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Machine-Vision Technology Shows Promise to Reduce Herbicide Use

Farmers and land-managers seeking to reduce their herbicide applications now have another promising option via machine-vision technology. That's the summary from a recently published research article in Weed Technology.

"Our research showed that, on average, this technology's targeted sprays saved a range of 28.4 to 62.4% on postemergence herbicides compared to traditional broadcast applications," says Tristen Avent, University of Arkansas, Senior Graduate Assistant in the Crop, Soil, and Environmental Sciences Department, and corresponding author of the study.

"In addition to significant opportunities to lower herbicide costs and improve profits, our research also showed that the targeted applications from machine-vision technology can be utilized to provide some soybean health benefits and improve ."

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Developing disease resistance in new wheat varieties

Video: Developing disease resistance in new wheat varieties


Dr. Colin Hiebert, research scientist with Agriculture and Agri-Food Canada – Morden, is focused on developing new tools that wheat breeders can use to improve, diversify and strengthen disease resistance in new wheat varieties. This includes new genomic tools that address resistance to five diseases including: Fusarium head blight, leaf rust, stripe rust, stem rust and common bunt.

Learn more about how research conducted at AAFC-Morden will impact wheat variety development, production and profitability for the future. This research is part of the Canadian National Wheat Cluster and funding is provided through the Sustainable Canadian Agricultural Partnership, Agriculture and Agri-Food Canada, Alberta Grains, Sask Wheat, Manitoba Crop Alliance, Western Grains Research Foundation and Canadian Field Crop Research Alliance.