Researchers at Oak Ridge National Laboratory are pushing the envelope of agricultural science, breaking ground with an autonomous robotic system that promises to significantly hasten data collection from plant-soil interactions—a critical component in understanding environmental dynamics and boosting bioenergy crop productivity. According to their recent Oak Ridge National Laboratory announcement, the goal is to better inform both fundamental and applied research into biomass productivity and carbon storage.
The urgency to precisely gauge soil carbon, estimated to lock away trillions of tons—eclipsing atmospheric carbon levels—is driving scientists to rapidly improve data-gathering methods. Udaya Kalluri, a senior staff scientist at ORNL, revealed in a statement obtained by Oak Ridge National Laboratory news, "We have over 250,000 different above-ground phenotypes collected of poplar alone through our DOE investments in bioenergy research." Yet, belowground data remain sparse due to the challenging nature of studying root-microbe interactions and soil dynamics. To bridge this gap, a custom-made robotic platform, the Sensors, Machine vision, Automation and Robotics for Transforming Plants Field Series (SMART Plant F-Series), has been deployed, showcasing its prowess at the laboratory's SMART field site, where poplar plants, potential biofuel feedstock, are cultivated.
The system is equipped with innovative navigation features, including GPS waypoints and a laser sensing system, allowing the robot to maneuver cautiously around sensitive plantation areas. Chris Masuo and other advanced manufacturing researchers from ORNL tailored a commercial robot to perform soil sampling by integrating onboard software, sensors, and an electromechanical system with components fabricated through 3D printing. "The robot can take up to four samples at once before returning independently to its home position," Masuo disclosed in the Oak Ridge National Laboratory report.
Enhancing lab-to-field connections, the ORNL team aligns this field sampling system with the Advanced Plant Phenotyping Laboratory (APPL), an advanced robotic greenhouse that conducts detailed plant imaging. Scheduled to include an underground imaging station by 2025, APPL's capabilities will expand further. "One of our goals with this project is to make connections between the laboratory and the field seamless," Kalluri told Oak Ridge National Laboratory news. The SMART field-based autonomous data collection stands testament to a burgeoning vision—an interconnected system of robots and sensors streamlining data collection across distributed environments to directly inform responsive models for smart agriculture and ecosystem management.
Reflecting on the interdisciplinary efforts, Kalluri lauded the rapid progress made by the cross-cut team that fused bioscience and manufacturing expertise. The project, part of ORNL's INTERSECT program, is a testament to the laboratory's commitment to fostering innovation through collaborative approaches, crucial in advancing the nascent domain of robotic environmental sampling and analysis. As the SMART system evolves, the potential for incorporating additional sensors and capabilities will inevitably deepen our comprehension of ecosystem health, plant growth, and responses to climatic stress, painting a clearer picture of the ecological dynamics underpinning bioenergy plantations.
