Keeping pace with rapid developments in plant phenotyping

Technology in plant phenotyping develops quickly. For Joey Koopman, Digital Phenotyping Data Specialist at Enza Zaden, that makes regularly stepping away from daily projects to examine new methods especially valuable.

Joey first heard about the Summer School Image Analysis for Plant Phenotyping through his manager, Nanne Faber, who attended the programme several years earlier. His positive experience made Joey curious about how the field, and the summer school itself, had developed since then.

“I wanted to learn more about the newer techniques that are currently being used in our field,” Joey explains. “After three years in this position, it felt like a good moment to refresh my professional knowledge.”

Some parts of the programme were familiar territory. Joey works with the production and interpretation of digital phenotyping data, so topics such as cameras, imaging and measuring plant material are closely connected to his everyday work.

What interested him most were the newer methods covered during the week. The programme introduced participants to the foundational work behind AI techniques such as deep learning and object detection, as well as statistical techniques such as decision trees and random forests

“Object detection was particularly relevant to me, but I also appreciated the attention given to the statistics behind these methods,” he says. “It gave me a better idea of how far certain technologies have progressed and where we may be able to use them.”

The summer school did not provide a single ready-made solution to take back to Enza Zaden. Instead, it gave Joey several new directions to investigate. “I picked up a number of ideas that made me think: this is worth exploring further. It offers a fresh perspective on some of the work we are already doing.”

Covering such a broad and technical field in five days makes for an intensive programme. According to Joey, the lecturers played an important role in keeping the material understandable.

“They managed to explain quite advanced subjects clearly and relatively quickly,” he says. “During one day, we covered several topics in AI and statistics. That is a lot to take in, but the lectures kept my attention throughout.”

Their enthusiasm also helped. Rather than presenting the techniques as abstract theory, the lecturers showed why they matter and how they can be applied. “You could really notice how enthusiastic some of the professors were about their subject. That enthusiasm is contagious, especially when you are working through challenging material in a short period of time.”

Although the programme was concentrated and demanding, Joey describes the atmosphere as informal and welcoming. Practical sessions and activities outside the lecture room helped balance the theoretical components. “We were not only sitting in a classroom listening to lectures,” he says. “The practical elements and the opportunity to see facilities and equipment made the overall picture much more complete.”

The international and professionally diverse group also added to the experience. Joey met participants from organisations he would not normally encounter in his daily work, creating opportunities to exchange perspectives and compare how image analysis is being used in different settings. “There are definitely people I expect to stay in contact with,” he says. “It was valuable to meet professionals from companies and organisations that I would not otherwise speak to very often.”

For Joey, the summer school also meant returning to familiar surroundings. He previously completed his master’s degree in Plant Biotechnology at Wageningen University & Research. Coming back as a professional allowed him to see the campus and its work from a different perspective.

“When you have just graduated, much of the knowledge is still fresh in your mind,” he says. “But technology moves fast. A programme like this helps you keep up with those developments and sharpen your knowledge again.”