamic equilibrium region division model, effectively improves the flexibility and adaptability of paddy field region division, ensuring the balance of nutrient monitoring and management in each region of the paddy field. By applying the dynamic equilibrium region division model, the division of paddy field regions becomes more scientific and reasonable, avoiding the problems of uneven region division and unbalanced nutrient management that may exist in traditional methods, and improving the accuracy and efficiency of nutrient monitoring.

[0008] Optionally, the dynamic equilibrium region partitioning model satisfies the following expression:

[0009] ,

[0010] in, For the first In the nth iteration The position of each coordinate point For the first In the nth iteration The position of each coordinate point For the first In the nth iteration The position of each coordinate point This is the iteration step size factor. The area is the preset equilibrium region. For the first In the nth iteration The area of ​​each region for and The distance between them This represents the adjustment range of the coordinate point position. This represents the total number of extracted coordinate points. This invention utilizes an iterative algorithm to continuously adjust the coordinate point positions, ensuring that the area of ​​each region closely approximates a preset equilibrium area. This effectively improves the accuracy and balance of region division, providing a reliable foundation for real-time nutrient monitoring and precision fertilization. By setting the iteration step size factor and the adjustment range of the coordinate point positions, the flexibility and adjustability of region division are enhanced, making the division of paddy field areas more in line with actual needs and improving the targeting and efficiency of nutrient management. By comprehensively considering the distance between coordinate points and the differences in area, a balanced division of paddy field areas is achieved, avoiding blind spots and duplicate monitoring in nutrient monitoring and optimizing the allocation of nutrient resources.

[0011] Optionally, the step of constructing a comprehensive assessment model for paddy field regions based on the soil data and the nutrient data to comprehensively evaluate the differences in nutrient content and soil characteristics in paddy field regions includes: constructing a nutrient assessment model for paddy field regions to evaluate the differences in nutrient content based on the soil data and the nutrient data; constructing a soil characteristic assessment model for paddy field regions to evaluate the differences in soil characteristics based on the soil data and the nutrient data; and constructing a comprehensive assessment model for paddy field regions to comprehensively evaluate the differences in nutrient content and soil characteristics based on the nutrient assessment model and the soil characteristic assessment model. This invention achieves comprehensive quantification of nutrient status in paddy fields by constructing a regional nutrient assessment model, effectively improving the accuracy of nutrient management. It also provides a scientific basis for paddy field soil improvement and fertility enhancement by constructing a regional soil characteristic assessment model. Furthermore, by utilizing both the regional nutrient assessment model and the regional soil characteristic assessment model, a comprehensive assessment model for paddy fields is constructed, comprehensively and objectively reflecting the differences in nutrient and soil characteristics within the paddy field region, providing strong decision support for precise management and optimized layout of paddy fields.

[0012] Optionally, the nutrient assessment model for paddy field areas satisfies the following expression:

[0013] ,

[0014] in, For the first Nutrient assessment index of each paddy field area For the first The first rice paddy area Standardized values ​​of each nutrient index, For the first The first rice paddy area The average of each nutrient index, For the first The first rice paddy area The standard deviation of each nutrient index For the first The first rice paddy area The weights of each nutrient index; the soil characteristic assessment model for the paddy field area satisfies the following expression:

[0015] ,

[0016] in, For the first Soil property assessment index for each paddy field area For the first The first rice paddy area Measured values ​​of soil property indicators, For the first The first rice paddy area The average of each soil characteristic index, For the first The first rice paddy area Standard deviation of each soil property index For the first The first rice paddy area The median of the soil property index, For the first The first rice paddy area Interquartile range of soil property indicators and For the first The first rice paddy area Adjustment parameters corresponding to each soil property index For the first The first rice paddy area The weight parameters corresponding to each soil characteristic index; the comprehensive evaluation model for the paddy field area satisfies the following expression:

[0017] ,

[0018] in, For the first A comprehensive assessment index of nutrient and soil characteristics in each paddy field area. For the first Nutrient assessment index of each paddy field area For the first Soil property assessment index for each paddy field area , The weighting coefficients represent the weighting factors. This invention achieves precise quantification of paddy field nutrient status by constructing a regional nutrient assessment model. This model comprehensively considers the standardized values, mean, standard deviation, and weights of nutrient indicators, effectively improving the scientific rigor and targeted nature of nutrient management and promoting balanced nutrient utilization in paddy fields. Furthermore, by constructing a regional soil characteristic assessment model, it achieves precise quantification of paddy field soil characteristics. This model not only considers the mean and standard deviation of soil characteristic indicators but also introduces the median, interquartile range, and adjustment parameters, making the assessment results more comprehensive and accurate, providing strong support for soil improvement and fertility enhancement. Finally, by constructing a regional comprehensive assessment model for paddy fields, it achieves a comprehensive and objective evaluation of regional nutrient and soil characteristics, providing a scientific basis for precise management and optimized layout of paddy fields.

[0019] Optionally, classifying the uniform region according to differences in nutrient and soil characteristics based on the comprehensive assessment model of the paddy field region and obtaining classified regions includes: setting a nutrient difference threshold for the comprehensive assessment index of nutrient and soil characteristics of the paddy field region based on the comprehensive assessment model of the paddy field region; comparing the comprehensive assessment index of nutrient and soil characteristics of the paddy field region with the nutrient difference threshold to determine nutrient-rich regions and nutrient-poor regions; and classifying the uniform region based on the nutrient-rich regions and the nutrient-poor regions, combined with the paddy field region soil characteristic assessment model, to obtain classified regions, wherein the classified regions include nutrient-rich regions with excellent soil characteristics, nutrient-rich regions with poor soil characteristics, nutrient-poor regions with excellent soil characteristics, and nutrient-poor regions with poor soil characteristics. This invention achieves precise classification of nutrient and soil characteristics in paddy field regions, greatly improving the accuracy and scientific nature of the classification; it can not only clearly determine the nutrient and soil characteristic status of paddy field regions, but also classify paddy field regions based on comparison results, making paddy field management more refined and facilitating differentiated management strategies for different types of paddy field regions.

[0020] Optionally, constructing a paddy field nutrient demand analysis model based on the classified regions includes: determining the fertilization priority ranking of paddy field regions based on the classified regions, wherein the fertilization priority ranking is as follows: nutrient-poor and poor soil characteristics region > nutrient-poor but good soil characteristics region > nutrient-rich but poor soil characteristics region > nutrient-rich and good soil characteristics region; and constructing a paddy field nutrient demand analysis model based on the fertilization priority ranking. This invention, by determining the fertilization priority ranking of paddy field regions based on classified regions, achieves accurate identification of paddy field nutrient needs, effectively improving the targeting and efficiency of nutrient management; by placing nutrient-poor and poor soil characteristics regions at the top of the fertilization priority, it ensures that the paddy field regions most in need of nutrients receive priority replenishment, which helps to quickly improve the nutrient status and soil quality of these regions; and by constructing a paddy field nutrient demand analysis model, it more scientifically predicts and plans the nutrient needs of different paddy field regions, providing a strong basis for formulating reasonable and precise fertilization plans.

[0021] Optionally, the paddy field nutrient requirement analysis model satisfies the following expression:

[0022] ,

[0023] in, For the first The rice paddy area for the first The amount of nutrients required for planting For the first A comprehensive assessment index of nutrient and soil characteristics in each paddy field area. For the first The basic nutrient requirement coefficient for planting For the first Adjustment coefficient for seed nutrients, For the first Recommended application rate of nutrients. For the first A comprehensive assessment index of nutrient and soil characteristics in each paddy field area. The total number of rice paddy areas, For the first The first rice paddy area Nutrient assessment index; the precision fertilization model satisfies the following expression:

[0024] ,

[0025] in, For the first The rice paddy area for the first The amount of fertilizer applied to the plant. For the first The rice paddy area for the first The amount of nutrients required for planting For the first The first in the soil of the paddy field area The current quantity of nutrients, For the first Fertilizer utilization rate of plant nutrients For the first The first type of fertilizer The content of nutrients, For the first Fertilizer in the first Preference coefficients for each paddy field region For the first A comprehensive assessment index of nutrient and soil characteristics in each paddy field area. For the first A comprehensive assessment index of nutrient and soil characteristics in each paddy field area. For the first The first rice paddy area Nutrient assessment index. This invention achieves precise quantification of nutrient requirements in paddy fields by constructing a nutrient demand analysis model, greatly improving the scientific nature of nutrient management. By constructing a precision fertilization model, based on the actual nutrient requirements of the paddy field, the existing soil nutrient content, and factors such as fertilizer nutrient content and utilization rate, the amount of fertilizer applied to each paddy field area is accurately calculated. This not only avoids excessive or insufficient application of nutrients but also improves fertilizer utilization, reduces nutrient loss and environmental pollution, and provides strong support for sustainable paddy field production and environmental protection.

[0026] Optionally, determining the fertilizer application rate through the paddy field precision fertilization model to achieve precise graded fertilization includes: determining the specific fertilizer application rate for a specific nutrient in a specific area using the paddy field precision fertilization model, thus achieving the connection between area, nutrient, fertilizer type, and fertilizer application rate. The connection process includes: obtaining the fertilization priority ranking of paddy field areas; determining the nutrient requirements in the classified areas based on the fertilization priority ranking; determining the fertilizer type according to the nutrient requirements; determining the fertilizer application rate based on the fertilizer type and the nutrient requirements; and performing precise graded fertilization based on the fertilizer application rate and the fertilization priority ranking. This invention determines fertilizer application rates through a precise fertilization model for paddy fields, achieving accurate alignment of region, nutrients, fertilizer type, and application rate, significantly improving the precision and efficiency of fertilization. By acquiring the fertilization priority ranking of paddy field regions, priority management is implemented for the nutrient needs of different classification areas, ensuring timely replenishment of nutrients to areas in urgent need. Fertilizer types are determined based on nutrient requirements, achieving precise matching between fertilizer and nutrient needs, avoiding fertilizer waste and mismatch. By determining the fertilizer application rate based on fertilizer type and nutrient requirements, and combining it with the fertilization priority ranking for precise graded fertilization, this invention not only meets the nutrient needs of paddy fields but also optimizes the allocation of fertilizer resources, reduces environmental pollution, and promotes the sustainable development of agricultural production.

[0027] Secondly, the present invention provides a precision fertilization system based on real-time monitoring of paddy field nutrients, comprising an input device, a processor, an output device, and a memory, wherein the input device, the processor, the output device, and the memory are interconnected, wherein the memory is used to store a computer program, the computer program including program instructions, the processor is configured to call the program instructions, and the system uses the aforementioned precision fertilization method based on real-time monitoring of paddy field nutrients. This invention monitors the nutrient content in paddy fields in real time and quickly adjusts fertilization plans to ensure that paddy fields receive just the right amount of nutrients. This avoids both the waste and environmental pollution caused by nutrient excess and the stunted growth caused by nutrient deficiency, thereby improving the efficiency and precision of fertilization. Fertilizing based on the actual nutrient needs of the paddy fields avoids the blind and excessive application of traditional fertilization methods. This not only significantly improves fertilizer utilization and reduces nutrient loss but also lowers production costs and increases the economic benefits of agricultural production. Precision fertilization reduces the excessive use of chemical fertilizers, lowers the risk of soil and water pollution, helps maintain the balance of the paddy field ecosystem, promotes soil health, and lays a solid foundation for the long-term sustainable development of agriculture. Attached Figure Description

[0028] Figure 1 This is a flowchart of a precision fertilization method based on real-time monitoring of paddy field nutrients, according to an embodiment of the present invention.

[0029] Figure 2 This is a diagram showing the result of paddy field area division in an embodiment of the present invention;

[0030] Figure 3 This is a schematic diagram of the structure of a precision fertilization system based on real-time monitoring of paddy field nutrients according to an embodiment of the present invention;

[0031] Figure 4 This is a flowchart illustrating the operation of a precision fertilization system based on real-time monitoring of paddy field nutrients, according to an embodiment of the present invention. Detailed Implementation

[0032] Specific embodiments of the present invention will now be described in detail. It should be noted that the embodiments described herein are for illustrative purposes only and are not intended to limit the invention. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be apparent to those skilled in the art that these specific details are not necessary to practice the invention. In other instances, well-known circuits, software, or methods have not been specifically described to avoid obscuring the invention.

[0033] Throughout this specification, references to "an embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in connection with that embodiment or example is included in at least one embodiment of the invention. Therefore, the phrases "in an embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily refer to the same embodiment or example. Furthermore, specific features, structures, or characteristics can be combined in one or more embodiments or examples in any suitable combination and / or sub-combination. Moreover, those skilled in the art will understand that the illustrations provided herein are for illustrative purposes and are not necessarily drawn to scale.

[0034] Please see Figure 1 The present invention provides a precision fertilization method based on real-time monitoring of nutrient content in paddy fields, the method comprising the following steps:

[0035] S1. Obtain map data of the paddy field, the map data including coordinate data and area data.

[0036] In one embodiment, the target paddy field area is first determined, and the accuracy and scope of the required map data are clarified.

[0037] Furthermore, satellite remote sensing image data of the target area are collected, with priority given to high-resolution images.

[0038] Furthermore, the satellite remote sensing images are preprocessed, including radiometric correction, geometric correction, and noise reduction.

[0039] Furthermore, using image classification algorithms, the preprocessed images are divided into rice paddies and other land cover categories.

[0040] Furthermore, the boundaries of the classified paddy field areas are extracted to generate a vector layer of the paddy field.

[0041] Furthermore, the vector layers are imported into the Geographic Information System (GIS) software.

[0042] Furthermore, in GIS software, projection conversion tools are used to ensure the coordinate system of paddy field data is consistent.

[0043] Furthermore, the area of ​​the paddy field was calculated using the area calculation function of GIS software.

[0044] Furthermore, the coordinate data of the paddy field area is extracted, including the coordinates of the boundary points and the center point.

[0045] Furthermore, the coordinate and area data are verified to ensure the accuracy and consistency of the data.

[0046] S2. Based on the map data, the paddy field is divided into multiple uniform areas using a random sampling algorithm and an expansion algorithm.

[0047] In one embodiment, based on step S1, a dynamic equilibrium region partitioning model is constructed using a random sampling algorithm and an expansion algorithm. The dynamic equilibrium region partitioning model satisfies the following expression:

[0048] ,

[0049] in, For the first In the nth iteration The position of each coordinate point For the first In the nth iteration The position of each coordinate point For the first In the nth iteration The position of each coordinate point This is the iteration step size factor. The area is the preset equilibrium region. For the first In the nth iteration The area of ​​each region for and The distance between them This represents the adjustment range of the coordinate point position. This represents the total number of coordinate points extracted.

[0050] Furthermore, before each iteration, the set of coordinate points obtained in step S1 is randomly sampled to generate a sample point set. It should be noted that the sampling method can be simple random sampling or sampling according to a certain probability distribution, including uniform distribution and normal distribution. The sample point set can be used for coordinate point position adjustment.

[0051] Furthermore, based on the aforementioned set of sampling points, GIS software was used to initially divide the paddy fields into... Each region corresponds to one extracted coordinate point.

[0052] Furthermore, based on the dynamic equilibrium region division model, an iterative process is performed to obtain new coordinate point positions.

[0053] Furthermore, based on the new coordinate point position, check whether the iteration meets the convergence conditions, including whether the deviation between the region area and the preset equilibrium region area is within the allowable range and whether the number of iterations reaches the preset upper limit.

[0054] Specifically, after each iteration, it is checked whether the area of ​​each region is closer to the preset equilibrium area. If the deviation between the area of ​​all regions and the preset equilibrium area is within an acceptable range, then an equilibrium state is considered to have been reached.

[0055] Furthermore, it is determined whether the number of iterations has reached the preset upper limit. If it has, the final coordinate point position is output; if it has not, the iteration continues until the convergence condition is met and the final coordinate point position is output.

[0056] Furthermore, based on the final coordinate point location, GIS software was used to redivide the paddy field area, update the boundary of each area, and obtain multiple uniform paddy field areas.

[0057] It is important to note that this embodiment combines the ideas of random sampling and region expansion, achieving uniform division of the region area through a dynamic equilibrium region partitioning model. This algorithm dynamically adjusts the location and number of sampling points to achieve dynamic equilibrium of the region area.

[0058] Please see Figure 2 , Figure 2 The actual result obtained by dividing paddy fields into regions according to the dynamic equilibrium region division model shows that the square grids are evenly distributed, which reflects the advanced nature of the algorithm.

[0059] S3. Based on the uniform area, obtain soil data and nutrient data of the paddy field; the soil data includes data on soil texture, water content, pH, and electrical conductivity, and the nutrient data includes data on nitrogen, phosphorus, potassium, and organic matter.

[0060] In one embodiment, based on the uniform area divided in step S2, soil data such as soil texture, water content, pH, and electrical conductivity, as well as nutrient data such as nitrogen, phosphorus, potassium, and organic matter, were obtained for the paddy field.

[0061] Specifically, the first step is to prepare a soil sampler, a soil moisture meter, a pH meter, a conductivity meter, and reagent kits or equipment for nutrient analysis.

[0062] Furthermore, within each uniformly divided paddy field area, sampling points were evenly distributed according to the area's size and shape. This ensured that each area had at least a sufficient number of sampling points to represent the soil characteristics of that area.

[0063] Next, soil samples are collected using a soil sampler at the determined sampling locations. It is important to maintain a consistent sampling depth; typically, the topsoil should be sampled at a depth of 0 to 20 centimeters to reflect the soil conditions of the main root zone.

[0064] Furthermore, the location information of each sampling point, as well as factors that may affect soil properties, such as sampling time and weather conditions, are recorded.

[0065] Furthermore, the moisture content of the collected soil samples was determined using a soil moisture meter or an oven-drying method, and the moisture content data for each sample was recorded.

[0066] Furthermore, the pH of the soil samples was measured using a pH meter, and the pH value of each sample was recorded.

[0067] Furthermore, the conductivity of the soil samples was measured using a conductivity meter to reflect the soil salinity, and the conductivity data for each sample was recorded.

[0068] Furthermore, soil samples were sent to the laboratory, where soil texture, such as the proportion of sand, silt, and clay, was analyzed using sieving and hydrometry methods, and soil texture data for each sample were recorded.

[0069] Furthermore, the nitrogen, phosphorus, and potassium contents, as well as the organic matter content, in the soil samples were determined using kits or specialized equipment. Nitrogen content was determined using the Kjeldahl method and ultraviolet spectrophotometry; phosphorus content was determined using the molybdenum blue method and spectrophotometry; potassium content was determined using flame photometry; and organic matter content was determined using the potassium dichromate oxidation-titration method.

[0070] S4. Based on the soil data and the nutrient data, construct a comprehensive assessment model for paddy field areas to comprehensively evaluate the differences in nutrient content and soil characteristics in paddy field areas.

[0071] S4 includes the following steps:

[0072] S41. Based on the nutrient data, construct a nutrient assessment model for paddy field regions to evaluate nutrient differences in paddy field areas.

[0073] In one embodiment, based on the nutrient data obtained in step 3, a nutrient assessment model for paddy field areas is constructed to evaluate nutrient differences in paddy field areas. The nutrient assessment model for paddy field areas satisfies the following expression:

[0074] ,

[0075] in, For the first Nutrient assessment index of each paddy field area For the first The first rice paddy area The standardized values ​​of each nutrient index are obtained by mapping the original data to the specified interval [0, 1] through linear transformation; For the first The first rice paddy area The average of each nutrient index, For the first The first rice paddy area The standard deviation of each nutrient index For the first The first rice paddy area The weights of each nutrient indicator are determined through data analysis methods and must meet the following conditions:

[0076] ,

[0077] S42. Based on the soil data, construct a soil characteristic assessment model for paddy field areas to evaluate the differences in soil characteristics in paddy field areas.

[0078] In one embodiment, based on the soil data obtained in step 3, a soil characteristic assessment model for paddy field areas is constructed to evaluate the differences in soil characteristics in the paddy field areas. The soil characteristic assessment model for paddy field areas satisfies the following expression:

[0079] ,

[0080] in, For the first Soil property assessment index for each paddy field area For the first The first rice paddy area Measured values ​​of soil property indicators, For the first The first rice paddy area The average of each soil characteristic index, For the first The first rice paddy area Standard deviation of each soil property index For the first The first rice paddy area The median of the soil property index, For the first The first rice paddy area The interquartile range of a soil property index, that is, the difference between the third quartile and the first quartile, is used to measure the dispersion of the data. and For the first The first rice paddy area Adjustment parameters corresponding to each soil property index For the first The first rice paddy area The weight parameters corresponding to each soil characteristic index; and stated Used to control various soil properties The degree of impact and the robustness of the data, and satisfying the following conditions: , ;

[0081] when When, it indicates the linear effect;

[0082] when When, it indicates the amplified effect of the difference;

[0083] when When, it indicates the effect of reducing the difference.

[0084] S43. Using the paddy field area nutrient assessment model and the paddy field area soil characteristic assessment model, construct a comprehensive assessment model for paddy field areas to comprehensively assess the differences in nutrient content and soil characteristics.

[0085] In one embodiment, based on steps S41 and S42, a comprehensive assessment model for paddy field areas is constructed to comprehensively evaluate the differences in nutrient content and soil characteristics within the paddy field area. The comprehensive assessment model for paddy field areas satisfies the following expression:

[0086] ,

[0087] in, For the first A comprehensive assessment index of nutrient and soil characteristics in each paddy field area. For the first Nutrient assessment index of each paddy field area For the first Soil property assessment index for each paddy field area , The weighting coefficients reflect the importance of nutrients and soil characteristics in the overall assessment.

[0088] S5. Based on the comprehensive evaluation model of the paddy field area, the uniform area is classified according to the differences in nutrients and soil characteristics to obtain the classified areas.

[0089] In one embodiment, firstly, based on the comprehensive assessment model for paddy field areas, a nutrient difference threshold for the comprehensive assessment index of nutrient and soil characteristics in paddy field areas is set, wherein the nutrient difference threshold is... ;

[0090] Furthermore, a comprehensive evaluation index will be developed. With the A comparison was performed, and the comparison results are as follows:

[0091] when At that time, the first The nutrient content in some rice paddy areas is low;

[0092] when At that time, the first The nutrient content of the rice paddy area is relatively high.

[0093] Furthermore, combining the soil characteristic assessment model for paddy field areas in S42, and using the threshold comparison method described above, the soil characteristics were determined when the nutrient content was low and high, respectively.

[0094] Furthermore, based on the differences in nutrients and soil characteristics, the uniform region is classified to obtain classified regions, which include nutrient-rich regions with excellent soil characteristics, nutrient-rich regions with poor soil characteristics, nutrient-poor regions with excellent soil characteristics, and nutrient-poor regions with poor soil characteristics.

[0095] S6. Based on the aforementioned classification regions, construct a nutrient demand analysis model for paddy fields.

[0096] S6 includes the following steps:

[0097] S61. Based on the classification regions, determine the fertilization priority ranking of the paddy field regions.

[0098] In one embodiment, based on the nutrient-rich and excellent soil characteristics, nutrient-rich but poor soil characteristics, nutrient-poor but excellent soil characteristics, and nutrient-poor and poor soil characteristics areas obtained in step S5, the fertilization priority ranking of the paddy field area is determined as follows:

[0099] Nutrient-poor areas with poor soil properties Nutrient-poor areas with excellent soil properties Nutrient-rich areas with poor soil properties Nutrient-rich areas with excellent soil properties

[0100] It is important to note that the fertilization priority ranking is determined by comprehensively considering the nutrient status and soil characteristics of the paddy field as a whole. The purpose is to initially identify areas requiring focused fertilization. Areas with higher priority require more fertilization than those with lower priority.

[0101] S62. Based on the fertilization priority ranking, construct a nutrient demand analysis model for paddy fields.

[0102] In one embodiment, a paddy field nutrient demand analysis model is constructed based on the fertilization priority ranking determined in step S61. The paddy field nutrient demand analysis model satisfies the following expression:

[0103] ,

[0104] in, For the first The rice paddy area for the first The amount of nutrients required for planting For the first A comprehensive assessment index of nutrient and soil characteristics in each paddy field area. For the first The basic nutrient requirement coefficient reflects the crop's basic nutrient needs. For the first The adjustment coefficient for soil nutrients reflects the impact of soil nutrient content on crop requirements. For the first Recommended application rates of nutrients are determined based on crop type, growth stage, and target yield. For the first A comprehensive assessment index of nutrient and soil characteristics in each paddy field area. The total number of rice paddy areas, For the first The first rice paddy area The assessment index of plant nutrients; The following relationship must be satisfied:

[0105]

[0106] in, For the first The first rice paddy area Standardized values ​​of each nutrient index, For the first The first rice paddy area The average of each nutrient index, For the first The first rice paddy area The standard deviation of each nutrient index.

[0107] It should be noted that the paddy field nutrient demand analysis model can further narrow down the area based on the key fertilization area determined in step S61, and obtain the specific nutrient demand corresponding to specific sub-areas, which is conducive to precise fertilization.

[0108] S7. Based on the paddy field nutrient demand analysis model, construct a paddy field precision fertilization model.

[0109] In one implementation, a precision fertilization model for paddy fields was constructed based on step S62, and the precision fertilization model for paddy fields satisfies the following expression:

[0110] ,

[0111] in, For the first The rice paddy area for the first The amount of fertilizer applied to the plant. For the first The rice paddy area for the first The amount of nutrients required for planting For the first The first in the soil of the paddy field area The current quantity of nutrients, For the first Fertilizer utilization rate of plant nutrients For the first The first type of fertilizer The content of nutrients, For the first Fertilizer in the first Preference coefficients for each paddy field region For the first A comprehensive assessment index of nutrient and soil characteristics in each paddy field area. For the first A comprehensive assessment index of nutrient and soil characteristics in each paddy field area. For the first The first rice paddy area Nutrient assessment index. Among them, Obtained through soil testing. This reflects the proportion of nutrients in the fertilizer actually absorbed by the paddy field, and is determined by factors such as fertilizer type, soil conditions, and climate conditions. The preference coefficient is determined by cost-effectiveness, environmental impact, and soil adaptability. A higher preference coefficient indicates a higher priority. The fertilizer is very suitable for the first A rice paddy area. Therefore, by determining... This allows us to determine the type of fertilizer.

[0112] It should be noted that the precise fertilization model for paddy fields comprehensively considers multiple factors such as the nutrient requirements of paddy fields, the existing nutrient content in the soil, fertilizer utilization rate, nutrient content in fertilizers, and the applicability of fertilizers, aiming to provide precise fertilization recommendations for the specific paddy field areas determined in step S6.

[0113] S8. Using the aforementioned precise fertilization model for paddy fields, the amount of fertilizer to be applied is determined, thereby achieving precise graded fertilization.

[0114] In one embodiment, the precise fertilization model for paddy fields accurately determines the specific amount of a specific fertilizer corresponding to a specific nutrient in a specific area, achieving precise alignment between region, nutrient, fertilizer type, and fertilization amount. The precise alignment or precise fertilization process includes:

[0115] Obtain the fertilization priority ranking for rice paddy areas;

[0116] Based on the fertilization priority ranking, the nutrient requirement for each nutrient in the classification area is determined sequentially.

[0117] The type of fertilizer should be determined based on the stated nutrient requirements;

[0118] The amount of fertilizer to be applied shall be determined based on the type of fertilizer and the required nutrient levels.

[0119] Based on the amount of fertilizer applied and the fertilization priority ranking, precise graded fertilization is carried out.

[0120] It is important to note that for high-priority areas, the precision fertilization model for paddy fields should be used first to determine nutrients, fertilizer types, and fertilizer amounts.

[0121] Compared with existing technologies, this invention has the following significant advantages: First, it realizes the refined division and dynamic equilibrium management of paddy field areas, improving the accuracy and efficiency of nutrient monitoring; second, it constructs a comprehensive and objective integrated assessment model for paddy field areas, providing a scientific basis for precise management and optimized layout; third, it achieves precise quantification and precise fertilization of paddy field nutrient requirements, significantly improving fertilizer utilization and reducing nutrient loss and environmental pollution; fourth, it provides the ability for real-time monitoring and dynamic adjustment, accurately predicting and responding to real-time changes in paddy field nutrient requirements, providing strong support for sustainable paddy field production and environmental protection.

[0122] Please see Figure 3 , Figure 3This is a schematic diagram of the structure of a precision fertilization system based on real-time monitoring of paddy field nutrients in an embodiment of the present invention. The system includes an input device, a processor, an output device, and a memory. The input device, processor, output device, and memory are interconnected. The memory stores a computer program, which includes program instructions. The processor is configured to call the program instructions. The system uses the precision fertilization method based on real-time monitoring of paddy field nutrients, and its specific operation flow is as follows: Figure 4 As shown.

[0123] In this embodiment, the input device includes a data acquisition module and a user interface. The data acquisition module includes a multi-parameter nutrient sensor and a multi-parameter soil characteristic sensor, used to collect data on the nutrient content and soil characteristic parameters of paddy field soil in real time. The user interface is used to input additional non-collection parameters.

[0124] The processor is the core component of the system, consisting of a high-performance microprocessor, including a data processing unit, a control unit, and a communication interface. It is used to receive data transmitted from input devices, perform real-time processing and analysis; calculate the nutrient requirements of paddy field soil according to preset algorithms and models, and generate precise fertilization suggestions; and control the operation of output devices and data exchange with memory.

