Application methods and systems of microbial fertilizers to promote phosphorus absorption in alfalfa

Abstract

This application discloses a method and system for applying microbial fertilizer to promote phosphorus absorption in alfalfa. The method includes: determining the amount of microbial fertilizer to be applied to each alfalfa area based on the plant phosphorus content, total soil phosphorus content, and available soil phosphorus content; activating sensor equipment pre-installed in the alfalfa field to acquire alfalfa growth environment information and calculating the daily irrigation amount for the alfalfa field using the growth environment information; preparing a fertilizer solution for a drip irrigation fertilization system based on the microbial fertilizer application amount and the daily irrigation amount, and using the fertilizer solution to perform irrigation fertilization on the alfalfa field to complete the application of microbial fertilizer to promote phosphorus absorption in alfalfa. Through the solution of this application, the dissolution and release of phosphorus in the soil can be promoted, thereby improving the phosphorus absorption efficiency of alfalfa.

Description

Technical Field

[0001] This application relates to the agricultural field, and in particular to a method and system for applying microbial fertilizer to promote phosphorus absorption in alfalfa. Background Technology

[0002] In recent years, global agriculture has faced challenges in soil nutrient management, particularly the efficient utilization of phosphorus (P). Alfalfa (Medicago sativa L.) is an important forage crop, and its growth and productivity are directly related to the development of animal husbandry. However, alfalfa's phosphorus absorption efficiency is relatively low, which severely restricts its yield and quality. Therefore, how to promote phosphorus absorption in alfalfa has become an important research topic. Promoting phosphorus absorption in alfalfa not only helps to improve its growth rate and nutritional value, but also reduces the amount of chemical fertilizers used, lowers agricultural costs, and mitigates environmental pollution. Current technologies mainly rely on the application of chemical phosphate fertilizers and improved fertilization methods to increase phosphorus utilization. However, these methods have some limitations, such as the limited effectiveness of chemical phosphate fertilizers in the soil, and long-term use leading to soil acidification, structural deterioration, and environmental pollution. Furthermore, phosphate fertilizers have poor mobility in the soil and are easily fixed by soil particles, preventing plants from effectively absorbing them. These problems seriously affect the phosphorus absorption efficiency of alfalfa and the sustainable development of agriculture.

[0003] To address these issues, researchers have proposed several solutions. For example, improved fertilization techniques, such as staggered fertilization and drip irrigation, can enhance phosphorus use efficiency. However, these methods have limited effectiveness in improving phosphorus utilization and are costly. Additionally, soil conditioners, such as organic fertilizers and lime, have been used to improve soil structure and chemical properties, thereby increasing phosphorus availability. However, these measures typically take a long time to show results and are difficult to implement on a large scale in agricultural production.

[0004] Therefore, there is an urgent need for a technical solution that can promote the dissolution and release of phosphorus in the soil, thereby improving the phosphorus absorption efficiency of alfalfa. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this application provides a method and system for applying microbial fertilizer to promote phosphorus absorption in alfalfa. This application solves the technical problem of low phosphorus absorption efficiency in existing technologies.

[0006] This application provides a method for applying microbial fertilizer to promote phosphorus absorption in alfalfa, comprising: receiving an irrigation and fertilization instruction to promote phosphorus absorption in alfalfa; dividing the alfalfa field into multiple alfalfa regions according to the irrigation and fertilization instruction; sequentially sampling alfalfa plants in the alfalfa regions and determining the phosphorus content of the plants in the alfalfa regions; and sequentially sampling alfalfa soil in the alfalfa regions and determining the total phosphorus content and available phosphorus content of the soil in the alfalfa regions. The following steps are taken: Based on the plant phosphorus content, soil total phosphorus content, and soil available phosphorus content, determine the amount of microbial fertilizer applied to each alfalfa area; activate the sensor equipment pre-installed in the alfalfa field to acquire alfalfa growth environment information, and use this information to calculate the daily irrigation amount for the alfalfa field; prepare a fertilizer solution for the drip irrigation fertilization system based on the microbial fertilizer application amount and the daily irrigation amount, and use this solution to perform irrigation fertilization on the alfalfa field to complete the application of microbial fertilizer that promotes phosphorus absorption by alfalfa.

[0007] In one possible implementation, determining the amount of microbial fertilizer applied to each alfalfa region based on the plant phosphorus content, soil total phosphorus content, and soil available phosphorus content includes: constructing a phosphorus use efficiency model to calculate phosphorus use efficiency using the plant phosphorus content, soil total phosphorus content, and soil available phosphorus content; constructing a constraint relationship between phosphorus use efficiency and microbial fertilizer application amount; constructing a microbial fertilizer application amount optimization model based on the phosphorus use efficiency model and the constraint relationship, and setting an objective function to maximize the sum of phosphorus use efficiency in all regions to obtain a target microbial fertilizer application amount optimization problem; and using a target numerical optimization algorithm to solve the target microbial fertilizer application amount optimization problem to obtain the optimal microbial fertilizer application amount.

[0008] In one possible implementation, the step of activating sensor equipment pre-installed in the alfalfa field to acquire alfalfa growth environment information and using the growth environment information to calculate the daily irrigation amount of the alfalfa field includes: acquiring the target meteorological data of the day from the sensor to calculate the water vapor parameter set for each field; substituting the water vapor parameter set into the Penman-Monteith equation to calculate the reference crop evapotranspiration for each field; and calculating the daily irrigation amount for each field based on the reference crop evapotranspiration and the alfalfa crop coefficient.

[0009] In one possible implementation, the preparation of the fertilizer solution for the drip irrigation fertilization system based on the amount of microbial fertilizer applied and the daily irrigation volume, wherein the fertilizer solution is used for irrigation fertilization of alfalfa fields to complete the application of microbial fertilizer to promote phosphorus absorption by alfalfa, includes: dissolving microbial fertilizer and compound fertilizer in batches to prepare a low-concentration stock solution, wherein the stock solution is used to prepare the required fertilizer solution; determining the target volume of the stock solution according to the amount of microbial fertilizer applied and the daily irrigation volume, and adding the target volume of stock solution to the daily irrigation volume of water to obtain the fertilizer solution; dividing the fertilizer solution into a preset application cycle of equal portions, so as to apply one portion of fertilizer solution in each cycle.

[0010] In one possible implementation, the construction of the phosphorus use efficiency model to calculate phosphorus use efficiency using plant phosphorus content, total soil phosphorus content, and available soil phosphorus content includes: in, This represents the phosphorus utilization efficiency of the i-th region. This represents the available phosphorus content in the soil of the i-th region. This represents the total phosphorus content of the soil in the i-th region. Let θ1 represent the phosphorus content of the plant in the i-th region, θ2 represent the first efficiency parameter with a value of 5, θ3 represent the second efficiency parameter with a value of 2, and θ3 represent the third efficiency parameter with a value of 3.

[0011] In one possible implementation, the constraint relationship between phosphorus utilization efficiency and microbial fertilizer application rate includes: in, The available phosphorus content in the soil of region i is represented by μ. i β1 represents the amount of microbial fertilizer applied in the i-th region, β2 represents the first constraint parameter with a value of 50, and β2 represents the second constraint parameter with a value of 0.1.

[0012] In one possible implementation, the step of constructing an optimization model for microbial fertilizer application rate based on the phosphorus utilization efficiency model and the constraint relationship, and setting an objective function to maximize the sum of phosphorus utilization efficiencies across all regions, to obtain the target microbial fertilizer application rate optimization problem, includes:

[0013] Where N represents the number of soil regions.

[0014] This application also provides a microbial fertilizer application system for promoting phosphorus absorption in alfalfa, including: a sampling unit, an optimization unit, and a configuration unit; wherein, the sampling unit is used to receive irrigation and fertilization instructions for promoting phosphorus absorption in alfalfa, and to perform grid division of the alfalfa field according to the irrigation and fertilization instructions to obtain multiple alfalfa regions; to sequentially sample alfalfa plants in the alfalfa regions and determine the phosphorus content of the plants in the alfalfa regions; to sequentially sample soil from the alfalfa regions and determine the total phosphorus content of the soil in the alfalfa regions and... The soil available phosphorus content; the optimization unit is used to determine the amount of microbial fertilizer applied to each alfalfa area based on the plant phosphorus content, soil total phosphorus content, and soil available phosphorus content; the configuration unit is used to activate the sensor equipment pre-installed in the alfalfa field to obtain alfalfa growth environment information and use the growth environment information to calculate the daily irrigation amount of the alfalfa field; based on the amount of microbial fertilizer applied and the daily irrigation amount, a fertilizer solution for the drip irrigation fertilization system is prepared, and the fertilizer solution is used to perform irrigation fertilization on the alfalfa field to complete the application of microbial fertilizer to promote phosphorus absorption by alfalfa.

[0015] In the above-mentioned method and system for applying microbial fertilizer to promote phosphorus absorption in alfalfa, the embodiments of this application promote the dissolution and release of phosphorus in the soil by the secretion of organic acids and enzymes by microorganisms in the microbial fertilizer, and also form a symbiotic relationship with plant roots, thereby improving the efficiency of phosphorus absorption by plants. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A schematic flowchart illustrating the application method of microbial fertilizer for promoting phosphorus absorption in alfalfa, as provided in the embodiments of this application.

[0018] Figure 2 A schematic block diagram of a microbial fertilizer application system for promoting phosphorus absorption in alfalfa, provided in an embodiment of this application. Detailed Implementation

[0019] Various exemplary embodiments of the present application will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present application.

[0020] Those skilled in the art will understand that the terms "first," "second," etc., in the embodiments of this application are only used to distinguish different steps, devices, or modules, and do not represent any specific technical meaning, nor do they indicate a necessary logical order between them. It should also be understood that in the embodiments of this application, "multiple" can refer to two or more, and "at least one" can refer to one, two, or more. It should also be understood that any component, data, or structure mentioned in the embodiments of this application can generally be understood as one or more unless explicitly limited or given a contrary suggestion in the context. Furthermore, the term "and / or" in this application is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this application generally indicates that the related objects before and after are in an "or" relationship. It should also be understood that the descriptions of the various embodiments in this application emphasize the differences between them; their similarities or commonalities can be referred to mutually, and for the sake of brevity, they will not be elaborated upon one by one.

[0021] Furthermore, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn to actual scale. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit this application or its application or use. Techniques, methods, and devices known to those skilled in the art will not be discussed in detail, but where appropriate, such techniques, methods, and devices should be considered part of the specification. It should be noted that similar reference numerals and letters in the following drawings denote similar items; therefore, once an item is defined in one drawing, it need not be further discussed in subsequent drawings.

[0022] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0023] Figure 1 This is a schematic flowchart illustrating the method for applying microbial fertilizer to promote phosphorus absorption in alfalfa, as provided in an embodiment of this application. Figure 1As shown, in step S101, an irrigation and fertilization command to promote phosphorus absorption in alfalfa is received. Based on this command, the alfalfa field is divided into grids, resulting in multiple alfalfa zones. It should be understood that this command can be issued by a remote control center or set by on-site personnel according to the actual situation. The command may include basic information such as the specific location and area of ​​the alfalfa field. Then, based on the irrigation and fertilization command, the alfalfa field is divided into grids, resulting in multiple alfalfa zones. The purpose of grid division is to more accurately measure and control the irrigation and fertilization of each zone. Grid division can employ GPS-based automatic zoning technology or be manually measured and marked by personnel.

[0024] In step S102, alfalfa plant samples are taken sequentially from the alfalfa area to determine the phosphorus content of the plants. Specifically, in one embodiment, 3-5 uniformly growing alfalfa plants are selected from the alfalfa area, and the above-ground parts of the alfalfa are cut off 2 cm above the soil surface. The above-ground parts are placed in a drying oven, wherein the drying oven intelligently displays the quality data of the material inside the oven, and the drying temperature is set to 105°C and the drying time is set to 30 minutes.

[0025] After the drying operation is completed, the drying temperature of the drying chamber is set again to 60℃-75℃, and the drying operation continues until the mass data of the material in the chamber is stable and no longer changes. The dried aboveground parts are removed from the drying chamber and weighed using an electronic balance to obtain the dry matter mass. The dried aboveground parts are then pulverized to obtain dry matter powder. The dry matter powder is then digested using the h2SO4-H2O2 method to prepare a sample test solution. The sample test solution is measured using a UV-Vis spectrophotometer to analyze the plant phosphorus concentration. Based on the dry matter mass and plant phosphorus concentration, the plant phosphorus content of the sample test solution is calculated, thus completing the determination of plant phosphorus content in the alfalfa region.

[0026] In step S103, soil samples are taken from the alfalfa area sequentially, and the total phosphorus content and available phosphorus content of the soil in the alfalfa area are measured. Specifically, in one implementation scenario, soil samples are collected from three locations in the alfalfa area at depths of 5cm, 10cm, and 15cm below the soil surface where the alfalfa is located. After being uniformly mixed, a sample soil is obtained. The sample soil is placed in a drying oven, wherein the drying oven intelligently displays the mass data of the materials inside the oven, and the drying temperature is set to 10℃~30℃, and the drying time is set to 60 minutes.

[0027] After the drying process is completed, the dried soil samples are sequentially compacted, crushed, and sieved to obtain fine-grained soil samples. The sieve aperture size for sieving is 2.00 mm. Two fine-grained soil samples, each weighing 2.00 g to 5.00 g, are weighed. The total phosphorus content of one fine-grained soil sample is determined using the H2SO4-HCIO digestion method, and the available phosphorus content of the other fine-grained soil sample is determined using the antimony-molybdenum colorimetric method. This completes the determination of the total phosphorus content and available phosphorus content of the soil in the alfalfa area.

[0028] In step S104, the amount of microbial fertilizer applied to each alfalfa area is determined based on the plant phosphorus content, total soil phosphorus content, and available soil phosphorus content. Specifically, a phosphorus use efficiency model is first constructed to calculate phosphorus use efficiency using plant phosphorus content, total soil phosphorus content, and available soil phosphorus content. (Phosphorus use efficiency) It is a key indicator for evaluating the level of phosphorus uptake and utilization in a region. It is related to the phosphorus content of plants. Soil total phosphorus content and soil available phosphorus content The following nonlinear relationship exists:

[0029]

[0030] in, This represents the phosphorus utilization efficiency of the i-th region. This represents the available phosphorus content in the soil of the i-th region. This represents the total phosphorus content of the soil in the i-th region. Let θ1 represent the phosphorus content of the plant in the i-th region, θ2 represent the first efficiency parameter with a value of 5, θ3 represent the second efficiency parameter with a value of 2, and θ4 represent the third efficiency parameter with a value of 3. It should be noted that parameters θ1, θ2, and θ3 can also be model parameters to be trained, and using the sigmoid function can effectively capture the influence of plant phosphorus content, total soil phosphorus content, and available soil phosphorus content on phosphorus use efficiency.

[0031] Furthermore, the phosphorus content of the plant This reflects the actual phosphorus uptake capacity of plants in the region; total phosphorus content in the soil. and available phosphorus content This reflects the soil's ability to supply phosphorus. By analyzing the relationship between these three indicators, phosphorus utilization efficiency can be assessed. The model parameters θ1, θ2, and θ3 can be determined by training historical data using machine learning algorithms (such as gradient descent).

[0032] Then, a constraint relationship between phosphorus use efficiency and microbial fertilizer application rate was established. Applying an appropriate amount of microbial fertilizer can promote the conversion of insoluble phosphorus in the soil into available phosphorus, thereby improving the absorption and utilization of phosphorus by plants. The applicant found through experiments that the appropriate amount of microbial fertilizer application rate (μ)... i With soil available phosphorus content The following logarithmic relationship exists between them:

[0033]

[0034] in, The available phosphorus content in the soil of region i is represented by μ. i Let β1 represent the amount of microbial fertilizer applied in the i-th region, β2 represent the first constraint parameter with a value of 50, and β2 represent the second constraint parameter with a value of 0.1. This also indicates that as the amount of microbial fertilizer applied increases, the available phosphorus content in the soil will gradually approach saturation.

[0035] Next, based on the phosphorus use efficiency model and the constraints, an optimization model for microbial fertilizer application rate is constructed, and an objective function is set to maximize the sum of phosphorus use efficiencies in all regions, thus obtaining the target microbial fertilizer application rate optimization problem. Specifically, this optimization problem can be described as follows:

[0036]

[0037] Here, N represents the number of soil regions. Specifically, the objective function is to maximize the sum of phosphorus use efficiency across all regions. The constraints are as follows: the phosphorus use efficiency of each region satisfies the pre-trained model; the available phosphorus content in the soil of each region satisfies a known logarithmic relationship with the amount of microbial fertilizer applied; and the amount of microbial fertilizer applied must be a non-negative number.

[0038] Because this optimization problem is a nonlinear programming problem, a target numerical optimization algorithm is used to solve the target microbial fertilizer application rate optimization problem to obtain the optimal microbial fertilizer application rate. In one embodiment, it can be solved using a numerical optimization algorithm (such as the interior point method, sequential quadratic programming, etc.). During the solution process, the known plant phosphorus content, soil total phosphorus content, and model parameters θ1, θ2, θ3, β1, and β2 for each region are required as input.

[0039] To illustrate this method more intuitively, we will analyze a specific alfalfa planting area as an example. This area is divided into 5 zones, and the relevant data for each zone are as follows:

[0040]

[0041] This application, through a series of experiments and machine learning training, obtained the following model parameter values: θ1=5, θ2=2, θ3=3, β1=50, β2=0.1. Substituting these data and parameters into the optimization model and using the sequential quadratic programming algorithm, the optimal application rate of microbial fertilizer can be obtained as follows:

[0042]

[0043]

[0044] The corresponding available phosphorus content in the soil is:

[0045]

[0046] By substituting the optimized available phosphorus content in the soil into the phosphorus use efficiency model, the phosphorus use efficiency of each region can be calculated:

[0047]

[0048] The total phosphorus use efficiency was 3.62, a 27% increase compared to 2.85 without microbial fertilizer application. This demonstrates that by establishing a mathematical model and optimizing calculations based on actual data, this application can accurately determine the optimal microbial fertilizer application rate for each region, thereby maximizing phosphorus use efficiency across the entire planting area. The model's advantages lie in its comprehensive consideration of three key factors: plant phosphorus content, total soil phosphorus content, and available soil phosphorus content; the use of machine learning methods to train the model parameters, resulting in a good fit to actual conditions; the modeling of microbial fertilizer application rate optimization as a mathematical programming problem, ensuring a rigorous solution process; and the ability to not only output the optimal microbial fertilizer application rate but also provide corresponding predicted values ​​for available soil phosphorus content and phosphorus use efficiency.

[0049] In step S105, the sensor equipment pre-installed in the alfalfa field is activated to acquire alfalfa growth environment information, and the daily irrigation amount for the alfalfa field is calculated using the growth environment information. To accurately control the irrigation amount in the alfalfa field and improve water resource utilization efficiency, various environmental sensors pre-installed in the field can be used to acquire key environmental parameters required for crop growth in real time, and mathematical models can be used to dynamically calculate and adjust the daily irrigation amount.

[0050] Specifically, firstly, the target meteorological data for the day is acquired from the sensors to calculate the water vapor parameter set for each field. In one embodiment, the following environmental sensors are installed in the alfalfa field: a soil moisture sensor to measure soil volumetric water content, reflecting soil moisture status; an air temperature and humidity sensor to measure air temperature and relative humidity, which can be used to calculate auxiliary parameters such as atmospheric saturation vapor pressure; a light sensor to measure solar radiation intensity, used to assess photosynthetic status; and a wind speed and direction sensor to detect wind speed and direction, used to estimate field water evaporation.

[0051] These sensors all employ wireless transmission technology, uploading detection data to a cloud server in real time. Simultaneously, several sets of identical sensors are installed in each field to ensure comprehensive coverage of the entire planting area. Then, the water vapor parameters are substituted into the Penman-Monteith equation to calculate the reference crop evapotranspiration for each field.

[0052] To calculate the daily irrigation amount based on sensor data, the following mathematical model was established in this embodiment: i: field number, taking values ​​of 1, 2, ..., N; I i Solar radiation intensity of the i-th field (W / m²) 2 );T i : Average temperature (°C) of the i-th field; RH i W represents the average relative humidity (%) of the i-th plot of land. i θ: Average wind speed of the i-th field (m / s); i : Average soil volumetric moisture content (%) of the i-th plot; ET i : Reference crop evapotranspiration (mm / day) for the i-th field; K c : Alfalfa crop coefficient, used to convert reference crop evapotranspiration into actual crop evapotranspiration; IR i : Daily irrigation amount (mm / day) for the i-th field.

[0053] Daily irrigation volume IR i Modeled as reference crop evapotranspiration ET i With alfalfa crop coefficient K c The product of, i.e.: IR i =K c ×ET i Among them, the reference crop evapotranspiration ET i Calculated using the FAO Penman-Monteith equation: This equation comprehensively considers the effects of various environmental factors such as radiation, temperature, humidity, and wind speed on evapotranspiration. Where: Δ is the slope of the saturated vapor pressure curve (kPa / ℃); R... n Net radiation on crop surface (MJ / m²) 2 / day; G is the soil heat flux density in MJ / m³ 2 / day; γ is a constant 0.067 kPa / ℃; T i U1 is the average temperature (°C) of the i-th field; U2 is the wind speed (m / s) at a height of 2m; e s It is the saturated vapor pressure in kPa; e a It is the actual water vapor pressure in kPa.

[0054] The above parameters can be calculated using sensor measurement data through a series of auxiliary equations. For example:

[0055]

[0056] R n =R ns -R nl ,

[0057] Where R ns and R nl These are shortwave radiation and longwave radiation, respectively, which can be determined by solar radiation intensity I. i It was obtained from estimations of other environmental parameters.

[0058] As for the crop coefficient K c This requires establishing empirical formulas or finding existing reference value tables based on extensive field experimental data, combined with factors such as crop growth stage and vegetation cover. Generally speaking, for medium-sized crops like alfalfa, its K... c The value is approximately 0.4 in the early stage of growth, approximately 1.0 in the middle stage, and approximately 0.6 in the later stage.

[0059] Secondly, based on the reference crop evapotranspiration and alfalfa crop coefficient, the daily irrigation amount for each field is calculated. In general, the specific steps for calculating the daily irrigation amount are as follows: Obtain the daily solar radiation intensity I from each sensor. i Average temperature T i Average relative humidity (RH) i Average wind speed W_i and average soil volumetric water content θ i Data; using the above auxiliary equations, the saturated vapor pressure e of each field is calculated. s Actual water vapor pressure e a , Slope Δ of saturated water vapor pressure curve, Net radiation R n Intermediate parameters; substitute these intermediate parameters into the Penman-Monteith equation to calculate the reference crop evapotranspiration for each field; based on the crop growth stage, consult or estimate the current alfalfa crop coefficient; and convert ET... i and K c Substitute into the formula IR i =K c ×ET iThis allows us to obtain the daily irrigation amount IR for the i-th field. i .

[0060] To illustrate the calculation process more clearly, we will use a specific field as an example. Assume the environmental parameter measurements for that field on that day were:

[0061] Solar radiation intensity I = 650 W / m 2 The average temperature T = 28℃; the average relative humidity RH = 65%; the average wind speed W = 1.8 m / s; the average soil volumetric moisture content θ = 25%; meanwhile, alfalfa is currently in the mid-growth stage, with a crop coefficient K... c =1.0. First, calculate the auxiliary parameters based on the measured values:

[0062]

[0063] Let R ns =20MJ / m 2 / day, R nl =5MJ / m 2 / day, G=0, then: R n =R ns -R nl =20-5=15MJ / m 2 / day.

[0064] Substituting the above intermediate parameters into the Penman-Monteith equation:

[0065]

[0066] Finally, the reference crop evapotranspiration and crop coefficient are substituted into the formula: IR = K c ×ET=1.0×5.83=5.83mm / day.

[0067] Therefore, under the above environmental conditions, the daily irrigation amount for alfalfa in this field should be controlled at around 5.83 mm / day.

[0068] In step S106, a fertilizer solution for the drip irrigation fertilization system is prepared based on the amount of microbial fertilizer applied and the daily irrigation volume. This fertilizer solution is used for irrigation fertilization of alfalfa fields to achieve the application of microbial fertilizer that promotes phosphorus absorption by alfalfa. To promote phosphorus absorption and utilization by alfalfa, microbial fertilizer containing phosphorus-dissolving bacteria can be applied, and the fertilizer solution, which is a mixture of microbial fertilizer and chemical fertilizer, is evenly delivered to the field through the drip irrigation system, achieving precise and efficient irrigation fertilization.

[0069] Specifically, firstly, the microbial fertilizer and compound fertilizer are dissolved in batches to prepare a low-concentration mother liquor, which is used to prepare the required fertilizer solution; then, the target volume of the mother liquor is determined according to the amount of microbial fertilizer applied and the daily irrigation amount, and the target volume of the mother liquor is added to the daily irrigation amount of water to obtain the fertilizer solution; finally, the fertilizer solution is divided into equal portions for a preset application cycle, so that one portion of the fertilizer solution is applied in each cycle.

[0070] In one implementation scenario, the first step is to determine the required amount of microbial fertilizer per hectare of field based on the growth status of alfalfa and the soil phosphorus content. Through field surveys and soil testing, the following data was obtained: Alfalfa phosphorus requirement: 60 kg / hm² 2 Soil available phosphorus content: 20 mg / kg; Number of phosphorus-solubilizing bacteria in microbial fertilizer: 10 8 CFU / g; Available phosphorus content in the microbial fertilizer: 8%. Therefore, the application rate M of microbial fertilizer per hectare of field can be calculated using the following formula: For ease of calculation, we take M = 7500 kg / hm. 2 = 750 kg / hectare.

[0071] Based on the model for calculating daily irrigation volume using environmental sensor data introduced earlier, let's assume the measured environmental parameters for a certain field on a given day are: solar radiation intensity I = 650 W / m². 2 The average temperature T = 28℃; the average relative humidity RH = 65%; the average wind speed W = 1.8 m / s; the average soil volumetric moisture content θ = 25%. Meanwhile, the alfalfa in this field is currently in the mid-to-late growth stage, and the crop coefficient K... c = 0.8. Following the aforementioned calculation steps, we can obtain:

[0072] e s =3.37kPa

[0073] e a =2.36kPa

[0074] Δ=0.221kPa / ℃,

[0075] R n = 16 MJ / m 2 / day

[0076] Substituting these intermediate parameters into the Penman-Monteith equation, the evapotranspiration of the reference crop can be calculated: Multiplying the reference crop evapotranspiration by the crop coefficient yields the irrigation amount for that field on that day: IR = K c ×ET=0.8×5.12=4.10mm / day. Converted to volume units, the daily irrigation volume per hectare is: V=IR×10000m³2 / hm 2 =4.10 × 10000 = 41000 L / hm 2 =41m 3 / hm 2 .

[0077] Next, prepare the drip irrigation fertilizer solution. To achieve the combined application of microbial fertilizer and chemical fertilizer, the microbial fertilizer can be dissolved in water first, and then an appropriate amount of compound fertilizer can be added. Assume the selected compound fertilizer is N:P₂O₅:K₂O = 15:15:15, and the required application rates of nitrogen, phosphorus, and potassium are as follows:

[0078] Nitrogen (N) requirement: 180 kg / hm 2 Phosphorus (P2O5) requirement: 90 kg / hm 2 Potassium (K2O) requirement: 120 kg / hm² 2 The application rate of compound fertilizer is:

[0079]

[0080] To avoid excessive fertilizer concentration affecting crop growth, microbial fertilizer and compound fertilizer can be dissolved in batches to prepare a low-concentration "mother liquor" first, and then the mother liquor can be used to prepare the required fertilizer solution.

[0081] Assume that in the first step, 1 / 4 of the microbial fertilizer and compound fertilizer are dissolved in 10ml 3 In water, the concentration of microbial fertilizer in the "mother liquor" is: The concentration of compound fertilizer is:

[0082] Then, prepare the fertilizer solution according to the daily irrigation volume of 41m³. 3 / hm 2 Calculate the volume of mother liquor required to prepare the fertilizer solution based on the total application amount of microbial fertilizer and compound fertilizer.

[0083] The total amount of microbial fertilizer used is 750 kg / hm. 2 Then the mother liquor is required: The total amount of compound fertilizer used was 2600 kg / hm. 2 Then the mother liquor is required: Add these two portions of mother liquor to 41m 3 The daily irrigation water volume can be used to obtain a fertilizer solution containing microbial fertilizer and compound fertilizer. At the same time, in order to ensure that the microbial fertilizer and compound fertilizer are fully mixed, a stirring device can be installed in the mixing tank, or two delivery lines can be used to separately deliver the microbial fertilizer mother liquor and the compound fertilizer mother liquor to the mixer for even mixing, and then the fertilizer solution can be evenly delivered to the field through the drip irrigation system.

[0084] Because the total application amount of microbial fertilizer and compound fertilizer is relatively large, applying it all at once would result in excessively high fertilizer concentrations, which would negatively impact crop growth. Therefore, the total application amount can be divided into batches, meaning that only a portion of the fertilizer solution is prepared each time and applied in several cycles.

[0085] In one embodiment, assuming the total application amount is divided into 5 equal parts, and 1 / 5 of the fertilizer amount is applied in each cycle, then the fertilizer application amount in each cycle is: Microbial fertilizer application amount: Compound fertilizer application rate: Calculated using the aforementioned method, the fertilizer solution to be prepared for each cycle contains: microbial fertilizer mother liquor: Compound fertilizer mother liquor: Use these 16m 3 The mother liquor was added to 41m 3 The fertilizer solution for that cycle can be obtained from the daily irrigation water volume.

[0086] By repeating this cycle five times, the total amount of microbial fertilizer and compound fertilizer can be applied to the field. A 7-10 day interval can be allowed between each cycle to give the crops sufficient time to absorb and utilize the applied nutrients.

[0087] Through the above process, the application rates of microbial fertilizer and chemical fertilizer can be scientifically and rationally determined, and a suitable drip irrigation fertilizer solution can be prepared based on factors such as daily irrigation volume and crop growth stage, enabling refined irrigation and fertilization operations for alfalfa fields.

[0088] This precision fertilization model based on environmental data can not only effectively promote the absorption and utilization of phosphorus by alfalfa, but also avoid resource waste and environmental pollution caused by excessive fertilization, thus having high economic and ecological value.

[0089] Of course, in practical applications, the fertilization plan needs to be adjusted appropriately according to the specific situation. At the same time, attention should be paid to regularly monitoring crop growth and soil nutrient changes, and timely feedback and adjustments should be made in order to obtain the best fertilization effect.

[0090] Figure 2 This is a schematic block diagram of a microbial fertilizer application system for promoting phosphorus absorption in alfalfa, provided as an embodiment of this application. It should be understood that the system shown in the figure is exemplary and not restrictive. This means that the system architecture involved is not limited to a specific form or design, but is presented as an example. In other words, the architecture shown in the figure can be considered as a way of expressing related concepts and relationships clearly, and does not exclude other forms of architecture. Therefore, when interpreting the architecture in the figure, it should be understood that the model is flexible and diverse, and its purpose is to provide an exemplary description, not a restrictive provision on a specific form.

[0091] Specifically, the system includes a sampling unit 201, an optimization unit 202, and a configuration unit 203. The sampling unit 201 receives irrigation and fertilization instructions to promote phosphorus absorption in alfalfa, divides the alfalfa field into grids according to the instructions, obtaining multiple alfalfa regions; sequentially samples alfalfa plants within each region to determine the phosphorus content of the plants; and sequentially samples soil samples from each region to determine the total phosphorus content and available phosphorus content of the soil. The optimization unit 202 determines the amount of microbial fertilizer to be applied to each alfalfa region based on the plant phosphorus content, total soil phosphorus content, and available soil phosphorus content. The configuration unit 203 is used to activate the sensor equipment pre-installed in the alfalfa field to obtain the growth environment information of alfalfa, and to calculate the daily irrigation amount of the alfalfa field using the growth environment information; and to prepare the fertilizer solution of the drip irrigation fertilization system based on the amount of microbial fertilizer applied and the daily irrigation amount. The fertilizer solution is used to perform irrigation fertilization on the alfalfa field to complete the application of microbial fertilizer to promote phosphorus absorption by alfalfa.

[0092] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0093] It should also be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0094] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for promoting phosphorus uptake by alfalfa using bacterial inoculants, characterized by, The method comprises the following steps: receiving irrigation and fertilization instructions for promoting phosphorus absorption of alfalfa, performing grid division on an alfalfa field according to the irrigation and fertilization instructions to obtain a plurality of alfalfa regions; sequentially performing plant sampling of alfalfa on the alfalfa regions to obtain plant phosphorus contents of the alfalfa regions; sequentially performing soil sampling of alfalfa on the alfalfa regions to obtain soil total phosphorus contents and soil available phosphorus contents of the alfalfa regions; determining a microbial fertilizer application amount of each of the alfalfa regions based on the plant phosphorus contents, the soil total phosphorus contents and the soil available phosphorus contents; starting a sensor device previously installed in the alfalfa field to obtain growth environment information of the alfalfa, and calculating a daily irrigation amount of the alfalfa field by using the growth environment information; preparing a fertilizer solution of a drip irrigation and fertilization system based on the microbial fertilizer application amount and the daily irrigation amount, wherein the fertilizer solution is used for irrigation and fertilization of the alfalfa field to complete microbial fertilizer application for promoting phosphorus absorption of the alfalfa; the method for determining the microbial fertilizer application amount of each of the alfalfa regions based on the plant phosphorus contents, the soil total phosphorus contents and the soil available phosphorus contents comprises: constructing a phosphorus utilization efficiency model to calculate phosphorus utilization efficiency by using the plant phosphorus contents, the soil total phosphorus contents and the soil available phosphorus contents; constructing a constraint relationship between the phosphorus utilization efficiency and the microbial fertilizer application amount; constructing a microbial fertilizer application amount optimization model based on the phosphorus utilization efficiency model and the constraint relationship, and setting a target function of maximizing a sum of phosphorus utilization efficiencies of all regions to obtain a target microbial fertilizer application amount optimization problem; solving the target microbial fertilizer application amount optimization problem by using a target numerical optimization algorithm to obtain an optimal microbial fertilizer application amount.

2. The method of claim 1, wherein the bacteria are applied to the plant at a concentration of about 1 x 10" to about 1 x 10" bacteria per gram of plant material. wherein the method for starting the sensor device previously installed in the alfalfa field to obtain the growth environment information of the alfalfa, and calculating the daily irrigation amount of the alfalfa field by using the growth environment information comprises: obtaining target meteorological data of the day in the sensor to calculate a water vapor parameter set of each field; substituting the water vapor parameter set into a Penman-Monteith equation to calculate a reference crop evapotranspiration of each field; calculating a daily irrigation amount of each field based on the reference crop evapotranspiration and a crop coefficient of alfalfa.

3. The method of claim 1, wherein the bacteria are applied to the plant at a concentration of about 1 x 10" to about 1 x 10" bacteria per gram of plant. wherein the method for preparing the fertilizer solution of the drip irrigation and fertilization system based on the microbial fertilizer application amount and the daily irrigation amount, wherein the fertilizer solution is used for irrigation and fertilization of the alfalfa field to complete microbial fertilizer application for promoting phosphorus absorption of the alfalfa comprises: dissolving the microbial fertilizer and the compound fertilizer in batches to prepare a mother liquor with a low concentration, wherein the mother liquor is used for preparing the required fertilizer solution; determining a target volume of the mother liquor according to the microbial fertilizer application amount and the daily irrigation amount, and adding the mother liquor with the target volume into water with the daily irrigation amount to obtain the fertilizer solution; dividing the fertilizer solution into equal parts for each application period to apply one part of the fertilizer solution in each period.

4. The method of claim 1, wherein the bacteria are applied to the plant at a concentration of about 1 x 10" to about 1 x 10" bacteria per gram of plant. wherein the method for constructing the phosphorus utilization efficiency model to calculate the phosphorus utilization efficiency by using the plant phosphorus contents, the soil total phosphorus contents and the soil available phosphorus contents comprises: ， wherein, represents the phosphorus use efficiency of the i-th region, represents the soil available phosphorus content of the i-th region, represents the soil total phosphorus content of the i-th region, represents the plant phosphorus content of the i-th region, represents a first efficiency parameter, having a value of 5, represents a second efficiency parameter, having a value of 2, represents a third efficiency parameter, having a value of 3.

5. The method according to claim 4, wherein the bacteria are applied to the plant in the form of a bacterial inoculant. wherein Construct a constraint relationship of phosphorus utilization efficiency and microbial fertilizer application amount, including: ， wherein, represents the soil available phosphorus content of the i-th region, represents the manure application amount of the i-th region, represents the first constraint parameter, and takes a value of 50, represents the second constraint parameter, and takes a value of 0.

1.

6. The method of claim 5, wherein the bacteria are applied to the plant at a concentration of about 1 x 10<5> to about 1 x 10<9> colony forming units per gram of plant. Wherein, Based on the phosphorus utilization efficiency model and the constraint relationship, a microbial fertilizer application amount optimization model is constructed, and a target function of maximizing the sum of phosphorus utilization efficiency of all regions is set to obtain a target microbial fertilizer application amount optimization problem, including: ， wherein, represents the number of soil regions.

7. A bacterial fertilizer application system for promoting phosphorus uptake of alfalfa, for implementing the bacterial fertilizer application method for promoting phosphorus uptake of alfalfa according to claim 1, characterized by, Including: A sampling unit, an optimization unit and a configuration unit; wherein, The sampling unit is used to receive irrigation and fertilization instructions for promoting phosphorus absorption of alfalfa, perform grid division on alfalfa fields according to the irrigation and fertilization instructions, obtain a plurality of alfalfa regions, and perform plant sampling of alfalfa on the alfalfa regions in turn to determine plant phosphorus content of the alfalfa regions; soil sampling of alfalfa is performed on the alfalfa regions in turn, and soil total phosphorus content and soil available phosphorus content of the alfalfa regions are determined; The optimization unit is used to determine the microbial fertilizer application amount of each alfalfa region based on the plant phosphorus content, soil total phosphorus content and soil available phosphorus content; The configuration unit is used to start the sensor device installed in the alfalfa field in advance, obtain growth environment information of alfalfa, and calculate the daily irrigation amount of the alfalfa field by using the growth environment information; based on the microbial fertilizer application amount and the daily irrigation amount, a fertilizer solution of a drip irrigation and fertilization system is prepared, and the fertilizer solution is used for irrigation and fertilization of the alfalfa field to complete the application of microbial fertilizer for promoting phosphorus absorption of alfalfa.

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