CN113039908A - Dynamic decision-making method and system for fertilization and irrigation - Google Patents

Dynamic decision-making method and system for fertilization and irrigation Download PDF

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Publication number
CN113039908A
CN113039908A CN202110271826.1A CN202110271826A CN113039908A CN 113039908 A CN113039908 A CN 113039908A CN 202110271826 A CN202110271826 A CN 202110271826A CN 113039908 A CN113039908 A CN 113039908A
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soil
irrigation
decision
nutrient
crop
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宫帅
郝文雅
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Sinochem Agriculture Holdings
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Sinochem Agriculture Holdings
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    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01C—PLANTING; SOWING; FERTILISING
    • A01C21/00—Methods of fertilising, sowing or planting
    • A01C21/007—Determining fertilization requirements
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01C—PLANTING; SOWING; FERTILISING
    • A01C21/00—Methods of fertilising, sowing or planting
    • A01C21/005—Following a specific plan, e.g. pattern
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
    • A01G25/00—Watering gardens, fields, sports grounds or the like
    • A01G25/16—Control of watering
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
    • A01G25/00—Watering gardens, fields, sports grounds or the like
    • A01G25/16—Control of watering
    • A01G25/167—Control by humidity of the soil itself or of devices simulating soil or of the atmosphere; Soil humidity sensors
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D27/00—Simultaneous control of variables covered by two or more of main groups G05D1/00 - G05D25/00
    • G05D27/02—Simultaneous control of variables covered by two or more of main groups G05D1/00 - G05D25/00 characterised by the use of electric means

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  • Life Sciences & Earth Sciences (AREA)
  • Soil Sciences (AREA)
  • Environmental Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Water Supply & Treatment (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Fertilizing (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention relates to a dynamic decision method and a system for fertilization and irrigation, wherein the method comprises the following steps: s1, the mobile terminal receives a decision request of a user, wherein the decision request is used for requesting the mobile terminal to generate a decision scheme, and the decision scheme comprises a fertilization scheme and an irrigation scheme; s2, the mobile terminal sends a scheduling request to a background management system and an IOT management platform to request to generate decision information required by the decision scheme; and S3, the mobile terminal receives the decision information returned by the background management system and the IOT management platform, and generates the decision scheme based on the decision information. The invention can dynamically generate a fertilization scheme and an irrigation scheme in real time, can provide real-time and precise water and fertilizer management suggestions for users, and effectively improves the utilization efficiency of field moisture and nutrients.

Description

Dynamic decision-making method and system for fertilization and irrigation
Technical Field
The invention relates to the technical field of agricultural water and fertilizer integration, in particular to a dynamic decision method and a dynamic decision system for fertilization and irrigation.
Background
In recent years, the continuous development of technologies such as soil testing, formulated fertilization, soil moisture content monitoring and the like gradually corrects the error region of 'large fertilizer and large water' in agricultural production, so that the accurate irrigation and fertilization can be realized, the waste of water and fertilizer can be reduced, and the utilization efficiency of the water and fertilizer can be improved, thereby becoming a research hotspot.
According to the technical principle of 'soil testing formula fertilization', the core of scientific fertilization lies in that according to nutrients which can be provided by soil and the nutrient requirement rule of crops in different growth stages under target yield, a fertilizer with accurate formula and dosage is provided for the crops in a correct time, so that the contradiction between the fertilizer requirement of the crops and the fertilizer supply of the soil is adjusted and solved.
The growth and the decay of the soil moisture directly influence the water consumption and the growth of crops, and are important indexes and data supports for accurate irrigation decisions in agricultural production, wherein the change of the soil moisture content of a root zone of the crops is an important factor directly influencing the growth of the crops. At present, based on the application of soil moisture content equipment, it is a typical application mode to formulate an irrigation system according to soil texture characteristics, water storage capacity and soil moisture content (namely soil moisture content) of a crop root zone.
Meanwhile, real-time irrigation forecasting is the basis for making a dynamic irrigation water plan. By utilizing a farmland water balance equation and measuring and calculating balance elements such as rainfall, crop evapotranspiration, soil moisture variation, underground water supply and deep layer leakage, the irrigation starting time and irrigation quantity in the future date can be calculated, so that real-time irrigation forecast is carried out.
However, the fertilization and irrigation scheme in the prior art has the following disadvantages:
the method mainly comprises the steps that accurate fertilization and accurate irrigation constructed through an algorithm are not organically combined, accurate coupling of water and fertilizer cannot be achieved for a plurality of crops with a water and fertilizer integrated planting management scene, and a complete water and fertilizer scheme cannot be provided for a grower.
Secondly, regarding accurate fertilization, the operation and distribution of nutrients are generally carried out by combining with the conventional fertilization frequency, and even if the total nutrient supply reaches a reasonable level according to the soil measurement result, the fertilizer efficiency still cannot be maximized if the nutrient supply and the crop growth cannot be synchronized.
For accurate irrigation, soil water content data monitoring based on a soil moisture content instrument is generally set according to a single threshold value on the determination of an irrigation compensation point (water shortage stress point), and the real-time judgment is not fully performed by combining weather and crop root water absorption change; in the aspect of irrigation prediction,coefficient of crop KCThe method usually adopts a common method to predict the evapotranspiration ET of the corresponding crop growth stageCThe simulation of water consumption is influenced by irrigation, rainfall and drought stress and has deviation from the measured value.
And fourthly, a decision for automatically providing irrigation and fertilization based on an algorithm and crop growth dynamics is lacked, and the user experience is poor for a single fertilization decision system or an irrigation decision system.
Disclosure of Invention
The invention mainly aims to overcome the defects of the prior art and provide a dynamic decision method and a dynamic decision system for fertilization and irrigation.
According to one aspect of the present invention, there is provided a method for dynamic decision of fertilization and irrigation, the method comprising the steps of:
s1, the mobile terminal receives a decision request of a user, wherein the decision request is used for requesting the mobile terminal to generate a decision scheme, and the decision scheme comprises a fertilization scheme and an irrigation scheme;
s2, the mobile terminal sends a scheduling request to a background management system and an IOT management platform to request to generate decision information required by the decision scheme;
and S3, the mobile terminal receives the decision information returned by the background management system and the IOT management platform, and generates the decision scheme based on the decision information.
Preferably, the decision information stored by the background management system comprises a phenological algorithm, a fertilization algorithm, an irrigation algorithm, lattice point meteorological data, a soil parameter table and a crop parameter table; the decision information stored by the IOT management platform comprises meteorological station data and soil moisture content instrument data.
Preferably, calculating the phenological stage of the crop based on the phenological algorithm specifically includes:
calculating the phenological stage of the crop by using a growth degree-of-day GDD method and sowing time; wherein, GDD is the accumulated effective temperature value of the crop in the specific growth stage under the actual environmental condition, and the formula is as follows: GDDs ═ Σ [ (Tav-Tb ], where Tav is daily average soil temperature or air temperature, Tb is biological zero temperature, i.e. the lower limit temperature of the growth and development process of the crop, GDD is calculated based on the soil temperature Tav when the specific stage is the vegetative growth stage of the crop, and GDD is calculated based on the air temperature Tav when the specific stage is the reproductive growth stage of the crop.
Preferably, the calculating of the fertilization scheme based on the fertilization algorithm specifically includes:
firstly, soil nutrient detection based on a block level: after sampling and processing soil of a plough layer of a land mass, carrying out soil chemical detection to obtain nutrient data representing soil fertility characteristics;
secondly, establishing a target yield: setting a target yield per mu which can be achieved in the production of specific regions, crops and varieties in the season;
thirdly, determining soil nutrients by establishing and retrieving a soil nutrient abundance and deficiency evaluation system, and retrieving a corresponding total nutrient recommended value according to a nutrient threshold range where a soil nutrient test value is located and a target yield;
fourthly, nutrient operation: distributing the total nutrients according to recommended amounts of base fertilizer and additional fertilizer according to nutrient demand rules of crops at different growth stages;
and fifthly, recommending fertilizers: according to the fertilizer and the nutrient formula thereof selected by the user at the mobile terminal at different growth stages, the corresponding fertilizer nutrient utilization rate at the background is called to calculate the fertilizer dosage, and if the fertilizer formula selected by the user is not matched with the nutrient proportion at a certain growth stage of crops, the fertilizer is calculated and recommended according to the default fertilizer of the system.
Preferably, calculating an irrigation scheme based on the irrigation algorithm specifically comprises:
(1) collecting soil moisture data by using a soil moisture sensor based on a frequency domain reflection principle; acquiring the volume water content of each layer of soil, and transmitting the volume water content to an IOT management platform for data storage and display;
(2) measuring the field water capacity of the soil by using a soil moisture sensor, and determining the field water capacity W according to a soil moisture content accumulation curveTian ChiAs a calculated upper limit for irrigation;
(3) establishing a root depth recognition model according to the daily and night humidity change rates of the root layer and the non-root layer of the crop, and calculating the root depth of the crop;
(4) calculating compensation/stress and wilting points:
when the change curve of the soil moisture shows that the water consumption rate is reduced, the inflection point of the change is taken as a stress point/compensation point WStressSetting the point as an irrigation starting point; when the water in the soil is continuously reduced to the water consumption rate close to 0 in the root zone range, the crops can not obtain water from the soil, and the water is expressed as withering and even death, namely the withering point WWithering and withering；
(5) Irrigation quantity calculation
Irrigation quantity (W)Tian ChiCurrent soil moisture content)/100 root depth irrigation area
(6) And (3) irrigation prediction:
calculate the evapotranspiration amount ∑jET and soil moisture content WReal timeIn units of mm
When W isReal time≤WStressThe day is the irrigation date;
when W isReal time>WStressCalculating WReal time–∑jET value: when W isReal time–∑jWhen ET is less than or equal to 0, the j day is the irrigation date, wherein j is less than or equal to 7; otherwise, irrigation is not carried out within seven days in the future.
According to another aspect of the invention, the invention also provides a fertilization and irrigation dynamic decision system, which comprises a mobile terminal, a background management system and an IOT management platform; the mobile terminal comprises a basic information module, a soil moisture content prediction module, a water and fertilizer recommendation module and a planning and recording module;
the mobile terminal receives a decision request of a user, wherein the decision request is used for requesting the mobile terminal to generate a decision scheme, and the decision scheme comprises a fertilization scheme and an irrigation scheme;
the mobile terminal sends a scheduling request to a background management system and an IOT management platform to request for generating decision information required by the decision scheme;
and the mobile terminal receives the decision information returned by the background management system and the IOT management platform and generates the decision scheme based on the decision information.
Preferably, the decision information stored by the background management system comprises a phenological algorithm, a fertilization algorithm, an irrigation algorithm, lattice point meteorological data, a soil parameter table and a crop parameter table; the decision information stored by the IOT management platform comprises meteorological station data and soil moisture content instrument data.
Preferably, calculating the phenological stage of the crop based on the phenological algorithm specifically includes:
calculating the phenological stage of the crop by using a growth degree-of-day GDD method and sowing time; wherein, GDD is the accumulated effective temperature value of the crop in the specific growth stage under the actual environmental condition, and the formula is as follows: GDDs ═ Σ [ (Tav-Tb ], where Tav is daily average soil temperature or air temperature, Tb is biological zero temperature, i.e. the lower limit temperature of the growth and development process of the crop, GDD is calculated based on the soil temperature Tav when the specific stage is the vegetative growth stage of the crop, and GDD is calculated based on the air temperature Tav when the specific stage is the reproductive growth stage of the crop.
Preferably, the calculating of the fertilization scheme based on the fertilization algorithm specifically includes:
firstly, soil nutrient detection based on a block level: after sampling and processing soil of a plough layer of a land mass, carrying out soil chemical detection to obtain nutrient data representing soil fertility characteristics;
secondly, establishing a target yield: setting a target yield per mu which can be achieved in the production of specific regions, crops and varieties in the season;
thirdly, determining soil nutrients by establishing and retrieving a soil nutrient abundance and deficiency evaluation system, and retrieving a corresponding total nutrient recommended value according to a nutrient threshold range where a soil nutrient test value is located and a target yield;
fourthly, nutrient operation: distributing the total nutrients according to recommended amounts of base fertilizer and additional fertilizer according to nutrient demand rules of crops at different growth stages;
and fifthly, recommending fertilizers: according to the fertilizer and the nutrient formula thereof selected by the user at the mobile terminal at different growth stages, the corresponding fertilizer nutrient utilization rate at the background is called to calculate the fertilizer dosage, and if the fertilizer formula selected by the user is not matched with the nutrient proportion at a certain growth stage of crops, the fertilizer is calculated and recommended according to the default fertilizer of the system.
Preferably, calculating an irrigation scheme based on the irrigation algorithm specifically comprises:
(1) collecting soil moisture data by using a soil moisture sensor based on a frequency domain reflection principle; acquiring the volume water content of each layer of soil, and transmitting the volume water content to an IOT management platform for data storage and display;
(2) measuring the field water capacity of the soil by using a soil moisture sensor, and determining the field water capacity W according to a soil moisture content accumulation curveTian ChiAs a calculated upper limit for irrigation;
(3) establishing a root depth recognition model according to the daily and night humidity change rates of the root layer and the non-root layer of the crop, and calculating the root depth of the crop;
(4) calculating compensation/stress and wilting points:
when the change curve of the soil moisture shows that the water consumption rate is reduced, the inflection point of the change is taken as a stress point/compensation point WStressSetting the point as an irrigation starting point; when the water in the soil is continuously reduced to the water consumption rate close to 0 in the root zone range, the crops can not obtain water from the soil, and the water is expressed as withering and even death, namely the withering point WWithering and withering；
(5) Irrigation quantity calculation
Irrigation quantity (W)Tian ChiCurrent soil moisture content)/100 root depth irrigation area
(6) And (3) irrigation prediction:
calculate the evapotranspiration amount ∑jET and soil moisture content WReal timeIn units of mm
When W isReal time≤WStressThe day is the irrigation date;
when W isReal time>WStressCalculating WReal time–∑jET value: when W isReal time–∑jWhen ET is less than or equal to 0, the j day is the irrigation date, wherein j is less than or equal to 7; otherwise, irrigation is not carried out within seven days in the future.
Has the advantages that: according to the method, by constructing the crop phenological model, the irrigation model based on soil moisture monitoring and the fertilization model based on soil testing and fertilization, soil moisture data and daily weather data of a specific plot are comprehensively and intelligently analyzed, the growth stages are divided according to experience in the crop growth period, the single irrigation compensation point threshold is determined according to the experience coefficient, and the crop K is determined according to the experience coefficientCThe 3 defects of the coefficient realize the depth perception and dynamic understanding of soil moisture content, crop root water consumption and crop growth stage change, provide real-time and precise water and fertilizer management suggestions for users through a designed and developed water and fertilizer dynamic decision system, effectively improve the utilization efficiency of field moisture and nutrients, and have important significance for developing high-efficiency water-saving agriculture. Meanwhile, the water and fertilizer decision system designed and developed by the invention carries out graphical display and operation on the water and fertilizer suggestions, has intuitive and simple interface, is easy for farmers to operate, does not need complicated parameter input, and is easy to propagate and popularize.
The features and advantages of the present invention will become apparent by reference to the following drawings and detailed description of specific embodiments of the invention.
Drawings
FIG. 1 is a flow chart of a fertilization and irrigation dynamic decision method of the present invention;
fig. 2 is a schematic diagram of the fertilization and irrigation dynamic decision system structure of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
Fig. 1 is a flow chart of a fertilization and irrigation dynamic decision method of the present invention. As shown in fig. 1, the present invention provides a fertilization and irrigation dynamic decision method, which comprises the following steps:
and S1, the mobile terminal receives a decision request of a user, wherein the decision request is used for requesting the mobile terminal to generate a decision scheme, and the decision scheme comprises a fertilization scheme and an irrigation scheme.
In the step, an APP is installed on a mobile terminal, and the APP in the mobile terminal comprises a basic information module, a soil moisture content prediction module, a water and fertilizer recommendation module and a planning and recording module; the user can send a decision request by clicking a corresponding module in the APP, for example, clicking a phenological stage module in the water and fertilizer recommendation module, and then the mobile terminal can be excited to call an algorithm and parameters in the background management system and data in the IOT management platform to calculate the phenological stage of the corresponding crop.
S2, the mobile terminal sends a scheduling request to a background management system and an IOT management platform to request to generate decision information required by the decision scheme;
in this step, the mobile terminal establishes a connection with the background management system and the IOT management platform in a wireless manner, and sends a scheduling request to the background management system and the IOT management platform. The decision information which is requested to be scheduled by the mobile terminal comprises an algorithm, parameters and data, wherein the decision information stored by the background management system comprises a phenological algorithm, a fertilization algorithm, an irrigation algorithm, lattice meteorological data, a soil parameter table and a crop parameter table; the decision information stored by the IOT management platform comprises meteorological station data and soil moisture content instrument data.
And S3, the mobile terminal receives the decision information returned by the background management system and the IOT management platform, and generates the decision scheme based on the decision information.
In the step, if the user requests to generate the fertilization scheme, the mobile terminal generates the fertilization scheme through decision information of a scheduling background management system and an IOT management platform, displays the fertilization scheme on an interface of the mobile terminal, and stores the fertilization scheme in a planning and recording module, so that the user can look up the fertilization scheme conveniently in the future. And if the user requests that the irrigation scheme is generated, the mobile terminal generates the irrigation scheme through the decision information of the scheduling background management system and the IOT management platform, and displays and stores the irrigation scheme.
Preferably, calculating the phenological stage of the crop based on the phenological algorithm specifically includes:
calculating the phenological stage of the crop by using a growth degree-of-day GDD method and sowing time; wherein, GDD is the accumulated effective temperature value of the crop in the specific growth stage under the actual environmental condition, and the formula is as follows: GDDs ═ Σ [ (Tav-Tb ], where Tav is daily average soil temperature or air temperature, Tb is biological zero temperature, i.e. the lower limit temperature of the growth and development process of the crop, GDD is calculated based on the soil temperature Tav when the specific stage is the vegetative growth stage of the crop, and GDD is calculated based on the air temperature Tav when the specific stage is the reproductive growth stage of the crop.
Specifically, Tav in the formula is daily average soil or air temperature, data of a meteorological station and a soil moisture content instrument are called for calculation and acquisition, the acquisition frequency is in the order of minutes, and the data under all frequencies are directly used for averaging. The embodiment sets and calculates the biological zero point according to different growth stages of different crops in a segmented manner, and the simulation precision is high. Taking cotton as an example for explanation:
different growth stages, biological zero temperature setting:
Figure BDA0002974461410000101
GDD calculation method in different growth stages;
vegetative growth stage: (bud sowing), GDD calculation based on soil temperature
In the period from sowing to budding and when the ground temperature has the greatest influence on cotton plants, most carbohydrate energy of the cotton plants is directly used for root growth, and the effective accumulated temperature of soil with the surface area of 5cm is calculated.
Reproductive growth stage: (bud to boll), GDD calculation based on air temperature
The cotton plants are greatly influenced by the temperature after budding and then grow in a reproductive mode, and the calculation needs to be carried out on the basis of the air temperature by combining different biological zero temperatures in all climatic stages.
Preferably, the calculating of the fertilization scheme based on the fertilization algorithm specifically includes:
firstly, soil nutrient detection based on a block level: after sampling and processing soil of a plough layer of a land mass, carrying out soil chemical detection to obtain nutrient data representing soil fertility characteristics;
specifically, after the processing processes of S-shaped multipoint sampling, quartering and mixing, drying and sample grinding and sieving are carried out on the plot plough layer soil, soil chemical detection is carried out, and nutrient data representing soil fertility characteristics including but not limited to soil organic matters, pH and effective content of 13 large essential nutrient elements (N, P, K, Mg, Zn and the like) are obtained.
Secondly, establishing a target yield: setting a target yield per mu which can be achieved in the production of specific regions, crops and varieties in the season; the step can be customized by the user.
Thirdly, establishing and searching a soil nutrient shortage evaluation system to determine whether soil nutrients are in shortage, suitable or excessive, and searching a corresponding total nutrient recommended value according to a nutrient threshold range where a soil nutrient test value is located and a target yield;
fourthly, nutrient operation: distributing the total nutrients according to recommended amounts of base fertilizer and additional fertilizer according to nutrient demand rules of crops at different growth stages;
and fifthly, recommending fertilizers: according to the fertilizer and the nutrient formula thereof selected by the user at the mobile terminal at different growth stages, the corresponding fertilizer nutrient utilization rate at the background is called to calculate the fertilizer dosage, and if the fertilizer formula selected by the user is not matched with the nutrient proportion at a certain growth stage of crops, the fertilizer is calculated and recommended according to the default fertilizer of the system.
Preferably, calculating an irrigation scheme based on the irrigation algorithm specifically comprises:
(1) collecting soil moisture data by using a soil moisture sensor based on a frequency domain reflection principle; acquiring the volume water content of each layer of soil, and transmitting the volume water content to an IOT management platform for data storage and display; the monitoring depth is selected according to the effective root depth range of crops, and the data acquisition frequency is in the order of minutes.
(2) Measuring the field water capacity of the soil by using a soil moisture sensor, and determining the field water capacity W according to a soil moisture content accumulation curveTian ChiAs the upper limit for the calculation of irrigation quantity.
(3) Establishing a root depth recognition model according to the daily and night humidity change rates of the root layer and the non-root layer of the crop, and calculating the root depth of the crop;
crops absorb water through root systems to maintain life activities, the depth of the root systems determines the depth of the crops absorbing the water, about 99% of the absorbed water is used for transpiration, and the transpiration is influenced by factors such as temperature, illumination, wind speed and the like. Based on the method, the day and night humidity change in the range of the root layer and the non-root layer show different change rates, so that the root depth identification method is established.
(4) Calculating compensation/stress and wilting points:
when the change curve of the soil moisture shows that the water consumption rate is reduced, the inflection point of the change is taken as a stress point/compensation point WStressSetting the point as an irrigation starting point; when the water in the soil is continuously reduced to the water consumption rate close to 0 in the root zone range, the crops can not obtain water from the soil, and the water is expressed as withering and even death, namely the withering point WWithering and withering；
Specifically, soil moisture content is reduced through processes such as soil evaporation, infiltration, runoff, and crop transpiration. Runoff and infiltration occur in the early stage of irrigation or rainfall and tend to be stable quickly, the water consumption way is changed into soil evaporation and crop transpiration, the soil evaporation is called as evaporation for short, the soil moisture is continuously reduced along with the evaporation, the difficulty of the crop absorbing water from the soil is gradually increased, the overground part gradually shows a drought-affected phenomenon, the change curve of the soil moisture shows that the water consumption rate is reduced, and the changed inflection point is a stress point/compensation point WStressThis point is usually set to irrigateA starting point; when the water in the soil is continuously reduced to the water consumption rate close to 0 in the root zone range, the crops can not obtain water from the soil, and the water is expressed as withering and even death, namely the withering water content WWithering and withering。
(5) Irrigation quantity calculation
Irrigation quantity (W)Tian ChiCurrent soil moisture content)/100 root depth irrigation area
(6) The irrigation prediction specifically comprises the following steps:
calculate the evapotranspiration amount ∑jET and soil moisture content WReal timeIn units of mm
Evapotranspiration: the weather forecast data is obtained, the weather data of 7 days in the future is obtained, and the reference crop evapotranspiration ET is calculated according to the evapotranspiration formula of FAO0Combining the K of different periods of the cropCObtaining the daily evapotranspiration of 7 days in the future by sigmajET＝ET0*KCAnd represents the cumulative evapotranspiration to day j in the future.
The water content of the soil is as follows: obtaining the soil water content W in the current effective root depth rangeReal time。
Calculating irrigation date:
when W isReal time≤WStressThe day is the irrigation date;
when W isReal time>WStressCalculating WReal time–∑jET value: when W isReal time–∑jWhen ET is less than or equal to 0, the j day is the irrigation date, wherein j is less than or equal to 7; otherwise, irrigation is not carried out within seven days in the future.
According to the method, by constructing the crop phenological model, the irrigation model based on soil moisture monitoring and the fertilization model based on soil testing and fertilization, soil moisture data and daily weather data of a specific plot are comprehensively and intelligently analyzed, the growth stages are divided according to experience in the crop growth period, the single irrigation compensation point threshold is determined according to the experience coefficient, and the crop K is determined according to the experience coefficientC3, realizing the deep perception and dynamic understanding of soil moisture content, crop root water consumption and crop growth stage change, and providing users with a water and fertilizer dynamic decision system through design and developmentProvides a real-time and precise water and fertilizer management suggestion, effectively improves the utilization efficiency of water and nutrients in the field, and has important significance for developing high-efficiency water-saving agriculture. Meanwhile, the water and fertilizer decision system designed and developed by the invention carries out graphical display and operation on the water and fertilizer suggestions, has intuitive and simple interface, is easy for farmers to operate, does not need complicated parameter input, and is easy to propagate and popularize.
Example 2
Fig. 2 is a schematic diagram of the fertilization and irrigation dynamic decision system structure of the invention. As shown in fig. 2, the present invention further provides a fertilization and irrigation dynamic decision system, which includes a mobile terminal, a background management system and an IOT management platform; the mobile terminal comprises a basic information module, a soil moisture content prediction module, a water and fertilizer recommendation module and a planning and recording module;
the mobile terminal receives a decision request of a user, wherein the decision request is used for requesting the mobile terminal to generate a decision scheme, and the decision scheme comprises a fertilization scheme and an irrigation scheme;
the mobile terminal sends a scheduling request to a background management system and an IOT management platform to request for generating decision information required by the decision scheme;
and the mobile terminal receives the decision information returned by the background management system and the IOT management platform and generates the decision scheme based on the decision information.
Preferably, the decision information stored by the background management system comprises a phenological algorithm, a fertilization algorithm, an irrigation algorithm, lattice point meteorological data, a soil parameter table and a crop parameter table; the decision information stored by the IOT management platform comprises meteorological station data and soil moisture content instrument data.
Preferably, calculating the phenological stage of the crop based on the phenological algorithm specifically includes:
calculating the phenological stage of the crop by using a growth degree-of-day GDD method and sowing time; wherein, GDD is the accumulated effective temperature value of the crop in the specific growth stage under the actual environmental condition, and the formula is as follows: GDDs ═ Σ [ (Tav-Tb ], where Tav is daily average soil temperature or air temperature, Tb is biological zero temperature, i.e. the lower limit temperature of the growth and development process of the crop, GDD is calculated based on the soil temperature Tav when the specific stage is the vegetative growth stage of the crop, and GDD is calculated based on the air temperature Tav when the specific stage is the reproductive growth stage of the crop.
Preferably, the calculating of the fertilization scheme based on the fertilization algorithm specifically includes:
firstly, soil nutrient detection based on a block level: after sampling and processing soil of a plough layer of a land mass, carrying out soil chemical detection to obtain nutrient data representing soil fertility characteristics;
secondly, establishing a target yield: setting a target yield per mu which can be achieved in the production of specific regions, crops and varieties in the season;
thirdly, determining soil nutrients by establishing and retrieving a soil nutrient abundance and deficiency evaluation system, and retrieving a corresponding total nutrient recommended value according to a nutrient threshold range where a soil nutrient test value is located and a target yield;
fourthly, nutrient operation: distributing the total nutrients according to recommended amounts of base fertilizer and additional fertilizer according to nutrient demand rules of crops at different growth stages;
and fifthly, recommending fertilizers: according to the fertilizer and the nutrient formula thereof selected by the user at the mobile terminal at different growth stages, the corresponding fertilizer nutrient utilization rate at the background is called to calculate the fertilizer dosage, and if the fertilizer formula selected by the user is not matched with the nutrient proportion at a certain growth stage of crops, the fertilizer is calculated and recommended according to the default fertilizer of the system.
Preferably, calculating an irrigation scheme based on the irrigation algorithm specifically comprises:
(1) collecting soil moisture data by using a soil moisture sensor based on a frequency domain reflection principle; acquiring the volume water content of each layer of soil, and transmitting the volume water content to an IOT management platform for data storage and display;
(2) measuring the field water capacity of the soil by using a soil moisture sensor, and determining the field water capacity W according to a soil moisture content accumulation curveTian ChiAs a calculated upper limit for irrigation;
(3) establishing a root depth recognition model according to the daily and night humidity change rates of the root layer and the non-root layer of the crop, and calculating the root depth of the crop;
(4) calculating compensation/stress and wilting points:
when the change curve of the soil moisture shows that the water consumption rate is reduced, the inflection point of the change is taken as a stress point/compensation point WStressSetting the point as an irrigation starting point; when the water in the soil is continuously reduced to the water consumption rate close to 0 in the root zone range, the crops can not obtain water from the soil, and the water is expressed as withering and even death, namely the withering point WWithering and withering；
(5) Irrigation quantity calculation
Irrigation quantity (W)Tian ChiCurrent soil moisture content)/100 root depth irrigation area
(6) And (3) irrigation prediction:
calculate the evapotranspiration amount ∑jET and soil moisture content WReal timeIn units of mm
When W isReal time≤WStressThe day is the irrigation date;
when W isReal time>WStressCalculating WReal time–∑jET value: when W isReal time–∑jWhen ET is less than or equal to 0, the j day is the irrigation date, wherein j is less than or equal to 7; otherwise, irrigation is not carried out within seven days in the future.
The specific implementation process of the method steps executed by the mobile terminal, the background management system and the IOT management platform in embodiment 2 of the present invention is the same as the implementation process of each step in embodiment 1, and is not described herein again.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all modifications and equivalents of the present invention, which are made by the contents of the present specification and the accompanying drawings, or directly/indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims (10)

1. A method for dynamic decision making for fertilization and irrigation, the method comprising the steps of:
s1, the mobile terminal receives a decision request of a user, wherein the decision request is used for requesting the mobile terminal to generate a decision scheme, and the decision scheme comprises a fertilization scheme and an irrigation scheme;
s2, the mobile terminal sends a scheduling request to a background management system and an IOT management platform to request to generate decision information required by the decision scheme;
and S3, the mobile terminal receives the decision information returned by the background management system and the IOT management platform, and generates the decision scheme based on the decision information.
2. The method of claim 1, wherein the decision information stored by the back-end management system includes a phenological algorithm, a fertilization algorithm, an irrigation algorithm, grid point meteorological data, a soil parameter table, a crop parameter table; the decision information stored by the IOT management platform comprises meteorological station data and soil moisture content instrument data.
3. The method according to claim 2, wherein calculating the phenological stage of the crop based on the phenological algorithm specifically comprises:
calculating the phenological stage of the crop by using a growth degree-of-day GDD method and sowing time; wherein, GDD is the accumulated effective temperature value of the crop in the specific growth stage under the actual environmental condition, and the formula is as follows: GDDs ═ Σ [ (Tav-Tb ], where Tav is daily average soil temperature or air temperature, Tb is biological zero temperature, i.e. the lower limit temperature of the growth and development process of the crop, GDD is calculated based on the soil temperature Tav when the specific stage is the vegetative growth stage of the crop, and GDD is calculated based on the air temperature Tav when the specific stage is the reproductive growth stage of the crop.
4. The method according to claim 2, wherein calculating a fertilization scheme based on the fertilization algorithm specifically comprises:
firstly, soil nutrient detection based on a block level: after sampling and processing soil of a plough layer of a land mass, carrying out soil chemical detection to obtain nutrient data representing soil fertility characteristics;
secondly, establishing a target yield: setting a target yield per mu which can be achieved in the production of specific regions, crops and varieties in the season;
thirdly, determining soil nutrients by establishing and retrieving a soil nutrient abundance and deficiency evaluation system, and retrieving a corresponding total nutrient recommended value according to a nutrient threshold range where a soil nutrient test value is located and a target yield;
fourthly, nutrient operation: distributing the total nutrients according to recommended amounts of base fertilizer and additional fertilizer according to nutrient demand rules of crops at different growth stages;
and fifthly, recommending fertilizers: according to the fertilizer and the nutrient formula thereof selected by the user at the mobile terminal at different growth stages, the corresponding fertilizer nutrient utilization rate at the background is called to calculate the fertilizer dosage, and if the fertilizer formula selected by the user is not matched with the nutrient proportion at a certain growth stage of crops, the fertilizer is calculated and recommended according to the default fertilizer of the system.
5. The method according to claim 2, wherein calculating an irrigation scheme based on the irrigation algorithm comprises:
(1) collecting soil moisture data by using a soil moisture sensor based on a frequency domain reflection principle; acquiring the volume water content of each layer of soil, and transmitting the volume water content to an IOT management platform for data storage and display;
(2) measuring the field water capacity of the soil by using a soil moisture sensor, and determining the field water capacity W according to a soil moisture content accumulation curveTian ChiAs a calculated upper limit for irrigation;
(3) establishing a root depth recognition model according to the daily and night humidity change rates of the root layer and the non-root layer of the crop, and calculating the root depth of the crop;
(4) calculating compensation/stress and wilting points:
when the change curve of the soil moisture shows that the water consumption rate is reduced, the inflection point of the change is taken as a stress point/compensation point WStressSetting the point as an irrigation starting point; when the water in the soil is continuously reduced to the water consumption rate close to 0 in the root zone range, the crops can not obtain the water from the soil,shows withering and even death, namely the withering point WWithering and withering；
(5) Irrigation quantity calculation
Irrigation quantity (W)Tian ChiCurrent soil moisture content)/100 root depth irrigation area
(6) And (3) irrigation prediction:
calculate the evapotranspiration amount ∑jET and soil moisture content WReal timeIn units of mm
When W isReal time≤WStressThe day is the irrigation date;
when W isReal time>WStressCalculating WReal time–∑jET value: when W isReal time–∑jWhen ET is less than or equal to 0, the j day is the irrigation date, wherein j is less than or equal to 7; otherwise, irrigation is not carried out within seven days in the future.
6. A fertilization and irrigation dynamic decision system is characterized by comprising a mobile terminal, a background management system and an IOT management platform; the mobile terminal comprises a basic information module, a soil moisture content prediction module, a water and fertilizer recommendation module and a planning and recording module;
the mobile terminal receives a decision request of a user, wherein the decision request is used for requesting the mobile terminal to generate a decision scheme, and the decision scheme comprises a fertilization scheme and an irrigation scheme;
the mobile terminal sends a scheduling request to a background management system and an IOT management platform to request for generating decision information required by the decision scheme;
and the mobile terminal receives the decision information returned by the background management system and the IOT management platform and generates the decision scheme based on the decision information.
7. The system of claim 6, wherein the decision information stored by the back-end management system includes a phenological algorithm, a fertilization algorithm, an irrigation algorithm, grid point meteorological data, a soil parameter table, a crop parameter table; the decision information stored by the IOT management platform comprises meteorological station data and soil moisture content instrument data.
8. The system according to claim 7, wherein calculating the phenological stage of the crop based on the phenological algorithm specifically comprises:
calculating the phenological stage of the crop by using a growth degree-of-day GDD method and sowing time; wherein, GDD is the accumulated effective temperature value of the crop in the specific growth stage under the actual environmental condition, and the formula is as follows: GDDs ═ Σ [ (Tav-Tb ], where Tav is daily average soil temperature or air temperature, Tb is biological zero temperature, i.e. the lower limit temperature of the growth and development process of the crop, GDD is calculated based on the soil temperature Tav when the specific stage is the vegetative growth stage of the crop, and GDD is calculated based on the air temperature Tav when the specific stage is the reproductive growth stage of the crop.
9. The system of claim 7, wherein calculating a fertilization protocol based on the fertilization algorithm comprises:
firstly, soil nutrient detection based on a block level: after sampling and processing soil of a plough layer of a land mass, carrying out soil chemical detection to obtain nutrient data representing soil fertility characteristics;
secondly, establishing a target yield: setting a target yield per mu which can be achieved in the production of specific regions, crops and varieties in the season;
thirdly, determining soil nutrients by establishing and retrieving a soil nutrient abundance and deficiency evaluation system, and retrieving a corresponding total nutrient recommended value according to a nutrient threshold range where a soil nutrient test value is located and a target yield;
fourthly, nutrient operation: distributing the total nutrients according to recommended amounts of base fertilizer and additional fertilizer according to nutrient demand rules of crops at different growth stages;
and fifthly, recommending fertilizers: according to the fertilizer and the nutrient formula thereof selected by the user at the mobile terminal at different growth stages, the corresponding fertilizer nutrient utilization rate at the background is called to calculate the fertilizer dosage, and if the fertilizer formula selected by the user is not matched with the nutrient proportion at a certain growth stage of crops, the fertilizer is calculated and recommended according to the default fertilizer of the system.
10. The system according to claim 7, wherein calculating an irrigation scheme based on the irrigation algorithm comprises:
(1) collecting soil moisture data by using a soil moisture sensor based on a frequency domain reflection principle; acquiring the volume water content of each layer of soil, and transmitting the volume water content to an IOT management platform for data storage and display;
(2) measuring the field water capacity of the soil by using a soil moisture sensor, and determining the field water capacity W according to a soil moisture content accumulation curveTian ChiAs a calculated upper limit for irrigation;
(3) establishing a root depth recognition model according to the daily and night humidity change rates of the root layer and the non-root layer of the crop, and calculating the root depth of the crop;
(4) calculating compensation/stress and wilting points:
when the change curve of the soil moisture shows that the water consumption rate is reduced, the inflection point of the change is taken as a stress point/compensation point WStressSetting the point as an irrigation starting point; when the water in the soil is continuously reduced to the water consumption rate close to 0 in the root zone range, the crops can not obtain water from the soil, and the water is expressed as withering and even death, namely the withering point WWithering and withering；
(5) Irrigation quantity calculation
Irrigation quantity (W)Tian ChiCurrent soil moisture content)/100 root depth irrigation area
(6) And (3) irrigation prediction:
calculate the evapotranspiration amount ∑jET and soil moisture content WReal timeIn units of mm
When W isReal time≤WStressThe day is the irrigation date;
when W isReal time>WStressCalculating WReal time–∑jET value: when W isReal time–∑jWhen ET is less than or equal to 0, the j day is the irrigation date, wherein j is less than or equal to 7; otherwise, irrigation is not carried out within seven days in the future.
CN202110271826.1A 2021-03-12 2021-03-12 Dynamic decision-making method and system for fertilization and irrigation Pending CN113039908A (en)

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