A cotton irrigation optimization method, device and terminal device

Abstract

The present application provides a cotton irrigation optimization method, device and terminal device, which are applicable to the field of irrigation technology. The method includes: obtaining a plurality of soil water matrix potential information, relative depth information of the planted soil layer, rooting depth information, relative root length density distribution information, net photosynthetic rate information, lower limit value of the initial field water holding capacity, and planting days information; obtaining a cotton water deficit index and an initial cotton water deficit index threshold according to the soil water matrix potential information, relative depth information of the planted soil layer, rooting depth information, relative root length density distribution information, and net photosynthetic rate information; determining a target cotton water deficit index threshold and a target field water holding capacity lower limit value according to the planting days information, the initial cotton water deficit index threshold, and the initial field water holding capacity lower limit value; and irrigating the cotton according to the target field water holding capacity lower limit value and a preset upper limit value of the field water holding capacity, so as to improve the management accuracy of irrigation water.

Description

Technical Field

[0001] This application belongs to the technical field of irrigation, and particularly relates to a cotton irrigation optimization method, device, and terminal device. Background Art

[0002] Water resource shortage is the main limiting factor in agricultural production, especially restricting the sustainable development of agriculture in arid and semi-arid regions that rely mainly on irrigation. Precise irrigation systems are an important means to optimize farmland water productivity, which depends on the timely and accurate assessment of plant water status. Those skilled in the art usually use the plant water stress or deficit index (PWDI) to quantify the degree of plant water deficit, so as to guide actual irrigation based on the quantified degree of plant water deficit.

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

[0004] In the prior art, the optimization of the irrigation system is only achieved through the single irrigation amount or the irrigation frequency, which is one-sided in terms of the optimization perspective. And optimizing the irrigation system under the premise of sufficient irrigation can only ensure that the water demand of plants is met, with low precision in water management, and easily leading to waste of irrigation water resources. Summary of the Invention

[0005] In view of this, the embodiments of this application provide a cotton irrigation optimization method, device, and terminal device. By simulating the irrigation scenario through a soil water movement simulation model, quantifying the degree of cotton water deficit according to the simulation results, and considering the response of the net photosynthetic rate of cotton to water stress, accurately calculating the lower limit value of the field water holding rate to guide the actual irrigation in the process of cotton planting, realizing the optimization of the cotton irrigation system under non-sufficient irrigation conditions, ensuring that the water demand during the cotton growth process can be met, while improving the precision of water management and effectively increasing the utilization rate of irrigation water resources.

[0006] The first aspect of the embodiments of this application provides a cotton irrigation optimization method, including:

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

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

[0009] 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;

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

[0011] Obtain a target lower limit value of the field water holding rate according to the target cotton water deficit index threshold and the initial lower limit value of the field water holding rate;

[0012] Irrigate the cotton 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.

[0013] A second aspect of the embodiments of the present application provides a cotton irrigation optimization device, including:

[0014] An information acquisition module, configured to acquire a plurality of soil water matrix potential information, relative depth information of the planting soil layer, rooting depth information, relative root length density distribution information, net photosynthetic rate information, a plurality of initial lower limit values of the field water holding rate, and planting days information; wherein, the soil water matrix potential information corresponds to the initial lower limit value of the field water holding rate;

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

[0016] An initial cotton water deficit index threshold determination module, configured to determine a plurality of initial cotton water deficit index thresholds according to the net photosynthetic rate information and the plurality of cotton water deficit indices;

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

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

[0019] A cotton irrigation module, configured to irrigate the cotton 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.

[0020] A third aspect of the embodiments of the present application provides a terminal device, which includes a memory and a processor. A computer program that can run on the processor is stored on the memory. When the processor executes the computer program, the steps of the cotton irrigation optimization method described in any one of the above first aspects are implemented.

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

[0022] The beneficial effects of the embodiments of the present application compared with the prior art are as follows: The irrigation scenario is simulated through a soil water movement simulation model, the degree of cotton water deficit is quantified according to the simulation results, and at the same time, the response of the net photosynthetic rate of cotton to water stress is considered. The lower limit value of the field water holding rate is accurately calculated to guide the actual irrigation in the process of cotton planting, realizing the optimization of the cotton irrigation system under non-sufficient irrigation conditions, ensuring that the water demand during the cotton growth process can be met, while improving the accuracy of water management and effectively increasing 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 following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0024] Figure 1 It is a schematic flowchart of the implementation of the cotton irrigation optimization method provided by the embodiments of the present application;

[0025] Figure 2 It is a schematic flowchart of the implementation of the cotton irrigation optimization method provided by the embodiments of the present application;

[0026] Figure 3 It is a schematic flowchart of the implementation of the cotton irrigation optimization method provided by the embodiments of the present application;

[0027] Figure 4 It is a schematic flowchart of the implementation of the cotton irrigation optimization method provided by the embodiments of the present application;

[0028] Figure 5 It is a schematic flowchart of the implementation of the cotton irrigation optimization method provided by the embodiments of the present application;

[0029] Figure 6 It is a schematic flowchart of the implementation of the cotton irrigation optimization method provided by the embodiments of the present application;

[0030] Figure 7 It is a schematic structural diagram of the cotton irrigation optimization device provided by the embodiments of the present application;

[0031] Figure 8 It is a schematic diagram of the terminal device provided by the embodiments of the present application. Specific embodiments

[0032] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can 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 avoid unnecessary details from interfering with the description of the present application.

[0033] In order to illustrate the technical solutions described in the present application, the following will be described through specific embodiments.

[0034] Figure 1 The implementation flowchart of the cotton irrigation optimization method provided by Embodiment 1 of the present application is shown and is described in detail as follows:

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

[0036] In this embodiment, the soil water matrix potential information refers to the soil water matrix potential, which is the potential energy caused by the adsorption force and capillary force of the soil matrix. Generally, it refers to the work done when moving a unit amount of water from a balanced soil-water system to another system without soil matrix, or the soil water potential restricted by the adsorption force and capillary force. The planting soil layer depth can be the thickness of the soil covering the cotton roots, that is, the planting soil layer depth available for the growth of cotton roots. The relative depth information of the planting soil layer is the relative depth value relative to the average value of the thickness of the soil covering the cotton roots. The rooting depth information refers to the extension depth of the cotton roots under the planting soil layer, which can be used to quantify the depth of the cotton roots in the soil-covered part relative to the ground. The root length density distribution information refers to the length of the roots in a unit volume of soil, which is used to reflect the distribution of the roots in the soil. The relative root length density distribution information can be the relative cotton root length value relative to the average value of the length of the cotton roots in a unit volume of soil. The net photosynthetic rate information can refer to the rate at which the organic matter produced by the plant through photosynthesis 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 all be measured by artificial experiments or measured by sensors and then manually input into the computer for subsequent calculation and analysis.

[0037] In this embodiment, the lower limit value of the initial field water holding rate and the planting days information can be set artificially. The field water holding rate refers to the water content that the soil can hold. The lower limit value of the initial field water holding rate can be 50%, 55%, 60%, 65% and 70%, which is used to screen the target lower limit value of the field water holding rate from multiple initial lower limit values of the field water holding rate in the follow-up to guide the actual irrigation work of cotton planting. The planting days information is used to represent the number of days of cotton planting, 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 water movement simulation model, obtain multiple cotton water deficit indices according to the multiple soil water matrix potential information, relative depth information of the planting soil layer, rooting depth information, and relative root length density distribution information.

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

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

[0041]

[0042] where h is the 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 drip irrigation under plastic film for cotton based on the Richards equation and the root water absorption equation through the HYDRUS model. Among them, the relative root length density distribution L nrd can be described by the following normalization function:

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

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

[0045] Step S103, determine 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, the plurality of net photosynthetic rate information and the plurality of cotton water deficit indexes can be in one-to-one correspondence. By setting one or more thresholds of the net photosynthetic rate, 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 scheme.

[0047] Step S104, determine the target cotton water deficit index threshold according to the planting days information and the initial cotton water deficit index threshold.

[0048] In this embodiment, each day during the planting process corresponds to a cotton water deficit index. Therefore, each initial cotton water deficit index threshold also corresponds to a planting date. It can be to first count the planting dates corresponding to the plurality of initial cotton water deficit index thresholds, and use the initial cotton water deficit index threshold with the most planting days as the target cotton water deficit index threshold for subsequent determination of the lower limit value of the target field water holding rate, so as to determine the cotton irrigation optimization scheme.

[0049] Step S105: Obtain the lower limit value of the target field water holding rate according to the target cotton water deficit index threshold and the lower limit value of the initial field water holding rate.

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

[0051] Step S106: Irrigate the cotton according to the lower limit value of the target field water holding rate and the preset upper limit value of the field water holding rate.

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

[0053] The cotton irrigation optimization method provided by the embodiment of the present application simulates the irrigation scenario through the soil water movement simulation model, quantifies the degree of cotton water deficit according to the simulation results, and at the same time considers the response of the net photosynthetic rate of cotton to water stress, accurately calculates the lower limit value of the field water holding rate to guide the actual irrigation in the cotton planting process, realizes the optimization of the cotton irrigation regime under non - full irrigation conditions, ensures that the water demand during the cotton growth process can be met, improves the accuracy of water management, and effectively improves the utilization rate of irrigation water resources.

[0054] Figure 2 The flowchart showing the implementation of the cotton irrigation optimization method provided by the second embodiment of the present application is different from the first embodiment above in that step S102 specifically includes:

[0055] Step S201: Based on the preset soil water movement simulation model, perform non - linear least - squares fitting calculation according to the actual value of the soil water matrix potential to obtain the change curve of the soil water stress correction coefficient.

[0056] In this embodiment, the inverse solution option of the HYDRUS model can be used to optimize the soil hydraulic parameters. The Levenberg-Marquardt nonlinear minimization method is used to minimize the objective function during the inverse solution process to achieve the fitting calculation of the nonlinear least squares method, so as to utilize the simulation means of soil moisture by HYDRUS and the analysis of cotton stress status based on the PWDI threshold. Among them, the soil hydraulic parameters used for optimization calculation can be the soil water matrix potential, or the soil water content obtained by measurement or simulation, and then the soil water content is converted into the soil water content. The soil water stress correction coefficient change curve obtained in this embodiment can have the soil water stress correction coefficient on the vertical axis and the soil water matrix potential on the horizontal axis.

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

[0058] In this embodiment, the soil water stress correction coefficient change curve can have the soil water stress correction coefficient on the vertical axis and the soil water matrix potential on the horizontal axis. The fitting parameters of the image curve can be obtained by optimizing the parameters through the nonlinear least squares method. These fitting parameters are the coefficient change fitting parameters, which can be represented by ρ. By optimizing the parameters through the nonlinear least squares method, ρ = 0.12 can be obtained, and the corresponding soil water stress correction coefficient γ(h) is a concave function.

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

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

[0061]

[0062] Where h H 、h L and h W are respectively the upper limit, lower limit and wilting coefficient of the soil water matrix potential suitable for crop growth, h is the soil water matrix potential, and in this embodiment, the measured or simulated soil water content can be converted into the soil water matrix potential according to the soil water characteristic curve. The selected parameters can be h H =-50, h L =-400, h W= -15000 cm. 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 matric potential is less than or equal to the wilting coefficient, γ(h) = 0, h ≤ h W 。

[0063] Step S204, determine whether the actual value of the soil water matric potential is less than the lower limit value of the soil water matric potential. If so, proceed 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, calculate the root-weighted water deficit index according to the coefficient change fitting parameter, the upper limit value of the soil water matric potential, the lower limit value of the soil water matric potential, the wilting coefficient, and the actual value of the soil water matric potential.

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

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

[0068] In this embodiment, the credibility of the HYDRUS model for simulating the soil water content change under different irrigation lower limits can be verified by calculating the error between the root-weighted water deficit index calculated above and the root-weighted water deficit index obtained by other calculation methods or simulation methods, so as to evaluate the accuracy and usability of the PWDI calculated based on the root-weighted soil moisture for guiding the drip irrigation under plastic film of cotton, which is convenient for determining the subsequent cotton irrigation optimization scheme. The error verification method can be to calculate the mean absolute error, or the mean square error, or the root mean square error, or the mean absolute percentage error. When the calculated error is less than the preset error threshold, it indicates that the calculation result of the root-weighted water deficit index above is reliable and can be used for the subsequent determination of the irrigation scheme.

[0069] The cotton irrigation optimization method provided by the embodiments of this application fits the change curve of the soil water stress correction coefficient through a preset soil water movement simulation model, calculates the soil water stress correction coefficient through the fitting parameter, verifies the credibility of the HYDRUS model for simulating the soil water content change under different irrigation lower limits through the error calculation result, and is used to evaluate the accuracy and usability of the PWDI calculated based on the root-weighted soil moisture for guiding the drip irrigation under plastic film of cotton, which is convenient for determining the subsequent cotton irrigation optimization scheme.

[0070] Figure 3The flowchart of the implementation of the cotton irrigation optimization method provided in Embodiment 3 of the present application is shown. The difference from Embodiment 2 above is that the step S206 specifically includes:

[0071] Step S301, obtain the actual transpiration rate of cotton, the potential transpiration rate of the 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, 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 sap flow measured by a heat ratio method (HRM) using a sap flow meter. The sap flow meter can be installed at the first internode of cotton from the budding stage to the flowering and boll stage, and data is recorded every 30 minutes. The sap flow velocity in the plant is determined by measuring the temperature ratio caused by the upward and downward sap movement. The unit effective leaf area refers to the leaf area of cotton that can actively utilize light energy for photosynthesis. The potential transpiration rate of the unit effective leaf area refers to the value that is equal under various water treatments and is approximately the actual transpiration rate of the unit effective leaf area under full irrigation conditions. The leaf area index refers to the multiple of the total area of plant leaves per unit land area to the land area. The above specific values can all be obtained through 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 ), and can be calculated by the following formula:

[0075]

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

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

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

[0079] T p = T pa ×LAI a

[0080] where T pa is the potential transpiration rate of the unit effective leaf area (mm d -1), assumed to be equal under various water treatments, approximately the actual transpiration rate per unit of effective leaf area under fully irrigated conditions; LAI a is the effective leaf area index (cm 2 cm -2 ), and 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 the 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 during the budding stage of cotton can be obtained by the water balance method.

[0085] The calculation of the actual transpiration rate of cotton is 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 sap flow velocity of the plant (cm hr -1 ), SA is the area through which the sap flow passes (cm 2 ), where V h The calculation formula is as follows:

[0088]

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

[0090] The calculation of SA is as follows:

[0091] SA = 3.14 × (D / 2) 2

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

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

[0094] T a = I + P - E - R - D - ΔW

[0095] Wherein, I is the irrigation amount (mm); P is the precipitation (mm), which is zero when there is a rain shelter; E is the soil evaporation amount (mm), and the soil evaporation amount under the film is obtained through a self-made small evaporator; R is the surface runoff amount (mm), which is ignored in this study due to effective water management; D is the deep drainage at the lower boundary (mm), and there is no deep drainage in this study of deficit irrigation, so D is zero; ΔW is the change in the water stored in the soil profile from the surface layer to the lower boundary, which is estimated by the measured soil water content.

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

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

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

[0099] In this embodiment, the simulation 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 water content under different irrigation lower limits.

[0100] Step S306, determine whether the root mean square error is less than a preset root mean square error threshold. If so, enter step S307; if not, use the cotton water deficit estimate value as the cotton water 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 subsequent determination of the cotton irrigation plan.

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

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

[0104] The cotton irrigation optimization method provided by the embodiment of the present application calculates the cotton water deficit estimate value through the actual transpiration rate of cotton, the potential transpiration rate per unit effective leaf area, and the leaf area index, and is used to verify the error of the root-weighted water deficit index, so as to evaluate the accuracy and usability of the PWDI calculated based on the root-weighted soil moisture in guiding the drip irrigation under plastic film of cotton, which is convenient for 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 implementation of the cotton irrigation optimization method provided by the fourth embodiment of the present application is shown. The difference from the above-mentioned first embodiment is that the step S103 specifically includes:

[0106] Step S401, obtain the response law of the net photosynthetic rate information to the 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 measured for the existing planted cotton through experiments. Then, the data measured and calculated for the net photosynthetic rate and the cotton water deficit index by the staff are input into the computer. Subsequently, it can be visualized in the form of a two-dimensional image with the PWDI as the abscissa and the net photosynthetic rate as the ordinate, which is used for 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, use the cotton water deficit index as the abscissa and the net photosynthetic rate information 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 PWDI as the abscissa and the net photosynthetic rate as the ordinate to obtain a water deficit response curve graph.

[0110] Step S403, determine the abscissa corresponding to the extreme point of the water deficit response curve graph to obtain 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. The corresponding abscissa at this time is used as the cotton water deficit numerical base point, which is used to characterize the subsequent adjustment of the range and value of the cotton water deficit numerical value, with the cotton water deficit numerical base point as the base point for change. 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 at the budding stage or the cotton water deficit numerical base point at the flowering and boll-setting stage.

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

[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. This ordinate is used as the net photosynthetic rate base point, which is used to characterize the subsequent adjustment of the range and value of the cotton water deficit numerical value at the budding stage, with the net photosynthetic rate base point as the base point for change.

[0114] Step S405: Calculate 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, when the net photosynthetic rate base point is adjusted based on a plurality of preset net photosynthetic rate change range values, the corresponding abscissa is adjusted accordingly. The change amount of the adjusted abscissa is the net photosynthetic rate change value, which 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, use the plurality of net photosynthetic rate change values as the ordinate to determine the corresponding abscissa to obtain a plurality of initial cotton water deficit index thresholds.

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

[0118] The cotton irrigation optimization method provided by the embodiments 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 cotton is not affected after the irrigation amount changes. It is used to optimize the irrigation plan while ensuring the normal growth of cotton after the irrigation amount changes, thereby improving the accuracy of irrigation water resource management and effectively increasing the utilization rate of irrigation water resources.

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

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

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

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

[0123] In this embodiment, by determining the maximum value of the cotton planting days, it is used to determine the initial cotton water deficit index threshold that appears the most days during the cotton planting process, indicating that this initial cotton water deficit index threshold is most suitable for the growth of cotton after the irrigation plan is adjusted.

[0124] Step S503: Determine 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, determining the initial cotton water deficit index threshold corresponding to the cotton water stress days as the target cotton water deficit index threshold is used to optimize and adjust the irrigation amount of cotton.

[0126] The cotton irrigation optimization method provided by the embodiments of the present application determines the cotton water deficit index threshold that appears the most days during the cotton planting process, which is used for subsequent conversion of the irrigation amount through this cotton water deficit index threshold, thereby guiding the irrigation work in the actual cotton planting process, realizing the optimization of the cotton irrigation system under non-full irrigation conditions, ensuring that the water demand during the cotton growth process can be met while improving the accuracy of water management and effectively increasing the utilization rate of irrigation water resources.

[0127] Another embodiment of the present application provides a cotton irrigation optimization method, which is different from the first embodiment above in that: step S105 specifically includes:

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

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

[0130] The cotton irrigation optimization method provided by 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, realizes the optimization of the cotton irrigation system under the condition of deficit irrigation, effectively improves the accuracy of water management, and thus improves the utilization rate of irrigation water resources.

[0131] Figure 6 The flowchart of the implementation of the cotton irrigation optimization method provided by the sixth embodiment of the present application is shown. It is different from the first embodiment above in that after step S106, it further includes:

[0132] Step S601: Obtain the cotton growth stage information and the actual irrigation amount information for each cotton growth stage.

[0133] In this embodiment, the cotton growth stage information may include the budding stage, the flowering and boll-forming stage, and the seedling stage. The irrigation amounts for each growth stage after irrigation are statistically summed to obtain the actual irrigation amount information for each cotton growth stage, which is used to provide reference data for the fixed irrigation of cotton in the future.

[0134] Step S602: Obtain the total cotton planting irrigation amount for each cotton growth stage according to the actual irrigation amount information for each cotton growth stage, so as to perform fixed irrigation on the cotton.

[0135] In this embodiment, the fixed irrigation amount for cotton is set through the total cotton planting irrigation amount for each cotton growth stage, which is used to achieve the purpose of water saving during the irrigation process.

[0136] In this embodiment, when the irrigation quota target is set to not exceed 420 mm, the irrigation schemes that meet the requirements at this time are: the field water holding rate during the budding stage is 50%, and the field water holding rate during the flowering and boll-forming stage is 50%; the field water holding rate during the budding stage is 55%, and the field water holding rate during the flowering and boll-forming stage is 50%; the field water holding rate during the budding stage is 60%, and the field water holding rate during the flowering and boll-forming stage is 50%; the field water holding rate during the budding stage is 65%, and the field water holding rate during the flowering and boll-forming stage is 50%; the field water holding rate during the budding stage is 70%, and the field water holding rate during the flowering and boll-forming stage is 50%; the field water holding rate during the budding stage is 50%, and the field water holding rate during the flowering and boll-forming stage is 55%. Among them, under the scheme where the field water holding rate during the budding stage is 70% and the field water holding rate during the flowering and boll-forming stage is 50%, the cumulative number of days with PWDI < 0.48 during the budding stage and PWDI < 0.52 during the flowering and boll-forming stage is the most, which is 60 days. Correspondingly, the lower limit of irrigation water during the cotton budding stage is 70% of the field water holding capacity, and the lower limit of irrigation water during the flowering and boll-forming stage is 50% of the field water holding capacity. When the irrigation quota target is set to not exceed 450 mm, the irrigation schemes that meet the requirements at this time are: the field water holding rate during the budding stage is 50%, and the field water holding rate during the flowering and boll-forming stage is 50%; the field water holding rate during the budding stage is 55%, and the field water holding rate during the flowering and boll-forming stage is 50%; the field water holding rate during the budding stage is 60%, and the field water holding rate during the flowering and boll-forming stage is 50%; the field water holding rate during the budding stage is 65%, and the field water holding rate during the flowering and boll-forming stage is 50%; the field water holding rate during the budding stage is 70%, and the field water holding rate during the flowering and boll-forming stage is 50%; the field water holding rate during the budding stage is 50%, and the field water holding rate during the flowering and boll-forming stage is 55%; the field water holding rate during the budding stage is 55%, and the field water holding rate during the flowering and boll-forming stage is 55%; the field water holding rate during the budding stage is 60%, and the field water holding rate during the flowering and boll-forming stage is 55%; the field water holding rate during the budding stage is 65%, and the field water holding rate during the flowering and boll-forming stage is 55%. Among them, under the scheme where the field water holding rate during the budding stage is 65% and the field water holding rate during the flowering and boll-forming stage is 55%, the total number of days with PWDI < 0.48 during the budding stage and < 0.52 during the flowering and boll-forming stage is the most, which is 67 days. Correspondingly, the lower limit of irrigation water during the cotton budding stage is 65% of the field water holding capacity, and the lower limit of irrigation water during the flowering and boll-forming stage is 55% of the field water holding capacity. The optimal irrigation schemes under the irrigation quota restrictions of 420 mm, 450 mm, and 480 mm are respectively: the field water holding rate during the budding stage is 70%, and the field water holding rate during the flowering and boll-forming stage is 50%; the field water holding rate during the budding stage is 65%, and the field water holding rate during the flowering and boll-forming stage is 55%; the field water holding rate during the budding stage is 70%, and the field water holding rate during the flowering and boll-forming stage is 55%.

[0137] The cotton irrigation optimization method provided by the embodiment of the present application calculates the fixed-quota irrigation amount, accurately calculates the lower limit value of the field water holding rate to guide the actual irrigation during the cotton planting process, realizes the optimization of the cotton irrigation system under the condition of deficit irrigation, ensures that the water demand during the cotton growth process can be met, improves the accuracy of water management, and effectively improves the utilization rate of irrigation water resources.

[0138] Corresponding to the method in the above embodiment, Figure 7The structural block diagram of the cotton irrigation optimization device provided by the embodiments of the present application is shown. For the sake of convenience of description, only the parts related to the embodiments of the present application are shown. Figure 7 The exemplary cotton irrigation optimization device may be the execution subject of the cotton irrigation optimization method provided in the foregoing Embodiment 1.

[0139] Referring to Figure 7 , the cotton irrigation optimization device includes:

[0140] An information acquisition module 710, configured to acquire multiple soil water matrix potential information, relative depth information of the planting soil layer, rooting depth information, relative root length density distribution information, net photosynthetic rate information, multiple lower limit values of the initial field water holding rate, and planting days information; wherein, the soil water matrix potential information corresponds to the lower limit value of the initial field water holding rate;

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

[0142] An initial cotton water deficit index threshold determination module 730, configured to determine multiple initial cotton water deficit index thresholds according to the net photosynthetic rate information and the multiple cotton water deficit indexes;

[0143] A target cotton water deficit index threshold determination module 740, configured to determine a target cotton water deficit index threshold according to the planting days information and the initial cotton water deficit index threshold;

[0144] A target field water holding rate lower limit value determination module 750, configured 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;

[0145] A cotton irrigation module 760, configured to irrigate the cotton according to the target field water holding rate lower limit value and a preset upper limit value of the field water holding rate.

[0146] For the process of each module in the cotton irrigation optimization device provided by the embodiments of the present application to implement its respective functions, reference may be specifically made to the description of Embodiment 1 shown above, which will not be elaborated here. Figure 1 It should be understood that the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0147]

[0148] ​It should be understood that, as used in the specification of this application and the appended claims, the term "comprising" indicates the presence of the described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or their combinations.

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

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

[0151] In addition, in the description of the specification of this application and the appended claims, the terms "first", "second", "third", etc. are used only for differential description and should not be construed as indicating or implying relative importance. It should also be understood that although the terms "first", "second", etc. are used in the text in some embodiments of this application to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, the first table can be named the second table, and similarly, the second table can be named 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] Reference to "one embodiment" or "some embodiments" or the like described in the specification of this application means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of this application. Thus, statements such as "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments", etc. that appear in different places in this specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in another way. The terms "comprising", "including", "having", and their variants all mean "including but not limited to", unless otherwise specifically emphasized in another way.

[0153] The cotton irrigation optimization method provided by the embodiments of this application can be applied to terminal devices such as mobile phones, tablet computers, wearable devices, in-vehicle devices, augmented reality (AR) / virtual reality (VR) devices, laptop computers, ultra-mobile personal computers (UMPCs), netbooks, personal digital assistants (PDAs), etc. The embodiments of this application do not impose any restrictions on the specific types of terminal devices.

[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 capabilities, a computing device or other processing devices connected to a wireless modem, an in-vehicle 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 television set-top box (set top box, STB), a customer premise equipment (CPE), and / or other devices for communicating on a wireless system, as well as next-generation communication systems, such as mobile terminals in a 5G network or mobile terminals in a future evolved Public Land Mobile Network (PLMN) network.

[0155] By way of example and not limitation, when the terminal device is a wearable device, the wearable device can also be a general term for devices that apply wearable technology to the intelligent design of daily wear and develop wearable devices, such as glasses, gloves, watches, clothing, and shoes. A wearable device is a portable device that is either directly worn on the body or integrated into the user's clothing or accessories. A wearable device is not just a hardware device, but also realizes powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable intelligent devices include those with complete functions and large sizes that can achieve complete or partial functions without relying on a smartphone, such as smart watches or smart glasses, as well as those that only focus on a certain type of application function and need to cooperate with other devices such as smartphones, such as various smart bracelets and smart jewelry for physical sign monitoring.

[0156] Figure 8It is a schematic structural diagram of a terminal device provided by an embodiment of the present application. As Figure 8 shown, the terminal device of this embodiment includes: at least one processor 800 ( Figure 8 only one is shown in the figure), and a memory 810. A computer program 820 that can run on the processor 800 is stored in the memory 810. When the processor 800 executes the computer program 820, the steps in the above-mentioned embodiments of each cotton irrigation optimization method are implemented, such as Figure 1 the steps S101 to S106 shown in the figure. Alternatively, when the processor 800 executes the computer program 820, the functions of each module / unit in the above-mentioned device embodiments are implemented, such as Figure 7 the functions of the modules 710 to 760 shown in the figure.

[0157] The terminal device may be a computing device such as a desktop computer, a notebook, a palm computer, and 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 can understand that Figure 8 this is only an example of the terminal device and does not constitute a limitation on the terminal device. It may include more or fewer components than those shown in the figure, or combine some components, or different components. For example, the terminal device may further include an input and sending device, a network access device, a bus, etc.

[0158] The so-called processor 800 may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

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

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

[0161] The embodiment of the present application further 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. When the processor executes the computer program, the terminal device implements the steps in any of the above method embodiments.

[0162] The embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps in any of the above method embodiments can be implemented.

[0163] The embodiment of the present application provides a computer program product. When the computer program product runs on a terminal device, the terminal device is enabled to execute the steps in any of the above method embodiments.

[0164] When 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, to implement all or part of the processes in the above-described embodiment methods of this application, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-described method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0165] In the above embodiments, the descriptions of each embodiment have their own emphases. For parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0166] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this document can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed 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 can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0168] The above-described embodiments are only used to illustrate the technical solutions of this application, rather than to limit them; although this application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of each embodiment of this application, and should all be included within the protection scope of this application.

Claims

1. A cotton irrigation optimization method, characterized in that, Including: Obtaining a plurality of soil water matrix potential information, relative depth information of the planted soil layer, rooting depth information, relative root length density distribution information, net photosynthetic rate information, a plurality of lower limit values of the initial field water holding rate, and planting days information; wherein, the soil water matrix potential information corresponds to the lower limit value of the initial field water holding rate; Based on a preset soil water movement simulation model, according to the plurality of soil water matrix potential information, relative depth information of the planted soil layer, rooting depth information, and relative root length density distribution information, obtaining a plurality of cotton water deficit indexes; Determining a plurality of initial cotton water deficit index thresholds according to the net photosynthetic rate information and the plurality of cotton water deficit indexes; Determining a target cotton water deficit index threshold according to the planting days information and the initial cotton water deficit index threshold; Obtaining a target field water holding rate lower limit value according to the target cotton water deficit index threshold and the lower limit value of the initial field water holding rate; Irrigating cotton according to the target field water holding rate lower limit value and a preset upper limit value of the field water holding rate.

2. The cotton irrigation optimization method according to claim 1, wherein The soil water matrix potential information includes an upper limit value of the soil water matrix potential, a lower limit value of the soil water matrix potential, a wilting coefficient, and an 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 the plurality of soil water matrix potential information, relative depth information of the planted soil layer, rooting depth information, and relative root length density distribution information, specifically includes: Based on a preset soil water movement simulation model, according to the actual value of the soil water matrix potential, performing non-linear least squares fitting calculation to obtain a soil water stress correction coefficient change curve; Obtaining coefficient change fitting parameters according to the soil water stress correction coefficient change curve; 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 value of the soil water matrix potential, calculating a root system weighted water deficit index according to the coefficient change fitting parameters, 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; Performing error verification on the root system weighted water deficit index to obtain a cotton water deficit index.

3. The cotton irrigation optimization method according to claim 2, wherein The step of performing error verification on the root system weighted water deficit index to obtain a cotton water deficit index specifically includes: Obtaining the actual transpiration rate of cotton, the potential transpiration rate per unit effective leaf area, and the leaf area index; Calculating the effective leaf area index according to the 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 the cotton water deficit according to the actual transpiration rate of cotton and the potential transpiration rate; Calculating the root mean square error and the mean absolute error percentage of the estimated value of the cotton water deficit and the root system 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, wherein 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 includes: obtaining the response law of the net photosynthetic rate information to the cotton water deficit index; According to the response law of the net photosynthetic rate information to the cotton water deficit index, taking the cotton water deficit index as the abscissa and the net photosynthetic rate information as the ordinate, generating a water deficit response curve graph; determining the abscissa corresponding to the extreme point of the water deficit response curve graph to obtain the cotton water deficit numerical base point; determining the ordinate corresponding to the extreme point of the water deficit response curve graph to obtain the net photosynthetic rate base point; 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 graph, taking the plurality of net photosynthetic rate change values as the ordinate, determining the corresponding abscissa to obtain a plurality of initial cotton water deficit index thresholds.

5. The cotton irrigation optimization method according to claim 1, wherein, The step of determining the target cotton water deficit index threshold according to the planting days information and the initial cotton water deficit index threshold specifically includes: According to the planting days 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; determining the initial cotton water deficit index threshold corresponding to the cotton water stress days as the target cotton water deficit index threshold.

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

7. The cotton irrigation optimization method according to claim 1, wherein After the step of irrigating the cotton according to the target field water holding rate lower limit value and the preset field water holding rate upper limit value, it further includes: obtaining the cotton growth stage information and the actual irrigation amount information of each cotton growth stage; According to the actual irrigation amount information of each cotton growth stage, obtaining the total cotton planting irrigation amount of each cotton growth stage to perform quota irrigation on the cotton.

8. An optimized cotton irrigation device, characterized in that, including: an information acquisition module for acquiring a plurality of soil water matrix potential information, relative planting soil layer depth information, rooting depth information, relative root length density distribution information, net photosynthetic rate information, a plurality of initial field water holding rate lower limit values, and planting days information; wherein, the soil water matrix potential information corresponds to the initial field water holding rate lower limit value; A cotton water deficit index calculation module, which is used to obtain a plurality of cotton water deficit indexes based on a preset soil water movement simulation model, according to a plurality of the soil water matrix potential information, the relative depth information of the planting soil layer, the rooting depth information, and the relative root length density distribution information; An initial cotton water deficit index threshold determination module, which 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 indexes; A target cotton water deficit index threshold determination module, which is used to determine a target cotton water deficit index threshold according to the planting days information and the initial cotton water deficit index threshold; A target field water holding rate lower limit value determination module, which 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; A cotton irrigation module, which is used to irrigate cotton according to the target field water holding rate lower limit value and a preset field water holding rate upper limit value.

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

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