Olds College Centre for Innovation (OCCI) and Alberta Grains are collaborating with producer partners to introduce a new on-farm research method in central Alberta. The project uses the On-Farm Precision Experimentation methodology defined by Data-Intensive Farm Management, focusing on different wheat seed and nitrogen rates over two years.
The Data-Intensive Farm Management platform uses machine learning to plan and analyze field-scale Latin square or checkerboard plot trials, providing insights into crop yield responses. The Data-Intensive Farm Management project is led by Dr. David Bullock from the University of Illinois, who has been conducting field trials using this method since 2016.
Project Goals
Test if the methodology inherent in the Data-Intensive Farm Management tool is valid, efficient and effective to conduct on-farm precision experiment trials in Alberta through the on-farm trial question: What is the optimal seeding and fertilization application rate, and does this optimal rate change significantly within a field?
Provide a recommendation on how Data-Intensive Farm Management can be a valid approach to generate regional recommendations by aggregating individual field data from multiple locations and multiple years.
Funders/Partners: RDAR, Alberta Grains