Mountain field meteorological data automatic acquisition system and method and application thereof

Abstract

This invention provides an automatic meteorological data acquisition system for mountainous fields. The system includes a data acquisition system, a data receiving device, and a data transmitting device. The data acquisition system is sequentially equipped with a rainfall meter, a light meter, an air temperature meter, and a soil temperature and humidity meter. The data receiving device is connected to each of the measuring devices in the data acquisition system. The data transmitting device is connected to the data receiving device. Both the data transmitting and receiving devices are connected to a battery. This system is simple in structure, low in cost, easy to install, and allows data to be transmitted on-site to a computer or remotely. The collected data can also be directly downloaded to a USB flash drive. It has wide applicability, accurate data transmission, and stable observation transmission quality. It can automatically, accurately, and in real-time collect meteorological data in mountainous fields without requiring dedicated personnel or on-site management; it can also enable personalized meteorological operations in remote mountainous areas.

Description

Technical Field

[0001] This invention relates to a meteorological data acquisition system, method, and application, specifically to an automatic meteorological data acquisition system for mountainous fields and its application method, belonging to the field of agricultural production equipment technology. Background Technology

[0002] Due to differences in topography and altitude, the climate resources and meteorological disaster patterns vary greatly among different ecological and climatic zones. The transplanting period, agronomic traits, and product quality of crops (such as tobacco) are unstable. In particular, in years with poor meteorological conditions, the quality of crop products in mid- to high-altitude areas is difficult to guarantee.

[0003] Meteorological conditions are closely related to the style, quality, and yield of crops. Altitude has a significant impact on meteorological conditions. Numerous studies have shown that as altitude changes, climatic elements such as light, temperature, and water, as well as meteorological disasters, also change, leading to differences in the climatic environment for crops at various growth and development stages, thereby affecting crop growth, development, and the formation of crop quality characteristics.

[0004] Currently, there are only two companies in China (Tianjin and Jiangsu) specializing in the research and development and production of ground-based and radiosonde meteorological instruments and equipment. They possess a series of processing and manufacturing equipment and metrological verification and testing methods for rainfall, air pressure, humidity, temperature coefficient, and wind tunnel measurements. They can produce nearly forty types of sensors and instruments for wind direction, wind speed, precipitation, evaporation, radiation, temperature and humidity, visibility, and weather phenomena. They can also construct various environmental monitoring network systems, radiosondes, and ground data processing systems. Furthermore, they undertake the design and modification of specialized vehicles for emergency command and on-site verification. Their service areas cover meteorology, hydrology, environmental protection, scientific research, transportation, agriculture, energy, and national defense. However, they suffer from the drawback of uneven spatial distribution and excessively large spatial distances between meteorological stations.

[0005] However, there is currently no automated meteorological data collection system for mountainous fields. Mountainous terrain is unique, and climate changes rapidly and complexly. Data measured by fixed meteorological stations represents too wide an area, and the data is only accurate within a very small region, unable to guide large-scale agricultural production in mountainous areas. Furthermore, there is a lack of research on the relationship between tobacco leaf maturity and climatic factors, particularly in flue-cured tobacco production. Especially in mountainous climates, if the multi-dimensional climate resources can be fully utilized, by adjusting the transplanting time to match the optimal maturity of tobacco leaves for harvest in each planting unit and by timely prevention of pests and diseases, the utilization efficiency of tobacco climate resources will be effectively increased, which will help achieve high-yield, high-quality, and efficient flue-cured tobacco production.

[0006] Furthermore, existing technologies for early warning of crop diseases based on meteorological data detection are not sufficiently advanced and cannot provide effective early warnings of potential crop pests and diseases based on specific meteorological conditions in mountainous fields.

[0007] Big data-based meteorological decision-making services have been developed in provinces such as Hunan, Anhui, and Guizhou. These systems are designed for major grain crops, vegetables, and fruits. However, there is still no development of an automatic meteorological data collection system for mountainous fields and its application methods. This directly impacts the level of ecological agriculture, lean tobacco production, and standardized production. Summary of the Invention

[0008] To address the shortcomings of existing technologies, this invention provides an automatic meteorological data acquisition system for mountainous fields and its application method. It aims to play a significant role in fully utilizing the three-dimensional climate resources of crops (e.g., tobacco) and improving the level of lean and standardized production. The automatic meteorological data acquisition system for mountainous fields provided by this invention includes a data acquisition system, a data receiving device, and a data transmitting device. The data acquisition system is sequentially equipped with a rainfall meter, a light meter, an air temperature meter, and a soil temperature and humidity meter. The data receiving device is connected to each of the measuring devices in the data acquisition system. The data transmitting device is connected to the data receiving device. Both the data transmitting device and the data receiving device are connected to a battery. This system has a simple structure, low cost, and is easy to install. Data can be transmitted on-site to a computer or remotely, or the collected data can be directly downloaded to a USB flash drive. It has wide applicability, accurate data transmission, and stable observation transmission quality. It can automatically, accurately, and in real-time collect meteorological data in mountainous fields without requiring dedicated personnel or site management; it can also enable personalized meteorological operations in remote mountainous areas.

[0009] According to the first embodiment of the present invention, an automatic meteorological data acquisition system for mountainous fields is provided.

[0010] An automatic meteorological data acquisition system for mountainous fields is disclosed. The system includes a data acquisition system, a data receiving device, and a data transmitting device. The data acquisition system includes a rainfall meter, a light intensity meter, an air temperature meter, a soil moisture meter, and a soil temperature meter. All of these meters are connected to the data receiving device. The data receiving device is connected to the data transmitting device. All three devices—the data acquisition system, the data receiving device, and the data transmitting device—are connected to a battery.

[0011] Preferably, the system also includes a data processing unit. The data processing unit is connected to the data transmission unit.

[0012] The data processing device includes a digital input module, an analog input module, a digital-to-analog converter, a digital output module, an analog comparator, an analog output module, logic gates, an application program, and a microprocessor.

[0013] Preferably, the system also includes an alarm device. The alarm device is connected to the data processing device.

[0014] The alarm device includes a terminal module, an alarm, and a communication module; the communication module includes a digital communication system and an analog communication system.

[0015] In this invention, the data processing device includes:

[0016] Data access service layer: consists of multiple gateways forming a dynamic Nginx load balancer, connected to the data sending device;

[0017] Data Analysis Service Layer: Utilizes a Spark cluster to perform statistical analysis on the data imported from the data access service layer.

[0018] Data storage service layer: Adopting the Hadoop architecture, it stores meteorological data parsed by the data analysis service layer and stores the results of data analysis in a distributed caching system and a relational database;

[0019] Data application service layer: It calls data from the data storage service layer through the REST API interface, realizes interaction with the web server, distributed caching system and storage system, and connects to the alarm device.

[0020] According to a second embodiment of the present invention, a method for climate suitability assessment is provided.

[0021] A method for climate suitability assessment using the automatic meteorological data acquisition system for mountainous fields described in the first embodiment, the method comprising the following steps:

[0022] 1) Meteorological element data detection: Rainfall meter detects the daily precipitation at the crop location, sunshine meter detects the sunshine duration at the crop location, air temperature meter detects the daily average temperature, maximum temperature, and minimum temperature at the crop location, soil moisture meter detects the daily average soil moisture at the crop location, and soil temperature meter detects the daily average soil temperature at the crop location.

[0023] 2) Meteorological element data processing: The multivariate regression residual Gaussian operator correction method (MRG) was used to interpolate the daily average temperature, maximum temperature, minimum temperature, sunshine duration, daily average soil humidity, and daily average soil temperature; the ordinary kriging method (KRG) was selected to interpolate the daily precipitation.

[0024] 3) Based on the results of step 2), conduct a climate suitability assessment of the crop location.

[0025] In this invention, step 3) employs a fuzzy mathematical model for climate suitability evaluation. Specifically, it involves using a membership function to represent the classification criteria of meteorological elements and their impact on crops, and using a membership function model and an index sum method to analyze the climate suitability of the crop's location. The climate suitability index (CFI) is:

[0026]

[0027] Wherein: the proposed crop planting area is divided into m regions, j∈[1,m]; meteorological element data is detected for each region, and the meteorological element data detection for each region includes i meteorological elements, i∈[precipitation, sunshine duration, daily average temperature, daily maximum temperature, daily minimum temperature, daily average soil humidity, daily average soil temperature]; N ij W represents the membership value of the j-th tobacco region and the i-th climate index; ij Let N and N represent the weighting coefficients of the j-th tobacco region and the i-th climate index, respectively, where 0 < N. ij ≦1, 0<W ij ≦1, and satisfy

[0028] As a preferred method, a climate-suitable crop growth curve is plotted with time on the horizontal axis and the Climate Suitability Index (CFI) on the vertical axis. Based on the relationship between time and the CFI in the climate-suitable crop growth curve, an appropriate time for crop planting is selected.

