A method and system for monitoring and evaluating the linkage between the growth cycle of sesbania and soil pH and salinity

Abstract

The application relates to the technical field of soil analysis, and discloses a monitoring and evaluation method and system for the linkage of the pH and salinity of soil in the growth cycle of Sesbania cannabina, which comprises the following steps: dividing background soil samples into salt-rich areas and desalination areas; collecting sub-samples from the salt-rich areas and the desalination areas, performing a desalination and re-wetting cycle operation on each sub-sample, continuously measuring the pH value and the salinity value of each sub-sample in the desalination stage and the re-wetting stage; generating pH value hysteresis loop curves and salinity value hysteresis loop curves of the salt-rich areas and the desalination areas, and analyzing the ion migration hysteresis difference of the background soil samples; when the Sesbania cannabina grows to the first sampling day and the second sampling day, analyzing the real-time ion migration hysteresis difference of real-time soil samples of the same Sesbania cannabina plant; superimposing the ion migration hysteresis difference and the real-time ion migration hysteresis difference in spatial distribution, and analyzing the cooperative improvement state of the pH and the salinity of soil in the growth cycle of the Sesbania cannabina based on the superimposed interval. The application can improve the accuracy of the monitoring of the pH and the salinity of soil in the growth cycle of the Sesbania cannabina.

Description

Technical Field

[0001] This invention relates to the field of soil analysis technology, and in particular to a method and system for monitoring and evaluating soil pH and salinity in conjunction with the growth cycle of sesbania. Background Technology

[0002] Saline-alkali land improvement is an important topic in agroecology. Sesbania, as a pioneer plant for salt tolerance, is believed to have a rhizosphere microbial community that can improve soil physicochemical properties. Current techniques typically employ static sampling, which involves collecting rhizosphere soil samples at different growth stages of Sesbania and measuring pH and salinity using a pH meter and conductivity meter. The improvement effect is evaluated by comparing the decrease in values ​​before and after sowing. For example, a common practice is to measure soil pH and salinity before sowing, during the middle growth stage, and at harvest; if both decrease significantly, the improvement is considered effective.

[0003] Current technologies cannot distinguish whether the decrease in pH and salinity is caused by active modification through sesbania-microbe interactions or by abiotic factors such as natural leaching and evaporative concentration. This may lead to misclassification of natural leaching as biological modification, or the underestimation of genuine biological modification as ineffective. Therefore, there is an urgent need for a dynamic monitoring method that can actively detect changes in soil ion migration and buffering capacity to objectively evaluate the synergistic modification of soil pH and salinity by sesbania-microbe interactions. Summary of the Invention

[0004] This invention provides a method and system for monitoring and evaluating soil pH and salinity in conjunction with the growth cycle of sesbania, the main purpose of which is to solve the problem of low accuracy in monitoring soil pH and salinity during the growth cycle of sesbania.

[0005] To achieve the above objectives, this invention provides a method for monitoring and evaluating the linkage between soil pH and salinity during the sesame growth cycle, comprising:

[0006] Before sowing sesame seeds, rhizosphere soil from the planting area is collected as a background soil sample, and the background soil sample is filled into a measuring container with electrodes at both ends.

[0007] A positive DC voltage is applied to one electrode of the measuring container to drive soluble salt ions in the background soil sample to migrate toward the opposite electrode. Based on the migration result, the background soil sample is divided into a salt-rich area and a desalination area.

[0008] After the power is turned off, sub-samples are collected from the salt-rich area and the desalination area respectively. A dehumidification-rehumidification cycle is performed on each sub-sample, and the pH and salinity values ​​of each sub-sample are continuously measured during the dehumidification and rehumidification stages.

[0009] Based on the pH value and the salinity value, pH hysteresis loop curves and salinity hysteresis loop curves are generated for the salt-rich area and the desalination area, respectively. The difference in ion migration hysteresis of the background soil sample is analyzed based on the pH hysteresis loop curves and the salinity hysteresis loop curves.

[0010] When the sesame plants reached the preset first and second sampling days, the rhizosphere soil of the same sesame plant was collected as real-time soil samples, and the difference in real-time ion migration lag of each real-time soil sample was analyzed.

[0011] The spatial distribution of the ion migration hysteresis difference and the real-time ion migration hysteresis difference is superimposed to obtain the superimposed interval. Based on the superimposed interval, the synergistic improvement status of soil pH and salinity during the growth cycle of sesbania is analyzed.

[0012] To address the aforementioned problems, this invention also provides a soil pH and salinity linkage monitoring and evaluation system for the sesame growth cycle, the system comprising:

[0013] The background soil sample filling module is used to collect rhizosphere soil from the planting area as a background soil sample before sowing sesame seeds, and fill the background soil sample into a measuring container with electrodes at both ends.

[0014] The background soil sample division module is used to apply a positive DC voltage to one end electrode of the measuring container, driving soluble salt ions in the background soil sample to migrate to the opposite electrode, and dividing the background soil sample into a salt-rich area and a desalination area based on the migration result.

[0015] The pH and salinity analysis module is used to collect sub-samples from the salt-rich area and the desalination area after power is turned off, perform dehumidification-rehumidification cycle operation on each sub-sample, and continuously measure the pH and salinity of each sub-sample during the dehumidification and rehumidification stages.

[0016] The ion migration hysteresis difference analysis module is used to generate pH hysteresis loop curves and salinity hysteresis loop curves for salt-rich and desalinated areas, respectively, based on the pH value and the salinity value, and to analyze the ion migration hysteresis difference of the background soil sample based on the pH hysteresis loop curves and the salinity hysteresis loop curves.

[0017] The real-time ion migration lag difference analysis module is used to collect rhizosphere soil samples from the same sesame plant when it grows to the preset first and second sampling days, and to analyze the real-time ion migration lag difference of each real-time soil sample.

[0018] The collaborative improvement state analysis module is used to spatially superimpose the ion migration hysteresis difference degree with the real-time ion migration hysteresis difference degree to obtain the superimposed interval, and analyze the collaborative improvement state of soil pH and salinity during the growth cycle of sesbania based on the superimposed interval.

[0019] This invention utilizes electric field-driven ion pre-separation to actively detect the soil's ability to migrate and fix different ions, overcoming the limitation of static measurements in reflecting dynamic ion behavior. Through hysteresis loop curve analysis in the desiccation-re-wetting cycle, it quantifies the soil's buffer memory during alternating wet and dry periods, revealing indirect evidence of microbial activity's role in soil ion immobilization. A comparative framework for hysteresis loop differences between saline and desalinated areas distinguishes between microbial-mediated ion fixation and natural leaching ion loss, enabling an objective evaluation of the actual improvement effect of microbial agents. Furthermore, through temporal difference superposition interval analysis, it outputs multiple states of microbial improvement, such as initiation, maturity, and lag, providing precise stage-specific diagnostic criteria for saline-alkali land biological improvement. Therefore, this invention proposes a method and system for monitoring and evaluating soil pH and salinity during the sesame growth cycle, solving the problem of low accuracy in monitoring soil pH and salinity during the sesame growth cycle. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating a method for monitoring and evaluating the linkage between soil pH and salinity during the growth cycle of sesbania, provided in an embodiment of the present invention.

[0021] Figure 2 This is a functional module diagram of a soil pH and salinity linkage monitoring and evaluation system for the growth cycle of sesbania provided in an embodiment of the present invention.

[0022] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0023] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0024] This application provides a method for monitoring and evaluating the linkage between soil pH and salinity during the sesame growth cycle. The executing entity of this method includes, but is not limited to, at least one electronic device that can be configured to execute the method provided in this application, such as a server or a terminal. In other words, the method can be executed by software or hardware installed on a terminal device or server device, and the software may be a blockchain platform. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cluster of cloud servers. The server can be an independent server or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0025] Reference Figure 1 The diagram shown is a flowchart illustrating a method for monitoring and evaluating the linkage between soil pH and salinity during the growth cycle of sesbania, according to an embodiment of the present invention. In this embodiment, the method includes:

[0026] S1. Before sowing sesame seeds, collect rhizosphere soil from the planting area as background soil sample, and fill the background soil sample into a measuring container with electrodes at both ends.

[0027] In this embodiment of the invention, the background soil sample refers to the original soil collected from the rhizosphere of the planting area to be monitored before sowing sesame seeds, used to establish the initial ion migration characteristics baseline of the soil in that area. The rhizosphere soil refers to the soil within 0 to 5 millimeters of the surface of the sesame root system, and this area is most significantly affected by root exudates and microbial activity.

[0028] In detail, before sowing sesame seeds, three representative sampling points were selected within the planting area. At each sampling point, with the expected location of the main stem of the sesame seed as the center, rhizosphere soil samples were collected to a depth of 10 to 20 centimeters using a sterile soil auger. The soil from the three sampling points was mixed evenly, stones and plant debris were removed, and the samples were passed through a 2-millimeter sieve to obtain background soil samples.

[0029] In this embodiment of the invention, the measuring container refers to an insulating cavity with a fixed internal volume, with inert metal electrodes, such as platinum electrodes, embedded at both ends for applying an electric field and measuring current.

[0030] In this embodiment of the invention, filling the background soil sample into a measuring container with electrodes at both ends includes:

[0031] Under inert gas protection, the background soil sample is uniformly filled into a measuring container with electrodes at both ends, and during the filling process, the background soil sample is simultaneously compacted to a preset filling ratio of the measuring container volume.

[0032] After filling is completed, an initial detection voltage is applied to the electrodes at both ends of the measuring container. Based on the initial detection voltage, the AC impedance amplitude and phase angle in the background soil sample are collected to generate an impedance spectrum curve.

[0033] The relaxation time distribution of the impedance spectrum curve was analyzed to obtain the characteristic frequencies corresponding to the relaxation peaks of different ion migrations in the background soil sample.

[0034] If the distribution of the characteristic frequency deviates from the distribution range in the preset soil sample effective frequency database, it is determined that the background soil sample has structural defects.

[0035] For background soil samples with structural defects, adjust the compressive strength and mixing method of the background soil samples until the characteristic frequency of the adjusted background soil samples falls within the specified distribution range.

[0036] In detail, inert gas protection refers to the filling operation being carried out in a nitrogen or argon atmosphere to prevent carbon dioxide in the air from dissolving in the soil pore water and thus altering the soil's original pH value. In a nitrogen-protected glove box, the background soil sample is filled into the measuring container in three stages. After each filling, a stainless steel pressure bar is used to compact the sample with a force of 5 Newtons, ensuring the top surface of the soil sample is flush with the container opening. The total filling mass is determined based on the container volume and a preset filling ratio. The filling ratio refers to the degree of compaction predetermined based on the field water holding capacity and bulk density of the background soil sample, ensuring the porosity of the filled soil sample is close to its natural state. Specifically, the field water holding capacity of the background soil sample is measured first. and dry density The filling ratio is calculated based on field water holding capacity and dry bulk density. ,Right now ,in, Soil particle density, usually taken as 2.65 g / cm³. This is an empirical coefficient, with a value range of 0.85 to 0.95. The lower limit is used for sandy soils and the upper limit is used for clay soils.

[0037] For example, for loamy soil with a bulk density of 1.2 g / cm³ and a field water holding capacity of 25%, the calculated filling ratio is approximately 80%. For instance, with a container volume of 50 cubic centimeters, a filling ratio of 80%, and a soil bulk density of 1.2 g / cm³, the total filling volume would be approximately 80 grams, though the actual mass may vary depending on the moisture content. After filling, an electrochemical workstation is used to apply a sinusoidal AC voltage of 10 mV to both electrodes, with the frequency scanning from 0.1 Hz to 10 MHz, taking 10 points every ten octaves at logarithmic intervals. The amplitude and phase angle of the current flowing through the soil sample are simultaneously measured, and curves depicting resistance and reactance versus frequency are plotted, i.e., impedance spectrum curves. Using broadband AC impedance spectroscopy instead of simple DC resistance measurement allows for the differentiation of relaxation processes of different ions and colloidal particles, providing multidimensional information for subsequent quality control.

[0038] Specifically, the impedance data is fitted to multiple relaxation time constants. Superposition: ,in Indicates at angular frequency The complex impedance of a soil sample obtained by measurement is a complex number containing information on resistance and reactance. It is used to describe the electrical response characteristics of the soil under AC electric fields of different frequencies, where resistance is the real part and reactance is the imaginary part. It represents the limiting resistance when the angular frequency approaches infinity, indicating the ohmic resistance of a soil sample at high frequencies. At this point, the polarization effects of ions and colloidal particles can be ignored, and it mainly reflects the conductivity of the soil pore solution. It is the first The resistive component of each relaxation process reflects the contribution of that relaxation process to the total impedance, and is related to the concentration and mobility of the ions or colloidal particles involved in the relaxation. It is the first The relaxation time constant of a relaxation process The imaginary unit represents the portion of the complex impedance related to the phase difference between voltage and current. Through Bayesian regularization inversion, the relaxation time distribution function is obtained, where each peak corresponds to the characteristic relaxation time of a particular ion or colloidal particle. Thus, the characteristic frequencies are obtained. For example, in the background soil sample, three distinct peaks were identified: peak A corresponds to sodium ions, with a characteristic frequency of approximately 250 Hz; peak B corresponds to chloride ions, with a characteristic frequency of approximately 600 Hz; and peak C corresponds to clay colloids, with a characteristic frequency of approximately 3500 Hz.

[0039] Further, the characteristic frequencies are compared with the distribution intervals in a preset soil sample effective frequency database, which refers to a characteristic frequency reference interval database pre-established through testing a large number of healthy soil samples, i.e., soil samples with no structural defects and normal microbial activity. For example, the relaxation peak characteristic frequency of sodium ions is usually 100 to 500 Hz, that of calcium ions is 500 to 2000 Hz, and that of clay colloid is 2000 to 10000 Hz.

[0040] Exemplarily, the database is pre-determined through 20 defect-free soil samples to obtain a sodium ion frequency interval of [200, 400] Hz, a chloride ion frequency interval of [500, 800] Hz, and a clay colloid frequency interval of [3000, 5000] Hz. If all characteristic frequencies of the background soil sample fall within the intervals, the soil sample is judged to be qualified; if a certain characteristic frequency deviates, it is judged that a structural defect exists. For example, the sodium ion peak appears at 80 Hz, which indicates that large pores in the soil sample lead to a shortened ion migration path. Using the deviation of characteristic frequency to quantify structural defects significantly improves the objectivity and repeatability of the filling quality. For a soil sample judged to be defective, it is taken out from the container, re-sieved, for example, the aggregates are broken through a 0.5 mm sieve mesh, then the compaction force is adjusted, for example, increased from 5 Newtons to 8 Newtons, and the soil sample is filled and tested again until all characteristic frequencies fall within the intervals, ensuring that each soil sample reaches a consistent structural state before entering the subsequent electric field driving test, and eliminating the influence of uneven soil samples on the difference degree of ion migration hysteresis.

[0041] Further, only qualified soil samples that have passed the relaxation spectrum test can ensure the repeatability of electric field-driven ion migration; otherwise, structural defects will lead to abnormal ion migration paths, rendering the division of the salt-rich zone and the desalination zone meaningless.

[0042] S2. Applying a forward DC voltage to the electrode at one end of the measuring container to drive soluble salt ions in the background soil sample to migrate to the opposite electrode, and dividing the background soil sample into a salt-rich zone and a desalination zone based on the migration result.

[0043] In the embodiment of the present invention, the forward DC voltage refers to a constant polarity voltage applied to the electrode at one end of the measuring container, and the opposite electrode is grounded or connected to a negative potential, wherein the measuring container holding the qualified background soil sample is connected to a programmable DC power supply through a wire to drive the soluble salt ions in the background soil sample to migrate to the opposite electrode.

[0044] In the embodiment of the present invention, the salt-rich zone refers to a region where soluble salt ions, such as sodium ions and chloride ions, migrate to the opposite electrode and accumulate under the action of an electric field, and the salinity of this region is significantly higher than that of the original soil sample. The desalination zone refers to a region close to the working electrode side, where the salinity is significantly reduced after the salt ions are driven away.

[0045] In this embodiment of the invention, the step of dividing the background soil sample into saline-rich and desalinized zones based on the migration results includes:

[0046] After applying a positive DC voltage to one end electrode of the measuring container, the voltage amplitude is gradually increased according to a set voltage increment rate, while the real-time current value passing through the measuring container is continuously collected.

[0047] A voltage-current response curve is generated based on the voltage amplitude and the real-time current value. A second-order difference analysis is performed on the voltage-current response curve to obtain the abrupt change inflection point where the current value changes abruptly with the increase of voltage, and the trigger voltage value corresponding to each abrupt change inflection point is recorded.

[0048] After the voltage has been applied for a preset duration or the current value has stabilized, the power supply is stopped, and the boundary position between the salt-rich zone and the desalination zone is recorded at the moment the power supply is stopped.

[0049] The migration rate of each ion is calculated based on the distribution range of the trigger voltage value. Based on the migration rate and the boundary position, the region in the measurement container that is close to the positive electrode and has a migration rate lower than a preset first migration threshold is divided into a desalination region, and the region that is close to the opposite electrode and has an ion migration rate higher than a preset second migration threshold is divided into a salt-rich region.

[0050] In detail, a programmable DC power supply was used to linearly increase the voltage from 0 volts to 50 volts at a rate of 5 volts per minute. For sandy soils, the upper limit could be adjusted to 40V; for clay soils, the upper limit could be adjusted to 60V, with the specific adjustment determined by the current stabilizing point, i.e., a change rate of less than 1% / min. Simultaneously, current values ​​were collected at a sampling rate of 10 times per second, and the corresponding voltage values ​​were recorded. Using a linear voltage increment instead of a step voltage allowed for continuous observation of the migration initiation behavior of different ions at their respective critical voltages, avoiding transient overshoot interference caused by step excitation. The collected voltage-current data were plotted as a curve. A second-order difference calculation was performed on this curve, i.e., the second-order difference between three adjacent data points was calculated. ,in For current, For voltage, It is a second-order differential voltage. For data points, This represents a second-order differential current. Furthermore, the occurrence of a local maximum in the absolute value of the second-order difference corresponds to abrupt inflection points. For example, when the voltage rises to 18 volts, the second-order difference exhibits its first positive maximum, corresponding to the start of significant sodium ion migration; at 32 volts, a second positive maximum occurs, corresponding to the start of chloride ion migration; and at 41 volts, a third positive maximum occurs, corresponding to the start of calcium ion migration. The trigger voltage value is recorded. Second-order differential analysis can automatically identify multiple abrupt inflection points, thereby separating the migration behavior of different ion components.

[0051] Specifically, a voltage is continuously applied until the rate of change of current is less than 1% over 5 consecutive minutes. At this point, the power is stopped, and the conductivity of the soil sample is immediately measured every 2 mm along the axial direction of the container using a miniature conductivity probe. For example, in the conductivity distribution curve along the axial direction, starting from the working electrode side, the conductivity first decreases in the desalination zone, then rises rapidly in the transition zone, and finally tends to stabilize at a high value in the salt-rich zone. The rate of change of conductivity at adjacent measurement points along the axial direction is calculated. When the rate of change of conductivity exceeds 0.5 mS / cm·mm for three consecutive measurement points, the first point exceeding the threshold is marked as the boundary position. The boundary is determined by static conductivity scanning after the power is stopped, rather than relying on dynamic measurements during the power-on process, thus avoiding interference from the electric field on the boundary position.

[0052] The migration rate is inversely proportional to the trigger voltage; that is, the lower the trigger voltage, the easier it is for the ion to migrate. Let the trigger voltage of the t-th ion be... Its relative migration rate The median of all ion migration rates is used as the first migration threshold, and the third quartile of all ion migration rates is used as the second migration threshold. The region in the measuring container near the positive electrode with a migration rate below the median is designated as the desalination zone, i.e., the area from the positive electrode end face to the boundary; the region near the opposing electrode with a migration rate above the third quartile is designated as the salt-rich zone, i.e., the area from the boundary to the opposing electrode end face. Furthermore, the intermediate transition zone, i.e., the migration rate between the two, can be discarded. Using statistical quantiles to dynamically determine the thresholds, rather than fixed values, makes the classification method adaptive to the ionic composition of different soil samples, highly versatile, and able to accurately reflect the differences in behavior of different ion components under an electric field.

[0053] Furthermore, the boundary locations of the salt-rich and desalination zones, as well as the trigger voltage values ​​of each ion, are used for comparison of subsample acquisition locations and trigger voltage offsets.

[0054] S3. After power is turned off, sub-samples are collected from the salt-rich area and the desalination area respectively. A dehumidification-rehumidification cycle is performed on each sub-sample, and the pH value and salinity value of each sub-sample are continuously measured during the dehumidification and rehumidification stages.

[0055] In this embodiment of the invention, after power is turned off, a certain number of sub-samples are collected from both the salt-rich and desalination zones using a micro sampler, with each sub-sample weighing approximately 5 grams wet. The dehydration-rehydration cycle refers to the process of first controlling the dehydration of soil samples to the wilting point moisture content, and then rehydrating them to the initial moisture content using a specific solution. This process is used to simulate natural wet-dry cycles and to detect the buffer memory of the soil.

[0056] In this embodiment of the invention, the step of performing a dehumidification-rehumidification cycle on each sub-sample includes:

[0057] Each collected sub-sample was placed in an independent measurement chamber;

[0058] The desiccation rate and rewetting rate for each sub-sample are determined based on the clay content of the background soil sample.

[0059] During the dehydration stage, sub-samples in different measurement chambers are dehydrated according to the dehydration rate to obtain the sample moisture content;

[0060] When the moisture content of the sample decreases to the preset wilting point moisture content, the sub-samples in different measurement chambers are rehumidified according to the rehumidification rate until the moisture content of the sample is restored to the initial moisture content before the dehumidification operation.

[0061] An asymmetric rate cycle is generated based on the dehumidification rate and the rehumidification rate. During the asymmetric rate cycle, data pairs of pH and salinity values ​​in the two measurement chambers are continuously monitored as a function of water content.

[0062] In detail, the sub-samples from the saline area are placed in measurement chamber A, and the sub-samples from the desalinated area are placed in measurement chamber B. Each chamber has a microporous plate with an adjustable opening at the bottom, and a pH electrode and a conductivity electrode are embedded inside. The sub-samples from the saline and desalinated areas are processed separately in independent chambers to avoid cross-contamination. At the same time, the drying and wetting rates of each chamber can be controlled independently to adapt to the differences in soil structure in different areas.

[0063] Clay content refers to the percentage by mass of particles smaller than 0.002 mm in soil, directly affecting the soil's water-holding capacity and hysteresis effect. Based on the clay content C of the background soil sample (range 0–100%), baseline dehydration rate V_dry_base and baseline rewetting rate V_wet_base were determined. The baseline rates were obtained through pre-experimental calibration: three background soil samples were taken using a constant temperature and humidity chamber, with temperature control accuracy ±0.5℃ and humidity control accuracy ±2%RH for baseline rate calibration. Each measurement was repeated three times, and the average value was taken, with a relative deviation not exceeding 5%. Then, the natural air-drying rate and capillary water absorption rate were measured under a constant temperature of 25℃, where the natural air-drying rate was used as the dehydration baseline and the capillary water absorption rate as the rewetting baseline. The average value of the three measurements was taken as the baseline rate. For example, for loam soil with a clay content of 18%, the calibrated baseline dehydration rate was approximately a decrease in water content of 5 percentage points per hour, and the baseline rewetting rate was approximately an increase in water content of 3 percentage points per hour. Then, the actual dehydration rate and rehydration rate are calculated using empirical formulas: Dehydration rate = V_dry_base × (1 + C / 50), Rehydration rate = V_wet_base × (1 - C / 50). The dehydration rate and rehydration rate are not equal; for example, dehydration is fast and rehydration is slow, or vice versa, to amplify the hysteresis effect and form an asymmetric cycle. Furthermore, the dehydration / rehydration rate is not fixed but dynamically adjusted according to the clay content. This is because soils with high clay content have strong water retention and a significant hysteresis effect, requiring a faster dehydration rate to fully activate the hysteresis loop, and vice versa.

