Variable N Fertility Management of Canola at the Field Scale, Based on Analysis of Yield Maps and Spatial and Statistical Variability of Soil Test N and P

Agronomic Practices  Agronomy Research 
Start Date
End Date
Principal Investigator
Dr. Alan Moulin - AAFC (Brandon)
Dr. Mohammad Khakbazan - AAFC (Brandon), Rejean Picard - Manitoba Agriculture, Food and Rural Initiatives, Steve Sager - AAFC (Morden), Don Cruickshank - Deerwood Soil and Water Management Association, Ken Coles - Farming Smarter, Dr. Stu Brandt - Northeast Agriculture Research Foundation
MCGA Funding
Total Project Funding
External Funding Partners
Alberta Canola, SaskCanola, Canola Council of Canada, Canadian Agricultural Partnership

Research Objective

  • Whether variable rate N management based on management zones (that were categorized by a series of yield maps over time) would  increase canola yield in areas with consistently high production 
  • Economic return and efficiency of fertilizer use from variable rate management of N 
  • Variability related to current soil test recommendations 
  • Digital elevation, landform and remote sensing data corresponding with canola yield

Project Description

The major objective of this project was to determine if variability of nitrogen (N) fertilizer according to management zones (based on statistical analysis) would increase canola yield in areas with consistently high production. Factors such as the digital elevation of the fields, overall landform, and remote sensing data were also to be collected for analysis to determine patterns in canola yield. Fields were selected at seven different sites with one or more field-scale trials based on the availability of 3 to 5 years of GPS located yield monitor data to determine management zones. The management zones were then categorized with high or very high yields in the high zone; average yield in the average zone; and low yields in the low zone. Fertilizer treatments were randomly located across management zones, with either 0, 50, 100, or 150% of N fertilized recommended being applied. 


The result of this project was a new method for variably applying N fertilizer based on temporal and spatial variability of historical crop yields, and this knowledge was made available to the public. It was clear that analysis with fields as a variable in the statistical model improved interpretation of the effects of management zones and fertilizer treatments, particularly for the year 2015. Yield zones and fertilizer management  influenced canola yield in analyses but were highly influenced by variability between farms. The absence of differences between higher fertilizer rates across most zones indicated a need to revisit soil test recommendations.

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