Method and system for in-situ diagnosis of salt injury degree of crop growth in saline-alkali soil

Abstract

The application provides a saline-alkali soil crop growth salt damage degree in-situ diagnosis method and system, relates to the technical field of crop growth monitoring, and the method comprises the following steps: acquiring first root system image information and first root layer soil moisture content of a first crop in a to-be-measured saline-alkali soil planting area, acquiring second root system image information and second root layer soil moisture content of a second crop in a preset control area; calculating first root system growth information and second root system growth information; constructing a first comprehensive growth response model and a second comprehensive growth response model; calculating a first comprehensive growth parameter based on the first comprehensive growth response model, calculating a second comprehensive growth parameter based on the second comprehensive growth response model; and determining the crop salt stress degree of the to-be-measured saline-alkali soil planting area based on the first comprehensive growth parameter and the second comprehensive growth parameter. The saline-alkali soil crop growth salt damage degree in-situ diagnosis method and system provided by the application realizes real-time and accurate detection of the saline-alkali soil crop salt stress degree.

Description

Technical Field

[0001] This invention relates to the field of crop growth monitoring technology, and in particular to an in-situ diagnostic method and system for the degree of salt damage to crops in saline-alkali land. Background Technology

[0002] Saline-alkali land is an important reserve of arable land, but soil salinity stress in saline-alkali land restricts stable and increased crop yields. Therefore, real-time and accurate diagnosis of the degree of salt damage to crops caused by saline-alkali land is the key to scientific regulation.

[0003] Existing methods for diagnosing salt damage mainly include soil sampling and remote sensing monitoring. Soil sampling assesses stress levels through laboratory analysis of soil salinity, but it is labor-intensive, cumbersome, and time-consuming, resulting in insufficient real-time data and an inability to achieve continuous, in-situ observation. This makes it difficult to match the dynamic evolution of soil salinity with field management practices. Remote sensing monitoring infers the degree of salt damage based on the spectral characteristics of crop canopies, but its accuracy is significantly affected by weather conditions such as rain and cloud cover. Furthermore, its long monitoring period makes it unable to promptly capture short-term crop responses to salt stress, leading to low accuracy and real-time performance in assessing the degree of salt stress in crops in saline-alkali land. Summary of the Invention

[0004] This invention provides an in-situ diagnostic method and system for the degree of salt damage to crops growing in saline-alkali land, which solves the technical problems of low real-time performance and low accuracy in detecting the degree of salt stress in crops in saline-alkali land in the prior art.

[0005] This invention provides an in-situ diagnostic method for the degree of salt damage to crops growing in saline-alkali land, comprising the following steps: At a first preset monitoring point, image information of the first root system and soil moisture content of the first root layer of the first crop in the saline-alkali land planting area to be tested are acquired. At a second preset monitoring point, image information of the second root system and soil moisture content of the second crop in a preset control area are acquired. The number of the first preset monitoring points and the second preset monitoring points are the same, and the number of the points is greater than or equal to three. The crop species and field management measures corresponding to the first crop and the second crop are the same. The location of the saline soil in the preset control area is greater than or equal to a preset depth. Based on the first root system image information, first root system growth information is obtained, and based on the second root system image information, second root system growth information is obtained; Based on the first root growth information and the first root layer soil moisture content, a first comprehensive growth response model is constructed, and based on the second root growth information and the second root layer soil moisture content, a second comprehensive growth response model is constructed. Based on the first comprehensive growth response model, the first comprehensive growth parameter of the first crop at the target time is calculated, and based on the second comprehensive growth response model, the second comprehensive growth parameter of the second crop at the target time is calculated. Based on the first comprehensive growth parameter and the second comprehensive growth parameter, the degree of crop salt stress corresponding to the saline-alkali land planting area to be tested is determined.

[0006] According to the present invention, an in-situ diagnostic method for the degree of salt damage to crops growing in saline-alkali land is provided, wherein the first comprehensive growth response model is constructed based on the first root growth information and the first root layer soil moisture content, including: Based on the first root growth information, calculate the current normalized value of each root growth index; Determine the weights of the root growth indicators; Calculate the root system comprehensive growth index based on the current normalized value and the index weight; Based on the fitting relationship between the root system comprehensive growth index and the soil moisture content of the first root layer, the first comprehensive growth response model is constructed.

[0007] According to the present invention, an in-situ diagnostic method for the degree of salt damage to crops growing in saline-alkali land is provided, wherein the root growth indicators include at least two of the following: root length, root length density, root surface area, and root diameter.

[0008] According to the present invention, an in-situ diagnostic method for the degree of salt damage to crops growing in saline-alkali land is provided, wherein determining the index weight of the root growth index includes: Multiple sets of historical test data were collected; each set of historical test data included measured values ​​of multiple root growth indicators of different crops planted in different salinity soils and the true values ​​of the corresponding comprehensive root growth index. The measured values ​​of each root growth index were normalized to obtain the corresponding historical normalized values. Under preset constraints, the historical normalized values ​​and the true values ​​of the root system comprehensive growth index are fitted to obtain the index weight of each root system growth index; the preset constraints are that the weight of each index is greater than or equal to 0, and the sum of the weights of all indices is 1.

