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Field trials on the farm follow applied research projects once they leave the lab bench. Field trials are a great way to gather on-farm perspectives, and the province-wide network of research centres owned by the Government of Ontario through its agency, the Agricultural Research Institute of Ontario, is home to many innovative field studies.

A complementary approach is for producers to take the lead in developing research questions and conducting projects on their own farms, working in cooperation with a support organization.

Dr. Leith Deacon, professor in the School of Environmental Design and Rural Development, conducted a large quantitative survey aimed to provide data to policy makers on how rural populations in Canada are underrepresented in COVID-19 emergency management policies. Thanks to Alliance funding, Deacon will be expanding his project to at least six additional rural counties in Ontario.

Soil mapping provides farmers and policy makers with detailed information on the condition and characteristics of land. Traditional soil mapping, in which a surveyor collects soil samples and maps their locations, was an important first step toward better soil conservation and environmental sustainability. However, it doesn’t provide the kind of broad picture now possible through digital soil mapping based on greater computational power and availability of environmental data.

For decades, researchers carrying out long-term crop rotation trials have found that diversification improves yield stability. Now, a long-term study is under way at the Ontario Crops Research Centre – Elora using new technology to investigate the mechanisms at play in the soil that account for these improvements. The ultimate goal is to determine best practices for producers.

The Ontario government is investing $7 million into agri-food research projects that will support greater environmentally friendly agricultural practices, protect livestock health and welfare, and stimulate economic growth within the agri-food sector and Ontario’s rural communities.

Through the Ontario Agri-Food Innovation Alliance Ontario is supporting advanced agri-food research in collaboration with the University of Guelph on projects that include:

Apple crops rely on pollinators to reproduce, so growers often spend thousands of dollars every year to house and manage honeybee colonies. However, previous studies have shown that, when diverse and abundant, wild bees can provide significant pollination services in orchards. Depending on the apple variety, growers may be able to use fewer hives or none at all.

From mid-summer until the following spring, some Ontario fields lie fallow while others are covered with crops designed to rejuvenate the soil. University of Guelph researchers are investigating various combinations of cover crops to see which ones offer the best environmental and economic improvements. This long-term study is being conducted at the Ontario Crops Research Centre sites in both Elora and Ridgetown, coordinated by plant agriculture professors Dr. Manish Raizada and Dr. Dave Hooker, respectively.

That silky, gold-coloured tuft you normally discard along with your corncob husks is worth more than you think.

For the first time, an Alliance research team has shown corn silks naturally contain diverse microbes, a finding that may point to a new strategy to protect the cob from fungal infections.

Their discovery of this corn silk microbiome may help improve breeding and farming practices to avert costly and harmful fungal outbreaks, protect one of the world’s three most important food crops and increase food security globally.

Since 2014, the Gryphon’s LAAIR (Leading to the Accelerated Adoption of Innovative Research) program has offered researchers who identify market potential in their agri-food inventions an opportunity to understand how their ideas can contribute to Ontario’s $37 billion agri-food industry.

A veterinary and computer science research team led by professors Dr. Rozita Dara (School of Computer Science) and Dr. Shayan Sharif (Department of Pathobiology) has developed a system using artificial intelligence (AI) and machine learning to detect outbreak locations and predict infectious diseases’ capacity to spread further.