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

    Abstract:

    The loss of nitrogen (N) from crop fields 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 in addition to loss of revenue for the producer. 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 sought 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. Full-field variable N rate experimentation conducted with precision agriculture technologies (VRA, yield monitors and protein sensors) numerous GIS, climate, and remote-sensing based covariates andspatiotemporally dense soil and plant sampling and N analysis were used to construct equations to predict optimum N rates in dryland small grain agroecosystems. The predictive equations were used in a software developed for this project to create site-specifically optimized nitrogen fertilizer application rates based on maximized net-return and minimized nitrate pollution under different climatic and weather scenarios. Site-specific N fertilizer management were compared with other application approaches based on net returns to producers and pollution potential tradeoffs. In all fields, adoption of site-specific N fertilizer management increased farmer profits compared to a uniform farmer selected N fertilizer rates. Using site-specific N management also tended to reduce the amount of total N applied across most fields. Annual workshops and reports for producers and the public happened every year to disseminate research results and a software package that automates the data management, analysis, and generation of optimized prescriptions has been developed. Future work will involve migrating the software package from the R environment into a web-based application that is user-friendly and accessible for farmers and crop consultants.

    Project objectives:

    The primary research goal was to estimate nitrogen use efficiency (NUE) from each point in a wheat field where yield is reported by the combine yield monitor and grain protein analyzer. This required measurement of NUE in representative dryland wheat systems of Montana and extrapolating the losses using a predictive model. To achieve this goal, the specific objectives were:

    • 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 NUE after soil and plant inventories by calculating a N mass balance using intensive soil and plant tissue sampling.
    • Predict NUE at each yield/protein monitored point using geostatistical techniques.
    • Quantify and package site-specific optimized N fertilizer application rates based on maximized net return and minimized pollution potential via 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.