Implementation of Machine Vision Algorithms in a Decision Support System for Variable Crop Management

The proposed research aims to develop machine vision-based decision support system for variable crop management. This research will deploy the deep learning models for plant/weed detection, plant growth indicators and soil organic matter assessment. The information retrieved from these models will be used to devise variable rate management map to optimize the consumption of agrochemical with reduced environmental risks. Other potential outcomes of this project include monitoring soil health in fields and linking those to productivity. Large-scale adoption of these concepts and services can improve productivity and ensure sustainability in Canadian agriculture.

Faculty Supervisor:

Aitazaz Farooque

Student:

Partner:

Croptimistic Technology Inc

Discipline:

Engineering

Sector:

Agriculture; Professional, scientific and technical services

University:

University of Prince Edward Island

Program: