Of interest for this DCL are applications focused on economically important plants, animals, and their environments—in particular food, fuel, feed, and health—and where research outcomes in a particular application area may be transferable to, or informative for, other agricultural application areas.
Specific topics of interest include, but are not limited to, the following:
Methods for analyzing existing, large datasets, such as artificial intelligence, machine learning, and computer vision, for example, leveraging environmental, imaging, and genomic data;
Models for genetic x environment x management x socioeconomic interactions (G x E x M x S) in order to predict livestock, aquaculture, and plant phenotypic outcomes and sustainabilit—such as yield, survivability, resistance to environmental stressors, pest resistance, drought resistance, and nutritional value;
Data storage, management, and integration across a range of data types to enable a systems-level approach, including integration of big data in real-time systems;
Wired and wireless networking challenges in rural settings, including computation at the edge;
Security, privacy, and management for access and sharing of farm and community data; and
Learning science innovations, which may include development of computational skills for biological and agricultural science majors, and communities of agricultural practice for a diverse and innovative future workforce.
Proposals pursuant to this DCL may be submitted to one of the three programs listed below: