On the basis of adequate understanding the significance of virtual crops research, according to the research state and characteristics of virtual crops’ typical modeling methods at home and abroad, a new modeling thoughtway of virtual crops system was put forward based on Agent technology. This method established crops self-learning system based on neural network. It is helpful to understand cr...

Crop models are increasingly used to simulate crop yields at the global scale, but so far there is no general framework on how to assess model performance. Here we evaluate the simulation results of 14 global gridded crop modeling groups that have contributed historic crop yield simulations for maize, wheat, rice and soybean to the Global Gridded Crop Model Intercomparison (GGCMI) of the Agricu...

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment mod...

H Harvest index (HI), ratio of seed yield to aboveground dry matter, is a very important parameter for estimating seed yield in several crop models. In this study, the importance, definition, variability and estimation methods of HI in crop models were discussed. HI estimation methods are categorized into two groups including: (i) complex methods that estimate HI from the beginning of seed gro...

Recent advances in ecological modeling have focused on novel methods for characterizing the environment that use presence-only data and machine-learning algorithms to predict the likelihood of species occurrence. These novel methods may have great potential for land suitability applications in the developing world where detailed land cover information is often unavailable or incomplete. This pa...

Severe large-scale diseases in agricultural regions have caused significant economic damage. In order to improve crop yields, we develop a framework to predict the occurrence of crop diseases. In the presence of risk and uncertainty, this paper focuses on finding out the best pest control decisionmaking program which is based on the Bayesian network. The paper describes the flowchart of a Bayes...