Join us in exploring the frontiers of smart agriculture in Precision Agriculture Lab
Master Thesis on Hyperspectral Photosynthetic Phenotyping of Winter Wheat
09.03.2026, Diplomarbeiten, Bachelor- und Masterarbeiten
This project aims to harness hyperspectral remote sensing to non-destructively monitor key photosynthesis-related traits of winter wheat during critical growth stages, and to uncover the intrinsic links between spectral signals and phenotypic characteristics through data-driven modeling.
- Technical skills: End-to-end hyperspectral data processing, from acquisition to analysis.
- Modeling experience: Training in statistics, machine learning/deep learning, with guidance and support.
- Physiological insight: Understanding how spectral signals and traits evolve across winter wheat growth stages.
- Field sampling: 4–5 data collection campaigns from April to July 2026, each lasting 1–3 days.
- Phenotyping: Simultaneous acquisition of hyperspectral data and photosynthesis-related traits.
- Thesis: Explore spectral–phenotypic relationships and complete the thesis.
Who We Are Looking For
We are looking for a motivated student with an interest in plant phenotyping or smart agriculture, who has basic data processing skills and is comfortable with field sampling work.
If you are interested in this thesis opportunity, please send a brief statement of motivation or your CV.
Kontakt: ying.yuan@tum.de


