Soil acidification improvement method

Abstract

The invention discloses a soil acidification improvement method, and relates to the technical field of soil improvement, according to the soil acidification improvement method, evaluation of soil attributes is completed through multi-level diagnosis and calculation of the acidification coefficient, the physical obstacle coefficient and the buffer capacity coefficient of soil, and comprehensiveness of soil acidification analysis is ensured. The problem of limitation existing in the current soil acidification analysis process is solved, meanwhile, a threshold value is used for driving decision control flow branches, an improvement scheme is flexibly upgraded based on real-time monitoring data, the soil improvement effect is improved, closed-loop learning double feedback and S6, data are fed back to S1, self-optimization of the system is achieved, the system adapts to soil changes, and the soil acidification analysis efficiency is improved. An abnormal state after improvement is warned in time, so that the soil safety is guaranteed; the method is suitable for the fields of land restoration and the like, the soil improvement efficiency is improved through data-driven intelligent decision, resource waste is reduced, soil acidification is improved and upgraded, and a technical engine is provided for agricultural sustainable development and cultivated land protection.

Description

Technical Field

[0001] The present application relates to the technical field of soil improvement, and in particular to a method for improving soil acidification. Background Art

[0002] Soil acidification poses a serious threat to agricultural development, especially in southern China, where more than one-fifth of the arable land is acidified. Traditional soil acidification improvement technologies still have many shortcomings, especially the contradiction between the rapid effectiveness and limitations of lime improvement. Therefore, it is very important to develop new soil improvement technologies.

[0003] Existing technology, such as the invention patent application with publication number CN119742003A, discloses a method for predicting soil acidification sensitivity based on regional big data. This method involves acquiring test data and developing a soil acidification sensitivity prediction model. The soil acidification sensitivity prediction model training process includes constructing a basic dataset, preprocessing the dataset, partitioning the dataset, and then training and screening the model. By introducing a machine learning model, this invention addresses the shortcomings of traditional laboratory methods that use continuous acid-base titration to determine acidification sensitivity, enabling rapid and accurate prediction of the acidification sensitivity of batch soil samples at a regional scale.

[0004] Regarding the above-mentioned scheme, the inventors of this application found that the above-mentioned technology has at least the following technical problems: 1. There is currently a lack of calculation of the soil acidification coefficient, physical barrier coefficient and buffering capacity coefficient to complete the evaluation of soil properties, which cannot ensure the comprehensiveness of soil acidification analysis and cannot solve the limitations of the current soil acidification analysis process. At the same time, there is no use of threshold-driven decision-making control process branches, and there is a lack of flexible upgrade and improvement plans based on real-time monitoring data, which cannot improve the effect of soil improvement. There is a lack of closed-loop learning and dual feedback, and it is impossible to achieve system self-optimization and adapt to soil changes, and it is impossible to provide a technical engine for sustainable agricultural development and farmland protection.

[0005] 2. Currently, there is a lack of analysis of the first comprehensive improvement coefficient to integrate the topsoil and plow bottom layer data, which makes it impossible to optimize resource allocation and avoid single factor deviation. There is also a lack of analysis of the second comprehensive improvement coefficient to solve the negative buffer risk of the subsoil layer and enhance the adaptability of the scheme. There is also a lack of synergistic improvement through electrochemical assisted deep loosening. Migration efficiency. Summary of the Invention

[0006] In view of the above-mentioned technical deficiencies, the purpose of this application is to provide a soil acidification improvement method.

[0007] In order to solve the above technical problems, the present application adopts the following technical solution: The present application provides a soil acidification improvement method, which includes the following steps: S1, calculating the soil acidification coefficient based on pre-acquired topsoil layer data.

[0008] S2. Calculate the soil physical barrier coefficient based on pre-acquired plow bottom layer data, and decide to execute S3 or S5 based on the soil acidification coefficient threshold and the physical barrier coefficient threshold.

[0009] S3. Calculate the soil buffering capacity coefficient based on the pre-acquired subsoil layer data, and execute S4 based on the buffering capacity coefficient threshold decision.

[0010] S4. Calculate a first comprehensive improvement coefficient or a second comprehensive improvement coefficient based on the soil acidification coefficient, physical barrier coefficient, and buffering capacity coefficient to trigger S5.

[0011] S5. Execute the first-level improvement plan based on the soil acidification coefficient, the first comprehensive improvement coefficient or the second comprehensive improvement coefficient and monitor the first time series of the soil. value, and then decide whether to execute the secondary improvement plan or execute S6 to obtain the second timing value.

[0012] S6, based on the second timing The value threshold executes the early warning and update mechanism and feeds back the updated data to S1.

[0013] Preferably, the soil acidification coefficient is calculated based on the pre-acquired surface soil layer data, and the specific calculation process is as follows: the surface soil layer data includes the surface soil layer Value, exchange acidity Content and content; According to the calculation formula Calculate the soil acidification coefficient ,in Expressed as the exchangeability of the preset soil The maximum content, Represented as the preset soil The maximum content, 、 and Represents the topsoil layer of soil The weight factor corresponding to the value, exchange acidity The weight factor corresponding to the content and The weight factor corresponding to the content.

[0014] Preferably, the physical barrier coefficient of the soil is calculated based on the pre-acquired plow bottom layer data, and the specific calculation process is as follows: the plow bottom layer data includes the compactness and Content, substitute into the calculation formula Calculate the physical barrier coefficient of the soil ,in It is expressed as the compaction of the soil plow bottom layer, It is expressed as the preset maximum value of soil compaction. and are respectively represented by the weight factors corresponding to the compaction of the soil plow bottom layer and The weight factor corresponding to the content.

[0015] Preferably, the decision to execute S3 or S5 based on the soil acidification coefficient threshold and the physical barrier coefficient threshold includes: Output the decision result 1 or 0. When the decision result is 1, execute S3. When the decision result is 0, execute B1 in S5. Expressed as the preset soil acidification coefficient threshold, Expressed as a preset soil physical barrier coefficient threshold.

[0016] Preferably, the soil buffering capacity coefficient is calculated based on the pre-acquired subsoil layer data, and the specific calculation process is as follows: the subsoil layer data includes the clay content and Substitute the value into the calculation formula Calculate the soil buffering capacity coefficient ,in Expressed as a natural constant term, It is expressed as the clay content of the soil subsoil layer. and are respectively represented by the weight factors corresponding to the clay content of the soil core layer and The weight factor corresponding to the value.

[0017] Preferably, the decision execution S4 based on the buffer capacity coefficient threshold includes: Output the decision result 1 or 0. When the decision result is 0, execute A1 in S4. When the decision result is 1, execute A2 in S4. It is represented as the preset buffer capacity coefficient threshold.

[0018] Preferably, the first comprehensive improvement coefficient or the second comprehensive improvement coefficient is calculated based on the soil acidification coefficient, physical barrier coefficient and buffering capacity coefficient. The specific calculation process is as follows: A1. Substitute the soil acidification coefficient and physical barrier coefficient into the calculation formula The first comprehensive improvement coefficient ,in and They are respectively expressed as the weight factor corresponding to the soil acidification coefficient and the weight factor corresponding to the physical barrier coefficient.

[0019] A2. Substitute the soil acidification coefficient, physical barrier coefficient and buffer capacity coefficient into the calculation formula The second comprehensive improvement coefficient ,in 、 and They are respectively expressed as the weight factor corresponding to the soil acidification coefficient, the weight factor corresponding to the physical barrier coefficient, and the weight factor corresponding to the buffering capacity coefficient.

[0020] Preferably, the first time series of the soil improvement program is executed based on the soil acidification coefficient, the first comprehensive improvement coefficient or the second comprehensive improvement coefficient and the soil is monitored. The values ​​include: B1, obtaining the amount of lime based on the soil type and acidification coefficient, mixing the soil and lime, turning the soil to the target depth, and turning the soil again in the cross direction of the turning to complete the soil mixing, then replenishing the soil based on the soil dryness and monitoring the first time series value of the soil.

[0021] B2. Based on the soil type and the first comprehensive improvement coefficient, the amount of dolomite powder is obtained, and then the electrochemically assisted deep loosening of the soil is completed, and the first time series value of the soil is monitored.

[0022] B3. Based on the soil type and the second comprehensive improvement coefficient, the amount of amendment is obtained. The amendment is a paste made of lime, phosphogypsum and biochar. The amendment is then injected into the subsoil layer and the first time series value of the soil is monitored.

[0023] Preferably, the decision whether to execute the secondary improvement plan or execute S6 includes: when the first time sequence of the soil When the value shows a downward trend or fluctuates, the decision is made to implement the secondary improvement plan; at the same time, the second time series of soil is monitored again. value, when the first timing of the soil When the value shows a downward trend or fluctuates up and down, the decision is to execute S6.

[0024] Preferably, the secondary improvement plan includes: C1, applying organic fertilizer.

[0025] C2. Based on the first comprehensive improvement coefficient, the amount of the improver is obtained, where the improver is phosphogypsum dolomite powder microcapsules, and then the improver is injected into the plow bottom layer of the soil.

[0026] C3. Carry out agronomic management of the soil.

[0027] The beneficial effects of the present application are: 1. A soil acidification improvement method provided by the present application completes the soil property evaluation by calculating the soil acidification coefficient, physical barrier coefficient and buffering capacity coefficient through multi-level diagnosis, ensuring the comprehensiveness of soil acidification analysis and solving the limitations of the current soil acidification analysis process. At the same time, the method uses threshold-driven decision-making control process branches to flexibly upgrade the improvement plan based on real-time monitoring data, thereby improving the effect of soil improvement. Closed-loop learning dual feedback, S6 feeds back data to S1, realizes system self-optimization, adapts to soil changes, and promptly warns of abnormal conditions after improvement to ensure soil safety; it is suitable for fields such as land remediation, improves soil improvement efficiency through data-driven intelligent decision-making, reduces resource waste, and improves soil acidification, providing a technical engine for sustainable agricultural development and farmland protection.

[0028] 2. This application uses the acidification coefficient to quantify the degree of acidification of the topsoil layer, the threshold decision to ensure efficient allocation of resources and avoid excessive processing, the physical obstacle coefficient to evaluate the mechanical obstacles of the plow bottom layer, the threshold decision to optimize the diagnosis process and reduce redundant operations, the buffering capacity coefficient to quantify the acid neutralization capacity of the subsoil layer and improve the diagnostic accuracy, the first comprehensive improvement coefficient integrates the topsoil and plow bottom layer data, optimizes resource allocation, and avoids single factor deviation, and the second comprehensive improvement coefficient solves the negative buffer risk of the subsoil layer and enhances the adaptability of the solution.

[0029] 3. This application uses electrochemical assisted deep loosening to synergistically improve Migration efficiency; dual-layer timing Threshold decision-making ensures precise control and reduces energy consumption. Data-driven closed-loop improves diagnostic accuracy, avoids ineffective operations, and develops early warning and feedback mechanisms that are optimized for soil-specific dynamic cycles. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0031] Figure 1 The figure is a flowchart of the steps for implementing the application method.

[0032] Figure 2 This is a diagram of the decision-making process for this application. DETAILED DESCRIPTION

[0033] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0034] See also Figure 1 As shown, the present application provides a soil acidification improvement method, including: S1, calculating the soil acidification coefficient based on pre-acquired topsoil layer data.

[0035] In a specific example, the soil acidification coefficient is calculated based on the pre-acquired surface soil layer data. The specific calculation process is as follows: the surface soil layer data includes the surface soil layer Value, exchange acidity Content and content.

[0036] According to the calculation formula Calculate the soil acidification coefficient ,in Expressed as the exchangeability of the preset soil The maximum content, Represented as the preset soil The maximum content, 、 and Represents the topsoil layer of soil The weight factor corresponding to the value, exchange acidity The weight factor corresponding to the content and The weight factor corresponding to the content.

[0037] It should be noted that the soil is divided into several areas, and the pH of the topsoil layer in each area is collected by pH sensors. Value and exchange acidity The content of the topsoil in each area was collected by KCl extraction combined with spectral analysis. content, and then the topsoil layer of each area Value, exchange acidity Content and The average values ​​of the contents were calculated to obtain the topsoil data of the soil.

[0038] It should be noted that .

[0039] It should be noted that the default , preset .

[0040] It should be noted that , , , ,like 、 and .

[0041] It should be noted that the factor analysis method is used to obtain the soil surface layer The weight factor corresponding to the value, exchange acidity The weight factor corresponding to the content and The weight factor corresponding to the content is firstly Value, exchange acidity Content and The information of the content is condensed, and then the variance explanation rate after rotation is obtained, and the weight is obtained by dividing the cumulative variance explanation rate.

[0042] It should be noted that factor analysis is a well-known technology. It is a multivariate statistical analysis method that starts from studying the internal dependencies of variables and reduces some variables with complex relationships to a few comprehensive factors; information concentration is expressed as calculating the median; the variance explanation rate is the amount of information extracted by the factor, and the variance explanation rate = characteristic root / total number of analysis items; the variance explanation rate after rotation is expressed as the variance explanation rate of the factor after maximum variance rotation.

[0043] S2. Calculate the soil physical barrier coefficient based on pre-acquired plow bottom layer data, and decide to execute S3 or S5 based on the soil acidification coefficient threshold and the physical barrier coefficient threshold.

[0044] In a specific example, the soil physical barrier coefficient is calculated based on the pre-acquired plow bottom layer data. The specific calculation process is as follows: the plow bottom layer data includes the compactness and Content, substitute into the calculation formula Calculate the physical barrier coefficient of the soil ,in It is expressed as the compaction of the soil plow bottom layer, It is expressed as the preset maximum value of soil compaction. and are respectively represented by the weight factors corresponding to the compaction of the soil plow bottom layer and The weight factor corresponding to the content.

[0045] It should be noted that the compaction of the plow bottom layer in each area was collected using a soil compaction meter, and the compaction of the plow bottom layer in each area was collected by KCl extraction combined with spectral analysis. content, and then the compactness and The mean values ​​of the contents were calculated respectively to obtain the plow bottom layer data of the soil.

[0046] It should be noted that , , .

[0047] It should be noted that the weight factors and The weight factor corresponding to the content is firstly the compactness of the soil plow bottom layer and The information of the content is condensed, and then the variance explanation rate after rotation is obtained, and the weight is obtained by dividing the cumulative variance explanation rate.

[0048] In a specific example, the decision to execute S3 or S5 based on the soil acidification coefficient threshold and the physical barrier coefficient threshold includes: Output the decision result 1 or 0. When the decision result is 1, execute S3. When the decision result is 0, execute B1 in S5. Expressed as the preset soil acidification coefficient threshold, Expressed as a preset soil physical barrier coefficient threshold.

[0049] It should be noted that the lime dosage is obtained based on the soil acidification coefficient. The specific calculation formula is: ,in It is expressed as the amount of lime applied corresponding to the soil type. For example, the amount of lime applied for clay soil is greater than that for sandy soil. The unit of lime application is tons per mu.

[0050] S3. Calculate the soil buffering capacity coefficient based on the pre-acquired subsoil layer data, and execute S4 based on the buffering capacity coefficient threshold decision.

[0051] In a specific example, the soil buffering capacity coefficient is calculated based on the pre-acquired subsoil layer data. The specific calculation process is as follows: the subsoil layer data includes the clay content and Substitute the value into the calculation formula Calculate the soil buffering capacity coefficient ,in Expressed as a natural constant term, It is expressed as the clay content of the soil subsoil layer. and are respectively represented by the weight factors corresponding to the clay content of the soil core layer and The weight factor corresponding to the value.

[0052] It should be noted that the soil is divided into several areas, and the pH of the topsoil layer in each area is collected by pH sensors. Value and exchange acidity The content of the topsoil in each area was collected by KCl extraction combined with spectral analysis. content, and then the topsoil layer of each area Value, exchange acidity Content and The average values ​​of the contents were calculated to obtain the topsoil data of the soil.

[0053] It should be noted that the pH of the subsoil layer in each area was collected by pH sensors. The clay content of the subsoil layer in each area was collected using a laser particle size analyzer, and the clay content of the subsoil layer in each area was calculated. The mean values ​​of the soil density and clay content were calculated respectively to obtain the soil subsoil data.

[0054] It should be noted that .

[0055] It should be noted that , , .

[0056] It should be noted that the weight factors and The weight factor corresponding to the content is firstly the compactness of the soil plow bottom layer and The information of the content is condensed, and then the variance explanation rate after rotation is obtained, and the weight is obtained by dividing the cumulative variance explanation rate.

[0057] In a specific example, the decision-making process based on the buffer capacity coefficient threshold value in step S4 includes: Output the decision result 1 or 0. When the decision result is 0, execute A1 in S4. When the decision result is 1, execute A2 in S4. It is represented as the preset buffer capacity coefficient threshold.

[0058] S4. Calculate a first comprehensive improvement coefficient or a second comprehensive improvement coefficient based on the soil acidification coefficient, physical barrier coefficient, and buffering capacity coefficient to trigger S5.

[0059] In a specific example, the first comprehensive improvement coefficient or the second comprehensive improvement coefficient is calculated based on the soil acidification coefficient, physical barrier coefficient, and buffering capacity coefficient. The specific calculation process is as follows: A1. Substitute the soil acidification coefficient and physical barrier coefficient into the calculation formula The first comprehensive improvement coefficient ,in and They are respectively expressed as the weight factor corresponding to the soil acidification coefficient and the weight factor corresponding to the physical barrier coefficient.

[0060] A2. Substitute the soil acidification coefficient, physical barrier coefficient and buffer capacity coefficient into the calculation formula The second comprehensive improvement coefficient ,in 、 and They are respectively expressed as the weight factor corresponding to the soil acidification coefficient, the weight factor corresponding to the physical barrier coefficient, and the weight factor corresponding to the buffering capacity coefficient.

[0061] This application uses the acidification coefficient to quantify the acidification degree of the topsoil layer, the threshold decision to ensure efficient resource allocation and avoid excessive processing, the physical obstacle coefficient to evaluate the mechanical obstacles of the plow bottom layer, the threshold decision to optimize the diagnosis process and reduce redundant operations, the buffering capacity coefficient to quantify the acid neutralization capacity of the subsoil layer and improve the diagnosis accuracy, the first comprehensive improvement coefficient integrates the topsoil and plow bottom layer data, optimizes resource allocation, and avoids single factor deviation, and the second comprehensive improvement coefficient solves the negative buffer risk of the subsoil layer and enhances the adaptability of the solution.

[0062] S5. Execute the first-level improvement plan based on the soil acidification coefficient, the first comprehensive improvement coefficient or the second comprehensive improvement coefficient and monitor the first time series of the soil. value, and then decide whether to execute the secondary improvement plan or execute S6 to obtain the second timing value.

[0063] It should be noted that the first time series of soil The value represents the soil after completing the first-level improvement plan according to the collection time point. value.

[0064] In a specific example, the first time series of the soil improvement program is executed based on the soil acidification coefficient, the first comprehensive improvement coefficient or the second comprehensive improvement coefficient and the soil is monitored. The values ​​include: B1, obtaining the amount of lime based on the soil type and acidification coefficient, mixing the soil and lime, turning the soil to the target depth, and turning the soil again in the cross direction of the turning to complete the soil mixing, then replenishing the soil based on the soil dryness and monitoring the first time series value of the soil.

[0065] It should be noted that the lime dosage is obtained based on the soil type and acidification coefficient of the soil, and a table of lime dosages corresponding to soil types and acidification coefficients is stored in the database.

[0066] It should be noted that lime is spread on the topsoil layer of the soil using a lime spreader, and then the soil and lime are mixed using a rotary tiller; the target depth is 15 to 20 cm; soil watering is performed based on soil dryness, and the specific process is as follows: soil dryness is obtained using a humidity sensor, and the corresponding water replenishment amount is retrieved from the database based on soil dryness and soil type, thereby completing soil watering.

[0067] B2. Based on the soil type and the first comprehensive improvement coefficient, the amount of dolomite powder is obtained, and then the electrochemically assisted deep loosening of the soil is completed, and the first time series value of the soil is monitored.

[0068] It should be noted that the amount of dolomite powder is obtained based on the soil type and the first comprehensive improvement coefficient of the soil, and a table of dolomite powder amounts corresponding to the soil type and the first comprehensive improvement coefficient is stored in the database.

[0069] It should be noted that electrochemical assisted deep loosening of soil is to install electrodes on the deep loosening plow to generate a low voltage electric field such as 5V / cm when loosening the soil, driving Migrate to the cathode, while the anode releases the , to achieve neutralization of the acidity gradient in the plow bottom layer.

[0070] B3. Based on the soil type and the second comprehensive improvement coefficient, the amount of amendment is obtained. The amendment is a paste made of lime, phosphogypsum and biochar. The amendment is then injected into the subsoil layer and the first time series value of the soil is monitored.

[0071] It should be noted that the amount of the amendment is obtained based on the soil type and the second comprehensive improvement coefficient, and a table of the amount of the amendment corresponding to the soil type and the second comprehensive improvement coefficient is stored in the database.

[0072] It should be noted that the moisture content of the amendment is less than 30 percent and it is injected into the deep soil through a borehole using a high-pressure pump.

[0073] In one embodiment, the decision whether to execute the secondary improvement plan or execute S6 includes: when the first time sequence of the soil When the value shows a downward trend or fluctuates, the decision is made to implement the secondary improvement plan; at the same time, the second time series of soil is monitored again. value, when the first timing of the soil When the value shows a downward trend or fluctuates up and down, the decision is to execute S6.

[0074] In one specific example, the secondary improvement plan includes: C1, applying organic fertilizer.

[0075] C2. Based on the first comprehensive improvement coefficient, the amount of the improver is obtained, where the improver is phosphogypsum dolomite powder microcapsules, and then the improver is injected into the plow bottom layer of the soil.

[0076] C3. Carry out agronomic management of the soil.

[0077] It should be noted that the secondary improvement scheme includes C1, C2 and C3, where C1, C2 and C3 correspond to B1, B2 and B3 respectively. For example, when B1 is executed, the first time series of soil monitoring When the value shows a downward trend or fluctuates, the decision is to implement C1 of the secondary improvement plan.

[0078] It should be noted that the amount of the amendment is obtained based on the soil type and the second comprehensive improvement coefficient, and a table of the amount of the amendment corresponding to the soil type and the second comprehensive improvement coefficient is stored in the database.

[0079] It should be noted that the phosphogypsum dolomite powder gel microcapsules are a composite of phosphogypsum and dolomite powder, wherein the phosphogypsum contains , formulated as microcapsules. When the pH of deep soil is less than 5.0, the capsule shell dissolves and releases calcium and magnesium ions, replacing aluminum ions and neutralizing acidity. Theoretical basis: Calcium in phosphogypsum can fix active aluminum , dolomite provides sustained alkalinity .

[0080] It should be noted that agronomic management of soil includes water optimization, planting structure adjustment and organic carbon addition.

