Dynamic Dark Root Chamber: Advancing non-invasive phenotyping of roots kept in darkness using infrared imaging

Abstract

Root phenotyping is a challenging task that would require monitoring root growth in soil under dark conditions to mimic natural conditions, while allowing the shoot to grow in light. Most existing methods involve exposing the roots to light, which substantially alters their growth and function. In this paper, we present an improved imaging system that can overcome this limitation of experiments performed in laboratories. The Dynamic Dark Root imaging Chamber (DDrC) enables continuous monitoring and image acquisition to track the dynamic development of root architecture under controlled growth conditions. Our imaging system is based on a Raspberry Pi camera module and infrared LEDs, which do not induce any stress responses in the roots. The DDrC setup is simple, affordable, and suitable for dynamic phenotyping experiments. We provide a detailed tutorial for the assembly and adjustment of the imaging chamber. We conclude that our system is a valuable tool for studying the genetic and environmental factors that affect the root system architecture and development, and for identifying the root traits that are related to plant adaptation and performance.

Code and data availability

The paper describes the DDrC root imaging system and a Python GUI/image-acquisition script, but the script is not publicly deposited; authors state it is available via email on request. No public phenotype datasets, images, or trained models are reported.

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