TRL ^ Multispectral Sensor Development

This project aims to develop a cost-effective imaging system for the early detection of crop diseases, with a particular focus on Fusarium Head Blight which is a disease responsible for an estimated $1 billion in annual losses to Canadian agriculture. Fusarium Head Blight produces deoxynivalenol (DON), a mycotoxin that renders grain unusable at concentrations as low as 2 ppm. While emerging precision agriculture technologies such as selective harvesting and variable rate spraying offer promising solutions to reduce these losses, they depend on fast, affordable, and scalable disease identification systems that can operate effectively in field conditions. Existing technologies, such as hyperspectral sensors, perform well in controlled environments but struggle in field conditions. Meanwhile, commercially available multispectral scanners lack the infrared bands necessary for comprehensive crop health analysis. As such, there is an urgent need for a new imaging solution tailored specifically to agricultural applications. The anticipated benefits of this project include faster, more scalable, and cost-effective disease detection, enabling farmers to take timely action and reduce crop losses. It also supports the broader adoption of precision agriculture practices, contributing to more sustainable and resilient farming systems across Canada.

Faculty Supervisor:

Abdul Raouf

Student:

Partner:

North Forge

Discipline:

Engineering

Sector:

Education; Management of companies and enterprises; Professional, scientific and technical services

University:

Saskatchewan Polytechnic

Program: