Intelligent decision-making system for water and fertilizer integrated regulation and control of compound substrate

Abstract

The invention discloses an intelligent decision-making system for compound substrate water and fertilizer integrated regulation and control, relates to the technical field of water and fertilizer integrated regulation and control, and aims to solve the problems that the water and fertilizer utilization efficiency is reduced and the resource waste risk is increased. Setting a plurality of groups of soil layer heights to detect the conductivity of a matrix, evaluating the fertilizer sprinkling stall rate according to the matrix conductivity, analyzing water utilization characteristics by combining a water taking coefficient, collecting the total amount of leachate and fertilizer at the bottom of a tank, screening a target cultivation area by combining the water utilization characteristics and the total amount of the leachate, marking the water-fertilizer ratio, and implementing irrigation. Statistical time is set to monitor the sugar degree of the fruits, whether the water and fertilizer proportion is stored in the proportion library or not is judged according to the result, accurate water and fertilizer management is achieved, it is ensured that the water and fertilizer utilization efficiency of a cultivation area is maximized, the crop yield and quality are improved, and meanwhile resource waste is reduced.

Description

Technical Field

[0001] This invention relates to the field of integrated water and fertilizer regulation technology, and more specifically, to an intelligent decision-making system for integrated water and fertilizer regulation of composite substrates. Background Technology

[0002] With the development of modern facility agriculture, fertigation technology has gradually become an important measure to improve crop yield and quality. The traditional fertigation model mainly delivers water and fertilizer to the root zone simultaneously through irrigation networks. However, in complex substrate environments (such as composite substrates like rock wool, coconut coir, and peat), the water absorption characteristics of crop roots, the changes in electrical conductivity of substrate layers, and the leaching patterns of fertilizers are highly dynamic and vary regionally.

[0003] The existing technology has the following shortcomings:

[0004] Currently, existing technologies rely on empirical irrigation parameter regulation, lacking joint analysis of crop root-strip data and substrate stratified electrical conductivity. This makes it impossible to accurately assess water use characteristics and fertilizer leaching rates, leading to reduced water and fertilizer utilization efficiency and increased risk of resource waste. Therefore, an intelligent decision-making system for integrated water and fertilizer regulation of composite substrates is proposed.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide an intelligent decision-making system for integrated water and fertilizer regulation of composite substrates. This system solves the problems mentioned in the background art by employing a combined modeling method that combines root-tiller parameter calculation, substrate stratified conductivity monitoring, and leachate fertilizer quantity analysis.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an intelligent decision-making system for integrated water and fertilizer regulation in a composite substrate, comprising a data acquisition module, a moisture analysis module, an evaluation and labeling module, and an irrigation monitoring module, the functions of which are as follows:

[0008] The data acquisition module is used to detect different water and fertilizer ratios in cultivation areas, measure the root-shrimp data of crops in each cultivation area, use the root-shrimp data to evaluate the crop water uptake coefficient, set multiple soil layer heights, detect the matrix conductivity of each soil layer height in the cultivation area, and transmit the crop water uptake coefficient and matrix conductivity to the water analysis module.

[0009] The water analysis module receives the matrix conductivity of each soil layer height in the cultivation area and analyzes the fertilizer leaching rate of the cultivation area. It combines the crop water intake coefficient to evaluate the water use characteristics of the cultivation area, collects the total amount of leachate fertilizer at the bottom of the cultivation area, and transmits the water use characteristics and the total amount of leachate fertilizer to the evaluation and labeling module.

[0010] After receiving the total amount of leachate fertilizer, the evaluation and labeling module evaluates the fertilizer utilization characteristics of the cultivation area, integrates water use characteristics and fertilizer use characteristics to screen target cultivation areas, and marks the water and fertilizer ratio in the target cultivation area and transmits it to the irrigation monitoring module.

[0011] The irrigation monitoring module uses the marked water-fertilizer ratio to irrigate various cultivation areas, sets the statistical time, monitors the fruit sugar content data of crops in each cultivation area, and determines whether to store the water-fertilizer ratio in the water-fertilizer ratio database based on the monitoring results.

[0012] In a preferred embodiment, the data acquisition module distinguishes and detects cultivation areas based on different water-fertilizer ratios;

[0013] Root-stem data for crops in various cultivation regions include root-stem mass and root length density.

[0014] The root dry mass of the crop samples was obtained by weighing the root system of the pretreated and dried crop samples using a precision electronic balance.

[0015] The total root length of crop samples was obtained using high-precision optical scanning technology;

[0016] The ratio of the total root length of the crop sample to the preset sampling volume is used as the root length density of the crop sample.

[0017] In a preferred embodiment, the root dry mass and root length density of crop samples are standardized in the data acquisition module to obtain a quality factor and a density factor.

[0018] The crop water intake coefficient for each cultivation area was calculated by combining quality factors and density factors.

[0019] Multiple soil layer heights and fixed sampling time intervals were set, and the matrix conductivity of each soil layer height in each cultivation area was obtained using a conductivity meter.

[0020] In a preferred embodiment, in the moisture analysis module, the ratio of the absolute value of the difference between the matrix conductivity of each group of soil layers in each cultivation area at adjacent sampling times to the fixed sampling time interval is used as the rate of change of conductivity of each group of soil layers in each cultivation area.

[0021] The fertilizer leaching rate of each soil layer height in each cultivation area is obtained by multiplying the rate of change of electrical conductivity of each soil layer height in each cultivation area by the calibration coefficient.

[0022] The fertilizer leaching rate for each cultivation area was obtained by averaging the fertilizer leaching rate at each soil layer height in each cultivation area.

[0023] In a preferred embodiment, in the water analysis module, the crop water intake coefficient and fertilizer leaching rate of each cultivation area are normalized according to the Max-Min normalization method to obtain the water intake factor and leaching factor.

[0024] Water use characteristics of each cultivation area were calculated by combining water intake and leaching factors.

[0025] In a preferred embodiment, in the moisture analysis module, the concentrations of nitrogen, phosphorus, and potassium ions in the leachate are obtained based on nitrogen, phosphorus, and potassium ion selection sensors.

[0026] The fertilizer concentration in the leachate is obtained by adding the ion concentrations of nitrogen, phosphorus, and potassium in the leachate.

[0027] The total amount of fertilizer in the leachate at the bottom of the tank in each cultivation area is calculated by multiplying the fertilizer concentration in the leachate by the weight of the leachate in the collection container of each cultivation area.

[0028] In a preferred embodiment, the total amount of fertilizer applied in each cultivation area is obtained in the evaluation marking module by means of a fertilizer database;

[0029] The total amount of fertilizer applied in each cultivation area was subtracted from the total amount of leachate fertilizer at the bottom of the trough, and the ratio of the difference to the total amount of fertilizer applied in each cultivation area was used as the fertilizer utilization characteristic of each cultivation area.

[0030] Water use and fertilizer use characteristics of different cultivation areas were normalized to obtain water factor and fertilizer factor.

[0031] In a preferred embodiment, the water-fertilizer synergy index for each cultivation area is calculated by integrating water and fertilizer factors in the evaluation labeling module.

[0032] If the water-fertilizer synergy index of each cultivation area is less than or equal to the preset water-fertilizer synergy threshold, then the cultivation area is not the target cultivation area.

[0033] If the water-fertilizer synergy index of each cultivation area is greater than the preset water-fertilizer synergy threshold, then the cultivation area is the target cultivation area.

[0034] The water and fertilizer ratios in the target cultivation areas are marked.

[0035] In a preferred embodiment, the irrigation monitoring module performs irrigation treatment on each cultivation area according to the marked water-fertilizer ratio;

[0036] Set the statistical time period and acquire fruit sugar content data of crops in various cultivation areas through near-infrared spectral sensors;

[0037] If the fruit sugar content data of crops in each cultivation area are all greater than the preset fruit sugar content threshold, then it is determined that the marked water and fertilizer ratio will be stored in the water and fertilizer ratio database.

[0038] If the fruit sugar content data of crops in each cultivation area is less than or equal to the preset fruit sugar content threshold, it is determined that the marked water and fertilizer ratio will not be stored in the water and fertilizer ratio database.

