Collaborative Research: EAGER SitS: Automated Imaging Platform for In Situ Sensing and Analysis of Roots, Fungi, and Soil Solution Chemistry

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Understanding how plant roots and soils interact is critical to proper management of global water, carbon, and nutrient cycles. Studying processes that occur below the soil surface, however is challenging. Getting the necessary information can be laborious and usually means disturbing the soil. Developing inexpensive methods to study soil without disturbing it is crucial for effective soil management. This project will develop a new soil sensor system that can automatically detect changes in roots and soil chemistry with little soil disturbance. This new sensor will use affordable, commercially available components, and will automatically collect and process data. The system will allow direct comparisons of root activity and soil chemistry, which is currently not possible in the field. Final designs and software will be made publicly available to help other scientists advance understanding of roots and soils. This project will also engage undergraduate students in research and data analysis.To develop the new sensor system, project researchers will modify and combine two existing technologies: minirhizotrons (clear plastic tubes installed in the soil that allow repeat imaging of plant roots) and planar optodes (two-dimensional optical sensors that fluoresce at varying intensities based on the dissolved concentration of the chosen analyte). Outside sections of standard acrylic minirhizotron tubes will be impregnated with chemical-sensitive dyes, enabling side-by-side imaging of roots and analyte concentrations along the length of the minirhizotron tube. Field application of minirhizotrons and planar optode technology is currently limited by the size and cost of imaging equipment and the cost of labor associated with image collection and analysis. The developed system will address these shortcomings by using 1) an automated camera system, built with off-the-shelf components, that will be small enough to fit in the inside of minirhizotron tubes and capable of imaging both roots and analyte concentrations, and 2) open-source software, developed by project researchers, to automatically collect, process, and analyze image data. The system (hardware and software) will be tested and refined based on performance in two contrasting environments, a remote thermokarst bog in Alaska and an easily accessible production agriculture field in Kansas.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.