Research
Advancing precision agriculture, UAV-based technologies, and data-driven weed management
Research Areas
Our Research Focus
Driving Innovation in Weed Science
The Digital Agronomy and Weeds Lab focuses on developing data-driven solutions for sustainable crop production. Our research integrates precision agriculture, UAV-based remote sensing, and weed ecology to improve decision-making and enhance crop productivity in modern farming systems.
Weed Ecology & Management
Understanding weed dynamics and developing sustainable weed control strategies.
UAV & Remote Sensing
Using drone-based imaging and sensor technologies for crop and weed monitoring.
Precision Agriculture
Applying site-specific management practices to optimize crop productivity.
Research Updates
Latest presentations, posters, abstracts, and conference highlights from the Digital Agronomy and Weeds Lab.
LiDAR in Precision Agriculture
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CWSS–WSSA Joint Meeting 2025
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Oral Presentation
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3rd Place
Evaluating LiDAR-derived metrics for crop growth, weed dynamics, and yield response in field pea systems.
Managing Kochia Seed Production
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Poster / Abstract
Studying how wheat seeding systems affect kochia seed production and soil seedbank return.
Integrated Crop Management in Wheat
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CWSS/WSSA 2025
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PSGSA 202Plant Canada 2024
Assessing how integrated crop management influences crop growth, weed phenology, and seed persistence.
Integrated Crop Management in Wheat
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CWSS-WSSA 2025
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PSGSA 2025
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Plant Canada 2024
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Award-winning presentations across multiple national conferences.
Research on the impacts of Integrated Crop Management (ICM) on crop growth, weed dynamics, phenology, and weed seed persistence in spring wheat systems.
Field Experiments & UAV Research
Field-based experiments and UAV-assisted technologies used for crop and weed monitoring across different cropping systems.
Research Tools & Technologies
UAV & Remote Sensing
Drone-based imaging, LiDAR, and multispectral data for crop and weed monitoring.
Field Experimentation
Plot trials, crop–weed interaction studies, and agronomic field experiments.
Data Analytics & Modeling
Statistical modeling, AI tools, and data-driven decision-making.
Our research collaborates with industry partners, producers, and academic institutions to develop practical solutions for sustainable agriculture. The lab focuses on translating research outcomes into real-world applications that benefit farmers and the agricultural sector.
• Industry partnerships for applied research
• Collaboration with academic and research institutions
• Focus on real-world agricultural impact