Phenotyping perennial ryegrass using image analysis

Project Details


Main research question/goal
The aim of the Fenogras project is to develop semi-automatic analysis procedures for images of individual perennial ryegrass plants grown in field trials. Growth and architectural features will be assessed using this phenotyping tool. The system will allow capture of many images of individual plants and efficient analysis of those images. The final aim is to use image analysis as a supporting technique for several research project. This will enable objective and efficient assessment of plant growth and architecture, even for other crops.

Research approach
To determine the capacity of growth and regrowth of perennial ryegrass, trials are performed in two locations (Belgium and France). The trials are mown similarly as in a standard pasture management systems and are followed during two growth seasons. Plant volume, habitus, and geometry are evaluated using top and side images. This allows an assessment of the plants which is not possible when only measuring plant height or diameter in a manual manner. Evaluation of growth dynamics of the plants in low or high resolution is done taking series of images every two months (to describe soil covering potential) or every week (to describe leaf growth).

Added value is generated by this research in terms of the possible optimization of the genetic capacity of perennial rye grass and other plants. The knowledge generated can be used in several other projects. This includes research related to the effect of crop management on plant productivity, effect of stress conditions, development of screening tools for use in breeding or DUS or VCU trials. In this way, we try to improve the quality and quantity of the arable crops and to elucidate the intrinsic potential of plant processes.
Effective start/end date1/01/10 → …

Data Management Plan flag for FRIS

  • DMP not present


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.