Continuous cropping obstacle repair ecological fertilizer application effect intelligent monitoring system

Abstract

The application discloses a kind of continuous cropping obstacle repair ecological fertilizer application effect intelligent monitoring systems, comprising: soil parameter acquisition module, crop growth monitoring module, repair effect evaluation module, comprehensive determination module, early warning output module.The application realizes the multi-source data synchronous acquisition of soil physical and chemical parameters and crop growth parameters by soil parameter acquisition module and crop growth monitoring module, overcomes the limitations of traditional single parameter monitoring, and the repair effect evaluation module divides the long-period repair process into multiple evaluation sub-periods based on the preset evaluation period division rule and calculates the repair effect evaluation value of single period, realizes the quantitative segmented evaluation of repair process, so that the change trend of repair effect can be traced back and analyzed.

Description

Technical Field

[0001] This invention relates to the field of agricultural monitoring system technology, specifically to an intelligent monitoring system for the application effect of ecological fertilizer for continuous cropping obstacle repair. Background Technology

[0002] Continuous cropping obstacles refer to the phenomenon where, after the same crop is continuously planted in the same plot for many years, the soil's physical and chemical properties deteriorate, the microbial community becomes unbalanced, and soil-borne diseases become more severe, leading to stunted crop growth and reduced yield and quality. Organic fertilizers, containing organic matter and beneficial microorganisms, can improve soil structure, regulate soil pH, and increase soil nutrient availability, making them one of the important means of repairing soils with continuous cropping obstacles.

[0003] However, the effectiveness of organic fertilizer application is affected by a combination of factors, including initial soil conditions, organic fertilizer formula, application amount, application method, and climate conditions. The restoration process varies significantly among different fields and crops, making it difficult to determine whether restoration is complete using a uniform fixed time point.

[0004] Currently, the evaluation of the effect of ecological fertilizer application on the repair of continuous cropping obstacles mainly relies on two methods: regular manual sampling and testing, and visual observation in the field.

[0005] Manual sampling and testing requires multiple trips to the field to collect soil samples and send them to the laboratory for analysis during the remediation period. This process is time-consuming, costly, and lacks timeliness, making it impossible to reflect the dynamic changes in the remediation effect in a timely manner. Visual observation in the field relies on the experience of the growers to judge the growth of crops and the appearance of the soil. This process is highly subjective, has low accuracy, and makes it difficult to quantify the true level of remediation effect.

[0006] While there are some existing soil moisture monitoring devices and crop growth monitoring devices, most of them only collect and display single parameters. They lack a systematic evaluation mechanism that integrates and analyzes multi-source soil parameters with crop growth parameters, and even more so, they lack a closed-loop monitoring scheme that can automatically determine the completion point of restoration and provide precise fertilization recommendations. Summary of the Invention

[0007] To address this, the present invention provides an intelligent monitoring system for the application effect of ecological fertilizer in the restoration of continuous cropping obstacles. This system solves the problems of existing technologies, which mostly only collect and display single parameters, lack a systematic evaluation mechanism that integrates and analyzes multi-source soil parameters and crop growth parameters, and lack a closed-loop monitoring scheme that can automatically determine the restoration completion point and provide precise fertilization suggestions.

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] A smart monitoring system for the application effect of ecological fertilizer for continuous cropping obstacle repair includes:

[0010] The soil parameter acquisition module is used to deploy multiple sensor nodes in the target field according to a preset spatial distribution scheme. Each sensor node collects soil physical parameters and soil chemical parameters before and after the continuous cropping obstacle repair at a set acquisition cycle. The soil physical parameters include soil temperature, soil moisture and soil electrical conductivity. The soil chemical parameters include soil pH value, soil organic matter content, soil available nitrogen content, soil available phosphorus content and soil available potassium content.

[0011] The crop growth monitoring module is used to acquire canopy images of crops in the target field through image acquisition equipment, extract the normalized vegetation index and crop coverage based on the canopy images, and record crop plant height and crop stem diameter.

[0012] The remediation effect evaluation module receives the soil parameter sequence output by the soil parameter acquisition module and the crop growth parameter sequence output by the crop growth monitoring module. Based on a preset evaluation period division rule, it divides the monitoring period into multiple evaluation sub-periods. At the end of each evaluation sub-period, it calculates the single-period remediation effect evaluation value, which is calculated according to the following formula:

[0013] E_i=α×(S_i / S_0)+β×(G_i / G_0)

[0014] Where E_i is the single-period remediation effect evaluation value of the i-th evaluation sub-period, S_i is the soil comprehensive index at the end of the i-th evaluation sub-period, S_0 is the soil comprehensive index before remediation, G_i is the crop comprehensive index at the end of the i-th evaluation sub-period, G_0 is the crop comprehensive index before remediation, α and β are weighting coefficients, and α+β=1.