[0009] According to the present invention, an in-situ diagnostic method for the degree of salt damage to crops in saline-alkali land is provided, wherein determining the degree of crop salt stress corresponding to the saline-alkali land planting area to be tested based on the first comprehensive growth parameter and the second comprehensive growth parameter includes: The crop salt damage index is calculated based on the first comprehensive growth parameter and the second comprehensive growth parameter. The degree of salt stress on the crop is determined based on the crop salt damage index.

[0010] According to the present invention, an in-situ diagnostic method for the degree of salt damage to crops growing in saline-alkali land is provided, wherein the degree of crop salt stress includes at least four preset levels: no stress, mild stress, moderate stress, and severe stress.

[0011] According to the present invention, an in-situ diagnostic method for the degree of salt damage to crops growing in saline-alkali land is provided, wherein determining the degree of salt stress of the crop based on the crop salt damage index includes: When the crop salt damage index is greater than 0 and less than or equal to the first threshold, the crop salt stress level is defined as no stress. When the crop salt damage index is greater than the first threshold and less than or equal to the second threshold, the degree of crop salt stress is the mild stress. When the crop salt damage index is greater than the second threshold and less than or equal to the third threshold, the degree of crop salt stress is the moderate stress. When the crop salt damage index is greater than the third threshold and less than or equal to the fourth threshold, the degree of crop salt stress is defined as severe stress.

[0012] This invention also provides an in-situ diagnostic system for the degree of salt damage to crops growing in saline-alkali land, comprising the following modules: The data acquisition module is used to acquire the first root system image information and the first root layer soil moisture content of the first crop in the saline-alkali land planting area to be tested at a first preset monitoring point, and to acquire the second root system image information and the second root layer soil moisture content of the second crop in a preset control area at a second preset monitoring point; the number of the first preset monitoring points and the second preset monitoring points is the same, and the number of the first preset monitoring points is greater than or equal to 3; the crop types and field management measures corresponding to the first crop and the second crop are the same; the location of the saline soil in the preset control area is greater than or equal to a preset depth; The image analysis module is used to obtain first root growth information based on the first root image information, and to obtain second root growth information based on the second root image information; The model building module is used to build a first comprehensive growth response model based on the first root growth information and the first root layer soil moisture content, and to build a second comprehensive growth response model based on the second root growth information and the second root layer soil moisture content. The growth calculation module is used to calculate the first comprehensive growth parameter of the first crop at the target time based on the first comprehensive growth response model, and to calculate the second comprehensive growth parameter of the second crop at the target time based on the second comprehensive growth response model. The salt damage diagnosis module is used to determine the degree of crop salt stress in the saline-alkali land planting area to be tested based on the first comprehensive growth parameter and the second comprehensive growth parameter.

[0013] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the in-situ diagnosis method for the degree of salt damage to crops growing in saline-alkali land as described above.

[0014] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the in-situ diagnosis method for the degree of salt damage to crops growing in saline-alkali land as described above.

[0015] The present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements the in-situ diagnosis method for the degree of salt damage to crops growing in saline-alkali land as described above.

[0016] This invention provides a method and system for in-situ diagnosis of salt damage to crops in saline-alkali land. It acquires first root system images and first root layer soil moisture content of a first crop in a saline-alkali land planting area at a first preset monitoring point, and second root system images and second root layer soil moisture content of a second crop in a preset control area at a second preset monitoring point. The number of the first and second preset monitoring points is the same, and greater than or equal to three. The crop types and field management practices for the first and second crops are the same. The saline soil in the preset control area is at a depth greater than or equal to a preset depth. This in-situ synchronous acquisition of root system images and root layer soil moisture content in the planting area and the preset control area solves the problems of soil structure damage in traditional soil drilling methods and weather interference in remote sensing methods, achieving in-situ, non-destructive, and real-time monitoring of the crop growth environment. Based on the first root system image information, first root growth information is acquired, and based on the second root system image information, second root growth information is acquired. Root growth information is obtained through image analysis, directly reflecting the physiological state of the crop affected by salt damage, thus improving the diagnosis of salt damage. The accuracy of the diagnosis is improved. Based on the first root growth information and the first root layer soil moisture content, a first comprehensive growth response model is constructed. Furthermore, based on the second root growth information and the second root layer soil moisture content, a second comprehensive growth response model is constructed. This integrates root growth information and root layer soil moisture content to construct comprehensive growth response models corresponding to different regions, eliminating the interference of soil moisture differences on root growth and ensuring the scientific validity and comparability of the model output. Based on the first comprehensive growth response model, the first comprehensive growth parameters of the first crop at the target time are calculated. Based on the second comprehensive growth response model, the second comprehensive growth parameters of the second crop at the target time are calculated. By calculating the comprehensive growth parameters of the tested saline-alkali land planting area and the preset control area at the same time, a dynamic benchmark for salt damage diagnosis is established, solving the misjudgment problem caused by the lack of synchronous controls in traditional methods. Based on the first and second comprehensive growth parameters, the degree of crop salt stress corresponding to the tested saline-alkali land planting area is determined, thus achieving real-time and accurate detection of the degree of salt stress in saline-alkali land crops, providing a reliable basis for timely and accurate intervention in field management measures. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating the in-situ diagnostic method for the degree of salt damage to crops in saline-alkali land provided by the present invention.

[0019] Figure 2 This is a schematic diagram of the in-situ diagnostic system for the degree of salt damage to crops in saline-alkali land provided by the present invention.

[0020] Figure 3 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0022] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element. Furthermore, it should be noted that the scope of the methods and systems in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0023] In this application's embodiments, "determine B based on A" means that factor A must be considered when determining B. It is not limited to "B can be determined based solely on A," but should also include: "determine B based on A and C," "determine B based on A, C, and E," "determine C based on A, and further determine B based on C," etc. Additionally, it can include using A as a condition for determining B, for example, "when A meets the first condition, determine B using the first method"; another example, "when A meets the second condition, determine B," etc.; another example, "when A meets the third condition, determine B based on the first parameter," etc. Of course, it can also be a condition where A is a factor in determining B, for example, "when A meets the first condition, determine C using the first method, and further determine B based on C," etc.

[0024] It should also be noted that the terms "target," "first," and "second" in this invention are used to distinguish similar objects, not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first" and "second" are generally of the same class, without limiting the number of objects; for example, the first object can be one or more.

[0025] In this invention, the term "multiple" refers to two or more kinds, and other quantifiers are similar.

[0026] The following is combined with Figures 1 to 3 This invention describes an in-situ diagnostic method and system for the degree of salt damage to crops growing in saline-alkali land.

[0027] Figure 1 This is a flowchart illustrating the in-situ diagnostic method for the degree of salt damage to crops in saline-alkali land provided by the present invention. Figure 1 As shown, the method includes the following: Step 101: Obtain the first root system image information and the first root layer soil moisture content of the first crop in the saline-alkali land planting area to be tested at the first preset monitoring point; and obtain the second root system image information and the second root layer soil moisture content of the second crop in the preset control area at the second preset monitoring point; the number of the first preset monitoring point and the second preset monitoring point are the same, and the number of the two preset monitoring points is greater than or equal to 3; the crop type and field management measures corresponding to the first crop and the second crop are the same; the location of the saline soil in the preset control area is greater than or equal to the preset depth.

[0028] Specifically, using the in-situ microroot canal method, three or more first-preset monitoring points were randomly arranged in the planting area of ​​the saline-alkali land to be tested, and image information of the first root system and soil moisture content of the first root layer were collected. At the same time, three or more second-preset monitoring points were randomly arranged in the preset control area, and image information of the second root system and soil moisture content of the second root layer were collected simultaneously. The number of first-preset monitoring points and second-preset monitoring points was the same.

[0029] For example, at the first and second preset monitoring points, a microroot canal system (MRS) is inserted into the pre-embedded pipe to collect corresponding first and second root system image information.

[0030] For example, at the first and second preset monitoring points, the soil moisture content of the first root layer and the second root layer in the 0-60cm soil layer are monitored using a frequency domain reflectometry (FDR) soil moisture sensor.

[0031] The saline-alkali land to be tested is the primary crop production area, with a planting area of ​​at least 10 mu (approximately 1.65 acres). The pre-set control area is an observation area free from salt stress. For example, using the plot isolation method, a separate soil column is set up in the saline-alkali land to be tested as an observation area to avoid water and salt migration and exchange with the surrounding soil. In the pre-set control area, the location of the saline soil is greater than or equal to a pre-set depth.

[0032] For example, if the height of the soil column is 1.5m, the soil column in the preset control area will be irrigated with a large amount of water before planting, and the salt in the soil will be washed away to below 1.5m (i.e., the preset depth) by rinsing.

[0033] By deploying soil conductivity sensors at different depths within the soil column, the soil salinity content can be monitored in real time to ensure that the second crop in the pre-set control area grows without salt stress throughout its entire growth period. The first crop in the tested saline-alkali land planting area and the second crop in the pre-set control area share the same crop species and field management practices; either the first or second crop can be a commonly grown crop in saline-alkali land, such as wheat or sunflower.

[0034] This invention achieves synchronous, in-situ, and continuous monitoring of crop root growth environment and phenotype by simultaneously collecting the first root system image information and first root layer soil moisture content of the first crop in the saline-alkali land planting area to be tested, as well as the second root system image information and second root layer soil moisture content of the second crop in the preset control area. This provides a high-precision and comparable data foundation for salt damage diagnosis.

[0035] Step 102: Based on the first root system image information, obtain the first root system growth information, and based on the second root system image information, obtain the second root system growth information.

[0036] Specifically, the root image information is converted into quantitative root growth information through image processing algorithm software, including at least root length, root length density, root surface area, and root diameter.

[0037] The root length is calculated using the following formula: In the formula, for Root length (mm) calculated at time 1; This represents the number of pixels occupied by the root system. Area occupied by a single pixel (mm) 2 ); The number of pixels occupied by the average diameter of the root system; Width per single pixel (mm).

[0038] Root length density is calculated using the following formula: in, for Root length density at time (mm·mm) -3 ); The actual area observed in the micro-root canal (mm²) 2 ); The distance (mm) from the wall of the micro-root canal to the surrounding soil is preferred. D The value is 2.5 mm.

[0039] The root surface area is calculated using the following formula: in, for Root surface area at time (mm) 2 ); This represents the total number of pixels in the root system. This represents the correspondence between pixel area and actual area in an image. This refers to the magnification factor of the optical element.

[0040] The root diameter is calculated using the following formula: in, for Average root diameter (mm) at any given time.

[0041] For example, the collected first root system image information can be imported into root system analysis software (such as WinRHIZO™ Pro 2019). The software automatically identifies the root outline, removes soil impurities, and calculates the corresponding first root system growth information, including root length, root length density, root surface area, and root diameter. Similarly, importing the second root system image information into the root system analysis software will calculate the corresponding second root system growth information.

[0042] Roots are the most sensitive organs to soil salinity stress, and changes in their length and surface area often precede visible symptoms in the above-ground parts. This invention transforms unstructured image data into structured, multi-dimensional root phenotypic parameters to obtain root growth information, providing a foundation for subsequent precise quantitative diagnosis of salinity levels.

[0043] Step 103: Based on the first root growth information and the first root layer soil moisture content, construct a first comprehensive growth response model, and based on the second root growth information and the second root layer soil moisture content, construct a second comprehensive growth response model.

[0044] Specifically, root growth is affected by both soil moisture and salinity. This invention introduces root zone soil moisture content as a covariate to construct a comprehensive growth response model. This model not only reflects the root growth status but also eliminates interference from soil moisture fluctuations, ensuring that the output value of the comprehensive growth response model accurately reflects the biological effects of salinity.

[0045] Furthermore, the construction of the first comprehensive growth response model based on the first root growth information and the first root layer soil moisture content includes: Based on the first root growth information, calculate the current normalized value of each root growth index; Determine the weights of the root growth indicators; Calculate the root system comprehensive growth index based on the current normalized value and the index weight; Based on the fitting relationship between the root system comprehensive growth index and the soil moisture content of the first root layer, the first comprehensive growth response model is constructed.

[0046] Furthermore, the root growth indicators include at least two of the following: root length, root length density, root surface area, and root diameter.

[0047] Specifically, the multi-dimensional root phenotypic parameters in the root growth information are used as root growth indicators, and then multiple root growth indicators are integrated to construct a comprehensive growth response model.

[0048] First, the root growth index data are normalized, and the normalized values ​​of the root growth index are calculated: in, For the first The current normalized value of each root growth index; For the first The average value of each root growth index; For the first The minimum value of each root growth index; For the first The maximum value of each root growth index.

[0049] Then, the root growth index is calculated based on the index weights of the root growth indicators and the current normalized value.

[0050] Further, determining the weights of the root growth indicators includes: Multiple sets of historical test data were collected; each set of historical test data included measured values ​​of multiple root growth indicators of different crops planted in different salinity soils and the true values ​​of the corresponding comprehensive root growth index. The measured values ​​of each root growth index were normalized to obtain the corresponding historical normalized values. Under preset constraints, the historical normalized values ​​and the true values ​​of the root system comprehensive growth index are fitted to obtain the index weight of each root system growth index; the preset constraints are that the weight of each index is greater than or equal to 0, and the sum of the weights of all indices is 1.

[0051] Specifically, by collecting multiple sets of historical test data for fitting, the error between the predicted value and the measured value is minimized during the fitting process, and the optimal weight combination is solved in reverse to serve as the index weight for each root growth index.

[0052] For example, firstly, 500 sets of winter wheat data from the past three years planted in a certain region are collected. Each set of data includes measured values ​​of root growth indicators and corresponding biomass (as a reference for the true value of the comprehensive growth index). Then, the measured values ​​of each root growth indicator are normalized to obtain the corresponding historical normalized values. Finally, an objective function is constructed to fit the historical normalized values ​​and the true value of the comprehensive root growth index, with the pre-set constraint condition being ∑ =1 and ≥0. Wherein, Indicates the first The weights of each root growth index are determined. The least squares method is used to solve this optimization problem, calculating the weights of each index for winter wheat in this region. = 4. The weights of the first to fourth root growth indicators. , , , The values ​​are 30%, 20%, 40%, and 10% respectively. , , , The weights of the indicators representing root length, root length density, root surface area, and root diameter are respectively.

[0053] The root system comprehensive growth index is calculated using the following formula: in, for The root system's overall growth index at any given time; The first root growth indicator is in The normalized value at time; The second root growth indicator is Normalized value at time; For the first Root growth indicators Normalized value at time step.

[0054] The expression for the integrated growth response model is: in, These are the comprehensive growth parameters output by the comprehensive growth response model; yes At any given time, the root zone soil moisture content (%), of which, The average moisture content of the root zone soil can be taken; A function representing the relationship between the root system comprehensive growth index and the root zone soil moisture content; It is the soil wilting moisture content (%). This refers to the soil moisture content (%) corresponding to rapid root growth, where 60% field capacity ≤ ≤80% field capacity; This refers to the soil moisture content (%) corresponding to a rapid decline in root growth, where 80% of the field capacity is < ≤100% field capacity; It is the soil saturated moisture content (%).

[0055] It should be noted that the expressions for the first and second integrated growth response models are the same. The difference lies in the source of the calculation data. If the calculation data comes from the planting area of ​​the saline-alkali land to be tested, then the first integrated growth response model is constructed accordingly. If the calculation data comes from the preset control area, then the second integrated growth response model is constructed accordingly.

[0056] This invention integrates root soil moisture content and multiple root growth indicators to construct a first comprehensive growth response model for the saline-alkali land planting area to be tested and a second comprehensive growth response model for the preset control area. This enables the model to be adaptively calibrated according to the growth characteristics of different regions and different crops, thereby improving the model's generalization ability and thus improving the accuracy of salt damage diagnosis.

[0057] Step 104: Based on the first comprehensive growth response model, calculate the first comprehensive growth parameter of the first crop at the target time, and based on the second comprehensive growth response model, calculate the second comprehensive growth parameter of the second crop at the target time.

[0058] Specifically, the root system comprehensive growth index and root zone soil moisture content of the saline-alkali land planting area acquired at the target time are input into the constructed first comprehensive growth response model to obtain the comprehensive growth parameters of the first crop in the saline-alkali land planting area at the target time, output by the first comprehensive growth response model. Similarly, the root system comprehensive growth index and root zone soil moisture content of the preset control area acquired at the target time are input into the constructed second comprehensive growth response model to obtain the comprehensive growth parameters of the second crop in the preset control area at the target time, output by the second comprehensive growth response model. This allows for real-time monitoring of the comprehensive growth parameters of the saline-alkali land planting area and the preset control area at any given time, improving the real-time nature and effectiveness of crop salt damage diagnosis.

[0059] Step 105: Based on the first comprehensive growth parameter and the second comprehensive growth parameter, determine the degree of crop salt stress corresponding to the saline-alkali land planting area to be tested.

[0060] Specifically, using the second comprehensive growth parameter of the preset control area as a benchmark, the growth inhibition rate of the saline-alkali land planting area to be tested relative to the preset control area is calculated as the crop salt damage index, thereby reflecting the real physiological damage suffered by the crop and determining the degree of crop salt stress corresponding to the saline-alkali land planting area to be tested.

[0061] Further, determining the degree of crop salt stress corresponding to the saline-alkali land planting area to be tested based on the first comprehensive growth parameter and the second comprehensive growth parameter includes: The crop salt damage index is calculated based on the first comprehensive growth parameter and the second comprehensive growth parameter. The degree of salt stress on the crop is determined based on the crop salt damage index.

[0062] Specifically, based on comprehensive growth parameters, the crop salt damage index at the target time is calculated. The crop salt damage index is calculated using the following formula: in, for Crop salt damage index at any given time; for The second comprehensive growth parameter of the control area is preset at all times; for The first comprehensive growth parameter of the saline-alkali land planting area is to be measured at all times.

[0063] Furthermore, the degree of crop salt stress includes at least four preset levels: no stress, mild stress, moderate stress, and severe stress.

[0064] Further, determining the degree of crop salt stress based on the crop salt damage index includes: When the crop salt damage index is greater than 0 and less than or equal to the first threshold, the crop salt stress level is defined as no stress. When the crop salt damage index is greater than the first threshold and less than or equal to the second threshold, the degree of crop salt stress is the mild stress. When the crop salt damage index is greater than the second threshold and less than or equal to the third threshold, the degree of crop salt stress is the moderate stress. When the crop salt damage index is greater than the third threshold and less than or equal to the fourth threshold, the degree of crop salt stress is defined as severe stress.

[0065] Specifically, the degree of crop salt stress is determined based on the crop salt damage index. The degree of crop salt stress is divided into at least four preset levels: no stress, mild stress, moderate stress, and severe stress.

[0066] For example, in one embodiment, if the first threshold is set to 25%, the second threshold to 50%, the third threshold to 75%, and the fourth threshold to 100%, the following rule can be used to determine the degree of crop salt stress at the target time. : in, for Crop salt damage index at any given time.

[0067] In some embodiments, the threshold setting can be adjusted according to actual needs, for example, set to 10 thresholds such as 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100%, thereby dividing the crop salt stress degree into 10 more detailed preset levels. The embodiments of the present invention do not limit this.

[0068] This invention improves the accuracy of assessing the degree of salt stress in crops in saline-alkali land by quantifying the degree of salt stress in crops.

[0069] This invention provides an in-situ diagnostic method for the degree of salt damage to crops in saline-alkali land. It acquires first root system images and first root layer soil moisture content of a first crop in a saline-alkali land planting area at a first preset monitoring point, and second root system images and second root layer soil moisture content of a second crop in a preset control area at a second preset monitoring point. The number of the first and second preset monitoring points is the same, and the number is greater than or equal to three. The crop types and field management practices for the first and second crops are the same. The saline soil in the preset control area is at a depth greater than or equal to a preset depth. This method solves the problems of soil structure damage caused by traditional soil drilling methods and weather interference with remote sensing methods by simultaneously acquiring root system images and root layer soil moisture content in the planting area and the preset control area. It achieves in-situ, non-destructive, and real-time monitoring of the crop growth environment. Based on the first root system image information, first root growth information is acquired, and based on the second root system image information, second root growth information is acquired. Root growth information is obtained through image analysis, directly reflecting the physiological state of the crop affected by salt damage, thus improving the diagnosis of salt damage. Accuracy: Based on the first root growth information and the first root layer soil moisture content, a first comprehensive growth response model is constructed. Furthermore, based on the second root growth information and the second root layer soil moisture content, a second comprehensive growth response model is constructed. This integrates root growth information and root layer soil moisture content to construct comprehensive growth response models corresponding to different regions, eliminating the interference of soil moisture differences on root growth and ensuring the scientific validity and comparability of the model output. Based on the first comprehensive growth response model, the first comprehensive growth parameters of the first crop at the target time are calculated. Based on the second comprehensive growth response model, the second comprehensive growth parameters of the second crop at the target time are calculated. By calculating the comprehensive growth parameters of the tested saline-alkali land planting area and the preset control area at the same time, a dynamic benchmark for salt damage diagnosis is established, solving the misjudgment problem caused by the lack of synchronous controls in traditional methods. Based on the first and second comprehensive growth parameters, the degree of crop salt stress corresponding to the tested saline-alkali land planting area is determined, thus achieving real-time and accurate detection of the degree of salt stress in saline-alkali land crops, providing a reliable basis for timely and accurate intervention in field management measures.

[0070] The in-situ diagnostic system for the degree of salt damage to crops in saline-alkali land provided by the present invention is described below. The in-situ diagnostic system for the degree of salt damage to crops in saline-alkali land described below can be referred to in correspondence with the in-situ diagnostic method for the degree of salt damage to crops in saline-alkali land described above.

[0071] Figure 2 This is a schematic diagram of the in-situ diagnostic system for the degree of salt damage to crops in saline-alkali land provided by the present invention, as shown in the figure. Figure 2As shown in the figure. An embodiment of the present invention provides an in-situ diagnostic system for the degree of salt damage to crops growing in saline-alkali land, comprising a data acquisition module 201, an image analysis module 202, a model construction module 203, a growth calculation module 204, and a salt damage diagnosis module 205, wherein: The data acquisition module 201 is used to acquire the first root system image information and the first root layer soil moisture content of the first crop in the saline-alkali land planting area to be tested at the first preset monitoring point, and to acquire the second root system image information and the second root layer soil moisture content of the second crop in the preset control area at the second preset monitoring point; the number of the first preset monitoring points and the second preset monitoring points is the same, and the number of the points is greater than or equal to 3; the crop types and field management measures corresponding to the first crop and the second crop are the same; the location of the saline soil in the preset control area is greater than or equal to a preset depth; the image analysis module 202 is used to acquire the first root system growth information based on the first root system image information, and to acquire the second root system growth information based on the second root system image information. The model construction module 203 is used to construct a first comprehensive growth response model based on the first root growth information and the first root layer soil moisture content, and to construct a second comprehensive growth response model based on the second root growth information and the second root layer soil moisture content; the growth calculation module 204 is used to calculate the first comprehensive growth parameter of the first crop at the target time based on the first comprehensive growth response model, and to calculate the second comprehensive growth parameter of the second crop at the target time based on the second comprehensive growth response model; the salt damage diagnosis module 205 is used to determine the degree of crop salt stress corresponding to the saline-alkali land planting area to be tested based on the first comprehensive growth parameter and the second comprehensive growth parameter.

[0072] This invention provides an in-situ diagnostic system for the degree of salt damage to crops in saline-alkali land. It acquires first root system images and first root layer soil moisture content of a first crop in a test saline-alkali land planting area at a first preset monitoring point, and second root system images and second root layer soil moisture content of a second crop in a preset control area at a second preset monitoring point. The number of the first and second preset monitoring points is the same, and the number is greater than or equal to three. The crop types and field management practices for the first and second crops are the same. The saline soil in the preset control area is at a depth greater than or equal to a preset depth. This system solves the problems of soil structure damage caused by traditional soil drilling methods and weather interference with remote sensing methods by simultaneously acquiring root system images and root layer soil moisture content in the test saline-alkali land planting area and the preset control area in situ. It achieves in-situ, non-destructive, and real-time monitoring of the crop growth environment. Based on the first root system image information, it acquires first root growth information, and based on the second root system image information, it acquires second root growth information. Through image analysis, it obtains root growth information, directly reflecting the physiological state of the crop affected by salt damage, thus improving the diagnosis of salt damage. Accuracy: Based on the first root growth information and the first root layer soil moisture content, a first comprehensive growth response model is constructed. Furthermore, based on the second root growth information and the second root layer soil moisture content, a second comprehensive growth response model is constructed. This integrates root growth information and root layer soil moisture content to construct comprehensive growth response models corresponding to different regions, eliminating the interference of soil moisture differences on root growth and ensuring the scientific validity and comparability of the model output. Based on the first comprehensive growth response model, the first comprehensive growth parameters of the first crop at the target time are calculated. Based on the second comprehensive growth response model, the second comprehensive growth parameters of the second crop at the target time are calculated. By calculating the comprehensive growth parameters of the tested saline-alkali land planting area and the preset control area at the same time, a dynamic benchmark for salt damage diagnosis is established, solving the misjudgment problem caused by the lack of synchronous controls in traditional methods. Based on the first and second comprehensive growth parameters, the degree of crop salt stress corresponding to the tested saline-alkali land planting area is determined, thus achieving real-time and accurate detection of the degree of salt stress in saline-alkali land crops, providing a reliable basis for timely and accurate intervention in field management measures.