[0125] The output device mainly consists of a fertilization control system, a touch screen control system, and an alarm device. The fertilization control system is connected to the processor via wires, receives fertilization commands, and controls the fertilization operation; the touch screen control system is used to display soil nutrient data and fertilization suggestions; the alarm device is used to issue an alarm when soil nutrient levels are abnormal or the fertilization system malfunctions.

[0126] The memory uses a high-speed solid-state drive, which features fast read and write speeds, large capacity, and high reliability. It is mainly used to store data acquired by input devices and the result data after processing by the processor, and can meet the needs of storing large amounts of data.

[0127] In summary, this invention provides a precision fertilization method based on real-time monitoring of paddy field nutrients. By utilizing random sampling and expansion algorithms, combined with paddy field map data, the paddy field area is uniformly divided, effectively improving the precision and efficiency of paddy field management and ensuring the accuracy of nutrient demand analysis. By constructing a comprehensive assessment model for paddy field areas, the differences in paddy field nutrients and soil characteristics are fully evaluated, providing a scientific basis for precision fertilization. Furthermore, by constructing and utilizing the paddy field nutrient demand analysis model and the paddy field precision fertilization model for precise graded fertilization, not only is fertilizer utilization significantly improved, nutrient loss and environmental pollution reduced, but sustainable paddy field production is also promoted, providing strong support for green agricultural development.

[0128] This invention provides a precision fertilization system based on real-time monitoring of paddy field nutrients. By monitoring the nutrient content in the paddy field in real time, the system can quickly adjust the fertilization plan to ensure that the paddy field receives just the right amount of nutrients. This avoids the waste and environmental pollution caused by nutrient excess, as well as the crop growth stagnation caused by nutrient deficiency, thereby improving the efficiency and precision of fertilization. Fertilizing according to the actual nutrient needs of the paddy field avoids the blind and excessive application of traditional fertilization methods. This not only significantly improves fertilizer utilization and reduces nutrient loss, but also lowers production costs and increases the economic benefits of agricultural production. Precision fertilization reduces the excessive use of chemical fertilizers, reduces the risk of soil and water pollution, helps maintain the balance of the paddy field ecosystem, promotes soil health, and lays a solid foundation for the long-term sustainable development of agriculture.

[0129] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A precision fertilization method based on real-time monitoring of nutrient levels in paddy fields, characterized in that, The method includes the following steps: Obtain map data of the paddy field, the map data including coordinate data and area data; Based on the map data, the paddy field was divided into multiple uniform areas using a random sampling algorithm and an expansion algorithm. Based on the uniform region, soil and nutrient data of the paddy field are obtained; the soil data includes data on soil texture, water content, pH, and electrical conductivity, and the nutrient data includes data on nitrogen, phosphorus, potassium, and organic matter; Based on the soil data and the nutrient data, a comprehensive assessment model for paddy field areas is constructed to comprehensively evaluate the differences in nutrient and soil characteristics in paddy field areas. Based on the comprehensive assessment model of the paddy field area, the uniform area is classified according to the differences in nutrients and soil characteristics to obtain classified areas; Based on the aforementioned classification regions, a nutrient demand analysis model for paddy fields is constructed, which satisfies the following expression: ， in, For the first The rice paddy area for the first The amount of nutrients required for planting For the first A comprehensive assessment index of nutrient and soil characteristics in each paddy field area. For the first The basic nutrient requirement coefficient for planting For the first Adjustment coefficient for seed nutrients, For the first Recommended application rate of nutrients. For the first A comprehensive assessment index of nutrient and soil characteristics in each paddy field area. The total number of rice paddy areas, For the first The first rice paddy area Nutrient assessment index; Based on the aforementioned paddy field nutrient requirement analysis model, a precision fertilization model for paddy fields is constructed, which satisfies the following expression: ， in, For the first The rice paddy area for the first The amount of fertilizer applied to the plant. For the first The rice paddy area for the first The amount of nutrients required for planting For the first The first in the soil of the paddy field area The current quantity of nutrients, For the first Fertilizer utilization rate of plant nutrients, For the first The first type of fertilizer The content of nutrients, For the first Fertilizer in the first Preference coefficients for each paddy field region For the first A comprehensive assessment index of nutrient and soil characteristics in each paddy field area. For the first A comprehensive assessment index of nutrient and soil characteristics in each paddy field area. For the first The first rice paddy area Nutrient assessment index; The precise fertilization model for paddy fields determines the specific amount of fertilizer to be applied for specific nutrients in specific regions, thus achieving a connection between region, nutrient, fertilizer type, and fertilizer amount. This connection process includes: Obtain the fertilization priority ranking of the paddy field area; determine the nutrient requirements of the classified area based on the fertilization priority ranking; determine the fertilizer type according to the nutrient requirements; determine the fertilizer amount according to the fertilizer type and the nutrient requirements; and perform graded fertilization according to the fertilizer amount and the fertilization priority ranking.