[0015] The comprehensive judgment module is used to compare the single-period repair effect evaluation value of each evaluation sub-period with the preset repair effect threshold. When the single-period repair effect evaluation value of N consecutive evaluation sub-periods is greater than or equal to the preset repair effect threshold, a repair compliance signal is generated; otherwise, a continue monitoring signal is generated.

[0016] The early warning output module is used to receive the repair compliance signal or the continued monitoring signal output by the comprehensive judgment module, and send a repair completion notification to the user terminal according to the repair compliance signal, or send a suggestion to the user terminal to continue applying ecological fertilizer according to the continued monitoring signal.

[0017] Preferably, the soil parameter acquisition module further includes a sensor node self-checking unit and an abnormal data removal unit. The sensor node self-checking unit is used to detect the working status of each sensor node before the start of each acquisition cycle. When an abnormal sensor node is detected, a node abnormality mark is generated. The abnormal data removal unit is used to remove the abnormal data collected by the corresponding sensor node in the current acquisition cycle according to the node abnormality mark, and to fill in the missing data by interpolation based on the valid data of adjacent sensor nodes in the same acquisition cycle.

[0018] Preferably, the comprehensive soil index is calculated according to the following formula:

[0019] S_i=w_1×(pH_{i} / pH_{std})+w_2×(OM_{i} / OM_{std})+w_3×(N_{i} / N_{st d})+w_4×(P_{i} / P_{std})+w_5×(K_{i} / K_{std})+w_6×(EC_{i} / EC_{std})

[0020] Wherein, S_i is the soil comprehensive index at the end of the i-th evaluation sub-period, pH_{i} is the measured soil pH value at the end of the i-th evaluation sub-period, pH_{std} is the standard soil pH value, OM_{i} is the measured soil organic matter content at the end of the i-th evaluation sub-period, OM_{std} is the standard soil organic matter content, N_{i} is the measured soil available nitrogen content at the end of the i-th evaluation sub-period, N_{std} is the standard soil available nitrogen content, and P_{i} is the soil organic matter content at the end of the i-th evaluation sub-period. The measured values ​​of available phosphorus content in the soil at the end of each evaluation sub-period, P_{std} is the standard value of available phosphorus content in the soil, K_{i} is the measured value of available potassium content in the soil at the end of the i-th evaluation sub-period, K_{std} is the standard value of available potassium content in the soil, EC_{i} is the measured value of electrical conductivity in the soil at the end of the i-th evaluation sub-period, EC_{std} is the standard value of electrical conductivity in the soil, and w_1 to w_6 are the weight coefficients of each indicator, and w_1+w_2+w_3+w_4+w_5+w_6=1.

[0021] Preferably, the crop comprehensive index is calculated according to the following formula:

[0022] G_i=v_1×(NDVI_{i} / NDVI_0)+v_2×(CC_{i} / CC_0)+v_3×(H_{i} / H_0)+v_4×(D_{i} / D_0)

[0023] Wherein, G_i is the crop composite index at the end of the i-th evaluation sub-period, NDVI_{i} is the measured value of the crop normalized vegetation index at the end of the i-th evaluation sub-period, NDVI_0 is the initial value of the crop normalized vegetation index before restoration, CC_{i} is the measured value of the crop cover at the end of the i-th evaluation sub-period, CC_0 is the initial value of the crop cover before restoration, H_{i} is the measured value of the crop plant height at the end of the i-th evaluation sub-period, H_0 is the initial value of the crop plant height before restoration, D_{i} is the measured value of the crop stem diameter at the end of the i-th evaluation sub-period, D_0 is the initial value of the crop stem diameter before restoration, v_1 ​​to v_4 are the weight coefficients of each index, and v_1+v_2+v_3+v_4=1.

[0024] Preferably, the repair effect evaluation module further includes a trend analysis unit, which is used to fit a repair effect change trend curve based on the single-period repair effect evaluation value of each evaluation sub-period, and predict the number of remaining evaluation sub-periods required to reach the preset repair effect threshold based on the repair effect change trend curve, and send the number of remaining evaluation sub-periods to the early warning output module, which includes the number of remaining evaluation sub-periods in the suggestion information for continuing to apply ecological fertilizer and sends it to the user terminal.

[0025] Preferably, the early warning output module further includes a graded early warning unit, which is used to determine the early warning level based on the ratio of the difference between the single-period repair effect evaluation value and the preset repair effect threshold. When the ratio of the difference is less than a first preset ratio, a level one early warning message is output; when the ratio of the difference is greater than or equal to the first preset ratio and less than a second preset ratio, a level two early warning message is output; and when the ratio of the difference is greater than or equal to the second preset ratio, a level three early warning message is output. The level one, level two, and level three early warning messages correspond to different recommended fertilizer application adjustment schemes.

[0026] Preferably, the preset spatial layout scheme involves uniformly arranging sensor nodes in the target field using a grid layout method. The grid spacing is determined based on the area and topography of the target field. Each sensor node is assigned a unique node number. The soil parameter acquisition module marks and stores the acquired soil parameter sequences according to the node numbers. Before calculating the single-period remediation effect evaluation value, the remediation effect evaluation module performs an arithmetic mean processing on the soil parameter sequences of each sensor node within the same evaluation sub-period according to the node numbers to obtain representative values ​​for each soil parameter in each evaluation sub-period.

[0027] Preferably, the soil parameter acquisition module further includes an adaptive acquisition cycle adjustment unit. The adaptive acquisition cycle adjustment unit is used to dynamically adjust the acquisition cycle of the current assessment sub-period based on the difference between the single-period remediation effect evaluation value of the previous assessment sub-period and the preset remediation effect threshold. When the difference is less than a first difference threshold, the acquisition cycle is adjusted to a first cycle value. When the difference is greater than or equal to the first difference threshold and less than a second difference threshold, the acquisition cycle is adjusted to a second cycle value. When the difference is greater than or equal to the second difference threshold, the acquisition cycle is adjusted to a third cycle value, wherein the first cycle value is less than the second cycle value, and the second cycle value is less than the third cycle value.

[0028] Preferably, the remediation effect evaluation module further includes an abnormal fluctuation detection unit. This unit calculates the rate of change of the soil composite index between two adjacent evaluation sub-periods. When the rate of change exceeds a preset rate of change threshold, an abnormal fluctuation marker is generated, and the soil parameter sequence within the evaluation sub-period corresponding to the abnormal fluctuation marker is marked as data to be reviewed. The abnormal fluctuation detection unit determines the rate of change according to the following rules:

[0029] R_i=|(S_i-S_{i-1}) / S_{i-1}|

[0030] Wherein, R_i is the rate of change of the soil comprehensive index of the i-th evaluation sub-period relative to the (i-1)-th evaluation sub-period. When R_i is greater than the preset rate of change threshold, the abnormal fluctuation marker is generated.

[0031] The present invention has the following advantages: The present invention realizes the synchronous acquisition of multi-source data of soil physicochemical parameters and crop growth parameters through the soil parameter acquisition module and the crop growth monitoring module, which overcomes the limitations of traditional single parameter monitoring. The remediation effect evaluation module divides the long-term remediation process into multiple evaluation sub-periods based on the preset evaluation period division rules and calculates the remediation effect evaluation value of a single period, realizing the quantitative segmented evaluation of the remediation process, and making the trend of remediation effect change traceable and analyzable.

[0032] The comprehensive judgment module continuously compares the evaluation values ​​of each sub-period with preset thresholds. Only when multiple consecutive sub-periods meet the standards will a repair compliance signal be generated, which effectively avoids misjudgment caused by single data fluctuations and improves the reliability of the judgment results.

[0033] The early warning output module sends differentiated suggestions to users based on different evaluation results, realizing a complete closed loop from data collection and effect evaluation to decision-making suggestions, providing reliable technical support for the precise application of ecological fertilizer and the efficient management of the continuous cropping obstacle repair process. Attached Figure Description

[0034] To more intuitively illustrate the prior art and this application, exemplary drawings are provided below. It should be understood that the specific shapes and structures shown in the drawings should not generally be regarded as limiting conditions for implementing this application; for example, based on the technical concept disclosed in this application and the exemplary drawings, those skilled in the art are able to easily make conventional adjustments or further optimizations to the addition / reduction / classification, specific shapes, positional relationships, connection methods, size ratios, etc. of certain units (components).

[0035] Figure 1 A block diagram of an intelligent monitoring system for the application effect of ecological fertilizer for continuous cropping obstacle repair provided in an embodiment of this application. Detailed Implementation

[0036] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. It should be understood that these embodiments are merely for further explanation of the present invention and should not be construed as limiting the scope of protection of the present invention. Technical engineers in the field can make some non-essential improvements and adjustments to the present invention based on the above-described content. 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.

[0037] Please see Figure 1 A smart monitoring system for the application effect of ecological fertilizer for continuous cropping obstacle repair includes:

[0038] The soil parameter acquisition module is used to deploy multiple sensor nodes in the target field according to a preset spatial distribution scheme. Each sensor node collects soil physical parameters and soil chemical parameters before and after the continuous cropping obstacle repair at a set acquisition cycle. The soil physical parameters include soil temperature, soil moisture and soil electrical conductivity. The soil chemical parameters include soil pH value, soil organic matter content, soil available nitrogen content, soil available phosphorus content and soil available potassium content.

[0039] The crop growth monitoring module is used to acquire canopy images of crops in the target field through image acquisition equipment, extract the normalized vegetation index and crop coverage based on the canopy images, and record crop plant height and crop stem diameter.

[0040] The remediation effect evaluation module receives the soil parameter sequence output by the soil parameter acquisition module and the crop growth parameter sequence output by the crop growth monitoring module. Based on a preset evaluation period division rule, it divides the monitoring period into multiple evaluation sub-periods. At the end of each evaluation sub-period, it calculates the single-period remediation effect evaluation value, which is calculated according to the following formula:

[0041] E_i=α×(S_i / S_0)+β×(G_i / G_0)

[0042] Where E_i is the single-period remediation effect evaluation value of the i-th evaluation sub-period, S_i is the soil comprehensive index at the end of the i-th evaluation sub-period, S_0 is the soil comprehensive index before remediation, G_i is the crop comprehensive index at the end of the i-th evaluation sub-period, G_0 is the crop comprehensive index before remediation, α and β are weighting coefficients, and α+β=1.

[0043] The comprehensive judgment module is used to compare the single-period repair effect evaluation value of each evaluation sub-period with the preset repair effect threshold. When the single-period repair effect evaluation value of N consecutive evaluation sub-periods is greater than or equal to the preset repair effect threshold, a repair compliance signal is generated; otherwise, a continue monitoring signal is generated.

[0044] The early warning output module is used to receive the repair compliance signal or the continued monitoring signal output by the comprehensive judgment module, and send a repair completion notification to the user terminal according to the repair compliance signal, or send a suggestion to the user terminal to continue applying ecological fertilizer according to the continued monitoring signal.

[0045] This embodiment provides an intelligent monitoring system for the application effect of ecological fertilizer for the restoration of continuous cropping obstacles. The system includes a soil parameter acquisition module, a crop growth monitoring module, a restoration effect evaluation module, a comprehensive judgment module, and an early warning output module.

[0046] I. Soil Parameter Acquisition Module

[0047] The soil parameter acquisition module is used to deploy multiple sensor nodes in the target field according to a preset spatial distribution scheme. The preferred preset spatial distribution scheme is to evenly arrange the sensor nodes in the target field using a grid method, with the grid spacing determined based on the area and topography of the target field. For example, for regular fields smaller than 10 mu (approximately 1.65 acres), the grid spacing can be set to 10 meters × 10 meters; for larger fields or fields with complex topography, the grid spacing can be appropriately increased or the distribution density increased. Each sensor node is assigned a unique node number for data traceability and management.

[0048] Each sensor node collects soil physical and chemical parameters before and after the replanting obstacle restoration at a set acquisition cycle. Soil physical parameters include soil temperature, soil moisture, and soil electrical conductivity; soil chemical parameters include soil pH, soil organic matter content, soil available nitrogen content, soil available phosphorus content, and soil available potassium content. The sensor nodes can employ multi-parameter soil sensor integration devices, capable of simultaneously measuring multiple parameters.

[0049] The sensor nodes are also equipped with a self-testing unit and an abnormal data removal unit. The self-testing unit checks the operating status of each sensor node before the start of each acquisition cycle, generating an abnormal node marker when an abnormality is detected. The abnormal data removal unit removes the abnormal data collected by the corresponding sensor node in the current acquisition cycle based on the abnormal node marker, and then uses interpolation to fill in the missing data based on the valid data from adjacent sensor nodes within the same acquisition cycle. The interpolation method can use inverse distance weighted interpolation or Kriging interpolation to ensure the integrity and continuity of the data sequence.

[0050] The soil parameter acquisition module marks and stores the collected soil parameter sequences according to the node number. Before calculating the remediation effect evaluation value for a single time period, the remediation effect evaluation module performs arithmetic mean processing on the soil parameter sequences of each sensor node within the same evaluation sub-time period according to the node number to obtain the representative value of each soil parameter in each evaluation sub-time period.

[0051] The data acquisition period can be set to adaptive adjustment. The adaptive adjustment unit dynamically adjusts the acquisition period of the current evaluation sub-period based on the difference between the single-period repair effect evaluation value of the previous evaluation sub-period and the preset repair effect threshold. When the difference is less than the first difference threshold, the acquisition period is adjusted to the first period value (e.g., 2 hours); when the difference is greater than or equal to the first difference threshold but less than the second difference threshold, the acquisition period is adjusted to the second period value (e.g., 6 hours); when the difference is greater than or equal to the second difference threshold, the acquisition period is adjusted to the third period value (e.g., 12 hours). The first period value is less than the second period value, and the second period value is less than the third period value. This adaptive adjustment mechanism can increase the acquisition frequency when the repair is close to meeting the target, improving monitoring accuracy, and reduce the acquisition frequency when the difference is large in the early stage of repair, saving energy consumption and data storage resources.

[0052] II. Crop Growth Monitoring Module

[0053] The crop growth monitoring module is used to acquire images of the crop canopy within the target field using image acquisition equipment. The image acquisition equipment can be a multispectral camera fixed in the field or a high-resolution camera mounted on a drone. The preferred acquisition time is between 10:00 AM and 2:00 PM on a sunny day to ensure consistent lighting conditions.

[0054] The Normalized Differential Vegetation Index (NDVI) and crop cover (CC) were extracted from canopy images. The NDVI was calculated based on reflectance in the near-infrared and red light bands, using the formula NDVI = (NIR - RED) / (NIR + RED), where NIR is the near-infrared reflectance and RED is the red light reflectance. Crop cover was obtained by extracting the proportion of green vegetation pixels to the total number of pixels using an image segmentation algorithm.

[0055] The crop growth monitoring module also records crop plant height (H) and crop stem diameter (D). Plant height can be obtained by conversion using the scale of a reference object in the image, or by measurement assisted by a laser rangefinder; stem diameter is measured at a fixed position at the base of the crop stem using vernier calipers. These parameters are measured once before restoration as initial values, and periodically during the restoration process according to the evaluation sub-periods.

[0056] III. Repair Effectiveness Evaluation Module

[0057] The remediation effect evaluation module receives the soil parameter sequence output by the soil parameter acquisition module and the crop growth parameter sequence output by the crop growth monitoring module, and divides the monitoring period into multiple evaluation sub-periods based on the preset evaluation period division rules.

[0058] The evaluation period can be determined based on the application cycle of the organic fertilizer and the growth cycle of the crop. For example, for a crop with a growth period of 120 days, each 10 days can be divided into an evaluation sub-period, for a total of 12 sub-periods; alternatively, based on the expected onset time of the organic fertilizer, the first 3 sub-periods can be set as the initiation period, the middle 6 sub-periods as the stabilization period, and the last 3 sub-periods as the verification period.

[0059] At the end of each assessment sub-period, the single-period repair effectiveness evaluation value is calculated. The single-period repair effectiveness evaluation value is calculated according to the following formula:

[0060] E_i=α×(S_i / S_0)+β×(G_i / G_0)

[0061] Where E_i is the single-period remediation effect evaluation value of the i-th evaluation sub-period, S_i is the soil comprehensive index at the end of the i-th evaluation sub-period, S_0 is the soil comprehensive index before remediation, G_i is the crop comprehensive index at the end of the i-th evaluation sub-period, G_0 is the crop comprehensive index before remediation, α and β are weighting coefficients, and α+β=1. The specific values ​​of α and β can be determined according to the crop type and soil conditions. For example, for a remediation scenario with soil improvement as the main goal, α can be set to 0.6 and β can be set to 0.4; for a scenario with crop yield increase as the main goal, α can be set to 0.4 and β can be set to 0.6.

[0062] The comprehensive soil index is calculated using the following formula:

[0063] S_i=w_1×(pH_{i} / pH_{std})+w_2×(OM_{i} / OM_{std})+w_3×(N_{i} / N_{st d})+w_4×(P_{i} / P_{std})+w_5×(K_{i} / K_{std})+w_6×(EC_{i} / EC_{std})

[0064] Wherein, S_i is the soil comprehensive index at the end of the i-th evaluation sub-period, pH_{i} is the measured soil pH value at the end of the i-th evaluation sub-period, pH_{std} is the standard soil pH value, OM_{i} is the measured soil organic matter content at the end of the i-th evaluation sub-period, OM_{std} is the standard soil organic matter content, N_{i} is the measured soil available nitrogen content at the end of the i-th evaluation sub-period, N_{std} is the standard soil available nitrogen content, and P_{i} is the soil organic matter content at the end of the i-th evaluation sub-period. The measured values ​​of available phosphorus content in the soil at the end of each evaluation sub-period are given, where P_{std} is the standard value of available phosphorus content, K_{i} is the measured value of available potassium content in the soil at the end of the i-th evaluation sub-period, and EC_{i} is the measured value of electrical conductivity in the soil at the end of the i-th evaluation sub-period, with EC_{std} being the standard value of electrical conductivity. w_1 to w_6 are the weighting coefficients for each indicator, and w_1+w_2+w_3+w_4+w_5+w_6=1. The values ​​of each weighting coefficient can be determined based on the nutrient requirements of the target crop and the type of soil obstacles. For example, for acidified soils, the weight of pH can be appropriately increased; for infertile soils, the weights of organic matter and available nutrients can be appropriately increased.

[0065] The crop composite index is calculated using the following formula:

[0066] G_i=v_1×(NDVI_{i} / NDVI_0)+v_2×(CC_{i} / CC_0)+v_3×(H_{i} / H_0)+v_4×(D_{i} / D_0)

[0067] Wherein, G_i is the crop composite index at the end of the i-th evaluation sub-period, NDVI_{i} is the measured value of the normalized vegetation index (NDVI) at the end of the i-th evaluation sub-period, NDVI_0 is the initial value of the normalized vegetation index before restoration, CC_{i} is the measured value of crop cover at the end of the i-th evaluation sub-period, CC_0 is the initial value of crop cover before restoration, H_{i} is the measured value of crop height at the end of the i-th evaluation sub-period, H_0 is the initial value of crop height before restoration, D_{i} is the measured value of crop stem diameter at the end of the i-th evaluation sub-period, D_0 is the initial value of crop stem diameter before restoration, and v_1 to v_4 are the weight coefficients of each index, and v_1+v_2+v_3+v_4=1. The values ​​of each weight coefficient can be determined according to the sensitivity of different crops to various growth parameters.

