IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i10p5649-d557296.html
   My bibliography  Save this article

Development of an Online Tool for Tracking Soil Nitrogen to Improve the Environmental Performance of Maize Production

Author

Listed:
  • Giovani Preza-Fontes

    (Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA)

  • Junming Wang

    (Illinois State Water Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA)

  • Muhammad Umar

    (Department of Meteorology, COMSATS University Islamabad, Islamabad Capital Territory 45550, Pakistan)

  • Meilan Qi

    (School of Science, Wuhan University of Technology, Wuhan 430070, China)

  • Kamaljit Banger

    (Plant Agriculture, University of Guelph, Guelph, ON N1G 2W1, Canada)

  • Cameron Pittelkow

    (Department of Plant Sciences, University of California, Davis, CA 65616, USA)

  • Emerson Nafziger

    (Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA)

Abstract

Freshwater nitrogen (N) pollution is a significant sustainability concern in agriculture. In the U.S. Midwest, large precipitation events during winter and spring are a major driver of N losses. Uncertainty about the fate of applied N early in the growing season can prompt farmers to make additional N applications, increasing the risk of environmental N losses. New tools are needed to provide real-time estimates of soil inorganic N status for corn ( Zea mays L.) production, especially considering projected increases in precipitation and N losses due to climate change. In this study, we describe the initial stages of developing an online tool for tracking soil N, which included, (i) implementing a network of field trials to monitor changes in soil N concentration during the winter and early growing season, (ii) calibrating and validating a process-based model for soil and crop N cycling, and (iii) developing a user-friendly and publicly available online decision support tool that could potentially assist N fertilizer management. The online tool can estimate real-time soil N availability by simulating corn growth, crop N uptake, soil organic matter mineralization, and N losses from assimilated soil data (from USDA gSSURGO soil database), hourly weather data (from National Weather Service Real-Time Mesoscale Analysis), and user-entered crop management information that is readily available for farmers. The assimilated data have a resolution of 2.5 km. Given limitations in prediction accuracy, however, we acknowledge that further work is needed to improve model performance, which is also critical for enabling adoption by potential users, such as agricultural producers, fertilizer industry, and researchers. We discuss the strengths and limitations of attempting to provide rapid and cost-effective estimates of soil N availability to support in-season N management decisions, specifically related to the need for supplemental N application. If barriers to adoption are overcome to facilitate broader use by farmers, such tools could balance the need for ensuring sufficient soil N supply while decreasing the risk of N losses, and helping increase N use efficiency, reduce pollution, and increase profits.

