Congratulations to Dr. Ali Mokhtari, who successfully defended his PhD thesis on estimating crop water and nitrogen limitations from satellite remote sensing, bridging soil physics, crop physiology, and Earth observation.

On 2 July 2026, University of Queensland delegation — including Prof. Andries Potgieter and Prof. Scott Chapman — visited the TUM Precision Agriculture Lab at the Dürnast Research Station to tour the wheat field phenotyping trials and discuss remote sensing for crop monitoring and modelling, and field protocols for agricultural remote sensing.

Photosynthetic traits are slow to measure by hand. In a new European Journal of Agronomy paper, we link UAV multispectral imagery to leaf physiology with a physics-informed machine learning framework — predicting CO₂ assimilation, stomatal conductance, photosystem II efficiency, biomass, and grain yield across winter wheat varieties.

On 10 June 2026, researchers from the University of Georgia (Athens, USA) and TUM met at the Weihenstephan campus for a full-day joint seminar — from variable-rate management and precision irrigation in Georgia to UAV and Satellite crop sensing and digital nutrient management at TUM.

Hyperspectral sensors see crop nitrogen in detail but are expensive; multispectral drones are cheap but spectrally coarse. Our new M2H-SWIR framework bridges the gap, reconstructing continuous 400–2500 nm reflectance from a 10-band UAV camera and improving nitrogen estimation in winter wheat.