Design And Implementation Of Heavy Metal Pollution Mechanism Analysis Platform For Agricultural Products

The quality of agricultural products is directly related to the health of the people.The study of the mechanism of heavy metal pollution in agricultural products has also become an important issue.However,because the relationship between pollution sources and polluting receptors is not obvious,there is a complex relationship between them.The analysis of agricultural pollution through agricultural and chemical methods is a high-cost work in both human and material resources.At present,there are not many researches and corresponding results on the analysis of pollution of agricultural products through computer technology,and most of them stay at the level of standard and qualitative analysis.In view of the above problems,this paper aims to develop a set of heavy metal pollution mechanism analysis platform for agricultural products.Through rich text parsing technology,data mining technology,parallel computing model and text data indexing technology,the functional design of five major modules: source file processing,resource management and retrieval,pollution judgment and mechanism analysis,personalized algorithm extension and user information management are completed.And implementation.Through the knowledge of computer data mining,the quantitative analysis of agricultural product pollution is solved,and the potential relationship between pollution sources and pollution receptors is demonstrated by Echarts visualization technology,and the research cost in the traditional way is also greatly reduced.This paper uses machine learning methods and parallelizes computational engineering to provide data analysis results more quickly.The platform uses the MVC architecture as a whole,and completes the construction of the Web platform through Spring,Mybatis,and SpringMVC.According to the platform test results,the platform implemented in this paper meets the design requirements.The platform interface is simple and easy to understand,and the command rules are clear,so that researchers engaged in agricultural related work can easily use the platform to complete related work,which has greatly facilitated the analysis of data,and has certain practical value and utilization value.