ABSTRACT

Digital Agriculture encompasses a wide range of scientific disciplines aimed at improving the efficiency, productivity, and sustainability of food production globally.  Agriculture, which is inherently dynamic due to broad soil, machine, and plant biology interactions, offers unique opportunities for applications of data science and advanced analytics.  From plant phenotyping to soil nutrient modeling to UAV yield predictions, the application of connected devices, machine learning, and computer science is at the heart of innovation in agriculture.  These innovations aim to reduce the complexity of agriculture and improve crop production efficiency through data science and targeted automation.  This presentation will discuss key technical drivers in Digital Agriculture solutions as well as strategies to successfully commercializing academic innovations through high impact industry partnerships.

BIOGRAPHY

Professor Matt Darr is the Kinze Manufacturing Fellow and a faculty member at Iowa State University in the Department of Agricultural and Biosystems Engineering.  Dr. Darr's research program focuses on the use of electronic technology and data analytics to solve applied engineering challenges in the agricultural industry.  He currently manages a team of 26 university professionals who provide leadership to a range of ag machinery topics including digital agriculture, telematics data analytics, unmanned aerial systems, and next-generation machinery automation. 

Lecture