[0029] Among them, the growth curve of crops in climate-suitable environments includes parabolic, S-shaped, or inverse S-shaped curve relationships. Crop planting stages include the root elongation stage, transplanting stage, vigorous growth stage, and maturity stage.

[0030] According to a third embodiment of the present invention, a method for early warning of crop diseases is provided.

[0031] A method for crop disease early warning using the automatic meteorological data acquisition system for mountainous fields described in the first embodiment, the method comprising the following steps:

[0032] 1) Meteorological element data detection: Rainfall meter detects the daily precipitation at the crop location, sunshine meter detects the sunshine duration at the crop location, air temperature meter detects the daily average temperature, maximum temperature, and minimum temperature at the crop location, soil moisture meter detects the daily average soil moisture at the crop location, and soil temperature meter detects the daily average soil temperature at the crop location.

[0033] 2) Based on the meteorological data obtained from the detection, early warnings are issued for possible crop diseases.

[0034] Preferably, the disease warning is for red spot disease. Specifically, it involves using the red spot disease severity index (Y1) as the dependent variable, and relevant meteorological factors and the previous year's red spot disease severity index (Y1') as independent variables, to calculate the probability of the crop contracting red spot disease during the observation period.

[0035] Y1=(2.7894-0.1674SSH-0.5382TM)Y1'-(0.05154Tm)Y1' 2 -0.0052;

[0036] Where: Tm is the lowest temperature during the observation period, TM is the highest temperature during the observation period, and SSH is the sunshine duration during the observation period.

[0037] When the red star disease severity index (Y1) is greater than 0.16%, it indicates that red star disease has begun to occur; when the red star disease severity index (Y1) is greater than 3.36%, it indicates that red star disease is severe.

[0038] Preferably, the disease warning is for black shank disease. Specifically, it involves using the black shank disease severity index (Y2) as the dependent variable, and relevant meteorological factors and the previous year's black shank disease severity index (Y2') as independent variables, to calculate the probability of the crop contracting black shank disease during the observation period.

[0039] Y2=(1.5195+0.0748R)Y2'-(0.0051+0.0007R)Y2' 2 -1.1548Rd-6.5428TM+1.1065SSH+9.5955;

[0040] Where: Tm is the lowest temperature during the observation period, TM is the highest temperature during the observation period, SSH is the sunshine duration during the observation period, R is the rainfall during the observation period, and Rd is the number of rainy days during the observation period.

[0041] When the black shank disease severity index (Y2) is greater than 0.16%, it indicates that black shank disease has begun to occur; when the black shank disease severity index (Y2) is greater than 5%, it indicates that black shank disease is severe.

[0042] Preferably, the disease warning is for mosaic virus. Specifically, it involves using the mosaic virus disease index (Y3) as the dependent variable, and relevant meteorological factors and the previous year's mosaic virus disease index (Y3') as independent variables, to calculate the probability of the crop contracting mosaic virus during the observation period.

[0043] Y3=1.1148TM×Y3'-0.0316RH×Y3'2 +0.3013;

[0044] Where: TM is the highest temperature during the observation period, and RH is the average soil humidity during the observation period.

[0045] When the mosaic disease severity index (Y3) is greater than 0.16%, it indicates that mosaic disease has begun to occur; when the mosaic disease severity index (Y3) is greater than 8.5%, it indicates that mosaic disease is severe.

[0046] According to the fourth embodiment of the present invention, an application of an automatic meteorological data acquisition system for mountainous fields is provided.

[0047] The automatic meteorological data acquisition system for mountainous fields described in the first implementation scheme is used to monitor flue-cured tobacco planting, determine the transplanting period of flue-cured tobacco, and prevent diseases during the tobacco planting period.

[0048] In this invention, data in the data receiving device can also be transmitted via a remote transmission system. The data transmission speed and frequency can be set according to actual conditions.

[0049] In this invention, the data receiving and processing device includes a digital input module, an analog input module, a 10-bit digital-to-analog converter, a digital output module, an analog comparator, an analog output module, logic gates, an application program, and a microprocessor. It includes functions such as data receiving, processing, storage, and statistics. It features a five-layer structure: data source, data access, analysis and storage, data service, and display.

[0050] 1) Data access service layer. Multiple gateways are used to form a dynamic Nginx load balancer to meet the concurrent requirements of terminal data access.

[0051] 2) Data Analysis Service Layer. A Spark cluster is used for statistical analysis of the data. This service employs a distributed architecture and master-slave scheduling node design to reuse system resources and ensure continuous system operation and uninterrupted upgrade capabilities in the event of a single point of failure. Data processing algorithms are encapsulated and deployed on Spark nodes.

[0052] 3) Data storage service layer. A Hadoop architecture is used to store meteorological data parsed by the access layer, and the results of data analysis are stored in a distributed caching system and a relational database. At the server hardware level, relational data RAID (Redundant Arrays of Independent Disks) is used for backup.

[0053] 4) Data Application Service Layer. This layer uses REST API interfaces to call data storage services from the data storage layer, enabling interaction with the web server, distributed caching system, and storage system. It also utilizes the web server and Nginx server to interact with mobile and desktop software.

[0054] In existing technology, the Wuling Mountains diagonally traverse the mountainous region from northeast to southwest. This region has complex terrain with elevations ranging from 97 to 1736 meters, exhibiting significant differences in altitude. Western Hunan has a subtropical monsoon climate, and due to its diverse topography and significant elevation differences, it possesses a very distinct three-dimensional climate characteristic. Western Hunan has suitable light, heat, water, and soil for tobacco growth, making it a suitable area for tobacco cultivation in China. However, due to differences in topography and altitude, the climate resources and meteorological disaster patterns vary considerably across different climatic ecological zones, leading to instability in tobacco transplanting time, agronomic traits, and yield and quality. Particularly in years with poor weather conditions, the yield and quality of tobacco leaves in mid-to-high altitude areas are difficult to guarantee. To improve the yield and quality of tobacco leaves in different climatic ecological zones, it is necessary to understand the characteristics of climate resources and the patterns of meteorological disasters in these zones, thereby implementing corresponding agricultural technical measures to provide strong support for improving the yield and quality of flue-cured tobacco.

[0055] Meteorological conditions are closely related to the style, quality, and yield of flue-cured tobacco. Altitude has a significant impact on meteorological conditions. Numerous studies have shown that with changes in altitude, climatic elements such as light, temperature, and water, as well as meteorological disasters, also change, resulting in differences in the climatic environment at various stages of tobacco growth and development, thus affecting the growth and development of flue-cured tobacco and the formation of tobacco leaf quality characteristics.

[0056] In this invention, a portable system is provided that integrates real-time automatic on-site observation and data transmission of mountain meteorological factors (temperature, light, rainfall, ground temperature, etc.) in response to the characteristics of mountain agriculture. In particular, it addresses the current situation where agricultural production is largely dependent on the weather (which is unpredictable) and cannot cope with severe weather problems such as droughts and floods. Furthermore, with global warming, abnormal disasters are becoming more frequent, making it difficult to effectively guarantee farmers' income and seriously affecting the sustainable and healthy development of modern agriculture.

[0057] The system described in this invention is a portable, underground, integrated functional unit. An external solar panel and temperature sensor are mounted on the exterior of a vertical support box. The internal cavity, from top to bottom, houses a data receiving device, a data transmitting device, and a battery. By installing a solar panel on the exterior of the box, this invention can utilize stored solar energy on sunny days, working in conjunction with the battery for energy conservation and environmental protection. Furthermore, this portable system integrates real-time, on-site automatic observation and data transmission, with fully automated control, solving the problem of high labor costs associated with conventional weather stations. The automatic data observation and transmission are accurate, eliminating human error and reducing costs while increasing efficiency.

[0058] The system was installed with a reasonable configuration in both north-south vertical and east-west horizontal directions. The sensor configuration strategy was optimized. While achieving the dual goals of accurately acquiring overall trend information on meteorological factors and enhancing the abundance of meteorological factor information, the spatial location of the crop canopy was also considered during sensor placement.

[0059] In this invention, the data acquisition system, data receiving device, and data sending device can employ a GPRS module. The GPRS module has three main functions: data acquisition (including storage of at least one month's worth of minute-by-minute observation data), data transmission (including 4G wireless communication), and terminal operation (including the transmission and setting of various parameters of the data acquisition device and the reading of various data from the data acquisition device).

[0060] Preferably, the rain sensor is SL5-1, with a measurement range of 0-4 mm / min, a resolution of 0.1 mm, and an accuracy of ±0.4 mm (≤10 mm) ±4% (>10 mm).

[0061] Preferably, the air temperature sensor is WZP1, with a temperature measurement range of -50℃ to 50℃, a resolution of 0.1℃, and an accuracy of ±0.2℃.

[0062] Preferably, the ground temperature sensor is a WZP2, with a temperature measurement range of -50℃ to 50℃ at 0CM and 5CM, a resolution of 0.1℃, and an accuracy of ±0.2℃.

[0063] Preferably, the soil moisture sensor has the following power requirements: 12VDC±20%@40mA, output: 4-20mA. Note: This can be converted to volts via a shunt resistor; maximum dimensions: 3 / 4” diameter × 27” length, sea freight weight: 1 lb, temperature output: 1uA / °K (i.e., 0℃=273uA, 50℃=323uA), power-on time: one minute after power-on.

[0064] Preferably, the solar radiation sensor has the following characteristics: 1) power supply: 9–15V DC; 2) spectral range: 400nm–1100nm; 3) threshold: direct irradiance 120W / m². 2 ;4) Maximum permissible error for threshold: ±5.5W / m 2 ;5) Maximum permissible error: ± 9.94%;6) Threshold annual stability: ±2.5%;7) Sensor power consumption: 0.12W without heating, 12VDC power supply; 8.5W with heating, 12VDC power supply (for clearing dew and frost).

[0065] Based on the automatic meteorological data acquisition system for mountainous fields of this invention, an application mini-program can also be created. The entire system adopts a layered architecture style, with interfaces between layers strictly designed according to RESTful Web APIs, and is specifically designed as an application layer, service layer, infrastructure layer, and logic layer. Figure 2 The application layer is based on the principle of data separation, adopts a unified REST API interface specification, and uses tenant identification for compilation and monitoring. The infrastructure layer is based on the Spring Boot + MyBatis framework, incorporates a caching system, and uses REST API for interface services, applied to database read / write separation. The facilities layer supports physical servers, virtual servers, etc. The logic layer is implemented using JavaScript. The application mini-program can provide early warnings for abnormal weather and crop diseases.

[0066] In this invention, an automatic meteorological data acquisition system for mountainous fields is equipped with an energy-saving power supply, including a solar panel, a battery, and connecting lines. The solar panel is located on the upper part of the chassis for efficient use of solar energy. The battery is detachably installed at the bottom of the chassis for easy maintenance and replacement. All power-consuming components of the system (e.g., rain sensors, temperature sensors, ground temperature sensors, soil moisture sensors, sunshine sensors, data acquisition system, GPRS module, etc.) are independently connected to the battery via connecting lines, and the battery is connected to the solar panel. The battery button in this invention is a power button with a control module. After the button is pressed, the system operates according to a pre-programmed and set program. Simultaneously, based on different meteorological factors, the data acquisition system (TYQ300) can identify and process data in real time and provide forecasts and early warnings. The data acquisition system (TYQ300) is connected to the GPRS module (General Purpose Radio Packet Transmitter). After receiving the data signal sent by the data acquisition system (TYQ300), the GPRS module automatically transmits it to the designated data center.

[0067] In this invention, the data acquisition system (TYQ300) includes a rainfall sensor (SL3-1), a temperature sensor (WZP1), a ground temperature sensor, a soil moisture sensor, and a sunshine sensor. The rainfall sensor (SL3-1), from top to bottom, includes a sensor bracket, a pre-embedded support for the rainfall sensor (SL3-1), a signal line, mounting holes, pre-embedded connecting wires, a PVC pipe, a deep sleeve, and ground anchor components. There should be no obstructions around or above it, and it cannot be installed in damp areas, but it must be installed approximately 5 meters away from the observed crop. The temperature sensor (WZP1), from top to bottom, includes a 1.5M cast aluminum support pole, a data acquisition unit bracket, a sensor bracket, a signal line, pre-embedded connecting wires, anchor bolts for the cast aluminum support pole, and underground PVC pipes for the cast aluminum support pole. The system consists of a pipe and a deep sleeve; its installation height is 1.5 meters high to distinguish it from the ground surface temperature, and it also needs to be installed about 4 meters away from the crop being observed; the ground temperature sensor, from top to bottom, includes a temperature and humidity ventilation cover, a temperature and humidity bracket, ground temperature sensor 1 (0CM), ground temperature sensor 2 (5CM), a sensor bracket, a shallow ground temperature bracket, a signal line, a pre-embedded connecting line, anchor bolts, an underground PVC pipe, and a deep sleeve; it needs to be installed about 3 meters away from the crop being observed; the soil moisture sensor, from top to bottom, includes a temperature and humidity ventilation cover, a temperature and humidity bracket, a signal line, a pre-embedded connecting line, anchor bolts, an underground PVC pipe, a stainless steel rod, and a deep sleeve; it needs to be installed about 2.5 meters away from the crop being observed; the sunlight sensor, from top to bottom, includes a sunlight sensor bracket, a sunlight sensor positioning plate, a signal line, a pre-embedded connecting line, a sunlight sensor (CSD3) angle design, a sunlight sensor (CSD3) trench design, anchor bolts, a positioning plate, a lead pipe, an underground PVC pipe, and a deep sleeve; There should be no obstacles around or above it, and there should be no large buildings or trees in the distance. It should not be installed in a dark place, but it should be installed at a distance of about 6 meters from the crop being observed.

[0068] In this invention, the GPRS module (General Wireless Packet Transmission Module) includes, from top to bottom, a power system, a chassis, a cast aluminum support pole for the chassis, communication cable 1, communication cable 2, a signal line, a pre-embedded connecting line, anchor bolts, an underground PVC pipe, and a deep conduit. After the power system is started, the received data signals are promptly transmitted to the designated data center through communication cable 1, communication cable 2, and the signal line.

[0069] In this invention, an inclined PVC pipe is fixedly installed below the rain sensor (SL3-1). The upper end of the PVC pipe is fixed to a pre-embedded connecting line, and its lower end extends downward at an incline into a deep sleeve. The first end is connected to a mounting hole, and the last end is connected to a signal line. After the power system is turned on, the rainfall data is automatically transmitted in real time to the data acquisition system (TYQ300), and then promptly sent to the designated data center via the GPRS module (General Purpose Radio Packet Transmitter).

[0070] In this invention, a temperature sensor (WZP1) is also installed directly above the chassis housing the GPRS module and the data acquisition system (TYQ300). An inclined data acquisition bracket is fixedly installed below the temperature sensor (WZP1), with one end attached to the sensor bracket and the other end connected to the signal line. After the power system is turned on, the temperature data is automatically transmitted to the data acquisition system (TYQ300) in real time, and then promptly sent to the designated data center via the GPRS module (General Purpose Wireless Packet Transmitter).

[0071] In this invention, an inclined temperature and humidity ventilation hood, a temperature and humidity bracket, and a sensor bracket are fixedly installed above the ground temperature sensor (SL3-1). A shallow ground temperature bracket is fixedly installed at the base below. An inclined PVC pipe is fixedly installed on the ground. The upper end of the PVC pipe is fixed to a pre-embedded connecting line, and its lower end extends downward at an incline to a deep sleeve. The first end is connected to the ground temperature sensor 1 (0CM), and the last end is connected to a signal line. The ground temperature sensor 1 (0CM) is connected to the ground temperature sensor 2 (5CM). After the power system is turned on, the ground temperature data is automatically transmitted to the data acquisition system (TYQ300) in real time, and then promptly sent to the designated data center via the GPRS module (General Purpose Wireless Packet Transmitter).

[0072] In this invention, two soil temperature sensors are connected in series from top to bottom. Because the nutritional needs of crops vary at different growth stages, soil temperatures at different depths are measured. The depths of soil temperature sensor 1 (0 cm) and soil temperature sensor 2 (5 cm) can be adjusted according to the soil temperature requirements of the crops at each growth stage; for example, they can be adjusted to soil temperature sensor 1 (5 cm) and soil temperature sensor 2 (10 cm) to ensure the crop's growth needs are met.

[0073] In this invention, both the soil moisture sensor and the ground temperature sensor are connected below the temperature and humidity ventilation hood. An inclined temperature and humidity bracket and a sensor bracket are fixedly installed above the soil moisture sensor, and a signal line is fixedly installed at its base. An inclined PVC pipe is fixedly installed on the ground surface, with its upper end fixed to a pre-embedded connecting line and its lower end extending downwards at an incline into a deep sleeve. A stainless steel rod is connected to the first end of the pipe, and the signal line is connected to the second end. After the power system is turned on, the soil moisture data is automatically transmitted in real-time to the data acquisition system (TYQ300), and then promptly sent to the designated data center via a GPRS module (General Purpose Wireless Packet Transmitter).

[0074] In this invention, an inclined solar sensor bracket is fixedly installed above the solar sensor, and a solar sensor positioning plate and signal line are fixedly installed at the base below. The solar sensor positioning plate is connected to the angle design of the solar sensor (CSD3), which is combined with the solar sensor (CSD3) trench design and fixed by anchor bolts. An inclined PVC pipe is fixedly installed on the ground surface. The upper end of the PVC pipe is fixed to a pre-embedded connecting line, and its lower end extends downward at an incline to a deep sleeve. The first end is connected to a lead pipe, and the last end is connected to the signal line. After the power system is turned on, the solar data is automatically transmitted to the data acquisition system (TYQ300) in real time, and then promptly sent to the designated data center via the GPRS module (General Purpose Wireless Packet Transmitter).

[0075] In this invention, the temperature sensor (WZP1), soil moisture sensor, ground temperature sensor, rainfall sensor, and sunshine sensor are installed in relatively independent locations and connected by underground PVC pipes.

[0076] In this invention, the solar radiation sensor (CSD3) is equipped with an angle design. The angle design module adjusts the angle direction via a photosensor and a caster wheel to ensure it faces the sun directly. The angle is continuously designed by controlling the relative tilt angle between the solar radiation sensor and the sun. In conventional meteorological observations, solar radiation observation equipment is fixed and cannot be rotated in real-time for accurate angle adjustment, often resulting in inaccurate solar radiation data, especially in mountainous areas where data is highly inaccurate due to the obstruction of hills and trees. Conventional meteorological observations often require multiple manual measurements, which are still inaccurate. This invention solves the problem of inaccurate solar radiation observation.

[0077] In this invention, the data acquisition system (TYQ300) can also analyze and process meteorological data through the TM8 chip applet, predict abnormal meteorological disasters, and send signals to the GPRS module (General Wireless Packet Transmission Module) for timely alarm, thus serving agricultural production.

[0078] In this invention, the main body of the TM8 chip mini-program consists of three files: app.js, app.json, and app.wxss. When developing a mini-program project, a file system corresponding to the product can be established according to requirements, which is a typical file system. The images in the mini-program file system mainly store the images required for the project. Images should not be too large, as mini-programs have size limitations. During development, vector icons can be created as needed, or free, small-sized images can be downloaded from the internet. If the required images are large, they can be uploaded to the server, and then accessed via the URL provided by the server through the image component. app.json is mainly responsible for global configuration, project page composition, window appearance, page switching, and tab bar appearance. app.js is the mini-program script code, responsible for handling common event logic, defining global variables, encapsulating common methods, and handling the mini-program lifecycle. app.wxss is responsible for the common styles of the entire project. Each page can call style rules through component attributes, and common styles across different pages can utilize common style layouts, thereby simplifying project code and making style layouts clearer. Figure 4 ).

[0079] In this invention, the TM8 chip app also includes a microservice architecture (microservice system and database). The microservice architecture style consists of multiple small services. Each service runs in an independent process and uses lightweight interaction. In most cases, it is an HTTP resource API. These services have independent business capabilities and can be deployed independently through automated deployment methods. This style minimizes centralized management, allowing the use of various programming languages ​​and data storage technologies (…). Figure 5 For mobile applications like Android and iPhone, Java and Objective-C programming languages ​​and data storage technologies are used. For website development, JSP, ASP, and PHP languages ​​and data storage technologies such as MySQL, Oracle, and SQL Server relational databases are used. Example 1): A system (mini-program) is built by using a front-end page to receive and send data, HTML for design, CSS for styling, JavaScript for data loading, Java for back-end database operations, and MySQL for data storage. Example 2): For official website software development, AngularJS, Vue, and React are better suited for the front-end, while Java Spring and Hibernate are more suitable for the back-end. Example 3): Develop a microcontroller or embedded system. Requirements include a user-friendly interface, powerful functionality, and easy debugging.

[0080] The top-level architecture of the data acquisition system (TYQ300) mini-program system described in this invention is as follows: Figure 2 As shown, the architecture is divided into three layers: application layer, infrastructure, and basic infrastructure. Each layer connects via defined interface protocols, and internal development within each layer is independent. The application layer is based on the principle of data separation and adopts a unified REST API interface specification. Although there are many application layer systems, most can be merged based on interfaces. Furthermore, there may be existing interfaces available. However, the challenge lies in code separation and data separation. Each application layer should adopt a tenant identification method, which avoids redundant interface development and provides a good foundation for compilation and monitoring, enabling rapid identification of application providers. The infrastructure layer is based on the Spring Boot + MyBatis framework, incorporating a caching system. Business data is deeply analyzed, and basic data is separated from business data based on access volume and data format, minimizing data coupling. For interface services, the currently popular and concise REST API method is used for database read / write separation. The infrastructure layer supports physical servers, virtualized servers, etc. Its purpose is to reduce system coupling, increase system cohesion, and enable rapid system modifications and reinstatement when requirements change. The overall system architecture is very clear, facilitating detailed design, coding, maintenance, and adaptation to changing requirements. Layering defines the interfaces between layers, allowing for more standardized yet flexible interface descriptions, reducing coupling between layers, and enhancing module reusability, scalability, and maintainability. Simultaneously, layering also benefits project module division and task allocation; clear interfaces reduce integration difficulty and improve efficiency.

[0081] The functional structure of the data acquisition system (TYQ300) mini-program described in this invention is as follows: Figure 3As shown, the meteorological disaster early warning product includes time resolution: daily monitoring of various meteorological disaster indicators such as low temperature, high temperature, rainstorm, drought, and continuous rain. When a planting area reaches the warning indicators, a meteorological disaster early warning signal is issued in real time, and corresponding defense measures are provided to users. The meteorological disaster indicators are: continuous rain: daily precipitation ≥ 0.1 mm for 7 consecutive days; high temperature: daily maximum temperature ≥ 35.0℃ for 7 consecutive days or daily maximum temperature ≥ 37.0℃ for 3 consecutive days; rainstorm: daily precipitation ≥ 50 mm; drought: cumulative precipitation ≤ 10.0 mm for 20 consecutive days from late June to mid-September. Disease meteorological level forecasts include: red spot disease index weather forecasts, black shank disease index weather forecasts, mosaic disease index weather forecasts before and after topping, and bacterial wilt disease index weather forecasts. Yield and quality predictions provide regional quality prediction products for key growth stages of flue-cured tobacco in various planting areas. Its function is to display real-time weather conditions, weather forecasts, weather disaster warnings, points of interest (historical data query, regular weather forecasts, weather disaster warnings, pest and disease weather level forecasts, yield and quality predictions, transplanting period forecasts), disease weather level forecasts, yield and quality predictions, and transplanting period forecasts. After logging in, users can view real-time weather conditions, weather forecasts, the latest weather disaster warning products, transplanting period forecasts, disease weather level forecast products, and yield and quality prediction products based on their location.

[0082] The file structure and microservice architecture (microservice system and database) of the data acquisition system (TYQ300) mini-program described in this invention are as follows: Figure 4-5 As shown

[0083] An example of the microservice architecture of the data acquisition system (TYQ300) mini-program system described in this invention is as follows: Figure 6-7As shown, the entire system is broken down into several subsystems or microservices based on business logic. Each subsystem can deploy multiple applications, and load balancing is used between these applications. This requires a service registry center, Eureka. All services register with this registry center, and load balancing is achieved by applying certain strategies to the services registered in the registry center. Multiple Eureka instances can be deployed to ensure high availability. Multiple Eureka instances can be deployed for high availability. Services communicate using Feign and Hystrix circuit breakers to handle timeouts and errors during service calls, preventing system-wide failures due to issues in one service. A monitoring function is also needed to track the time spent on each service call, using Spring Cloud Config for unified configuration management, requiring consideration of integration with the company's configuration management platform. Hystrix acts as both a monitoring and circuit breaker; simply adding a Hystrix tag to the service interface enables monitoring and circuit breaker functionality. The Hystrix Dashboard provides a monitoring interface for tracking the time consumed by service calls across various services. Turbine aggregates monitoring information; unlike Hystrix which requires viewing monitoring data for each individual service instance, Turbine consolidates monitoring information from all service instances into a single, unified view, eliminating the need to access individual pages. Its effects include: breaking down product functions into several microservices; allowing a single function to create multiple microservices and deploy them across multiple server nodes for load balancing; designing an atomic service layer to streamline and extract core and common applications, which are then deployed as independent services to the core and common capability layer, gradually forming a stable service center that enables applications to respond more quickly to changing customer needs; designing API interfaces (RESTful) for each service; and categorizing different services, as different service types require different resources and can be configured with different resources, including CPU, memory, and storage.

[0084] The data acquisition system (TYQ300) mini-program system described in this invention consists of two parts: an interface server and a service terminal. The interface server is based on a standardized interface standard system using RESTful within the Spring Boot framework. The service terminal is based on a client / server architecture interaction method using the WeChat platform on either a computer or mobile device, enabling efficient operation and data transmission of the mini-program. The top-level architecture of the interface server (…) Figure 2The process involves a newly measured database, linked via a key framework for database web-based architecture. To achieve data access interface standardization, the business database is published as a REST API. Spring Boot allows for rapid construction of web-based database access, and its integration with Mybatis further leverages Mybatis' rich query features, making the API functionality more complete. The linking process involves transferring data from the newly measured database to the API and then to the new application layer. The data in the new application layer is separated from the original application environment and system data, and then compiled. The service terminal is implemented through a logic layer and a view layer. The logic layer uses JavaScript to implement the mini-program's logic behavior, while the view layer is edited using WXML (WeiXinMark Language) and WXSS (Wei Xin Style Sheet) languages ​​provided by the computer's official documentation. The interaction between the view layer and the logic layer is completed through data transmission and an event system. The MINA framework not only provides a development foundation for mini-program development but also manages the routing of all pages in the mini-program and assigns page lifecycles. The framework maintains the current page in a stack-like manner, and when a page switches routes, the page stack exhibits stack and push behavior. Each page's lifecycle typically begins with `onLoad` and ends with `onUnload`. Within this lifecycle, page rendering, function calls, and data updates can be performed. In addition, the MINA framework provides mini-programs with a rich set of components, unique style sheets, and native APIs. Components are the basic building blocks of the web; by combining different components and using matching style sheets, various mini-programs can be developed. The APIs enable functions such as data storage, page routing, and network requests.

[0085] In this invention, a climate suitability crop growth curve is plotted with time (in months and / or days) on the x-axis and the climate suitability index (CFI) on the y-axis. Based on the relationship between time and the CFI in the growth curve, the appropriate time for crop planting is selected. The CFI integrates information such as temperature (weather), rainfall, soil temperature, and soil moisture. A CFI greater than 80 and soil moisture greater than 90% is suitable for tobacco sowing. A CFI greater than 85% and temperature greater than 12°C is suitable for tobacco transplanting. A CFI greater than 78% and soil moisture less than 70% is suitable for harvesting mature tobacco leaves.

[0086] Furthermore, based on the climate suitability growth curves obtained from various regions, and considering the different climate requirements of various crops, it is possible to determine the crops suitable for planting in different areas. For example, using the technical solution provided by this invention to test the climate suitability index of flue gas in Xiangxi Prefecture (Huayuan County, Yongshun County, Fenghuang County, Longshan County, Baojing County, Guzhang County, and Luxi County), the climate suitability index of the tobacco-growing areas in Xiangxi Prefecture ranges from 77.60 to 93.79. The climate suitability index of the tobacco-growing areas in Xiangxi Prefecture is relatively high, making it the most suitable and appropriate area for flue-cured tobacco planting. Further precise determination: based on the requirements for tobacco leaf planting and the results of the Climate Suitability Index (CFI), the ranking is as follows: Huayuan County > Yongshun County > Fenghuang County > Longshan County > Baojing County > Guzhang County > Luxi County.

[0087] Environmental factors are the leading cause of crop diseases. Accurately detecting various environmental conditions can help prevent crop diseases in a timely manner. Furthermore, monitoring environmental meteorological factors allows for timely assessment of crop disease status, enabling prompt pest and disease control and maximizing the economic value of the crop. The technical solution provided in this invention can also calculate the likelihood and severity of crop diseases by detecting environmental meteorological factors.

[0088] For red spot disease, the disease severity index (Y1) is calculated by monitoring the minimum and maximum temperatures and sunshine duration of the crop. When the Y1 is less than 0.16%, the crop is currently free of the disease. A Y1 of 0.16% or higher indicates the onset of red spot disease, requiring immediate preventative measures (using commonly available preventative agents). A Y1 greater than 3.36% indicates severe red spot disease, necessitating spraying or application of antiviral agents to kill the virus.

[0089] For black shank disease, the disease severity index (Y2) is calculated by monitoring the minimum and maximum temperatures, sunshine duration, average rainfall, and number of rainy days at the crop's location. A Y2 score less than 0.16% indicates the crop is currently free of black shank disease. A score of 0.16% or higher indicates the onset of black shank disease, requiring immediate preventative measures (using commonly available black shank disease preventative agents). A Y2 score greater than 5% indicates severe black shank disease, requiring spraying or application of anti-black shank agents to kill the virus.

[0090] For mosaic virus, the disease severity index (Y3) is calculated by detecting the lowest temperature at which the crop is located and the average soil moisture. When the Y3 is less than 0.16%, the crop is currently free of mosaic virus. A Y3 of 0.16% or higher indicates the onset of mosaic virus and requires immediate preventative measures (using commonly available mosaic virus preventative agents). When the Y3 is greater than 8.5%, the mosaic virus is severe and requires spraying or applying insecticides to kill the virus.

[0091] Compared with the prior art, the beneficial technical effects of the present invention are as follows:

[0092] 1. Solve the following key technical problems in tobacco production in mountainous areas: (1) Clarify the temperature index of the tobacco transplanting period, propose the climate suitability index of the transplanting period based on the combination of elements such as temperature, precipitation, sunshine, and soil moisture, and propose the optimal transplanting period for major varieties; (2) Utilize field microclimate observation data and data on tobacco agronomic traits and yield and quality, adopt mathematical statistics methods and crop models, construct a relationship model between climate factors and flue-cured tobacco appearance quality, physical properties and chemical composition, reveal the influence of meteorological conditions in different climate ecological zones on major varieties, and improve the key meteorological technologies for improving yield and quality; (3) Develop a meteorological decision-making service system based on meteorological big data, including six modules: data query, agricultural weather forecast, meteorological disaster early warning, flue-cured tobacco yield and quality prediction, meteorological level forecast of major diseases and meteorological forecast of fertilizer application, to provide decision-making basis for tobacco management personnel at all levels; (4) Be able to predict abnormal meteorological disasters, send signals to the GPRS module (general wireless packet transmission module) for timely alarm, and serve agricultural production. (5) It can predict crop diseases and send signals to the GPRS module (general wireless packet transmission module) to provide early warning and serve agricultural production.

[0093] 2. This invention allows for historical data retrieval, enabling the selection of crop planting plots and transplanting periods, thereby reducing crop disease losses and losses from meteorological disasters such as hail, heavy rain, and drought. It also provides forecasts of regional average temperature, maximum temperature, minimum temperature, precipitation, and ground temperature for the current period and the next week, offering scientific and easy-to-operate methods for field management operations such as crop transplanting, fertilization, and hilling, thus reducing costs and increasing efficiency.

[0094] 3. This invention enables early warning of meteorological disasters, reducing crop losses due to meteorological disasters. It also enables forecasting of disease weather levels, further reducing losses from disease-related disasters.

[0095] 4. This invention enables yield and quality prediction, thereby optimizing the transplanting period, fully utilizing climatic resources such as temperature, sunlight, and precipitation, and improving crop yield and quality. It allows for transplanting period forecasting, enabling the selection of the optimal transplanting period for any small region, thus solving the problem of reduced yield and quality in a single transplanting period within a county or township, and improving tobacco yield and quality.

[0096] 5. This invention enables interactive information updates and adjustments for different crops, climate years, altitudes, and regions, ensuring stable crop yields and value preservation. Attached Figure Description

[0097] Figure 1 This is a schematic diagram of the structure of an automatic meteorological data acquisition system for mountainous fields according to the present invention.

[0098] Figure 2 This is a top-level architecture diagram of the climate suitability evaluation based on the automatic meteorological data acquisition system in mountainous fields of this invention.

[0099] Figure 3 This is a functional structure diagram of the climate suitability evaluation based on the automatic meteorological data acquisition system in mountainous fields of the present invention.

[0100] Figure 4 This is a file structure diagram of the climate suitability evaluation based on the automatic meteorological data acquisition system in mountainous fields, as described in this invention.

[0101] Figure 5 This is a diagram of the microservice architecture (microservice system and database) of the climate suitability evaluation based on the automatic meteorological data acquisition system in mountainous fields of this invention.

[0102] Figure 6 This is an example of the microservice architecture for climate suitability assessment based on an automatic meteorological data acquisition system for mountainous fields, as described in this invention. Figure 1 .

[0103] Figure 7 This is an example of the microservice architecture for climate suitability assessment based on an automatic meteorological data acquisition system for mountainous fields, as described in this invention. Figure 2 .

[0104] Figure 8 This diagram shows the fitting effect of the model on the relationship between the development speed of red spot disease and meteorological factors when using the automatic meteorological data acquisition system for mountainous fields of the present invention to provide early warning of red spot disease.

[0105] Figure 9 This diagram shows the fitting effect of the model on the relationship between the development speed of black shank and meteorological factors when using the automatic meteorological data acquisition system for mountainous fields of the present invention to provide early warning of black shank.

[0106] Figure 10This diagram shows the fitting effect of the model on the relationship between the development speed of mosaic disease and meteorological factors when using the automatic meteorological data acquisition system for mountainous fields of the present invention to provide early warning of mosaic disease.

[0107] Reference numerals: 1: Data acquisition system; 101: Rainfall measuring device; 102: Light measuring device; 103: Air temperature measuring device; 104: Soil moisture measuring device; 105: Soil temperature measuring device; 2: Data receiving device; 3: Data transmitting device; 4: Battery; 5: Data processing device; 6: Alarm device. Detailed Implementation

[0108] The technical solution of the present invention will be illustrated below with examples. The scope of protection sought by the present invention includes, but is not limited to, the following embodiments.

[0109] Example 1

[0110] like Figure 1 As shown, an automatic meteorological data acquisition system for mountainous fields includes a data acquisition system 1, a data receiving device 2, and a data transmitting device 3. The data acquisition system 1 includes a rainfall meter 101, a light intensity meter 102, an air temperature meter 103, a soil moisture meter 104, and a soil temperature meter 105. All four meters are connected to the data receiving device 2. The data receiving device 2 is connected to the data transmitting device 3. All three devices—data acquisition system 1, data receiving device 2, and data transmitting device 3—are connected to a battery 4.

[0111] Example 2

[0112] The system repeats Embodiment 1, except that it further includes a data processing device 5. The data processing device 5 is connected to the data transmitting device 3. The data processing device 5 includes a digital input module, an analog input module, a digital-to-analog converter, a digital output module, an analog comparator, an analog output module, logic gates, an application program, and a microprocessor.

[0113] Example 3

[0114] Repeating Embodiment 2, the system further includes an alarm device 6. The alarm device 6 is connected to the data processing device 5. The alarm device 6 includes a terminal module, an alarm, and a communication module; the communication module includes a digital communication system and an analog communication system.

[0115] Example 4

[0116] Repeat Example 3, except that the data processing device 5 includes:

[0117] Data access service layer: composed of multiple gateways forming a dynamic Nginx load balancer, connected to data sending device 3;

[0118] Data Analysis Service Layer: Utilizes a Spark cluster to perform statistical analysis on the data imported from the data access service layer.

[0119] Data storage service layer: Adopting the Hadoop architecture, it stores meteorological data parsed by the data analysis service layer and stores the results of data analysis in a distributed caching system and a relational database;

[0120] Data application service layer: It calls data from the data storage service layer through the REST API interface, realizes interaction with the web server, distributed caching system and storage system, and is connected to alarm device 6.

[0121] Example 5

[0122] A method for climate suitability assessment using the automatic meteorological data acquisition system for mountainous fields described in Example 4, the method comprising the following steps:

[0123] 1) Meteorological element data detection: Rainfall meter (101) detects the daily precipitation at the crop location, light meter (102) detects the sunshine duration at the crop location, air temperature meter (103) detects the daily average temperature, maximum temperature and minimum temperature at the crop location, soil moisture meter (104) detects the daily average soil moisture at the crop location, and soil temperature meter (105) detects the daily average soil temperature at the crop location.

[0124] 2) Meteorological element data processing: The multivariate regression residual Gaussian operator correction method (MRG) was used to interpolate the daily average temperature, maximum temperature, minimum temperature, sunshine duration, daily average soil humidity, and daily average soil temperature; the ordinary kriging method (KRG) was selected to interpolate the daily precipitation.

[0125] 3) Based on the results of step 2), conduct a climate suitability assessment of the crop location.

[0126] Example 6

[0127] Repeat Example 5, except that step 3) uses a fuzzy mathematical model for climate suitability evaluation. Specifically, this involves using a membership function to represent the classification criteria of meteorological elements and their impact on crops, and employing a membership function model and an index sum method to analyze the climate suitability of the crop location. The climate suitability index (CFI) is:

[0128]

[0129] Wherein: the proposed crop planting area is divided into m regions, j∈[1,m]; meteorological element data is detected for each region, and the meteorological element data detection for each region includes i meteorological elements, i∈[precipitation, sunshine duration, daily average temperature, daily maximum temperature, daily minimum temperature, daily average soil humidity, daily average soil temperature]; N ij W represents the membership value of the j-th tobacco region and the i-th climate index; ij Let N and N represent the weighting coefficients of the j-th tobacco region and the i-th climate index, respectively, where 0 < N. ij ≦1, 0<W ij ≦1, and satisfy

[0130] Example 7

[0131] Repeat Example 6, but plot the climate suitability crop growth curve with time on the x-axis and the climate suitability index (CFI) on the y-axis. Based on the time-climate relationship in the climate suitability crop growth curve, select the appropriate time for crop planting.

[0132] Among them, the growth curve of crops in climate-suitable environments includes parabolic, S-shaped, or inverse S-shaped curve relationships. Crop planting stages include the root elongation stage, transplanting stage, vigorous growth stage, and maturity stage.

[0133] Example 8

[0134] A method for crop disease early warning using the automatic meteorological data acquisition system for mountainous fields described in Example 4, the method comprising the following steps:

[0135] 1) Meteorological element data detection: Rainfall meter (101) detects the daily precipitation at the crop location, light meter (102) detects the sunshine duration at the crop location, air temperature meter (103) detects the daily average temperature, maximum temperature and minimum temperature at the crop location, soil moisture meter (104) detects the daily average soil moisture at the crop location, and soil temperature meter (105) detects the daily average soil temperature at the crop location.

[0136] 2) Based on the meteorological data obtained from the detection, early warnings are issued for possible crop diseases.

[0137] Example 9

[0138] Example 8 is repeated, except that the disease warning is for red spot disease. Specifically, the red spot disease severity index (Y1) is used as the dependent variable, and relevant meteorological factors and the previous year's red spot disease severity index (Y1') are used as independent variables to calculate the probability of the crop contracting red spot disease during the observation period.

[0139] Y1=(2.7894-0.1674SSH-0.5382TM)Y1'-(0.05154Tm)Y1' 2 -0.0052;

[0140] Where: Tm is the lowest temperature during the observation period, TM is the highest temperature during the observation period, and SSH is the sunshine duration during the observation period.

[0141] Example 10

[0142] Example 8 is repeated, except that the disease warning is for black shank disease. Specifically, the black shank disease severity index (Y2) is used as the dependent variable, and relevant meteorological factors and the previous year's black shank disease severity index (Y2') are used as independent variables to calculate the probability of the crop contracting black shank disease during the observation period.

[0143] Y2=(1.5195+0.0748R)Y2'-(0.0051+0.0007R)Y2' 2 -1.1548Rd-6.5428TM+1.1065SSH+9.5955;

[0144] Where: Tm is the lowest temperature during the observation period, TM is the highest temperature during the observation period, SSH is the sunshine duration during the observation period, R is the rainfall during the observation period, and Rd is the number of rainy days during the observation period.

[0145] Example 11

[0146] Example 8 is repeated, except that the disease warning is for mosaic virus. Specifically, the mosaic virus disease index (Y3) is used as the dependent variable, and relevant meteorological factors and the mosaic virus disease index of the previous year (Y3') are used as independent variables to calculate the probability of the crop contracting mosaic virus during the observation period.

[0147] Y3=1.1148TM×Y3'-0.0316RH×Y3' 2 +0.3013;

[0148] Where: TM is the highest temperature during the observation period, and RH is the average soil humidity during the observation period.

[0149] Example 12

[0150] An automatic meteorological data acquisition system for mountainous fields, as described in Example 4, is used for monitoring flue-cured tobacco planting, determining the transplanting period of flue-cured tobacco, and preventing diseases during the planting period.

[0151] Application Example 1

[0152] The automatic meteorological data acquisition system for mountainous fields according to this invention was used to monitor the meteorological data in Daoer Village, Huayuan Town, Huayuan County in real time. The data is shown in Table 1.

[0153]

[0154] Application Example 2

[0155] The automatic meteorological data acquisition system for mountainous fields of the present invention is used to collect and analyze meteorological factors of flue gas in Xiangxi Prefecture.

[0156] Based on the measured data, the daily average temperature, maximum temperature, minimum temperature, and sunshine duration are interpolated using the multiple regression residual Gaussian operator correction method (MRG). The specific steps are as follows: First, a multiple regression model is established using ground meteorological observation data, station latitude and longitude, and altitude, and the residuals are calculated. Then, the residuals are corrected using the inverse distance Gaussian operator method (IDWG). The final values ​​for the grid points are obtained using the following formula:

[0157]

[0158] In the formula, T ij b is the value of the grid point feature to be interpolated; b0 is the constant term; b k x is the coefficient of the k-th influence factor; k For k influencing factor values; e ij This represents the residual value to be inserted.

[0159] Similarly, the Kriging method (KRG) is chosen to interpolate daily precipitation. Kriging interpolation is also known as the spatial autocovariance optimal interpolation method. The ordinary Kriging interpolation (KRG) calculation formula is as follows:

[0160]

[0161] In the formula, z(t) ij Z(t) represents the raster point feature value to be interpolated; n represents the number of stations referenced to the interpolation point; Z(t) represents the raster point feature value to be interpolated. k λ represents the feature value of the k-th point; k is the k-th interpolation point that is referenced. k These are the weighting coefficients, and their sum equals 1.

[0162] In calculating the weighting coefficient λ k Two conditions must be met: first, z(t) must be satisfied. ij The estimate of z(t) is unbiased, meaning the expected value of the bias is zero; secondly, it is optimal, even if the estimated value z(t) is... ij ) and the true value z(t) ij ) trueThe sum of squares of the differences is minimized. Therefore, ordinary Kriging (KRG) is often called a locally optimal linear unbiased estimator.

[0163] Application Example 3

[0164] The climate suitability assessment of flue gas in Xiangxi Prefecture was conducted using an automatic meteorological data acquisition system for mountainous fields according to the present invention.

[0165] Introducing fuzzy mathematics into climate suitability assessment, this invention uses membership functions to represent the classification criteria of a meteorological element and its impact on flue-cured tobacco. Based on this, fuzzy comprehensive evaluation is performed, which effectively addresses the fuzzy concept of flue-cured tobacco climate suitability assessment. This invention uses a membership function model and the index sum method to analyze the climate suitability of the main tobacco-growing area in Xiangxi Prefecture. There are m tobacco-growing areas (m = 1…j), and each area has n climate indicators (n = 1…i). Nij and Wij represent the membership value and weight coefficient of the j-th tobacco-growing area and the ith climate indicator, respectively, where 0 ∠Nij ij ≦1,0∠W ij ≦1, and satisfy The climate feasibility index for each tobacco-growing region can then be expressed as:

[0166] Because the dimensions and optimal value ranges of various climate indicators are inconsistent, fuzzy mathematics theory is used to calculate the membership degree of each climate indicator, converting the original data of each climate indicator into values ​​of 0.1 to 1 to eliminate the influence of dimensions. There are three main types of membership function relationships in fuzzy mathematics: parabolic relationship, S-curve relationship, and inverse S-curve relationship. Factors exhibiting a parabolic relationship have an optimal suitable range for tobacco growth and development; beyond this range, the greater the deviation, the more detrimental the impact on tobacco growth and development. Factors exhibiting an S-curve relationship are positively correlated with tobacco yield and quality within a certain range; factors exhibiting an inverse S-curve relationship are negatively correlated with tobacco yield and quality within a certain range. For ease of calculation, the parabola can be approximated as a trapezoidal distribution, the S-curve as an ascending semi-trapezoidal shape, and the inverse S-curve as a descending semi-trapezoidal shape. Based on the relationship between flue-cured tobacco growth and climatic factors, the suitability models for the various indicators in the flue-cured tobacco climate suitability index system are as follows: average temperature during the root extension period, average temperature during the vigorous growth period, average temperature during the maturity period, precipitation during the root extension period, precipitation during the vigorous growth period, precipitation during the maturity period, and relative humidity in the field are parabolic models; sunshine hours in the field are S-shaped. The types and inflection point values ​​of each membership function curve are shown in Table 2. The expression for the parabolic function is: The expression for the S-shaped function is: In the formula, x is the actual value of the meteorological element index of each tobacco-growing area, and x1, x2, x3, and x4 represent the lower critical value, upper critical value, lower limit of the optimal value, and upper limit of the optimal value of the meteorological element index of each tobacco-growing area, respectively.

[0167] In the evaluation of tobacco climate suitability, the contributions of each evaluation indicator to suitability vary, resulting in different relative importance. Therefore, it is necessary to use appropriate methods to determine their weights. This invention employs the Analytic Hierarchy Process (AHP) to determine the weights of each evaluation indicator. When applying the AHP method to analyze decision-making problems, the problem must first be organized and hierarchically structured to construct a hierarchical model. This invention uses climate suitability as the target layer, heat conditions, rainfall conditions, light conditions, and relative humidity affecting flue-cured tobacco growth as the criterion layer, and meteorological factors included in meteorological factors as the indicator layer. Through constructing a judgment matrix, hierarchical single ranking, and consistency testing, the combined weights shown in Table 2 are calculated using DPS11.0 statistical software. It is concluded that a daily average temperature exceeding 12℃ is an important meteorological indicator for tobacco to transition from seedling to field growth. In the Xiangxi tobacco region, the earliest exceeding 12℃ mostly occurs in the late early March, while the latest exceeding 12℃ is generally consistent, between April 14th and 15th, with a difference of 38-50 days. The average date for exceeding 12℃ is around March 27th. An 80% success rate is generally achieved by the end of March. Based on the climate characteristics of the Xiangxi tobacco-growing area, transplanting at low altitudes can be scheduled for the end of March, while in areas using plastic film mulching, it can be appropriately advanced to the early part of late March. However, in high-altitude areas, it should be appropriately delayed. The abundant sunshine hours and gradually decreasing rainfall in July, August, and September are conducive to the ripening of flue-cured tobacco.

[0168] Table 2. Inflection Points and Weights of Climate Indicators

[0169]

[0170] Application Example 4

[0171] The present invention provides an automatic meteorological data acquisition system for mountainous fields, which collects relevant meteorological data and develops a flue-cured tobacco decision-making service system (APP) to realize the intelligent release of products such as meteorological warnings and disease warnings and forecasts.

[0172] The evaluation method of this invention utilizes fuzzy mathematics to evaluate the climate suitability of the tobacco-growing areas in Xiangxi Prefecture. Three years of data and analysis show that the climate suitability index of the tobacco-growing areas in Xiangxi Prefecture ranges from 77.60 to 93.79, with the counties ranked as follows: Huayuan County > Yongshun County > Fenghuang County > Longshan County > Baojing County > Guzhang County > Luxi County. The climate suitability index for flue-cured tobacco shows a decreasing trend from southeast to west and north. The high climate suitability index of the tobacco-growing areas in Xiangxi Prefecture indicates that it is the most suitable and appropriate area for flue-cured tobacco cultivation. The sunlight, temperature, and rainfall in the tobacco-growing areas are well-matched with the growth requirements of high-quality tobacco, making it suitable for the production of high-quality flue-cured tobacco.

[0173] Application Example 5

[0174] Red Star Disease Warning

[0175] The severity index and progression rate of red star disease after onset are most strongly correlated with temperature and sunshine duration; they also show some correlation with humidity and rainy days. Using the severity index (Y1) as the dependent variable, all relevant meteorological factors, the product of each meteorological factor and the previous severity index (Y'), and the square of the previous severity index (Y1') are considered. 2 The product of the values ​​of Y1 and Y2 was used as the independent variable for forward stepwise regression to screen factors and rank their importance. The results showed that the disease index Y1 was most significantly correlated with the previous disease index Y1', followed by Tm*Y', SSH*Y', and TM*Y', where Tm is the lowest temperature within the observation period (5 days), TM is the highest temperature, and SSH is the sunshine duration. The results of the relationship model constructed using multiple regression are as follows:

[0176] Y=(2.7894-0.1674SSH-0.5382TM)Y′-(0.05154Tm)Y′ 2 -0.0052

[0177] Model determination coefficient R 2 The value was 0.9391, with 108 degrees of freedom, and passed the 0.05 significance test, indicating high accuracy. Sunlight and temperature are the main meteorological factors affecting the development of red spot disease. Higher temperatures and more sunlight inhibit the development of red spot disease and delay the warning time. Warnings are issued when the disease index reaches the level that harms crops (generally 0.5-1). The accuracy rate of warnings in mountainous areas reaches about 80%, with a 20% probability of a one-day error (delay or advancement). This method can be used in non-mountainous areas, but the accuracy will be even higher due to the absence of mountain microclimate influences. Experimental results are as follows... Figure 8 As shown.

[0178] Application Example 6

[0179] Black shin disease warning

[0180] The severity index of black shank disease showed the strongest correlation with temperature, humidity, and sunshine after onset, followed by precipitation and rainy days.

[0181] Table 3 shows the correlation between the outbreak rate of black shank and meteorological factors (dimensionless) during this period.

[0182]

[0183] *Y represents the current disease index, Y' represents the disease index 5 days ago, and ΔY represents Y-Y'. ** and * indicate that the correlation coefficients passed the significance tests at 0.01 and 0.05, respectively.

[0184] Forward stepwise regression was performed to screen factors and rank their importance. The results showed that the black shank disease index was most significantly correlated with the earlier disease index Y', followed by R*Y', R*Y', and R*Y'. 2 Rd, TM, and SSH (the letters represent meteorological factors as shown in Table 7.5). The results of the multiple regression are as follows:

[0185] Y=(1.5195+0.0748R)Y′-(0.0051+0.0007R)Y′ 2 -1.1548RD-6.5428TM+1.1065SSH+9.5955

[0186] The model has a coefficient of determination of 0.9908 and 176 degrees of freedom, passing the significance test and showing good fit. This indicates that precipitation, sunshine, and temperature are the main meteorological factors affecting the development of black shank disease. More rainy days with less rainfall, higher temperatures, and less sunshine inhibit the development of black shank. Early warning is initiated when the disease index reaches the level that damages crops (generally 0.5-1). The accuracy rate of early warnings in mountainous areas reaches approximately 80%, with a 20% probability of error of one day (delay or advancement). This method can be used in non-mountainous areas, but the accuracy rate will be even higher due to the absence of mountain microclimate influences. Experimental results are as follows... Figure 9 As shown.

[0187] Application Example 7

[0188] Mosaic Disease Warning

[0189] The disease index of tobacco mosaic virus before topping is most strongly correlated with temperature and humidity, followed by rainy days.

[0190] Table 4 shows the correlation between the outbreak rate of mosaic virus before topping and meteorological factors (dimensionless) during this period.

[0191]

[0192] *Y represents the current disease index, Y' represents the disease index 5 days ago, and ΔY represents Y-Y'. ** and * indicate that the correlation coefficients passed the significance tests at 0.01 and 0.05, respectively.

[0193] Forward stepwise regression was performed to screen factors and rank their importance. The results showed that the disease index before topping of mosaic virus was most significantly correlated with TMY', followed by RH*Y'. 2 (The letters represent the meteorological factors as shown in the table above). The results of the multiple regression are as follows:

[0194] Y=1.1148TM×Y′-0.0316RH×Y′-+0.3013

[0195] The model has a coefficient of determination of 0.9577 and 79 degrees of freedom, passing the significance test and showing good fit. This indicates that precipitation and humidity are the main meteorological factors affecting the disease development rate; low temperature and high humidity inhibit the development of mosaic virus in flue-cured tobacco before topping. Early warning is initiated when the disease index reaches the level that harms the crop (generally 0.5-1). The accuracy rate of early warning in mountainous areas reaches approximately 80%, with a 20% probability of a one-day error (delay or advancement). This method can be used in non-mountainous areas, but the accuracy rate will be even higher due to the absence of mountain microclimate influences. Experimental results are as follows... Figure 10 As shown.

Claims

1. A method for crop disease early warning by using mountain field meteorological data automatic acquisition system, the system comprising a data acquisition system (1), a data receiving device (2), and a data sending device (3); wherein: The data acquisition system (1) includes a rainfall meter (101), a light meter (102), an air temperature meter (103), a soil moisture meter (104), and a soil temperature meter (105); the rainfall meter (101), light meter (102), air temperature meter (103), soil moisture meter (104), and soil temperature meter (105) are all connected to the data receiving device (2), and the data receiving device (2) is connected to the data transmitting device (3); the data acquisition system (1), the data receiving device (2), and the data transmitting device (3) are all connected to the battery (4); the crop is flue-cured tobacco; The method includes the following steps: 1) Meteorological element data detection: Rainfall meter (101) detects the daily precipitation at the crop location, light meter (102) detects the sunshine duration at the crop location, air temperature meter (103) detects the daily average temperature, maximum temperature and minimum temperature at the crop location, soil moisture meter (104) detects the daily average soil moisture at the crop location, and soil temperature meter (105) detects the daily average soil temperature at the crop location. 2) Based on the meteorological data obtained from the monitoring, early warnings are issued regarding potential crop diseases; The disease warning mentioned is for red spot disease, which specifically involves: using the red spot disease severity index Y1 as the dependent variable, and relevant meteorological factors and the previous year's red spot disease severity index Y1' as independent variables, to calculate the probability of the crop contracting red spot disease during the observation period. ； Where: Tm is the lowest temperature during the observation period, TM is the highest temperature during the observation period, and SSH is the sunshine duration during the observation period; when the red star disease severity index Y1 is greater than 0.16%, it indicates that red star disease has begun to occur; when the red star disease severity index Y1 is greater than 3.36%, it indicates that red star disease is severe. or The disease warning mentioned is for black shank disease, specifically: using the black shank disease severity index Y2 as the dependent variable, and relevant meteorological factors and the previous year's black shank disease severity index Y2' as independent variables, the probability of the crop contracting black shank disease during the observation period is calculated. ； Where: TM is the highest temperature during the observation period, SSH is the sunshine duration during the observation period, R is the rainfall during the observation period, and Rd is the number of rainy days during the observation period; when the black shank disease index Y2 is greater than 0.16%, it indicates that black shank disease has begun to occur; when the black shank disease index Y2 is greater than 5%, it indicates that black shank disease is severe. or The disease warning mentioned is for mosaic virus, which specifically involves: using the mosaic virus disease index Y3 as the dependent variable, and relevant meteorological factors and the previous year's mosaic virus disease index Y3' as independent variables, to calculate the probability of the crop contracting mosaic virus during the observation period. ； Where: TM is the highest temperature during the observation period, and RH is the average soil moisture during the observation period; when the mosaic disease severity index Y3 is greater than 0.16%, it indicates that mosaic disease has begun to occur; when the mosaic disease severity index Y3 is greater than 8.5%, it indicates that mosaic disease is severe.

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