2. The precision fertilization method based on real-time monitoring of paddy field nutrients according to claim 1, characterized in that, The process of dividing the paddy field into multiple uniform regions based on the map data, using a random sampling algorithm and an expansion algorithm, includes: Based on the map data, a dynamic equilibrium region partitioning model is constructed using random sampling and expansion algorithms; The dynamic equilibrium region division model is used to divide the paddy field into multiple uniform regions.

3. The precision fertilization method based on real-time monitoring of paddy field nutrients according to claim 2, characterized in that, The dynamic equilibrium region partitioning model satisfies the following expression: ， in, For the first In the nth iteration The position of each coordinate point For the first In the nth iteration The position of each coordinate point For the first In the nth iteration The position of each coordinate point This is the iteration step size factor. The area is the preset equilibrium region. For the first In the nth iteration The area of ​​each region for and The distance between them This represents the adjustment range of the coordinate point position. This represents the total number of coordinate points extracted.

4. The precision fertilization method based on real-time monitoring of paddy field nutrients according to claim 1, characterized in that, The comprehensive assessment model for paddy field areas, constructed based on the soil data and the nutrient data, for comprehensively evaluating the differences in nutrient content and soil characteristics in paddy field areas includes: Based on the soil data and the nutrient data, a nutrient assessment model for paddy field areas is constructed to evaluate the differences in nutrient content in paddy field areas. Based on the soil data and nutrient data, a soil characteristic assessment model for paddy field areas is constructed to evaluate the differences in soil characteristics in paddy field areas. By using the aforementioned paddy field nutrient assessment model and the aforementioned paddy field soil characteristic assessment model, a comprehensive assessment model for paddy field regions is constructed to comprehensively evaluate the differences in nutrient content and soil characteristics within the paddy field regions.

5. The precision fertilization method based on real-time monitoring of paddy field nutrients according to claim 4, characterized in that, The nutrient assessment model for paddy field areas satisfies the following expression: ， in, For the first Nutrient assessment index of each paddy field area For the first The first rice paddy area Standardized values ​​of each nutrient index, For the first The first rice paddy area The average of each nutrient index, For the first The first rice paddy area The standard deviation of each nutrient index For the first The first rice paddy area The weights of each nutrient index; the soil characteristic assessment model for the paddy field area satisfies the following expression: ， in, For the first Soil property assessment index for each paddy field area For the first The first rice paddy area Measured values ​​of soil property indicators, For the first The first rice paddy area The average of each soil characteristic index, For the first The first rice paddy area Standard deviation of each soil property index For the first The first rice paddy area The median of the soil property index, For the first The first rice paddy area Interquartile range of soil property indicators and For the first The first rice paddy area Adjustment parameters corresponding to each soil property index For the first The first rice paddy area The weight parameters corresponding to each soil characteristic index; the comprehensive evaluation model for the paddy field area satisfies the following expression: ， in, For the first A comprehensive assessment index of nutrient and soil characteristics in each paddy field area. For the first Nutrient assessment index of each paddy field area For the first Soil property assessment index for each paddy field area , These are the weighting coefficients.

6. The precision fertilization method based on real-time monitoring of paddy field nutrients according to claim 1, characterized in that, The process of classifying the homogeneous area according to differences in nutrients and soil properties based on the comprehensive assessment model of the paddy field area to obtain classified areas includes: Based on the comprehensive assessment model for paddy field areas, a nutrient difference threshold is set for the comprehensive assessment index of nutrient and soil characteristics in paddy field areas; The comprehensive evaluation index of nutrient and soil characteristics in the paddy field area is compared with the nutrient difference threshold to determine the nutrient-rich area and the nutrient-poor area; Based on the nutrient-rich areas and the nutrient-poor areas, and combined with the paddy field area soil characteristic assessment model, areas with nutrient-rich soil and excellent soil characteristics, areas with nutrient-rich soil but poor soil characteristics, areas with nutrient-poor soil but excellent soil characteristics, and areas with nutrient-poor soil and poor soil characteristics are identified.

7. The precision fertilization method based on real-time monitoring of paddy field nutrients according to claim 1, characterized in that, The construction of the paddy field nutrient demand analysis model based on the aforementioned classification regions includes: Based on the aforementioned classification regions, the fertilization priority ranking for paddy field areas is determined as follows: Areas with poor nutrient content and unfavorable soil properties > Areas with poor nutrient content but excellent soil properties > Areas with abundant nutrient content but unfavorable soil properties > Areas with abundant nutrient content and excellent soil properties; Based on the fertilization priority ranking, a nutrient demand analysis model for paddy fields is constructed.

8. A precision fertilization system based on real-time monitoring of paddy field nutrients, wherein the system uses the precision fertilization method based on real-time monitoring of paddy field nutrients as described in any one of claims 1 to 7, characterized in that, The system includes an input device, a processor, an output device, and a memory, which are interconnected. The memory stores a computer program, which includes program instructions, and the processor is configured to invoke the program instructions.

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