This talk will provide an overview of how AI is being used in agriculture, give some example success stories for AI applications in agriculture, and discuss future directions and challenges for accelerating the adoption of AI in agriculture. Artificial Intelligence (AI) applications are rapidly emerging to assist producers improve productivity, efficiency of inputs and sustainability of agricultural practices such as tilling the soil, planting a crop, applying irrigation, fertilizer, manure or crop protection products, and harvesting.  AI is a powerful approach for assessing spatiotemporal patterns and uncertainty arising from variations in weather, soils, nutrient availability, insects, and disease that may affect productivity. AI guided tools are emerging to help producers with early detection and treatment of stresses from water, nutrients, pests and diseases.

Specific strengths of AI include computer perception and vision, classification, regression, clustering, and predictive analytics, multi-criteria, multi-objective decision-making, and natural language processing tools as exemplified by chatbots and virtual assistants. Advances in AI have fostered the widespread adoption of autosteer tractors in agriculture. Advances have also been significant in the areas of a) remote sensing for precision agriculture, b) detection of stress from weeds, insects, nitrogen or water, c) robotic navigation and manipulation, and d) crop phenology assessment.

Speaker: Dr. David Mulla, Department of Soil, Water & Climate at the University of Minnesota