ASC hosts leading researchers at the Frontiers of Agricultural Nitrogen Symposium

The Agroecosystem Sustainability Center, in collaboration with the Levenick Center for a Climate-Smart Circular Bioeconomy, hosted a symposium on April 28th titled The Frontiers of Agricultural Nitrogen: Geopolitics, Industry, Innovation, and Farming Management symposium at the Beckman Institute for Advanced Science and Technology on the University of Illinois Urbana-Champaign campus. The event brought together internationally recognized researchers, policy experts, and UIUC faculty to examine the science, economics, and regulations around nitrogen, a substance which is both essential to modern food production and the source of pressing environmental challenges. 

The symposium kicked off with an introduction by Dr. Kaiyu Guan, director of the Agroecosystem Sustainability Center, followed by keynote presentations by two distinguished visitors. Dr. David Kanter (New York University; Chair of the International Nitrogen Initiative) gave a talk titled “Nitrogen Governance in a World at War”, which discussed the growing need for more intelligent policy guidance and consideration when considering the global nitrogen fertilizer economy, and its impacts, in both the short and long term to the development of the field. Dr. Xin Zhang (University of Maryland Center for Environmental Science; Director, NICCEE) delivered a talk on “Decarbonization in a Eutrophic World”. Dr. Zhang described the challenges in attempting to reduce the carbon intensity of agricultural nitrogen,due to its exceptional interconnectedness, while also describing how canny innovation can create opportunities that benefit multiple sectors in their adoption.

Two prominent University of Illinois researchers also shared their expertise on agricultural nitrogen. Dr. Wendy Yang spoke on “New International Initiatives to Advance Nitrogen Sustainability in Agriculture”, highlighting recent projects aimed at improving and advancing global nitrogen cycle data that have received funding from Novo Nordisk and FFAR. These projects form a core component of the aims of the Agricultural Nitrogen Use Efficiency Platform, or AgNUE, which is an international research initiative aimed at enhancing nitrogen management in agriculture . Dr. Angela Kent’s talk,  “NSAVE Maize: Building the Future of Bioenergy from the Ground Up“, discussed the reintroduction and breeding of ancient strains of maize with current hybrids to improve nitrogen efficiency by changing soil microbiology. The keynote speakers then took part in a Q & A panel mediated by Dr. Kaiyu Guan. 

An afternoon panel discussion on Agricultural Nitrogen Measurement was moderated by Dr. Wendy Yang, including Dr. John Jones (UIUC), Dr. Zhang, and Dr. Bin Peng (UIUC). Discussions centered on improving management processes and collaborating with farmers and land managers to better design innovations and implement science-backed solutions for nitrogen application and use. The need for flexibility in nitrogen use and acquisition was introduced in an increasingly volatile market. Dr. Peng emphasized the value of proactively engaging with younger generations of farmers to better co-manage the trajectory and implications of innovation within the agricultural space.

Looking Ahead

The symposium reflected a growing recognition within the research community that nitrogen is not merely a soil chemistry problem, it poses geopolitical, economic, ecological, and social challenges. The April 28 conversations demonstrated that meaningful progress will require the kind of cross-disciplinary, cross-border, and cross-sector collaboration that events like this help catalyze. With initiatives like AgNUE now underway and UIUC researchers playing leading roles in international nitrogen science, the Agroecology Sustainability Center looks forward to continuing this vital work in the field, in the lab, and at the policy table.

Read the full story here.

URBANA, Ill. – Predicting how water and nutrients move through agricultural landscapes is essential for protecting water quality, managing fertilizers, and preparing for extreme weather. Yet scientists have long struggled to forecast these dynamics across entire watersheds. Monitoring networks are sparse, and traditional models often struggle to capture the complex interactions among climate, land use, and river systems.

A new study from researchers at the University of Illinois Urbana-Champaign shows that artificial intelligence can significantly improve predictions of both streamflow and nitrogen pollution across agricultural watersheds. The study was recently published in the journal Water Research.

The research team developed a new AI system, HydroGraphNet, that combines machine learning with scientific knowledge of how water and nutrients move through river networks. The method represents a watershed as a connected system of upstream and downstream areas, allowing the model to better capture how water and pollutants move through the landscape.

“Our goal is to bridge the gap between traditional hydrologic models and modern artificial intelligence,” said first author Jie Yang, a researcher in the Agroecosystem Sustainability Center at Illinois. “By embedding scientific knowledge into AI models, we can make predictions that are both more accurate and more consistent with how real watersheds behave.”

Unlike many previous AI models that treat each watershed as a single unit, the new approach can generate daily predictions for individual sub-watersheds across an entire river network. This allows scientists to identify where water and nitrogen pollution originate and how they move downstream.

The Illinois team tested their model in the Upper Sangamon River Basin, a largely agricultural watershed in central Illinois dominated by corn and soybean production. The AI system was trained using both existing monitoring data and results from hydrologic simulations, allowing it to learn patterns from observations while also incorporating scientific understanding of water movement.

The results showed that the new approach substantially improved predictions of both streamflow and nitrogen export, especially in areas with limited monitoring data. The model also revealed clear seasonal patterns in nitrogen losses, with large pulses of nitrogen leaving fields during wet periods when runoff and drainage rapidly carry nutrients into streams.

“Hydrologic systems are inherently connected,” said Bin Peng, a professor of crop sciences at Illinois. “By explicitly representing those connections in an AI framework, we can better understand how upstream conditions influence downstream water quality.”

Beyond improving predictions, the researchers say the approach reflects a broader shift in environmental science. “Artificial intelligence is rapidly transforming Earth system science,” said Kaiyu Guan, founding director of the Agroecosystem Sustainability Center. “By combining physical understanding with AI, we can generate high-resolution predictions of water and nutrient dynamics across large landscapes.”

Such capabilities could help scientists and policymakers design more targeted strategies to reduce nutrient pollution, manage water resources, and adapt agriculture to a changing climate. By providing detailed daily predictions across entire river networks, the new system could support next-generation monitoring and decision tools for sustainable watershed management.

Why this matters: Nitrogen runoff from agricultural landscapes is a major contributor to the Gulf “Dead Zone.” Better information about when and where nitrogen leaves fields could help farmers and policymakers target conservation practices more effectively.

The paper, “Knowledge-guided graph machine learning for spatially distributed prediction of daily discharge and nitrogen export dynamics,” is published in Water Research [DOI: 10.1016/j.watres.2026.125613]. The research was supported by the U.S. Department of Energy, the National Science Foundation, and the U.S. Department of Agriculture.

For more information, contact:

Bin Peng, Assistant Professor
Department of Crop Sciences
University of Illinois Urbana-Champaign
binpeng@illinois.edu

Jie Yang, PhD
Postdoctoral Research Associate
Department of Crop Sciences
University of Illinois Urbana-Champaign
jieyang7@illinois.edu

Kaiyu Guan, Professor
Department of Natural Resources and Environmental Sciences
University of Illinois Urbana-Champaign
kaiyug@illinois.edu

Image credit: Sands, G., Ale, S., Christianson, L., & Utt, N.  (2017, September 26). Subsurface (Tile) Agricultural Drainage. Oxford Research Encyclopedia of Environmental Science. 

URBANA, Ill. [26th Nov. 2025] — A new study from the Agroecosystem Sustainability Center (ASC) of the University of Illinois Urbana-Champaign provides one of the most comprehensive explanation to date of how tile drainage, a common agricultural practice, enhances the functioning of agricultural landscapes. Although tile drainage has been widely studied as an important form of agricultural infrastructure, the new study built a comprehensive framework to explain why tile drainage is so effective across a wide range of outcomes. The study pinpoints soil oxygen dynamics as the critical, hidden mediator that is pivotal for drainage impacts on crop growth, soil health, and crop resilience.

The study recently published in Hydrology and Earth System Sciences demonstrates that the benefits of tile drainage extend far beyond simply removing excess water from fields. Tile drainage fundamentally alters soil hydrology by reducing soil water content, which then enhances soil oxygenation. These hydrological impacts have complex effects on soil biogeochemistry and plant biology. For example, the improved aerobic condition alleviates crop oxygen stress during wet springs, which, in turn, promotes early crop root growth. The increase in oxygen availability also stimulates microbial activity, which accelerates the decomposition of organic matter and nutrient cycling.

The research team used an advanced, process-based model called ecosys that is uniquely capable of simulating the physics of soil oxygen movement and crop oxygen uptake. After validating the model against multi-year field data, the researchers ran simulations comparing drained and undrained conditions to understand the full set of ecological changes following drainage.