[0039] The technical effects and advantages of this invention are as follows:

[0040] This invention involves testing cultivation areas with different water-fertilizer ratios, measuring crop root-stalk data in each area, evaluating crop water uptake coefficient using the root-stalk data, setting multiple soil layer heights and measuring the matrix conductivity of each soil layer, assessing fertilizer leaching rate based on matrix conductivity, and evaluating water use characteristics in conjunction with the crop water uptake coefficient. It also collects the total amount of fertilizer in the leachate from the bottom of the cultivation area, selects target cultivation areas based on water use characteristics and total leachate fertilizer amount, marks the water-fertilizer ratios, irrigates according to the marked ratios, sets statistical time intervals, monitors crop fruit sugar content data, and determines whether to store the water-fertilizer ratio in a water-fertilizer ratio database based on the monitoring results. This achieves precise water and fertilizer management, ensuring maximum water and fertilizer utilization efficiency in the cultivation area, improving crop yield and quality, and reducing resource waste. Attached Figure Description

[0041] Figure 1 This is a flowchart illustrating the implementation of an intelligent decision-making system for integrated water and fertilizer regulation of a composite substrate, as described in this invention.

[0042] Figure 2 This is a schematic diagram of a module of an intelligent decision-making system for integrated water and fertilizer regulation of a composite substrate according to the present invention. Detailed Implementation

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] This invention involves testing cultivation areas with different water-fertilizer ratios, measuring crop root-stalk data in each area, evaluating crop water uptake coefficient using the root-stalk data, setting multiple soil layer heights and measuring the matrix conductivity of each soil layer, assessing fertilizer leaching rate based on matrix conductivity, and evaluating water use characteristics in conjunction with the crop water uptake coefficient. It also collects the total amount of fertilizer in the leachate from the bottom of the cultivation area, selects target cultivation areas based on water use characteristics and total leachate fertilizer amount, marks the water-fertilizer ratios, irrigates according to the marked ratios, sets statistical time intervals, monitors crop fruit sugar content data, and determines whether to store the water-fertilizer ratio in a water-fertilizer ratio database based on the monitoring results. This achieves precise water and fertilizer management, ensuring maximum water and fertilizer utilization efficiency in the cultivation area, and improving crop yield and quality.

[0045] Example 1: An intelligent decision-making system for integrated water and fertilizer regulation in a composite substrate, such as... Figures 1 to 2 As shown, it includes a data acquisition module, a moisture analysis module, an assessment and marking module, and an irrigation monitoring module. The modules interact with each other through signal connections.

[0046] The functions of each module are as follows:

[0047] The data acquisition module is used to detect different water and fertilizer ratios in cultivation areas, measure the root-shrimp data of crops in each cultivation area, use the root-shrimp data to evaluate the crop water uptake coefficient, set multiple soil layer heights, detect the matrix conductivity of each soil layer height in the cultivation area, and transmit the crop water uptake coefficient and matrix conductivity to the water analysis module.

[0048] The water analysis module receives the matrix conductivity of each soil layer height in the cultivation area and analyzes the fertilizer leaching rate of the cultivation area. It combines the crop water intake coefficient to evaluate the water use characteristics of the cultivation area, collects the total amount of leachate fertilizer at the bottom of the cultivation area, and transmits the water use characteristics and the total amount of leachate fertilizer to the evaluation and labeling module.

[0049] After receiving the total amount of leachate fertilizer, the evaluation and labeling module evaluates the fertilizer utilization characteristics of the cultivation area, integrates water use characteristics and fertilizer use characteristics to screen target cultivation areas, and marks the water and fertilizer ratio in the target cultivation area and transmits it to the irrigation monitoring module.

[0050] The irrigation monitoring module uses the marked water-fertilizer ratio to irrigate various cultivation areas, sets the statistical time, monitors the fruit sugar content data of crops in each cultivation area, and determines whether to store the water-fertilizer ratio in the water-fertilizer ratio database based on the monitoring results.

[0051] The specific implementation is as follows:

[0052] In the data acquisition module, cultivation areas are differentiated and tested based on different water and fertilizer ratios;

[0053] Root-dry data of crops in various cultivation areas refers to a set of quantitative information that characterizes the dry matter state, distribution characteristics and water absorption potential of crop roots in the soil, including the root-dry mass and root length density of crops.

[0054] Crop samples from various cultivation areas were collected on-site at a predetermined sampling volume. The original sampling method was used to ensure the integrity of the sample structure. After sampling, the crop samples were sealed to avoid moisture evaporation or structural disturbance from affecting the test results.

[0055] The collected crop samples were brought into the laboratory environment for pretreatment, including separating the roots of the crop samples from the soil, cleaning them, removing impurities and soil clods, and placing them under standard maintenance temperature conditions.

[0056] After pretreatment, the roots of the crop samples were dried in an electric constant temperature drying oven, and the root dry mass of the crop samples was obtained by weighing the roots of the crop samples using a precision electronic balance.

[0057] Furthermore, the total root length of the crop sample was obtained using high-precision optical scanning technology;

[0058] The ratio of the total root length of the crop sample to the preset sampling volume is used as the root length density of the crop sample.

[0059] It should be noted that the preset sampling volume refers to the standardized sampling space volume pre-set for the crop roots and surrounding substrate in each cultivation area during the on-site collection process. The depth is taken as 80% to 100% of the main distribution depth of the crop roots as a benchmark, and the length and width are usually 10 to 15 cm based on the operability of manual handling and weighing. The electric heating constant temperature drying oven is a laboratory device that uses electric heating elements to provide a stable heat source and maintains the set temperature through an automatic temperature control system. It is used to dry the roots of crop samples to constant weight. The precision electronic balance is a laboratory device that uses the principle of electromagnetic force balance to achieve high-precision mass measurement. It is used to weigh the roots of crop samples. High-precision optical scanning technology uses a high-resolution imaging system and optical sensing principle to capture two-dimensional or three-dimensional images of the roots under specific optical conditions and automatically analyze the images to directly obtain the length of the roots, which is used to obtain the total root length of the crop sample.

[0060] The root dry weight and root length density of crop samples were standardized to obtain the quality factor and density factor.

[0061] The crop water intake coefficient for each cultivation area is calculated by combining the quality factor and density factor. The calculation formula is as follows: ,in, For quality factor, Density factor The crop water intake coefficient for each cultivation area;

[0062] It should be noted that the greater the root mass and the smaller the root length density, the richer the root dry matter, the more concentrated the root distribution, the stronger the water absorption capacity, and the greater the crop water extraction coefficient in each cultivation area. Conversely, the smaller the root mass and the greater the root length density, the scarcer the root dry matter, the more dispersed the root distribution, the weaker the water absorption capacity, and the smaller the crop water extraction coefficient in each cultivation area.

[0063] Multiple soil layer heights and fixed sampling time intervals were set up. The matrix conductivity of each soil layer height in each cultivation area was obtained using a conductivity meter. The matrix conductivity characterizes the soil layer's ability to conduct electric current and reflects the content of soluble salt ions in the soil layer. The higher the matrix conductivity, the higher the content of soluble salts in the soil layer, and the greater the fertilizer solubility and salt accumulation level; conversely, it indicates that the soil layer has a lower salt content, and the lower the fertilizer solubility and salt accumulation level.

[0064] It needs to be explained that multiple soil layer heights refer to dividing the soil profile in a cultivation area into several relatively independent depth layers vertically according to a preset depth range, with 15cm as a basic stratification unit, and stratifying sequentially within the total depth range, such as 0 to 15cm, 15 to 30cm, etc.; fixed sampling interval refers to the method of measuring or recording data on the same object at the same preset time interval during continuous monitoring, which is set according to the rate of change of the monitored object. For example, when monitoring the matrix conductivity of each soil layer height in each cultivation area, it can be set to 10 to 30 minutes; conductivity meter is an instrument for measuring the conductivity of soil, cultivation substrate or leachate, used to obtain the matrix conductivity of each soil layer height in each cultivation area.

[0065] In the moisture analysis module, the ratio of the absolute value of the difference between the matrix conductivity of each group of soil layers in each cultivation area at adjacent sampling times to the fixed sampling time interval is used as the rate of change of conductivity of each group of soil layers in each cultivation area.

[0066] The fertilizer leaching rate of each soil layer height in each cultivation area is obtained by multiplying the rate of change of electrical conductivity of each soil layer height in each cultivation area by the calibration coefficient.

[0067] The fertilizer leaching rate of each cultivation area was obtained by averaging the fertilizer leaching rate of each soil layer height in each cultivation area.

[0068] It should be noted that the calibration coefficient is an important parameter reflecting the relationship between the rate of change of conductivity and the rate of fertilizer leaching. This coefficient was determined through previous calibration experiments. The rate of change of conductivity in multiple cultivation areas was selected, and under the same experimental conditions, the actual fertilizer leaching rate of the corresponding cultivation area was obtained by measuring the actual amount of fertilizer carried away by the leachate within a fixed time period. The calibration coefficient was obtained based on the ratio between the rate of change of conductivity in each cultivation area and the actual fertilizer leaching rate of the corresponding cultivation area. At the same time, the water and fertilizer retention capacity of compound fertilizers varies greatly, and the calibration coefficient is related to the fertilizer type. The experiment was conducted in groups according to fertilizer type.

[0069] The crop water uptake coefficient and fertilizer leaching rate for each cultivation area were normalized using the Max-Min normalization method to obtain the water uptake factor and leaching factor. The calculation formula is as follows:

[0070] , ;

[0071] in, and These represent the crop water uptake coefficient and fertilizer leaching rate for each cultivation region. and These represent the minimum and maximum values ​​of the crop water intake coefficient for each cultivation region. and These represent the minimum and maximum fertilizer leaching rates for each cultivation region. and These are water intake factor and leaching factor, respectively;

[0072] The water use characteristics of each cultivation area were calculated by combining water intake and leaching factors. The calculation formula is as follows: ,in, For water intake factors, It is a leukemia loss factor. Water use characteristics of different cultivation areas;

[0073] It should be noted that the higher the crop water uptake coefficient in each cultivation area, the slower the fertilizer leaching rate, the more efficient the crop absorbs water, the less water is lost, and the greater the water use characteristics of each cultivation area; conversely, the lower the crop water uptake coefficient in each cultivation area, the faster the fertilizer leaching rate, the weaker the crop absorption capacity, the more water is lost, and the smaller the water use characteristics of each cultivation area.

[0074] Drainage channels are set at the bottom of the troughs in each cultivation area to introduce leachate into collection containers in each cultivation area;

[0075] The weight of the leachate in the collection containers of each cultivation area was obtained using a weight sensor;

[0076] The concentrations of nitrogen, phosphorus, and potassium ions in the leachate are obtained by selecting sensors based on nitrogen, phosphorus, and potassium ions.

[0077] The fertilizer concentration in the leachate is obtained by adding the ion concentrations of nitrogen, phosphorus, and potassium in the leachate.

[0078] The total amount of fertilizer in the leachate at the bottom of the tank in each cultivation area is calculated by multiplying the fertilizer concentration in the leachate by the weight of the leachate in the collection container of each cultivation area.

[0079] It needs to be explained that a gravimetric sensor is a sensor that measures the mass or weight of an object, used to obtain the weight of leachate in collection containers in various cultivation areas; a nitrogen, phosphorus, and potassium ion selective sensor is a sensor that detects the concentration of specific ions in an aqueous solution in real time and online, used to obtain the ion concentration of nitrogen, phosphorus, and potassium in the leachate; the fertilizer concentration in the leachate refers to the total content of soluble nutrients in the leachate, used to reflect the amount of fertilizer carried away by water loss in the soil or cultivation substrate, and is the sum of the concentrations of all major nutrient element ions in the leachate, including the ion concentrations of nitrogen, phosphorus, and potassium in the leachate; when calculating the fertilizer concentration in the leachate, the effectiveness of different ion forms is distinguished, and only the concentration of effective ion forms is included in the calculation to accurately reflect the actual amount of fertilizer that crops can absorb. Effective forms are ion forms that can be directly absorbed by crop roots or quickly converted into absorbable forms in the soil, thus actually participating in the crop nutrition process. This is determined based on long-term experimental research in agricultural chemistry and plant nutrition, conclusions on crop absorption mechanisms, and the recognized provisions of current national or industry fertilizer testing standards, which will not be elaborated here.

