PhenoRob
Robotics and Phenotyping for Sustainable Crop Production
Food, feed, fiber, and fuel: Crop farming plays an essential role for the future of humanity and our planet. The environmental footprint of agriculture needs to be reduced: less input of chemicals like herbicides and fertilizer and other limited resources like water or energy. Simultaneously, the decline in arable land and climate change pose additional constraints like drought, heat, and other extreme weather events.
Achieving sustainable crop production with limited resources is a task of immense proportions. In order to achieve this, the University of Bonn together with Forschungszentrum Jülich conducts research in the Cluster of Excellence “PhenoRob – Robotics and Phenotyping for Sustainable Crop Production” to develop methods and new technologies that observe, analyze, better understand and specifically treat plants.
PhenoRob PhD Graduate Talks: Hendrik Zeddies
PhenoRob PhD Graduate Talks: Adrian Haupenthal
PhenoRob PhD Graduate Talks: Alireza Ahmadi
PhenoRob PhD Graduate Talks: Erekle Chakhvashvili
PhenoRob PhD Graduate Talks: Julius Rückin
PhenoRob PhD Graduate Talks: Elin Martinsson
J. Moscona, MIT Department of Economics (25.06.2025)
PhenoRob PhD Graduate Talks: Benedikt Mersch
PhenoRob PhD Graduate Talks: Dereje T. Demie
Hannah M. Schneider - Integrated Root Cortical Tissues for Enhanced Drought Tolerance
Andreas Hund - Computer vision to evaluate field experiments
Bruno Basso - Digital Twins to Scale Sustainable Agricultural Systems
Madhu Khanna - Artificial Intelligence-Based Digital Technologies for Sustainable Agriculture
Peter Groot Koerkamp - A Systems’ Perspective on Robotization
Stefano Mintchev - Interactive Drones for Biodiversity Monitoring
PhenoRob PhD Graduate Talks: Federico Magistri
Sustainable AI and the next wave of AI ethics
Franziska Brohmeyer - VariableRain: Resource-conserving irrigation providing optimal yield
Lena Brüggemann - Agrivoltaics Crop Yield Modeling
Maria Lackmann, Meltem Cantürk - SmartBeans Project: Using prebreeding approaches in dry edible bean
Linn Chong - No Labels Required: Zero-Shot Segmentation with Foundation Models
Jianchao Ci - Self-supervised learning-based NBV algorithm for 3D plant reconstruction by robots
Jonathan Cox, Riccardo Polvara - AGRIDS An Integrated Framework for Vineyard Data Management
Rajitha De Silva - Keypoint-Semantic Integration for Improved Feature Matching in Agriculture
Paulina Englert, Ana Meijide - Quantifying N2O Fluxes with Eddy Covariance
Kaouter Essakkat - From Data to Decisions: Modeling Farmer Adoption of AI Weed Technology
Felix Esser - Field Robot for High-throughput and High-resolution 3D Plant Phenotyping
Joaquin Gajardo - Wheat 3DGS: In-field 3D Reconstruction, Instance Segmentation and Phenotyping
Sven Gedicke - Light-Weight Algorithms for In-Field Data Quality Assessment in Agricultural Science
Kathrin Grahmann - Landscape experimentation: knowledge gaps filled from patchCROP's 1st phase