COVID-19 update; this seminar is now zoom-only. REGISTRATION REQUIRED: https://cornell.zoom.us/meeting/register/tJ0rcO-qpj0iHdAK6d5qVg9jiqmgBCLdKOzu

One key emerging technology in agricultural engineering that researchers and growers are eager to know more about, is novel remote sensing technology that can detect agricultural problems such as crop stress and disease nondestructively for the purpose of best management practices on farms and high-throughput phenotyping in large-scale trial fields. Toward this goal, my group studies novel experimental and computational approaches integrating the following techniques: drone multispectral/hyperspectral imaging, sensor development, machine learning and deep learning to address corn nutrient deficiency and management, as well as high-throughput phenotyping for disease resistance in wheat.

Dr. Ce Yang is an Assistant Professor in the Department of Bioproducts and Biosystems Engineering at the University of Minnesota. She leads the Agricultural Robotics Laboratory which focuses on remote sensing (ground-based and air-borne) for solving various agricultural problems. Her group’s tools for carrying out the research projects are unmanned aerial vehicle, unmanned ground vehicle, digital camera, multispectral camera, hyperspectral camera, DGPS, and various electrical, optical, and chemical sensors.

The Cornell Institute for Digital Agriculture (CIDA), a faculty led initiative focused on creating a strong voice in the emerging area of Digital Agriculture (DA), invites Asst. Professor Yang to present his research for CIDA’s monthly seminar series.