In-situ monitoring method based on root mechanics-soil multi-parameter coupling

Abstract

The present application belongs to the field of farmland soil monitoring, and relates to an in-situ monitoring method based on root mechanics-soil multi-parameter coupling. In the crop planting area, a sensor unit is deployed stereoscopically to collect root zone strain signals, root zone pressure signals and soil multi-parameter data. A root growth rate and spatial expansion model is used to retrieve root growth dynamics. A root activity and stress diagnosis model is used to calculate root activity index and determine stress degree. A root-soil interaction intensity model is used to analyze root-soil contact conditions. A tuber swelling rate and initial swelling time model is used to monitor the tuber swelling process. A tuber stress diagnosis model is used to determine stress type and degree. A root-tuber collaborative matching degree model is used to quantify the collaborative relationship between root supply capacity and tuber absorption capacity. A soil environment comprehensive influence model is used to identify limiting factors. The present application realizes comprehensive perception and collaborative analysis of root, tuber and soil environment, and provides an effective technical means for precision agriculture and crop health management.

Description

Technical Field

[0001] This invention belongs to the field of farmland soil monitoring and relates to an in-situ monitoring method based on the coupling of root mechanics and soil multi-parameters. Background Technology

[0002] The rapid development of agricultural IoT and smart agriculture has provided new technological means for soil-plant system monitoring. Among them, sensor-based in-situ monitoring technology has become a research hotspot in the field of precision agriculture. By integrating sensor arrays that measure parameters such as soil temperature, humidity, conductivity, and pH, real-time perception and data collection of farmland soil environment can be achieved, providing important information support for crop growth management. However, existing monitoring systems still have significant shortcomings in terms of parameter coverage, sensor layout, and data fusion depth. They have not yet formed an effective correlation analysis between soil environmental parameters and crop root growth status, making it difficult to meet the needs of modern agricultural production for precise monitoring of the growth dynamics of crop underground parts.

[0003] Among these, the coupled analysis of root growth monitoring and soil environmental parameters is a core technological direction in this field. As the main organs for crop water and nutrient absorption, the root system's growth directly determines the development of the above-ground parts and yield formation. Soil, as the carrier of root survival, plays a crucial regulatory role in root physiological functions through parameters such as water potential, oxygen concentration, and heat flux. Achieving in-situ synchronous acquisition and coupled analysis of root mechanical signals and multiple soil parameters can not only reveal the real-time dynamics of root growth but also elucidate the mechanisms by which the soil environment influences root physiological functions, which is of great significance for guiding precision irrigation, fertilization, and cultivation management. However, existing technologies face multi-dimensional technical bottlenecks in the coupling of root monitoring and soil parameters, hindering the in-depth development and practical application of this direction.

[0004] The main shortcomings of existing technologies are concentrated in the following aspects: First, the coverage of soil parameter monitoring is limited. Most integrated systems only focus on conventional parameters such as temperature, humidity, electrical conductivity, and pH, lacking key indicators closely related to root physiological functions, such as soil water potential, oxygen concentration, and heat flux. These systems cannot comprehensively reflect the soil environmental status, let alone achieve deep coupling analysis with root parameters. Second, root monitoring methods have significant limitations. Existing root monitoring technologies either rely on non-in-situ, destructive observation methods such as optical scanning, which can only obtain root morphological phenotypic information and cannot reflect the root physiological activity status, or only collect single mechanical parameters, lacking synergistic analysis with soil environmental parameters. Furthermore, existing technical solutions are mostly designed for farmland soil scenarios and have not been optimized for crop root growth characteristics and the specific biological needs of tuber crops (such as potatoes), making accurate monitoring difficult. The existing systems suffer from several limitations. First, they fail to fully integrate root mechanics and tuber enlargement dynamics. Second, they lack data synergy and anti-interference capabilities. Current systems primarily collect soil and root parameters independently, failing to establish a coupled analysis model of "root mechanics changes - soil environmental parameters," thus hindering the understanding of their interaction. Furthermore, cross-interference exists between multiple sensors, and existing technologies do not adequately consider the impact of environmental noise on measurement accuracy, limiting the reliability and accuracy of monitoring data. Third, system adaptability is limited. Existing sensor packaging solutions either prioritize ease of installation or adapt to farmland soil monitoring needs, without specifically designing for the characteristics of the rhizosphere environment in agricultural soils. Moreover, existing monitoring systems are mostly general-purpose solutions, lacking dedicated adaptation mechanisms for specific crops, and failing to effectively link with integrated water and fertilizer management systems, making it difficult to transform monitoring data into precise management decisions. In summary, existing technologies in the field of in-situ coupled monitoring of root mechanics and soil multi-parameters suffer from technical bottlenecks such as incomplete parameter coverage, limited monitoring methods, poor data synergy, and insufficient adaptability, which urgently require technological innovation to address. Summary of the Invention

[0005] The main objective of this invention is to provide solutions to the problems existing in the prior art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: An in-situ monitoring method based on root mechanics-soil multi-parameter coupling includes the following steps: Step 1: In-situ sensor array three-dimensional deployment. Multiple sets of sensor units are deployed three-dimensionally in the crop planting area to perform in-situ synchronous acquisition of soil environmental parameters and root mechanical signals. Step 2: Collect and preprocess root mechanical signals. Collect strain values ​​inside the root zone, pressure values ​​outside the root zone, and environmental noise values ​​in real time. Based on the environmental noise values, perform noise reduction processing on the collected strain and pressure signals to obtain corrected root zone strain and pressure signals. Step 3: Synchronously collect multiple soil parameters and construct a soil environmental parameter dataset by synchronously collecting data from the multiple sets of sensor units; Step 4: Root growth rate and spatial expansion inversion. Calculate the time rate of change of strain signal and the time rate of change of pressure signal. Use the root growth rate and spatial expansion model to calculate the instantaneous root growth rate. Invert the root growth direction and spatial expansion intensity based on the instantaneous root growth rate values ​​at different locations. Step 5: Perform root vitality and stress diagnosis and root-soil interaction strength analysis. Use the root vitality and stress diagnosis model to calculate the root vitality index, determine the degree of drought stress and salt stress on the roots, and use the root-soil interaction strength model to calculate the root-soil interaction strength index to quantitatively analyze the degree of root-soil contact. Step 6: For potato planting areas, the tuber expansion rate and initial expansion time model are used to calculate the instantaneous tuber expansion rate. The tuber formation start time is determined based on the time point when the instantaneous tuber expansion rate first exceeds the preset expansion rate threshold. Step 7: Perform tuber stress diagnosis and yield prediction and root-tuber synergy matching degree analysis. Calculate the tuber stress index to determine the type and degree of stress on the tuber and predict the tuber maturity period. Use the root-tuber synergy matching degree model to calculate the root-tuber synergy matching degree index and obtain the synergistic relationship between root supply capacity and tuber absorption capacity. Step 8: Comprehensive assessment of soil environmental impact factors. The comprehensive soil environmental impact model is used to calculate the comprehensive soil environmental impact factors and identify the limiting factors that have the greatest impact on the root-tuber system.

[0007] Furthermore, step 1 also includes: The strain sensor, pressure sensor, soil water potential sensor, soil oxygen concentration sensor, soil heat flux sensor, soil temperature and humidity sensor, soil electrical conductivity sensor and soil pH sensor are deployed in a three-dimensional layout with three layers in the vertical direction and eight directions in the horizontal direction, forming a total of 24 sensor units. The specific division of the three vertical layers is as follows: The first layer is the shallow root zone, with a depth ranging from 0 to 15 centimeters, where the crop's absorbing roots and primary tubers are distributed; The second layer is the middle root zone, with a depth of 15 to 30 centimeters, where active roots are distributed; The third layer is the deep root zone, with a depth of 30 to 60 centimeters, where the supporting root system is distributed; Each floor is equipped with sensor groups in eight horizontal directions: east, southeast, south, southwest, west, northwest, north, and northeast.

[0008] Furthermore, the method also includes: The strain sensor is a high-precision resistance strain gauge sensor with a range that covers the preset strain range and a sampling frequency that is not lower than the preset sampling frequency. The pressure sensor uses a miniature earth pressure cell, and its range covers a preset pressure range with a response time less than a preset response time threshold. The soil water potential sensor is a gypsum resistance block type water potential sensor, and the measurement range is a preset water potential range. The soil oxygen concentration sensor is a polarographic oxygen electrode sensor, and the measurement range is a preset oxygen concentration range. The soil heat flux sensor is a heat flux plate sensor, and the measurement range is a preset heat flux range. The soil conductivity sensor adopts a four-electrode design and measures within a preset conductivity range. The soil pH sensor adopts a glass electrode design and measures within a preset pH range. The sensor array is centrally managed by a main control unit, which is equipped with a multi-channel synchronous acquisition module.

[0009] Furthermore, step 3 also includes A soil environmental parameter dataset is constructed by synchronously collecting soil water potential, soil oxygen concentration, soil heat flux, soil temperature, soil moisture, soil electrical conductivity, and soil pH value using multiple sets of sensor units.

[0010] Furthermore, step 4 also includes: The time-varying rate of change of the strain signal was calculated using a sliding window difference algorithm, and the root growth rate and spatial expansion model were derived using the formula... ; : Instantaneous root growth rate, inverting the "real-time root growth rate", with positive values ​​indicating growth and negative values ​​indicating stagnation / senescence; The time-varying rate of change of the strain signal in the root region is acquired in real time by the system strain sensor and calculated by the main control unit, where ε is the strain value inside the root region. The time rate of change of the root zone pressure signal is acquired in real time by the system pressure sensor and calculated by the main control unit. Real-time soil temperature is collected by the system's temperature and humidity sensors; : The optimal temperature for crop root growth; Real-time soil oxygen concentration, collected by the system's soil oxygen / respiration sensor; : Soil saturated oxygen concentration; Weighting coefficient.

[0011] Furthermore, step 5 also includes: The root vitality and stress diagnostic model adopts ; The root vitality index ranges from 0 to 10. The higher the value, the stronger the root vitality and the healthier the physiological state. It is a core inversion indicator. The strain inside the root zone and the pressure outside the root zone are collected in real time by the system's strain and pressure sensors, reflecting the intensity of root physiological activity. : Environmental noise value in non-planting areas, collected by sensors in non-planting areas of the system, used to filter natural environmental interference and improve calculation accuracy; Soil water potential is collected by the system's soil water potential sensors and is primarily used to invert the degree of drought stress. Soil electrical conductivity, collected by the system's electrical conductivity sensor, is primarily used to invert the degree of salt stress; Weight calibration coefficient; Soil water potential correction function quantifies the degree of drought stress. The lower the water potential, the larger the function value, and the stronger the inhibitory effect on root activity. Soil electrical conductivity correction function quantifies the degree of salt stress. The higher the electrical conductivity, the larger the function value, and the stronger the inhibitory effect on root vitality.

[0012] Furthermore, step 5 also includes: The root-soil interaction strength model uses the formula... ; Root-soil interaction strength, ranging from 0 to 5. The higher the value, the closer the root-soil contact and the stronger the interaction. Root zone strain and pressure; Interaction coefficient; Suitable water potential for root growth; : Maximum EC value tolerable by crop roots.

[0013] Furthermore, step 6 also includes: The tuber enlargement rate and initial enlargement time model uses the formula... ; : Instantaneous tuber enlargement rate, inversely reflecting the tuber growth rate; Strain and pressure in the tuber region were collected by shallow sensors in the root zone. Optimal temperature for potato tuber enlargement; Tuber-specific calibration coefficient; Furthermore, step 7 also includes: Based on the instantaneous tuber enlargement rate, the tuber sink strength and tuber dry matter accumulation amount are calculated by combining the tuber sink strength and dry matter accumulation model. The tuber stress index is calculated by the tuber stress diagnosis model to determine the type and degree of stress on the tuber. The tuber maturity period is predicted based on the tuber stress index and tuber sink strength. ; : Tuber storage strength, with a value of 0-8. The higher the value, the stronger the tuber's ability to absorb photosynthetic products. Soil heat flux, collected by the system's soil heat flux sensor, reflects the soil's energy supply; The optimal EC value for potato tuber growth; : Accumulation of dry matter in tubers; : Initial expansion time and current time; : Tuber-specific coefficient.

[0014] ; Tuber stress index, ranging from 0 to 1, with higher values ​​indicating more severe stress; The maximum tuber enlargement rate was calibrated through experiments. Maximum storage strength of tubers.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. Comprehensive parameter coverage and deep coupling capability Breaking through the limitations of traditional parameters: This invention integrates key parameters closely related to root physiological functions, such as soil water potential, soil oxygen concentration, and soil heat flux, and combines them with root mechanical signals collected by strain and pressure sensors to construct a deep-coupled monitoring system for root mechanics and multiple soil parameters, solving the problem of incomplete parameter coverage in existing technologies; Three-dimensional perception capability: By deploying multiple sensor units in a three-dimensional layout with three layers vertically and eight directions horizontally, it achieves comprehensive perception of root growth dynamics and soil environmental parameters in three-dimensional soil space, providing a data foundation for the inversion of root growth direction and spatial expansion intensity.

[0016] 2. Precise root system monitoring and physiological state inversion capability In-situ non-destructive monitoring: This invention uses strain sensors and pressure sensors for in-situ monitoring, which can acquire mechanical signals generated by root growth in real time without damaging the soil structure, solving the problems of non-in-situ and destructiveness of existing optical scanning methods; Multi-dimensional physiological state inversion: Through the root growth rate and spatial expansion model, the root vitality and stress diagnosis model, and the root-soil interaction strength model, the quantitative inversion of real-time root growth rate, root vitality index, and root-soil contact status is realized. It can accurately determine the degree of drought stress and salt stress on the root system, as well as the root aging and necrosis state, making up for the shortcomings of existing single mechanical parameter monitoring.

[0017] 3. Solutions to tuber biology problems Precise monitoring of tuber enlargement dynamics: This invention addresses biological issues in potato tubers by constructing models for tuber enlargement rate and initial enlargement time, tuber stress diagnosis, and tuber sink strength and dry matter accumulation. This enables precise determination of the initial enlargement time, quantitative calculation of the daily tuber enlargement rate, and prediction of tuber dry matter accumulation intensity, solving the technical challenge of in-situ monitoring of tuber growth. Precise identification of stress types: The tuber stress diagnosis model can distinguish between drought stress, hypoxia stress, temperature stress, and salt stress, and determines whether tuber enlargement has stagnated based on the stress index, providing a basis for timely management measures.

[0018] 4. Root-tuber synergistic analysis capability Source-sink relationship disclosure: This invention quantifies the matching degree between root supply capacity and tuber absorption capacity through a root-tuber synergistic matching degree model. It can determine whether the root system meets the tuber growth requirements, whether the tuber sink strength is sufficient, and whether excessive vegetative growth occurs, thus realizing a quantitative analysis of the synergistic relationship of the root-tuber system. Precise identification of limiting factors: By comprehensively assessing the comprehensive impact of environmental factors such as soil water potential, oxygen, heat flux, and nutrients on the root-tuber system through a soil environment comprehensive impact model, it can identify the primary limiting factor for yield, providing a scientific basis for precise water and fertilizer management.

