What is Digital Agriculture?

Digital Agriculture integrates advanced technologies to enhance the agricultural production systems. It includes cutting-edge techniques to acquire data, convert them to practical knowledge using validated interpretation models, and exploit this knowledge as decision-support tools.

Our main goal in the Digital Agriculture Lab is to optimize food production by developing mechanized approaches that improve yield while reducing waste, inputs and environmental footprint. Sensing and actuation are the two essential aspects of our research program. Proper farm management relies on accurate data interpretation models that make sense of big data generated by costly sensing systems. Although advanced remote sensing technologies are currently employed in agricultural systems, lack of validated and crop-specific data interpretation models limits its value for the California specialty crops producers. In our commitment to advance our research goal, we defined our top priority as developing data interpretation models for several major crops in California such as almond, grape, and pistachio.

Our extension program in the Digital Agriculture lab concentrates on the development and dissemination of hands-on scientific knowledge, practical recommendations and tools for agricultural mechanization, sensing technologies, and applications of small unmanned aerial systems (UAV/UAS). We extend scientific knowledge through extension talks, interviews, field days, workshops, and social media, extension publications.

Research Updates

Spray Backstop

Spray Backstop is a low maintenance attachment system for air-assist sprayers that blocks the spray droplets escaping the canopy from tree's top or sides. 

Virtual Orchard

Virtual Orchard (VO) is a technology to describe canopy geometry for individual trees in an orchard using 3D reconstruction of tree canopies.