Researchers at the Carnegie Institution for Science have unveiled a robot that automatically images underground plant root growth. The GLO-Bot operates using GLO-Root, a root imaging software released in 2015. The system solves many of the problems associated with conventional root imaging techniques.
Plant roots are sensitive to environmental changes but observing underground growth is difficult. Researchers study root development in viewing instruments called rhizotrons. However, conventional rhizotron imaging techniques subject roots to unnatural conditions by exposing them to light or placing them in sterile soil and air conditions.
The GLO-Root and GLO-Bot system offers an alternative. Plant roots are treated with a ‘luminescent marker’ called luciferase and placed in the rhizotron. Luciferase emits a form of light capable of penetrating soil, making roots ‘glow’. Luciferase helps the GLO-Root software pick out even the thin, transparent roots of Arabidopsis through non-sterile soil.
Because plant roots grow slowly, manually imaging the roots is labour-intensive. GLO-Bot solves this by taking automatic images at regular time intervals. At maximum capacity, the GLO-Bot can water and image 96 rhizotrons within 24 hours. The result is an accurate visual panorama of root formation over long periods. These detailed images enable researchers to accurately understand how roots branch and extend under specific soil conditions.
The GLO-Bot is the only root imaging system that uses both luminescence techniques and rhizotrons. Combining these methods means detailed images and minimal disturbance to the natural growth process.
GLO-Bot construction began in 2015 at the Carnegie Institution for Science. It was developed by José R. Dinneny, Associate Professor of Biology at Stanford University with Heike Lindner and Therese LaRue, plant biologists at the Carnegie Institution for Science. The researchers collaborated with sustainable agritech company Modular Science. Dinneny was also behind GLO-Roots, the root imaging software automated by GLO-Bot. He designed the concept in 2014 and refined the system with Ruben Rellan-Alvarez between 2012 to 2015.
Target users for the GLO-Bot are researchers interested in understanding plant development, root-soil interactions, and plant-environment interactions. The GLO-Bot and GLO-Root system could potentially advance research into climate-resilient food systems. Automating root growth imaging could help researchers more quickly identify genomic variants associated with root system traits that suit nutrient-poor or arid soil conditions.