Implementation of Imaging Solutions for Agri-Biotechnology

The costs of manually sorting seeds and plants for commercial clients and international export is costly and at risk of human error. Correspondingly, 2020 Seed Labs requires cost-effective, custom solutions to enhance automation in their seed sorting and plant selection workflows. Across diverse sectors, image analysis combined with machine has provided a wide-range of benefits. Here, we propose to capitalize on these technologies to address biotechnological challenges unique to 2020 Seed Labs by utilizing successfully implemented workflows developed by the partner academic labs. In addition, we will develop a new image analysis workflow that utilizes diffracted light to reveal unique features of seeds and plants to address 2020 Seed Labs challenges. Collectively, this project aims to assist 2020 Seed Labs find enhanced efficiencies in their production workflows by reducing human intervention in critical process central to their operation.

Faculty Supervisor:

Richard Glen Uhrig

Student:

Partner:

20/20 Seed Labs Inc.

Discipline:

Life Sciences

Sector:

Agriculture and Food; Biotechnology

University:

University of Alberta

Program: