CN109934464A - A kind of water-fertilizer-pesticide decision system and method based on plant life sign - Google Patents
A kind of water-fertilizer-pesticide decision system and method based on plant life sign Download PDFInfo
- Publication number
- CN109934464A CN109934464A CN201910126913.0A CN201910126913A CN109934464A CN 109934464 A CN109934464 A CN 109934464A CN 201910126913 A CN201910126913 A CN 201910126913A CN 109934464 A CN109934464 A CN 109934464A
- Authority
- CN
- China
- Prior art keywords
- decision
- plant
- fertilizer
- water
- pesticide
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Landscapes
- Hydroponics (AREA)
Abstract
The present disclosure proposes a kind of water-fertilizer-pesticide decision systems and method based on plant life sign, it include: plant life sign information acquisition unit, above- mentioned information are simultaneously transmitted to information collection and intelligent decision integrated control cabinet by the moisture of herborization blade, the nutrient of young sprout, leaf nutrient, trunk nutrient and root nutrient；High-definition camera, pictorial information in herborization growth course are simultaneously transmitted to intelligent decision integrated control cabinet；The intelligent decision integrated control cabinet includes controller, and the controller judges the health status of plant according to information collected and realizes the application to water-fertilizer-pesticide based on the health status.
Description
Technical field
This disclosure relates to farmland management technical field, more particularly to a kind of water-fertilizer-pesticide decision based on plant life sign
System and method.
Background technique
It exists in the prior art and plant physiology information is monitored by image and to the parameter of plant (including plant
Moisture, temperature of leaf of stem etc.) be monitored, in order to the growth characteristics for solving plant, to physiological feature into
Row analysis, obtains the health status (including growth information and disease and insect information) of plant, and make corresponding evaluation.
The prior art is there is also the monitoring to plant growth environment, such as weather information, soil information (including moisture, nutrient
Deng), it is therefore an objective to carry out environmental Kuznets Curves, the control including water-fertilizer-pesticide provides a suitable growing environment for plant, as temperature,
Illumination, moisture, fertility etc., to reach the high-yield high-quality of plant.
As it can be seen that carrying out plant health evaluation only by monitoring physiological property in the prior art or being joined by monitoring environment
Number carries out environmental Kuznets Curves, and there is no the health with plant for target, growing environment management and decision based on plant life sign
System and method, especially to the decision system and method for water-fertilizer-pesticide needed for plant growth.
Summary of the invention
In order to solve the deficiencies in the prior art, present disclose provides a kind of water-fertilizer-pesticide decision system based on plant life sign
System realizes the control of the application to the water-fertilizer-pesticide of plant.
To achieve the goals above, the disclosure uses following technical scheme:
A kind of water-fertilizer-pesticide decision system based on plant life sign, comprising:
Plant life sign information acquisition unit, the moisture of herborization blade, the nutrient of young sprout, leaf nutrient, trunk
Above- mentioned information are simultaneously transmitted to information collection and intelligent decision integrated control cabinet or cloud service platform by nutrient and root nutrient；
Image acquisition units, pictorial information in herborization growth course and be transmitted to intelligent decision integrated control cabinet or
Cloud service platform；
The intelligent decision integrated control cabinet or cloud service platform judge the healthy shape of plant according to information collected
Condition simultaneously realizes the application to water-fertilizer-pesticide based on the health status.
Further technical solution, the plant life sign information acquisition unit include leaf water sensor, young sprout
Nutrient sensor, leaf nutrient sensor, trunk nutrient sensor and root nutrient sensor, the leaf water sensor,
Young sprout nutrient sensor, leaf nutrient sensor, trunk nutrient sensor and root nutrient sensor are respectively connected to intelligence and determine
Controller in plan integrated control cabinet.
Further technical solution, the intelligent decision integrated control cabinet include processor and display, the controller
It is additionally coupled to control valve, the control valve is separately mounted on high-pressure fog pipeline and water-fertilizer-pesticide pipeline.
