This project was awarded through the "Signals in the Soil (SitS)" opportunity, a collaborative solicitation that involves the United States Department of Agriculture National Institute of Food and Agriculture (USDA NIFA) and the following United Kingdom Research and Innovation (UKRI) research councils: 1) The Natural Environment Research Council (NERC), 2) the Biotechnology and Biological Sciences Research Council (BBSRC), 3) the Engineering and Physical Sciences Research Council (EPSRC), and the Science and Technology Facilities Council (STFC). Nitrate runoff from soil in drainage water from agricultural and horticultural lands into waterways, a process that is increased even more by nitrogen-containing fertilizer use, is a long-standing challenge for agricultural sustainability and environmental protection. One effective approach to improve efficiency of water and fertilizer use, and thereby decrease nitrate runoff, is through precision farming practices guided by real-time monitoring and near-term forecasts of crop irrigation and fertilization needs. Currently, there is a severe lack of reliable sensing technologies and modeling tools for monitoring the variability of soil moisture and nitrogen concentration over different scales. This interdisciplinary collaborative project involving researchers at the University of Connecticut and the University of New Hampshire in the U.S., and at the University of Southampton and the University of Reading in the U.K., aims to tackle the grand challenge of decoding nitrogen dynamics in soil through integration of four innovative solutions: 1) High frequency wireless nitrogen sensing technology; 2) Field-deployable high-accuracy calibration sensors in soil; 3) Real-time profiling of nitrogen species and soil moisture levels in two typical ecosystems (corn farm and deciduous forest); and 4) Data-driven modeling of nitrogen dynamics in the region of soil in the vicinity of plant roots where the soil chemistry and microbiology are influenced by root growth, respiration, and nutrient exchange. The proposed convergent research of innovative in-situ sensing and data-driven modeling will close the technology gap between soil signal detection and agricultural management. Unique integration of soil sensor development, lab-scale tests and field tests, wireless sensor networks, and model validation will yield significant impacts on broader scientific communities and key stakeholders. Multiple education and outreach initiatives, including hands-on experiments and online video clips, will stimulate student interest in STEM careers, especially for underrepresented groups. Interactions with industrial partners, policy makers, and end users will be strengthened through workshops and seminars. All these features contribute to improving resource use, better food security, and the reduction of soil and water contamination in the US and UK.
By targeting two critical soil signals, nitrogen species (ammonium and nitrate) and soil moisture, this US-UK SitS collaborative project will be conducted through six interactive tasks. First, high frequency fine-resolution miniature hydrogel-coating solid-state ion selective membrane-based (HS-ISM) wireless nitrogen sensors will be developed by the US team to enable real-time in situ nitrogen detection in soil. Second, droplet-flow microfluidic-based sensors (DFMS) for nitrogen will be developed by the UK team for in situ calibration of the mass-deployed HS-ISM sensors. Third, low-cost and low-energy wireless networks will be developed for data collection from multiple sensors across large fields. Fourth, in a lab-scale soil system, HS-ISM nitrogen sensors, in conjunction with newly developed mm-sized soil moisture sensors (MSMS), will be assessed for high-resolution profiling and wireless data transmission capability and calibrated in situ using DFMS sensors. Fifth, wireless nitrogen sensors and MSMS sensors will be deployed at two ecosystems, a corn farm in the US and a forest ecosystem in the UK, and examined for 13 months. Finally, numerical models of the rhizosphere nitrogen cycle will be calibrated based on the in-situ nitrogen profiling data. These new numerical models will be used to simulate and predict the rhizosphere nitrogen dynamics under different weather and farming practices beyond the end of the project. This project will transform existing inefficient and labor-intensive soil analysis practices to an automated and highly-efficient soil nitrogen dynamics decoding and field modeling strategy. This project will lead to a better understanding of soil nitrogen dynamics and provide a new vision in nitrogen sensing technology and soil modeling methodology, enabling better soil management by key stakeholders in both the US and UK.
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.