[0068] The repair effectiveness evaluation module also includes a trend analysis unit. This unit fits a trend curve of repair effectiveness changes based on the single-period repair effectiveness evaluation values ​​for each evaluation sub-period. The fitting method can be either least squares linear fitting or polynomial fitting. Based on the trend curve of repair effectiveness changes, it predicts the number of remaining evaluation sub-periods required to reach the preset repair effectiveness threshold and sends this number to the early warning output module.

[0069] The remediation effectiveness evaluation module also includes an abnormal fluctuation detection unit. This unit calculates the rate of change of the soil composite index between two adjacent evaluation sub-periods, and the rate of change is determined according to the following rules:

[0070] R_i=|(S_i-S_{i-1}) / S_{i-1}|

[0071] Where R_i represents the rate of change of the soil composite index in the i-th evaluation sub-period relative to the (i-1)-th evaluation sub-period. When R_i exceeds a preset rate of change threshold, an abnormal fluctuation marker is generated, and the soil parameter sequence within the evaluation sub-period corresponding to the abnormal fluctuation marker is marked as data to be reviewed. The preset rate of change threshold can be determined based on the statistical distribution of historical monitoring data, for example, set to twice the standard deviation of the mean of the historical data rate of change. The abnormal fluctuation marker prompts the user to check the data within that period to eliminate interference from accidental factors such as sensor malfunctions and sudden environmental changes.

[0072] IV. Comprehensive Judgment Module

[0073] The comprehensive judgment module is used to compare the single-period remediation effect evaluation value of each evaluation sub-period with the preset remediation effect threshold. The preset remediation effect threshold can be determined based on the soil conditions required for the normal growth of the target crop and historical high-yield data, for example, it can be set to 0.85.

[0074] When the single-period repair effect evaluation value of N consecutive evaluation sub-periods is greater than or equal to the preset repair effect threshold, the comprehensive judgment module generates a repair compliance signal; otherwise, it generates a continue monitoring signal. The preferred value of N is 3, that is, the repair is judged to be complete only after three consecutive sub-periods meet the standard, in order to avoid misjudgment due to accidental drop after a single compliance. The value of N can also be adjusted according to the length of the evaluation sub-periods; the value of N can be appropriately increased when the sub-periods are short, and appropriately decreased when the sub-periods are long.

[0075] V. Early Warning Output Module

[0076] The early warning output module is used to receive the repair compliance signal or the continued monitoring signal output by the comprehensive judgment module, and send a repair completion notification to the user terminal based on the repair compliance signal, or send a suggestion to the user terminal to continue applying ecological fertilizer based on the continued monitoring signal.

[0077] The early warning output module also includes a tiered early warning unit. This unit determines the early warning level based on the ratio of the difference between the single-period repair effect evaluation value and the preset repair effect threshold. The ratio is defined as (preset repair effect threshold - single-period repair effect evaluation value) / preset repair effect threshold. When the ratio is less than the first preset ratio (e.g., 10%), a Level 1 early warning is output, indicating that the repair is nearing completion and it is recommended to maintain the current fertilization plan. When the ratio is greater than or equal to the first preset ratio and less than the second preset ratio (e.g., 30%), a Level 2 early warning is output, indicating that the repair has made some progress but has not yet reached the target, and it is recommended to appropriately increase the amount of fertilizer or adjust the fertilization method. When the ratio is greater than or equal to the second preset ratio, a Level 3 early warning is output, indicating that the repair effect is unsatisfactory, and it is recommended to comprehensively evaluate and adjust the repair plan. Level 1, Level 2, and Level 3 early warnings correspond to different recommended fertilization adjustment plans. For example, a Level 1 early warning suggests keeping the fertilization unchanged, a Level 2 early warning suggests increasing the fertilization by 10%-20%, and a Level 3 early warning suggests increasing the fertilization by more than 30% in conjunction with other agronomic measures.

[0078] The early warning output module also includes the number of remaining assessment sub-periods predicted by the trend analysis unit in the recommendation information for continuing to apply organic fertilizer and sends it to the user terminal, enabling users to plan subsequent agricultural arrangements in advance.

