CN115421539A - Method and system for cloud intelligent management of crop root water, fertilizer and soil properties - Google Patents
Method and system for cloud intelligent management of crop root water, fertilizer and soil properties Download PDFInfo
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- 239000003337 fertilizer Substances 0.000 title claims abstract description 59
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- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 24
- 230000004720 fertilization Effects 0.000 claims description 24
- 229910052760 oxygen Inorganic materials 0.000 claims description 24
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- 244000005700 microbiome Species 0.000 claims description 16
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Abstract
The invention provides a method and a system for cloud intelligent management of crop root water, fertilizer and soil properties, wherein the method comprises the following steps: obtaining growth environment information of crop roots in a health management area; determining a growth environment interference item of the root of the crop in the health management area; determining the priority and the interference degree of the interference item of the growing environment according to the growing environment information by adopting an interference item interference degree algorithm; and regulating and managing the growth environment of the crop roots according to the priority and the interference degree of the growth environment interference items. The invention manages the most important rhizosphere part for plant nutrition and substance exchange in four aspects of water consumption, fertilizer consumption, gas consumption and medicine consumption of the plant so as to achieve the effect that 1 percent of rhizosphere management is more than 100 percent of field management, not only can realize the automation of plant health management, but also can save the control and management cost and improve the production and management efficiency.
Description
Technical Field
The invention relates to the technical field of automatic control, in particular to a method for carrying out cloud intelligent management on water, fertilizer and soil characteristics of crop roots and a system for carrying out cloud intelligent management on the water, fertilizer and soil characteristics of the crop roots.
Background
With the rapid progress of science and technology, the great change of modern agricultural automation, informatization and standardization brings the improvement of agricultural productivity, and the development of agricultural automation is the concrete embodiment of the progress of science and technology. However, agriculture is a huge and complex system, and not all sub-divided agricultural fields follow the historical trend in automated processes, such as fruit farming. The orchard mechanization degree in China is still in a starting stage, although the research and development of orchard mechanization and intellectualization are very fast, due to the complexity of an orchard and the dependence on agricultural experience, the popularization degree of orchard automation is not high at present, orchard management operation is mainly performed manually, and the fruit industry production efficiency is greatly reduced.
Disclosure of Invention
The invention aims to solve the technical problems and provides a method for carrying out cloud intelligent management on water and fertilizer of crop roots and soil properties, the most important rhizosphere part of plant nutrition and matter exchange is managed in four aspects of water use, fertilizer use, gas use and medicine use of plants, so that the effect of 1% rhizosphere management of more than 100% field management is achieved, the automation of plant health management can be realized, the control and management cost can be saved, and the production management efficiency can be improved.
The technical scheme adopted by the invention is as follows:
a method for carrying out cloud intelligent management on crop root water, fertilizer and soil properties comprises the following steps: obtaining growth environment information of crop roots in a health management area; determining a growth environment interference item of the root of the crop in the health management area; determining the priority and the interference degree of the interference item of the growth environment according to the information of the growth environment by adopting an interference item interference degree algorithm; and regulating and managing the growth environment of the crop roots according to the priority and the interference degree of the growth environment interference item.
According to one embodiment of the present invention, the growth environment information includes soil temperature, soil humidity, soil oxygen concentration, soil PH, soil EC, and soil respiration rate.
According to one embodiment of the present invention, the growth environment disturbance items include irrigation water amount, fertilization amount, oxygen addition amount, and microbial addition amount.
According to an embodiment of the present invention, the interference term disturbance degree algorithm is:
wherein x is i Representing the degree of interference of the i-th growth environment interference term, f i,j () Representing a functional relationship, y ', between each of the growth environment disturbance terms and the growth environment information' j Initial value, y, representing the jth of the growth environment information " j A target value representing jth of said growth environment information, a j And d represents the weight of the growth environment information difference value j, and delta represents the weighted difference value of the overall growth environment information.
According to one embodiment of the invention, the priority of the growing environment interference term is determined by the weight.
According to one embodiment of the invention, the interference level of the growing environment interference term is determined by calculating the overall weighted difference minimum.
According to one embodiment of the invention, the soil microorganism amount is characterized by the soil respiration rate, and specifically, the soil respiration rate is characterized by the following model:
wherein W represents the amount of soil microorganisms, h represents the duration of monitoring, and W h0 Representing the initial soil microbial biomass, R representing the intrinsic growth rate, SRV representing the total respiration rate of the soil, and SRVR representing the respiration rate of the soil roots.
According to one embodiment of the invention, x n The following formula is used to obtain:
x n ＝εQ i ÷(εQ i ÷y i )
wherein Q i Weight, y, representing the ith said growth circumstance information i An availability value representing an ith one of the growth environment information.
In accordance with one embodiment of the present invention,
y i the following formula is used to obtain:
y i ＝WPF i ÷WPF s
wherein, WPF i Current value, WPF, representing the ith said growth circumstance information s An optimum value indicating the ith growth environment information;
Q i the following formula is used to obtain:
wherein, Y i 0.5 Represents a value at which the actual growth rate of soil microorganisms is half the maximum growth rate.
A system for carrying out cloud intelligent management on crop root water, fertilizer and soil properties comprises: the system comprises an acquisition module, a management module and a management module, wherein the acquisition module is used for acquiring the growth environment information of the crop roots in a health management area; the input module is used for inputting and determining a growth environment interference item of the crop roots in the health management area; the processing module is used for determining the priority and the interference degree of the growth environment interference item according to the growth environment information by adopting an interference item disturbance degree algorithm; and the adjusting module is used for adjusting and managing the growth environment of the crop roots according to the priority and the interference degree of the growth environment interference item.
The invention has the beneficial effects that:
the invention manages the most important rhizosphere part for plant nutrition and substance exchange in four aspects of water consumption, fertilizer consumption, gas consumption and medicine consumption of the plant so as to achieve the effect that 1 percent of rhizosphere management is more than 100 percent of field management, not only can realize the automation of plant health management, but also can save the control and management cost and improve the production and management efficiency.
Drawings
FIG. 1 is a flow chart of a method for cloud intelligent management of water, fertilizer and soil properties of crop roots according to an embodiment of the present invention;
fig. 2 is a block diagram of a system for cloud intelligent management of water, fertilizer and soil properties of crop roots according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be 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 of the 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.
Fig. 1 is a flowchart of a method for cloud intelligent management of water, fertilizer and soil properties of crop roots according to an embodiment of the present invention.
As shown in fig. 1, the method for cloud intelligent management of water, fertilizer and soil properties of crop roots according to the embodiment of the invention comprises the following steps:
s1, obtaining growth environment information of crop roots in a health management area.
Specifically, growth environment information of crop roots in the health management area can be acquired through the data perception device. The growth environment information can comprise soil temperature, soil humidity, soil oxygen concentration, soil pH value, soil EC value and soil respiration rate, the data sensing equipment can comprise a soil temperature sensor, a soil humidity sensor, a soil water dissolved oxygen sensor, a soil pH value sensor, a soil EC value sensor and a soil respiration rate sensor, and the data sensing equipment can be used for correspondingly acquiring the soil temperature, the soil humidity, the soil oxygen concentration, the soil pH value, the soil EC value and the soil respiration rate of the crop root in the health management area.
And S2, determining a growth environment interference item of the crop roots in the health management area.
Specifically, the growth environment disturbance terms of the crop roots in the health management area can be determined according to the prior knowledge of the health management of the crop roots, and the growth environment disturbance terms can be determined to include irrigation water amount, fertilization amount, oxygen addition amount and microorganism addition amount.
And S3, determining the priority and the interference degree of the interference item of the growing environment according to the growing environment information by adopting an interference item disturbance degree algorithm.
Specifically, the disturbance degree algorithm of the interference term may be:
wherein x is i Representing the degree of interference of the i-th growth environment interference term, f i，j () Representing a functional relationship, y ', between each growth environment interference term and the growth environment information' j Initial value, y ″, representing jth growth environment information " j Target value representing jth growth environment information, a j Represents the weight of the j-th growth environment information difference value, and δ represents the weighted difference value of the overall growth environment information.
More specifically, the establishment process of the interference term disturbance degree algorithm of the embodiment of the present invention is as follows:
first, initial values of growth environment information acquired by the data sensing apparatus, i.e., the respective sensors, may be set to:
y’ i ，y’ 2 ，y’ 3 ，y’ 4 ...y’ m (m∈N)
where m represents the number of sensors and N represents an integer greater than or equal to zero.
Furthermore, the interference modes of the growth environment interference items, such as watering, fertilizing, oxygenating, medication and the like, can be set as follows:
x 1 ，x 2 ，x 3 ，x 4 ...x n (n∈N)
where n represents the type of interference pattern.
Further, the functional relationship between each interference mode and the growth environment information can be set as follows:
Δ(y 1 ，y 2 ...y j )＝f i，j (x 1 ，x 2 ，...，x i )(i，j∈N，0＜i≤n，0＜j≤m)
there is more than one disturbance item for each disturbance mode, for example, there are two disturbance items of irrigation water quantity and oxygen adding quantity for watering irrigation.
Further, the growth environment information obtained after each operation of the disturbance may be set as:
further, the target value of the growth environment information after each interference operation may be set as:
y” 1 ，y” 2 ，y” 3 ，y” 4 ....y” j (j∈N)；
thus, the difference between the initial value and the target value of each growth environment information can be obtained as:
δ i ＝|y” j -y j |。
furthermore, the importance degree of different growth environment information can be judged according to the prior knowledge, and corresponding weight can be set for each type of growth environment information according to the importance degree so as to obtain an integral weighted difference value:
further, can be
The disturbance degree algorithm of the interference term of the embodiment of the invention can be obtained by substituting the formula:
furthermore, the priority of the growth environment interference item can be determined through the weight of the growth environment information difference value, and the interference degree of the growth environment interference item, namely the interference mode, can be determined through calculating the overall weighted difference value minimum value.
In addition, it should be noted that there is a correlation between the soil respiration rate and the soil microbial biomass, activity and microbial community before the soil types are different, and therefore, the soil respiration rate can be used as a representative value of the soil microbial biomass in the present invention.
Specifically, the model for characterizing soil microbial load by soil respiration rate may be:
wherein W represents the amount of soil microorganisms, h represents the duration of monitoring, W h0 Representing the initial soil microbial biomass (which can be directly measured by soil collection), R representing the intrinsic growth rate (which can be measured by rhizosphere soil microbial experiment), SRV representing the total soil respiration rate (which can be measured by a soil respiration rate sensor), and SRVR representing the total soil respiration rateThe soil root respiration rate (the difference of the soil respiration rates inside and outside the area can be recorded by a soil respiration rate sensor by setting a root-free area).
More specifically, x n Can be obtained by the following formula:
x n ＝εQ i ÷(εQ i ÷y i )
wherein Q i Weight, y, representing the ith growth environment information i An available value representing the ith growth environment information.
Further, y i Can be obtained by the following formula:
y i ＝WPF i ÷WPF s
wherein, WPF i Current value, WPF, representing the ith growth circumstance information s An optimum value indicating the i-th growth environment information;
Q i can be obtained by the following formula:
wherein, Y i 0.5 Represents a value at which the actual growth rate of soil microorganisms is half the maximum growth rate. Drawing a curve chart by taking the usable value of the growth environment information as the abscissa and the growth rate of the soil microorganisms as the ordinate, and obtaining a weighted value Q through the equation set i The solution of (2) is approximated by multiple surfaces.
In addition, it should be noted that the plants cannot directly absorb the organic matters through the root system, and the consumption ways of the soil organic matters mainly include surface runoff, leaching loss and soil respiration, so that the accuracy of detecting the consumption of the soil organic matters on the rhizosphere soil of the water-saving irrigation agricultural farmland through the soil respiration rate is very high, correlation functions can be determined through test monitoring means for different soil types, and the change of the content of the soil organic matters can be calculated in real time.
Specifically, the simulation process of the functional relationship between the soil respiration rate and the soil organic matter may be: and (3) measuring the rhizosphere soil respiration value and the soil organic matter content of the area to be measured, wherein the sample size is not less than 100, and performing correlation analysis and regression analysis by adopting SPSS software and mapping. From this, it is possible to obtain:
linear model:
SRV-SRVR＝a+b×C÷f
power function model:
SRV-SRVR＝a×(C÷f) b
an index model:
SRV-SRVR＝a×e b×C÷f
wherein, a and b are condition coefficients, C is soil carbon content, and f is an organic matter conversion coefficient, which can be 1.724, and can be obtained by correlation analysis and regression analysis. The organic matter content can be obtained by solving an equation.
And S4, regulating and managing the growth environment of the crop roots according to the priority and the interference degree of the growth environment interference item.
Specifically, the growth environment of the crop roots can be adjusted and managed through the smart cloud platform according to the priority and the interference degree of the growth environment interference items, for example, corresponding health management control instructions can be generated through the smart cloud platform according to the priority and the interference degree of the growth environment interference items, so that water, fertilizer and gas can be used for regulating and controlling the nutrient and water supply, the soil oxygen content and the soil microbial biomass of the crop roots through the water and fertilizer integrated management system.
In addition, the method for cloud intelligent management of the water, the fertilizer and the soil properties of the crop roots can determine the priority and the interference degree of the interference items of the growing environment according to the plant species and the plant growth period, so that the healthy management of the crop roots is realized.
The invention has the following beneficial effects:
the invention manages the most important rhizosphere part for plant nutrition and substance exchange in four aspects of water consumption, fertilizer consumption, gas consumption and medicine consumption of the plant, so as to achieve the effect that 1 percent of rhizosphere management is more than 100 percent of field management.
The practical application effect of the method for cloud intelligent management of water, fertilizer and soil properties of crop roots will be further explained by taking the apple rhizosphere as an example.
In an embodiment of the present invention, taking irrigation of an apple orchard (only adding water) as an example, in the period of treetop, the target value of the growth environment information of the apple orchard and the weight value of each growth environment information are shown in table 1:
TABLE 1
Thus, the functional relationship between each interference mode and the growth environment information can be determined as follows:
wherein x is 1 Denotes the amount of irrigation water, x 2 Indicating the oxygen content of the irrigation water, y 1 Indicates soil moisture, y 2 Indicates the nitrogen content of the soil, y 3 Indicates the phosphorus content of the soil, y 4 Indicating potassium content in the soil, y 5 Indicating that the soil contains oxygen ppm, y 6 Representing the rate of decrease of the soil respiration rate, and a represents a 6 x 2 matrix.
Further, the matrix a may be set as:
wherein, y' 5 The initial value of the sensor is the oxygen ppm of the soil.
The following two sets of measured values were obtained by experiment, wherein the first set of measured values is shown in table 2:
TABLE 2
Referring to table 1, it can be seen that the target value of the apple orchard growth environment information should be greater than 10 in soil temperature, and thus even if the soil moisture deviates from the target value, no disturbing operation is performed here.
The second set of measured values is shown in table 3:
TABLE 3
Referring to table 1, it can be seen that the target value of the apple orchard growth environment information is that the soil temperature should be greater than 10, and thus when the soil temperature is greater than 10, the interference operation, i.e., the irrigation operation, may be performed.
Specifically, the measured values in table 3 can be substituted into the above formula to obtain:
Δ(y 1 ，y 2 ，y 3 ，y 4 ，y 5 ，y 6 )
＝(0.4x 1 ，-0.05x 1 ，-0.05x 1 ，-0.05x 1 ，0.08(x 2 -12)x 1 ，0.08(x 2 -12)x 1 )
further, the disturbance degree algorithm of the interference term in combination with the present invention can obtain:
further, carry in Δ (y) 1 ，y 2 ，y 3 ，y 4 ，y 5 ，y 6 ) The following can be obtained:
δ＝1×|7-0.4x 1 |+1.5×|0.1+0.05x 1 |+1.3×|0.05x 1 |+1.2×|0.05x 1 |+0.7×|0.08(12-x 2 )x 1 |+1.1×|0.06(12-x 2 )x 1 |
further, since the operation is interrupted only by irrigation and no oxygen is added, x can be obtained 2 =12, substituting the above formula yields:
δ＝1×|7-0.4x 1 |+1.5×|0.1+0.05x 1 |+1.3×|0.05x 1 |+1.2×|0.05x 1 |
further, byCalculating x determined by overall weighted difference delta minimum 1 The value:
x 1 ＝17.5
namely, the interference operation can obtain the minimum delta value after 17.5 cubic meters of water is irrigated to the apple orchard.
Test examples
In another embodiment of the invention, taking apple orchard fertilization as an example, the specific fertilization types and proportions are shown in tables 4-6, the test site can be a orchard area, the test time is 3 months-12 months, the tested apple variety is Fuji, the row spacing of planted plants is 2m × 4m, the planting area is 30 mu, and the treated area is about 10 mu/cell.
Specifically, 3 fertilization operations T1, T2, T3 can be designed, each fertilization operation being randomly repeated, with each experimental treatment as follows:
t1: and (3) conventional fertilization treatment: the specific fertilizing amount and the nutrient content are shown in a table 4;
t2: and (3) water and fertilizer integrated conventional fertilization treatment: the specific fertilizing amount and the nutrient content are shown in a table 5;
t3: the method for cloud intelligent management of water, fertilizer and soil properties of crop roots based on the invention carries out fertilization treatment: the specific fertilizing amount and the nutrient content are shown in table 6.
TABLE 4
TABLE 5
Strip 6
Wherein, the fertilizer can be uniformly scattered on the soil surface and then turned by a rotary cultivator during the conventional fertilization; when the water and fertilizer integrated conventional fertilization is carried out, the fertilizer is dissolved and uniformly mixed, and then the fertilizer and irrigation water are applied together by drip irrigation; the fertilizing treatment based on the method for cloud intelligent management of the crop root water and fertilizer and the soil properties determines a control instruction, namely whether to fertilize and the fertilizing amount, through the growth environment information acquired in real time, for example, when the fertilizing is determined to be needed, a fertilizer applicator can be started to add corresponding nutrients as required, when the irrigation is determined to be needed, an infiltration irrigation system can be started to start infiltration irrigation, and when the oxygenation is determined to be needed, a soil aerator can be started to start oxygenation.
The apple orchard test is carried out based on the standards of tables 4-6, and other health management measures are guaranteed to be consistent, so that the acre yield, the single fruit weight, the hardness, the soluble solid content, the titratable acid content and the soluble sugar content of the apples can be measured in the fruit ripening period of the apple orchard, and the test results are shown in table 7.
TABLE 7
Referring to table 7, the per mu yield of the apple orchard treated by the method for cloud intelligent management of water, fertilizer and soil properties of crop roots is obviously higher than that of the apple orchard treated by T2 and T1. Compared with the apple orchard treated by T2 and T1, the apple orchard under the method for cloud intelligent management of water, fertilizer and soil properties of crop roots has the advantages that the single fruit weight, hardness, soluble solid content and soluble total sugar content of the apples are all improved, and the titratable acid content is obviously reduced. Therefore, the method for cloud intelligent management of the water, the fertilizer and the soil properties of the roots of the crops can realize healthy management of the rhizosphere of the apples and can achieve the aim of healthy whole apple plants.
Corresponding to the method for cloud intelligent management of the water and fertilizer of the crop roots and the soil characters in the embodiment, the invention also provides a system for cloud intelligent management of the water and fertilizer of the crop roots and the soil characters.
As shown in fig. 2, the system for cloud intelligent management of water, fertilizer and soil properties of crop roots according to the embodiment of the present invention includes an obtaining module 10, an input module 20, a processing module 30 and a regulating module 40. The obtaining module 10 is configured to obtain growth environment information of crop roots in the health management area; the input module 20 is used for inputting growth environment interference items for determining the roots of crops in the health management area; the processing module 30 is configured to determine the priority and the interference degree of the growth environment interference item according to the growth environment information by using an interference item interference degree algorithm; the adjusting module 40 is used for adjusting and managing the growing environment of the crop roots according to the priority and the interference degree of the growing environment interference items.
In one embodiment of the present invention, the obtaining module 10 may obtain the growth environment information of the roots of the crops in the health management area through a data sensing device. The growth environment information can comprise soil temperature, soil humidity, soil oxygen concentration, soil pH value, soil EC value and soil respiration rate, the data sensing equipment can comprise a soil temperature sensor, a soil humidity sensor and a soil water dissolved oxygen sensor, a soil pH value sensor, a soil EC value sensor and a soil respiration rate sensor, and the data sensing equipment can be used for correspondingly acquiring the soil temperature, the soil humidity, the soil oxygen concentration, the soil pH value, the soil EC value and the soil respiration rate of the crop roots in the health management area.
In one embodiment of the present invention, the input module 20 may determine the growth environment disturbance terms for the roots of crops in the health management area based on a priori knowledge of the health management of the roots of crops, for example, the growth environment disturbance terms may include irrigation water, fertilizer, oxygen, and microbial additions.
In one embodiment of the present invention, the processing module 30 may be provided with an interference term perturbation degree algorithm.
Specifically, the disturbance degree algorithm of the interference term may be:
wherein x is i Representing the degree of interference of the i-th growth environment interference term, f i,j () Representing a functional relationship, y ', between each growth environment interference term and the growth environment information' j Initial value, y ″, representing jth growth environment information " j Target value representing jth growth environment information, a j Represents the weight of the j-th growth environment information difference value, and δ represents the weighted difference value of the overall growth environment information.
More specifically, the process of establishing the interference term disturbance degree algorithm according to the embodiment of the present invention is as follows:
first, the initial values of the growth environment information acquired by the data sensing device, i.e., the respective sensors, may be set to:
y′ 1 ，y’ 2 ，y′ 3 ，y’ 4 ...y’ m (m∈N)
where m represents the number of sensors and N represents an integer greater than or equal to zero.
Furthermore, the interference modes of the growth environment interference items, such as watering, fertilizing, oxygenating, medication and the like, can be set as follows:
x 1 ，x 2 ，x 3 ，x 4 ...x n (n∈N)
where n represents the type of interference pattern.
Further, the functional relationship between each interference mode and the growth environment information can be set as follows:
Δ(y 1 ，y 2 ...y j )＝f i，j (x 1 ，x 2 ，...，x i )(i，j∈N，0＜i≤n，0＜j≤m)
there is more than one disturbance item for each disturbance mode, for example, there are two disturbance items of irrigation water quantity and oxygen adding quantity for watering irrigation.
Further, the growth environment information obtained after each operation of the disturbance may be set as:
further, the target value of the growth environment information after each interference operation may be set as:
y” 1 ，y” 2 ，y” 3 ，y” 4 ....y” j (j∈N)；
thus, the difference between the initial value and the target value of each growth environment information can be obtained as:
δ i ＝|y” j -y j |。
further, the importance degree of different growth environment information can be judged according to the priori knowledge, and corresponding weight can be set for each growth environment information according to the importance degree so as to obtain the overall weighted difference:
further, can be
The disturbance degree algorithm of the interference term of the embodiment of the invention can be obtained by substituting the formula:
furthermore, the priority of the growth environment interference item can be determined through the weight of the growth environment information difference value, and the interference degree, namely the interference mode, of the growth environment interference item can be determined through calculating the minimum value of the overall weighted difference value.
In addition, it should be noted that there is a correlation between the soil respiration rate and the soil microbial biomass, activity and microbial community before the soil types are different, and therefore, the soil respiration rate can be used as a representative value of the soil microbial biomass in the present invention.
Specifically, the model for characterizing soil microbial load by soil respiration rate may be:
wherein W represents the amount of soil microorganisms, h represents the duration of monitoring, and W h0 The method is characterized by comprising the following steps of representing the initial soil microbial biomass (directly measuring through soil collection), R representing the intrinsic growth rate (measuring through rhizosphere soil microbial experiments), SRV representing the total soil respiration rate (detecting through a soil respiration rate sensor), and SRVR representing the soil root respiration rate (recording the difference of the soil respiration rates inside and outside a region through a soil respiration rate sensor by setting an ungrooved region).
More specifically, x n Can be obtained by the following formula:
x n ＝εQ i ÷(εQ i ÷y i )
wherein Q i Weight, y, representing the ith growth environment information i An available value representing the ith growth environment information.
Further, y i Can be obtained by the following formula:
y i ＝WPF i ÷WPF s
wherein, WPF i Current value, WPF, representing the ith growth circumstance information s An optimum value indicating the i-th growth environment information;
Q i can be obtained by the following formula:
wherein, Y i 0.5 Represents a value at which the actual growth rate of soil microorganisms is half the maximum growth rate. Drawing a curve chart by taking the available value of the growth environment information as the abscissa and the growth rate of the soil microorganisms as the ordinateObtaining the weight value Q by the program group i The solution of (2) is approximated by multiple surfaces.
In addition, it should be noted that the plants cannot directly absorb the organic matters through the root system, and the consumption ways of the soil organic matters mainly include surface runoff, leaching loss and soil respiration, so that the accuracy of detecting the consumption of the soil organic matters on the rhizosphere soil of the water-saving irrigation agricultural farmland through the soil respiration rate is very high, correlation functions can be determined through test monitoring means for different soil types, and the change of the content of the soil organic matters can be calculated in real time.
Specifically, the simulation process of the functional relationship between the soil respiration rate and the soil organic matter may be: and (3) measuring the rhizosphere soil respiration value and the soil organic matter content of the area to be measured, wherein the sample size is not less than 100, and performing correlation analysis and regression analysis by adopting SPSS software and mapping. Thus, it is possible to obtain:
linear model:
SRV-SRVR＝a+b×C÷f
power function model:
SRV-SRVR＝a×(C÷f) b
an index model:
SRV-SRVR＝a×e b×C÷f
wherein, a and b are condition coefficients, C is soil carbon content, and f is an organic matter conversion coefficient, which can be 1.724, and can be obtained by correlation analysis and regression analysis. The organic matter content can be obtained by solving an equation.
In an embodiment of the present invention, the adjusting module 40 may perform adjustment management on the growing environment of the crop roots according to the priority and the interference degree of the growing environment interference item through the smart cloud platform, for example, a corresponding health management control instruction may be generated through the smart cloud platform according to the priority and the interference degree of the growing environment interference item, so that the water, the fertilizer, and the air are used to regulate and control the nutrient and water supply, the oxygen content of the soil, and the amount of soil microorganisms of the crop roots through the water and fertilizer integrated management system.
In addition, the system for cloud intelligent management of the water, the fertilizer and the soil properties of the crop roots can determine the priority and the interference degree of the growth environment interference items according to the plant species and the plant growth period, so that the healthy management of the crop roots is realized.
The invention has the following beneficial effects:
the invention manages the rhizosphere part which is the most important for plant nutrition and substance exchange in four aspects of water consumption, fertilizer consumption, gas consumption and medicine consumption of the plant, so as to achieve the effects of 1 percent of rhizosphere management and more than 100 percent of field management.
The practical application effect of the system for cloud intelligent management of water, fertilizer and soil properties of crop roots is further described below by taking the apple rhizosphere as an example.
In an embodiment of the present invention, taking irrigation of an apple orchard (only adding water) as an example, in the period of treetop, the target value of the growth environment information of the apple orchard and the weight value of each growth environment information are shown in table 1:
TABLE 1
Thus, the functional relationship between each interference mode and the growth environment information can be determined as follows:
wherein x is 1 Denotes the amount of irrigation water, x 2 Indicating the oxygen content, y, of the irrigation water 1 Denotes soil moisture, y 2 Indicates the nitrogen content of the soil, y 3 Indicates the phosphorus content of the soil, y 4 Indicating potassium content in the soil, y 5 Indicating that the soil contains oxygen ppm, y 6 Representing the rate of decrease of the soil respiration rate, and a represents a 6 x 2 matrix.
Further, matrix a may be set as:
wherein, y' 5 The initial value of the sensor is the oxygen ppm of the soil.
The following two sets of measured values were obtained by experiment, wherein the first set of measured values is shown in table 2:
TABLE 2
Referring to table 1, it can be seen that the target value of the apple orchard growth environment information should be greater than 10 in soil temperature, and thus even if the soil moisture deviates from the target value, no disturbing operation is performed here.
The second set of measured values is shown in table 3:
TABLE 3
Referring to table 1, it can be seen that the target value of the apple orchard growth environment information is that the soil temperature should be greater than 10, and thus when the soil temperature is greater than 10, the interference operation, i.e., the irrigation operation, may be performed.
Specifically, the measured values in table 3 can be substituted into the above formula to obtain:
Δ(y 1 ，y 2 ，y 3 ，y 4 ，y 5 ，y 6 )
＝(0.4x 1 ，-0.05x 1 ，-0.05x 1 ，-0.05x 1 ，0.08(x 2 -12)x 1 ，0.08(x 2 -12)x 1 )
further, the disturbance degree algorithm of the interference term in combination with the present invention can obtain:
further, carry in Δ (y) 1 ，y 2 ，y 3 ，y 4 ，y 5 ，y 6 ) The following can be obtained:
δ＝1×|7-0.4x 1 |+1.5×|0.1+0.05x 1 |+1.3×|0.05x 1 |+1.2×|0.05x 1 |+0.7×|0.08(12-x 2 )x 1 |+1.1×|0.06(12-x 2 )x 1 |
furthermore, since the operation is only irrigated without adding oxygen, x can be obtained 2 =12, substituting the above formula yields:
δ＝1×|7-0.4x 1 |+1.5×|0.1+0.05x 1 |+1.3×|0.05x 1 |+1.2×|0.05x 1 |
further, x is determined by calculating the overall weighted difference δ minimum 1 The value:
x 1 ＝17.5
namely, the interference operation can obtain the minimum delta value after 17.5 cubic meters of water is irrigated to the apple orchard.
Test examples
In another embodiment of the invention, taking the fertilization of an apple orchard as an example, the specific fertilization types and proportions are shown in tables 4-6, the test site can be a orchard area, the test time is 3 months-12 months, the variety of the tested apple is Fuji, the row spacing of the planted plants is 2m multiplied by 4m, the planting area is 30 mu in total, and each treated area is about 10 mu/plot.
Specifically, 3 fertilization operations T1, T2, T3 can be designed, each fertilization operation being repeated in a random arrangement, each experimental treatment being as follows:
t1: and (3) conventional fertilization treatment: the specific fertilizing amount and the nutrient content are shown in a table 4;
t2: and (3) water and fertilizer integrated conventional fertilization treatment: the specific fertilizing amount and the nutrient content are shown in a table 5;
t3: the system for cloud intelligent management of water, fertilizer and soil properties of crop roots performs fertilization treatment based on the method provided by the invention: the specific fertilizing amount and the nutrient content are shown in a table 6.
TABLE 4
TABLE 5
Strip 6
Wherein, the fertilizer can be uniformly scattered on the soil surface and then turned by a rotary cultivator during the conventional fertilization; when the water and fertilizer integrated conventional fertilization is carried out, the fertilizer is dissolved and uniformly mixed, and then the fertilizer and irrigation water are applied together by drip irrigation; the fertilization processing of the system for cloud intelligent management of crop root water and fertilizer and soil properties based on the invention is to determine a control instruction, namely whether fertilization and fertilization amount are carried out or not, through the growth environment information acquired in real time.
The apple orchard test is carried out based on the standards of tables 4-6, and other health management measures are guaranteed to be consistent, so that the acre yield, the single fruit weight, the hardness, the soluble solid content, the titratable acid content and the soluble sugar content of the apples can be measured in the fruit ripening period of the apple orchard, and the test results are shown in table 7.
TABLE 7
Referring to table 7, the per mu yield of the apple orchard under the system for cloud intelligent management of water, fertilizer and soil properties of crop roots based on the method is obviously higher than that of the apple orchard treated by T2 and T1. Compared with the apple orchard treated by T2 and T1, the apple orchard under the system for cloud intelligent management of water, fertilizer and soil properties of crop roots has the advantages that the single fruit weight, hardness, soluble solid content and soluble total sugar content of apples are improved, and the titratable acid content is obviously reduced. Therefore, the system for cloud intelligent management of water, fertilizer and soil properties of crop roots can realize healthy management of apple rhizosphere and can achieve the purpose of whole apple plant health.
In the description of the present invention, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or to imply that the number of technical features indicated is significant. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. The meaning of "plurality" is two or more unless specifically limited otherwise.
In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the present invention, unless otherwise expressly stated or limited, the first feature "on" or "under" the second feature may be directly contacting the first and second features or indirectly contacting the first and second features through an intermediate. Also, a first feature "on," "above," and "over" a second feature may be directly on or obliquely above the second feature, or simply mean that the first feature is at a higher level than the second feature. A first feature being "under," "below," and "beneath" a second feature may be directly under or obliquely under the first feature, or may simply mean that the first feature is at a lesser elevation than the second feature.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Claims (10)
1. A method for carrying out cloud intelligent management on crop root water, fertilizer and soil properties is characterized by comprising the following steps:
acquiring growth environment information of crop roots in a health management area;
determining a growth environment interference item of the root of the crop in the health management area;
determining the priority and the interference degree of the interference item of the growth environment according to the information of the growth environment by adopting an interference item interference degree algorithm;
and regulating and managing the growth environment of the crop roots according to the priority and the interference degree of the growth environment interference item.
2. The method for cloud intelligent management of crop root water, fertilizer and soil characteristics as claimed in claim 1, wherein the growth environment information comprises soil temperature, soil humidity, soil oxygen concentration, soil PH value, soil EC value and soil respiration rate.
3. The method for cloud intelligent management of crop root water, fertilizer and soil traits as claimed in claim 2, characterized in that, the growth environment disturbance items comprise irrigation water amount, fertilization amount, oxygen addition amount and microorganism addition amount.
4. The method for cloud intelligent management of crop root water, fertilizer and soil traits as claimed in claim 2, characterized in that the disturbance degree algorithm of the interference term is:
wherein x is i Representing the degree of interference of the i-th growth environment interference term, f i,j () Representing a functional relationship, y ', between each of the growth environment disturbance terms and the growth environment information' j An initial value, y ″, representing the jth piece of the growth environment information j A target value representing jth of said growth environment information, a j And d represents the weight of the growth environment information difference value j, and delta represents the weighted difference value of the overall growth environment information.
5. The method for cloud intelligent management of crop root water, fertilizer and soil traits as claimed in claim 4, characterized in that the priority of the growth environment interference item is determined by the weight.
6. The method for cloud intelligent management of crop root water, fertilizer and soil characteristics according to claim 4, wherein the interference degree of the growth environment interference term is determined by calculating the overall weighted difference minimum value.
7. The method for cloud intelligent management of crop root water, fertilizer and soil traits as claimed in claim 3, characterized in that, the soil respiration rate is used for characterizing the soil microorganism amount, specifically, the soil respiration rate is used for characterizing the soil microorganism amount in a model of:
wherein W represents the amount of soil microorganisms, h represents the duration of monitoring, and W h0 Representing the initial soil microbial biomass, R representing the intrinsic growth rate, SRV representing the total respiration rate of the soil, and SRVR representing the respiration rate of the soil roots.
8. The method for cloud intelligent management of crop root water, fertilizer and soil characteristics according to claim 7, wherein x is n The following formula is used to obtain:
x n ＝εQ i ÷(εQ i ÷y i )
wherein Q is i Weight, y, representing the ith said growth environment information i An availability value representing an ith one of the growth environment information.
9. The method for cloud intelligent management of crop root water, fertilizer and soil characteristics according to claim 8, wherein,
y i the following formula is used to obtain:
y i ＝WPF i ÷WPF s
wherein, WPF i Current value, WPF, representing the ith said growth circumstance information s An optimum value indicating the ith growth environment information;
Q i the following formula is used to obtain:
wherein, Y i 0.5 Represents a value at which the actual growth rate of soil microorganisms is half the maximum growth rate.
10. The utility model provides a system for carry out cloud intelligent management to crop root liquid manure and soil property which characterized in that includes:
the system comprises an acquisition module, a management module and a management module, wherein the acquisition module is used for acquiring growth environment information of crop roots in a health management area;
the input module is used for inputting and determining a growth environment interference item of the crop roots in the health management area;
the processing module is used for determining the priority and the interference degree of the growth environment interference item according to the growth environment information by adopting an interference item disturbance degree algorithm;
and the adjusting module is used for adjusting and managing the growth environment of the crop roots according to the priority and the interference degree of the growth environment interference item.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111337587A (en) * | 2020-02-10 | 2020-06-26 | 广西大学 | Method for high-flux determination of soil microbial biomass |
| CN113229123A (en) * | 2021-06-02 | 2021-08-10 | 湖北工程学院 | Intelligent irrigation method, device and equipment for crops and storage medium |
| CN113466143A (en) * | 2021-07-01 | 2021-10-01 | 中煤航测遥感集团有限公司 | Soil nutrient inversion method, device, equipment and medium |
| US20220183243A1 (en) * | 2020-12-10 | 2022-06-16 | Semiosbio Technologies Inc. | Method for managing crop irrigation, and system using same |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111337587A (en) * | 2020-02-10 | 2020-06-26 | 广西大学 | Method for high-flux determination of soil microbial biomass |
| US20220183243A1 (en) * | 2020-12-10 | 2022-06-16 | Semiosbio Technologies Inc. | Method for managing crop irrigation, and system using same |
| CN113229123A (en) * | 2021-06-02 | 2021-08-10 | 湖北工程学院 | Intelligent irrigation method, device and equipment for crops and storage medium |
| CN113466143A (en) * | 2021-07-01 | 2021-10-01 | 中煤航测遥感集团有限公司 | Soil nutrient inversion method, device, equipment and medium |
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