[0019] 5. Highly reliable data quality assurance Environmental noise filtering: This invention effectively reduces the impact of natural environmental noise on measurement accuracy by setting up sensors in non-planting areas to synchronously collect environmental noise values ​​and denoising the root mechanical signals based on these values, thus solving the problem that existing technologies do not consider environmental noise interference; Multi-sensor collaborative correction: Through collaborative analysis of multiple soil parameters and root mechanical signals, combined with soil water potential correction functions and soil electrical conductivity correction functions, the monitoring results are corrected, improving the reliability and accuracy of the monitoring data. Attached Figure Description

[0020] Figure 1 The flowchart illustrates an in-situ monitoring method based on root mechanics-soil multi-parameter coupling, as claimed in this embodiment of the invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0022] The terms "first," "second," and "third" used in this invention are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this invention are only used to explain the relative positional relationships and movements between components in a specific orientation (as shown in the accompanying drawings). If the specific orientation changes, the directional indications also change accordingly. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0023] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0024] The in-situ monitoring method based on root mechanics-soil multi-parameter coupling provided by this invention is based on the acquisition of mechanical signals generated by root growth through strain and pressure sensors. This data is then combined with soil environmental parameters such as soil water potential, soil oxygen concentration, soil heat flux, soil temperature, soil moisture, soil electrical conductivity, and soil pH to construct a deep coupling monitoring system between root mechanics and soil multi-parameters. This method achieves quantitative inversion of root biology, potato tuber biology, and root-tuber synergistic biology problems through three core modules. All model parameters can be directly calculated from the system's acquired data without requiring additional hardware. The following detailed description of the method is provided with reference to specific embodiments.

[0025] According to the first embodiment of the present invention, referring to Figure 1 This invention claims protection for an in-situ monitoring method based on root mechanics-soil multi-parameter coupling, comprising the following steps: Step 1: In-situ sensor array three-dimensional deployment. Multiple sets of sensor units are deployed three-dimensionally in the crop planting area to perform in-situ synchronous acquisition of soil environmental parameters and root mechanical signals. Step 2: Collect and preprocess root mechanical signals. Collect strain values ​​inside the root zone, pressure values ​​outside the root zone, and environmental noise values ​​in real time. Based on the environmental noise values, denoise the collected strain and pressure signals to obtain the corrected root zone strain and pressure signals. Step 3: Synchronously collect multiple soil parameters and construct a soil environmental parameter dataset by synchronously collecting data from multiple sets of sensor units; Step 4: Root growth rate and spatial expansion inversion. Calculate the time rate of change of strain signal and the time rate of change of pressure signal. Use the root growth rate and spatial expansion model to calculate the instantaneous root growth rate. Invert the root growth direction and spatial expansion intensity based on the instantaneous root growth rate values ​​at different locations. Step 5: Perform root vitality and stress diagnosis and root-soil interaction strength analysis. Use the root vitality and stress diagnosis model to calculate the root vitality index, determine the degree of drought stress and salt stress on the roots, and use the root-soil interaction strength model to calculate the root-soil interaction strength index to quantitatively analyze the degree of root-soil contact. Step 6: For potato planting areas, the tuber expansion rate and initial expansion time model are used to calculate the instantaneous tuber expansion rate. The tuber formation start time is determined based on the time point when the instantaneous tuber expansion rate first exceeds the preset expansion rate threshold. Step 7: Perform tuber stress diagnosis and yield prediction and root-tuber synergy matching degree analysis. Calculate the tuber stress index to determine the type and degree of stress on the tuber and predict the tuber maturity period. Use the root-tuber synergy matching degree model to calculate the root-tuber synergy matching degree index and obtain the synergistic relationship between root supply capacity and tuber absorption capacity. Step 8: Comprehensive assessment of soil environmental impact factors. The comprehensive soil environmental impact model is used to calculate the comprehensive soil environmental impact factors and identify the limiting factors that have the greatest impact on the root-tuber system.

[0026] Furthermore, step 1 also includes: The strain sensor, pressure sensor, soil water potential sensor, soil oxygen concentration sensor, soil heat flux sensor, soil temperature and humidity sensor, soil electrical conductivity sensor and soil pH sensor are deployed in a three-dimensional layout with three layers in the vertical direction and eight directions in the horizontal direction, forming a total of 24 sensor units. The specific division of the three vertical layers is as follows: The first layer is the shallow root zone, with a depth ranging from 0 to 15 centimeters, where the crop's absorbing roots and primary tubers are distributed; The second layer is the middle root zone, with a depth of 15 to 30 centimeters, where active roots are distributed; The third layer is the deep root zone, with a depth of 30 to 60 centimeters, where the supporting root system is distributed; Each floor is equipped with sensor groups in eight horizontal directions: east, southeast, south, southwest, west, northwest, north, and northeast.

[0027] Furthermore, the method also includes: The strain sensor is a high-precision resistance strain gauge sensor with a range that covers the preset strain range and a sampling frequency that is not lower than the preset sampling frequency. The pressure sensor uses a miniature earth pressure cell, and its range covers a preset pressure range with a response time less than a preset response time threshold. The soil water potential sensor is a gypsum resistance block type water potential sensor, and the measurement range is a preset water potential range. The soil oxygen concentration sensor is a polarographic oxygen electrode sensor, and the measurement range is a preset oxygen concentration range. The soil heat flux sensor is a heat flux plate sensor, and the measurement range is a preset heat flux range. The soil conductivity sensor adopts a four-electrode design and measures within a preset conductivity range. The soil pH sensor adopts a glass electrode design and measures within a preset pH range. The sensor array is centrally managed by a main control unit, which is equipped with a multi-channel synchronous acquisition module.

[0028] Furthermore, step 3 also includes A soil environmental parameter dataset is constructed by synchronously collecting soil water potential, soil oxygen concentration, soil heat flux, soil temperature, soil moisture, soil electrical conductivity, and soil pH value using multiple sets of sensor units.

[0029] Furthermore, step 4 also includes: The time-varying rate of change of the strain signal was calculated using a sliding window difference algorithm, and the root growth rate and spatial expansion model were derived using the formula... ; : Instantaneous root growth rate, inverting the "real-time root growth rate", with positive values ​​indicating growth and negative values ​​indicating stagnation / senescence; The time-varying rate of change of the strain signal in the root region is acquired in real time by the system strain sensor and calculated by the main control unit, where ε is the strain value inside the root region. The time rate of change of the root zone pressure signal is acquired in real time by the system pressure sensor and calculated by the main control unit. Real-time soil temperature is collected by the system's temperature and humidity sensors; : The optimal temperature for crop root growth; Real-time soil oxygen concentration, collected by the system's soil oxygen / respiration sensor; : Soil saturated oxygen concentration; Weighting coefficient.

[0030] Furthermore, step 5 also includes: The root vitality and stress diagnostic model adopts ; The root vitality index ranges from 0 to 10. The higher the value, the stronger the root vitality and the healthier the physiological state. It is a core inversion indicator. The strain inside the root zone and the pressure outside the root zone are collected in real time by the system's strain and pressure sensors, reflecting the intensity of root physiological activity. : Environmental noise value in non-planting areas, collected by sensors in non-planting areas of the system, used to filter natural environmental interference and improve calculation accuracy; Soil water potential is collected by the system's soil water potential sensors and is primarily used to invert the degree of drought stress. Soil electrical conductivity, collected by the system's electrical conductivity sensor, is primarily used to invert the degree of salt stress; Weight calibration coefficient; Soil water potential correction function quantifies the degree of drought stress. The lower the water potential, the larger the function value, and the stronger the inhibitory effect on root activity. Soil electrical conductivity correction function quantifies the degree of salt stress. The higher the electrical conductivity, the larger the function value, and the stronger the inhibitory effect on root vitality.

[0031] Furthermore, step 5 also includes: The root-soil interaction strength model uses the formula... ; Root-soil interaction strength, ranging from 0 to 5. The higher the value, the closer the root-soil contact and the stronger the interaction. Root zone strain and pressure; Interaction coefficient; Suitable water potential for root growth; : Maximum EC value tolerable by crop roots.

[0032] Furthermore, step 6 also includes: The tuber enlargement rate and initial enlargement time model uses the formula... ; : Instantaneous tuber enlargement rate, inversely reflecting the tuber growth rate; Strain and pressure in the tuber region were collected by shallow sensors in the root zone. Optimal temperature for potato tuber enlargement; Tuber-specific calibration coefficient.

[0033] Furthermore, step 7 also includes: Based on the instantaneous tuber enlargement rate, the tuber sink strength and tuber dry matter accumulation amount are calculated by combining the tuber sink strength and dry matter accumulation model. The tuber stress index is calculated by the tuber stress diagnosis model to determine the type and degree of stress on the tuber. The tuber maturity period is predicted based on the tuber stress index and tuber sink strength. ; : Tuber storage strength, with a value of 0-8. The higher the value, the stronger the tuber's ability to absorb photosynthetic products. Soil heat flux, collected by the system's soil heat flux sensor, reflects the soil's energy supply; The optimal EC value for potato tuber growth; : Accumulation of dry matter in tubers; : Initial expansion time and current time; : Tuber-specific coefficient.

[0034] Furthermore, step 7 also includes: The tuber stress diagnostic model uses the formula ; Tuber stress index, ranging from 0 to 1, with higher values ​​indicating more severe stress; The maximum tuber enlargement rate was calibrated through experiments. Maximum storage strength of tubers.

[0035] In this embodiment, constructing a three-dimensional sensor monitoring network in the crop planting area is the foundation for comprehensive perception of root growth dynamics and soil environmental parameters. In this embodiment, strain sensors, pressure sensors, soil water potential sensors, soil oxygen concentration sensors, soil heat flux sensors, soil temperature and humidity sensors, soil electrical conductivity sensors, and soil pH sensors are deployed in the potato planting area in a three-dimensional layout with three layers vertically and eight directions horizontally, forming a total of 24 sensor units, realizing in-situ synchronous acquisition of root growth dynamics and soil environmental parameters in the three-dimensional space of the soil.

[0036] The vertical division into three layers is as follows: The first layer is the shallow root zone, with a depth of 0 to 15 cm. This layer mainly contains potato absorbing roots and primary tubers, and is the core area for monitoring tuber enlargement. The second layer is the middle root zone, with a depth of 15 to 30 cm. This layer contains a large number of active roots and is the main area for monitoring root growth. The third layer is the deep root zone, with a depth of 30 to 60 cm. This layer contains a small number of supporting roots and is used to monitor the dynamics of deep root expansion. Sensor groups are deployed in eight horizontal directions in each layer: east, southeast, south, southwest, west, northwest, north, and northeast, forming a complete 360-degree horizontal coverage.

[0037] Each sensor unit includes a strain sensor, a pressure sensor, a soil water potential sensor, a soil oxygen concentration sensor, a soil heat flux sensor, a soil temperature and humidity sensor, a soil conductivity sensor, and a soil pH sensor. The strain sensor employs a high-precision resistance strain gauge, with a measurement range covering 0 to 2000 με, a sensitivity better than 0.1 με, and a sampling frequency of no less than 10 Hz. The sensor is encapsulated in a corrosion-resistant stainless steel shell with a diameter of 15 mm and a length of 100 mm, suitable for long-term installation in the rhizosphere environment of agricultural soils. The pressure sensor uses a miniature soil pressure cell, with a measurement range of 0 to 500 kPa, an accuracy of 0.1% of full scale, and a response time of less than 10 milliseconds, accurately capturing the compressive effect of roots on the surrounding soil.

[0038] The soil water potential sensor employs a gypsum resistance block type, with a measurement range of -10 to -300 kPa and an accuracy of ±1 kPa, reflecting the availability of soil moisture to plants. The soil oxygen concentration sensor uses a polarographic oxygen electrode sensor, with a measurement range of 0 to 21% and a response time of less than 30 seconds, enabling real-time monitoring of oxygen content in soil pores. The soil heat flux sensor uses a heat flux plate type sensor, with a measurement range of -500 to 500 W / m² and a sensitivity better than 5 W / (m²·mV), used to monitor heat exchange in the soil. The soil temperature and humidity sensor adopts a composite design, capable of simultaneously measuring soil temperature and volumetric water content; the temperature measurement range is -20 to 60 degrees Celsius with an accuracy of ±0.5 degrees Celsius, and the humidity measurement range is 0 to 100% with an accuracy of ±2%. The soil conductivity sensor uses a four-electrode design, with a measurement range of 0 to 10 mS / cm and an accuracy of ±2%, used to monitor soil salinity. The soil pH sensor uses a glass electrode design, measures pH 2 to pH 12 with an accuracy of ±0.1, and is used to monitor soil acidity and alkalinity.

[0039] The sensor array is centrally managed by a main control unit, which is equipped with a multi-channel synchronous acquisition module. This module supports simultaneous data acquisition from 24 sensor units, with an acquisition cycle adjustable from 1 minute to 24 hours. Data storage capacity is no less than 32GB, and it supports LoRa or 4G wireless data transmission protocols. The main control unit is responsible for coordinating the operation of functional modules such as sensor power supply control, data acquisition scheduling, signal preprocessing, and store-and-forward functionality.

[0040] Given that potato tubers are primarily distributed in shallow soil, the sensor density in the shallow root zone is appropriately increased, with three sensor units deployed for tuber area monitoring to ensure accurate acquisition of tuber enlargement signals. At different growth stages of the potato plant, the system supports dynamic adjustment of sampling frequency and data upload cycle based on monitoring needs. For example, during the critical period of tuber enlargement, the sampling frequency can be increased to a higher level to ensure the timeliness and accuracy of the monitoring data.

[0041] The acquisition and preprocessing of root mechanical signals are fundamental steps in subsequent model calculations. Strain values ​​inside the root zone are acquired in real time using strain sensors, and pressure values ​​outside the root zone are acquired in real time using pressure sensors. Environmental noise values ​​are also acquired synchronously using sensors placed in non-planting areas. The acquired strain and pressure signals are then denoised based on the environmental noise values ​​to obtain corrected root zone strain and pressure signals.

[0042] The strain values ​​inside the root zone, collected in real time by strain sensors, reflect the minute deformations produced by the root system during growth. When the root system elongates or thickens, it exerts a compressive force on the surrounding soil, causing changes in the arrangement of soil particles and generating strain signals. The trend of strain value changes is directly related to the activity level of root growth: during the rapid growth stage, the strain value shows an increasing trend; during the stagnant or senescent stage of root growth, the strain value tends to stabilize or slightly decrease. The pressure values ​​outside the root zone, collected in real time by pressure sensors, reflect the intensity of the compressive force exerted by the root system on the surrounding soil, and the magnitude of the pressure value is positively correlated with root activity.

[0043] Environmental noise levels were collected by installing strain and pressure sensors of the same specifications in non-planted areas. Since the sensors in non-planted areas are unaffected by root growth, the strain and pressure signals they collect originate entirely from natural environmental factors, including thermal expansion and contraction due to soil temperature changes, changes in soil self-weight pressure, groundwater level fluctuations, and changes in surface load. By subtracting the environmental noise levels from those in non-planted areas from the monitoring signals from planted areas, the interference of environmental factors on root mechanical signals can be effectively eliminated, significantly improving the signal-to-noise ratio and calculation accuracy of the monitoring data.

[0044] After noise filtering and time-varying rate calculation, the system outputs the corrected root zone strain signal, root zone pressure signal, strain signal time-varying rate of change dε / dt, and pressure signal time-varying rate of change dP / dt, which serve as input parameters for subsequent model calculations. These parameters have a time resolution of 1 hour, and the data format includes timestamps, strain values, pressure values, and their rates of change, providing a complete data foundation for root growth dynamic analysis.

[0045] Soil environmental parameters are important bases for assessing root growth conditions and tuber enlargement environment. A soil environmental parameter dataset was constructed by simultaneously collecting soil water potential, soil oxygen concentration, soil heat flux, soil temperature and humidity, soil electrical conductivity, and soil pH values ​​using soil water potential sensors, soil oxygen concentration, soil heat flux, soil temperature, soil humidity, soil electrical conductivity, and soil pH values.

[0046] Soil water potential values ​​collected by soil water potential sensors reflect the availability of soil moisture for plant roots. When the soil water potential is close to 0 kPa, the soil is saturated; when the soil water potential is between -10 and -33 kPa, the soil water content is within the field capacity range; when the soil water potential is below -1500 kPa, the soil water content is close to the permanent wilting point. Roots can only absorb water from soil with a water potential higher than their own; therefore, soil water potential is a core indicator for assessing the degree of drought stress on roots.

[0047] Soil oxygen concentration sensors, which collect data on soil oxygen concentration, reflect the oxygen supply status for root respiration and soil microbial activity. Potato roots require a soil oxygen concentration of at least 10% for normal growth; when the oxygen concentration falls below 5%, root respiration is severely inhibited, leading to hypoxia stress. Soil heat flux sensors, which collect data on soil heat flux, reflect the amount of heat passing through a unit area of ​​soil per unit time. Positive values ​​indicate heat transfer from the atmosphere to the soil, while negative values ​​indicate heat loss from the soil to the atmosphere. Soil heat flux is closely related to root metabolic activity and tuber enlargement.

[0048] The soil temperature and humidity sensor simultaneously measures soil temperature and soil volumetric water content. Soil temperature directly affects root physiological activity and enzymatic reaction rates, while soil humidity reflects the actual water content of the soil. The soil conductivity sensor collects soil conductivity values ​​that reflect the concentration of ions in the soil solution. Excessive conductivity indicates soil salt accumulation, which can cause salt stress to the roots. The soil pH sensor collects soil pH values ​​that reflect soil acidity or alkalinity; the suitable soil pH range for potato growth is 5.0 to 6.5.

[0049] The acquisition cycle for all soil environmental parameters is synchronized with root mechanical signals to ensure data temporal consistency. After acquisition, the main control unit performs calibration transformation and outlier removal on the raw data. The calibration transformation formula is determined based on the factory calibration parameters of each sensor and the field calibration results. Outlier removal adopts the 3σ criterion or the interquartile range method. The processed soil environmental parameter dataset is stored in time series format, including the time values ​​of each parameter and the corresponding data quality indicators.

[0050] Root growth rate is a direct indicator of root growth status, while spatial expansion information reflects the dynamic distribution of roots in the three-dimensional soil space. Based on the corrected root zone strain and pressure signals, the time-varying rates of change of the strain and pressure signals were calculated. Combined with soil temperature and soil oxygen concentration, the instantaneous root growth rate was calculated using a root growth rate and spatial expansion model. Furthermore, the root growth direction and spatial expansion intensity were inverted based on the instantaneous root growth rate values ​​at different locations.

[0051] The physiological basis of this model is that root elongation and thickening generate strain and pressure signals. When the root system is in an active growth state, both dε / dt and dP / dt are positive, indicating that strain and pressure increase over time; the root growth rate is positively correlated with these two signals. Meanwhile, temperatures deviating from the optimal temperature range inhibit root growth, and this temperature-inhibiting effect is subtracted by the |kT-T_opt| term; insufficient soil oxygen concentration reduces root respiration and metabolic activity.

[0052] The inverse relationship between root growth direction and spatial expansion intensity depends on the three-dimensional layout of the system. This is achieved by comparing data from different locations and at different times. Values ​​can be used to determine the spatial distribution characteristics and growth dynamics of the root system. When a certain direction... When the value continuously increases over time, it indicates that the root system is expanding in that direction; when the shallow layer... Value greater than depth When the value is [value], it indicates that the root system is mainly distributed in the shallow soil layer; when [value] in all directions... Significant differences in values ​​indicate directional heterogeneity in root growth. The system calculates values ​​at 24 locations in each sampling period. Values ​​were used to construct a three-dimensional dynamic distribution map of root growth.

[0053] Identification of root growth arrest and acceleration nodes through monitoring The sign of the value is changed. When When the value changes from positive to negative, it indicates that the root system has entered a stagnant or senescent stage; when When the value changes from negative to positive, it indicates that the root system has entered a new period of active growth. The system automatically records this. By analyzing the time points of change in the sign of the value, combined with changes in soil environmental parameters, the reasons for the transformation of the growth state can be determined.

[0054] Root vigor is a core indicator characterizing the physiological function of roots, while stress diagnosis can identify limiting factors affecting root growth. Based on corrected root zone strain and pressure signals, combined with soil water potential and soil electrical conductivity correction functions, a root vigor index is calculated using a root vigor and stress diagnosis model. The degree of drought and salt stress on the roots is then determined based on the root vigor index.

[0055] The soil water potential correction function f(ψ) is used to quantify the degree of inhibition of root activity by drought stress. When the soil water potential is below -100 kPa, the value of f(ψ) increases sharply, indicating that severe drought strongly inhibits root activity; when the soil water potential is between -50 and -100 kPa, the value of f(ψ) increases slowly, indicating that mild drought has a certain inhibitory effect; when the soil water potential is above -50 kPa, the value of f(ψ) is close to 0, indicating no water stress.

[0056] The soil electrical conductivity correction function g(EC) is used to quantify the degree of inhibition of root activity by salt stress. When the soil electrical conductivity exceeds 4 mS / cm, the g(EC) value increases sharply, indicating that high salt content damages the root cell membrane structure; when the soil electrical conductivity is between 2 and 4 mS / cm, the g(EC) value increases slowly, indicating that mild salt stress has a certain inhibitory effect; when the soil electrical conductivity is below 2 mS / cm, the g(EC) value is close to 0, indicating no salt stress. This function can be calculated using a similar piecewise exponential form.

[0057] The criteria for judging the root vitality index are: When the value is less than 3, the root vitality is extremely low, and root necrosis or severe aging may occur, requiring immediate management measures. From 3 to 6 o'clock, the root system is under moderate stress, and its physiological activities are inhibited, so water and fertilizer management needs to be strengthened. When the value is greater than or equal to 6, the root system is in a healthy state, with vigorous physiological activity and strong nutrient absorption capacity.

[0058] The ability of roots to absorb nutrients is assessed indirectly through the root vitality index. It is positively correlated with nutrient absorption efficiency, when When the temperature is high, the root system has a stronger ability to absorb nutrients such as nitrogen, phosphorus, and potassium. When the temperature is low, the root system's ability to absorb nutrients is limited, requiring appropriate fertilizer supplementation.

[0059] Root-soil interaction strength is an important indicator characterizing the contact between roots and soil and the degree to which soil compaction restricts root growth. Based on the ratio of the corrected root zone strain signal to the root zone pressure signal, combined with soil water potential and soil electrical conductivity, a root-soil interaction strength model is used to calculate the root-soil interaction strength index and quantitatively analyze the degree of root-soil contact compaction.

[0060] The physiological basis of this model is that the closer the root-soil contact, the more stable the ratio of strain to pressure generated by root growth; when the soil water potential is suitable and the soil electrical conductivity is moderate, the cohesion between roots and soil is strong, the root system can effectively absorb soil water and nutrients, and the root-soil interaction strength is high; when the soil is dry, the soil salinity is too high, or the soil structure is damaged, the root-soil contact is loose, the root growth is restricted, and the root-soil interaction strength is low.

[0061] The criteria for judging the strength of root-soil interaction are: When the value is less than 2, the root-soil contact is loose, and there may be root gaps or soil cracks. The contact area between the root system and the soil is reduced, and the efficiency of water and nutrient absorption is reduced. When the temperature is between 2 and 4, the root-soil contact is normal, and the root system can effectively absorb water and nutrients. When the value is greater than or equal to 4, the soil is too compacted, which mechanically restricts root growth, and it is necessary to loosen the soil or improve the soil structure.

[0062] Dynamic monitoring of potato tuber enlargement is one of the core application scenarios of this invention. The tuber enlargement process generates strain signals significantly stronger than those of ordinary root systems and continuous, stable pressure signals. For potato-growing areas, strain and pressure signals in the tuber region are collected using strain and pressure sensors. Combined with soil temperature, soil water potential, and soil oxygen concentration, an instantaneous tuber enlargement rate is calculated using a tuber enlargement rate and initial enlargement time model. The tuber formation start time is determined based on the first detected instantaneous tuber enlargement rate exceeding a preset enlargement rate threshold.

[0063] The core calculation formula for the tuber enlargement rate and initial enlargement time model is: ; Instantaneous tuber enlargement rate (unit: mm / d), used to determine the rate of tuber growth; Strain (με) and pressure (kPa) in the tuber region are collected by sensors in the shallow root zone (the main distribution area of ​​tubers) (the system is deployed in three dimensions to adapt to the tuber distribution). Optimal temperature for potato tuber enlargement (17-20℃, specifically adapted to potato physiology). Tuber-specific calibration coefficient (recommended initial value: .

[0064] The physiological basis of this model is that potato tuber enlargement is the result of cell division and elongation. During the tuber volume increase process, it continuously compresses the surrounding soil, generating significant strain and pressure signals. The enlargement rate is positively correlated with the mechanical signals. Temperature deviations from the optimal temperature range inhibit cell division and elongation rates, drought stress reduces tuber enlargement activity, and hypoxia inhibits tuber cell respiration and metabolism, thereby reducing the enlargement rate.

[0065] The criterion for determining the start time of tuber formation is the first detection of... The time points where the strain / pressure rate is greater than 0.2 mm / d. The system continuously monitors the strain and pressure signals in the tuber region and calculates... Value, when The time point when the rate first exceeds 0.2 mm / d is recorded as the starting point of the tuber formation period. This criterion is based on the physiological characteristics of potato tuber enlargement; when the tuber enters the enlargement stage, the enlargement rate rapidly increases from near zero to above 0.2 mm / d.

[0066] Tuber size growth trend through It is obtained by integrating over time. Integrating over time yields the change in tuber diameter or volume. This integration calculation continues after the tuber formation stage begins, updating the tuber growth progress in real time. When the integral value reaches the expected tuber size for the variety, the system outputs a corresponding notification.

[0067] Early identification of tuber malformation and uneven enlargement by comparing different locations in the superficial layer. Value implementation. When different positions When the values ​​differ too much, it indicates that the tubers are not expanding evenly, which may result in deformities or significant differences in tuber size. It is necessary to check the soil environmental conditions and nutrient supply status in a timely manner.

[0068] Tuber stress diagnosis and yield prediction are crucial for optimizing tuber growth environment management. Based on the instantaneous tuber enlargement rate, tuber sink strength and tuber dry matter accumulation are calculated using a tuber stress diagnosis model. A tuber stress index is then calculated to determine the type and degree of stress on the tubers. Finally, the tuber maturity period is predicted based on the tuber stress index and tuber sink strength.

[0069] The tuber sink strength and dry matter accumulation model is used to assess the tuber's ability to accumulate photosynthetic products and the intensity of dry matter accumulation. The tuber sink strength ranges from 0 to 8, with higher values ​​indicating a stronger ability of the tuber to absorb photosynthetic products.

[0070] Tuber sink strength is positively correlated with tuber enlargement rate, soil heat flux, and soil electrical conductivity, and negatively correlated with soil water potential. A higher tuber enlargement rate indicates more active cell division and elongation, resulting in stronger sink strength. Soil heat flux reflects soil energy supply; sufficient energy leads to vigorous tuber metabolism, which is beneficial for dry matter accumulation. When soil electrical conductivity is close to an optimal value, salt stress is low, and sink strength is normal. Low soil water potential leading to drought stress inhibits tuber enlargement and reduces sink strength.

[0071] The determination of tuber stress type is achieved by combining multiple soil parameters: when soil water potential is too low and A value greater than 0.5 indicates drought stress; when the soil oxygen concentration is too low and When the value is greater than 0.5, it is considered hypoxic stress; when the soil temperature deviates from the suitable range and When the value is greater than 0.5, it is considered temperature stress; when the soil electrical conductivity is too high and A value greater than 0.5 is considered salt stress. A value greater than 0.8 indicates severe stress, with tuber enlargement essentially halted, requiring immediate management measures.

[0072] The prediction of tuber maturity is based on the trends in swelling rate and sink strength. When tending to 0 and A value less than 1 indicates that the tuber has stopped growing and entered the maturity stage. The system automatically marks this time point and, combined with historical data and variety characteristics, predicts the optimal harvest time.

[0073] Root-tuber synergy matching degree analysis is a key step in revealing the synergistic relationship between root supply capacity and tuber absorption capacity. Based on root vitality index, root-soil interaction intensity index, and tuber sink strength, combined with soil water potential and soil oxygen concentration, a root-tuber synergy matching degree model is used to calculate the root-tuber synergy matching degree index, revealing the synergistic relationship between root supply capacity and tuber absorption capacity.

[0074] The core calculation formula of the root-tuber synergistic matching degree model is: ; Root-tuber synergy matching degree (unitless, value from 0 to 6, the closer the value is to 3, the better the synergy); Root vitality index; : Root-soil interaction strength; Strong tuber storage capacity; Synergy coefficient (recommended initial value 3.0).

[0075] The physiological basis of this model is that the root system is the source, responsible for supplying water, nutrients, and energy; the tuber is the sink, responsible for consuming and accumulating dry matter. The root system's supply capacity depends on root vigor and root-soil contact, while the tuber's absorption capacity depends on the strength of the tuber sink. The synergy between the two determines the overall yield formation efficiency. Soil environmental parameters (soil water potential and oxygen concentration) affect the efficiency of this synergy.

[0076] The criteria for judging the root-tuber synergistic matching degree are: When the value is less than 2, the root system's energy and fertilizer supply is insufficient and cannot meet the tuber's growth needs. It is necessary to strengthen the supply of water and fertilizer or promote root growth. When the ratio is 2 to 4, the root and tuber synergy is normal, and the root supply capacity and tuber absorption capacity are well matched; When the value is greater than 4, the tuber storage strength is insufficient and the root system supply is excessive, which may lead to excessive growth of the above-ground parts. It is necessary to control the application of nitrogen fertilizer or promote tuber development.

[0077] The feedback regulation effect of tubers on the root system is achieved by monitoring the changing trend of the root vitality index. When Greater than 4 and When the trend is downward, it indicates that the tuber enlargement is exerting mechanical pressure on the root system, restricting root growth. The system automatically outputs feedback control information, suggesting that measures such as loosening the soil or adjusting the planting density may be necessary.

[0078] Comprehensive assessment of soil environmental impact factors is a crucial step in identifying yield-limiting factors and guiding precision management. Based on soil water potential, soil oxygen concentration, soil temperature, soil electrical conductivity, and soil heat flux, a comprehensive soil environmental impact model is used to calculate comprehensive soil environmental impact factors and identify the limiting factors with the greatest impact on the root-tuber system.

[0079] The core calculation formula of the soil environmental comprehensive impact model is: ; : Comprehensive influence factor of soil environment (unitless, value from 0 to 5, the higher the value, the more suitable the soil environment is for root-tuber growth); : Minimum temperature for root-tuber growth (take 5℃); Suitable soil heat flux for root-tuber growth (take 60W / m²). Weighting coefficients (aligning with potato physiology, recommended initial values:) ).

[0080] The comprehensive impact factors of soil environment were calculated using a linear weighted method, with different weights for each environmental factor on root-tuber growth. Soil moisture was the most influential factor, with a weight of 0.3; soil oxygen was the second most important factor, with a weight of 0.25; soil temperature was the third most important factor, with a weight of 0.2; and soil electrical conductivity and soil heat flux had weights of 0.15 and 0.1, respectively.

[0081] The method for identifying the first limiting factor for output is to calculate the product of the weights corresponding to each parameter and the normalized values, and take the factor with the smallest product as the first limiting factor.

[0082] According to the second embodiment of the present invention, taking potato field planting as an example, the actual application process of the method of the present invention is described in detail. Assume that monitoring is being conducted at a potato planting base in North China, the planted variety is a late-maturing potato variety, the planting time is mid-April, and the expected harvest time is late September.

[0083] Before planting, sensor arrays were deployed in the selected monitoring plots according to the requirements of step 1, using a three-dimensional layout with three vertical layers and eight horizontal directions. The shallow root zone, located at a depth of 0 to 15 cm, was mainly used to monitor tuber enlargement dynamics; the middle root zone, located at a depth of 15 to 30 cm, was mainly used to monitor root growth dynamics; and the deep root zone, located at a depth of 30 to 60 cm, was mainly used to monitor deep root expansion. After the sensor deployment was completed, system calibration and communication tests were performed to ensure that each sensor was working properly and that data transmission was stable.

[0084] Thirty days after planting, the seedling stage begins, and the system starts monitoring root vitality and root-soil interaction intensity. Following steps 2 and 3, the system simultaneously collects root mechanical signals and soil environmental parameters. Calculations in step 5 show that the root vitality index during the seedling stage stabilizes between 7.0 and 8.0, indicating good root vitality. The root-soil interaction intensity during the seedling stage also stabilizes between 2.5 and 3.0, indicating normal root-soil contact. The comprehensive soil environmental impact factor stabilizes between 3.5 and 4.0, indicating suitable soil conditions for root growth.

[0085] On day 55 post-planting, tuber formation begins, and the system starts focusing on monitoring the initial tuber enlargement. Following step 6, the system continuously collects strain and pressure signals from the tuber area. On day 58 post-planting, the system-calculated instantaneous tuber enlargement rate first exceeds 0.2 mm / d, automatically determining the start of the tuber formation period and recording this time point. This determination result is consistent with actual field observations, verifying the accuracy of the system's tuber formation period determination.

[0086] After the tuber formation stage begins, the system continuously monitors the dynamics of tuber enlargement. Calculations in step 7 show that the tuber enlargement rate is 0.3 to 0.5 mm / d in the early tuber formation stage, gradually increasing to 0.8 to 1.0 mm / d as the tubers continue to enlarge, entering the peak enlargement stage. The tuber sink strength gradually increases from 2.0 in the early tuber formation stage to 5.5 to 6.0 in the peak enlargement stage, indicating a continuously enhancing ability of the tubers to accumulate dry matter. The accumulated dry matter in the tubers continues to increase over time, reaching the expected yield level before harvest.

[0087] Irrigation was carried out on the 75th day after planting. System monitoring data before and after irrigation showed that the soil water potential was -85 kPa before irrigation and rose to -35 kPa after irrigation; the tuber enlargement rate was 0.65 mm / d before irrigation and increased to 0.85 mm / d after irrigation. Irrigation improved soil moisture conditions and significantly increased the tuber enlargement rate, verifying the promoting effect of irrigation on tuber enlargement.

[0088] Ninety days after planting, the plant encountered continuous rainy weather, resulting in persistently high soil moisture and a drop in soil oxygen concentration to 8%. System monitoring data showed that during the rainy period, soil oxygen concentration decreased to 8%, and the tuber stress index (S_{t,stress}) rose to 0.55, indicating a risk of hypoxia stress. The system issued a warning and recommended drainage and soil loosening measures. After the farmer took these measures, soil oxygen concentration returned to normal levels, and the tuber stress index fell below 0.2.

[0089] Through a comprehensive assessment of soil environmental impact factors, the system identified the primary limiting factor for this field at different growth stages. During the seedling stage, the primary limiting factor was soil temperature (with the smallest weighted product), and the system recommended using mulch to increase soil temperature. During tuber formation, the primary limiting factor was soil water potential, and the system recommended strengthening irrigation management. During the peak tuber enlargement stage, the primary limiting factor was soil oxygen concentration, and the system recommended maintaining loose soil aeration. During maturity, the primary limiting factor was soil heat flux, and the system recommended appropriately controlling water to promote maturity. Farmers implemented corresponding management measures based on the system's recommendations, effectively improving yield and quality.

[0090] This invention collects root mechanics signals using strain and pressure sensors, and combines this with multiple soil parameters to construct a deeply coupled monitoring system for root mechanics and soil parameters. This system enables quantitative inversion of root biology, potato tuber biology, and root-tuber synergistic biology issues. The method comprehensively covers key parameters such as soil water potential, soil oxygen concentration, and soil heat flux. It achieves three-dimensional spatial perception through a three-dimensional layout and precise monitoring through multi-model collaborative analysis, providing a new technical means for crop production management.

[0091] This invention is mainly applicable to potatoes because their signal acquisition is obvious; however, it is also applicable to other crops, such as soybeans (where the signal may not be obvious). The specific relevant models used for different crops are slightly different.

[0092] In the several embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0093] Furthermore, the functional units 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 units described above can be implemented in hardware or as software functional units. The above are merely embodiments of the present invention and do not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

[0094] The specific embodiments of the invention have been described in detail above, but these are merely examples, and the invention is not limited to the specific embodiments described above. For those skilled in the art, any equivalent modifications or substitutions to the invention are also within the scope of this invention. Therefore, all equivalent transformations, modifications, and improvements made without departing from the spirit and principles of this invention should be included within the scope of this invention.

Claims

1. An in-situ monitoring method based on root mechanics-soil multi-parameter coupling, characterized in that, Includes the following steps: Step 1: In-situ sensor array three-dimensional deployment. Multiple sets of sensor units are deployed in three dimensions in the crop planting area to perform in-situ synchronous acquisition of soil environmental parameters and root mechanical signals. Step 2: Collect and preprocess root mechanical signals. Collect strain values ​​inside the root zone, pressure values ​​outside the root zone, and environmental noise values ​​in real time. Based on the environmental noise values, perform noise reduction processing on the collected strain and pressure signals to obtain corrected root zone strain and pressure signals. Step 3: Synchronously collect multiple soil parameters and construct a soil environmental parameter dataset by synchronously collecting data from the multiple sets of sensor units; Step 4: Root growth rate and spatial expansion inversion. Calculate the time rate of change of strain signal and the time rate of change of pressure signal. Use the root growth rate and spatial expansion model to calculate the instantaneous root growth rate. Invert the root growth direction and spatial expansion intensity based on the instantaneous root growth rate values ​​at different locations. Step 5: Perform root vitality and stress diagnosis and root-soil interaction strength analysis. Use the root vitality and stress diagnosis model to calculate the root vitality index, determine the degree of drought stress and salt stress on the roots, and use the root-soil interaction strength model to calculate the root-soil interaction strength index to quantitatively analyze the degree of root-soil contact. Step 6: For potato planting areas, the tuber expansion rate and initial expansion time model are used to calculate the instantaneous tuber expansion rate. The tuber formation start time is determined based on the time point when the instantaneous tuber expansion rate first exceeds the preset expansion rate threshold. Step 7: Perform tuber stress diagnosis and yield prediction and root-tuber synergy matching degree analysis. Calculate the tuber stress index to determine the type and degree of stress on the tuber and predict the tuber maturity period. Use the root-tuber synergy matching degree model to calculate the root-tuber synergy matching degree index and obtain the synergistic relationship between root supply capacity and tuber absorption capacity. Step 8: Comprehensive assessment of soil environmental impact factors. The comprehensive soil environmental impact model is used to calculate the comprehensive soil environmental impact factors and identify the limiting factors that have the greatest impact on the root-tuber system.

2. The in-situ monitoring method based on root mechanics-soil multi-parameter coupling according to claim 1, characterized in that, Step 1 also includes: The strain sensor, pressure sensor, soil water potential sensor, soil oxygen concentration sensor, soil heat flux sensor, soil temperature and humidity sensor, soil electrical conductivity sensor and soil pH sensor are deployed in a three-dimensional layout with three layers in the vertical direction and eight directions in the horizontal direction, forming a total of 24 sensor units. The specific division of the three vertical layers is as follows: The first layer is the shallow root zone, with a depth ranging from 0 to 15 centimeters, where the crop's absorbing roots and primary tubers are distributed; The second layer is the middle root zone, with a depth of 15 to 30 centimeters, where active roots are distributed; The third layer is the deep root zone, with a depth of 30 to 60 centimeters, where the supporting root system is distributed; Each floor is equipped with sensor groups in eight horizontal directions: east, southeast, south, southwest, west, northwest, north, and northeast.

3. The in-situ monitoring method based on root mechanics-soil multi-parameter coupling according to claim 2, characterized in that, Also includes: The strain sensor is a high-precision resistance strain gauge sensor with a range that covers the preset strain range and a sampling frequency that is not lower than the preset sampling frequency. The pressure sensor uses a miniature earth pressure cell, and its range covers a preset pressure range with a response time less than a preset response time threshold. The soil water potential sensor is a gypsum resistance block type water potential sensor, and the measurement range is a preset water potential range. The soil oxygen concentration sensor is a polarographic oxygen electrode sensor, and the measurement range is a preset oxygen concentration range. The soil heat flux sensor is a heat flux plate sensor, and the measurement range is a preset heat flux range. The soil conductivity sensor adopts a four-electrode design and measures within a preset conductivity range. The soil pH sensor adopts a glass electrode design and measures within a preset pH range. The sensor array is centrally managed by a main control unit, which is equipped with a multi-channel synchronous acquisition module.

4. The in-situ monitoring method based on root mechanics-soil multi-parameter coupling according to claim 3, characterized in that, Step 3 also includes A soil environmental parameter dataset is constructed by synchronously collecting soil water potential, soil oxygen concentration, soil heat flux, soil temperature, soil moisture, soil electrical conductivity, and soil pH value using multiple sets of sensor units.

5. The in-situ monitoring method based on root mechanics-soil multi-parameter coupling according to claim 4, characterized in that, Step 4 also includes: The time-varying rate of change of the strain signal was calculated using a sliding window difference algorithm, and the root growth rate and spatial expansion model were derived using the formula... ； : Instantaneous root growth rate, inverting the "real-time root growth rate", with positive values ​​indicating growth and negative values ​​indicating stagnation / senescence; The time-varying rate of change of the strain signal in the root region is acquired in real time by the system strain sensor and calculated by the main control unit, where ε is the strain value inside the root region. The time rate of change of the root zone pressure signal is acquired in real time by the system pressure sensor and calculated by the main control unit. Real-time soil temperature is collected by the system's temperature and humidity sensors; : The optimal temperature for crop root growth; Real-time soil oxygen concentration, collected by the system's soil oxygen / respiration sensor; : Soil saturated oxygen concentration; Weighting coefficient.

6. The in-situ monitoring method based on root mechanics-soil multi-parameter coupling according to claim 5, characterized in that, Step 5 further includes: The root vitality and stress diagnostic model adopts ； The root vitality index ranges from 0 to 10. The higher the value, the stronger the root vitality and the healthier the physiological state. It is a core inversion indicator. The strain inside the root zone and the pressure outside the root zone are collected in real time by the system's strain and pressure sensors, reflecting the intensity of root physiological activity. : Environmental noise value in non-planting areas, collected by sensors in non-planting areas of the system, used to filter natural environmental interference and improve calculation accuracy; Soil water potential is collected by the system's soil water potential sensors and is primarily used to invert the degree of drought stress. Soil electrical conductivity, collected by the system's electrical conductivity sensor, is primarily used to invert the degree of salt stress; Weight calibration coefficient; Soil water potential correction function quantifies the degree of drought stress. The lower the water potential, the larger the function value, and the stronger the inhibitory effect on root activity. Soil electrical conductivity correction function quantifies the degree of salt stress. The higher the electrical conductivity, the larger the function value, and the stronger the inhibitory effect on root vitality.

7. The in-situ monitoring method based on root mechanics-soil multi-parameter coupling according to claim 6, characterized in that, Step 5 further includes: The root-soil interaction strength model uses the formula... ； Root-soil interaction strength, ranging from 0 to 5. The higher the value, the closer the root-soil contact and the stronger the interaction. Root zone strain and pressure; Interaction coefficient; Suitable water potential for root growth; : Maximum EC value tolerable by crop roots.

8. The in-situ monitoring method based on root mechanics-soil multi-parameter coupling according to claim 7, characterized in that, Step 6 further includes: The tuber enlargement rate and initial enlargement time model uses the formula... ； : Instantaneous tuber enlargement rate, inversely reflecting the tuber growth rate; Strain and pressure in the tuber region were collected by shallow sensors in the root zone. Optimal temperature for potato tuber enlargement; Tuber-specific calibration coefficient.

9. The in-situ monitoring method based on root mechanics-soil multi-parameter coupling according to claim 8, characterized in that, Step 7 further includes: Based on the instantaneous tuber enlargement rate, the tuber sink strength and tuber dry matter accumulation amount are calculated by combining the tuber sink strength and dry matter accumulation model. The tuber stress index is calculated by the tuber stress diagnosis model to determine the type and degree of stress on the tuber. The tuber maturity period is predicted based on the tuber stress index and tuber sink strength. ； : Tuber storage strength, with a value of 0-8. The higher the value, the stronger the tuber's ability to absorb photosynthetic products. Soil heat flux, collected by the system's soil heat flux sensor, reflects the soil's energy supply; The optimal EC value for potato tuber growth; : Accumulation of dry matter in tubers; : Initial expansion time and current time; : Tuber-specific coefficient.

10. The in-situ monitoring method based on root mechanics-soil multi-parameter coupling according to claim 9, characterized in that, Step 7 further includes: The tuber stress diagnostic model uses the formula ； Tuber stress index, ranging from 0 to 1, with higher values ​​indicating more severe stress; The maximum tuber enlargement rate was calibrated through experiments. Maximum storage strength of tubers.

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