Agricultural systems are pressured by growing global population, increasing water scarcity, and changing climate. In the pursuit of increasing food security, agriculture (especially intensive systems) should also minimize negative and undesired impacts on the environment and on rural societies. Part of the solution to this challenge lies in understanding how environmental factors such as soil, water, and weather influence crop yield over space and time and in employing that knowledge in spatially aware agronomic practices. Soils are notoriously spatially heterogeneous and many soil properties (e.g., water content, organic carbon, salinity, etc.) are temporally variable, making soil a complex media. This talk will feature research on the use of field measurements, near ground and remote sensing, and spatiotemporal multi-scale (field to the regional scale) data analysis for understanding soil-plant-water interactions across scales and manage agricultural inputs site-specifically. The talk will include an overview of research gaps and opportunities for the use of data science in agriculture.

Dr. Elia Scudiero