Literature DB >> 30653830

Robotic weeders can improve weed control options for specialty crops.

Steven A Fennimore1, Matthew Cutulle2.   

Abstract

Specialty crop herbicides are not a priority for the agrochemical industry, and many of these crops do not have access to effective herbicides. High-value fruit and vegetable crops represent small markets and high potential liability in the case of herbicide-induced crop damage. Meanwhile, conventional and organic specialty crop producers are experiencing labor shortages and higher manual weeding costs. Robotic weeders are promising new weed control tools for specialty crops, because they are cheaper to develop and, with fewer environmental and human health risks, are less regulated than herbicides. Now is the time for greater investment in robotic weeders as new herbicides are expensive to develop and few in number, organic crops need better weed control technology and governments are demanding reduced use of pesticides. Public funding of fundamental research on robotic weeder technology can help improve weed and crop recognition, weed control actuators, and expansion of weed science curricula to train students in this technology. Robotic weeders can expand the array of tools available to specialty crop growers. However, the development of robotic weeders will require a broader recognition that these tools are a viable path to create new weed control tools for specialty crops.
© 2019 Society of Chemical Industry. © 2019 Society of Chemical Industry.

Entities:  

Keywords:  disruptive technology; physical weed control; robotic weeders; robotics; specialty crops

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Year:  2019        PMID: 30653830     DOI: 10.1002/ps.5337

Source DB:  PubMed          Journal:  Pest Manag Sci        ISSN: 1526-498X            Impact factor:   4.845


  1 in total

1.  High Speed Crop and Weed Identification in Lettuce Fields for Precision Weeding.

Authors:  Lydia Elstone; Kin Yau How; Samuel Brodie; Muhammad Zulfahmi Ghazali; William P Heath; Bruce Grieve
Journal:  Sensors (Basel)       Date:  2020-01-14       Impact factor: 3.576

  1 in total

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