Alberta’s Olds College Builds Pan-Canadian Smart Farm Network
Olds College in Alberta, Canada, has launched a cross-country Smart Farm network designed to trial and develop agriculture technologies and practices to help Canadian farmers solve Canadian farming problems, according to Future Farming.
As with other smart farm initiatives around the globe, the end goal is to accelerate the adoption of proven agricultural technologies and improved production overall. For those working within the network, though, the breadth and scale of the Pan-Canadian Smart Farm Network makes the initiative stand out.
Olds College officially launched its local Smart Farm in June, 2018. It’s currently comprised of 3,600 acres of land for crop and forage production, 1,000-head capacity feedlot, a commercial cow-calf herd, Purebred Red Angus beef herd, sheep flock, greenhouse, and other facilities where both existing and emerging smart technologies are researched and developed.
Dr. Joy Agnew, vice-president of research at the Central Alberta post-secondary institution, says the wider Canadian Smart Farm network is a newer concept, but the idea has been in development since the formation of Olds College’s original Smart Farm. The intention was, and is, to build a collaborative framework for sharing of data and expertise to help farmers, industry, and technology developers better understand, utilize, and develop smart agriculture technologies and systems.
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Accounting for Canadian farm diversity
Currently, the national Smart Farm network is comprised of seven institutions and groups – including other post secondary institutions as well as commercial enterprises – from central Alberta to Southwestern Ontario. While some research projects are shared between locations, others are unique to specific locations.
“We realized there’s only so much one Smart farm can do in terms of supporting and accelerating the adoption of tech and practices. Canada is really agriculturally diverse…Every site brings something a little different. A requirement to joining the network is [a desire to] increase their expertise and ability to work in precision-ag space,” says Agnew.
Smart weed identification is one project which involves more than one Smart Farm participant. Both Olds College and Enterprise Machine Learning and Intelligence Initiative – a Manitoba-based commercial enterprise – are contributing to an identification database to help spur green-on-green detection of different weed species, and see how detection works across different geographies.
Read more at Future Farming.
https://www.futurefarming.com/
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