Development of yield prediction system based on real-time agricultural meteorological information

This paper contains about the research and the building of an effective agricultural yield forecasting system based on real-time monthly weather. It is difficult to predict the agricultural crop production because of the abnormal weather that happens every year and rapid regional climate change due to global warming. The development of agricultural yield forecasting system that leverages real-time weather information is urgently required. In this research, we cover how to process the number of weather data(monthly, daily) and how to configure the prediction system. We establish a non-parametric statistical model on the basis of 33 years of agricultural weather information. According to the implemented model, we predict final production using the monthly weather information. This paper contains the results of the simulation.