"The goal of the Computational Agriculture project is to enhance the decision-making of agricultural producers", stated CTC Executive Director, Linda Callahan. "We're bringing high-performance computing to precision agriculture."

Projects include developing a server-based tool for precision nitrogen management using real-time climate information and a dynamic simulation model and determining procedures for using hyperspectral sensing to rapidly assess a wide range of soil characteristics. In addition, researchers will apply real option theory to determine the optimal timing of investments to reduce the cost of climate change to agriculture in the Northeastern United States.

Agriculture is a very complex system with many interacting components that make its management very challenging. Research in agriculture has become increasingly quantitative and computational, and the generation of data is no longer a limiting factor, provided that researchers have the necessary hardware and software tools. The Computational Agriculture initiative's interdisciplinary orientation reflects the fact that real world agricultural problems require multi-disciplinary perspectives. The project also reflects CALS' strong traditional relationship with stakeholders in agriculture and the environment.

"Several project components of this partnership are based on strong stakeholder demands for improved technology and tools", stated Harold van Es, the project's director. "For example, the lack of high-resolution weather data severely limits precise management of irrigation and nitrogen in a variety of cropping systems. These are significant production expenses to land managers and involve materials that are also of environmental concern."

In addition to assisting with data integration, mining, and warehousing, CTC will contribute its expertise in Windows HPC and .Net Web Services to the project.