Precision ag advancement for Ontario

The story map can show multiple layers of data for each field, including elevation, soil conductivity, yield, target N rate, soil sample, and yield potential index (YPI)

Share Adjust Comment Print

Results from the 2016 and 2017 growing seasons in the Precision Agriculture Advancement for Ontario project can now be found through an interactive story map available online.

The story map can show multiple layers of data for each field, including elevation, soil conductivity, yield, target N rate, soil sample, and yield potential index (YPI). In the left margin is a quick summary of the most recent case study for each field and a quick look at the prescription map in that year.

This map is a good learning tool for anyone interested in learning more about how precision agriculture data can be interpreted and use to inform crop management decisions.

The YPI was the foundation of any prescription making process in the project. In a limited three growing season project, the project team had to start somewhere and keep a consistent approach across the years. This became an important factor in the resulting statistical analysis. A YPI takes yield data and normalizes it across years by defining grids that are above or below the average yield for the field within each year so that you can better define the spatial consistency of the performance-based management zones across the field.

Yield maps don’t explain why the zone is poor performing, therefore in this project many other soil-landscape layers were collected as well. Yield data (especially older yield data) can be quite flawed and inaccurate, so our collaborators at Niagara College developed some very rigorous cleaning tools for any precision agriculture dataset (Niagara Research Crop Portal). Niagara also programmed in some very advanced topographic elevation data modelling tools to create landform classes (e.g. foot, shoulder and side slopes).

For more on this story, visit the Field Crop News website.

Comments