CN115222305B - Wheat yield data management and early warning method - Google Patents
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Abstract
The invention discloses a management and early warning method based on wheat yield data, which relates to the technical field of agricultural resource research and comprises a data acquisition module, a yield early warning module, an environment analysis module and an on-site analysis module, wherein the yield early warning module is arranged, whether a wheat field grid is a low-yield wheat field grid or an over-yield wheat field grid can be judged according to the actual yield of the wheat field grid, the wheat field grid can be subjected to early warning analysis in time, workers can be arranged to perform on-site analysis on the low-yield wheat field grid and the over-yield wheat field grid through the on-site analysis module, the on-site analysis of the workers is reasonably arranged, the wheat field is divided into a plurality of grid areas, the environment data of the grid areas is acquired through a remote sensing satellite, the environment data of the grid areas is analyzed through the environment analysis module, and the workers can adjust the modes of pricing, marketing and the like of wheat according to the yield conditions of the low-yield wheat field grid and the over-yield wheat field grid in combination with the environment data.
Description
Technical Field
The invention relates to the technical field of agricultural resource research, in particular to a wheat yield data management and early warning method.
Background
Wheat is one of four main grain and oil crops, contains rich nutrients such as starch, fat, protein, vitamins, phosphorus, calcium, iron and the like, can be cultivated all over the country, and is second to rice in sowing area and total yield. Wheat plants are relatively short and small, but have developed root systems, strong absorption capacity, more nutrients needed and large soil fertility consumption.
The wheat planting process is influenced by various factors such as environment, pollution and the like, so that the actual yield of wheat is difficult to control. And the area that the wheat field is very big, and the staff is difficult to carry out comprehensive analysis and consideration to the wheat field, when the output in wheat field goes wrong, can't in time adjust the selling price and the selling mode of wheat, meets the condition that the wheat can't in time sell when output is too high easily and the condition that the output was too low when the output was too low and the wheat supply is short of asking.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a wheat yield data management and early warning method.
In order to achieve the purpose, the invention provides the following technical scheme:
a management early warning method based on wheat yield data comprises the following steps:
the method comprises the following steps: acquiring environmental data of a grid area through a remote sensing satellite, dividing a wheat field into a plurality of grid areas, and analyzing the environmental data of the grid area acquired by the remote sensing satellite;
step two: marking each grid area as a wheat field grid, obtaining a low yield value Ce of the wheat field grid, obtaining a low yield interval mean value Hu, obtaining an over-yield value Kc of the wheat field grid, sequencing dates corresponding to the over-energy wheat yield according to time sequence, obtaining an over-yield interval mean value Hz, obtaining the number of days of low-energy wheat yield of the wheat field grid 15 days before the current time of the system, marking the number of days of over-energy wheat yield of the wheat field grid 15 days before the current time of the system as Th, obtaining the number of days of over-energy wheat yield of the wheat field grid 15 days before the current time of the system, marking the number of days as Tq, and utilizing a formula to obtain the number of days of over-energy wheat yield of the wheat field grid
Obtaining a low yield early warning value Gs of the wheat field grid, wherein a1, a2 and a3 are all preset proportionality coefficients, the coefficient 0.15 is obtained according to experience or laboratory simulation, and a formula is utilized
Obtaining an overproduction early warning value Ls of the wheat field grid, wherein b1, b2 and b3 are all preset proportionality coefficients, the coefficient 0.23 is obtained according to experience or laboratory simulation, and a formula is utilized
Obtaining an early warning priority value Fu of the wheat field grid, wherein c1 and c2 are both preset proportionality coefficients, setting an early warning priority value threshold value as Eh, and when the early warning priority value Fu is larger than or equal to the early warning priority value threshold value Eh, obtaining the early warning priority value Fu of the wheat field gridThe method comprises the steps that a cornfield grid is marked as an early-warning cornfield grid, when a low-yield early-warning value Gs of the early-warning cornfield grid is larger than an over-yield early-warning value Ls, the early-warning cornfield grid is marked as the low-yield cornfield grid, when the low-yield early-warning value Gs of the early-warning cornfield grid is smaller than the over-yield early-warning value Ls, the early-warning cornfield grid is marked as the over-yield cornfield grid, the low-yield cornfield grid is sorted according to the early-warning priority value, and the over-yield cornfield grid is sorted according to the early-warning priority value;
step three: obtaining the position of a mobile phone terminal of a worker, drawing a circle by taking the current position as the circle center and the preset radius as the radius to obtain an analysis range, marking a low-yield cornfield grid and an over-yield cornfield grid which are positioned in the analysis range as pre-analysis grids, obtaining an early warning priority value Fu of the pre-analysis grids, obtaining an effective value of the pre-analysis grids and marking the effective value as Rw, calculating the distance difference between the position of the mobile phone terminal of the worker and the position of the pre-analysis grids to obtain an analysis distance and marking the analysis distance as Qy, and utilizing a formula to obtain the analysis distance and marking the analysis distance as Qy
And obtaining a prior analysis value Vz of the pre-analysis grid, and displaying the position of the pre-analysis grid with the maximum prior analysis value on a mobile phone terminal of a worker, wherein d1, d2 and d3 are preset proportionality coefficients, and the coefficient 0.34 is obtained according to experience or laboratory simulation.
Further, the low yield value of the wheat field grid is obtained by the following steps:
the method comprises the steps of marking the wheat yield of a wheat field grid 15 days before the current time of a system every day as an actual wheat yield, setting each actual wheat yield to correspond to an early-warning wheat yield, comparing the actual wheat yield with the early-warning wheat yield, marking the actual wheat yield as a low-energy wheat yield when the actual wheat yield is less than the early-warning wheat yield, calculating the difference between the early-warning wheat yield and the low-energy wheat yield to obtain a low-yield difference, marking the low-yield difference as Hy, setting a low-yield difference coefficient as Rs, and utilizing a formula to calculate the difference between the early-warning wheat yield and the low-energy wheat yield to obtain a low-yield difference, marking the low-yield difference coefficient as Hy, and utilizing the formula to calculate the yield of the wheat in the wheat field grid
The low yield value Ce, i =1,2, \8230;, n, i indicates the number of days, of the resulting wheat field grid was obtained.
Further, the over-yield value of the wheat field grid is obtained through the following steps:
when the actual wheat yield is larger than the early warning wheat yield, marking the actual wheat yield as the over-energy wheat yield, calculating the difference between the over-energy wheat yield and the early warning wheat yield to obtain an over-yield difference, marking the over-yield difference as Bu, setting an over-yield difference coefficient as Jr, and utilizing a formula to calculate the over-yield difference and obtain the over-yield difference
The over-yield value Kc, i =1,2, \8230;, n, i indicates the number of days, of the resulting wheat field grid was obtained.
Further, the low-yield interval mean value is obtained by the following steps:
the dates corresponding to the low-yield wheat quantities are sequenced according to time, the dates corresponding to two adjacent low-yield wheat quantities are subjected to difference calculation to obtain low-yield intervals, all the low-yield intervals are subjected to summation processing, and the average value is taken to obtain the low-yield interval average value.
Further, the average overproduction interval is obtained by the following steps:
and sequencing dates corresponding to the excessive wheat yield according to time, calculating a difference value of the dates corresponding to two adjacent excessive wheat yields to obtain an excessive interval, summing all the excessive intervals, and averaging to obtain an excessive interval average value.
Further, the specific steps of analyzing the environmental data of the remote sensing satellite acquisition grid area are as follows:
obtaining remote sensing images of a low-yield wheat field grid and an over-yield wheat field grid;
carrying out image processing on the remote sensing image to obtain remote sensing original data of an original image; wherein the image processing comprises image cropping, radiation correction and atmospheric correction;
and analyzing the original image according to the environment type to obtain the environment states of the low-yield wheat field and the over-yield wheat field.
Further, the effective value of the pre-analysis grid is obtained by the following steps:
when the mobile phone terminal location of a worker coincides with the position of the pre-analysis grid with the maximum analysis value, marking the moment as the analysis starting moment, when the worker completes the analysis, marking the moment as the analysis completing moment, calculating the difference between the analysis completing moment and the analysis starting moment to obtain the analysis duration, summing the analysis durations of the pre-analysis grid 15 days before the current time of the system, averaging to obtain the average value of the analysis durations, marking the average value as Jp, and utilizing a formula to calculate the analysis duration of the pre-analysis grid
And obtaining an effective value of the pre-analysis grid, wherein e1 is a preset proportionality coefficient.
Compared with the prior art, the invention has the following beneficial effects:
1. the yield early warning module is arranged, whether the cornfield grid is a low-yield cornfield grid or an over-yield cornfield grid can be judged according to the actual yield of the cornfield grid, early warning analysis can be carried out on the cornfield grid in time, workers can be arranged to carry out on-site analysis on the low-yield cornfield grid and the over-yield cornfield grid through the on-site analysis module, and the on-site analysis of the workers is reasonably arranged;
2. the wheat field is divided into a plurality of grid areas, the environment data of the grid areas are collected through a remote sensing satellite, the environment data of the grid areas are analyzed through an environment analysis module, and workers can adjust modes such as pricing and selling of wheat according to the yield conditions of low-yield wheat field grids and over-yield wheat field grids in combination with the environment data.
Drawings
Fig. 1 is a flow chart of a wheat yield data management early warning method.
Detailed Description
Example 1
Referring to fig. 1, a wheat yield data management early warning method comprises a data acquisition module, a yield early warning module and an environment analysis module;
the data acquisition module is used for acquiring environmental data of a grid area through a remote sensing satellite and sending the environmental data to the server for storage;
the yield early warning module is used for early warning the yield of the wheat field grids, marking the wheat field grids with low yield as low-yield wheat field grids, and marking the wheat field grids with over-yield as over-yield wheat field grids:
dividing a wheat field into a plurality of grid areas, setting a data acquisition module for each grid area, marking each grid area as a wheat field grid, setting the wheat yield of the wheat field grid 15 days before the current time of the system every day, marking the wheat yield of the wheat field grid every day as an actual wheat yield, setting each actual wheat yield to correspond to one early warning wheat yield, comparing the actual wheat yield with the early warning wheat yield, marking the actual wheat yield as a low-energy wheat yield when the actual wheat yield is less than the early warning wheat yield, calculating the difference between the early warning wheat yield and the low-energy wheat yield to obtain a low-yield difference, and marking the low-yield difference as Hy;
setting the low yield difference coefficient as Rs, s =1,2,3, \8230s; r1< R2< R3< \ 8230, and < Rs, wherein each low yield difference coefficient is set to correspond to a range of low yield differences, including (0, H1], (H1, H2], \ 8230; (Hy-1, hy), and when Hy belongs to (0, H1], the corresponding low yield difference coefficient takes the value of R1;
using formulas
Obtaining a low yield value Ce of the wheat field grid, sequencing dates corresponding to the low-yield wheat quantities according to time, calculating a difference value of the dates corresponding to two adjacent low-yield wheat quantities to obtain a low-yield interval, summing all the low-yield intervals, taking the average value to obtain a low-yield interval average value, and marking the average value as Hu;
when the actual wheat yield is larger than the early warning wheat yield, marking the actual wheat yield as an over-energy wheat yield, calculating the difference between the over-energy wheat yield and the early warning wheat yield to obtain an over-yield difference, and marking the over-yield difference as Bu;
setting the over yield difference coefficient as Jr, r =1,2,3, \8230r; j1< J2< J3< \ 8230, jr, setting the range of each over-yield difference coefficient corresponding to an over-yield difference, including (0, B1], (B1, B2], \8230, (Bu-1, bu), when Bu belongs to (0, B1), the value of the corresponding over-yield difference coefficient is J1;
using formulas
Obtaining an overproduction value Kc of a wheat field grid, sequencing dates corresponding to the overproduction quantities according to time, calculating a difference value of the dates corresponding to two adjacent overproduction quantities to obtain an overproduction interval, summing all the overproduction intervals, taking the average value to obtain an overproduction interval average value, and marking the average value as Hz;
obtaining the number of days that the low-energy wheat yield appears in the wheat field grids 15 days before the current time of the system, marking the number of days as Th, obtaining the number of days that the excessive wheat yield appears in the wheat field grids 15 days before the current time of the system, and marking the days as Tq;
using formulas
Acquiring a low yield early warning value Gs of the wheat field grid; wherein a1, a2 and a3 are all preset proportionality coefficients;
using formulas
Obtaining an overproduction early warning value Ls of the wheat field grid; wherein b1, b2 and b3 are all preset proportionality coefficients;
using formulas
Obtaining an early warning priority value Fu of the wheat field grid, setting an early warning priority value threshold value as Eh, marking the wheat field grid as the early warning wheat field grid when the early warning priority value Fu is larger than or equal to the early warning priority value threshold value Eh, and marking the early warning wheat field grid when the low yield early warning value Gs of the early warning wheat field grid is larger than the over-yield early warning value LsThe method comprises the steps that an alarm wheat field grid is marked as a low-yield wheat field grid, when the low-yield early warning value Gs of the early-warning wheat field grid is smaller than an over-yield early warning value Ls, the early-warning wheat field grid is marked as an over-yield wheat field grid, the low-yield wheat field grid is sorted according to the early-warning priority value, and the over-yield wheat field grid is sorted according to the early-warning priority value; wherein c1 and c2 are both preset proportionality coefficients;
the environment analysis module is used for analyzing the environment data of the remote sensing satellite acquisition grid area, and specifically comprises the following steps:
obtaining remote sensing images of a low-yield wheat field grid and an over-yield wheat field grid;
carrying out image processing on the remote sensing image to obtain remote sensing original data of an original image; wherein the image processing comprises image cropping, radiation correction and atmospheric correction;
and analyzing the original image according to the environment type to obtain the environment states of the low-yield wheat field and the over-yield wheat field.
Example 2
On the basis of the embodiment 1, the system further comprises a field analysis module, wherein the field analysis module is used for arranging workers to go to the low-yield wheat field grid and the over-yield wheat field grid for field analysis, and specifically comprises the following steps:
the method comprises the following steps: acquiring the position of a mobile phone terminal of a worker, drawing a circle by taking the current position as the center of the circle and a preset radius as the radius to obtain an analysis range, and marking a low-yield wheat field grid and a high-yield wheat field grid which are positioned in the analysis range as pre-analysis grids;
step two: acquiring an early warning priority value Fu of the pre-analysis grid;
step three: obtaining an effective value of the pre-analysis grid and marking the effective value as Rw;
step four: calculating the distance difference between the position of the mobile phone terminal of the worker and the position of the pre-analysis grid to obtain an analysis distance, and marking the analysis distance as Qy;
step five: using a formula
Obtaining a priority analysis value Vz of a pre-analysis grid; wherein, the first and the second end of the pipe are connected with each other,d1, d2 and d3 are all preset proportionality coefficients; displaying the position of the pre-analysis grid with the maximum priority analysis value on a mobile phone terminal of a worker;
the effective value of the pre-analysis grid is obtained by the following steps:
when the mobile phone terminal location of a worker coincides with the position of the pre-analysis grid with the maximum analysis value, marking the moment as the analysis starting moment, when the worker completes the analysis, marking the moment as the analysis completing moment, calculating the difference between the analysis completing moment and the analysis starting moment to obtain the analysis duration, summing the analysis durations of the pre-analysis grid 15 days before the current time of the system, averaging to obtain the average value of the analysis durations, marking the average value as Jp, and utilizing a formula to calculate the analysis duration of the pre-analysis grid
And obtaining an effective value of the pre-analysis grid, wherein e1 is a preset proportionality coefficient.
The working principle is as follows:
the wheat field early warning system is characterized in that a yield early warning module is arranged, whether a wheat field grid is a low-yield wheat field grid or an over-yield wheat field grid can be judged according to the actual yield of the wheat field grid, early warning analysis can be timely carried out on the wheat field grid, workers can be arranged to carry out on-site analysis on the low-yield wheat field grid and the over-yield wheat field grid through an on-site analysis module, the on-site analysis of the workers is reasonable, the wheat field is divided into a plurality of grid areas, the environment data of the grid areas are collected through a remote sensing satellite, the environment data of the grid areas are analyzed through the environment analysis module, and the workers can adjust modes such as pricing and selling of wheat according to the yield conditions of the low-yield wheat field grid and the over-yield wheat field grid and the environment data.
The above description is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments, and all technical solutions belonging to the idea of the present invention belong to the protection scope of the present invention. It should be noted that modifications and embellishments within the scope of the present template may be made by those skilled in the art without departing from the principles of the present invention.
Claims (7)
1. A management early warning method based on wheat yield data is characterized by comprising the following steps:
the method comprises the following steps: acquiring environmental data of a grid area through a remote sensing satellite, dividing a wheat field into a plurality of grid areas, and analyzing the environmental data of the grid area acquired by the remote sensing satellite;
step two: marking each grid area as a wheat field grid, obtaining a low yield value Ce of the wheat field grid, obtaining a low yield interval mean value Hu, obtaining an over-yield value Kc of the wheat field grid, sequencing dates corresponding to the over-energy wheat yield according to time sequence, obtaining an over-yield interval mean value Hz, obtaining the number of days of low-energy wheat yield of the wheat field grid 15 days before the current time of the system, marking the number of days of over-energy wheat yield of the wheat field grid 15 days before the current time of the system as Th, obtaining the number of days of over-energy wheat yield of the wheat field grid 15 days before the current time of the system, marking the number of days as Tq, and utilizing a formula to obtain the number of days of over-energy wheat yield of the wheat field grid
Acquiring a low yield early warning value Gs of the wheat field grid, wherein a1, a2 and a3 are all preset proportionality coefficients, and utilizing a formula
Obtaining an overproduction early warning value Ls of the wheat field grid, wherein b1, b2 and b3 are all preset proportionality coefficients, and utilizing a formula
Obtaining an early warning priority value Fu of a wheat field grid, wherein c1 and c2 are both preset proportionality coefficients, setting an early warning priority value threshold value as Eh, when the early warning priority value Fu is larger than or equal to the early warning priority value threshold value Eh, marking the wheat field grid as an early warning wheat field grid, when a low yield early warning value Gs of the early warning wheat field grid is larger than an over-yield early warning value Ls, marking the early warning wheat field grid as a low yield wheat field grid, and when the low yield early warning value Gs of the early warning wheat field grid is smaller than the over-yield early warning value Ls, marking the early warning wheat field grid as a low yield wheat field gridThe grids are marked as over-yield cornfield grids, the low-yield cornfield grids are sorted according to the early warning priority value, and the over-yield cornfield grids are sorted according to the early warning priority value;
step three: obtaining the position of a mobile phone terminal of a worker, drawing a circle by taking the current position as the center of a circle and taking the preset radius as the radius to obtain an analysis range, marking a low-yield cornfield grid and a high-yield cornfield grid which are positioned in the analysis range as pre-analysis grids, obtaining an early warning priority value Fu of the pre-analysis grids, obtaining an effective value of the pre-analysis grids and marking the effective value as Rw, calculating the distance difference between the position of the mobile phone terminal of the worker and the position of the pre-analysis grids to obtain an analysis distance and marking the analysis distance as Qy, and utilizing a formula to obtain the analysis distance and marking the analysis distance as Qy
And obtaining a prior analysis value Vz of the pre-analysis grid, and displaying the position of the pre-analysis grid with the maximum prior analysis value on a mobile phone terminal of a worker, wherein d1, d2 and d3 are all preset proportionality coefficients.
2. The wheat yield data management and early warning method based on claim 1, wherein the low yield value of the wheat field grid is obtained by the following steps:
obtaining the wheat yield of each day of a wheat field grid 15 days before the current time of the system, marking the wheat yield of each day of the wheat field grid as actual wheat yield, setting each actual wheat yield to correspond to one early warning wheat yield, comparing the actual wheat yield with the early warning wheat yield, marking the actual wheat yield as low-energy wheat yield when the actual wheat yield is less than the early warning wheat yield, calculating the difference between the early warning wheat yield and the low-energy wheat yield, obtaining a low-yield difference, marking the low-yield difference as Hy, setting a low-yield difference coefficient as Rs, and utilizing a formula to calculate the difference between the early warning wheat yield and the low-energy wheat yield to obtain a low-yield difference, marking the low-yield difference as Hy, and utilizing the formula to calculate the low-yield difference coefficient as Rs
And obtaining the low yield value Ce of the wheat field grids.
3. The wheat yield data management and early warning method based on claim 1, wherein the over-yield value of the wheat field grid is obtained by the following steps:
when the actual wheat yield is larger than the early warning wheat yield, marking the actual wheat yield as the over-energy wheat yield, calculating the difference between the over-energy wheat yield and the early warning wheat yield to obtain an over-yield difference, marking the over-yield difference as Bu, setting an over-yield difference coefficient as Jr, and utilizing a formula
And obtaining the over-yield value Kc of the wheat field grid.
4. The wheat yield data management and early warning method as claimed in claim 2, wherein the low yield interval mean value is obtained by the following steps:
the dates corresponding to the low-yield wheat quantities are sequenced according to time, the dates corresponding to two adjacent low-yield wheat quantities are subjected to difference calculation to obtain low-yield intervals, all the low-yield intervals are subjected to summation processing, and the average value is taken to obtain the low-yield interval average value.
5. The wheat yield data management and early warning method as claimed in claim 3, wherein the average value of the overproduction interval is obtained by the following steps:
and sequencing dates corresponding to the excessive wheat yield according to time, calculating a difference value of the dates corresponding to two adjacent excessive wheat yields to obtain an excessive interval, summing all the excessive intervals, and averaging to obtain an excessive interval average value.
6. The wheat yield data management and early warning method based on the claim 1 is characterized in that the specific steps of analyzing the environmental data of the remote sensing satellite acquisition grid area are as follows:
obtaining remote sensing images of a low-yield wheat field grid and an over-yield wheat field grid;
carrying out image processing on the remote sensing image to obtain remote sensing original data of an original image; wherein the image processing comprises image cropping, radiation correction and atmospheric correction;
and analyzing the original image according to the environment type to obtain the environment states of the low-yield wheat field and the over-yield wheat field.
7. The wheat yield data management and early warning method based on the claim 1 is characterized in that the effective value of the pre-analysis grid is obtained through the following steps:
when the mobile phone terminal location of a worker coincides with the position of the pre-analysis grid with the maximum analysis value, marking the moment as the analysis starting moment, when the worker completes the analysis, marking the moment as the analysis completing moment, calculating the difference between the analysis completing moment and the analysis starting moment to obtain the analysis duration, summing the analysis durations of the pre-analysis grid 15 days before the current time of the system, averaging to obtain the average value of the analysis durations, marking the average value as Jp, and utilizing a formula to calculate the analysis duration of the pre-analysis grid
And obtaining an effective value of the pre-analysis grid, wherein e1 is a preset proportionality coefficient.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006277321A (en) * | 2005-03-29 | 2006-10-12 | Toshiba Socio System Support Co Ltd | Business analysis support system and method by gis |
| CN109451026A (en) * | 2018-11-15 | 2019-03-08 | 合肥思博特软件开发有限公司 | A kind of wheatland intelligent early-warning monitoring system based on Internet of Things |
| CN109451905A (en) * | 2018-12-19 | 2019-03-12 | 西南大学 | A kind of slope of hilly and mountainous land land control changes slow method |
| CN110309478A (en) * | 2019-07-06 | 2019-10-08 | 温州科技职业学院 | A kind of shared system based on agriculture big data |
| CN113473840A (en) * | 2019-02-21 | 2021-10-01 | 克莱米特公司 | Agricultural field digital modeling and tracking for realizing agricultural field test |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11069005B2 (en) * | 2014-09-12 | 2021-07-20 | The Climate Corporation | Methods and systems for determining agricultural revenue |
| WO2017004074A1 (en) * | 2015-06-30 | 2017-01-05 | Precision Planting Llc | Systems and methods for image capture and analysis of agricultural fields |
-
2022
- 2022-09-21 CN CN202211146605.2A patent/CN115222305B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006277321A (en) * | 2005-03-29 | 2006-10-12 | Toshiba Socio System Support Co Ltd | Business analysis support system and method by gis |
| CN109451026A (en) * | 2018-11-15 | 2019-03-08 | 合肥思博特软件开发有限公司 | A kind of wheatland intelligent early-warning monitoring system based on Internet of Things |
| CN109451905A (en) * | 2018-12-19 | 2019-03-12 | 西南大学 | A kind of slope of hilly and mountainous land land control changes slow method |
| CN113473840A (en) * | 2019-02-21 | 2021-10-01 | 克莱米特公司 | Agricultural field digital modeling and tracking for realizing agricultural field test |
| CN110309478A (en) * | 2019-07-06 | 2019-10-08 | 温州科技职业学院 | A kind of shared system based on agriculture big data |
Non-Patent Citations (2)
| Title |
|---|
| 利用网格法确定县域农田整治优先度;沈立宏等;《农业工程学报》;20120915(第18期);全文 * |
| 黄土高原台塬区域麦田土壤养分的管理分区;原亚超等;《山西农业科学》;20200515(第05期);全文 * |
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