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
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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?
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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