Humboldt-Universität zu Berlin - Urban Plant Ecophysiology





Project title: "FYTA-Beam"


Funding: IBB, The project is co-financed by the Europäischen Fonds für regionale Entwicklung [EFRE].


Project duration:

08/01/2021 until 07/31/2023


Project management:


Claudia Nassif, General project management

HU-Berlin, Faculty of Life Science, Division Urban Plant Ecophysiology

Prof. Dr. Dr. Christian Ullrichs, Project management HU-Berlin

PD Dr. Heiner Grüneberg, Project coordinator

Dr. Matthias Zander, Project support

M.Sc. Jens Neumann, Project support


Project description:

The ornamental plant assortment offers a wide range of species and varieties of different origins. This can lead to mistakes in the cultivation of these plants and ultimately death for many inexperienced consumers when trying to meet the species-specific requirements. On the other hand, plants are often seen as nothing more than inanimate objects or decoration, creating a certain throwaway mentality among many consumers.

The Berlin start-up company FYTA GmbH has set itself the goal of actively supporting people in the care of their plants and also educating them about the basics of ornamental plant cultivation. Through positive experiences and an active engagement with the plants, long-term plant survival be supported and encouraged.

This is to be made possible by a newly developed plant sensor (FYTA Beam), which is to monitor the essential growth parameters of light, ambient temperature, substrate moisture and salinity. The user will be informed via smartphone-based software if limit values are exceeded and can then initiate an appropriate measure based on recommendations for action.

Humboldt-Universität zu Berlin supports FYTA GmbH by providing scientific support for the project. In a series of experiments, it will be investigated to what extent the sensor is able to map the condition of a plant. For this purpose, experiments with different stressors will be carried out. Humboldt-Universität zu Berlin is also investigating the stress states using hyperspectral imaging (HSI). The results of this non-destructive analysis procedure are to be used in the future for the automatic detection of stress in different plants.