Cotton irrigation optimization method and device and terminal equipment

Abstract

The invention provides a cotton irrigation optimization method and device and terminal equipment, and is suitable for the technical field of irrigation. The method comprises the following steps: acquiring multiple pieces of soil water matrix potential information, planting soil layer relative depth information, rooting depth information, relative root length density distribution information, net photosynthetic rate information, an initial field water holding rate lower limit value and planting day number information; obtaining a cotton water deficit index and an initial cotton water deficit index threshold according to the soil water matrix potential information, the planting soil layer relative depth information, the rooting depth information, the relative root length density distribution information and the net photosynthetic rate information; according to the planting day number information, the initial cotton water deficit index threshold value and the initial field water holdup lower limit value, determining a target cotton water deficit index threshold value and a target field water holdup lower limit value; according to the target lower limit value of the field water holding rate and a preset upper limit value of the field water holding rate, cotton is irrigated, so that the management accuracy of irrigation water is improved.

Description

Technical Field

[0001] The present application belongs to the field of irrigation technology, and in particular to a cotton irrigation optimization method, device and terminal equipment. Background Art

[0002] Water shortage is the main limiting factor for agricultural production, especially restricting the sustainable development of agriculture in arid and semi-arid areas where irrigation is the main source. Precision irrigation system is an important means to optimize the water productivity of farmland, which depends on timely and accurate assessment of plant water status. Those skilled in the art usually use plant water stress or deficit index (PWDI) to quantify the degree of water deficit of plants, so as to guide actual irrigation through the quantified degree of plant water deficit.

[0003] In the prior art, under sufficient irrigation conditions, the total irrigation water consumption is usually reduced by reducing the single irrigation amount or changing the irrigation frequency.

[0004] The existing technology is used to optimize the irrigation system only through the single irrigation amount or irrigation frequency, which is one-sided in terms of optimization. Moreover, the optimization of the irrigation system under the premise of sufficient irrigation can only ensure that the plant's demand for water is met. The accuracy of water management is not high, which easily leads to a waste of irrigation water resources. Summary of the invention

[0005] In view of this, the embodiments of the present application provide a cotton irrigation optimization method, device and terminal equipment, which simulate the irrigation situation through a soil moisture movement simulation model, quantify the degree of water deficit of cotton according to the simulation results, and consider the response of the net photosynthetic rate of cotton to water stress. The lower limit of field water holding rate is accurately calculated to guide the actual irrigation in the cotton planting process, and the cotton irrigation system is optimized under non-sufficient irrigation conditions, ensuring that the water demand for cotton during growth can be met while improving the accuracy of water management and effectively improving the utilization rate of irrigation water resources.

[0006] A first aspect of an embodiment of the present application provides a cotton irrigation optimization method, comprising:

[0007] Acquire multiple soil water matrix potential information, planting soil layer relative depth information, rooting depth information, relative root length density distribution information, net photosynthetic rate information, multiple initial field water holding rate lower limits and planting day information; wherein the soil water matrix potential information corresponds to the initial field water holding rate lower limit;

[0008] Based on a preset soil moisture movement simulation model, multiple cotton water deficit indexes are obtained according to multiple soil water matrix potential information, planting soil layer relative depth information, rooting depth information, and relative root length density distribution information;

[0009] Determining a plurality of initial cotton water deficit index thresholds according to the net photosynthetic rate information and a plurality of cotton water deficit indexes;

[0010] Determining a target cotton water deficit index threshold according to the planting day information and the initial cotton water deficit index threshold;

[0011] According to the cotton water deficit index threshold and the initial field water holding capacity lower limit value, a target field water holding capacity lower limit value is obtained;

[0012] The cotton is irrigated according to the target lower limit of the field water holding capacity and the preset upper limit of the field water holding capacity.

[0013] A second aspect of an embodiment of the present application provides a cotton irrigation optimization device, comprising:

[0014] An information acquisition module, used to obtain multiple soil water matrix potential information, planting soil layer relative depth information, rooting depth information, relative root length density distribution information, net photosynthetic rate information, multiple initial field water holding rate lower limits and planting days information; wherein the soil water matrix potential information corresponds to the initial field water holding rate lower limit;

[0015] A cotton water deficit index calculation module is used to obtain multiple cotton water deficit indexes based on a preset soil water movement simulation model and according to multiple soil water matrix potential information, planting soil layer relative depth information, rooting depth information and relative root length density distribution information;

[0016] An initial cotton water deficit index threshold determination module is used to determine multiple initial cotton water deficit index thresholds according to the net photosynthetic rate information and multiple cotton water deficit indices;

[0017] A target cotton water deficit index threshold determination module, used to determine a target cotton water deficit index threshold according to the planting day information and the initial cotton water deficit index threshold;

[0018] A target field water holding rate lower limit value determination module is used to obtain a target field water holding rate lower limit value according to the target cotton water deficit index threshold and the initial field water holding rate lower limit value;

[0019] The cotton irrigation module is used to irrigate the cotton according to the target lower limit value of the field water holding capacity and the preset upper limit value of the field water holding capacity.

[0020] A third aspect of an embodiment of the present application provides a terminal device, which includes a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, the steps of the cotton irrigation optimization method as described in any one of the first aspects above are implemented.

[0021] A fourth aspect of an embodiment of the present application provides a computer-readable storage medium, comprising: storing a computer program, characterized in that when the computer program is executed by a processor, the steps of the cotton irrigation optimization method as described in any one of the first aspects above are implemented.

[0022] Compared with the prior art, the embodiments of the present application have the following beneficial effects: simulating irrigation scenarios through a soil moisture movement simulation model, quantifying the degree of water deficit of cotton based on the simulation results, and considering the response of the net photosynthetic rate of cotton to water stress, accurately calculating the lower limit of field water holding rate to guide the actual irrigation during cotton planting, and optimizing the cotton irrigation system under non-sufficient irrigation conditions, ensuring that the water demand for cotton during growth can be met, while improving the accuracy of water management and effectively improving the utilization rate of irrigation water resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0024] Figure 1 It is a schematic diagram of the implementation process of the cotton irrigation optimization method provided in the embodiment of the present application;

[0025] Figure 2 It is a schematic diagram of the implementation process of the cotton irrigation optimization method provided in the embodiment of the present application;

[0026] Figure 3 It is a schematic diagram of the implementation process of the cotton irrigation optimization method provided in the embodiment of the present application;

[0027] Figure 4 It is a schematic diagram of the implementation process of the cotton irrigation optimization method provided in the embodiment of the present application;

[0028] Figure 5 It is a schematic diagram of the implementation process of the cotton irrigation optimization method provided in the embodiment of the present application;

[0029] Figure 6 It is a schematic diagram of the implementation process of the cotton irrigation optimization method provided in the embodiment of the present application;

[0030] Figure 7 is a schematic diagram of the structure of a cotton irrigation optimization device provided in an embodiment of the present application;

[0031] Figure 8 It is a schematic diagram of a terminal device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0033] In order to illustrate the technical solution described in this application, a specific embodiment is provided below for illustration.

[0034] Figure 1 The following is a flowchart of the cotton irrigation optimization method provided in Example 1 of the present application, which is described in detail as follows:

[0035] Step S101, obtaining multiple soil water matrix potential information, planting soil layer relative depth information, rooting depth information, relative root length density distribution information, net photosynthetic rate information, multiple initial field water holding rate lower limits and planting day information; wherein the soil water matrix potential information corresponds to the initial field water holding rate lower limit.

[0036] In this embodiment, the soil water matrix potential information refers to the soil water matrix potential, that is, the potential energy caused by the adsorption force and capillary force of the soil matrix, which generally refers to the work done when a unit amount of water is moved from a balanced soil-water system to another system without a soil matrix, or the soil water potential constrained by the adsorption force and capillary force. The planting soil layer depth can be the thickness of the soil covering the cotton root system, that is, the planting soil layer depth that can be used for the growth of the cotton root system, and the planting soil layer relative depth information is the relative depth value relative to the average value of the thickness of the soil covering the cotton root system. The rooting depth information refers to the extension depth of the cotton root system under the planting soil layer, which can be used to quantify the depth of the cotton root system in the soil covering part relative to the ground. The root length density distribution information refers to the length of the root system in a unit volume of soil, which is used to reflect the distribution of the root system in the soil, and the relative root length density distribution information can be the relative cotton root length value relative to the average value of the cotton root length in a unit volume of soil. The net photosynthetic rate information can refer to the rate of organic matter produced by photosynthesis of plants minus the organic matter consumed by respiration, which can be the value of the total photosynthetic rate minus the respiration rate. The above information can be measured by manual experiments or measured by sensors and then manually input into a computer for subsequent calculation and analysis.

[0037] In this embodiment, the initial field water holding rate lower limit value and planting days information can be manually set. Field water holding rate refers to the moisture content that the soil can maintain. The initial field water holding rate lower limit value can be 50%, 55%, 60%, 65% and 70%, which is used to subsequently screen out the target field water holding rate lower limit value from multiple initial field water holding rate lower limits to guide the actual irrigation work of cotton planting. The planting days information is used to indicate the planting days of cotton, usually starting from the sowing time, such as 45 days, 52 days, 59 days, 66 days, 73 days, 80 days, 87 days, 94 days, 101 days, 108 days, 115 days, 122 days.

[0038] Step S102, based on a preset soil moisture movement simulation model, multiple cotton moisture deficit indexes are obtained according to multiple soil water matrix potential information, planting soil layer relative depth information, rooting depth information and relative root length density distribution information.

[0039] In this embodiment, the preset soil moisture movement simulation model can be a HYDRUS model, which is used to simulate the soil moisture movement of cotton drip irrigation under film based on the Richards equation and the root water absorption equation. The cotton water deficit index can be represented by PWDI, which is a dimensionless coefficient used to quantify the degree of water deficit and is defined as the ratio of water deficit to water demand.

[0040] In this embodiment, the estimation of PWDI based on root-weighted soil moisture availability can be described as:

[0041]

[0042] Where, h is soil water matrix potential (cm); z r is the relative depth of the planting soil layer, z r = z L r -1 , z is the soil layer depth (cm); L r is the maximum rooting depth (cm), that is, the rooting depth information; L nrd is the relative root length density distribution; γ(h) is the soil water stress correction coefficient, which can be obtained by simulating the soil water movement of cotton drip irrigation under film based on the Richards equation and the root water absorption equation through the HYDRUS model. nrd It can be described by the following normalized function:

[0043] L nrd (Z r )=a(1-z r ) a-1

[0044] Where a is the relative root length density on the ground surface. For cotton, a = 1.96.

[0045] Step S103: determining a plurality of initial cotton water deficit index thresholds according to the net photosynthetic rate information and a plurality of cotton water deficit indexes.

[0046] In this embodiment, multiple net photosynthetic rate information and multiple cotton water deficit indices can be one-to-one corresponding. By setting one or more net photosynthetic rate thresholds, the cotton water deficit index corresponding to the net photosynthetic rate can be used as the initial cotton water deficit index threshold for subsequent determination of the cotton irrigation optimization plan.

[0047] Step S104, determining a target cotton water deficit index threshold value according to the planting day information and the initial cotton water deficit index threshold value.

[0048] In this embodiment, each day in the planting process corresponds to a cotton water deficit index, so each initial cotton water deficit index threshold also corresponds to a planting date. The planting dates corresponding to multiple initial cotton water deficit index thresholds may be first counted, and the initial cotton water deficit index threshold with the most planting days is used as the target cotton water deficit index threshold, which is used for the subsequent determination of the lower limit of the target field water holding rate, thereby determining the cotton irrigation optimization plan.

[0049] Step S105, obtaining a target field water holding capacity lower limit value according to the target cotton water deficit index threshold and the initial field water holding capacity lower limit value.

[0050] In this embodiment, the initial field water holding capacity lower limit value of the planting days corresponding to the target cotton water deficit index threshold value may be used as the target field water holding capacity lower limit value for subsequent determination of the cotton irrigation optimization plan.

[0051] Step S106, irrigating the cotton according to the target lower limit of the field water holding capacity and the preset upper limit of the field water holding capacity.

[0052] In this embodiment, it is understood that the lower limit of the target field water holding rate means that when the field water holding rate is lower than this value, the cotton needs to be irrigated. The upper limit of the field water holding rate means that when the field water holding rate is reached, the cotton needs to be stopped from being irrigated. The single quota irrigation amount can be calculated by the lower limit of the target field water holding rate. For example, when the lower limit of the target field water holding rate is 50%, the irrigation amount for cotton in the bud stage is 25.64 mm, and the irrigation amount for cotton in the flowering and boll stage is 45.47 mm; when the lower limit of the target field water holding rate is 60%, the irrigation amount for cotton in the bud stage is 18.32 mm, and the irrigation amount for cotton in the flowering and boll stage is 34.11 mm. The preset upper limit of the field water holding rate can be: 85% for the bud stage and 90% for the flowering and boll stage. It is understandable that a higher lower limit of irrigation means more frequent irrigation, which is also beneficial to reduce the impact of water stress during the flowering and boll stage of cotton.

[0053] The cotton irrigation optimization method provided in the embodiment of the present application simulates the irrigation situation through a soil moisture movement simulation model, quantifies the degree of water deficit of the cotton according to the simulation results, and simultaneously considers the response of the net photosynthetic rate of the cotton to water stress, accurately calculates the lower limit of the field water holding rate to guide the actual irrigation during the cotton planting process, and optimizes the cotton irrigation system under insufficient irrigation conditions, ensuring that the water demand for cotton during growth can be met while improving the accuracy of water management and effectively improving the utilization rate of irrigation water resources.

[0054] Figure 2 The flowchart of the cotton irrigation optimization method provided in the second embodiment of the present application is shown. The difference between the second embodiment and the first embodiment is that the step S102 specifically includes:

[0055] Step S201, based on a preset soil water movement simulation model and according to the actual value of the soil water matrix potential, a nonlinear least squares fitting calculation is performed to obtain a soil water stress correction coefficient variation curve.

[0056] In the present embodiment, the soil hydraulic parameters can be optimized by using the inverse solution option of the HYDRUS model, and the objective function is minimized in the inverse solution process by using the Levenberg-Marquardt nonlinear minimization method to realize the nonlinear least squares fitting calculation, thereby using the simulation means of soil moisture by HYDRUS and the analysis of cotton stress conditions based on the PWDI threshold. Among them, the soil hydraulic parameter used for optimizing the calculation can be the soil water matrix potential, or it can be the soil moisture content obtained by actual measurement or simulation, and then converted into soil moisture content by the soil moisture content. The soil water stress correction coefficient variation curve obtained in the present embodiment can be a vertical coordinate for the soil water stress correction coefficient, and abscissa for the soil water matrix potential.

[0057] Step S202: obtaining coefficient variation fitting parameters according to the soil water stress correction coefficient variation curve.

[0058] In this embodiment, the soil water stress correction coefficient change curve can be a vertical coordinate of the soil water stress correction coefficient, and the horizontal coordinate is the soil water matrix potential. The nonlinear least squares method can be used to optimize the parameters to obtain the fitting parameters of the image curve, and the fitting parameters, that is, the coefficient change fitting parameters, can be represented by ρ. The nonlinear least squares method can be used to optimize the parameters ρ = 0.12, and the corresponding soil water stress correction coefficient γ (h) is a concave function.

[0059] Step S203, determining whether the actual value of the soil water matrix potential is greater than the wilting coefficient, if so, proceeding to step S204; if not, the root weighted water deficit index is 0.

[0060] In this embodiment, the wilting coefficient refers to the soil moisture content when the leaves of crops growing on moist soil wilt after a long period of drought because the water absorption is insufficient to compensate for the transpiration consumption. γ(h) is the soil moisture stress correction coefficient, which is described by a commonly used nonlinear function as follows:

[0061]

[0062] Among them, h H 、h L and h W are the upper limit, lower limit and wilting coefficient of soil water matrix potential suitable for crop growth, respectively, and h is soil water matrix potential. In this embodiment, the measured or simulated soil moisture content can be converted into soil water matrix potential according to the soil moisture characteristic curve. The selected parameters can be h H =-50,h L =-400,h W=-15000cm. ρ is a fitting parameter, and its value range is 0<ρ<10. When 0<ρ<1, γ(h) is a concave function; when ρ=1, γ(h) is a linear function; when 1<ρ<10, γ(h) is a convex function. When the actual value of soil water matrix potential is less than or equal to the wilting coefficient, γ(h)=0, h≤h W .

[0063] Step S204, determining whether the actual value of the soil water matrix potential is less than the lower limit value of the soil water matrix potential, if so, proceeding to step S205; if not, the root weighted water deficit index is 1.

[0064] In this embodiment, γ(h)=1, h L <h≤h H .

[0065] Step S205, calculating the root weighted water deficit index according to the coefficient change fitting parameter, the upper limit value of the soil water matrix potential, the lower limit value of the soil water matrix potential, the wilting coefficient and the actual value of the soil water matrix potential.

[0066] In this embodiment, when the actual value of the soil water matrix potential is greater than the wilting coefficient and less than the lower limit of the soil water matrix potential,

[0067] Step S206, performing error verification on the root weighted water deficit index to obtain the cotton water deficit index.

[0068] In this embodiment, the root weighted water deficit index obtained by the above calculation can be compared with the root weighted water deficit index obtained by other calculations or simulation methods to perform error calculation to verify whether the above calculation result is credible. The error verification method can be to calculate the mean absolute error, or to calculate the mean square error, or to calculate the root mean square difference, or to calculate the mean absolute percentage error. When the calculated error is less than the preset error threshold, it indicates that the above calculation result for the root weighted water deficit index is reliable and can be used for the subsequent determination of the irrigation plan.

[0069] The cotton irrigation optimization method provided in the embodiment of the present application fits the soil moisture stress correction coefficient change curve through a preset soil moisture movement simulation model, calculates the soil moisture stress correction coefficient through the fitting parameters, verifies the credibility of the HYDRUS model in simulating the soil moisture content changes at different irrigation lower limits through the error calculation results, and is used to evaluate the accuracy and usability of PWDI calculated based on root-weighted soil moisture in guiding cotton sub-film drip irrigation, so as to facilitate the subsequent determination of the cotton irrigation optimization plan.

[0070] Figure 3The flowchart of the cotton irrigation optimization method provided in the third embodiment of the present application is shown. The difference between the third embodiment and the second embodiment is that the step S206 specifically includes:

[0071] Step S301, obtaining the actual transpiration rate of cotton, the potential transpiration rate per unit effective leaf area, and the leaf area index.

[0072] In this embodiment, the actual transpiration rate of cotton refers to the amount of water transpired per unit leaf area of ​​cotton within a certain period of time, which is generally expressed in grams of water transpired per square meter of leaf area per hour (g·m-2·h-1), and can be obtained by calculating the cotton liquid flow measured by the heat ratio method (HRM) using a stem flow meter. The stem flow meter can be installed in the first internode of cotton from the bud stage to the boll stage, and data can be recorded every 30 minutes. The stem flow rate in the plant is determined by measuring the temperature ratio caused by the upward and downward movement of stem liquid. Unit effective leaf area refers to the leaf area of ​​cotton that can actively use light energy for photosynthesis. The potential transpiration rate per unit effective leaf area refers to the actual transpiration rate per unit effective leaf area under various water treatments, which is approximately equal to the actual transpiration rate per unit effective leaf area under sufficient irrigation conditions. The leaf area index refers to the multiple of the total area of ​​plant leaves per unit land area. The above specific values ​​can all be obtained by experimental measurement and calculation.

[0073] Step S302: Calculate the effective leaf area index according to the leaf area index.

[0074] In this embodiment, LAI a is the effective leaf area index (cm 2 cm -2 ), can be calculated by the following formula:

[0075]

[0076] Where LAI is the leaf area index (cm 2 cm -2 ).

[0077] Step S303, calculating the potential transpiration rate according to the potential transpiration rate per unit effective leaf area and the effective leaf area index.

[0078] In this example, the potential transpiration rate is calculated by the following formula:

[0079] T p =T pa ×LAI a

[0080] Among them, T pa is the potential transpiration rate per unit effective leaf area (mm d -1), assuming that it is equal under various water treatments, approximates the actual transpiration rate per unit effective leaf area under full irrigation conditions; LAI a is the effective leaf area index (cm 2 cm -2 ), can be calculated by the following formula (Jin et al., 2016):

[0081]

[0082] Where LAI is the leaf area index (cm 2 cm -2 .

[0083] Step S304: Calculate an estimated value of cotton water deficit according to the actual transpiration rate and potential transpiration rate of the cotton.

[0084] In this embodiment, the transpiration rate of cotton at the bud stage can be obtained by the water balance method.

[0085] The actual transpiration rate of cotton is calculated as follows:

[0086] T r =V h ×SA×24

[0087] Where Tr represents the actual transpiration rate of cotton (mm d -1 plant -1 ), V h is the plant flow velocity (cm hr -1 ), SA is the area through which the liquid flows (cm 2 ), where V h The calculation formula is as follows:

[0088]

[0089] Where k is the thermal diffusivity of the plant, which is set to 0.0025 cm in this study. 2 s -1 , x is the distance between the heating needle and any probe, fixed at 0.5 cm, and v1 and v2 are the temperatures of the paired thermistors.

[0090] SA is calculated as follows:

[0091] SA=3.14×(D / 2) 2

[0092] Where D is the cotton stem diameter (cm), measured at the first internode of the cotton.

[0093] Calculate the actual transpiration of plants (Ta, mm) according to the water balance equation:

[0094] T a =I+PERD-ΔW

[0095] Where I is the irrigation amount (mm); P is the precipitation (mm), which is zero when there is a canopy; E is the soil evaporation (mm), and the soil evaporation under the film was obtained by a homemade small evaporation dish; R is the surface runoff (mm), which was ignored in this study due to effective water management; D is the deep drainage at the lower boundary (mm), and this study was insufficiently irrigated, so there was no deep drainage and D was zero; ΔW is the change in water stored in the soil profile from the surface to the lower boundary, which was estimated by measuring the soil moisture content.

[0096] The root-weighted soil water availability estimation PWDI can be described as:

[0097] Among them, T a is the actual transpiration of the plant (mm); T p is the potential transpiration of the plant (mm).

[0098] Step S305, calculating the root mean square error and mean absolute error percentage of the cotton water deficit estimation value and the root weighted water deficit index.

[0099] In this embodiment, the simulated values ​​based on the HYDRUS model and the measured results are in the range of 0.97-0.99, the RMSE range is 0.01-0.03 cm3 cm-3, and the MAPE range is 4.78%-7.74%, indicating that the HYDRUS model can better simulate the changes in soil moisture content at different irrigation limits.

[0100] Step S306, determining whether the root mean square error is less than a preset root mean square error threshold, if so, proceeding to step S307; if not, taking the cotton moisture deficit estimate as the cotton moisture deficit index.

[0101] In this embodiment, when the root mean square error is less than the preset root mean square error threshold and the mean absolute error percentage is less than the preset mean absolute error percentage threshold, it indicates that the calculated PWDI has a high credibility and can be used for the subsequent determination of the cotton irrigation plan.

[0102] Step S307, determining whether the mean absolute error percentage is less than a preset mean absolute error percentage threshold, if so, taking the root weighted water deficit index as the cotton water deficit index; if not, taking the cotton water deficit estimate as the cotton water deficit index.

[0103] In this embodiment, when the root mean square error is greater than the preset root mean square error threshold, or the mean absolute error percentage is greater than the preset mean absolute error percentage threshold, it indicates that the calculated PWDI does not have a high degree of credibility and cannot be used for subsequent determination of the cotton irrigation plan. The cotton water deficit estimate is used as the cotton water deficit index for subsequent analysis to provide irrigation guidance for cotton.

[0104] The cotton irrigation optimization method provided in the embodiment of the present application calculates the estimated value of cotton water deficit through the actual transpiration rate of cotton, the potential transpiration rate per unit effective leaf area and the leaf area index, which is used to perform error verification on the root weighted water deficit index to evaluate the accuracy and usability of PWDI calculated based on root weighted soil moisture in guiding cotton sub-film drip irrigation, so as to facilitate the subsequent determination of the cotton irrigation optimization plan, thereby ensuring the accuracy and reliability of the cotton irrigation optimization plan.

[0105] Figure 4 The flowchart of the cotton irrigation optimization method provided in the fourth embodiment of the present application is shown. The difference between the fourth embodiment and the first embodiment is that the step S103 specifically includes:

[0106] Step S401, obtaining the response law of net photosynthetic rate information to cotton water deficit index.

[0107] In this embodiment, the response law of the net photosynthetic rate information to the cotton water deficit index can be determined by experiments on the existing cotton planted, and then the staff will input the measured and calculated data of the net photosynthetic rate and the cotton water deficit index into a computer. Subsequently, it can be visualized in the form of a two-dimensional image with the horizontal axis being PWDI and the vertical axis being the net photosynthetic rate, which is used for the subsequent determination of the PWDI threshold.

[0108] Step S402, according to the response law of the net photosynthetic rate information to the cotton water deficit index, the cotton water deficit index is used as the abscissa and the net photosynthetic rate information is used as the ordinate to generate a water deficit response curve graph.

[0109] In this embodiment, the response law of the net photosynthetic rate information to the cotton water deficit index is visualized in the form of a two-dimensional image with the abscissa being PWDI and the ordinate being the net photosynthetic rate, thereby obtaining a water deficit response curve diagram.

[0110] Step S403, determining the abscissa corresponding to the extreme point of the water deficit response curve diagram, and obtaining the cotton water deficit numerical base point.

[0111] In this embodiment, the extreme point of the water deficit response curve is used to represent the highest value of the net photosynthetic rate, and the corresponding horizontal axis at this time is used as the cotton water deficit numerical base point, which is used to represent that the subsequent adjustment of the range and value of the cotton water deficit numerical value is changed based on the cotton water deficit numerical base point. It can be understood that according to different growth stages of cotton, the cotton water deficit numerical base point can be the cotton water deficit numerical base point in the bud stage, or the cotton water deficit numerical base point in the flower and boll stage.

[0112] Step S404, determining the ordinate corresponding to the extreme point of the water deficit response curve diagram to obtain the base point of the net photosynthetic rate.

[0113] In this embodiment, the extreme point of the water deficit response curve is used to represent the highest value of the net photosynthetic rate, and this vertical coordinate is used as the net photosynthetic rate base point to characterize the subsequent adjustment of the range and value of the water deficit of cotton in the bud stage based on the net photosynthetic rate base point.

[0114] Step S405, calculating a plurality of net photosynthetic rate change values ​​according to the net photosynthetic rate base point and a plurality of preset net photosynthetic rate change range values.

[0115] In this embodiment, in the water deficit response curve diagram, when the net photosynthetic rate base point is adjusted based on multiple preset net photosynthetic rate change range values, the corresponding horizontal axis is adjusted accordingly, and the adjusted horizontal axis change amount, that is, the net photosynthetic rate change value, is used for the subsequent determination of the PWDI threshold to determine the cotton irrigation amount for adjustment.

[0116] Step S406, based on the water deficit response curve, using the multiple net photosynthetic rate change values ​​as ordinates, determining corresponding abscissas, and obtaining multiple initial cotton water deficit index thresholds.

[0117] In this embodiment, the net photosynthetic rate base point and the net photosynthetic rate change value can be added or subtracted, and the abscissa corresponding to the calculated point is the initial cotton water deficit index threshold. It can be understood that when the PWDI changes, but the change in the net photosynthetic rate is not significant, it means that the irrigation amount can be adjusted to meet the value after the PWDI changes, and the photosynthesis of the cotton will not change significantly due to the change in the irrigation amount.

[0118] The cotton irrigation optimization method provided in the embodiment of the present application quantifies the adjustable range of the cotton water deficit index through the net photosynthetic rate, thereby guiding the adjustment of the irrigation amount during the actual irrigation process to ensure that the normal photosynthesis of the cotton is not affected after the irrigation amount changes. It is used to optimize the irrigation plan while ensuring the normal growth of the cotton after the irrigation amount changes, thereby improving the accuracy of irrigation water resource management and effectively improving the utilization rate of irrigation water resources.

[0119] Figure 5 The flowchart of the cotton irrigation optimization method provided in the fifth embodiment of the present application is shown. The difference between the fifth embodiment and the first embodiment is that the step S104 specifically includes:

[0120] Step S501: according to the planting day information, counting the cotton planting days corresponding to all the initial cotton water deficit index thresholds.

[0121] In this embodiment, the cotton planting days corresponding to all initial cotton water deficit index thresholds may be added to obtain the number of days each initial cotton water deficit index threshold appears during the cotton planting process, which is used for subsequent determination of the irrigation optimization plan.

[0122] Step S502, extracting the maximum value of the cotton planting days to obtain the cotton water stress days.

[0123] In this embodiment, the maximum value of the cotton planting days can be determined to determine the initial cotton water deficit index threshold that occurs the most days during the cotton planting process, indicating that the initial cotton water deficit index threshold is most suitable for cotton growth after the irrigation plan is adjusted.

[0124] Step S503, determining the initial cotton water deficit index threshold corresponding to the cotton water stress days as the target cotton water deficit index threshold.

[0125] In this embodiment, the initial cotton water deficit index threshold corresponding to the cotton water stress days is determined as the target cotton water deficit index threshold, which is used to optimize the irrigation amount of cotton.

[0126] The cotton irrigation optimization method provided in the embodiment of the present application determines the cotton water deficit index threshold value that occurs the most number of days during the cotton planting process, and is used to subsequently convert the irrigation amount through the cotton water deficit index threshold value, thereby guiding the irrigation work in the actual cotton planting process, and optimizing the cotton irrigation system under non-sufficient irrigation conditions, ensuring that the water demand for cotton during growth can be met, while improving the accuracy of water management and effectively improving the utilization rate of irrigation water resources.

[0127] The cotton irrigation optimization method provided in another embodiment of the present application is different from the above-mentioned embodiment 1 in that: the step S105 specifically includes:

[0128] Step S1051, according to the target cotton water deficit index threshold, determine the initial field water holding capacity lower limit value corresponding to the target cotton water deficit index threshold value, and obtain the target field water holding capacity lower limit value.

[0129] In this embodiment, the single quota irrigation amount can be calculated by the lower limit of the target field water holding rate. For example, when the lower limit of the target field water holding rate is 50%, the irrigation amount for cotton in the bud stage is 25.64 mm, and the irrigation amount for cotton in the flowering and boll stage is 45.47 mm; when the lower limit of the target field water holding rate is 60%, the irrigation amount for cotton in the bud stage is 18.32 mm, and the irrigation amount for cotton in the flowering and boll stage is 34.11 mm. The preset upper limit of the field water holding rate can be: 85% for the bud stage and 90% for the flowering and boll stage.

[0130] The cotton irrigation optimization method provided in the embodiment of the present application converts the irrigation amount through the cotton water deficit index threshold to guide the irrigation work in the actual cotton planting process, optimize the cotton irrigation system under insufficient irrigation conditions, effectively improve the accuracy of water management, and thus improve the utilization rate of irrigation water resources.

[0131] Figure 6 The flowchart of the cotton irrigation optimization method provided in the sixth embodiment of the present application is shown. The difference between the sixth embodiment and the first embodiment is that after the step S106, the method further includes:

[0132] Step S601, obtaining cotton growth stage information and actual irrigation amount information at each cotton growth stage.

[0133] In this embodiment, the cotton growth stage information may include the bud stage, the boll stage and the seedling stage. The irrigation amount of each growth stage after irrigation is statistically summed to obtain the actual irrigation amount information of each cotton growth stage, which is used to provide reference data for the subsequent quota irrigation of cotton.

[0134] Step S602, according to the actual irrigation amount information of each cotton growth stage, the total irrigation amount of cotton planting in each cotton growth stage is obtained to perform quota irrigation on the cotton.

[0135] In this embodiment, the quota irrigation amount for cotton is set according to the total irrigation amount of cotton planting in each cotton growth stage, so as to achieve the purpose of water saving during the irrigation process.

[0136] In this embodiment, when the irrigation quota target is set to no more than 420 mm, the irrigation plans that meet the requirements are: the field water holding rate in the bud stage is 50%, and the field water holding rate in the flowering and boll stage is 50%; the field water holding rate in the bud stage is 55%, and the field water holding rate in the flowering and boll stage is 50%; the field water holding rate in the bud stage is 60%, and the field water holding rate in the flowering and boll stage is 50%; the field water holding rate in the bud stage is 65%, and the field water holding rate in the flowering and boll stage is 50%; the field water holding rate in the bud stage is 70%, and the field water holding rate in the flowering and boll stage is 50%; the field water holding rate in the bud stage is 50%, and the field water holding rate in the flowering and boll stage is 55%. Among them, the cumulative number of days with PWDI < 0.48 in the bud stage and PWDI < 0.52 in the flowering and boll stage is the largest, which is 60 days. The corresponding lower limits of irrigation in the bud stage and the flowering and boll stage are 70% and 50% respectively. When the irrigation quota target is set to no more than 450mm, the irrigation schemes that meet the requirements are: field water holding rate of 50% in the bud stage and 50% in the flowering and boll stage; field water holding rate of 55% in the bud stage and 50% in the flowering and boll stage; field water holding rate of 60% in the bud stage and 50% in the flowering and boll stage; field water holding rate of 65% in the bud stage and 50% in the flowering and boll stage; field water holding rate of 70% in the bud stage and 50% in the flowering and boll stage; field water holding rate of 50% in the bud stage and 50% in the flowering and boll stage. 55%; the field water holding rate in the bud stage is 55%, and the field water holding rate in the flowering and boll stage is 55%; the field water holding rate in the bud stage is 60%, and the field water holding rate in the flowering and boll stage is 55%; the field water holding rate in the bud stage is 65%, and the field water holding rate in the flowering and boll stage is 55%. Among them, under the scheme with the field water holding rate of 65% in the bud stage and 55% in the flowering and boll stage, the total number of days with PWDI <0.48 in the bud stage and <0.52 in the flowering and boll stage is the largest, 67 days. Correspondingly, the lower limit of irrigation in the bud stage of cotton is 65% field water holding rate, and the lower limit of irrigation in the flowering and boll stage is 55% field water holding rate. The maximum irrigation plans under the irrigation quota limits of 420mm, 450mm and 480mm are respectively: the field water holding rate of 70% in the bud stage and 50% in the flowering and boll stage; the field water holding rate of 65% in the bud stage and 55% in the flowering and boll stage; the field water holding rate of 70% in the bud stage and 55% in the flowering and boll stage.

[0137] The cotton irrigation optimization method provided in the embodiment of the present application calculates the quota irrigation amount and accurately calculates the lower limit of the field water holding rate to guide the actual irrigation in the cotton planting process, thereby optimizing the cotton irrigation system under non-sufficient irrigation conditions, ensuring that the water demand in the cotton growth process can be met while improving the accuracy of water management and effectively improving the utilization rate of irrigation water resources.

[0138] Corresponding to the method of the above embodiment, Figure 7A structural block diagram of a cotton irrigation optimization device provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown. Figure 7 The exemplified cotton irrigation optimization device may be an execution body of the cotton irrigation optimization method provided in the aforementioned first embodiment.

[0139] Reference Figure 7 , the cotton irrigation optimization device comprises:

[0140] The information acquisition module 710 is used to obtain a plurality of soil water matrix potential information, relative depth information of planting soil layer, rooting depth information, relative root length density distribution information, net photosynthetic rate information, a plurality of initial field water holding rate lower limits and planting days information; wherein the soil water matrix potential information corresponds to the initial field water holding rate lower limit;

[0141] The cotton water deficit index calculation module 720 is used to obtain multiple cotton water deficit indexes based on a preset soil water movement simulation model and according to the multiple soil water matrix potential information, planting soil layer relative depth information, rooting depth information and relative root length density distribution information;

[0142] An initial cotton water deficit index threshold determination module 730 is used to determine a plurality of initial cotton water deficit index thresholds according to the net photosynthetic rate information and a plurality of cotton water deficit indices;

[0143] The target cotton water deficit index threshold determination module 740 is used to determine the target cotton water deficit index threshold according to the planting day information and the initial cotton water deficit index threshold;

[0144] A target field water holding capacity lower limit value determination module 750 is used to obtain a target field water holding capacity lower limit value according to the target cotton water deficit index threshold and the initial field water holding capacity lower limit value;

[0145] The cotton irrigation module 760 is used to irrigate the cotton according to the target lower limit value of the field water holding capacity and the preset upper limit value of the field water holding capacity.

[0146] The process of each module realizing its own function in the cotton irrigation optimization device provided in the embodiment of the present application can be specifically referred to the aforementioned Figure 1 The description of the first embodiment is not repeated here.

[0147] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0148] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0149] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0150] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0151] In addition, in the description of the present specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish descriptions, and cannot be understood as indicating or suggesting relative importance. It should also be understood that although the terms "first", "second", etc. are used to describe various elements in some embodiments of the present application in the text, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, the first table can be named as the second table, and similarly, the second table can be named as the first table without departing from the scope of the various described embodiments. The first table and the second table are both tables, but they are not the same table.

[0152] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0153] The cotton irrigation optimization method provided in the embodiment of the present application can be applied to terminal devices such as mobile phones, tablet computers, wearable devices, vehicle-mounted devices, augmented reality (AR) / virtual reality (VR) devices, laptop computers, ultra-mobile personal computers (UMPC), netbooks, personal digital assistants (PDA), etc. The embodiment of the present application does not impose any restrictions on the specific type of the terminal device.

[0154] For example, the terminal device can be a station (STAION, ST) in a WLAN, a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA) device, a handheld device with wireless communication function, a computing device or other processing device connected to a wireless modem, a vehicle-mounted device, a vehicle networking terminal, a computer, a laptop computer, a handheld communication device, a handheld computing device, a satellite wireless device, a wireless modem card, a TV set top box (STB), a customer premises equipment (CPE) and / or other devices for communicating on a wireless system and a next-generation communication system, such as a mobile terminal in a 5G network or a mobile terminal in a future evolved Public Land Mobile Network (PLMN) network, etc.

[0155] As an example but not limitation, when the terminal device is a wearable device, the wearable device can also be a general term for wearable devices that are intelligently designed and developed using wearable technology for daily wear, such as glasses, gloves, watches, clothing and shoes. A wearable device is a portable device that is worn directly on the body or integrated into the user's clothes or accessories. Wearable devices are not just hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable smart devices include those that are fully functional, large in size, and can achieve complete or partial functions without relying on smartphones, such as smart watches or smart glasses, as well as those that only focus on a certain type of application function and need to be used in conjunction with other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

[0156] Figure 8Schematic diagram of the structure of a terminal device provided by an embodiment of the present application. Figure 8 As shown, the terminal device of this embodiment includes: at least one processor 800 ( Figure 8 Only one is shown in the figure), a memory 810, wherein the memory 810 stores a computer program 820 that can be run on the processor 800. When the processor 800 executes the computer program 820, the steps in the above-mentioned cotton irrigation optimization method embodiments are implemented, for example Figure 1 Alternatively, when the processor 800 executes the computer program 820, the functions of each module / unit in the above-mentioned device embodiments are implemented, for example Figure 7 Functions of modules 710 to 760 are shown.

[0157] The terminal device may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The terminal device may include, but is not limited to, a processor 800 and a memory 810. Those skilled in the art will appreciate that Figure 8 It is only an example of a terminal device and does not constitute a limitation of the terminal device. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal device may also include an input sending device, a network access device, a bus, etc.

[0158] The processor 800 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0159] In some embodiments, the memory 810 may be an internal storage unit of the terminal device, such as a hard disk or memory of the terminal device. The memory 810 may also be an external storage device of the terminal device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the terminal device. Further, the memory 810 may also include both an internal storage unit of the terminal device and an external storage device. The memory 810 is used to store an operating system, an application program, a boot loader (BootLoader), data and other programs, such as the program code of the computer program, etc. The memory 810 may also be used to temporarily store data that has been sent or is to be sent.

[0160] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0161] An embodiment of the present application also provides a terminal device, which includes at least one memory, at least one processor, and a computer program stored in the at least one memory and executable on the at least one processor, wherein when the processor executes the computer program, the terminal device implements the steps in any of the above-mentioned method embodiments.

[0162] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0163] An embodiment of the present application provides a computer program product. When the computer program product runs on a terminal device, the terminal device can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0164] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0165] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0166] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0167] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0168] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A cotton irrigation optimization method, characterized in that: include: Acquire multiple soil water matrix potential information, planting soil layer relative depth information, rooting depth information, relative root length density distribution information, net photosynthetic rate information, multiple initial field water holding rate lower limits and planting day information; wherein the soil water matrix potential information corresponds to the initial field water holding rate lower limit; Based on a preset soil moisture movement simulation model, multiple cotton water deficit indexes are obtained according to multiple soil water matrix potential information, planting soil layer relative depth information, rooting depth information, and relative root length density distribution information; Determining a plurality of initial cotton water deficit index thresholds according to the net photosynthetic rate information and a plurality of cotton water deficit indexes; Determining a target cotton water deficit index threshold according to the planting day information and the initial cotton water deficit index threshold; According to the cotton water deficit index threshold and the initial field water holding capacity lower limit value, a target field water holding capacity lower limit value is obtained; The cotton is irrigated according to the target lower limit of the field water holding capacity and the preset upper limit of the field water holding capacity.

2. The cotton irrigation optimization method according to claim 1, characterized in that: The soil water matrix potential information includes the soil water matrix potential upper limit value, the soil water matrix potential lower limit value, the wilting coefficient and the actual value of the soil water matrix potential; The step of obtaining a plurality of cotton water deficit indexes based on a preset soil water movement simulation model according to a plurality of soil water matrix potential information, planting soil layer relative depth information, rooting depth information and relative root length density distribution information specifically includes: Based on the preset soil moisture movement simulation model, according to the actual value of the soil water matrix potential, a nonlinear least squares fitting calculation is performed to obtain a soil moisture stress correction coefficient change curve; According to the soil water stress correction coefficient change curve, a coefficient change fitting parameter is obtained; When the actual value of the soil water matrix potential is greater than the wilting coefficient, and the actual value of the soil water matrix potential is less than the lower limit of the soil water matrix potential, the root weighted water deficit index is calculated according to the coefficient change fitting parameter, the upper limit of the soil water matrix potential, the lower limit of the soil water matrix potential, the wilting coefficient and the actual value of the soil water matrix potential; The root weighted water deficit index is error verified to obtain the cotton water deficit index.

3. The cotton irrigation optimization method according to claim 2, characterized in that: The step of performing error verification on the root weighted water deficit index to obtain the cotton water deficit index specifically includes: Obtain the actual transpiration rate of cotton, the potential transpiration rate per unit effective leaf area, and the leaf area index; According to the leaf area index, calculating the effective leaf area index; Calculating the potential transpiration rate according to the potential transpiration rate per unit effective leaf area and the effective leaf area index; Calculating an estimated value of cotton water deficit based on the actual transpiration rate and potential transpiration rate of the cotton; Calculating the root mean square error and mean absolute error percentage of the cotton water deficit estimate and the root weighted water deficit index; When the root mean square error is less than a preset root mean square error threshold, or the mean absolute error percentage is less than a preset mean absolute error percentage threshold, the root weighted water deficit index is used as the cotton water deficit index.

4. The cotton irrigation optimization method according to claim 1, characterized in that: The step of determining a plurality of initial cotton water deficit index thresholds according to the net photosynthetic rate information and a plurality of cotton water deficit indexes specifically comprises: Obtain the response law of net photosynthetic rate information to cotton water deficit index; According to the response law of the net photosynthetic rate information to the cotton water deficit index, the cotton water deficit index is used as the abscissa and the net photosynthetic rate information is used as the ordinate to generate a water deficit response curve graph; Determine the abscissa corresponding to the extreme point of the water deficit response curve diagram to obtain the numerical base point of cotton water deficit; Determine the ordinate corresponding to the extreme point of the water deficit response curve and obtain the base point of the net photosynthetic rate; Calculating a plurality of net photosynthetic rate change values ​​according to the net photosynthetic rate base point and a plurality of preset net photosynthetic rate change range values; Based on the water deficit response curve, the corresponding horizontal coordinates are determined with the multiple net photosynthetic rate change values ​​as vertical coordinates to obtain multiple initial cotton water deficit index thresholds.

5. The cotton irrigation optimization method according to claim 1, characterized in that: The step of determining the target cotton water deficit index threshold according to the planting day information and the initial cotton water deficit index threshold specifically includes: According to the planting day information, counting the cotton planting days corresponding to all the initial cotton water deficit index thresholds; Extracting the maximum value of the cotton planting days to obtain the cotton water stress days; The initial cotton water deficit index threshold corresponding to the cotton water stress days is determined as the target cotton water deficit index threshold.

6. The cotton irrigation optimization method according to claim 1, characterized in that: The step of obtaining the target field water holding rate lower limit value according to the target cotton water deficit index threshold value and the initial field water holding rate lower limit value specifically includes: According to the target cotton water deficit index threshold, the initial field water holding rate lower limit value corresponding to the target cotton water deficit index threshold value is determined to obtain the target field water holding rate lower limit value.

7. The cotton irrigation optimization method according to claim 1, characterized in that: After the step of irrigating the cotton according to the target lower limit of field water holding capacity and the preset upper limit of field water holding capacity, the method further includes: Obtain information on cotton growth stages and actual irrigation amounts at each cotton growth stage; According to the actual irrigation amount information of each cotton growth stage, the total irrigation amount of cotton planting in each cotton growth stage is obtained to carry out quota irrigation for cotton.

8. A cotton irrigation optimization device, characterized in that: include: An information acquisition module, used to obtain multiple soil water matrix potential information, planting soil layer relative depth information, rooting depth information, relative root length density distribution information, net photosynthetic rate information, multiple initial field water holding rate lower limits and planting days information; wherein the soil water matrix potential information corresponds to the initial field water holding rate lower limit; A cotton water deficit index calculation module is used to obtain multiple cotton water deficit indexes based on a preset soil water movement simulation model and according to multiple soil water matrix potential information, planting soil layer relative depth information, rooting depth information and relative root length density distribution information; An initial cotton water deficit index threshold determination module is used to determine multiple initial cotton water deficit index thresholds according to the net photosynthetic rate information and multiple cotton water deficit indices; A target cotton water deficit index threshold determination module, used to determine a target cotton water deficit index threshold according to the planting day information and the initial cotton water deficit index threshold; A target field water holding rate lower limit value determination module is used to obtain a target field water holding rate lower limit value according to the target cotton water deficit index threshold and the initial field water holding rate lower limit value; The cotton irrigation module is used to irrigate the cotton according to the target lower limit value of the field water holding capacity and the preset upper limit value of the field water holding capacity.

9. A terminal device, characterized in that: The terminal device includes a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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