Aerial view of agricultural research fields
University of Manitoba

Digital Agronomy & Weeds Lab

Advancing sustainable agriculture through precision technology and data-driven research

Remote Sensing

UAV & satellite imagery analysis

Data-Driven

Machine learning & AI applications

Sustainable Agriculture

Environmentally conscious solutions

About the Lab

Bridging traditional weed science with digital agriculture

The Digital Agronomy and Weeds Lab (DAWL) at the University of Manitoba focuses on advancing sustainable crop production through precision agriculture and data-driven weed management.

Our research integrates remote sensing, UAV-based technologies, and field experimentation to better understand crop-weed interactions and improve agricultural decision-making.

We aim to bridge the gap between scientific innovation and practical applications for farmers and industry stakeholders.

Dr. Dilshan Benaragama

Principal Investigator

Dr. Dilshan Benaragama

Assistant Professor

Dr. Benaragama leads the Digital Agronomy and Weeds Lab at the University of Manitoba. His research focuses on developing innovative approaches to weed management and crop production using cutting-edge digital technologies.

  • Ph.D. in Plant Science
  • Expert in Precision Agriculture
  • UAV Remote Sensing Specialist

Research Areas

What we do

Our research integrates traditional weed science with cutting-edge digital technologies to advance sustainable crop production.

Precision Agriculture
01

Precision Agriculture

Developing site-specific management strategies using advanced sensing technologies, GPS mapping, and variable rate application systems to optimize crop inputs and maximize yields.

Remote SensingGPS MappingVariable Rate Technology
Weed Science & Management
02

Weed Science & Management

Investigating integrated weed management approaches combining cultural, mechanical, and chemical control methods to develop sustainable and effective weed control strategies.

Integrated ManagementHerbicide ResistanceCover Crops
Digital Agriculture & AI
03

Digital Agriculture & AI

Leveraging machine learning, computer vision, and big data analytics to develop decision support tools for modern farming operations.

Machine LearningComputer VisionData Analytics

Our Team

Meet the researchers

Our diverse team combines expertise in weed science, remote sensing, machine learning, and agronomy.

Research Staff

DM

Dr. Mujahid Hussain

Postdoctoral Fellow

Postdoctoral Fellow at the University of Manitoba focusing on precision agriculture, UAV-based technologies, and data-driven weed management.

UAV sprayingPrecision agricultureRemote sensingWeed management
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DK

Dr. Kenneth Anku

Postdoctoral Fellow

Postdoctoral Fellow at the University of Manitoba focusing on remote sensing, plant physiology, and data-driven approaches for precision agriculture and crop productivity.

Remote sensingPlant physiologyCrop phenotypingMachine learning
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MR

Mike Runzika

Research Technician

Research Technician at the University of Manitoba with expertise in field experimentation, data collection, and agricultural research operations.

Field trialsData collectionCrop researchExperimental design
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Graduate Students

SD

Stephanie Dushimwe

M.Sc. Student

Machine learning for weed detection

TD

Thinuja Dharmarathna

Ph.D. Student

UAV-based crop monitoring

MN

Mohamed Naeem

M.Sc. Student

Precision herbicide application

HR

Heshan Ranawake

Ph.D. Student

Digital phenotyping

Publications

Recent publications

Our research has been published in leading peer-reviewed journals in weed science, remote sensing, and agricultural technology.

2024

Machine learning approaches for early weed detection in wheat fields using UAV imagery

Hussain, S., Benaragama, D., et al.

Computers and Electronics in Agriculture, 215: 108432

2024

Evaluation of cover crop mixtures for weed suppression in organic canola production

Anku, E., Benaragama, D., et al.

Weed Technology, 38(2): e15

2023

Spectral indices for detecting nitrogen stress in canola using multispectral UAV imagery

Dharmarathna, T., Benaragama, D., et al.

Remote Sensing of Environment, 298: 113812

2023

Integrated weed management reduces herbicide use while maintaining wheat yields

Dushimwe, S., Anku, E., Benaragama, D.

Field Crops Research, 302: 109078

2022

Variable rate herbicide application based on weed density maps in soybean

Naeem, M., Hussain, S., Benaragama, D.

Precision Agriculture, 23(4): 1245-1262

Opportunities

Join our team

We are always looking for talented and motivated individuals to join our team at the University of Manitoba.

Graduate Students (MSc / PhD)

Graduate

We welcome applications from highly motivated students interested in weed science, precision agriculture, and UAV-based technologies.

Apply Now

Postdoctoral Researchers

Postdoc

Opportunities may be available for postdoctoral researchers with strong backgrounds in agronomy, remote sensing, or data-driven agriculture.

Apply Now

Don't see a fit?

We welcome applications from exceptional candidates at any time. If you're passionate about agricultural research and technology, we'd love to hear from you.

Send Your CV

Contact

Get in touch

Interested in our research, collaboration opportunities, or joining the lab? We'd love to hear from you.

Location

222 Agriculture Building, 66 Dafoe Road, Winnipeg, MB R3T 2N2, Canada

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