SEE THE FIELD IN A NEW WAY
BY ROY MAKI • PHOTO COURTESY OF OLDS COLLEGE
On the Olds College Smart Farm, data is rolling in from an ongoing research project that utilizes the Raven Augmenta Field Analyzer. This camera vision machine learning technology senses crop conditions using digital imagery to adjust input application during field operations. Unlike current methods that rely on pre-determined maps, the camera uses an algorithm to make instantaneous decisions about the rate of inputs to apply on crops.
The Smart Agriculture Applied Research team at the Olds College Centre for Innovation has now completed the first year of a two-year trial that outfits a sprayer with the Field Analyzer to apply a crop desiccant. As the sprayer moves through the field, the system continuously performs optical analysis and signals the sprayer controller to adjust desiccant rates as needed in real time. The Field Analyzer’s camera focuses on the area approximately 15 metres ahead and 42 metres wide while it analyzes field imagery data to determine the correct application rate.
This past growing season, the experiment was conducted on wheat and canola using four treatments and four replications each for a total of 32 plots sprayed. The four treatments included a zone variable rate, Augmenta’s live variable rate, a flat rate and a negative control, where zero rate or no desiccant was applied. Field Analyzer results were compared to traditional application methods. Data collection focused on the grain quality—moisture, grading dockage, yield and green percentage for canola.
Data gathered from the trials is being used to calculate the return on investment based on the various application methods. The process will identify the potential for desiccant rate reductions that allow farmers to save money.
Olds College researchers have also gained hands-on experience with the technology. They have found its interface intuitive and its data collection and storage processes easy to navigate. The Analyzer’s scout mode proved to be a valuable tool when applying pesticides to monitor crop health and maturity, and its periodic snapshot feature provided additional records of field conditions.
Valuable insights from this first year of research will help to refine and strengthen the Field Analyzer research to be carried out in the second season of the project. The two-year window will allow data to be gathered in a variety of field conditions and supply a greater amount of data on input variability and cost per acre. In 2026, the project will utilize a larger field to support expanded data collection.
Through a previous four-year study of autonomous agricultural equipment for broadacre crop production, Olds College has built a strong partnership with Raven, a brand of CNH Industrial. Olds College greatly appreciates Raven’s collaboration and continued support.
This applied research project exemplifies how Olds College supports the development and testing of innovative agricultural technology in its work with companies across the world. Visit oldscollege.ca/smart-farm for updates on the Raven Augmenta Field Analyzer project and the full range of Olds College research activities.
Roy Maki is research project manager with Smart Agriculture Applied Research at Olds College Centre for Innovation.
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