How AI could help farming become more efficient and sustainable

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At Nature Fresh Farms in Leamington, Ont., there’s something new amid the rows of tomatoes, cucumbers, peppers and strawberries.

Smoke from wildfires fills the air as a woman harvests a field of hay on a farm in Northern B.C., on Thursday, Aug. 16, 2018. THE CANADIAN PRESS/Darryl Dyck

The next phase of that technology involves AI models using that data to make inferences, predictions and even decisions, said Keena — and AI enables agriculture to become “hyper-optimized” down to a more specific level than before. As an example, his group is invested in a company called Croptimistic, Petras said, which gathers data from the field to detect pests, changes in crop colour, and other potential stressors on the crop.

Another one of the smart farms is at Olds College, where Felippe Karp is conducting research into how to develop standards for data collection and processing to build AI models. “And so we can't ask them to take big risks on integrating new technologies at scale as part of their operations in things that are unproven.”

Farmers can be resistant to sharing their own data, said Karp: “That's one of the challenges we face when we talk about developing more complex models.”“Farmer engagement is absolutely critical” to developing AI tools for agriculture, he said, which can include field demonstration days, conferences and workshops, he said.

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