New directions in weed management and research using 3D imaging

April M. Dobbs, Daniel Ginn, Soren Kelstrup Skovsen, Muthukumar V. Bagavathiannan, Steven B. Mirsky, Chris S. Reberg-Horton, Ramon G. Leon*

*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperReviewResearchpeer-review

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Abstract

Recent innovations in 3D imaging technology have created unprecedented potential for better understanding weed responses to management tactics. Although traditional 2D imaging methods for mapping weed populations can be limited in the field by factors such as shadows and tissue overlap, 3D imaging mitigates these challenges by using depth data to create accurate plant models. Three-dimensional imaging can be used to generate spatiotemporal maps of weed populations in the field and target weeds for site-specific weed management, including automated precision weed control. This technology will also help growers monitor cover crop performance for weed suppression and detect late-season weed escapes for timely control, thereby reducing seedbank persistence and slowing the evolution of herbicide resistance. In addition to its many applications in weed management, 3D imaging offers weed researchers new tools for understanding spatial and temporal heterogeneity in weed responses to integrated weed management tactics, including weed-crop competition and weed community dynamics. This technology will provide simple and low-cost tools for growers and researchers alike to better understand weed responses in diverse agronomic contexts, which will aid in reducing herbicide use, mitigating herbicide-resistance evolution, and improving environmental health.

Original languageEnglish
JournalWeed Science
Volume70
Issue6
Pages (from-to)641-647
Number of pages7
ISSN0043-1745
DOIs
Publication statusPublished - Nov 2022

Keywords

  • Integrated weed management
  • point cloud
  • remote sensing
  • stereo vision
  • structure-from-motion

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