According to Kaiyu Guan, the project’s principal investigator and a Levenick Endowed Professor and Director of the Agroecosystem Sustainability Center at the University of Illinois, “Previous models that do not explicitly simulate soil oxygen dynamics fail to capture the true impacts of tile drainage, making it hard to accurately predict agriculture outcomes such as yield, nutrient availability, and nutrient leaching. These outcomes and the underlying processes must be understood through the lens of soil oxygen.”

“Most models use soil water as a simple proxy for oxygen stress, but without explaining the underlying physical mechanisms that improve crop outcomes. Our work focuses on the central role of oxygen. Its availability depends on the balance between supply (oxygen diffusion through soil) and demand from roots and microbes. This allows us to provide a holistic view of how tile drainage impacts the broader agroecosystem,” said lead author Zewei Ma, a PhD student at the University of Illinois under Prof. Guan.

The authors note that while conventional tile drainage provides clear agronomic benefits, emerging practices such as controlled drainage offer a more comprehensive approach that help mitigate potential water-quality trade-offs. By adjusting outflow during different parts of the season, controlled drainage can retain more water and nutrients in the field while still improving soil oxygen dynamics when crops are most vulnerable to oxygen stress.

The key findings of the study include:

  • Soil oxygen as the key controlling factor: By removing excess water, tile drainage actively oxygenates the soil. The improved aerobic environment results in a range of soil health benefits.
  • Stronger root development: Improved soil oxygen levels during wet springs alleviate stress on crop roots, allowing them to respire and grow more efficiently. This leads to the development of denser and deeper root systems.
  • Accelerated nutrient cycling: Higher oxygen levels stimulate microbial activity, which accelerates organic matter turnover and increases nutrient availability for crops.
  • Water quality trade-off: The study also confirmed that tile drainage can lead to increased leaching of soil nitrogen into waterways, highlighting the need for paired conservation practices to protect water quality.
Oxygen dynamics in the root zone are the key to effective crop benefits from tile drainage.


“This research provides a mechanistic understanding of why drainage benefits crops. It goes far beyond water management; it improves the conditions for microbes and crop roots in the soil. By reducing oxygen stress in the root zone, the plants have greater ability to establish a resilient foundation for the entire growing season,” said co-author Bin Peng, an assistant professor on agricultural water management and water quality at the Department of Crop Sciences at the University of Illinois.

Professor Guan emphasized the broader implications, saying: “As we face a future with more climate extremes, strategic water management is essential for food security. This study gives us a powerful predictive tool to assess where and how tile drainage can best serve as an adaptation strategy, not just for increased yield, but for greater long-term yield stability.” 

The researchers hope their findings will inform farmers, agricultural advisors, and policymakers on the multifaceted value of drainage management and the importance of integrating it with other practices to ensure both productivity and environmental sustainability.

The paper, “Soil oxygen dynamics: a key mediator of tile drainage impacts on coupled hydrological, biogeochemical, and crop systems,” is published in Hydrology and Earth System Sciences [DOI: 10.5194/hess-29-6393-2025]. The work was supported by the National Science Foundation, the U.S. Department of Agriculture, the Foundation for Food & Agriculture Research, and the U.S. Department of Energy.

For more information, contact:
Kaiyu Guan, Professor
Department of Natural Resources and Environmental Sciences
University of Illinois Urbana-Champaign
kaiyug@illinois.edu 

Bin Peng, Assistant Professor
Department of Crop Sciences
University of Illinois Urbana-Champaign
binpeng@illinois.edu

Author: Lesly Goh. On September 5, 2025, I had the privilege of speaking at the FAO Inter-Regional Digital Agriculture Solutions Forum (IDASF 2025) in Bangkok. This global event brought together policymakers, researchers, and innovators to explore how digital technologies can accelerate rural transformation and bridge the digital divide in agrifood systems.

The Role of Academia in Digital Inclusion

My panel, “Role of academia in powering digital innovations and enhancing digital inclusion,” focused on how universities and research institutions can drive impactful change through cross-sector partnerships. Academia plays a critical role in translating cutting-edge research into practical solutions that empower rural communities, strengthen food security, and promote sustainability.

The Vision Behind SIGMA

The inspiration for my talk came from my experience at the Rockefeller Foundation’s Bellagio Residency in September 2023. That experience helped me crystallize the concept of developing a multi-stakeholder rice ecosystem. Over the past year, I’ve been collaborating with top scientists at the University of Illinois and University of Arkansas to operationalize this concept, moving beyond research to translate technology directly into local communities in Southeast Asia.

Introducing SIGMA: A Global Model for Agri-Food Systems

This effort led to the formation of the Southeast Asia Innovation Alliance for a Global Model of Agri-Food Systems (SIGMA). Co-led by the University of Illinois and the National University of Singapore (NUS), SIGMA is an academic research initiative that digitally captures plant growing systems, starting with rice. We leverage advanced sensing, modeling technology, and rich data to understand how crop systems respond to different conditions. SIGMA is designed to transform academic innovation into real-world solutions for economic development, improve farmers’ livelihoods, and promote environmental sustainability in Southeast Asia. Learn more about SIGMA: https://asc.illinois.edu/sigma/

A Solution for the Digital Divide: Our SYMFONI MRV Technology

During my presentation, I discussed the limitations of current Measurement, Reporting, and Verification (MRV) technologies, many of which require extensive data and are too costly or complex for smallholder farmers. These systems often work well for large, consolidated farms with strong digital infrastructure but pose a significant burden on smallholders in developing countries.

To address this, the SIGMA team developed a system-of-systems approach called SYMFONI, which is specifically designed to overcome these challenges. SYMFONI combines process-based modeling, ground data collection, remote sensing, and AI-empowered model-data fusion. This approach minimizes the need for extensive manual data input from farmers, making it far more accessible and cost-effective. The rapid adoption of SYMFONI on over one million hectares in the U.S. demonstrates its clear practical advantages over traditional methods.

The Vietnam Pilot Project: A Real-World Example

Vietnam offers an ideal context to pilot our sustainable practices. Rice is a big part of the economy, and it is a symbol of Vietnamese culture and the people’s staple food. Rice production contributes 30% of the country’s agricultural production value and provides food security for the nation. While grown across the country, about 50% of rice fields are concentrated in the Mekong Delta region which produces half of the nation’s rice and 90% of its exports.

With support from the World Bank between 2016 and 2022, the Viet Nam Sustainable Agriculture Transformation Project (VNSAT) trained 155,000 rice farming households on climate resilient farming and helped cultivate 180,000 hectares of low-emission rice fields. Through the project, farmers’ profits have increased by 30-35% as a result of direct savings incurred from reduced fertilizer, pesticide and water consumption, in addition to income increases from higher yields and certain price premium due to quality improvement.

As a result, the Vietnamese government has taken bold new steps in the Mekong Delta to develop one million hectares of high-quality, low-emission rice –with higher yield, better quality, and up to 70% less methane emissions.

The SIGMA MRV solution can be a critical tool in this effort, helping to accurately monitor decarbonization progress, ensure carbon credit integrity, and maximize the program’s effectiveness.

Scaling Impact Through Collaboration

A key strength of the SIGMA alliance is its collaborative model. Academia provides research, philanthropy de-risks initial investments, and the private sector is essential for scaling solutions. Partners like multilateral development organizations and governments are crucial for ensuring that these tools reach and benefit smallholders.

The SIGMA team is actively developing an ecosystem, together with Global Methane Hub, working with strategic partners to expand the uptake of SYMFONI beyond the U.S. My hope is that by working together, we can transform advanced MRV systems into actionable solutions, promoting sustainable rice cultivation and delivering scalable climate impact across Southeast Asia. It was an honor to share this vision at IDASF2025 and to highlight how the University of Illinois is at the forefront of this critical research to bring the MRV solution to Southeast Asia, starting with Vietnam as the first pilot.

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Drought negatively affects plants and the environment, but to accurately model it is no easy task. Accurately simulating transpiration is key to understanding plant and ecosystem response to drought.

URBANA, Ill. — In the face of increasing global drought risk, understanding how plants respond to water stress has never been more critical. Researchers at the University of Illinois Agroecosystem Sustainability Center have delivered a pioneering synthesis that reconciles decades of differing approaches to modeling water use and dynamics in plants. The result: a unified theoretical framework and improved tools for predicting plant behavior under drought, and more informed decisions for agriculture and ecosystem management.

Transpiration, the process by which water moves from soil, through plants, and into the atmosphere, is a critical part of Earth’s water and energy cycles. It links plant physiology to weather and climate patterns and returns a significant amount of water that falls on land back to the air. During transpiration, the tiny pores in plants – stomata – release water vapor on the leaf surface and also absorb carbon dioxide to fuel photosynthesis, making transpiration a crucial indicator of plant health and productivity. 

Modeling transpiration has a long and evolving history. Scientists have historically used two broad types of models to simulate plant water stress: empirical models based on  statistical relationships between water in soil and plants, and mechanistic models based on physical laws that describe biological and biophysical processes. Early mechanistic models introduced empirical approaches, such as the Beta function, which scales transpiration in proportion to the soil water content. The supply-demand balance scheme is a more sophisticated empirical approach used in crop growth models that accounts for how easily water moves through soil and plant roots. These approaches are easy to implement and efficient, but often oversimplify plant physiology and lead to errors. Ideally, a model should be just complex enough to accurately simulate a specific environment. 

In contrast, advanced mechanistic approaches such as plant hydraulic models offer detailed simulations of water transport through plants, but require many parameters that are difficult to measure and long computation times. Until now, the relationships among these models (and the best choice for a given application) have remained unclear.

Lead author Dr. Yi Yang and colleagues, led by the project director Dr. Kaiyu Guan, have now developed a novel mathematical framework that formally connects these different approaches. The team was able to see that the simple empirical approaches are specific cases of the complex mechanistic approach. “Scientists have debated which method is the best way to capture how plants respond to drought, but what we really needed was a clear way to connect them all,” said Yang, the former Ph.D. student of Dr. Guan in the Department of Natural Resources and Environmental Sciences. “We show that we don’t have to choose between simplicity and realism. We can understand where each method fits and see that they are connected as special cases within a unified system.”

The researchers used data from three contrasting ecosystems: a humid Midwestern cropland, a semi-arid conifer forest, and an arid grassland, to show how the best choice of model depends on the specific site and conditions. Researchers were then able to see how the models respond to different environments and different plants. 

Understanding whether plant stress is caused by dry air, dry soil, or both is key. While droughts in many parts of the world are becoming more common, the Midwest U.S. often experiences ‘atmospheric drought’ (hot, dry air), even when soil moisture is still available.  “This framework helps us better simulate how plants respond when the air is dry but the soil may not be,” Yang said. “That’s crucial for predicting stress under future climate conditions.” 

In the example of U.S. corn and soy fields, the empirical models strongly overestimated transpiration during periods of atmospheric drought with normal soil moisture but dry air. In this case, detailed models that capture how plants manage internal water flow become more important for accurate predictions.

However, in consistently dry environments or for plants such as grasses with a fairly simple water transport pathway, the simpler Beta model works well. The arid grassland case study demonstrated that the more empirical models performed similarly to the complex mechanistic models, suggesting that the more sophisticated approach isn’t needed for reliable results in these settings. 

“Our contribution allows us to determine how the drought stress affects plant transpiration with fewer data and with better efficiency,” Yang said. “If you need to rely on the more complex mechanistic model, you must gather more data and likely must go to the field to measure its hydraulic parameters in order to predict the stress level. With our improved framework and understanding, we can instead estimate that stress level with satellite data in some cases, because we can remove unnecessary parameters from the equation.”

From an agricultural management perspective, more precise estimates of plant water use help farmers optimize irrigation, saving water while protecting yield. By knowing when crops are likely to suffer stress, growers can better time irrigation during critical growth stages like mid-summer, when healthy transpiration supports peak photosynthesis and grain fill.

“How to reconcile these different transpiration modeling theories was a long-standing problem of mine from my own PhD time through my early career as a professor, ” said Guan. “I am so proud that my student Yi made such a breakthrough to close this major scientific gap.” 

ASC researchers Bin Peng, Jingwen Zhang, Lisa Ainsworth, and Sheng Wang joined scientists from the University of Minnesota, Cornell University, the University of California-San Diego, University of Texas Austin and the Pacific Northwest Natural Laboratory on this project.

The project received support from an NSF CAREER award managed through the NSF Environmental Sustainability Program and USDA/NSF Cyber-Physical-System Program as well as a an annual small grant award from USGS Illinois Water Resources Center. Funding for AmeriFlux and FLUXNET data resources and core site data was provided by the U.S. Department of Energy’s Office of Science. Funded was also provided by the DOE Center for Advanced Bioenergy and Bioproducts Innovation (CABBI) funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research.

The new study is titled “A Unified Framework to Reconcile Different Approaches of Modeling Transpiration Response to Water Stress: Plant Hydraulics, Supply Demand Balance, and Empirical Soil Water Stress Function” and is published in Journal of Advances for Modeling the Earth System (JAMES) [doi: 10.1029/2023MS003911].