Design and Application of crop Variety Recommendation and Production Decision System in Agricultural Production

Given the problems existing in the application of agricultural resources data, such as scattered datum resources, low degree of sharing, poor pertinence of technical guidance, low efficiency, and so on, this study designed a crop Variety Recommendation and Production Decision System based on GIS technology, multi-source database, and knowledge model, and preliminarily realized the sharing and visual analysis of meteorological environment, soil fertility and other agricultural resources data. The system adopts the REST framework to discover the front and back separation framework. Deep data mining builds expert knowledge rules for crop production technology management based on factors such as historical meteorological data, soil data, and crop variety suitability. They rely on spatial statistical analysis, time series data analysis, multi-source data fusion, and related crop knowledge model technology. It realizes application services such as various recommendations, post-disaster emergency guidance, production management decision-making, etc. The system was popularized and applied in Yuanyang County, Xinxiang City, in July 2021. According to the flood disaster on July 20 and the Internet weather forecast for seven days after the disaster, the system provides growers with replanted crops and varieties. Technical services are provided to reduce post-disaster economic losses and guide agricultural water-saving, fertilizer-saving, and other production applications.