Making a digital twin of a tomato crop

Background

This data is used to update the model as the real crop grows, which will improve its predictions. This is important, because the output of the model is used to steer the growth of the real crop through management and greenhouse settings. This creates a closed feedback loop between the real and the digital twin members.

We are setting up a digital twin called the Virtual Tomato Crop. For that we will conduct a large experiment in the new NPEC greenhouse facilities in which the plants and climate will be measured automatically (phenotyped) in great spatial and temporal detail. An important aspect in this regard is the ‘ground-truthing’ of the phenotyping data, using reliable manual measurements on the plants. This includes 3D morphological and physiological plant traits, as well as environmental conditions like the 3D distribution of light. This data will be used to parameterize the tomato simulation model.

Types of work

Within this project, we are looking for students who are interested in making a comprehensive study on the development over time of tomato in the NPEC greenhouse and make a comparison to the data coming from the phenotyping. For this the student will get involved in the experimental work in the greenhouse. An additional component of the thesis could be the development of a dataset of light distribution in the tomato canopy to verify the predictions of light distribution by the model that is currently under development.

This thesis topic is interesting for students who want to work on the cutting edge of phenotyping and plant model development. The exact contents of the thesis can be defined taking into account the wishes of the student and the requirements of the project.

Due to the reliance on the experiment in the NPEC greenhouse, the thesis can start September 2021 and be finished mid 2022.