[0080] In the evaluation and labeling module, the total amount of fertilizer applied in each cultivation area is obtained through the fertilizer application database;

[0081] The total amount of fertilizer applied in each cultivation area was subtracted from the total amount of leachate fertilizer at the bottom of the trough, and the ratio of the difference to the total amount of fertilizer applied in each cultivation area was used as the fertilizer utilization characteristic of each cultivation area.

[0082] The water use and fertilizer use characteristics of different cultivation areas were normalized to obtain water factor and fertilizer factor, and the calculation formula is as follows: , ,in, and For respectively the first Water use characteristics and fertilizer use characteristics of each cultivation area The number of cultivation areas. and

[0083] These are moisture factor and fertilizer factor, respectively;

[0084] The water-fertilizer synergy index for each cultivation region is calculated by combining water and fertilizer factors. The calculation formula is as follows: ,in, It is a moisture factor. As fertilizer factors, The water and fertilizer synergy index for each cultivation region. The water-fertilizer interaction coefficient has a value range of 0.8-1.2 and is determined experimentally based on crop type and substrate characteristics.

[0085] It should be noted that the greater the water use characteristics and fertilizer use characteristics of each cultivation area, the higher the crop's absorption and utilization rate of water and fertilizer, and the greater the water-fertilizer synergy index of each cultivation area; conversely, the smaller the water use characteristics and fertilizer use characteristics of each cultivation area, the lower the crop's absorption and utilization rate of water and fertilizer, and the smaller the water-fertilizer synergy index of each cultivation area.

[0086] The water-fertilizer synergy index of each cultivation area was compared with the preset water-fertilizer synergy threshold for evaluation.

[0087] If the water-fertilizer synergy index of each cultivation area is less than or equal to the preset water-fertilizer synergy threshold, then the cultivation area is not the target cultivation area.

[0088] If the water-fertilizer synergy index of each cultivation area is greater than the preset water-fertilizer synergy threshold, then the cultivation area is the target cultivation area.

[0089] The water and fertilizer ratios in the target cultivation areas are marked.

[0090] It should be explained that the fertilizer input database refers to a structured data system that stores and manages fertilizer application information for various cultivation areas, used to record the total amount of fertilizer applied each time in each cultivation area. The preset water-fertilizer synergy threshold is an important parameter for determining whether each cultivation area is a target cultivation area. The historical water-fertilizer synergy index of each cultivation area is collected, the average value or distribution range is calculated, and the threshold is set at a position higher than the average value but not too harsh, such as the average value plus the standard deviation. The historical data should cover more than 3 growing seasons of the same crop and samples from at least 20 cultivation areas. If the historical data is insufficient, a small-scale pilot can be used first, such as the average value plus the standard deviation of 5 to 8 cultivation areas as a temporary threshold, and then updated after the data is accumulated.

[0091] In the irrigation monitoring module, irrigation treatment is carried out for each cultivation area according to the marked water and fertilizer ratio;

[0092] Set the statistical time period and acquire fruit sugar content data of crops in various cultivation areas through near-infrared spectral sensors;

[0093] It should be noted that when sampling with the near-infrared spectral sensor, fruits that have reached the commercial maturity standard (such as soluble solids content exceeding the standard value) are selected, and spectral scanning is performed in the middle of the equatorial plane of the fruit. The average value of three measurements is taken as the fruit sugar content data.

[0094] The fruit sugar content data of crops in various cultivation areas are compared with the preset fruit sugar content threshold to determine the result.

[0095] If the fruit sugar content data of crops in each cultivation area are all greater than the preset fruit sugar content threshold, then it is determined that the marked water and fertilizer ratio will be stored in the water and fertilizer ratio database.

[0096] If the fruit sugar content data of crops in each cultivation area is less than or equal to the preset fruit sugar content threshold, it is determined that the marked water and fertilizer ratio will not be stored in the water and fertilizer ratio database.

[0097] It needs to be explained that the statistical time period refers to the time period used to collect, summarize, and analyze crop fruit sugar content data during irrigation monitoring. For crops that grow quickly and whose fruit sugar content changes rapidly, a shorter statistical time period can be set, such as 1 to 3 days. For crops that grow slowly and whose sugar content accumulates slowly, a longer statistical time period can be set, such as 7 to 14 days. The statistical time period should cover at least one irrigation or water and fertilizer management cycle in order to observe the crop's response to the current water and fertilizer measures. The near-infrared spectral sensor is a sensor that uses the interaction between near-infrared light and the vibrational characteristics of matter molecules to quickly and non-destructively detect the composition of substances. It is used to obtain fruit sugar content data of crops in various cultivation areas. Fruit sugar content data refers to the numerical value reflecting the soluble sugar content in crop fruits. The preset fruit sugar content threshold is an important parameter for determining whether to store the marked water and fertilizer ratio in the water and fertilizer ratio database. It depends on the crop variety and market standards: different crops have different requirements for fruit sugar content. For example, grapes, tomatoes, and strawberries all have their own maturity and quality standards. The minimum qualified sugar content can be determined as the threshold by referring to industry or national standards. The water and fertilizer ratio database is a data system used to store and manage the verified water and fertilizer ratio information of cultivation areas.

[0098] Finally, it should be noted that in this paper, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0099] 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 limitation, 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.

[0100] In this document, the singular forms “a,” “an,” and “the” may also include the plural forms unless the context clearly indicates otherwise. It should also be understood that terms such as “comprising / including” or “having” specify the presence of the stated features, integrals, steps, operations, components, parts, or combinations thereof, but do not preclude the possibility of the presence or addition of one or more other features, integrals, steps, operations, components, parts, or combinations thereof. Meanwhile, the term “and / or” as used in this specification includes any and all combinations of the associated listed items.

[0101] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0102] The above description of the disclosed embodiments will enable those skilled in the art to make or use various modifications to these embodiments. It will be readily apparent to those skilled in the art that 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. An intelligent decision-making system for integrated water and fertilizer regulation in composite substrates, characterized in that: It includes a data acquisition module, a moisture analysis module, an assessment and labeling module, and an irrigation monitoring module. The functions of each module are as follows: The data acquisition module is used to detect different water and fertilizer ratios in cultivation areas, measure the root-shrimp data of crops in each cultivation area, use the root-shrimp data to evaluate the crop water uptake coefficient, set multiple soil layer heights, detect the matrix conductivity of each soil layer height in the cultivation area, and transmit the crop water uptake coefficient and matrix conductivity to the water analysis module. The water analysis module receives the matrix conductivity of each soil layer height in the cultivation area and analyzes the fertilizer leaching rate of the cultivation area. It combines the crop water intake coefficient to evaluate the water use characteristics of the cultivation area, collects the total amount of leachate fertilizer at the bottom of the cultivation area, and transmits the water use characteristics and the total amount of leachate fertilizer to the evaluation and labeling module. After receiving the total amount of leachate fertilizer, the evaluation and labeling module evaluates the fertilizer utilization characteristics of the cultivation area, integrates water use characteristics and fertilizer use characteristics to screen target cultivation areas, and marks the water and fertilizer ratio in the target cultivation area and transmits it to the irrigation monitoring module. The irrigation monitoring module uses the marked water-fertilizer ratio to irrigate various cultivation areas, sets the statistical time, monitors the fruit sugar content data of crops in each cultivation area, and determines whether to store the water-fertilizer ratio in the water-fertilizer ratio database based on the monitoring results.

2. The intelligent decision-making system for integrated water and fertilizer regulation of composite substrate according to claim 1, characterized in that: In the data acquisition module, cultivation areas are differentiated and tested based on different water and fertilizer ratios; Root-stem data for crops in various cultivation regions include root-stem mass and root length density. The root dry mass of the crop samples was obtained by weighing the root system of the pretreated and dried crop samples using a precision electronic balance. The total root length of crop samples was obtained using high-precision optical scanning technology; The ratio of the total root length of the crop sample to the preset sampling volume is used as the root length density of the crop sample.

3. The intelligent decision-making system for integrated water and fertilizer regulation of composite substrate according to claim 2, characterized in that: In the data acquisition module, the root dry mass and root length density of crop samples are standardized to obtain the quality factor and density factor. The crop water intake coefficient for each cultivation area was calculated by combining quality factors and density factors. Multiple soil layer heights and fixed sampling time intervals were set, and the matrix conductivity of each soil layer height in each cultivation area was obtained using a conductivity meter.

4. The intelligent decision-making system for integrated water and fertilizer regulation of composite substrate according to claim 3, characterized in that: In the moisture analysis module, the ratio of the absolute value of the difference between the matrix conductivity of each group of soil layers in each cultivation area at adjacent sampling times to the fixed sampling time interval is used as the rate of change of conductivity of each group of soil layers in each cultivation area. The fertilizer leaching rate of each soil layer height in each cultivation area is obtained by multiplying the rate of change of electrical conductivity of each soil layer height in each cultivation area by the calibration coefficient. The fertilizer leaching rate for each cultivation area was obtained by averaging the fertilizer leaching rate at each soil layer height in each cultivation area.

5. The intelligent decision-making system for integrated water and fertilizer regulation of composite substrate according to claim 3, characterized in that: In the water analysis module, the crop water intake coefficient and fertilizer leaching rate of each cultivation area are normalized according to the Max-Min normalization method to obtain the water intake factor and leaching factor. Water use characteristics of each cultivation area were calculated by combining water intake and leaching factors.

6. The intelligent decision-making system for integrated water and fertilizer regulation of composite substrate according to claim 1, characterized in that: In the moisture analysis module, the concentrations of nitrogen, phosphorus, and potassium ions in the leachate are obtained by selecting sensors based on nitrogen, phosphorus, and potassium ions. The fertilizer concentration in the leachate is obtained by adding the ion concentrations of nitrogen, phosphorus, and potassium in the leachate. The total amount of fertilizer in the leachate at the bottom of the tank in each cultivation area is calculated by multiplying the fertilizer concentration in the leachate by the weight of the leachate in the collection container of each cultivation area.

7. The intelligent decision-making system for integrated water and fertilizer regulation of composite substrate according to claim 5, characterized in that: In the evaluation and labeling module, the total amount of fertilizer applied in each cultivation area is obtained through the fertilizer application database; The total amount of fertilizer applied in each cultivation area was subtracted from the total amount of leachate fertilizer at the bottom of the trough, and the ratio of the difference to the total amount of fertilizer applied in each cultivation area was used as the fertilizer utilization characteristic of each cultivation area. Water use and fertilizer use characteristics of different cultivation areas were normalized to obtain water factor and fertilizer factor.

8. The intelligent decision-making system for integrated water and fertilizer regulation of composite substrate according to claim 7, characterized in that: In the evaluation and labeling module, the water-fertilizer synergy index of each cultivation area is calculated by combining water and fertilizer factors. If the water-fertilizer synergy index of each cultivation area is less than or equal to the preset water-fertilizer synergy threshold, then the cultivation area is not the target cultivation area. If the water-fertilizer synergy index of each cultivation area is greater than the preset water-fertilizer synergy threshold, then the cultivation area is the target cultivation area. The water and fertilizer ratios in the target cultivation areas are marked.

9. The intelligent decision-making system for integrated water and fertilizer regulation of composite substrate according to claim 1, characterized in that: In the irrigation monitoring module, irrigation treatment is carried out for each cultivation area according to the marked water and fertilizer ratio; Set the statistical time period and acquire fruit sugar content data of crops in various cultivation areas through near-infrared spectral sensors; If the fruit sugar content data of crops in each cultivation area are all greater than the preset fruit sugar content threshold, then it is determined that the marked water and fertilizer ratio will be stored in the water and fertilizer ratio database. If the fruit sugar content data of crops in each cultivation area is less than or equal to the preset fruit sugar content threshold, it is determined that the marked water and fertilizer ratio will not be stored in the water and fertilizer ratio database.

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