Nitrogen Fertilizer Management Based on Site-Specific Maximized Profit and Minimized Pollution

Project Overview

GW19-190
Project Type: Graduate Student
Funds awarded in 2019: $24,992.00
Projected End Date: 01/31/2022
Host Institution Award ID: 4W8087
Grant Recipient: Montana State University
Region: Western
State: Montana
Graduate Student:
Principal Investigator:
Dr. Stephanie Ewing
Montana State University
Principal Investigator:

Information Products

Commodities

  • Agronomic: wheat

Practices

  • Crop Production: application rate management, fertilizers, nutrient cycling, nutrient management
  • Education and Training: decision support system, on-farm/ranch research, participatory research
  • Farm Business Management: budgets/cost and returns
  • Natural Resources/Environment: habitat enhancement
  • Production Systems: agroecosystems, dryland farming
  • Soil Management: nutrient mineralization, soil analysis, soil chemistry, soil quality/health

    Proposal abstract:

    The loss of nitrogen (N) from agricultural systems is a national issue that plagues not only terrestrial and aquatic ecosystems, but human and animal health as well. The over application of fertilizer on farms across the country results in N that is left unused by crops, acidifying soils and flowing into waterways. Using variable rate N application (VRA) to site-specifically apply fertilizer, rather than application of a uniform rate, has potential to reduce the amount of N applied to fields and increase grower profits. This study seeks to determine the amount of nitrogen fertilizer to place at each point in the field to maximize profit and at the same time minimize nitrogen lost to leaching through the soil profile. I will use full-field Variable N rate experimentation conducted with precision agriculture technologies (VRA, yield monitors and protein sensors) numerous GIS, climate, and remote-sensing based covariatesand 15N isotope tracking to construct equations that will allow prediction of optimum N rates in dryland small grain agroecosystems.The predictive equations will be used in a software developed for this project to to create site-specifically optimized nitrogen fertilizer application rates based on maximized net-return and minimized nitrate pollution under different climatic and weather scenarios and to generate nitrate-loss potential maps at subfield scales. Site-specific N fertilizer manageent will be compared with other application approaches based on net returns to producers and polution potential tradeoffs. Annual workshops and reports for producers and the public will happen every year in order to disseminate research results. If site-specific management indicates a decrease in nitrogen pollution and is economically efficient, it could spur a major shift of growers statewide on the path to more sustainable agriculture.

    Project objectives from proposal:

    The research question pursued is: Can full-field experimentation conducted with precision agriculture technologies, along with modern analysis techniques, offer an efficient way to reduce N pollution in dryland small grain agroecosystems?

    My primary research goal is to estimate the N fertilizer loss (N not taken up by plants) from each point in a wheat field where yield is reported by the combine yield monitor and grain protein analyzer. This will require measurement of N loss under the range of conditions encountered and extrapolating the losses using predictive models that I will develop. To achieve this goal, my specific objectives are:

    • Quantify the relationship of crop (dryland winter wheat) yield and grain protein with N fertilizer rates from variable rate application (VRA) on-farm experiments (OFE) utilizing grain yield combine-harvester monitor data and protein analysis along with GIS, climate, and remote sensing-based covariates.
    • Determine the fate of site-specific fertilizer N applications in soil and crops at the subfield scale using 15N labeled (5%) urea fertilizer and deep coring.
    • Extrapolate N loss to each yield/protein monitored point using geostatistical techniques.

    Quantify and package site-specific optimized N fertilizer application rates and loss potential maps based on maximized net return and minimized pollution potential by leaching, surface runoff and atmospheric loss into a field-specific software application available for use by growers.

    Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.