Development of a protocol for farmer participatory validation of a corn nitrogen decision support system (DSS)

Principal Investigator

Bill Deen

Research Institution

University of Guelph

External Funding Partners

Project Start

April 2017

Project End

April 2019


  • Demonstrate on two medium textured soils in Ontario how nitrogen (N) and soil moisture supply interact across the corn lifecycle to influence yield potential.
  • Generate a peer reviewed manuscript that conclusively demonstrates that Maximum Economic Rate of Nitrogen (MERN) can be predicted from the delta-yield, which is the yield difference between zero N and a sufficient N rate, using a model based on biologically relevant parameters.
  • Develop a Corn N-Decision Support System (DSS) that considers moisture interactions with N on corn N demand and a protocol for farmer participation in validation.


  • The investigation of how moisture interacts with nitrogen (N) influences corn yield potential and corn N requirements in Ontario soils/cropping systems will help farmers better interpret the data they are collecting with precision agriculture technologies and improve their management of N inputs.
  • The development of an improved Corn N-DSS may lead to increased farm profits and minimize environmental N losses by improving the ability of farmers to predict optimal fertilizer N rates across their fields and across years.

Scientific Summary

Corn is the largest single recipient of nitrogen (N) fertilizers applied to agricultural crops, yet less than half of the N fertilizer applied to corn is recovered in grain. Greater than 50% of fertilizer N remains at risk of exiting the agro-ecosystem before crop uptake. Low fertilizer nitrogen use efficiency (NUE) is an economic inefficiency with profound implications for global N cycling and N pollution. Optimal fertilizer N rates in corn varies across years and across fields, making it difficult to predict the correct rate. The primary reason for this variation in optimum N rates is because soil moisture affects both natural soil N supply and corn N demand. Existing N recommendation systems have had limited success in predicting this variation, because the effect of moisture availability on corn N demand is often ignored. The effect moisture on corn N demand remains difficult to address, since this variation occurs after traditional side-dress timing, usually within the first two weeks of June.

The objective of this proposal is to develop a corn N decision support system (DSS) and on-farm protocol in collaboration with stakeholders. The corn N DSS will build on the "OMAFRA General Recommended Nitrogen Rates for Corn: Corn N Calculator" and will be designed to consider the effects of moisture on both soil N supply and corn N demand. Field trials on new corn hybrids will test how soil moisture affects corn N requirements at different corn stages and uptake at later stages of growth. New N datasets produced from these field trials will be added to the current Corn N Calculator and will be used to determine if delta-yield will predict Maximum Economic Rate of Nitrogen (MERN). This delta-yield approach simplifies MERN calculations, and if proven, would allow farmers to more easily measure the variability of yield response to N across their fields. The validation of a corn N DSS requires substantial amounts of data. Historically researchers have assumed this task, but with the emergence of precision agriculture/big data capabilities, farmers can now also be directly involved with data generation. A protocol will be developed so that farmers can actively participate in data generation for on-farm validation.

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