The Weed Science Society of America (WSSA) recently conducted a survey among U.S. and Canadian weed science leaders to highlight the need for expanded technical competencies in weed science. According to the survey, precision weed management and robotics emerged as crucial areas requiring expertise in artificial intelligence (AI), machine learning, and UAV technologies. However, there is a notable gap in these skillsets among current leaders, especially when it comes to UAV-based herbicide applications that require specific licenses and training, and data analytics expertise.
Virginia Tech Weed Science Assistant Professor, Vijay Singh, Ph.D., emphasized this point in a press release, stating that “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.”
Survey findings show a shift in research priorities, with herbicides ranking lower than cultural and preventative weed management and precision weed management. Despite advancements like UAV-based herbicide applications showing promise, public funding for weed research has declined, raising concerns about the lack of support for vital areas like integrated weed management. Weed scientists emphasize the necessity for increased public funding to address these challenges and accelerate the development and application of AI and machine learning technologies in weed management.
Brian German, Ag News Director at AgNet West, shared more on this report, highlighting the importance of expanding technical competencies in weed science to address current challenges and opportunities in the industry.
