Light conditions in strawberry production vary strongly over time, while fixed lighting strategies do not always match the actual physiological demand of the crop.
The student will investigate how continuous photosynthesis monitoring and environmental sensors can be used to better understand and optimize light supply in strawberry. Measurements may include photosynthetic activity, PAR or light spectrum, temperature, humidity/VPD and other relevant plant or environmental variables. Where relevant, contrasting light-transmission conditions or covering materials may also be included.
The collected data will be used to explore simple data-driven or AI-based approaches for identifying conditions under which additional light is most beneficial for plant carbon gain and resource-use efficiency.
The exact experimental setup and modelling approach will be adapted to available data and thesis extent.
The project is aligned to UN's SGD:
