Fully automatic monitoring of plant growth, development and disease progression with Helios
Conveyor belts take plants on a journey along a series of optical sensors
Thanks to Helios, a new research installation that is part of the Netherlands Plant Eco-phenotyping Centre (NPEC), it is now possible to automatically monitor the growth and development of more than a thousand plants, while gaining insights into how microorganisms affect them. Housed within the NPEC building at the Utrecht Science Park, the installation consists of, among other things, a growth chamber, a system of conveyor belts, several special cameras and a 3D laser scanner. Researcher Bart Schimmel is putting Helios into operation with an experiment focused on the early and objective detection of the plant pathogen Bremia lactucae that causes downy mildew infection on lettuce plants.
Helios, which enables observations beyond the capabilities of the human eye, greatly reduces the practical workload for plant researchers. This does, however, not imply that researchers are completely relieved of hands-on tasks. They are, for instance, still responsible for sowing the plants and filling the pots. Additionally, researchers have the option to infect all or part of the plants with pathogens such as fungi and bacteria, or to introduce microorganisms into the potting soil to study their effects on the plants. Experiments can involve genetically modified plants and/or microorganisms, as Helios incorporates stringent safety measures to prevent the unwanted release of organisms from the installation.
Once the plants are placed inside Helios, there is basically no need for human intervention for weeks. During this time, the plants reside primarily within a growth chamber, where environmental conditions like temperature and humidity are meticulously controlled. The plants experience alternating periods of light and darkness, creating a simulation of day and night.
Following a pre-programmed schedule, each plant goes on a fully automated journey through the installation at regular intervals during the day but also at night. Guided by a conveyor belt, the plant travels along a series of cameras: a conventional camera captures visible light images, a second camera records the chlorophyll fluorescence—light re-emitted by chloroplasts during the photosynthesis process—and a third camera captures the near-infrared (NIR) spectrum, which is invisible to human eyes. Furthermore, a 3D laser scanner generates a spatial image of the plant. Once the plant has undergone imaging via these various methods, it is automatically watered and transported back to the growth chamber via the conveyor belt.
Bart Schimmel has become the first researcher to utilize Helios for a research project. His experiment revolves around the destructive pathogen Bremia lactucae, which infects lettuce and causes significant economic losses for growers of this popular vegetable. Bremia lactucae is an oomycete, a microorganism that resembles fungi both in terms of its life cycle and in the way it grows branching threads.
The researcher aims to determine the feasibility of an earlier and more objective detection of pathogen infection in lettuce plants, which is crucial for identifying resistance traits in lettuce. Schimmel: "Although early signs of a Bremia infection may not be readily apparent on the plant, in practice, detection of this pathogen still largely relies on visual inspections. With ample experience and proper training, one can typically observe the oomycete's reproductive organs as whitish dots on the leaves approximately 10 days after infection."
Bart Schimmel is currently using Helios to explore the possibility of detecting infections before they become visible to the naked eye. His colleagues previously discovered that the pathogen can be made visible after 4 to 5 days by illuminating lettuce plants with UV light while viewing them with a fluorescence camera. Schimmel: “I want to know if this method can be scaled up and automated. Within the PathoView research program, I am currently investigating the applicability of this approach to a selection of twelve varieties. If successful, it would enable us to rapidly and objectively determine the resistance levels of large numbers of lettuce lines against this disease. The knowledge gained can then be used to breed disease-resistant lettuce varieties.”
For his experiment, the researcher will take advantage of the full potential of Helios, making use of all cameras and the 3D scanner. This will not only lead to insights into the early detection of resistant lettuce plants, but will also serve as a valuable learning experience, revealing the capabilities and possibilities afforded by Helios.
Helios facilitates the rapid collection of vast amounts of data. Schimmel highlights that new data analysis methods utilizing artificial intelligence (AI) allow for the effective extraction of meaningful insights from this wealth of data. Schimmel: "Thanks to Helios, we now have the ability to make use of plant variation in a more accessible and objective manner, enabling us to address intriguing biological questions and to find solutions for agricultural challenges."
Helios is part of the Plant-Microbe Interaction Phenotyping research module of the Netherlands Plant Eco-phenotyping Centre. NPEC is a collaboration between Utrecht University and Wageningen University & Research. Using the six modules, researchers have the opportunity to study plant properties across a range of scales, from small-scale laboratory experiments to research in the open field.