CN112715119A - Intelligent water and fertilizer decision method and system for greenhouse matrix cultivation - Google Patents
Intelligent water and fertilizer decision method and system for greenhouse matrix cultivation Download PDFInfo
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
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- A01C21/00—Methods of fertilising, sowing or planting
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- A—HUMAN NECESSITIES
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- A01C—PLANTING; SOWING; FERTILISING
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Abstract
The invention discloses an intelligent water and fertilizer decision method and an intelligent water and fertilizer decision system for greenhouse matrix cultivation, wherein the method comprises the following steps: s1, setting the substrate water content, substrate conductivity and water-fertilizer ratio of each growth stage of crops; s2, calculating the amount of each nutrient element required by each growth stage of the crops, and determining the reference fertilizing amount per day; s3, collecting and storing monitoring data of air and soil; s4, determining the irrigation starting time and irrigation quantity of the second irrigation; s5, determining the starting time and fertilizer amount of the water-bearing fertilizer for the second irrigation; s6, acquiring the actual applied fertilizer amount of the current growth stage, calculating the total amount of the remaining nutrient elements required by the crops, recalculating the daily reference fertilizer amount of the remaining days in the current growth stage, and repeating the steps S4 and S5. The intelligent water and fertilizer decision method can realize the whole-process intelligent decision management of the crops along with the water and fertilizer strategy and the water and fertilizer in each growth stage, and improve the precision of water and fertilizer irrigation and the efficiency of water and fertilizer utilization.
Description
Technical Field
The application relates to the technical field of agricultural irrigation, in particular to an intelligent water and fertilizer decision method and system for greenhouse matrix cultivation.
Background
With the development of modern greenhouses, more and more greenhouses adopt solid substrates to replace soil, and a water and fertilizer all-in-one machine is used for automatic irrigation, as for the irrigation starting conditions and irrigation quantity of crops, the number of times of irrigation in one day, the irrigation starting time of each time and the irrigation quantity or duration of each time are basically set by experience, so that larger water and fertilizer errors are easily caused, and better growth of the crops is influenced. Therefore, the irrigation conditions and the irrigation quantity of the water and fertilizer are automatically decided by using the technologies of the Internet of things and the like, the intelligent control of the water and fertilizer is realized, the manual judgment errors can be avoided, the resources are saved, and the labor is saved.
In the prior art, the irrigation is started by using the lower limit of the water content of the matrix mostly for the starting condition of irrigation, or the solar accumulated radiation value and accumulated temperature are combined with the water content of the matrix to be used as the starting condition, the irrigation quantity is calculated by using a water balance method or the upper and lower limits of the water content of the matrix mostly for control, most researches are carried out on a water utilization strategy, but the intelligent guiding strategy is lacked for fertilization along with water.
In addition, automatic irrigation in the prior art basically only provides an automatic idea of an irrigation mode, some implementations utilize a default prepared nutrient solution, a complete fertilization strategy is not provided according to the change of the demand of the crops for nutrients in different growth stages, and meanwhile, data such as the irrigation quantity of the nutrient solution and the like are excessively estimated depending on experience, some irrigation opportunities and irrigation quantities are finely adjusted only according to one environmental factor of sunlight radiation, irrigation is not accurate enough, and crop growth is influenced.
Disclosure of Invention
An object of the application is to provide a new technical scheme of an intelligent water and fertilizer decision method and system for greenhouse substrate cultivation, which can solve the problem of the prior art that the automatic irrigation lacks intelligent guidance strategy for water-following fertilizer application.
The invention provides an intelligent water and fertilizer decision method for greenhouse substrate cultivation, which comprises the following steps:
s1, setting the lower limit V of the water content of the substrate at each growth stage of the cropsLUpper limit of substrate conductivity ECHAnd lower limit ECLUpper limit R of water-fertilizer ratioH；
S2, calculating the amount of each nutrient element required by each growth stage of the crops according to a target yield method, and determining the reference fertilizing amount per day;
s3, collecting and storing monitoring data of air and soil;
s4, according to the monitoring data, when the collected water content of the matrix is lower than the lower limit VLWhen the water is filled, the water filling is started; calculating the irrigation quantity of the first irrigation according to the planting time and the first starting time, and calculating the irrigation quantity according to the irrigation starting time of the second irrigation and the interval time of the first irrigation;
s5, according to the monitoring data, when the conductivity of the matrix is collected to be higher than the upper limit EC each time irrigation is to be carried outHOnly water irrigation is started; the conductivity of the matrix is collected to be lower than the upper limit ECHAnd above the lower limit ECLThe time is based on the time length ratio and the upper limit R of the water-fertilizer ratioHDetermining the fertilizer amount, and starting fertilization with water; when the substrate conductivity is collected below the lower limit ECLAccording to the upper limit R of the water-fertilizer ratioHDetermining the fertilizer amount, and starting fertilization with water;
s6, repeating the step S4 and the step S5 until one day is finished, acquiring the actual applied fertilizer amount of the current growth stage, calculating the total amount of the remaining nutrient elements required by the crops, recalculating the daily reference fertilizing amount of the remaining days of the current growth stage, and repeating the step S4 and the step S5;
the monitoring data comprise substrate moisture content, substrate conductivity, air temperature and humidity, wind speed and solar net radiation data.
Further, in step S2, the calculation formula of the target yield method for each birth phase is:
and calculating the amount of each nutrient element required by each growth stage of the crops.
Further, in the step S5, the ratio of water to fertilizer for the first irrigation is calculated to be greater than the upper limit RHAccording to the upper limit RHAnd calculating the actual fertilizer application amount and updating the applied fertilizer amount data of the current growth stage of the crops.
Further, in the step S5, the conductivity of the matrix is collected to be higher than the upper limit ECHAnd under the condition that the time length continuously higher than the upper limit exceeds a first preset time length, the irrigation of the crops is started in a flood irrigation mode.
Further, in the step S5, the conductivity of the matrix is collected to be lower than the lower limit ECLAnd when the duration continuously lower than the lower limit exceeds a second preset duration, according to the upper limit R of the water-fertilizer ratioHAnd (5) starting fertilization with water.
Further, the intelligent water and fertilizer decision method further comprises the following steps:
when the substrate conductivity is collected below the lower limit ECLAnd when the daily fertilizer usage amount of the crop exceeds the daily reference fertilizing amount, repeatedly executing the step S5.
Further, in the intelligent water and fertilizer decision method, irrigation and fertilization are not performed at night.
In a second aspect of the present invention, an intelligent water and fertilizer decision system for greenhouse substrate cultivation is provided, which includes: the data acquisition and processing module is used for acquiring and processing monitoring data of each growth stage of crops; the data storage module is connected with the data acquisition and processing module and is used for storing the monitoring data; the water and fertilizer strategy calculation module is connected with the data storage module and calculates irrigation quantity, fertilizer quantity and water and fertilizer ratio of irrigation according to the monitoring data and generates a real-time calculation result; the water and fertilizer irrigation control module is connected with the water and fertilizer strategy calculation module and is used for receiving the calculation result of the water and fertilizer strategy calculation module and sending out a corresponding water and fertilizer decision signal; and the water and fertilizer integrated irrigation module is connected with the water and fertilizer irrigation control module, and is used for performing water and fertilizer integrated irrigation on crops according to the water and fertilizer decision signal.
Furthermore, the acquisition frequency of the data acquisition processing module is 5s-20 s.
Further, the data storage module stores the monitoring data in a relational database or a non-relational database.
According to the intelligent water and fertilizer decision method provided by the embodiment of the invention, the irrigation starting condition and irrigation quantity are determined by collecting monitoring data of each growth stage of crops and combining the water content of the matrix, so that an irrigation strategy is realized. Meanwhile, the amount of each nutrient element required by each growth stage of the crop is calculated according to a target yield method, the reference fertilizing amount every day is calculated, the starting condition and the fertilizer amount of the water-associated fertilization are determined, and the water-associated fertilization strategy of the crop at each growth stage is realized. The intelligent water and fertilizer decision method realizes water and fertilizer integrated whole-course intelligent decision management, improves the precision of water and fertilizer irrigation and the efficiency of water and fertilizer utilization, and saves resources and manpower.
Further features of the present application and advantages thereof will become apparent from the following detailed description of exemplary embodiments thereof, which is to be read in connection with the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the application and together with the description, serve to explain the principles of the application.
FIG. 1 is a block flow diagram of an intelligent water fertilizer decision method of the present invention;
FIG. 2 is a control flow diagram of the intelligent water and fertilizer decision method of the present invention;
FIG. 3 is a schematic diagram of the structure of the intelligent water and fertilizer decision system of the present invention;
fig. 4 is a working schematic diagram of an electronic device of the intelligent water and fertilizer decision method of the invention.
Reference numerals:
an intelligent water and fertilizer decision making system 100;
a data acquisition processing module 10;
a data storage module 20;
a water and fertilizer strategy calculation module 30;
a water and fertilizer irrigation control module 40;
a water and fertilizer integrated irrigation module 50;
an electronic device 200;
a processor 201;
a memory 202; an operating system 2021; application programs 2022;
a network interface 203;
an input device 204;
a hard disk 205;
a display device 206.
Detailed Description
Various exemplary embodiments of the present application will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present application unless specifically stated otherwise.
The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the application, its application, or uses.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.
