Since its founding in 2020, the TUM Precision Agriculture Lab has been committed to empower smart farming research, education, and practice.


The inaugural LSE Get2Gether brought together early-career researchers across the Life Science Engineering department. PagLab was represented with three poster presentations and a group overview highlighting our mission in precision agriculture and remote sensing.

The BIGSTAR workshop successfully brought together internationally renowned scientists from across the world to discuss remote sensing technologies for global sustainable agricultural resources.

DeepSpecN combines PROSPECT-PRO simulations with Conv-Transformer models to estimate leaf nitrogen content from hyperspectral reflectance, eliminating the need for field data collection while achieving unprecedented accuracy.

Members of the Precision Agriculture Lab at the Technical University of Munich participated in the European Plant Phenomics Symposium (EPPS 2025), held in Bonn, Germany, from 16–19 September 2025.
Professor Kang Yu, together with PhD candidates Wuhua Wang, Xiaoxin Song, and Fei Wu, represented the group and shared our recent activities in UAV-based field phenotyping.


Our research team has introduced a novel approach (Song et al. 2025) to quantify wheat senescence dynamics by integrating UAV-based multispectral imaging with generalized additive models (GAMs).
Unlike traditional methods that capture only single time points, this study tracked the entire senescence process throughout the growing season and validated it, in collaboration with Prof. Minceva’s Lab at TUM, using laboratory measurements of leaf anthocyanins. The results revealed clear nitrogen-related differences among wheat varieties, demonstrating that the area under the curve (AUC) of UAV-derived vegetation indices strongly correlates with grain yield.