This summer saw the latest edition of the PhD course 'High-Throughput Field Phenotyping and Vegetation Mapping'. The five-day course combines lectures from leading experts with extensive hands-on training in UAV operations, field sensors, image processing, and data analysis, giving participants practical experience with state-of-the-art phenotyping technologies.
Participants gain practical experience with state-of-the-art phenotyping technologies and analytical workflows used in modern plant science, plant breeding, and precision agriculture. These technologies are increasingly being adopted in plant breeding, precision agriculture, and climate-resilient crop research, making quantitative phenotyping an essential skill for the next generation of plant scientists.
The course takes advantage of NMBU's internationally recognized plant phenotyping facilities, providing participants with access to advanced UAV platforms, imaging sensors, field experiments, and the course is organized as part of the Nordic Forestry, Veterinary and Agricultural (NOVA) University Network. This year, 2026, more than 30 participants from across Europe took part.
Broad research interests, with a shared long-term goal
Participants came from a wide range of disciplines, including Plant breeding, Data science, Computer science, Plant physiology, Ecology and Precision agriculture. While research interests varied, many shared a common goal: gaining a better understanding of how emerging sensing technologies can be used to answer biological questions in real-world conditions.
Several participants highlighted the combination of theory and practice as being particularly valuable. Throughout the week, attendees explored UAV-based phenotyping workflows, worked with handheld sensors, and gained practical experience in collecting and processing field data.
Yannick Valentin El Khoury, a PhD student at the University of Copenhagen, appreciated seeing the entire workflow from start to finish.
"The most valuable part was understanding the complete workflow behind UAV-based field phenotyping, from flight planning, sensor calibration, and image acquisition to data processing, quality control, and biological interpretation," he explains. "It really emphasized that collecting the images is only a small part of the process."
For Fitim Kastrati, Assistant Professor at the University for Business and Technology in Kosovo, the course represented a valuable opportunity to connect plant physiology with modern imaging technologies.
"The most valuable takeaway was learning how UAVs (drones), imaging sensors, and advanced data analysis can be integrated to monitor plant traits quickly and non-destructively,"
"The course showed how these tools can bridge plant physiology and field phenotyping."
Fitim Kastrati, University for Business and Technology in Kosovo
Comprehensive introductions to new phenotyping technologies
The course also introduced participants to a range of sensing technologies, including RGB, multispectral, hyperspectral and thermal imaging, as well as emerging approaches involving robotics, machine learning and remote sensing.
Anna Fischer, a PhD student at the University of Helsinki, joined the course to gain understanding of imaging technologies beyond the greenhouse-based work conducted in their PhD project.
"I got insights into how to collect, analyze, and interpret multispectral and hyperspectral images, which was entirely new to me," they say.
Fischer particularly enjoyed the practical field sessions.
"Seeing drones and robots in action and trying out various hand-held sensors myself was fascinating."
El Khoury agrees the course was well suited to those at the early stages of their research careers, as well as those who are more experienced:
“The repeated introduction to the fundamental concepts was really helpful for those of us who are new to the field, while the more advanced lectures showed the wide range of applications across agricultural research” he says.
The importance of data analysis
For many participants, the week also reinforced the importance of turning large volumes of sensor data into meaningful biological information.
Francesco Paladini, a PhD student from the University of Turin, found the sessions on data analysis especially valuable.
"We are often taught how to collect data, but we receive less training on how to analyse the large datasets that these technologies can produce," he says.
Paladini says he left the course with new ideas for applying spectral indices in his own plant biology research and was particularly impressed by drone-based imaging systems.
The practical applications of high-throughput phenotyping were a recurring theme throughout the week. Henrik Høegh, a PhD student in Genetics and Plant Breeding at NMBU, attended the course to support his research on drought tolerance in wheat.
“For me, the most valuable takeaway was understanding the appropriate scale of data collection and analysis, from country-level observations to field and plot-level data”, says Henrik. He is planning to apply the drone phenotyping approaches introduced during the course to identify traits associated with drought tolerance.
Multi-disciplinary and multi-national learning environment
Beyond the technical training, participants consistently highlighted the value of learning alongside researchers from different countries and disciplines. The interdisciplinary nature of the course created opportunities for scientific discussion and future collaboration.
"It was amazing," says Fischer. "I met so many great people from different countries and continents. We had meaningful discussions about our research, current advancements and challenges in our fields, and gave each other advice on how to tackle challenges."
Kastrati similarly described the experience as collaborative and inspiring.
"The exchange of ideas and perspectives created a collaborative learning environment. I made several new professional connections and look forward to developing future collaborations."
Paladini agrees.
"It was a great experience to meet scientists from different countries, universities, and research backgrounds. I made some valuable contacts for potential future collaborations, and most of all I made some great friends."
Francesco Paladini, University of Turin
With new knowledge, new professional contacts, and fresh ideas to bring back to their own research, participants left NMBU ready to put what they had learned into practice. The overwhelmingly positive feedback was reflected in the course evaluation: 100% of participants who completed the evaluation said they would recommend the course to other students, highlighting the course's value for early-career researchers working in plant phenotyping and precision agriculture.
As demand for quantitative and AI-enabled plant phenotyping continues to grow, the NOVA course provides an important platform for training the next generation of researchers. By combining theory, practical fieldwork, and interdisciplinary collaboration, the course equips participants with the skills needed to address some of the most pressing challenges facing agriculture under climate change.
You can learn more about the content, learning outcomes, and other practical information on the NMBU courses webpages