Plants as computational models

(07-06-2022) In his PhD, Olivier Pieters investigates whether plants can be used as computational models.

"Plants are ubiquitous on Earth. They are often considered as organisms that undergo changes in their environment. However, with the research I conducted, I want to call for a more integrated view: a plant as a computational unit," Olivier explains.

"Plants are complex organisms, composed of many connected nodes and modules. These nodes and modules enable a plant to cope with the rapidly changing environmental variables resulting from weather patterns, predation and disease. Despite the absence of a central nervous system and inability to move, plants can effectively respond to changes in their environment. A plant continuously optimizes its internal state based on internal signals and information it gathers from the environment. I propose to consider the plant as a computational unit in the context of physical reservoir computing (PRC)," Olivier explains.

"At first glance, it seems strange that PRC can work. However, there are strong similarities with conventional computing in, say, a computer. Computing involves transforming information to achieve a certain goal. Conventional systems do this using an algorithm. Input is processed by an algorithm designed for it until the desired outcome or output is obtained. With PRC, this algorithm is replaced by a physical substrate that does the computational work," Olivier continues.

"In a first part of the PhD, the applicability of hyperspectral cameras was investigated. Such cameras turned out to be unsuitable for detecting subtle spectral changes required for PRC. Thereupon, a new sensor platform was developed, specifically designed to read contact sensors. Using leaf thickness sensors, we showed that plants can indeed be used as reservoirs for PRC. Plants were more performant than a control substrate in solving eco-physiological and environmental tasks."

"In summary,  we can think of the plant as a computational unit that processes input signals from the environment and adjusts its physiology accordingly. This increased holistic approach can help breeding, phenotyping and precision agriculture do better than current methods," Olivier concludes.

Read a more detailed summary or the entire PhD


PhD Title: Reservoir Computing with Plants


Contact: Olivier Pieters, Michiel Stock, Tom De Swaef, Francis wyffels

Olivier Pieters

Olivier Pieters (Aalst, 1994) obtained his master degree Master of Science in Electrical Engineering: Communication and Information Technology with highest distinction from Ghent University in 2017.

In September of the same year, he started as a doctoral researcher with BOF funding under the supervision of Francis wyffels, Tom De Swaef and Michiel Stock. The primary research line of this PhD involved investigating the computational properties of plants for biological problems. This highly interdisciplinary research combines aspects from electrical engineering, phenotyping and data analysis.

Olivier is first author of three publications in peer-reviewed journals, and one conference publication. He is also co-author of a review article and conference contribution. These publications were produced as part of the primary line of research, as well as side projects in collaboration with other groups at Ghent University.

Olivier plans to continue his research as a postdoctoral researcher to deepen our knowledge of the computational properties of plants.


Editor: Jeroen Ongenae - Illustrator: Roger Van Hecke