Westminster, Colorado, USA
15 May 2024

Technical competencies among weed scientists
will likely need to expand quickly to accomplish future research priorities, according to recent results from a Weed Science Society of America (WSSA) online survey. The survey asked U.S. and Canadian leaders in weed science to identify pertinent weed research topics for the next five to 10 years. The survey also asked these leaders to identify expertise and funding gaps that are currently lacking to address the newly identified research priorities.

Survey respondents identified one particular concern related to skillsets needed for precision weed management and robotics. Precision weed management combines artificial intelligence (AI) and machine learning with ground robotics and unmanned aerial vehicle (UAV) technologies to map and identify weeds and implement management solutions for farmers.

“We see gaps in expertise in these areas,” says Vijay Singh, Ph.D., Virginia Tech Weed Science Assistant Professor, whose research team uses machine learning systems to generate weed databases. “That’s especially true with UAV-based herbicide applications, which require specific licenses and training, and data analytics expertise,” he emphasizes. “We do not find many people who possess these attributes. A similar challenge is finding engineering graduates—who have knowledge in areas such as AI and machine learning and are ready to work on interdisciplinary research.”

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Website: http://www.wssa.net

Published: May 16, 2024