Suggested Citation

  • Giovani Preza-Fontes & Junming Wang & Muhammad Umar & Meilan Qi & Kamaljit Banger & Cameron Pittelkow & Emerson Nafziger, 2021. "Development of an Online Tool for Tracking Soil Nitrogen to Improve the Environmental Performance of Maize Production," Sustainability, MDPI, vol. 13(10), pages 1-14, May.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:10:p:5649-:d:557296
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/10/5649/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/10/5649/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Christianson, L.E. & Harmel, R.D., 2015. "The MANAGE Drain Load database: Review and compilation of more than fifty years of North American drainage nutrient studies," Agricultural Water Management, Elsevier, vol. 159(C), pages 277-289.
    2. Jakku, E. & Thorburn, P.J., 2010. "A conceptual framework for guiding the participatory development of agricultural decision support systems," Agricultural Systems, Elsevier, vol. 103(9), pages 675-682, November.
    3. Timothy M. Bowles & Shady S. Atallah & Eleanor E. Campbell & Amélie C. M. Gaudin & William R. Wieder & A. Stuart Grandy, 2018. "Addressing agricultural nitrogen losses in a changing climate," Nature Sustainability, Nature, vol. 1(8), pages 399-408, August.
    4. Michael J. Castellano & Sotirios V. Archontoulis & Matthew J. Helmers & Hanna J. Poffenbarger & Johan Six, 2019. "Sustainable intensification of agricultural drainage," Nature Sustainability, Nature, vol. 2(10), pages 914-921, October.
    5. Grace, Peter R. & Philip Robertson, G. & Millar, Neville & Colunga-Garcia, Manuel & Basso, Bruno & Gage, Stuart H. & Hoben, John, 2011. "The contribution of maize cropping in the Midwest USA to global warming: A regional estimate," Agricultural Systems, Elsevier, vol. 104(3), pages 292-296, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sisi Li & Yanhua Zhuang & Hongbin Liu & Zhen Wang & Fulin Zhang & Mingquan Lv & Limei Zhai & Xianpeng Fan & Shiwei Niu & Jingrui Chen & Changxu Xu & Na Wang & Shuhe Ruan & Wangzheng Shen & Menghan Mi , 2023. "Enhancing rice production sustainability and resilience via reactivating small water bodies for irrigation and drainage," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    2. Mohammad Valipour & Jens Krasilnikof & Stavros Yannopoulos & Rohitashw Kumar & Jun Deng & Paolo Roccaro & Larry Mays & Mark E. Grismer & Andreas N. Angelakis, 2020. "The Evolution of Agricultural Drainage from the Earliest Times to the Present," Sustainability, MDPI, vol. 12(1), pages 1-30, January.
    3. Daly, K. & Tuohy, P. & Peyton, D. & Wall, D.P. & Fenton, O., 2017. "Field soil and ditch sediment phosphorus dynamics from two artificially drained fields on poorly drained soils," Agricultural Water Management, Elsevier, vol. 192(C), pages 115-125.
    4. Soraya Tanure & Carlos Nabinger & João Luiz Becker, 2015. "Bioeconomic Model of Decision Support System for Farm Management: Proposal of a Mathematical Model," Systems Research and Behavioral Science, Wiley Blackwell, vol. 32(6), pages 658-671, November.
    5. So Pyay Thar & Thiagarajah Ramilan & Robert J. Farquharson & Deli Chen, 2021. "Identifying Potential for Decision Support Tools through Farm Systems Typology Analysis Coupled with Participatory Research: A Case for Smallholder Farmers in Myanmar," Agriculture, MDPI, vol. 11(6), pages 1-20, June.
    6. Miller, Samuel A. & Witter, Jonathan D. & Lyon, Steve W., 2022. "The impact of automated drainage water management on groundwater, soil moisture, and tile outlet discharge following storm events," Agricultural Water Management, Elsevier, vol. 272(C).
    7. Sophia Xiaoxia Duan & Santoso Wibowo & Josephine Chong, 2021. "A Multicriteria Analysis Approach for Evaluating the Performance of Agriculture Decision Support Systems for Sustainable Agribusiness," Mathematics, MDPI, vol. 9(8), pages 1-16, April.
    8. Mourtzinis, Spyridon & Andrade, José F. & Grassini, Patricio & Edreira, Juan I. Rattalino & Kandel, Hans & Naeve, Seth & Nelson, Kelly A. & Helmers, Matthew & Conley, Shawn P., 2021. "Assessing benefits of artificial drainage on soybean yield in the North Central US region," Agricultural Water Management, Elsevier, vol. 243(C).
    9. Moglia, Magnus & Alexander, Kim S. & Thephavanh, Manithaythip & Thammavong, Phomma & Sodahak, Viengkham & Khounsy, Bountom & Vorlasan, Sysavanh & Larson, Silva & Connell, John & Case, Peter, 2018. "A Bayesian network model to explore practice change by smallholder rice farmers in Lao PDR," Agricultural Systems, Elsevier, vol. 164(C), pages 84-94.
    10. Schnebelin, Éléonore, 2022. "Linking the diversity of ecologisation models to farmers' digital use profiles," Ecological Economics, Elsevier, vol. 196(C).
    11. Luisa Bettili & Eva Pek & Maher Salman, 2019. "A Decision Support System for Water Resources Management: The Case Study of Mubuku Irrigation Scheme, Uganda," Sustainability, MDPI, vol. 11(22), pages 1-19, November.
    12. Eric C. Edwards & Walter N. Thurman, 2022. "The Economics of Climatic Adaptation: Agricultural Drainage in the United States," NBER Chapters, in: American Agriculture, Water Resources, and Climate Change, pages 29-51, National Bureau of Economic Research, Inc.
    13. Liu, Lianhua & Ouyang, Wei & Wang, Yidi & Lian, Zhongmin & Pan, Junting & Liu, Hongbin & Chen, Jingrui & Niu, Shiwei, 2023. "Paddy water managements for diffuse nitrogen and phosphorus pollution control in China: A comprehensive review and emerging prospects," Agricultural Water Management, Elsevier, vol. 277(C).
    14. Tanure, Soraya & Nabinger, Carlos & Becker, João Luiz, 2013. "Bioeconomic model of decision support system for farm management. Part I: Systemic conceptual modeling," Agricultural Systems, Elsevier, vol. 115(C), pages 104-116.
    15. Phelan, David C. & Harrison, Matthew T. & McLean, Greg & Cox, Howard & Pembleton, Kieth G. & Dean, Geoff J. & Parsons, David & do Amaral Richter, Maria E. & Pengilley, Georgie & Hinton, Sue J. & Moham, 2018. "Advancing a farmer decision support tool for agronomic decisions on rainfed and irrigated wheat cropping in Tasmania," Agricultural Systems, Elsevier, vol. 167(C), pages 113-124.
    16. Liu, Wenlong & Youssef, Mohamed A. & Birgand, François P. & Chescheir, George M. & Tian, Shiying & Maxwell, Bryan M., 2020. "Processes and mechanisms controlling nitrate dynamics in an artificially drained field: Insights from high-frequency water quality measurements," Agricultural Water Management, Elsevier, vol. 232(C).
    17. Srinivasan, M.S. & Jongmans, C. & Bewsell, D. & Elley, G., 2019. "Research idea to science for impact: Tracing the significant moments in an innovation based irrigation study," Agricultural Water Management, Elsevier, vol. 212(C), pages 181-192.
    18. Hermans, Frans & Stuiver, Marian & Beers, P.J. & Kok, Kasper, 2013. "The distribution of roles and functions for upscaling and outscaling innovations in agricultural innovation systems," Agricultural Systems, Elsevier, vol. 115(C), pages 117-128.
    19. Ojeda, Jonathan J. & Volenec, Jeffrey J. & Brouder, Sylvie M. & Caviglia, Octavio P. & Agnusdei, Mónica G., 2018. "Modelling stover and grain yields, and subsurface artificial drainage from long-term corn rotations using APSIM," Agricultural Water Management, Elsevier, vol. 195(C), pages 154-171.
    20. Byrne, Ian & Healy, Mark Gerard & Fenton, Owen & Tuohy, Patrick, 2023. "Assessment of the hydraulic and filter performance of different drainage stone aggregates to elucidate an optimum size range for use in clay-textured soils," Agricultural Water Management, Elsevier, vol. 278(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:10:p:5649-:d:557296. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.