[0073] Figure 3 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 3 As shown, the electronic device may include: a processor 310, a communication interface 320, a memory 330, and a communication bus 340, wherein the processor 310, the communication interface 320, and the memory 330 communicate with each other via the communication bus 340. The processor 310 can call logical instructions in the memory 330 to execute an in-situ diagnostic method for the degree of salt damage to crops growing in saline-alkali land, which includes: At a first preset monitoring point, image information of the first root system and soil moisture content of the first root layer of the first crop in the saline-alkali land planting area to be tested are acquired. At a second preset monitoring point, image information of the second root system and soil moisture content of the second crop in a preset control area are acquired. The number of the first preset monitoring points and the second preset monitoring points are the same, and the number of the points is greater than or equal to three. The crop species and field management measures corresponding to the first crop and the second crop are the same. The location of the saline soil in the preset control area is greater than or equal to a preset depth. Based on the first root system image information, first root system growth information is obtained, and based on the second root system image information, second root system growth information is obtained; Based on the first root growth information and the first root layer soil moisture content, a first comprehensive growth response model is constructed, and based on the second root growth information and the second root layer soil moisture content, a second comprehensive growth response model is constructed. Based on the first comprehensive growth response model, the first comprehensive growth parameter of the first crop at the target time is calculated, and based on the second comprehensive growth response model, the second comprehensive growth parameter of the second crop at the target time is calculated. Based on the first comprehensive growth parameter and the second comprehensive growth parameter, the degree of crop salt stress corresponding to the saline-alkali land planting area to be tested is determined.

[0074] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0075] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to perform the in-situ diagnostic method for the degree of salt damage to crops in saline-alkali land provided by the above methods, the method comprising: At a first preset monitoring point, image information of the first root system and soil moisture content of the first root layer of the first crop in the saline-alkali land planting area to be tested are acquired. At a second preset monitoring point, image information of the second root system and soil moisture content of the second crop in a preset control area are acquired. The number of the first preset monitoring points and the second preset monitoring points are the same, and the number of the points is greater than or equal to three. The crop species and field management measures corresponding to the first crop and the second crop are the same. The location of the saline soil in the preset control area is greater than or equal to a preset depth. Based on the first root system image information, first root system growth information is obtained, and based on the second root system image information, second root system growth information is obtained; Based on the first root growth information and the first root layer soil moisture content, a first comprehensive growth response model is constructed, and based on the second root growth information and the second root layer soil moisture content, a second comprehensive growth response model is constructed. Based on the first comprehensive growth response model, the first comprehensive growth parameter of the first crop at the target time is calculated, and based on the second comprehensive growth response model, the second comprehensive growth parameter of the second crop at the target time is calculated. Based on the first comprehensive growth parameter and the second comprehensive growth parameter, the degree of crop salt stress corresponding to the saline-alkali land planting area to be tested is determined.

[0076] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the in-situ diagnostic method for the degree of salt damage to crops growing in saline-alkali land provided by the methods described above, the method comprising: At a first preset monitoring point, image information of the first root system and soil moisture content of the first root layer of the first crop in the saline-alkali land planting area to be tested are acquired. At a second preset monitoring point, image information of the second root system and soil moisture content of the second crop in a preset control area are acquired. The number of the first preset monitoring points and the second preset monitoring points are the same, and the number of the points is greater than or equal to three. The crop species and field management measures corresponding to the first crop and the second crop are the same. The location of the saline soil in the preset control area is greater than or equal to a preset depth. Based on the first root system image information, first root system growth information is obtained, and based on the second root system image information, second root system growth information is obtained; Based on the first root growth information and the first root layer soil moisture content, a first comprehensive growth response model is constructed, and based on the second root growth information and the second root layer soil moisture content, a second comprehensive growth response model is constructed. Based on the first comprehensive growth response model, the first comprehensive growth parameter of the first crop at the target time is calculated, and based on the second comprehensive growth response model, the second comprehensive growth parameter of the second crop at the target time is calculated. Based on the first comprehensive growth parameter and the second comprehensive growth parameter, the degree of crop salt stress corresponding to the saline-alkali land planting area to be tested is determined.

[0077] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units 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. Those skilled in the art can understand and implement this without any creative effort.

[0078] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for in-situ diagnosis of salt damage to crops growing in saline-alkali land, characterized in that, include: At the first preset monitoring point, the first root system image information and the first root layer soil moisture content of the first crop in the saline-alkali land planting area to be tested are obtained. At the second preset monitoring point, the second root system image information and the second root layer soil moisture content of the second crop in the preset control area are obtained. The number of the first preset monitoring points and the second preset monitoring points is the same, and the number of points is greater than or equal to three; the crop types and field management measures corresponding to the first crop and the second crop are the same; the location of saline soil in the preset control area is greater than or equal to a preset depth; Based on the first root system image information, first root system growth information is obtained, and based on the second root system image information, second root system growth information is obtained; Based on the first root growth information and the first root layer soil moisture content, a first comprehensive growth response model is constructed, and based on the second root growth information and the second root layer soil moisture content, a second comprehensive growth response model is constructed. Based on the first comprehensive growth response model, the first comprehensive growth parameter of the first crop at the target time is calculated, and based on the second comprehensive growth response model, the second comprehensive growth parameter of the second crop at the target time is calculated. Based on the first comprehensive growth parameter and the second comprehensive growth parameter, the degree of crop salt stress corresponding to the saline-alkali land planting area to be tested is determined.

2. The in-situ diagnostic method for the degree of salt damage to crops in saline-alkali land according to claim 1, characterized in that, The construction of a first comprehensive growth response model based on the first root growth information and the first root layer soil moisture content includes: Based on the first root growth information, calculate the current normalized value of each root growth index; Determine the weights of the root growth indicators; Calculate the root system comprehensive growth index based on the current normalized value and the index weight; Based on the fitting relationship between the root system comprehensive growth index and the soil moisture content of the first root layer, the first comprehensive growth response model is constructed.

3. The in-situ diagnostic method for the degree of salt damage to crops in saline-alkali land according to claim 2, characterized in that, The root growth indicators include at least two of the following: root length, root length density, root surface area, and root diameter.

4. The in-situ diagnostic method for the degree of salt damage to crops in saline-alkali land according to claim 2, characterized in that, The determination of the weights of the root growth indicators includes: Multiple sets of historical test data were collected; each set of historical test data included measured values ​​of multiple root growth indicators of different crops planted in soils with different salinity, as well as the true values ​​of the corresponding comprehensive root growth index. The measured values ​​of each root growth index were normalized to obtain the corresponding historical normalized values. Under preset constraints, the historical normalized values ​​and the true values ​​of the root system comprehensive growth index are fitted to obtain the index weight of each root system growth index; the preset constraints are that the weight of each index is greater than or equal to 0, and the sum of the weights of all indices is 1.

5. The in-situ diagnostic method for the degree of salt damage to crops in saline-alkali land according to claim 1, characterized in that, The determination of crop salt stress degree in the tested saline-alkali land planting area based on the first comprehensive growth parameter and the second comprehensive growth parameter includes: The crop salt damage index is calculated based on the first comprehensive growth parameter and the second comprehensive growth parameter. The degree of salt stress on the crop is determined based on the crop salt damage index.

6. The in-situ diagnostic method for the degree of salt damage to crops in saline-alkali land according to claim 5, characterized in that, The degree of crop salt stress includes at least four preset levels: no stress, mild stress, moderate stress, and severe stress.

7. The in-situ diagnostic method for the degree of salt damage to crops in saline-alkali land according to claim 6, characterized in that, The determination of the degree of crop salt stress based on the crop salt damage index includes: When the crop salt damage index is greater than 0 and less than or equal to the first threshold, the crop salt stress level is defined as no stress. When the crop salt damage index is greater than the first threshold and less than or equal to the second threshold, the degree of crop salt stress is the mild stress. When the crop salt damage index is greater than the second threshold and less than or equal to the third threshold, the degree of crop salt stress is the moderate stress. When the crop salt damage index is greater than the third threshold and less than or equal to the fourth threshold, the degree of crop salt stress is defined as severe stress.

8. An in-situ diagnostic system for the degree of salt damage to crops growing in saline-alkali land, characterized in that, include: The data acquisition module is used to acquire the first root system image information and the first root layer soil moisture content of the first crop in the saline-alkali land planting area to be tested at the first preset monitoring point, and to acquire the second root system image information and the second root layer soil moisture content of the second crop in the preset control area at the second preset monitoring point. The number of the first preset monitoring points and the second preset monitoring points is the same, and the number of points is greater than or equal to three; the crop types and field management measures corresponding to the first crop and the second crop are the same; the location of saline soil in the preset control area is greater than or equal to a preset depth; The image analysis module is used to obtain first root growth information based on the first root image information, and to obtain second root growth information based on the second root image information; The model building module is used to build a first comprehensive growth response model based on the first root growth information and the first root layer soil moisture content, and to build a second comprehensive growth response model based on the second root growth information and the second root layer soil moisture content. The growth calculation module is used to calculate the first comprehensive growth parameter of the first crop at the target time based on the first comprehensive growth response model, and to calculate the second comprehensive growth parameter of the second crop at the target time based on the second comprehensive growth response model. The salt damage diagnosis module is used to determine the degree of crop salt stress in the saline-alkali land planting area to be tested based on the first comprehensive growth parameter and the second comprehensive growth parameter.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the in-situ diagnostic method for the degree of salt damage to crops growing in saline-alkali land as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the in-situ diagnostic method for the degree of salt damage to crops growing in saline-alkali land as described in any one of claims 1 to 7.

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