The intelligent water and fertilizer decision method for greenhouse substrate cultivation according to the embodiment of the invention is specifically described below with reference to the accompanying drawings.
As shown in fig. 1 and fig. 2, the intelligent water and fertilizer decision method for greenhouse substrate cultivation according to the embodiment of the invention comprises the following steps:
s1, setting the lower limit V of the water content of the substrate at each growth stage of the cropsLUpper limit of substrate conductivity ECHAnd lower limit ECLUpper limit R of water-fertilizer ratioH；
S2, calculating the amount of each nutrient element required by each growth stage of the crops according to a target yield method, and determining the reference fertilizing amount per day;
s3, collecting and storing monitoring data of air and soil;
s4, according to the monitoring data, when the water content of the collected matrix is lower than the lower limit VLWhen the water is filled, the water filling is started; calculating the irrigation quantity of the first irrigation according to the planting time and the first starting time, and calculating the irrigation quantity according to the irrigation starting time of the second irrigation and the interval time of the first irrigation;
s5, according to the monitoring data, when the conductivity of the matrix is higher than the upper limit EC when irrigation is to be carried out each timeHOnly water irrigation is started; when the conductivity of the matrix is collected to be lower than the upper limit ECHAnd above the lower limit ECLThe upper limit R of the time length ratio and the water-fertilizer ratio isHDetermining the fertilizer amount, and starting fertilization with water; when the conductivity of the matrix is collected to be lower than the lower limit ECLAccording to the upper limit R of the water-fertilizer ratioHDetermining the fertilizer amount, and starting fertilization with water;
s6, repeating the steps S4 and S5 until one day is finished, acquiring the actual applied fertilizer amount of the current growth stage, calculating the total amount of the remaining nutrient elements required by the crops, recalculating the daily reference fertilizer application amount of the remaining days in the current growth stage, and repeating the steps S4 and S5.
The monitoring data comprises substrate moisture content, substrate conductivity, air temperature and humidity, wind speed and solar clean radiation data.
Specifically, referring to fig. 1 and 2, in the intelligent water and fertilizer decision method for greenhouse substrate cultivation according to the embodiment of the invention, the lower limit V of the substrate water content in each growth stage of the crop can be setLUpper limit of substrate conductivity ECHAnd lower limit ECLUpper limit R of water-fertilizer ratioH. If the calculated water-fertilizer ratio exceeds the upper limit RHAnd calculating the actual fertilizer consumption and updating the applied fertilizer data of the crop based on the above limit.
According to the target yield method, the amount of each nutrient element required by each growth stage of the crops can be calculated, and the reference fertilizing amount per day is determined. In the process, according to a target yield method, calculating the amount formula of each nutrient element required by each growth stage of the crops, wherein the nutrient elements of the crops mainly consider three nutrient elements of nitrogen, phosphorus and potassium which are beneficial to the growth of the crops. The target yield method can be expressed as the following equation:
the nutrient amount of nitrogen, phosphorus and potassium absorbed by crops in each growth stage per hundred kilograms of yield can be obtained according to empirical values, and 10% -15% of the nutrient amount is increased as a target yield on the basis of the average yield of the crops in the previous three years. The matrix does not provide nutrients, and the nutrient quantity required by the actual planting area can be converted according to the area after the nutrient demand of each growth stage of each mu of crops is calculated. Since the greenhouse environment is relatively stable, the total amount of each nutrient element can be approximately evenly distributed to each day according to the number of days of each growth stage empirically.
And then, collecting and storing monitoring data of the air and the soil, wherein the monitoring data mainly comprises substrate moisture content, substrate conductivity, air temperature and humidity, wind speed, solar clean radiation data and the like. Wherein, the water content of the substrate, the conductivity of the substrate, the temperature and humidity of air, the wind speed and the solar net radiation data can be classified as environmental factor data. Of course, it will be understood by those skilled in the art that the monitoring data for each growth stage of the crop in the present application includes, but is not limited to, substrate moisture content, substrate conductivity, air temperature and humidity, wind speed, and solar net radiation data.
According to the monitoring data, when the water content of the collected matrix is lower than the lower limit VLWhen the water is filled, the water filling is started. According to the fixed value time and the first starting time, the irrigation water quantity of the first irrigation can be calculated. And calculating the irrigation quantity according to the irrigation starting time of the second irrigation and the interval time of the first irrigation. The irrigation quantity of the first irrigation can be understood as the irrigation quantity of the last irrigation, and the irrigation quantity of the second irrigation can be understood as the irrigation quantity of the current time point.