[0081] S6, based on the second timing The value threshold executes the early warning and update mechanism and feeds back the updated data to S1.

[0082] It should be noted that according to the second sequence in S5 Value, start data update according to the warning type, second time series When the value is greater than 5.5, a first-level warning prompt is issued, and the second-level When the value is greater than 6.5, a second-level warning prompt is issued, and the second time sequence When the value is greater than 7, a level 3 warning prompt is issued, and the updated data is fed back to S1 to re-execute each step.

[0083] This application uses electrochemical assisted deep loosening to synergistically improve Migration efficiency; dual-layer timing Threshold decision-making ensures precise control and reduces energy consumption. Data-driven closed-loop improves diagnostic accuracy, avoids ineffective operations, and develops early warning and feedback mechanisms to optimize soil-specific dynamic cycles.

[0084] The present application provides a soil acidification improvement method. Through multi-level diagnosis, the soil acidification coefficient, physical barrier coefficient, and buffering capacity coefficient are calculated to complete the soil property assessment, ensuring the comprehensiveness of the soil acidification analysis and solving the limitations of the current soil acidification analysis process. At the same time, the method uses threshold-driven decision-making control process branches to flexibly upgrade the improvement plan based on real-time monitoring data, thereby improving the effect of soil improvement. Closed-loop learning and dual feedback are implemented, and S6 feeds data back to S1 to achieve system self-optimization, adapt to soil changes, and promptly warn of abnormal conditions after improvement to ensure soil safety. The method is applicable to fields such as land remediation, and improves soil improvement efficiency and reduces resource waste through data-driven intelligent decision-making. The soil acidification improvement and upgrade provide a technical engine for sustainable agricultural development and farmland protection.

[0085] In the several embodiments provided by the present invention, it should be understood that the disclosed method can be implemented in other ways.

[0086] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0087] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method and technology of using digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to achieve optimal results.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for improving soil acidification, characterized in that: include: S1. calculating the soil acidification coefficient based on pre-acquired topsoil data; S2, calculating the soil physical barrier coefficient based on pre-acquired plow bottom layer data, and deciding to execute S3 or S5 based on the soil acidification coefficient threshold and the physical barrier coefficient threshold; S3, calculating the soil buffering capacity coefficient based on the pre-acquired subsoil layer data, and executing S4 based on the buffering capacity coefficient threshold decision; S4. Calculating a first comprehensive improvement coefficient or a second comprehensive improvement coefficient based on the soil acidification coefficient, physical barrier coefficient, and buffering capacity coefficient to trigger S5; S5. Execute the first-level improvement plan based on the soil acidification coefficient, the first comprehensive improvement coefficient or the second comprehensive improvement coefficient and monitor the first time series of the soil. value, and then decide whether to execute the secondary improvement plan or execute S6 to obtain the second timing value; S6, based on the second timing The value threshold executes the early warning and update mechanism and feeds back the updated data to S1.

2. A soil acidification improvement method according to claim 1, characterized in that: The soil acidification coefficient is calculated based on the pre-acquired topsoil data. The specific calculation process is as follows: Topsoil data include the topsoil layer of the soil Value, exchange acidity Content and content; According to the calculation formula Calculate the soil acidification coefficient ,in Expressed as the exchangeability of the preset soil The maximum content, Represented as the preset soil The maximum content, 、 and Represents the topsoil layer of soil The weight factor corresponding to the value, exchange acidity The weight factor corresponding to the content and The weight factor corresponding to the content.

3. A soil acidification improvement method according to claim 2, characterized in that: The physical barrier coefficient of the soil is calculated based on the pre-acquired plow bottom layer data. The specific calculation process is as follows: Sub-soil data include soil sub-soil compaction and Content, substitute into the calculation formula Calculate the physical barrier coefficient of the soil ,in It is expressed as the compaction of the soil plow bottom layer, It is expressed as the preset maximum value of soil compaction. and are respectively represented by the weight factors corresponding to the compaction of the soil plow bottom layer and The weight factor corresponding to the content.