[0079] The entire system's workflow is as follows: Before the application of ecological fertilizer, the soil parameter acquisition module and crop growth monitoring module collect initial data before remediation, including S_0 and G_0, respectively; after the application of ecological fertilizer, the system enters a cyclical monitoring state according to the preset evaluation period division rules, and automatically calculates the single-period remediation effect evaluation value E_i at the end of each evaluation sub-period; the comprehensive judgment module continuously judges E_i, and once the condition of meeting the standard for N consecutive sub-periods is met, the remediation is judged to be completed; the early warning output module continuously provides feedback to the user on the current remediation progress and subsequent suggestions throughout the process.

[0080] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An intelligent monitoring system for the application effect of ecological fertilizer for continuous cropping obstacle repair, characterized in that, include: The soil parameter acquisition module is used to deploy multiple sensor nodes in the target field according to a preset spatial distribution scheme. Each sensor node collects soil physical parameters and soil chemical parameters before and after the continuous cropping obstacle repair at a set acquisition cycle. The soil physical parameters include soil temperature, soil moisture and soil electrical conductivity. The soil chemical parameters include soil pH value, soil organic matter content, soil available nitrogen content, soil available phosphorus content and soil available potassium content. The crop growth monitoring module is used to acquire canopy images of crops in the target field through image acquisition equipment, extract the normalized vegetation index and crop coverage based on the canopy images, and record crop plant height and crop stem diameter. The remediation effect evaluation module receives the soil parameter sequence output by the soil parameter acquisition module and the crop growth parameter sequence output by the crop growth monitoring module. Based on a preset evaluation period division rule, it divides the monitoring period into multiple evaluation sub-periods. At the end of each evaluation sub-period, it calculates the single-period remediation effect evaluation value, which is calculated according to the following formula: E_i=α×(S_i / S_0)+β×(G_i / G_0) Where E_i is the single-period remediation effect evaluation value of the i-th evaluation sub-period, S_i is the soil comprehensive index at the end of the i-th evaluation sub-period, S_0 is the soil comprehensive index before remediation, G_i is the crop comprehensive index at the end of the i-th evaluation sub-period, G_0 is the crop comprehensive index before remediation, α and β are weighting coefficients, and α+β=1. The comprehensive judgment module is used to compare the single-period repair effect evaluation value of each evaluation sub-period with the preset repair effect threshold. When the single-period repair effect evaluation value of N consecutive evaluation sub-periods is greater than or equal to the preset repair effect threshold, a repair compliance signal is generated; otherwise, a continue monitoring signal is generated. The early warning output module is used to receive the repair compliance signal or the continued monitoring signal output by the comprehensive judgment module, and send a repair completion notification to the user terminal according to the repair compliance signal, or send a suggestion to the user terminal to continue applying ecological fertilizer according to the continued monitoring signal.

2. The intelligent monitoring system for the application effect of ecological fertilizer for continuous cropping obstacle repair according to claim 1, characterized in that, The soil parameter acquisition module also includes a sensor node self-checking unit and an abnormal data removal unit. The sensor node self-checking unit is used to detect the working status of each sensor node before the start of each acquisition cycle. When an abnormal sensor node is detected, a node abnormality mark is generated. The abnormal data removal unit is used to remove the abnormal data collected by the corresponding sensor node in the current acquisition cycle according to the node abnormality mark, and to fill in the missing data by interpolation based on the valid data of adjacent sensor nodes in the same acquisition cycle.

3. The intelligent monitoring system for the application effect of ecological fertilizer for continuous cropping obstacle repair according to claim 2, characterized in that, The comprehensive soil index is calculated according to the following formula: S_i=w_1×(pH_{i} / pH_{std})+w_2×(OM_{i} / OM_{std})+w_3×(N_{i} / N_{st d})+w_4×(P_{i} / P_{std})+w_5×(K_{i} / K_{std})+w_6×(EC_{i} / EC_{std}) Wherein, S_i is the soil comprehensive index at the end of the i-th evaluation sub-period, pH_{i} is the measured soil pH value at the end of the i-th evaluation sub-period, pH_{std} is the standard soil pH value, OM_{i} is the measured soil organic matter content at the end of the i-th evaluation sub-period, OM_{std} is the standard soil organic matter content, N_{i} is the measured soil available nitrogen content at the end of the i-th evaluation sub-period, N_{std} is the standard soil available nitrogen content, and P_{i} is the soil organic matter content at the end of the i-th evaluation sub-period. The measured values ​​of available phosphorus content in the soil at the end of each evaluation sub-period, P_{std} is the standard value of available phosphorus content in the soil, K_{i} is the measured value of available potassium content in the soil at the end of the i-th evaluation sub-period, K_{std} is the standard value of available potassium content in the soil, EC_{i} is the measured value of electrical conductivity in the soil at the end of the i-th evaluation sub-period, EC_{std} is the standard value of electrical conductivity in the soil, and w_1 to w_6 are the weight coefficients of each indicator, and w_1+w_2+w_3+w_4+w_5+w_6=1.

4. The intelligent monitoring system for the application effect of ecological fertilizer for continuous cropping obstacle repair according to claim 3, characterized in that, The crop composite index is calculated according to the following formula: G_i=v_1×(NDVI_{i} / NDVI_0)+v_2×(CC_{i} / CC_0)+v_3×(H_{i} / H_0)+v_4×(D_{i} / D_0) Wherein, G_i is the crop composite index at the end of the i-th evaluation sub-period, NDVI_{i} is the measured value of the crop normalized vegetation index at the end of the i-th evaluation sub-period, NDVI_0 is the initial value of the crop normalized vegetation index before restoration, CC_{i} is the measured value of the crop cover at the end of the i-th evaluation sub-period, CC_0 is the initial value of the crop cover before restoration, H_{i} is the measured value of the crop plant height at the end of the i-th evaluation sub-period, H_0 is the initial value of the crop plant height before restoration, D_{i} is the measured value of the crop stem diameter at the end of the i-th evaluation sub-period, D_0 is the initial value of the crop stem diameter before restoration, v_1 ​​to v_4 are the weight coefficients of each index, and v_1+v_2+v_3+v_4=1.

5. The intelligent monitoring system for the application effect of ecological fertilizer for continuous cropping obstacle repair according to claim 4, characterized in that, The repair effect evaluation module also includes a trend analysis unit. The trend analysis unit is used to fit a repair effect change trend curve based on the single-period repair effect evaluation value of each evaluation sub-period, and predict the number of remaining evaluation sub-periods required to reach the preset repair effect threshold based on the repair effect change trend curve. The remaining number of evaluation sub-periods is then sent to the early warning output module. The early warning output module includes the remaining number of evaluation sub-periods in the suggestion information for continuing to apply ecological fertilizer and sends it to the user terminal.

6. The intelligent monitoring system for the application effect of ecological fertilizer for continuous cropping obstacle repair according to claim 5, characterized in that, The early warning output module further includes a graded early warning unit, which is used to determine the early warning level based on the difference ratio between the single-period repair effect evaluation value and the preset repair effect threshold. When the difference ratio is less than a first preset ratio, a level 1 early warning information is output; when the difference ratio is greater than or equal to the first preset ratio and less than a second preset ratio, a level 2 early warning information is output; and when the difference ratio is greater than or equal to the second preset ratio, a level 3 early warning information is output. The level 1, level 2, and level 3 early warning information correspond to different recommended fertilizer application adjustment schemes.

7. The intelligent monitoring system for the application effect of ecological fertilizer for continuous cropping obstacle repair according to claim 1, characterized in that, The preset spatial layout scheme involves uniformly arranging sensor nodes in the target field using a grid layout method. The grid spacing is determined based on the area and topography of the target field. Each sensor node is assigned a unique node number. The soil parameter acquisition module marks and stores the collected soil parameter sequences according to the node numbers. Before calculating the single-period remediation effect evaluation value, the remediation effect evaluation module performs an arithmetic mean processing on the soil parameter sequences of each sensor node within the same evaluation sub-period according to the node numbers to obtain representative values ​​for each soil parameter in each evaluation sub-period.

8. The intelligent monitoring system for the application effect of ecological fertilizer for continuous cropping obstacle repair according to claim 1, characterized in that, The soil parameter acquisition module further includes an adaptive acquisition cycle adjustment unit. The adaptive acquisition cycle adjustment unit is used to dynamically adjust the acquisition cycle of the current assessment sub-period based on the difference between the single-period remediation effect evaluation value of the previous assessment sub-period and the preset remediation effect threshold. When the difference is less than a first difference threshold, the acquisition cycle is adjusted to a first cycle value. When the difference is greater than or equal to the first difference threshold and less than a second difference threshold, the acquisition cycle is adjusted to a second cycle value. When the difference is greater than or equal to the second difference threshold, the acquisition cycle is adjusted to a third cycle value, wherein the first cycle value is less than the second cycle value, and the second cycle value is less than the third cycle value.

9. The intelligent monitoring system for the application effect of ecological fertilizer for continuous cropping obstacle repair according to claim 3, characterized in that, The remediation effect evaluation module also includes an abnormal fluctuation detection unit. This unit calculates the rate of change of the soil comprehensive index between two adjacent evaluation sub-periods. When the rate of change exceeds a preset rate of change threshold, an abnormal fluctuation marker is generated, and the soil parameter sequence within the evaluation sub-period corresponding to the abnormal fluctuation marker is marked as data to be reviewed. The abnormal fluctuation detection unit determines the rate of change according to the following rules: R_i=|(S_i-S_{i-1}) / S_{i-1}| Wherein, R_i is the rate of change of the soil comprehensive index of the i-th evaluation sub-period relative to the (i-1)-th evaluation sub-period. When R_i is greater than the preset rate of change threshold, the abnormal fluctuation marker is generated.

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