In the application, the irrigation quantity from the last irrigation to the current time point can be calculated according to a water balance method, and an equation of the water balance method is as follows:
M＝We+ETc
by combining the greenhouse environment, the water balance equation can be simplified, wherein M is the irrigation quantity, WeIs the variation of the effective water storage capacity of the substrate in a time period, WeCan be calculated by the volume of the matrix and the variation range of the water content of the matrix, ETcThe amount of transpiration of the crops.
In the present application, the crop transpiration ET is calculatedcThe formula of (1) is:
ETc＝ET0×Kc
wherein, ETcIs the amount of transpiration of the crop, ET0For reference crop transpiration, KcAs a crop coefficient, KcThe reference value in the field can be used, and the real-time calculation can be carried out according to the accumulated temperature.
ET0As the reference crop transpiration amount, in the calculation time period, if the wind speed is high, the reference crop transpiration amount can be calculated by adopting the following model, and the calculation formula is as follows:
in the calculation time period, if the wind speed is 0, the following correction model can be adopted to calculate the reference crop transpiration amount, and the calculation formula is as follows:
in the above two reference crop transpiration calculation formulas, RnIs the average net radiation of the crop surface in hours (unit: MJm)-2day-1) G is the soil heat flux (unit: MJm-2day-1)，ThrThe average temperature in hours (. degree. C.), μ2Is the average wind speed (unit: ms) at two meters in an hour-1)，esIs saturated water vapor pressure (unit: KPa), eaIn the actual water vapor pressure (unit: KPa), Δ is the slope of the saturated water vapor pressure temperature curve (unit: KPa/deg.C), and γ is the thermometer constant (unit: KPa/deg.C).
And after the calculation is finished, calculating the actual water quantity according to the planting area and the like.
According to the monitoring data, when the substrate conductivity is collected to be higher than the upper limit EC each time irrigation is to be carried outHIn time, only irrigation is started, and fertilization can be omitted. When the conductivity of the matrix is collected to be lower than the upper limit ECHAnd above the lower limit ECLThe upper limit R of the time length ratio and the water-fertilizer ratio isHDetermining the fertilizer amount, and starting fertilization with water. When the conductivity of the matrix is collected to be lower than the lower limit ECLIn time, the upper limit R of the water-fertilizer ratio can be determinedHDetermining the fertilizer amount, and starting fertilization with water.
In the application, the fertilizer application amount with water each time is based on the total amount of each nutrient element every day, and the fertilizer application amount with water can be divided according to the proportion that the time interval between the front and back two times of fertilizer application accounts for 24 hours a day. Although the greenhouse has relatively independent microclimate environment, the greenhouse is closely related to the external environment at present, the temperature at night is low, natural illumination is avoided, the transpiration effect is weak, the transportation of water and inorganic salts in the plant body is slower, so the time duration at night and the time duration in daytime cannot be uniformly divided, the time duration in day and night can be determined according to the local latitude, specific gravity coefficients are set for the night and the day, for example, the general transpiration amount at night in day and night or the accumulated temperature in day and night is used as a reference, the time duration of the interval between two times of irrigation is calculated, and the fertilizer amount is calculated in proportion (calculation over the day: the calculation is divided into two parts and then added).
And finally, repeating the steps S4 and S5 to the end of one day, acquiring the actual applied fertilizer amount of the current growth stage of the crops, calculating the total amount of the remaining nutrient elements required by the elements of the crops in the growth stage, recalculating the daily reference fertilizer application amount of the remaining days in the current growth stage, and then repeating the steps S4 and S5 to calculate the daily water and fertilizer.
According to the intelligent water and fertilizer decision method provided by the embodiment of the invention, the irrigation starting condition and irrigation quantity are determined by collecting monitoring data of each growth stage of crops and combining the water content of the matrix, so that an irrigation strategy is realized. Meanwhile, the amount of each nutrient element required by each growth stage of the crop is calculated according to a target yield method, the reference fertilizing amount every day is calculated, the starting condition and the fertilizer amount of the water-associated fertilization are determined, and the water-associated fertilization strategy of the crop at each growth stage is realized. The intelligent water and fertilizer decision method realizes water and fertilizer integrated whole-course intelligent decision management, improves the precision of water and fertilizer irrigation and the efficiency of water and fertilizer utilization, and saves resources and manpower.
According to an embodiment of the invention, in step S5, the ratio of water to fertilizer for irrigation is calculated to be greater than the upper limit RHAccording to the upper limit RHAnd calculating the actual fertilizer application amount. Meanwhile, the conductivity of the collected matrix is higher than the upper limit ECHAnd under the condition that the time length continuously higher than the upper limit exceeds a first preset time length, the irrigation of the crops is started in a flood irrigation mode.
That is, if the substrate conductivity EC value is currently judged to be above the upper limit ECHThe time length continuously higher than the upper limit of the EC value in the history data may be additionally determined, if the time length continuously higher than the upper limit exceeds a first predetermined time length, for example: one day, the plant can be judged to have excessive soluble salt accumulation, and the plant root system can be damaged and cannot absorb water at the momentAnd (4) separating and nourishing. And at present, desalting is immediately performed by adopting a flood irrigation mode, and the flood irrigation mode can set more water volume exceeding the maximum water holding capacity of the matrix according to the water content condition of the matrix to perform flood irrigation.
In some embodiments of the invention, in step S5, the conductivity of the collected substrate is lower than the lower limit ECLAnd under the condition that the duration continuously lower than the lower limit exceeds a second preset duration, according to the upper limit R of the water-fertilizer ratioHAnd (5) starting fertilization with water.
In other words, if the current substrate conductivity EC value is judged to be below the lower limit EC for that fertility stageLThe threshold value is added to determine the time length continuously below the lower limit of the EC value in the historical data, and if the time length continuously below the lower limit exceeds a second predetermined time length, for example: one day, the fertilizer supply is low, and the upper limit R of the water-fertilizer ratio in the growth stage can be determinedHAnd setting the fertilizer amount for irrigation, calculating the amount of each nutrient element, and updating the applied fertilizer amount data of the greenhouse crops in the database.
According to an embodiment of the invention, the intelligent water and fertilizer decision method further comprises:
when the conductivity of the matrix is collected to be lower than the lower limit ECLAnd when the daily fertilizer usage amount of the crop exceeds the daily reference fertilizing amount, repeatedly executing the step S5.
That is, if the amount of fertilizer used per day exceeds the daily reference amount of fertilizer to be applied because the substrate conductivity EC is too low, the calculation is performed according to the daily reference amount of fertilizer or repeatedly performed in step S5 when the fertilization requirement is still satisfied.
In the intelligent water and fertilizer decision method, the temperature is low at night, natural illumination is avoided, the transpiration effect is weaker, the transportation of water and inorganic salt in the plant body is slower, irrigation and fertilization can be avoided at night, and the resource utilization efficiency is improved.
In summary, the intelligent water and fertilizer decision method for greenhouse substrate cultivation in the embodiment of the invention obtains the transpiration amount in the corresponding time period by monitoring the environmental data and calculating, and realizes the irrigation strategy by combining the substrate water content. The total fertilizer amount is obtained according to a conventional target yield method, and a scheme capable of automatically calculating and distributing the fertilizer amount is designed according to conditions such as the growth stage, the irrigation amount and the like. The intelligent water and fertilizer decision method for greenhouse substrate cultivation, provided by the embodiment of the invention, realizes water and fertilizer integrated whole-course intelligent decision management, improves the precision of water and fertilizer irrigation and the efficiency of water and fertilizer utilization, and saves resources and manpower.
In a second aspect of the invention, an intelligent water and fertilizer decision making system 100 for greenhouse substrate cultivation is provided, which comprises a data acquisition module 10, a data storage module 20, a water and fertilizer strategy calculation module 30, a water and fertilizer irrigation control module 40 and a water and fertilizer integrated irrigation module 50.
Specifically, the data collecting and processing module 10 is used for collecting and processing the monitoring data of each growth stage of the crops. The data storage module 20 is connected with the data acquisition processing module 10, and the data storage module 20 is used for storing the monitoring data. The water and fertilizer strategy calculation module 30 is connected with the data storage module 20, and the water and fertilizer strategy calculation module 30 calculates irrigation quantity, fertilizer quantity and water and fertilizer ratio according to the monitoring data and generates a real-time calculation result. The water and fertilizer irrigation control module 40 is connected to the water and fertilizer strategy calculation module 30, and the water and fertilizer irrigation control module 40 is configured to receive the calculation result of the water and fertilizer strategy calculation module 30 and send a corresponding water and fertilizer decision signal. The water and fertilizer integrated irrigation module 50 is connected with the water and fertilizer irrigation control module 40, and the water and fertilizer integrated irrigation module 50 performs water and fertilizer integrated irrigation on crops according to the water and fertilizer decision signals.
In other words, as shown in fig. 3, the intelligent water and fertilizer decision system 100 for greenhouse substrate cultivation according to the embodiment of the present invention mainly comprises a data acquisition module 10, a data storage module 20, a water and fertilizer strategy calculation module 30, a water and fertilizer irrigation control module 40, and a water and fertilizer integrated irrigation module 50. The data acquisition and processing module 10 is used for acquiring and processing monitoring data of each growth stage of crops. The collected monitoring data can comprise substrate conductivity, substrate moisture content, air temperature and humidity, wind speed, net radiation data and the like, and the collection frequency of the data collection processing module 10 is 5s-20 s. Alternatively, the data acquisition processing module 10 may acquire every 10 seconds. The data acquisition processing module 10 may include sensors, and for non-uniformity and possible abnormal conditions of data acquisition, the maximum reasonable range may be set for each acquisition value by reasonably laying the sensor positions, and when there is an abnormal value, an alarm may be given and corrected. And multiple sets of the method can be arranged at multiple places, and a Kalman filtering algorithm is introduced for calculation so as to reduce abnormal conditions.
The data storage module 20 is connected with the data acquisition processing module 10, and the data storage module 20 is used for storing the monitoring data. The data storage module 20 may store the monitoring data in a relational or non-relational database. Relational databases, such as mysql, or non-relational databases, such as mongodb, are employed to create the library and table for storing a variety of different types of data. The plurality of different types of data include expert experience data, real-time acquired data, model calculation data, and the like. The expert experience data comprises the amount of absorbed nutrients per hundred kilograms of yield of different crops, the crop coefficient of each growth stage of different crops, the upper and lower limits of the water content of the substrate of each growth stage of different crops and the like. The real-time data collected mainly includes data collected by the data collecting and processing module 10 in real time, and may also include data of the working state and working time of the water and fertilizer integrated irrigation module 50. The model calculation data comprises a reference value of the fertilizer amount per day, time of each water and fertilizer calculation, input parameters, output results and the like.
The water and fertilizer strategy calculation module 30 is connected with the data storage module 20 in advance, and the water and fertilizer strategy calculation module 30 calculates irrigation quantity, fertilizer quantity and water and fertilizer ratio of irrigation according to the monitoring data and generates a real-time calculation result. The water and fertilizer strategy calculation module 30 mainly adopts the intelligent water and fertilizer decision method for greenhouse substrate cultivation to realize computer coding, and the model calculation part can adopt python programming language to read expert experience data and real-time collected monitoring data in the data storage module 20 to generate real-time water and fertilizer decision results of crops.
The water and fertilizer irrigation control module 40 is connected to the water and fertilizer strategy calculation module 30, and the water and fertilizer irrigation control module 40 is configured to receive the calculation result of the water and fertilizer strategy calculation module 30 and send a corresponding water and fertilizer decision signal. The liquid manure irrigation control module 40 receives the calculation result of the liquid manure strategy calculation module 30 and pushes the calculation result to the liquid manure integrated irrigation module 50, and according to the working mode of the liquid manure integrated irrigation module 50, if irrigation is performed, the water quantity can be directly pushed to the liquid manure integrated irrigation module 50, or the irrigation duration obtained by calculating the flow rate of the water quantity and the liquid manure integrated irrigation module 50 is pushed to the liquid manure integrated irrigation module 50. In the case of fertilization, the first method may be to calculate the ratio of water to fertilizer and then push the ratio of water to fertilizer to the local setting of the water-fertilizer integrated irrigation module 50 in real time. The second is to remotely start the water and fertilizer integrated irrigation module 50, and after the previous step pushes the water and fertilizer data to the water and fertilizer integrated irrigation module 50, the water and fertilizer irrigation control module 40 can directly start the machine, so that the machine can work according to the data of the previous step, and the machine can automatically stop working when the set numerical value or time is reached. And the third method is to monitor whether the operation of the water and fertilizer integrated irrigation module 50 is normal and irrigation data, to ensure that the water and fertilizer integrated irrigation module 50 is indeed successfully irrigated, and if a problem occurs, to give an alarm, the water and fertilizer strategy calculation module 30 and the water and fertilizer irrigation control module 40 are suspended to operate, and the water and fertilizer integrated irrigation module 50 is resumed to operate.
The water and fertilizer integrated irrigation module 50 is connected with the water and fertilizer irrigation control module 40, and the water and fertilizer integrated irrigation module 50 performs water and fertilizer integrated irrigation on crops according to the water and fertilizer decision signals. The water and fertilizer integrated irrigation module 50 mainly comprises a water and fertilizer integrated machine for actually implementing irrigation work in a greenhouse and water sources, pipeline equipment and the like at the periphery of the water and fertilizer integrated machine. Besides the general functions of local work, the water and fertilizer all-in-one machine mainly has to provide interfaces for on-line management, such as control interfaces for starting and stopping the machine, setting water quantity and fertilizer quantity, and the like, and an acquisition interface for water quantity and fertilizer quantity data after actual work, and the like.
In summary, the intelligent water and fertilizer decision system 100 for greenhouse substrate cultivation according to the embodiment of the present invention calculates the transpiration amount in the corresponding time period by monitoring the environmental data, and implements the irrigation strategy by combining the substrate water content. The total fertilizer amount is obtained according to a conventional target yield method, and a scheme capable of automatically calculating and distributing the fertilizer amount is designed according to conditions such as the growth stage, the irrigation amount and the like. The intelligent water and fertilizer decision system 100 for greenhouse substrate cultivation, provided by the embodiment of the invention, realizes water and fertilizer integrated whole-course intelligent decision management, improves the precision of water and fertilizer irrigation and the efficiency of water and fertilizer utilization, and saves resources and manpower.