4. A soil acidification improvement method according to claim 3, characterized in that: The decision to execute S3 or S5 based on the soil acidification coefficient threshold and the physical barrier coefficient threshold includes: According to the decision formula Output the decision result 1 or 0. When the decision result is 1, execute S3. When the decision result is 0, execute B1 in S5. Expressed as the preset soil acidification coefficient threshold, Expressed as a preset soil physical barrier coefficient threshold.

5. A soil acidification improvement method according to claim 4, characterized in that: The soil buffering capacity coefficient is calculated based on the pre-acquired subsoil layer data. The specific calculation process is as follows: Subsoil data include clay content and Substitute the value into the calculation formula Calculate the soil buffering capacity coefficient ,in Expressed as a natural constant term, It is expressed as the clay content of the soil subsoil layer. and are respectively represented by the weight factors corresponding to the clay content of the soil core layer and The weight factor corresponding to the value.

6. The soil acidification improvement method according to claim 5, characterized in that: The step of executing S4 based on the buffer capacity coefficient threshold decision includes: According to the decision formula Output the decision result 1 or 0. When the decision result is 0, execute A1 in S4. When the decision result is 1, execute A2 in S4. It is represented as the preset buffer capacity coefficient threshold.

7. The soil acidification improvement method according to claim 6, characterized in that: The first comprehensive improvement coefficient or the second comprehensive improvement coefficient is calculated based on the soil acidification coefficient, physical barrier coefficient and buffering capacity coefficient. The specific calculation process is as follows: A1. Substitute the soil acidification coefficient and physical barrier coefficient into the calculation formula The first comprehensive improvement coefficient ,in and They are respectively expressed as the weight factors corresponding to the soil acidification coefficient and the physical barrier coefficient; A2. Substitute the soil acidification coefficient, physical barrier coefficient and buffer capacity coefficient into the calculation formula The second comprehensive improvement coefficient ,in 、 and They are respectively expressed as the weight factor corresponding to the soil acidification coefficient, the weight factor corresponding to the physical barrier coefficient, and the weight factor corresponding to the buffering capacity coefficient.

8. The soil acidification improvement method according to claim 7, characterized in that: The first time series of executing the first improvement plan based on the soil acidification coefficient, the first comprehensive improvement coefficient or the second comprehensive improvement coefficient and monitoring the soil Values, including: B1. Determine the lime dosage based on the soil type and acidification coefficient, mix the soil and lime, and turn the soil to the target depth. Turn the soil again in the cross-direction of the turn to complete the soil mixing. After the soil is fully mixed, rehydrate the soil based on soil dryness and monitor the first time series value of the soil. B2. Determine the amount of dolomite powder based on the soil type and the first comprehensive improvement coefficient, thereby completing electrochemically assisted deep loosening of the soil and monitoring the first time series value of the soil; B3. Based on the soil type and the second comprehensive improvement coefficient, the amount of amendment is obtained. The amendment is a paste made of lime, phosphogypsum and biochar. The amendment is then injected into the subsoil layer and the first time series value of the soil is monitored.

9. The soil acidification improvement method according to claim 8, characterized in that: The decision on whether to implement the secondary improvement plan or S6 includes: When the first sequence of soil When the value shows a downward trend or fluctuates, the decision is made to implement the secondary improvement plan; at the same time, the second time series of soil is monitored again. value, when the first timing of the soil When the value shows a downward trend or fluctuates up and down, the decision is to execute S6.

10. The soil acidification improvement method according to claim 9, characterized in that: The secondary improvement plan includes: C1. Apply organic fertilizer; C2. Based on the first comprehensive improvement coefficient, the amount of the amendment is obtained, where the amendment is phosphogypsum dolomite powder microcapsules, and the amendment is then injected into the plow bottom layer of the soil; C3. Carry out agronomic management of the soil.

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