| In response to the demand for production management of spring soybean sowing in cold regions,in order to improve the timeliness and accuracy of determining the sowing date of spring soybean,Io T technology is used to design a farmland environmental information collection system,supporting cloud service platform,and sowing date decision-making function module based on cold climate conditions.This provides a basis for real-time monitoring of large-scale farmland environmental information,determining crop sowing dates,and formulating agricultural production plans,Providing decision-making suggestions for intelligent management of production processes is of great significance.The main content and results of the study can be summarized as follows:(1)Construction of a knowledge model for determining the sowing date of spring soybeans.Utilizing drones to obtain farmland image information from the experimental site,strictly following the principles of monitoring point layout and combining with terrain image features,the placement and distribution of monitoring nodes were designed,integrating farmland environment and variety information,providing important decision-making parameters for model construction.Analyze the factors affecting the sowing date,combine with the agronomic requirements related to the cultivation and management of spring soybean in cold regions,convert conceptual indicators into parameterized mathematical functions,use JAVA as the main programming language,establish an executable prototype system,and complete the construction of a model for determining the sowing date of spring soybean.(2)Design of a farmland soil environment information collection system.Smart agriculture cloud platform management system design and function implementation.A set of soil environment information collection system was designed by using wireless sensor network technology,single-chip technology,cloud database and other technologies.The overall design plan of the system mainly includes analysis of system functional requirements,design ideas,and operational processes.The hardware design of the system involves selecting and designing information collection modules,wireless communication modules,and various sensors.The system software design is based on the requirements for collecting parameters.The microcontroller is programmed for collection,control,and transmission,and the wireless communication module is used for data transmission function testing.Realize real-time monitoring of agricultural crop growth environment parameter information,providing data support for the implementation of cloud platform module functions and sowing date decision-making.(3)Design and function implementation of the intelligent agricultural cloud platform management system.Starting from the functional and performance requirements of the cloud platform system,the system construction architecture,main functional modules,and database have been designed in sequence;From the perspective of user usage and needs,the cloud platform system login interface,user monitoring interface,and broadcast decision module have been designed and implemented with corresponding functions.It can provide important functional display cloud for monitoring data and scheduling decisions.(4)Experimental design and validation of the knowledge model application for determining broadcast dates.Using the sowing date decision system,experiments were conducted on experimental fields in the Jiusan Reclamation Area of Heilongjiang Province.A pre sowing meteorological and soil data measurement plan was developed,and the decision data was processed to analyze the trend of daily average soil temperature and humidity changes before sowing.The application of the sowing date model in the experimental site was verified,and the results showed that the output results of the sowing date decision model showed good consistency with the high-yield cultivation mode of spring soybean in cold regions in the past two years,This demonstrates the rationality of the model design and indicator selection,and has good applicability and decision-making ability for determining the sowing date of spring soybeans in cold regions. |