[0064] Specifically, dehumidification was initiated by opening the microplate to the calculated opening based on a pre-calibrated flow-aperture curve, while maintaining a constant chamber temperature of 25°C using hot air circulation. The subsample mass, pH value, and conductivity value were recorded every 10 minutes using an electronic balance at the bottom of the chamber. The subsample mass was converted to water content using the formula (wet weight - dry weight) / dry weight, and the pH value was converted to salinity using a standard curve of conductivity and salinity. Dehumidification was stopped when the water content dropped to the wilting point. The wilting point water content refers to the soil mass water content corresponding to a soil water potential of -1.5 MPa, which is the known permanent wilting point for plants. The moisture characteristic curve of the background soil sample was determined using a pressure membrane method, and the water content corresponding to a water potential of -1.5 MPa was read from this curve as the wilting point water content. For example, for loamy soil with a clay content of 18%, the wilting point moisture content is approximately 35%–40% of field capacity. If pressure membrane measurement is not possible, it can be estimated using an empirical formula: wilting point moisture content (%) = clay content (%) × 0.4 + 2.5. Therefore, the measurement or estimation method can be selected according to the actual situation. Furthermore, real-time recording of moisture content, rather than relying on preset time points, ensures that each cycle occurs at the same moisture content switching stage, improving repeatability.

[0065] Rewetting was initiated by adding rewetting solution dropwise at a rate of 3.2% / hour using a peristaltic pump, with data recorded every 10 minutes until the water content returned to its initial value. The ionic composition of the rewetting solution was pre-analyzed using the filtrate from the background soil sample, for example, sodium ions 20 mmol / L, chloride ions 15 mmol / L, calcium ions 5 mmol / L, pH 8.0. The rewetting solution had the same ionic composition as the original pore water, avoiding interference from the introduction of exogenous ions in pH and salinity measurements.

[0066] Furthermore, the asymmetric rate cycling leads to a clear separation between the dehydration and rehydration pathways, amplifying the impact of microbial activity on hysteresis characteristics and making subtle differences easier to detect. Therefore, continuous monitoring of the water content-pH data pairs during the dehydration phase, the rehydration phase sequence, and the corresponding salinity sequence in the saline zone can be obtained in the asymmetric rate cycling; the same applies to the desalination zone.

[0067] Furthermore, water content-pH and water content-salinity data pairs are direct inputs for generating hysteresis loop curves. The amplified hysteresis signal generated by asymmetric rate cycling allows even very weak buffer memory changes caused by microbial activity, such as when there is no difference in static pH / salinity, to be detected in the hysteresis loop features.

[0068] S4. Generate pH hysteresis loop curves and salinity hysteresis loop curves for the salt-rich area and the desalination area respectively based on the pH value and the salinity value, and analyze the ion migration hysteresis difference of the background soil sample based on the pH hysteresis loop curves and the salinity hysteresis loop curves.

[0069] In this embodiment of the invention, the hysteresis loop curve refers to a closed loop curve formed by connecting the data points of the dehumidification stage and the data points of the rehumidification stage in the dehumidification-rehumidification cycle, with water content as the abscissa and pH or salinity as the ordinate.

[0070] In this embodiment of the invention, generating pH hysteresis loop curves and salinity hysteresis loop curves for the salt-rich zone and the desalination zone respectively based on the pH value and the salinity value includes:

[0071] Extract the first data pair of pH value changes with water content of the sub-sample of salt-rich area, connect the data points of the dehumidification stage in the order of decreasing water content to form the first dehumidification trajectory based on the first data pair, and connect the data points of the rehumidification stage in the order of increasing water content to form the first rehumidification trajectory.

[0072] The first dehumidification trajectory and the first rehumidification trajectory are used to form a pH hysteresis loop curve for the salt-rich zone.

[0073] Extract a second data pair of salinity values ​​as a function of water content from a subsample of the same saline-rich area, and generate a salinity hysteresis loop curve for the saline-rich area based on the second data pair.

[0074] A third data pair showing the change in pH value with water content and a fourth data pair showing the change in salinity value with water content are extracted from the subsamples of the desalination area. A hysteresis loop curve for pH value of the desalination area is generated based on the third data pair, and a hysteresis loop curve for salinity value of the desalination area is generated based on the fourth data pair.

[0075] In detail, based on the dehumidification stage data pairs of the saline area pH, for example: (moisture content 0.30, pH 8.12), (0.28, 8.10), (0.26, 8.07), ..., (0.105, 7.65) (wilt point), these points are connected sequentially using linear interpolation in descending order of moisture content to form a dehumidification trajectory. Similarly, the data points of the rehumidification stage are connected sequentially using linear interpolation in ascending order of moisture content to form a rehumidification trajectory. When the moisture content interval between adjacent data points exceeds 5 percentage points, a linear interpolation point is added between the two points with an interpolation interval of 1 percentage point to ensure the smoothness of the trajectory and to retain the true response of each measured data point, avoiding smoothing that masks outliers that may reflect local hotspots of microbial activity.

[0076] Specifically, the dehydration trajectory and the rehydration trajectory are plotted on the same coordinate system. The area between the two is the pH hysteresis loop curve of the salt-rich area. The hysteresis loop curve intuitively shows the irreversibility of the pH response of the soil during water loss and water absorption. The area and shape of the loop can serve as the basis for subsequent feature extraction. Furthermore, hysteresis feature point sets were extracted from the dehydration and rehydration trajectories, including the dehydration start point, rehydration end point, maximum hysteresis interval point, and curvature abrupt change points between dehydration and rehydration. These feature points were constructed into multiple nested sub-cycles according to the time sequence of the dry-wet cycle. Each sub-cycle consists of an arc segment between a dehydration feature point and a rehydration feature point, representing the local hysteresis behavior of pH buffer memory during the formation and rupture of water film within a specific pore size range in the soil. Then, the closed area, curvature change rate, and area transfer coefficient between adjacent sub-cycles were calculated for each sub-cycle to construct a hierarchical hysteresis chain from micropores to macroscopic soil. Finally, the sub-cycles were superimposed stepwise according to water content from high to low and fused with the area transfer coefficient of each sub-cycle as the weight to generate a composite hysteresis loop curve with a multi-layer memory structure. This allows for the differentiation of the contribution of microbial extracellular polymers to the stability of water film at different pore scales, enabling the hysteresis loop curve to reflect not only macroscopic pH irreversibility. Similarly, the salinity data pairs from the salinity-rich areas were processed to generate salinity hysteresis loop curves for the salinity-rich areas. Hysteresis loops for pH and salinity were established separately, providing two independent dimensions for subsequent comparisons of eccentricity differences. This is because pH is mainly affected by carbonate balance and organic acids, while salinity is mainly affected by the total amount of soluble salts, and the two may be decoupled.

[0077] Furthermore, the above operation was repeated for the desalination subsamples to obtain the pH hysteresis loop curve and the salinity hysteresis loop curve for the desalination area. The hysteresis loops of both the salt-rich and desalination areas were retained, allowing for the calculation of the difference between them, thereby eliminating the background influence of soil texture on the hysteresis characteristics.

[0078] In this embodiment of the invention, the ion migration hysteresis difference is a quantitative index used to comprehensively reflect the differences in pH and salinity hysteresis characteristics between salt-rich areas and desalination areas. The larger the value, the more significant the ion concentration gradient driven by the electric field and the weaker the soil's ability to fix ions.

[0079] In this embodiment of the invention, the step of analyzing the ion migration hysteresis difference of the background soil sample based on the pH hysteresis loop curve and the salinity hysteresis loop curve includes:

[0080] Ellipse fitting was performed on the pH hysteresis loop curve and the salinity hysteresis loop curve respectively, and the length of the major axis, the length of the minor axis, and the angle between the major axis and the water content coordinate axis of the fitted ellipse were calculated.

[0081] The ratio of the major axis length to the minor axis length is determined as the eccentricity, which reflects the degree of anisotropy of the soil's pH or salinity response during alternating wet and dry periods.

[0082] The included angle is determined as the response hysteresis angle, which reflects the directional shift characteristics of the soil's response to changes in water content.

[0083] The first eccentricity difference between the pH hysteresis loop curve of the salt-rich zone and the pH hysteresis loop curve of the desalination zone, and the second eccentricity difference between the salinity hysteresis loop curve of the salt-rich zone and the salinity hysteresis loop curve of the desalination zone are calculated based on the eccentricity and the response hysteresis angle.

[0084] The weighted sum of the first eccentricity difference and the second eccentricity difference is used as the ion migration hysteresis difference of the background soil sample.

[0085] In detail, elliptic fitting was performed on all measured data points on the pH hysteresis loop curve of the saline region. The ellipse equation was solved using the least squares elliptic fitting algorithm. The parameters are obtained by constructing a design matrix and solving an overdetermined system of linear equations, with the goal of minimizing the algebraic distance, thus obtaining the ellipse parameters, i.e., the length of the major axis. minor axis length and Angle between axes After fitting, the coefficient of determination R² is calculated. When R² ≥ 0.85, the fitting result is considered valid; when R² < 0.85, it indicates that the shape of the hysteresis loop deviates significantly from the ellipse. In this case, the ellipse fitting method is abandoned, and the circumscribed rectangle method is used to calculate the equivalent aspect ratio of the hysteresis loop as a substitute estimate of the eccentricity. The circumscribed rectangle method is as follows: calculate the length of the minimum circumscribed rectangle of the hysteresis loop curve on the water content axis, i.e., the span in the water content direction and the width in the pH or salinity direction, and use the aspect ratio as the equivalent eccentricity.

[0086] The hysteresis loop is abstracted as an elliptical geometry, rather than simply calculating its area, because hysteresis loops with the same area may have different shapes, such as flat or circular. Eccentricity can capture this difference. A larger eccentricity indicates a flatter hysteresis loop, and a more irreversible pH response in soil during wet-dry cycles. Eccentricity is dimensionless and unaffected by coordinate scaling, facilitating comparisons between different soil samples. The response hysteresis angle is... , A positive value indicates that the desiccation trajectory is to the right of the rewetting trajectory, meaning that at the same moisture content, the desiccation pH is lower than the rewetting pH. This reflects the memory of the soil's acidification buffering capacity. The hysteresis angle provides directional information, for example... A value close to 0 degrees indicates symmetry in the hysteresis loop. A larger value indicates a significant response lag.

[0087] Specifically, elliptical fitting was performed on the salinity hysteresis loop in the saline-rich area, the pH hysteresis loop in the desalination area, and the salinity hysteresis loop in the desalination area to obtain their respective eccentricities. The difference between the pH eccentricity in the saline-rich area and the pH eccentricity in the desalination area was determined as the first eccentricity difference, and the difference between the salinity eccentricity in the saline-rich area and the salinity eccentricity in the desalination area was determined as the second eccentricity difference. By using the difference rather than the absolute value, the general influence of soil background texture on the shape of the hysteresis loop was eliminated, highlighting the regional differences caused by electric field-driven ion separation. The weighted sum of the first and second eccentricity differences was used as the ion migration hysteresis difference of the background soil sample. The ion migration hysteresis difference of the background soil sample was used as the benchmark value of the real-time soil sample difference and the origin of the difference benchmark axis.

[0088] The weighting coefficients can be calculated based on the clay content (C) and organic matter content (OM) of the background soil sample, with the ratio r = C / OM. When r is in the range of 0.5 to 5.0, the weights are calculated using the following formulas: w_pH = 0.3 + 0.02 × r, w_sal = 1 - w_pH, where w_pH is the weighting coefficient for pH and w_sal is the weighting coefficient for salinity. The values ​​of 0.3 and 0.02 are determined through statistical fitting of the correlation analysis between the clay content, organic matter content, and hysteresis loop of typical saline-alkali soils. When r < 0.5, w_pH = 0.35 and w_sal = 0.65 are used, emphasizing the dominant role of salinity changes. When r > 5.0, w_pH = 0.55 and w_sal = 0.45 are used, emphasizing the dominant role of pH changes. The weighting coefficients are dynamically determined by the soil's physicochemical properties. Clay minerals are the main contributors to soil cation exchange capacity and pH buffering capacity. The higher their content, the stronger the soil's buffer memory of pH changes. Therefore, the pH hysteresis loop is more sensitive to the response of microbial improvement activities and should be given a higher weight. Organic matter not only participates in pH buffering but also regulates salt transport by affecting soil aggregate structure and ion exchange sites. Therefore, when the relative content of organic matter is high, the weight of the salinity index should be increased accordingly.

[0089] S5. When the sesame plants have grown to the preset first and second sampling days, rhizosphere soil samples from the same sesame plant are collected as real-time soil samples, and the differences in real-time ion migration lag between the real-time soil samples are analyzed.

[0090] In this embodiment of the invention, real-time soil samples refer to soil samples collected from the rhizosphere of the same sesame plant when the sesame has grown to a preset number of days. The first sampling days and the second sampling days correspond to the early stage of sesame growth, such as 70 days after sowing and the middle stage, such as 110 days after sowing, respectively, and are used to monitor the development process of the microbial community.

[0091] In this embodiment of the invention, the analysis of the real-time ion migration hysteresis difference of each real-time soil sample includes:

[0092] When the sesame plants have grown to the preset first sampling day, the first real-time rhizosphere soil sample is collected with the main stem of the sesame plant as the center and according to the preset sampling depth and sampling distance.

[0093] The first real-time soil sample was subjected to a dehumidification-rewetting cycle to obtain the first real-time ion migration hysteresis difference of the first real-time soil sample.

[0094] When the sesame plants have grown to the preset second sampling day, the second real-time rhizosphere soil is collected as the second real-time soil sample, and the second real-time soil sample is subjected to a dehumidification-rehydration cycle to obtain the second real-time ion migration hysteresis difference of the second real-time soil sample.

[0095] Record the sets of trigger voltage values ​​for the first real-time soil sample and the second real-time soil sample during the application of a positive DC voltage, respectively.

[0096] The set of trigger voltage values ​​is compared with the set of background trigger voltage values ​​of the background soil sample in terms of offset direction. If the offset direction is consistent and the offset amount changes monotonically, it is determined that the ion migration characteristics of the real-time soil sample have changed directionally.

[0097] For example, 70 days after sowing sesame seeds, approximately 100 grams of rhizosphere soil was collected using a soil auger at a depth of 15 cm and 8 cm from the main stem of the sesame seed. Visible roots and stones were removed, and the soil was sieved through a 2 mm sieve to obtain the first real-time soil sample. The sampling location was consistent with the background soil sample, i.e., at the same depth and distance, to ensure comparability. Simultaneously, the real-time soil sample also originated from the rhizosphere to reflect the influence of microbial activity. The first real-time soil sample was processed using the same steps S1 to S4, including filling, electric field driving, dehumidification and rehumidification, hysteresis loop ellipse fitting, and weighted difference calculation, to obtain the first real-time ion migration hysteresis difference D1. Therefore, the analytical process of completely replicating the background soil sample was ensured, guaranteeing the comparability of the difference and avoiding systematic errors caused by methodological differences. As another example, 110 days after sowing sesame seeds, a second real-time soil sample was collected and processed to obtain the second real-time ion migration hysteresis difference D2. Therefore, by observing the difference between the two time points, we can observe the dynamic trend of microbial improvement, such as a decrease in D1 and a rebound in D2, which may indicate that the microorganisms have become active.

[0098] Specifically, during the application of a positive DC voltage, the trigger voltage set for the first real-time soil sample was recorded. For example, the trigger voltage for sodium ions was 19 volts, and the background soil sample voltage was 18 volts; for chloride ions, it was 33 volts, and the background soil sample voltage was 32 volts; for calcium ions, it was 43 volts, and the background soil sample voltage was 41 volts. The trigger voltage set for the second real-time soil sample was recorded: sodium ions were 20 volts, chloride ions were 34 volts, and calcium ions were 44 volts. The background trigger voltage set was 18 volts for sodium, 32 volts for chloride, and 41 volts for calcium. The trigger voltage is a direct electrochemical characterization of ion migration properties, unaffected by short-term fluctuations in soil moisture content and temperature, and is more stable than static pH / salinity.

[0099] For trigger voltages of at least three main ions, if two or more (including two) of them have the same offset direction (i.e., all are positive offsets or all are negative offsets), then the offset directions are considered to be consistent. For monotonically changing conditions, let the trigger voltage offset of the t-th ion in the first real-time soil sample be... The trigger voltage offset of the t-th ion in the second real-time soil sample is If for at least two principal ions, the following conditions are met: When the offset direction is positive or When the offset direction is negative, the offset is considered to be monotonically changing. When the absolute value of the offset is less than 2% of the background trigger voltage, it is considered a fluctuation within the measurement error range and is not included in the monotonicity determination. Therefore, if the offset direction is consistent and the offset is monotonically changing, it is determined that the ion migration characteristics of the real-time soil sample have changed directionally, that is, microbial activity makes ions require a higher voltage to migrate, indicating that the ions are fixed by soil colloids. False positives caused by random fluctuations or measurement errors can be ruled out. Only continuous microbial action can lead to monotonically changing offsets.

[0100] Furthermore, based on the results of D1, D2, and the offset direction determination, an overlap interval is constructed and used as an important basis for judging the suppression / activation / transition state.

[0101] S6. The spatial distribution of the ion migration hysteresis difference and the real-time ion migration hysteresis difference is superimposed to obtain the superimposed interval. Based on the superimposed interval, the synergistic improvement status of soil pH and salinity during the growth cycle of sesbania is analyzed.

[0102] In this embodiment of the invention, the overlapping interval refers to projecting the real-time difference at different time points onto a reference axis with the background difference as the origin to form a one-dimensional interval. The change trend of the improved state is judged by the sign and length of the interval.

[0103] In this embodiment of the invention, the step of spatially superimposing the ion migration hysteresis difference with the real-time ion migration hysteresis difference to obtain the superimposed interval includes:

[0104] Using the difference in ion migration hysteresis of the background soil sample as the benchmark value, a one-dimensional difference benchmark axis is constructed, wherein the origin of the difference benchmark axis corresponds to the background difference, the positive half axis represents the direction greater than the background difference, and the negative half axis represents the direction less than the background difference.

[0105] The first real-time ion migration hysteresis difference in the real-time ion migration hysteresis difference is projected onto the difference reference axis to obtain the first projection point; the second real-time ion migration hysteresis difference in the real-time ion migration hysteresis difference is projected onto the same difference reference axis to obtain the second projection point.

[0106] Using the first projection point and the second projection point as endpoints, a closed interval is constructed on the difference reference axis. The closed interval is used as the initial overlapping interval, wherein the left boundary of the closed interval is the smaller value between the first projection point and the second projection point, and the right boundary is the larger value between the first projection point and the second projection point.

[0107] Data on soil texture type and groundwater depth in the sesame planting area are obtained. The initial overlapping interval is then bidirectionally corrected based on the soil texture type and groundwater depth data to obtain the overlapping interval.

[0108] In detail, a one-dimensional axis is constructed with the background difference D0 as the origin. The positive half-axis indicates a difference greater than D0, and the negative half-axis indicates a difference less than D0. The absolute difference is converted into an offset relative to the background, eliminating the differences in background difference values ​​between different soils and allowing for a unified comparison of monitoring results from different plots and at different times. The first real-time difference D1 is projected at point P1 = D1 - D0; the second real-time difference D2 is projected at point P2 = D2 - D0. The sign of the projection point directly indicates whether the real-time difference is higher or lower than the background value. A negative value indicates that microbial activity has not yet restored the difference to the background level, possibly because the inoculant has not yet fully colonized. A closed interval is constructed with P1 and P2 as endpoints, with the left boundary being min(P1,P2) and the right boundary being max(P1,P2). The initial overlapping interval is [min(P1,P2), max(P1,P2)], where the interval length reflects the magnitude of the difference change between the two time points. When the interval lies entirely on the negative half-axis, it indicates that both real-time differences are less than the background value.

[0109] Specifically, two-way correction refers to adjusting the left and right boundaries of the interval to expand or contract according to soil texture and groundwater depth, respectively. For example, the soil texture is sandy, loamy, clayey, etc.; the groundwater depth is shallower than 1 meter, 1-2 meters, deeper than 2 meters, etc. First, obtain the soil sand content of the planting area. and groundwater level depth Calculate the correction factor H, i.e. ,in, This is the sand grain correction factor, typically taken as 0.15. α is the water level correction factor, typically taken as 0.10. The range and parameters of the correction factor are derived from statistical calibration based on years of monitoring data from saline-alkali land. α and β can be appropriately adjusted according to the actual hydrogeological conditions of the region. When H > 50%, the interval expands towards the positive half-axis to correct the overestimation of variability caused by natural leaching of sandy soil; when When the groundwater level is less than 50%, H < 1, and the interval shrinks towards the negative half-axis; when the groundwater level is shallow, i.e. When the depth is less than 2m, H increases; when the groundwater level is deeper, that is... When the value is greater than 2m, H decreases. The corrected overlap interval boundaries are: Q1=P1×H, Q2=P2×H. For example, when the calculated value of the correction coefficient H exceeds the range of [0.7,1.3], H=0.7 (lower limit) or H=1.3 (upper limit) is taken to avoid overcorrection.

[0110] Furthermore, the corrected overlay interval will determine the state of synergistic improvement of soil pH and salinity during the sesbania growth cycle. The interval is entirely located on the negative half-axis, indicating that it may output an inhibitory or initiating state, depending on the sign and length.

[0111] In this embodiment of the invention, the synergistic improvement state of soil pH and salinity refers to a functional state in which the pH and salinity values ​​of sesbania rhizosphere soil exhibit a synchronous, coupled, and irreversible downward trend during alternating wet and dry periods, driven by microbial activity, while the soil's memory capacity for ion migration and buffering is enhanced.

[0112] In this embodiment of the invention, the step of analyzing the synergistic improvement status of soil pH and salinity during the growth cycle of sesbania based on the superimposed interval includes:

[0113] Determine the signs of the left and right boundaries of the overlapping interval relative to the origin of the reference axis;

[0114] If the signs of both the left and right boundaries are negative, it is determined to be an inhibited state; if the signs of both the left and right boundaries are positive, it is determined to be an activated state; if the signs of the left and right boundaries are opposite, it is determined to be a transitional state.

[0115] When the state is determined to be active, the ratio of the length of the overlapping interval to the background difference is calculated. If the ratio is less than the preset compaction threshold, the evaluation result that the microbial synergistic improvement has entered a stable and mature state is output. If the ratio is greater than or equal to the preset compaction threshold, the evaluation result that the microbial synergistic improvement is still in a fluctuating development state is output.

[0116] When the state is determined to be suppressed, if the difference in the second real-time ion migration hysteresis is greater than the difference in the first real-time ion migration hysteresis, the evaluation result of natural leaching-dominated decline is output; if the difference in the second real-time ion migration hysteresis is less than or equal to the difference in the first real-time ion migration hysteresis, the evaluation result of no effective improvement activity is output.

[0117] When the state is determined to be transitional, the evaluation results of the microbial synergistic improvement are in the initiation and activation phase.

[0118] In detail, determine the signs of the left and right boundaries of the overlapping interval relative to the origin: if both boundaries are negative, it indicates that the real-time difference is always less than the background value, and output an inhibited state. An inhibited state means that the real-time difference is continuously lower than the background value, possibly because microbial activity is inhibited or soil structure is degraded, that is, microbial activity may be inhibited or not activated; if both are positive, output an activated state. An activated state means that the real-time difference is continuously higher than the background value, indicating that microorganisms have enhanced the soil's ion fixation capacity, that is, microbial activity has enhanced the ion fixation capacity; if one is positive and the other is negative, output a transitional state. A transitional state means that one is lower than the background and the other is higher than the background, indicating that improvement is happening but unstable, that is, improvement is in the process of starting.

[0119] Specifically, when the condition is determined to be in an active state, the ratio of the interval length to D0 is calculated. If the ratio is less than the compaction threshold, the output indicates that the microbial synergistic improvement has entered a stable and mature state; otherwise, the output indicates a fluctuating development state. The compaction threshold is a dimensionless parameter used to distinguish between stable maturity and fluctuating development in the improvement state. Stable maturity refers to a small difference in interval length relative to the background, while fluctuating development refers to a large difference in interval length relative to the background. The compaction threshold can be calculated by collecting historical monitoring data from at least five plots with known improvement effects, including at least three plots with confirmed successful and stable improvement and at least two plots with unstable improvement effects. The ratio of the superimposed interval length to the background difference for each plot is calculated, and the geometric mean of the maximum value of this ratio in stable plots and the minimum value of this ratio in unstable plots is used as the compaction threshold. The applicable compaction threshold can be determined based on the actual plot conditions.

[0120] When the state is determined to be inhibited, comparing D2 and D1: if D2 > D1, the output shows a decrease in the natural leaching-dominated type, indicating that the difference is recovering towards the background value. However, the reason for the recovery may be salt leaching rather than microbial fixation, because although the trigger voltage offset direction is consistent, the offset amount is small, indicating weak ion fixation. Otherwise, the output shows no effective improvement activity. When the state is determined to be transitional, the output shows that microbial synergistic improvement is in the initiation and activation stage. Therefore, by constructing a difference baseline axis and overlapping intervals, the comparison between the background and real-time is transformed into geometric interval analysis, and corrected by combining soil texture and groundwater level, ultimately outputting multiple refined improvement state types.

[0121] Furthermore, the improved state type can be directly used to guide production practices. For example, when the output of the naturally leaching-dominant type decreases, it means that there is no need to supplement the microbial agent, only to control irrigation; when the activated type is stable and mature, it means that the microbial agent has taken effect and the status quo can be maintained.

[0122] like Figure 2 The diagram shown is a functional module diagram of a soil pH and salinity linkage monitoring and evaluation system for the sesame growth cycle provided in an embodiment of the present invention.

[0123] The soil pH and salinity linkage monitoring and evaluation system 100 for the sesame growth cycle described in this invention can be installed in an electronic device. Depending on the functions implemented, the soil pH and salinity linkage monitoring and evaluation system 100 for the sesame growth cycle may include a background soil sample filling module 101, a background soil sample division module 102, a pH and salinity value analysis module 103, an ion migration hysteresis difference analysis module 104, a real-time ion migration hysteresis difference analysis module 105, and a collaborative improvement status analysis module 106. The modules described in this invention can also be referred to as units, which are a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and are stored in the memory of the electronic device.

[0124] In this embodiment, the functions of each module / unit are as follows:

[0125] The background soil sample filling module 101 is used to collect rhizosphere soil in the planting area as a background soil sample before sowing sesame seeds, and fill the background soil sample into a measuring container with electrodes at both ends.

[0126] The background soil sample division module 102 is used to apply a positive DC voltage to one end electrode of the measuring container, drive soluble salt ions in the background soil sample to migrate to the opposite electrode, and divide the background soil sample into a salt-rich area and a desalination area based on the migration result.

[0127] The pH and salinity analysis module 103 is used to collect sub-samples from the salt-rich area and the desalination area after power is turned off, perform dehumidification-rehumidification cycle operation on each sub-sample, and continuously measure the pH and salinity of each sub-sample during the dehumidification and rehumidification stages.

[0128] The ion migration hysteresis difference analysis module 104 is used to generate pH hysteresis loop curves and salinity hysteresis loop curves for salt-rich areas and desalination areas respectively based on the pH value and the salinity value, and to analyze the ion migration hysteresis difference of the background soil sample based on the pH hysteresis loop curves and the salinity hysteresis loop curves.

[0129] The real-time ion migration lag difference analysis module 105 is used to collect rhizosphere soil from the same sesame plant as real-time soil samples when the sesame plant has grown to the preset first sampling day and second sampling day, and to analyze the real-time ion migration lag difference of each real-time soil sample.

[0130] The synergistic improvement state analysis module 106 is used to spatially superimpose the ion migration hysteresis difference degree with the real-time ion migration hysteresis difference degree to obtain the superimposed interval, and analyze the synergistic improvement state of soil pH and salinity during the growth cycle of sesbania based on the superimposed interval.

[0131] In detail, the modules of the soil pH and salinity linkage monitoring and evaluation system 100 for the sesame growth cycle described in this embodiment of the invention adopt the same characteristics as those described above. Figure 1 The method described herein is the same as the method for monitoring and evaluating soil pH and salinity in conjunction with the growth cycle of sesbania, and can produce the same technical effect, so it will not be elaborated here.

[0132] In the several embodiments provided by this invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0133] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0134] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0135] 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.

[0136] Therefore, the embodiments should be regarded as exemplary and non-limiting in all respects. The scope of the invention is not limited to the foregoing description, and all variations within the meaning and scope of equivalents falling within the protection scope are intended to be included in the invention.

[0137] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0138] Furthermore, it is clear that the word "including" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or systems described can also be implemented by a single unit or system through software or hardware. Terms such as "first," "second," etc., are used to indicate names and do not indicate any specific order.

[0139] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for monitoring and evaluating the linkage between soil pH and salinity during the sesame growth cycle, characterized in that, The method includes: Before sowing sesame seeds, rhizosphere soil from the planting area is collected as a background soil sample, and the background soil sample is filled into a measuring container with electrodes at both ends. A positive DC voltage is applied to one electrode of the measuring container to drive soluble salt ions in the background soil sample to migrate toward the opposite electrode. Based on the migration result, the background soil sample is divided into a salt-rich area and a desalination area. After the power is turned off, sub-samples are collected from the salt-rich area and the desalination area respectively. A dehumidification-rehumidification cycle is performed on each sub-sample, and the pH and salinity values ​​of each sub-sample are continuously measured during the dehumidification and rehumidification stages. Based on the pH value and the salinity value, pH hysteresis loop curves and salinity hysteresis loop curves are generated for the salt-rich area and the desalination area, respectively. The difference in ion migration hysteresis of the background soil sample is analyzed based on the pH hysteresis loop curves and the salinity hysteresis loop curves. When the sesame plants reached the preset first and second sampling days, the rhizosphere soil of the same sesame plant was collected as real-time soil samples, and the difference in real-time ion migration lag of each real-time soil sample was analyzed. The spatial distribution of the ion migration hysteresis difference and the real-time ion migration hysteresis difference is superimposed to obtain the superimposed interval. Based on the superimposed interval, the synergistic improvement status of soil pH and salinity during the growth cycle of sesbania is analyzed.

2. The method for monitoring and evaluating the linkage between soil pH and salinity during the growth cycle of sesbania as described in claim 1, characterized in that, The step of filling the background soil sample into a measuring container with electrodes at both ends includes: Under inert gas protection, the background soil sample is uniformly filled into a measuring container with electrodes at both ends, and during the filling process, the background soil sample is simultaneously compacted to a preset filling ratio of the measuring container volume. After filling is completed, an initial detection voltage is applied to the electrodes at both ends of the measuring container. Based on the initial detection voltage, the AC impedance amplitude and phase angle in the background soil sample are collected to generate an impedance spectrum curve. The relaxation time distribution of the impedance spectrum curve was analyzed to obtain the characteristic frequencies corresponding to the relaxation peaks of different ion migrations in the background soil sample. If the distribution of the characteristic frequency deviates from the distribution range in the preset soil sample effective frequency database, it is determined that the background soil sample has structural defects. For background soil samples with structural defects, adjust the compressive strength and mixing method of the background soil samples until the characteristic frequency of the adjusted background soil samples falls within the specified distribution range.

3. The method for monitoring and evaluating the linkage between soil pH and salinity during the growth cycle of sesbania as described in claim 1, characterized in that, The background soil samples, based on the migration results, are divided into saline-rich and desalinated zones, including: After applying a positive DC voltage to one end electrode of the measuring container, the voltage amplitude is gradually increased according to a set voltage increment rate, while the real-time current value passing through the measuring container is continuously collected. A voltage-current response curve is generated based on the voltage amplitude and the real-time current value. A second-order difference analysis is performed on the voltage-current response curve to obtain the abrupt change inflection point where the current value changes abruptly with the increase of voltage, and the trigger voltage value corresponding to each abrupt change inflection point is recorded. After the voltage has been applied for a preset duration or the current value has stabilized, the power supply is stopped, and the boundary position between the salt-rich zone and the desalination zone is recorded at the moment the power supply is stopped. The migration rate of each ion is calculated based on the distribution range of the trigger voltage value. Based on the migration rate and the boundary position, the region in the measurement container that is close to the positive electrode and has an ion migration rate lower than a preset first migration threshold is divided into a desalination region, and the region that is close to the opposite electrode and has an ion migration rate higher than a preset second migration threshold is divided into a salt-rich region.

4. The method for monitoring and evaluating the linkage between soil pH and salinity during the growth cycle of sesbania as described in claim 1, characterized in that, The process of performing a dehumidification-rehumidification cycle on each sub-sample includes: Each collected sub-sample was placed in an independent measurement chamber; The desiccation rate and rewetting rate for each sub-sample are determined based on the clay content of the background soil sample. During the dehydration stage, sub-samples in different measurement chambers are dehydrated according to the dehydration rate to obtain the sample moisture content; When the moisture content of the sample decreases to the preset wilting point moisture content, the sub-samples in different measurement chambers are rehumidified according to the rehumidification rate until the moisture content of the sample is restored to the initial moisture content before the dehumidification operation. An asymmetric rate cycle is generated based on the dehumidification rate and the rehumidification rate. During the asymmetric rate cycle, data pairs of pH and salinity values ​​in the two measurement chambers are continuously monitored as a function of water content.

5. The method for monitoring and evaluating the linkage between soil pH and salinity during the growth cycle of sesbania as described in claim 1, characterized in that, The process of generating pH hysteresis loop curves and salinity hysteresis loop curves for the salt-rich zone and the desalination zone based on the pH value and the salinity value, respectively, includes: Extract the first data pair of pH value changes with water content of the sub-sample of salt-rich area, connect the data points of the dehumidification stage in the order of decreasing water content to form the first dehumidification trajectory based on the first data pair, and connect the data points of the rehumidification stage in the order of increasing water content to form the first rehumidification trajectory. The first dehumidification trajectory and the first rehumidification trajectory are used to form a pH hysteresis loop curve for the salt-rich zone. Extract a second data pair of salinity values ​​as a function of water content from a subsample of the same saline-rich area, and generate a salinity hysteresis loop curve for the saline-rich area based on the second data pair. A third data pair showing the change in pH value with water content and a fourth data pair showing the change in salinity value with water content are extracted from the subsamples of the desalination area. A hysteresis loop curve for pH value of the desalination area is generated based on the third data pair, and a hysteresis loop curve for salinity value of the desalination area is generated based on the fourth data pair.

6. The method for monitoring and evaluating the linkage between soil pH and salinity during the growth cycle of sesbania as described in claim 1, characterized in that, The analysis of the ion migration hysteresis difference of the background soil sample based on the pH hysteresis loop curve and the salinity hysteresis loop curve includes: Ellipse fitting was performed on the pH hysteresis loop curve and the salinity hysteresis loop curve respectively, and the length of the major axis, the length of the minor axis, and the angle between the major axis and the water content coordinate axis of the fitted ellipse were calculated. The ratio of the major axis length to the minor axis length is determined as the eccentricity, which reflects the degree of anisotropy of the soil's pH or salinity response during alternating wet and dry periods. The included angle is determined as the response hysteresis angle, which reflects the directional shift characteristics of the soil's response to changes in water content. The first eccentricity difference between the pH hysteresis loop curve of the salt-rich zone and the pH hysteresis loop curve of the desalination zone, and the second eccentricity difference between the salinity hysteresis loop curve of the salt-rich zone and the salinity hysteresis loop curve of the desalination zone are calculated based on the eccentricity and the response hysteresis angle. The weighted sum of the first eccentricity difference and the second eccentricity difference is used as the ion migration hysteresis difference of the background soil sample.

7. The method for monitoring and evaluating the linkage between soil pH and salinity during the growth cycle of sesbania as described in claim 1, characterized in that, The analysis of the real-time ion migration hysteresis differences of each real-time soil sample includes: When the sesame plants have grown to the preset first sampling day, the first real-time rhizosphere soil sample is collected with the main stem of the sesame plant as the center and according to the preset sampling depth and sampling distance. The first real-time soil sample was subjected to a dehumidification-rewetting cycle to obtain the first real-time ion migration hysteresis difference of the first real-time soil sample. When the sesame plants have grown to the preset second sampling day, the second real-time rhizosphere soil is collected as the second real-time soil sample, and the second real-time soil sample is subjected to a dehumidification-rehydration cycle to obtain the second real-time ion migration hysteresis difference of the second real-time soil sample. Record the sets of trigger voltage values ​​for the first real-time soil sample and the second real-time soil sample during the application of a positive DC voltage, respectively. The set of trigger voltage values ​​is compared with the set of background trigger voltage values ​​of the background soil sample in terms of offset direction. If the offset direction is consistent and the offset amount changes monotonically, it is determined that the ion migration characteristics of the real-time soil sample have changed directionally.

8. The method for monitoring and evaluating soil pH and salinity in the growth cycle of sesbania as described in claim 1, characterized in that, The step of spatially superimposing the ion migration hysteresis difference with the real-time ion migration hysteresis difference to obtain the superimposed interval includes: Using the difference in ion migration hysteresis of the background soil sample as the benchmark value, a one-dimensional difference benchmark axis is constructed, wherein the origin of the difference benchmark axis corresponds to the background difference, the positive half axis represents the direction greater than the background difference, and the negative half axis represents the direction less than the background difference. The first real-time ion migration hysteresis difference in the real-time ion migration hysteresis difference is projected onto the difference reference axis to obtain the first projection point; the second real-time ion migration hysteresis difference in the real-time ion migration hysteresis difference is projected onto the same difference reference axis to obtain the second projection point. Using the first projection point and the second projection point as endpoints, a closed interval is constructed on the difference reference axis. The closed interval is used as the initial overlapping interval, wherein the left boundary of the closed interval is the smaller value between the first projection point and the second projection point, and the right boundary is the larger value between the first projection point and the second projection point. Data on soil texture type and groundwater depth in the sesame planting area are obtained. The initial overlapping interval is then bidirectionally corrected based on the soil texture type and groundwater depth data to obtain the overlapping interval.

9. The method for monitoring and evaluating the linkage between soil pH and salinity during the growth cycle of sesbania as described in claim 7, characterized in that, The analysis of the synergistic improvement of soil pH and salinity during the growth cycle of sesbania based on the superimposed intervals includes: Determine the signs of the left and right boundaries of the overlapping interval relative to the origin of the reference axis; If the signs of both the left and right boundaries are negative, it is determined to be an inhibited state; if the signs of both the left and right boundaries are positive, it is determined to be an activated state; if the signs of the left and right boundaries are opposite, it is determined to be a transitional state. When the state is determined to be active, the ratio of the length of the overlapping interval to the background difference is calculated. If the ratio is less than the preset compaction threshold, the evaluation result that the microbial synergistic improvement has entered a stable and mature state is output. If the ratio is greater than or equal to the preset compaction threshold, the evaluation result that the microbial synergistic improvement is still in a fluctuating development state is output. When the state is determined to be suppressed, if the difference in the second real-time ion migration hysteresis is greater than the difference in the first real-time ion migration hysteresis, the evaluation result of natural leaching-dominated decline is output; if the difference in the second real-time ion migration hysteresis is less than or equal to the difference in the first real-time ion migration hysteresis, the evaluation result of no effective improvement activity is output. When the state is determined to be transitional, the evaluation results of the output microbial synergistic improvement are in the initiation and activation phase.

10. A soil pH and salinity linkage monitoring and evaluation system for the sesbania growth cycle, characterized in that, The system is used to perform the soil pH and salinity linkage monitoring and evaluation method for the growth cycle of sesquiterpene as described in any one of claims 1-9, the system comprising: The background soil sample filling module is used to collect rhizosphere soil from the planting area as a background soil sample before sowing sesame seeds, and fill the background soil sample into a measuring container with electrodes at both ends. The background soil sample division module is used to apply a positive DC voltage to one end electrode of the measuring container, driving soluble salt ions in the background soil sample to migrate to the opposite electrode, and dividing the background soil sample into a salt-rich area and a desalination area based on the migration result. The pH and salinity analysis module is used to collect sub-samples from the salt-rich area and the desalination area after power is turned off, perform dehumidification-rehumidification cycle operation on each sub-sample, and continuously measure the pH and salinity of each sub-sample during the dehumidification and rehumidification stages. The ion migration hysteresis difference analysis module is used to generate pH hysteresis loop curves and salinity hysteresis loop curves for salt-rich and desalinated areas, respectively, based on the pH value and the salinity value, and to analyze the ion migration hysteresis difference of the background soil sample based on the pH hysteresis loop curves and the salinity hysteresis loop curves. The real-time ion migration lag difference analysis module is used to collect rhizosphere soil samples from the same sesame plant when it grows to the preset first and second sampling days, and to analyze the real-time ion migration lag difference of each real-time soil sample. The collaborative improvement state analysis module is used to spatially superimpose the ion migration hysteresis difference degree with the real-time ion migration hysteresis difference degree to obtain the superimposed interval, and analyze the collaborative improvement state of soil pH and salinity during the growth cycle of sesbania based on the superimposed interval.

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