Determining the utility of an unmanned ground vehicle for weed control in specialty crop systems

Authors

  • Matthew A. Cutulle Clemson University, Coastal Research and Education Center, Charleston, SC https://orcid.org/0000-0002-3572-2498
  • Joe Mari Maja Clemson University, Coastal Research and Education Center, Charleston, SC

DOI:

https://doi.org/10.4081/ija.2021.1865

Keywords:

Robotic weed control, unmanned ground vehicles, specialty crops.

Abstract

Specialty crop herbicides are not a target for herbicide discovery programs, and many of these crops do not have access to relevant herbicides. High-value fruit and vegetable crops represent high potential liability in the case of herbicide-induced crop damage and low acres for revenue. Labour shortages and higher manual weeding costs are an issue for both conventional and organic specialty crop growers. 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. However, many of the robotic weeders are too expensive for small growers to use. In the future, greater investment into robotic weeders for small-scale growers will be important. The Clearpath robotics platform Husky may provide a cheap and autonomous way to control weeds in small diversified specialty crop farms. Being able to work autonomously in multiple soil moisture environments is the driving factor behind optimizing the Husky platform for weed control. Research has been conducted to evaluate the impact of soil moisture and mechanical actuator on mobility and weed control. Though weed control was not commercially acceptable in these studies, future optimizations to the Husky robotics platform can achieve commercial success.

Highlights
- Specialty crop production is labor-intensive and vulnerable to rising labor expenses.
- Robotic weeders are promising weed control tools, with fewer environmental and human health risks.

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References

Avo. Available from: https://www.ecorobotix.com/en/avoautonomous-robot-weeder/ Last accessed: 02 May 2021.

Bangert W, Kielhorn A, Rahe F, Albert A, Biber P, Grzonka S, 2013. Field-robot-based agriculture: “RemoteFarming.1” and “BoniRob-Apps”. pp 439-445 in AgEng, Internationale Tagung Land.Technik, Düsseldorf, Germany: VDI-Verlag.

Cutulle M, Armel G, Brosnan J, Kopsell D, Hart W, Vargas J, Gibson L, Messer R, McLemore A, Duncan H, 2013. Evaluation of a cryogenic sprayer using liquid nitrogen and a ballasted roller for weed control. J. Testing Evaluat. 41:869-74.

Cutulle M, Campbell H, Couillard D, Farnham M, 2019. Pre-plant herbicide application and cultivation to manage weeds in southeastern broccoli production. Crop Prot. 124:104862.

Clearpathrobotics. Available from: https://www.clearpathrobotics.com Accessed: 02 May 2021.

Ditlevsen K, Denver S, Christensen T, Lassen J, 2020. A taste for locally produced food-values, opinions and sociodemographic differences among ‘organic’ and ‘conventional’ consumers. Appetitie. 147:104544.

Fennimore SA, Slaughter DC, Siemens MC, Leon Saber MN, 2016. Technology for automation of weed control in specialty crops. WeedTechnol. 30:823-37.

Fennimore S, Cutulle M, 2019. Robotic weeders can improve weed control options for specialty crops. Pest Manage. Sci. 75:1767-74.

Hamann E, 2020. Amid rising costs and limited availability, farmers struggle to find enough workers. Business of Agriculture 2020. Available from: https://www.bizjournals.com/ sacramento/news/2020/04/24/amid-rising-costs-and-limited-availability-farmers.html Accessed: 02 May 2021.

Lanini WT, LeStrange M, 1991. Low-input management of weeds in vegetable fields. Calif. Agric. 45:11-3.

Lamm RD, Slaughter DC, Giles DK, 2002. Precision weed control system for cotton. Trans. ASAE. 45:231-8.

McElroy JS, 2014. Vavilovian Mimicry: Nikolai Vavilov and his little-known impact on weed science. Weed Sci. 62:207-16.

Mennan H, Ngouajio M, Isik D, Kaya E, 2009. Effects of alternative winter cover cropping systems on weed suppression in organically grown tomato (Solanum lycopersicum). Phytoparasitica. 37:385-96.

Shafiekhani A, Kadam S, Fritschi BF, DeSouza NG, 2017. Vinobot and vinoculer: Two robotic platforms for high-throughput field phenotyping. Sensors 17:214.

Slaughter DC, Giles DK, Fennimore SA, Smith RF. 2008. Multispectral machine vision identification of lettuce and weed seedlings for automated weed control. Weed Technol. 22:378-84.

Slaughter DV, Lanini WT Giles DK, 2004. Discriminating weeds from processing tomato plants using visible and near-infrared spectroscopy. Trans. ASAE 47:1907-11.

Slaughter DC, Chen P, Curley RG, 1999. Vision guided precision cultivation. Precis. Agric. 1:199-216.

Steponavich S, Datta A, Neilson B, Bruening C, Shapiro CA, Gogos G, Knezevic SZ, 2016. Effectiveness of flame weeding and cultivation for weed control in organic maize. Biol. Agric. Hortic. 32:47-62.

USDA NASS, 2020. United States Department of Agriculture - National Agricultural Statistic Service. Available from: https://www.nass.usda.gov

USDA ERS, 2020. United States Department of Agriculture - Economic Research Service. USDA ERS - Farm Labor. Accessed: November 2020.

USGS United States Geological Survery, 2019. Available from: https://www.usgs.gov

Weedzapper. