Grants and Contributions:
Title:
Optimizing computer vision approaches for field pea imaging
Agreement Number:
1001473
Agreement Value:
$249,997.00
Agreement Date:
Feb 16, 2023 - Feb 15, 2026
Description:
Implementation of digital agriculture through high throughput-imaging is key to improving plant phenotyping for crop improvement. Image analyses utilizing machine learning (ML) approaches have the potential to dramatically improve crop phenotyping. The intent of the project is to capture above-ground image datasets of peas in an agricultural field, establish an ML pipeline to identify plants and quantify biomass, and begin to associate field traits such as yield and protein with beneficial root traits. For roots, an automated ML pipeline will be established to characterize rhizobium nodules and root system architecture in controlled environments. The foundational datasets generated will enable field to lab comparisons and importantly facilitate the development of advanced tools deployable for improving pea production in the Canadian Prairies
Organization:
National Research Council Canada
Expected Results:
In the short term, anticipated outcomes will be strengthened collaborations across industry, academia, and government to support research excellence. In the medium term, anticipated outcomes will be the development of new and potentially disruptive technologies with collaborators. In the long term, find collaborative solutions to public policy challenges and create stronger innovation systems.
Location:
Oak Bluff, Manitoba, CA R4G 0B1
Reference Number:
172-2022-2023-Q4-1001473
Agreement Type:
Grant
Report Type:
Grants and Contributions
Recipient Business Number:
763638697
Recipient Type:
Not-for-profit organization or charity
Additional Information:
This agreement has been amended 1 time(s). The total amended value is $249,997.
Amendment Date
Mar 7, 2025
Recipient's Legal Name:
Enterprise Machine Intelligence and Learning Initiative
Federal Riding Name:
Portage--Lisgar
Federal Riding Number:
46005
Program:
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Program Purpose:
Collaborate on multiparty research and development programs to catalyze transformative, high-risk, high-reward research with the potential for game-changing scientific discoveries and technological breakthroughs in priority areas.
NAICS Code:
541710
Amendments: