Precision agriculture is the science of linking differential global positioning systems with significant computational resources to apply customized quantities of pesticide, seeds, and fertilizer according to a particular field’s specific needs. This project will use data from Geographic Information Systems (GIS) mapping systems and from moisture sensors connected to farm machinery and inserted into the soil to help farmers adjust the amount of pesticide and fertilizer applied to their fields. The process provides data that can help farmers eliminate unnecessary and costly pesticide and fertilizer applications. Additional sensors planned for the project will measure soil properties such as acidity and nutrient levels, and crop conditions.
The project, a collaboration with the North Carolina State University Department of Soil Science, addresses several issues of interest to 21st century agriculture:
- How to collect, manage and utilize the growing amount of agricultural data collected by environmental sensors,
- How to translate these new data collection and analysis techniques into practices that can help farmers grow better and safer crops more cost effectively,
- How to use sensor technology and computational science to help agricultural scientists and farmers understand the interrelationships among the physical, chemical, and biological soil characteristics and the processes related to soil quality, especially water, nutrients and environment health.
Precision agriculture can have a positive impact on environmental quality. The opportunity exists to show producers how changing agriculture management practices will not place crops at risk and produce positive economic and environmental benefits.
RENCI experts are creating the visualizations and interpolating data that will help give farmers an idea about the trends in their crop fields and enable them to visually pinpoint potential problem areas, such as the correlations between nitrogen concentrations and water table depths. RENCI researchers have created the isosurface, or visual “sheet”, that is shaped like the physical ground displaying the depth of the water table and NO3 concentration. Project leader, Jeff White, will continue to work with RENCI researchers Jeff Heard and Steve Chall on improving the visualization and adding more animation sequences. The researchers envision another isosurface showing the height of the terrain colored by NO3 concentration.
- North Carolina State University Department of Soil Science
- The North Carolina State Climate Office
- Jeffrey G. White, assistant professor, Department of Soil Science, NCSU (Principal Investigator)
- Ryan Bowles, NC State Climate Office
- Theresa-Marie Rhyne (project leader)
- Steve Chall, RENCI at NCSU
- Jeff Heard
- David Knowles
- Jason Coposky