In a third embodiment of the present invention, an electronic device 200 is provided, including: a processor 201 and a memory 202, wherein the memory 202 stores computer program instructions, and when the computer program instructions are executed by the processor 201, the processor 201 is caused to execute the steps of the intelligent water and fertilizer decision method for greenhouse substrate cultivation in the above embodiment.
Further, as shown in fig. 4, the electronic apparatus 200 further includes a network interface 203, an input device 204, a hard disk 205, and a display device 206.
The various interfaces and devices described above may be interconnected by a bus architecture. A bus architecture may include any number of interconnected buses and bridges. One or more central processing units 201 (CPUs), represented in particular by processor 201, and one or more memories 202, represented by memory 202, are connected together. The bus architecture may also connect various other circuits such as peripherals, voltage regulators, power management circuits, and the like. It will be appreciated that a bus architecture is used to enable communications among the components. The bus architecture includes a power bus, a control bus, and a status signal bus, in addition to a data bus, all of which are well known in the art and therefore will not be described in detail herein.
The network interface 203 may be connected to a network (e.g., the internet, a local area network, etc.), and may obtain relevant data from the network and store the relevant data in the hard disk 205.
The input device 204 may receive various commands input by the operator and send the commands to the processor 201 for execution. The input device 204 may include a keyboard or pointing device (e.g., a mouse, trackball, touch pad, touch screen, or the like).
The display device 206 may display the result obtained by the processor 201 executing the instructions.
The memory 202 is used for storing programs and data necessary for the operation of the operating system 2021, and data such as intermediate results in the calculation process of the processor 201.
It will be appreciated that memory 202 in embodiments of the invention may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The nonvolatile memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), or a flash memory. Volatile memory can be Random Access Memory (RAM), which acts as external cache memory. The memory 202 of the apparatus and methods described herein is intended to comprise, without being limited to, these and any other suitable types of memory 202.
In some embodiments, memory 202 stores the following elements, executable modules or data structures, or a subset thereof, or an expanded set thereof: an operating system 2021 and application programs 2022.
The operating system 2021 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is used for implementing various basic services and processing hardware-based tasks. The application programs 2022 include various application programs 2022 such as a Browser (Browser) and the like, and are used to implement various application services. A program implementing the method of an embodiment of the present invention may be included in the application 2022.
The processor 201 executes the steps of the intelligent water and fertilizer decision method for greenhouse substrate cultivation according to the above embodiment when calling and executing the application program 2022 and data stored in the memory 202, specifically, the application program or instructions stored in the application program 2022.
The method disclosed by the above embodiment of the present invention can be applied to the processor 201, or implemented by the processor 201. The processor 201 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 201. The processor 201 may be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof, and may implement or perform the methods, steps, and logic blocks disclosed in the embodiments of the present invention. A general purpose processor may be a microprocessor or the processor 201 may be any conventional processor 201 or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in the memory 202, and the processor 201 reads the information in the memory 202 and completes the steps of the method in combination with the hardware.
It is to be understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For a hardware implementation, the processing units may be implemented within one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), general purpose processors, controllers, micro-controllers, microprocessors, other electronic units designed to perform the functions of the present application, or a combination thereof.
For a software implementation, the techniques herein may be implemented with modules (e.g., procedures, functions, and so on) that perform the functions herein. The software codes may be stored in memory 202 and executed by processor 201. The memory 202 may be implemented in the processor 201 or external to the processor 201.
Specifically, the processor 201 is further configured to read a computer program and execute the following steps of implementing water and fertilizer integrated irrigation by the intelligent water and fertilizer decision method for greenhouse substrate cultivation.
In the fourth aspect of the present invention, a computer-readable storage medium is further provided, where a computer program is stored, and when the computer program is executed by the processor 201, the processor 201 is caused to execute the steps of the intelligent water and fertilizer decision method for greenhouse substrate cultivation in the foregoing embodiment.
In the several embodiments provided in the present application, it should be understood that the disclosed method and apparatus may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be physically included alone, or two or more units may be integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) to execute some steps of the transceiving method of the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
Although some specific embodiments of the present application have been described in detail by way of example, it should be understood by those skilled in the art that the above examples are for illustrative purposes only and are not intended to limit the scope of the present application. It will be appreciated by those skilled in the art that modifications may be made to the above embodiments without departing from the scope and spirit of the present application. The scope of the application is defined by the appended claims.
Claims (10)
1. An intelligent water and fertilizer decision method for greenhouse matrix cultivation is characterized by comprising the following steps:
s1, setting the lower limit V of the water content of the substrate at each growth stage of the cropsLUpper limit of substrate conductivity ECHAnd lower limit ECLUpper limit R of water-fertilizer ratioH；
S2, calculating the amount of each nutrient element required by each growth stage of the crops according to a target yield method, and determining the reference fertilizing amount per day;
s3, collecting and storing monitoring data of air and soil;
s4, according to the monitoring data, when the collected water content of the matrix is lower than the lower limit VLWhen the water is filled, the water filling is started; calculating the irrigation quantity of the first irrigation according to the planting time and the first starting time, and calculating the irrigation quantity according to the irrigation starting time of the second irrigation and the interval time of the first irrigation;
s5, according to the monitoring data, when the conductivity of the matrix is collected to be higher than the upper limit EC each time irrigation is to be carried outHOnly water irrigation is started; the conductivity of the matrix is collected to be lower than the upper limit ECHAnd above the lower limit ECLThe time is based on the time length ratio and the upper limit R of the water-fertilizer ratioHDetermining the fertilizer amount, and starting fertilization with water; when the substrate conductivity is collected below the lower limit ECLAccording to the upper limit R of the water-fertilizer ratioHDetermining the fertilizer amount, and starting fertilization with water;
s6, repeating the step S4 and the step S5 until one day is finished, acquiring the actual applied fertilizer amount of the current growth stage, calculating the total amount of the remaining nutrient elements required by the crops, recalculating the daily reference fertilizing amount of the remaining days of the current growth stage, and repeating the step S4 and the step S5;
the monitoring data comprise substrate moisture content, substrate conductivity, air temperature and humidity, wind speed and solar net radiation data.
2. The intelligent water and fertilizer decision method for greenhouse substrate cultivation as claimed in claim 1, wherein in step S2, the calculation formula of the target yield method for each breeding stage is as follows:
and calculating the amount of each nutrient element required by each growth stage of the crops.
3. The intelligent water-fertilizer decision method for greenhouse substrate cultivation as claimed in claim 1, wherein in step S5, the water-fertilizer ratio is calculated to be greater than the upper limit RHAccording to the upper limit RHAnd calculating the actual fertilizer application amount and updating the applied fertilizer amount data of the current growth stage of the crops.
4. The intelligent water and fertilizer decision method for greenhouse substrate cultivation as claimed in claim 1, wherein in step S5, the conductivity of the substrate is collected to be higher than the upper limit ECHAnd under the condition that the time length continuously higher than the upper limit exceeds a first preset time length, the irrigation of the crops is started in a flood irrigation mode.
5. The intelligent water and fertilizer decision method for greenhouse substrate cultivation as claimed in claim 1, wherein in step S5, the conductivity of the substrate is collected to be lower than the lower limit ECLAnd when the duration continuously lower than the lower limit exceeds a second preset duration, according to the upper limit R of the water-fertilizer ratioHAnd (5) starting fertilization with water.
6. The intelligent water and fertilizer decision method for greenhouse substrate cultivation as claimed in claim 1, further comprising:
when the substrate conductivity is collected below the lower limit ECLAnd the daily fertilizer consumption of the crops exceedsAnd repeating the step S5 when the fertilizing amount is referred to every day.
7. The intelligent water and fertilizer decision method for greenhouse substrate cultivation as claimed in claim 1, wherein in the intelligent water and fertilizer decision method, irrigation and fertilization are not performed at night.
8. An intelligent water and fertilizer decision making system for greenhouse matrix cultivation is characterized by comprising:
the data acquisition and processing module is used for acquiring and processing monitoring data of each growth stage of crops;
the data storage module is connected with the data acquisition and processing module and is used for storing the monitoring data;
the water and fertilizer strategy calculation module is connected with the data storage module and calculates irrigation quantity, fertilizer quantity and water and fertilizer ratio of irrigation according to the monitoring data and generates a real-time calculation result;
the water and fertilizer irrigation control module is connected with the water and fertilizer strategy calculation module and is used for receiving the calculation result of the water and fertilizer strategy calculation module and sending out a corresponding water and fertilizer decision signal;
and the water and fertilizer integrated irrigation module is connected with the water and fertilizer irrigation control module, and is used for performing water and fertilizer integrated irrigation on crops according to the water and fertilizer decision signal.
9. The intelligent water and fertilizer decision system for greenhouse substrate cultivation as claimed in claim 8, wherein the data acquisition and processing module has an acquisition frequency of 5s-20 s.
10. The intelligent water and fertilizer decision system for greenhouse substrate cultivation as claimed in claim 8, wherein the data storage module stores the monitoring data in a relational database or a non-relational database.
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