Background of Summer School / Introduction
The core objective of this Summer School is to bridge the gap between theoretical data science and practical application in the context of Integrated Weed Management (IWM). As agriculture transitions toward "Agriculture 4.0", there is an increasing need for experts who can navigate both methodological foundations and their field-scale applications.
This Summer School, hosted by the University of Hohenheim (Department of Weed Science, Institute of Phytomedicine), focuses on the synergy between modern Information Technologies and advanced Field Machinery. By bringing together students and researchers, the program facilitates a hands-on knowledge exchange to explore how Precision Weed Management can be utilized to improve overall IWM strategies.
Hosting University
University of Hohenheim (UHOH)
Venue
Ihinger Hof (Research Station of the University of Hohenheim), 71272 Renningen, Germany
Date
May 25 - June 14 (Online phase), June 15 – 19 (On-site workshop)
Participants
30
Previous Knowledge
Participants should hold a bachelor’s or master’s degree in a relevant discipline, preferably with a background in agriculture or related life sciences. Prior experience with spatial data, UAVs, or data-driven methods is an advantage but not mandatory.
Course Content
Our Summer School begins with an online phase delivered via ILIAS. This phase provides all participants with progressively structured foundational knowledge on relevant topics regarding precision weed management and establishes a common baseline prior to the on-site phase. After completing the online modules, participants are required to prepare a mandatory abstract summarizing their acquired knowledge in approximately 600 words. The abstract should describe the core principles of precision weed management within Integrated Weed Management, their future potential and limitations under practical field conditions. Additionally, students must include an individualized “Scenario Reflection” in which they select one specific weed species from their home region and propose a detection and control strategy using the methods discussed in the online phase.
The following on-site workshop is structured into two parts, moving from digital data processing to physical field application and final evaluation.
I. Methodological Foundations
This section covers the essential steps required to enable the practical applications.
Crop Identification & Image Annotation: Learning methods to identify species-specific features and to annotate image data for the creation of training datasets used in machine learning.
AI-Based Classification: Applying neural network–based approaches to develop models for automated species identification and for distinguishing crops from weeds.
Spatial Data Analysis: Processing classification outputs into spatial maps and management zones to support site-specific decision-making and guide field machinery.
II. Practical Field Application
The theoretical foundations learned prior will now be put into practice. Participants will be introduced to the setup, calibration and operation of selected precision weed management technologies, including:
Autonomous Weeding Robots
Field application of autonomous robotic systems utilizing navigation technologies and mechanical weed control strategies.
Camera-Guided Mechanical Hoes
Use of real-time camera and sensor systems for crop–weed differentiation and guidance of mechanical weeding implements.
Spot Spraying Technologies
Application of site-specific spraying based on previously annotated and processed spatial maps.
UAV Systems
Execution of UAV-based mapping flights and demonstration of drone seeding and spraying technologies.
Intended Learning Outcome (ILO)
After successful completion of the Summer School, participants will be able to:
• Explain the principles of precision weed management within Integrated Weed Management (IWM) systems
• Identify crops and weeds under field conditions
• Annotate image data for the creation of training datasets for machine learning
• Train and evaluate basic AI-based classification models for crop–weed differentiation
• Acquire UAV-based imagery and understand its limitations for weed mapping
• Analyze spatial data using GIS tools and generate weed maps and management zones
• Interpret classification and mapping results for site-specific weed management decisions
• Set up, calibrate and operate selected precision weed management technologies, including camera-guided hoes, autonomous weeding robots, UAV systems and spot spraying technologies
• Apply basic principles of experimental design, field data collection and evaluation of weed control measures
• Critically assess technological, agronomic and practical constraints of precision weed management approaches
Course Schedule
The course consists of an online phase from 25 May to 14 June, which can be done independently by participants.
It is followed by an intensive on-site phase with lectures and practical field exercises at the Ihinger Hof Research Station from June 15 to June 19.
Course Language
English
Course Format / Teaching Methods
Online phase (three weeks) followed by whole-day, in-person lectures and exercises (one week).
Credits
ECTS Credits and Workload Overview
| Number of Credits [ECTS] | 6 |
|---|---|
| TOTAL Workload [hours] | 180 estimated |
| Student's own work [hours] | 130 estimated |
| Contact classes [hours] | 50 estimated |
| Exam [hours] | 2 |
Type of Assessment and Assessment Criteria
On-site block: Practical examination (30%) + Exam (70%).
Cultural Activities / Social Program
Excursion to the Rangendingen Biosphere, identification of rare arable weeds, Pizza party, exchange with experienced researchers and professors from the European Weed Research Society.
Tuition Fees
No tuition fee
Additional Costs
149 Euros, including accommodation costs and food.
Accommodation
Directly in the dormitory at the research station Ihinger Hof.
Health Insurance
Participants are responsible for an adequate health insurance during their participation in the program.
Visa
Participants are responsible for checking whether a visa is required.
Application Deadline
15 May 2026
Link to online Application form
Will be opened 15.2.2026: https://forms.office.com/e/qTP91pwWMu
Contact persons for scientific questions
Marian Weigel marian.weigel@uni-hohenheim.de, Roland Gerhards roland.gerhards@uni-hohenheim.de
Contact person for administrative questions
Marian Weigel marian.weigel@uni-hohenheim.de