Crop Diagnostics & Decision Support

Greenhouse systems can be more resource use efficient if the environmental control system include plant responses measured in real-time in the decision making process. Imaging techniques have potential to identify emerging stresses and to guide sampling for identification of the stressor. These remote sensing applications are increasingly being applied in the rapidly evolving precision agriculture, which can improve crop production, while being more environmentally friendly than the 'classic' production methods.

Our research focus on design, development and implementation of computer vision guided real time crop health and growth monitoring systems for timely identification of crop status and improved resource use efficiency. We are also developing web based decision support systems enabling operators with remote access to meaningful information on crop and greenhouse system status for improved system operation and decision making.