Further technical solution judges the strong of plant according to information collected in the intelligent decision integrated control cabinet
Health situation simultaneously realizes the application to water-fertilizer-pesticide based on the health status, wherein medicine application program makes mode are as follows: is directed to image
Acquisition unit acquisition plant image, image is handled and is identified by image processing algorithm, extract plant growing way,
Color, unity and coherence in writing information, realize to growth and development situation, bloom bear fruit, the automation of pest and disease damage situation, arid, frost calamity supervise
Survey, according to monitoring result determine whether medication and medication number.
Further technical solution judges the strong of plant according to information collected in the intelligent decision integrated control cabinet
Health situation simultaneously realizes the application to water-fertilizer-pesticide based on the health status, wherein liquid manure application program makes mode are as follows: monitoring is planted
The vital sign information of object growing environment information and plant ontology obtains corresponding predicted value using Secondary Exponential Smoothing Method, benefit
Overall merit is carried out with analytic hierarchy process (AHP), with reference to the expert's recommendation and user experience value of expert data, show that several are suitable for
Liquid manure application program, and recommend optimal fertigation scheme automatically.
Further technical solution, the control mode of the intelligent decision integrated control cabinet include: timing controlled, quantitative
System and condition control；
Wherein, timing controlled: setting starting and end time, intelligent decision integrated control cabinet according to setting when
Between, automatic start-stop；
Quantitative control: setting duty, fertilizer amount, dose reach after intelligent decision integrated control cabinet controls equipment starting
Corresponding set amount, is automatically stopped；
Condition control: setting irrigation is applied fertilizer, the opening and closing condition of application equipment, intelligent decision integrated control cabinet control
Control equipment automatic running when meeting condition.
Embodiment of the disclosure also discloses a kind of decision-making party of water-fertilizer-pesticide decision system based on plant life sign
Method, comprising the following steps:
For the image information of the plant of acquisition, image is handled and identified by image processing algorithm, extracted and plant
Growing way, color, the unity and coherence in writing information of object, realize to growth and development situation, bloom bear fruit, pest and disease damage situation, arid, frost calamity
Automatic monitoring determines whether the number of medication and medication according to monitoring result；
The vital sign information for monitoring plant growth environment information and plant ontology, obtains phase using Secondary Exponential Smoothing Method
The predicted value answered carries out overall merit using analytic hierarchy process (AHP) and obtains with reference to the expert's recommendation and user experience value of expert data
Several suitable liquid manure application programs out, and recommend optimal fertigation scheme automatically.
Further technical solution obtains corresponding predicted value, prediction steps using Secondary Exponential Smoothing Method are as follows:
Establish liquid manure decision hierarchy Model；
Based on above-mentioned Construction of A Model judgment matrix, when structural matrix in such a way that influence factor factor compares in pairs；
Mode of Level Simple Sequence is carried out for judgment matrix and is confirmed using consistency check；
Total hierarchial sorting is carried out for judgment matrix and is confirmed using consistency check；
Last decision is made according to liquid manure decision hierarchy Model lowest level, that is, decision-making level total hierarchial sorting.
Further technical solution establishes liquid manure decision hierarchy Model: by optimal liquid manure scheme, decision rule and shadow
The factor of sound is divided into top, middle layer and lowermost layer by the correlation between them, draws hierarchical chart, wherein decision
Criterion includes leaf water, leaf nutrient, stalk rugosity and fruit size, and influence factor includes meteorology, soil, expert and use
Family.
Further technical solution, the element corresponding to the feature vector of judgment matrix Maximum characteristic root, after normalizing
It is same level factor for the sequencing weight of upper level factor factor relative importance, it is single that this process is known as level
Sequence；
All factors of a certain level are calculated for the weight of top relative importance, referred to as total hierarchial sorting.
Compared with prior art, the beneficial effect of the disclosure is:
1, for the disclosure in terms of fertigation, the technical solution of the disclosure is the feature by monitoring plant itself, such as water
Point, nutrient, and combine the information of air and soil, expert database and user experience value to determine whether need fertigation and
Fertigation amount, the prior art are mostly whether the feature of monitoring soil needs fertigation come what is judged.
2, for the disclosure in terms of application, embodiment of the disclosure is special by using the early evil of disease of automatic identification plant
Sign, and aggrieved grade is distinguished, it establishes whether to need to be administered and be administered automatically according to expert database and user experience value
Amount.
Detailed description of the invention
The Figure of description for constituting a part of this disclosure is used to provide further understanding of the disclosure, and the disclosure is shown
Meaning property embodiment and its explanation do not constitute the improper restriction to the disclosure for explaining the disclosure.
Fig. 1 is the hardware setting figure of embodiment of the present disclosure；
The irrigation effect schematic diagram of Fig. 2 embodiment of the present disclosure；
Fig. 3 is the fertilization effect schematic diagram of embodiment of the present disclosure；
Fig. 4 is the decision schematic diagram of embodiment of the present disclosure；
Fig. 5 is the hierarchical chart of embodiment of the present disclosure.
Specific embodiment
It is noted that following detailed description is all illustrative, it is intended to provide further instruction to the disclosure.Unless another
It indicates, all technical and scientific terms used herein has usual with disclosure person of an ordinary skill in the technical field
The identical meanings of understanding.
It should be noted that term used herein above is merely to describe specific embodiment, and be not intended to restricted root
According to the illustrative embodiments of the disclosure.As used herein, unless the context clearly indicates otherwise, otherwise singular
Also it is intended to include plural form, additionally, it should be understood that, when in the present specification using term "comprising" and/or " packet
Include " when, indicate existing characteristics, step, operation, device, component and/or their combination.
In a kind of typical embodiment of the disclosure, a kind of water-fertilizer-pesticide decision system based on plant life sign is provided
System, referring to figure 1, by high-definition camera (1), information collection and intelligent decision integrated control cabinet (2), display screen (3), fruit
Real size sensor (4), leaf temperature sensor (5), high-pressure fog pipeline (6), leaf water sensor (7), young sprout nutrient
Sensor (8), leaf nutrient sensor (9), trunk nutrient sensor (10), the composition such as root nutrient sensor (11)；It is described
Water-fertilizer-pesticide intelligent decision system by information collection and intelligent decision integrated control cabinet (2), display screen (3), high-pressure fog pipeline
(6), water-fertilizer-pesticide pipeline (12) etc. forms.
Specifically, randomly selecting a certain number of fruits in practical operation, 1 is such as selected per acre, is monitored, it is right
Each fruit installs fruit size sensor, monitors respectively.Leaf temperature sensor needs to be placed on each blade, is equally
Certain blade is randomly selected to be installed；Nutrient sensor it is clipping, it is easy to installation and removal；Young sprout is with 7 days for one
It in a period, is replaced.High-pressure atomization pipeline can be sprayed, and the liquid of atomization can be the pesticide after irrigation water, dilution, dilution
Liquid Fertilizer (mainly foliar fertilizer) afterwards.
Specifically, the plant image information of camera acquisition, upload to information collection and intelligent decision integrated control cabinet and
Cloud service platform handles image and is identified by image processing algorithm pair, extracts the letter such as growing way, color, unity and coherence in writing
Breath, to growth and development situation, bloom bear fruit, the automatic monitoring of the disasters such as pest and disease damage situation, arid, frost.
In the specific implementation, carrying out image processing algorithm to the plant image information of camera acquisition can be in information collection
Carried out with intelligent decision integrated control cabinet or cloud service platform, when information collection and intelligent decision integrated control cabinet not with
When cloud service platform is communicated, information collection carries out data processing with intelligent decision integrated control cabinet and obtains corresponding data
Processing result, also or, there is no the processing for carrying out image procossing for information collection and intelligent decision integrated control cabinet, only by phase
It closes image information and is uploaded to cloud service platform, corresponding information is transmitted to information after cloud service platform progress data processing
Acquisition and intelligent decision integrated control cabinet are irrigated or are applied fertilizer or is administered by instruction corresponding below the control cabinet.
The control program of information collection and intelligent decision integrated control cabinet can be divided into three kinds: timing controlled quantitatively controls, item
Part control.
Wherein, timing controlled: can design starting and end time (date), equipment can according to the time of setting,
Automatic start-stop.
Quantitative control: setting duty, fertilizer amount, dose reach corresponding set amount, are automatically stopped after equipment starting.
Condition control: the opening and closing condition of the equipment such as setting irrigation, fertilising, application controls equipment automatic running；Such as
Leaf water is irrigated lower than lower limit value, and each duty is set amount；Nutrient applies fertilizer lower than lower limit value, applies every time
Fertilizer amount is set amount；When the harm program of certain pest and disease damage is higher than some value, it is administered.
The irrigation control effect that may be implemented by above-mentioned control system, referring to shown in attached drawing 2, time coordinate axis (13),
Plant moisture reference axis (14), plant physiology need water curve (15), intelligent irrigation curve (16).Final purpose is to realize intelligence
Curve and plant physiology, which can be irrigated, needs water curve to match.
By the Nutrient distribution period control effect for the plant that above-mentioned control system may be implemented, referring to shown in attached drawing 3, when
Between reference axis (17), plant nutrient reference axis (18), young sprout nutrition accumulation (19), trunk nutrition accumulation (20), root
Nutrition accumulation (21), leaf nutrient accumulation (22).Young sprout nutrition accumulation (19), trunk nutrition accumulation (20), root
Nutrition accumulation (21), leaf nutrient accumulation (22)), this kind of parameter can be measured by chemical examination.
The realization plant life sign of embodiment of the disclosure detects and health control, be able to detect plant moisture,
The vital signs such as nutrient, temperature, fruit size, and the health status of detection plant is judged, it is water-fertilizer-pesticide intelligent decision
Foundation is provided.
The water-fertilizer-pesticide intelligent decision system of embodiment of the disclosure can be detected according to plant life sign and be managed with health
Reason system needs water curve (15) to determine intelligence evaluation result, the embodiment of intelligent decision water, fertilizer, medicine in conjunction with plant physiology
Curve (16) can be irrigated, in conjunction with young sprout nutrition accumulation (19), trunk nutrition accumulation (20), root nutrition accumulation (21),
Leaf nutrient accumulation (22), determines dose.
Another embodiment of the present disclosure also discloses a kind of determining for water-fertilizer-pesticide decision system based on plant life sign
Plan method monitors plant growth environment information (air themperature, air humidity, the soil moisture, soil moisture referring to shown in attached drawing 4
Deng) and plant ontology vital sign information (leaf temperature, stalk rugosity, fruit size etc.), using Secondary Exponential Smoothing Method
It obtains corresponding predicted value, carries out overall merit using analytic hierarchy process (AHP), passed through with reference to expert's recommendation of expert data and user
Value is tested, obtains 3 suitable liquid manure application programs, and recommend optimal fertigation scheme automatically.
Specifically, being predicted using Secondary Exponential Smoothing Method each monitor value:
Wherein, St (1)For the single exponential smoothing value of t phase；St (2)For the double smoothing value of t phase；α is smooth normal
Number.
The prediction model of Secondary Exponential Smoothing Method are as follows:
Ft+T=at+btT (3)
Wherein:
Ft+TFor t+T phase predicted value；T is the issue to future anticipation；at、btRespectively model parameter.
Specifically, prediction steps:
Step 1 establishes liquid manure decision hierarchy Model:
By optimal liquid manure scheme, decision rule (leaf water, leaf nutrient, stalk rugosity, fruit size) and influence because
Plain (meteorology, soil, expert, user) is divided into top, middle layer and lowermost layer by the correlation between them, draws level
Structure chart, referring to shown in attached drawing 5.
Step 2, construction judgement (in pairs relatively) matrix: Consistent Matrix method, it may be assumed that all factors are not put together and is compared,
But it is compared to each other two-by-two；It is tired with reduce that the different factors of property are compared to each other as far as possible to using relative scalar at this time
Difficulty, to improve accuracy.If will more each criterion C1,C2,…,CnTo the importance of target O.
Wherein, n is the dimension of judgment matrix and the quantity of rule layer.
The judgment matrix of liquid manure decision system is as follows:
Step 3, Mode of Level Simple Sequence and its consistency check: correspond to judgment matrix Maximum characteristic root λmaxFeature vector,
Normalized and (the sum of each element in vector made to be equal to 1) postscript W.The element of W be same level factor for a upper level because
The sequencing weight of certain plain factor relative importance, this process are known as Mode of Level Simple Sequence.Can confirm Mode of Level Simple Sequence, need into
Row consistency check, so-called consistency check, which refers to, determines inconsistent allowed band to A.
Define coincident indicator:
Wherein, λ is judgment matrix characteristic root, and n is the dimension of judgment matrix.CI is coincident indicator.
CI=0 has complete consistency；
CI has satisfied consistency close to 0；
CI is bigger, inconsistent more serious；
Define consistency ratio:
Wherein, CR is consistency ratio, and RI is Aver-age Random Consistency Index RI standard value.
Generally, as consistency ratio CR < 0.1, it is believed that the inconsistent degree of A has satisfied one within permissible range
Cause property, passes through consistency check.Its normalization characteristic vector can be used as weight vector, otherwise to reconfigure in pairs relatively matrix
A, to aijIt is adjusted.
In the application example, Maximum characteristic root λ=5.073 of the judgment matrix of liquid manure decision system.
Weight vector (feature vector) w=(0.263,0.475,0.055,0.090,0.110)T。
Coincident indicator
Random index RI=1.12 (tables look-up).
Consistency ratio CR=0.018/1.12=0.016 < 0.1.
Pass through consistency check.
Step 4, total hierarchial sorting and its consistency check.
All factors of a certain level are calculated for the weight of top (general objective) relative importance, referred to as level is always arranged
Sequence.
This process is successively carried out from highest level to lowest level.
Wherein, parameter a is constant, and m is the number of coincident indicator.
As CR < 1, it is believed that total hierarchial sorting passes through consistency check.Total hierarchial sorting has satisfied consistency, otherwise
Need to readjust the element value of the high judgment matrix of those consistency ratios.
This is arrived, last decision is made according to the total hierarchial sorting of lowest level (decision-making level).
The foregoing is merely preferred embodiment of the present disclosure, are not limited to the disclosure, for the skill of this field
For art personnel, the disclosure can have various modifications and variations.It is all within the spirit and principle of the disclosure, it is made any to repair
Change, equivalent replacement, improvement etc., should be included within the protection scope of the disclosure.
Claims (10)
1. a kind of water-fertilizer-pesticide decision system based on plant life sign, characterized in that include:
Plant life sign information acquisition unit, the moisture of herborization blade, the nutrient of young sprout, leaf nutrient, trunk nutrient
And root nutrient and above- mentioned information are transmitted to information collection and intelligent decision integrated control cabinet or cloud service platform；
Image acquisition units, pictorial information in herborization growth course are simultaneously transmitted to intelligent decision integrated control cabinet or cloud
Service platform；
The intelligent decision integrated control cabinet or cloud service platform judge the health status of plant simultaneously according to information collected
The application to water-fertilizer-pesticide is realized based on the health status.
2. a kind of water-fertilizer-pesticide decision system based on plant life sign as described in claim 1, characterized in that the plant
Vital sign information acquisition unit includes leaf water sensor, young sprout nutrient sensor, leaf nutrient sensor, trunk nutrient
Sensor and root nutrient sensor, the leaf water sensor, young sprout nutrient sensor, leaf nutrient sensor, trunk
Nutrient sensor and root nutrient sensor are respectively connected to the controller in intelligent decision integrated control cabinet.
3. a kind of water-fertilizer-pesticide decision system based on plant life sign as described in claim 1, characterized in that the intelligence
Decision integrated control cabinet includes processor and display, and the controller is additionally coupled to control valve, the control valve difference
It is mounted on high-pressure fog pipeline and water-fertilizer-pesticide pipeline.
4. a kind of water-fertilizer-pesticide decision system based on plant life sign as described in claim 1, characterized in that the intelligence
The health status of plant is judged according to information collected in decision integrated control cabinet and is realized based on the health status to liquid manure
The application of medicine, wherein medicine application program makes mode are as follows: for the image of the plant of image acquisition units acquisition, pass through figure
As Processing Algorithm is handled and identified to image, the growing way, color, unity and coherence in writing information of plant are extracted, is realized to growth and development feelings
Condition, bloom bear fruit, the automatic monitoring of pest and disease damage situation, arid, frost calamity, medication and use are determined whether according to monitoring result
The number of medicine.
5. a kind of water-fertilizer-pesticide decision system based on plant life sign as described in claim 1, characterized in that the intelligence
The health status of plant is judged according to information collected in decision integrated control cabinet and is realized based on the health status to liquid manure
The application of medicine, wherein liquid manure application program makes mode are as follows: the life entity of monitoring plant growth environment information and plant ontology
Reference breath, obtains corresponding predicted value using Secondary Exponential Smoothing Method, overall merit is carried out using analytic hierarchy process (AHP), with reference to expert
The expert's recommendation and user experience value of data obtain several suitable liquid manure application programs, and recommend optimal irrigation automatically
Fertilizer applications.
6. a kind of water-fertilizer-pesticide decision system based on plant life sign as described in claim 1, characterized in that the intelligence
The control mode of decision integrated control cabinet includes: timing controlled, quantitative control and condition control；
Wherein, timing controlled: setting starting and end time, intelligent decision integrated control cabinet according to time of setting, from
Dynamic start and stop；
Quantitative control: setting duty, fertilizer amount, dose reach corresponding after intelligent decision integrated control cabinet controls equipment starting
Set amount, be automatically stopped；
Condition control: setting irrigation is applied fertilizer, the opening and closing condition of application equipment, and the control of intelligent decision integrated control cabinet is set
The standby automatic running when meeting condition.
7. a kind of decision-making technique of the water-fertilizer-pesticide decision system based on plant life sign, characterized in that the following steps are included:
For the image information of the plant of acquisition, image is handled and identified by image processing algorithm, extracts plant
Growing way, color, unity and coherence in writing information, realize to growth and development situation, bloom bear fruit, pest and disease damage situation, arid, frost calamity it is automatic
Change monitoring, according to monitoring result determine whether medication and medication number；
The vital sign information for monitoring plant growth environment information and plant ontology, is obtained accordingly using Secondary Exponential Smoothing Method
Predicted value carries out overall merit using analytic hierarchy process (AHP), with reference to the expert's recommendation and user experience value of expert data, if obtaining
Dry suitable liquid manure application program, and recommend optimal fertigation scheme automatically.
8. a kind of decision-making technique of the water-fertilizer-pesticide decision system based on plant life sign as claimed in claim 7, feature
It is that corresponding predicted value, prediction steps are obtained using Secondary Exponential Smoothing Method are as follows:
Establish liquid manure decision hierarchy Model；
Based on above-mentioned Construction of A Model judgment matrix, when structural matrix in such a way that influence factor factor compares in pairs；
Mode of Level Simple Sequence is carried out for judgment matrix and is confirmed using consistency check；
Total hierarchial sorting is carried out for judgment matrix and is confirmed using consistency check；
Last decision is made according to liquid manure decision hierarchy Model lowest level, that is, decision-making level total hierarchial sorting.
9. a kind of decision-making technique of the water-fertilizer-pesticide decision system based on plant life sign as claimed in claim 8, feature
It is to establish liquid manure decision hierarchy Model: by optimal liquid manure scheme, decision rule and influence factor by mutual between them
Relationship is divided into top, middle layer and lowermost layer, draws hierarchical chart, wherein decision rule include leaf water, blade support
Divide, stalk rugosity and fruit size, influence factor include meteorology, soil, expert and user.
10. a kind of decision-making technique of the water-fertilizer-pesticide decision system based on plant life sign as claimed in claim 8, feature
It is that, corresponding to the feature vector of judgment matrix Maximum characteristic root, the element after normalizing is same level factor for upper one
The sequencing weight of level factor factor relative importance, this process are known as Mode of Level Simple Sequence；
All factors of a certain level are calculated for the weight of top relative importance, referred to as total hierarchial sorting.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910126913.0A CN109934464A (en) | 2019-02-20 | 2019-02-20 | A kind of water-fertilizer-pesticide decision system and method based on plant life sign |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910126913.0A CN109934464A (en) | 2019-02-20 | 2019-02-20 | A kind of water-fertilizer-pesticide decision system and method based on plant life sign |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109934464A true CN109934464A (en) | 2019-06-25 |
Family
ID=66985656
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910126913.0A Pending CN109934464A (en) | 2019-02-20 | 2019-02-20 | A kind of water-fertilizer-pesticide decision system and method based on plant life sign |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109934464A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110719336A (en) * | 2019-10-21 | 2020-01-21 | 江苏省农业科学院 | Irrigation water analysis monitoring system based on Internet of things |
| CN111638306A (en) * | 2020-06-11 | 2020-09-08 | 中国农业科学院农业信息研究所 | Crop dynamic monitoring method, device, equipment and system |
| CN112765327A (en) * | 2021-01-27 | 2021-05-07 | 维沃移动通信有限公司 | Natural language information output method and device and electronic equipment |
| CN113406075A (en) * | 2021-06-08 | 2021-09-17 | 内蒙古工业大学 | Setting method of plant growth environment and plant growth monitoring device |
| CN113396753A (en) * | 2020-03-16 | 2021-09-17 | 上海原初农业发展有限公司 | Big data analysis-based intelligent agricultural planting management and control system |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2001031532A2 (en) * | 1999-10-28 | 2001-05-03 | Ecolab Inc. | Data processing system for managing chemical product usage |
| CN1559175A (en) * | 2004-02-24 | 2005-01-05 | 深圳市宝安区农业科学技术推广中心 | Remote radio information feedback and controlable environment intelligent system for agricultural crops |
| CN103699668A (en) * | 2013-12-30 | 2014-04-02 | 贵州电力试验研究院 | Power distribution network electric equipment combination state evaluation method based on data section consistency |
| CN106718363A (en) * | 2017-01-06 | 2017-05-31 | 安徽农业大学 | A kind of irrigation tests method and its test platform towards precision agriculture |
| CN106912237A (en) * | 2017-03-20 | 2017-07-04 | 浙江省农业科学院 | Water-fertilizer integral four controls fertigation method |
| CN107203947A (en) * | 2017-05-22 | 2017-09-26 | 武汉大学 | A kind of digital substation relay protection evaluation mode of system condition method |
| CN108288170A (en) * | 2017-12-07 | 2018-07-17 | 上海电力学院 | A kind of evaluation method of the Demand Side Response project based on analytic hierarchy process (AHP) |
| CN109348819A (en) * | 2018-11-14 | 2019-02-19 | 山东省农业机械科学研究院 | A kind of intelligent and high-efficiency water-fertilizer-pesticide integral system |
-
2019
- 2019-02-20 CN CN201910126913.0A patent/CN109934464A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2001031532A2 (en) * | 1999-10-28 | 2001-05-03 | Ecolab Inc. | Data processing system for managing chemical product usage |
| CN1559175A (en) * | 2004-02-24 | 2005-01-05 | 深圳市宝安区农业科学技术推广中心 | Remote radio information feedback and controlable environment intelligent system for agricultural crops |
| CN103699668A (en) * | 2013-12-30 | 2014-04-02 | 贵州电力试验研究院 | Power distribution network electric equipment combination state evaluation method based on data section consistency |
| CN106718363A (en) * | 2017-01-06 | 2017-05-31 | 安徽农业大学 | A kind of irrigation tests method and its test platform towards precision agriculture |
| CN106912237A (en) * | 2017-03-20 | 2017-07-04 | 浙江省农业科学院 | Water-fertilizer integral four controls fertigation method |
| CN107203947A (en) * | 2017-05-22 | 2017-09-26 | 武汉大学 | A kind of digital substation relay protection evaluation mode of system condition method |
| CN108288170A (en) * | 2017-12-07 | 2018-07-17 | 上海电力学院 | A kind of evaluation method of the Demand Side Response project based on analytic hierarchy process (AHP) |
| CN109348819A (en) * | 2018-11-14 | 2019-02-19 | 山东省农业机械科学研究院 | A kind of intelligent and high-efficiency water-fertilizer-pesticide integral system |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110719336A (en) * | 2019-10-21 | 2020-01-21 | 江苏省农业科学院 | Irrigation water analysis monitoring system based on Internet of things |
| CN110719336B (en) * | 2019-10-21 | 2020-06-16 | 江苏省农业科学院 | Irrigation water analysis monitoring system based on Internet of things |
| CN113396753A (en) * | 2020-03-16 | 2021-09-17 | 上海原初农业发展有限公司 | Big data analysis-based intelligent agricultural planting management and control system |
| CN111638306A (en) * | 2020-06-11 | 2020-09-08 | 中国农业科学院农业信息研究所 | Crop dynamic monitoring method, device, equipment and system |
| CN111638306B (en) * | 2020-06-11 | 2022-05-17 | 中国农业科学院农业信息研究所 | Crop dynamic monitoring method, device, equipment and system |
| CN112765327A (en) * | 2021-01-27 | 2021-05-07 | 维沃移动通信有限公司 | Natural language information output method and device and electronic equipment |
| CN113406075A (en) * | 2021-06-08 | 2021-09-17 | 内蒙古工业大学 | Setting method of plant growth environment and plant growth monitoring device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109934464A (en) | A kind of water-fertilizer-pesticide decision system and method based on plant life sign | |
| Lu et al. | Combining plant height, canopy coverage and vegetation index from UAV-based RGB images to estimate leaf nitrogen concentration of summer maize | |
| EP3707990B1 (en) | Information processing device, information processing method, and vegetation management system | |
| Chen et al. | A neural network integrated approach for rice crop monitoring | |
| Kumar et al. | Application of indicators for identifying climate change vulnerable areas in semi-arid regions of India | |
| CN106354184B (en) | Agricultural production Efficient intelligent managing and control system | |
| AU2020102100A4 (en) | Disease detection using iot and machine learning in rice crops | |
| CN116738766B (en) | Intelligent agriculture online industrialization service system based on digital twinning | |
| Dobermann et al. | The evolution of site-specific nutrient management in irrigated rice systems of Asia | |
| Barbottin et al. | Using the French LPIS database to highlight farm area dynamics: The case study of the Niort Plain | |
| Zhang et al. | Quantifying the relationships of soil properties and crop growth with yield in a NPK fertilizer application maize field | |
| Ricard et al. | Comparison of adaptative strategies to climate variability in rural areas of Argentine Chaco and US Southern Plains during the last century | |
| Innes | Theoretical and practical criteria for the selection of ecosystem monitoring plots in Swiss forests | |
| Davis et al. | Reducing yield variation in peach orchards by geographic scattering | |
| da Silva Junior et al. | Comparison of mapping soybean areas in Brazil through perceptron neural networks and vegetation indices | |
| Singh | Crop growth simulation models | |
| Mir et al. | Improving the food and agriculture sector tehran stock exchange by using artificial intelligence | |
| Mallarino et al. | Role of precision agriculture in phosphorus management practices | |
| Velandia et al. | Factors influencing the adoption of automatic section control technologies and GPS auto-guidance systems in cotton production | |
| Bakema et al. | Using a simulation model to evaluate weather effects | |
| Palomo et al. | Land usage classification: a hierarchical neural network approach | |
| Uma Maheswari et al. | IoT-Based Automated Drip Irrigation and Plant Health Management System | |
| Michelini et al. | KULTIVAS: Feasability study of a variety-location model for apple cultivation | |
| Gikunda et al. | Effect of certifiation on adoption and sustainability of organic agricultural practices | |
| Devi et al. | Statistical evaluation of regional level agricultural and socio economic development in Haryana |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |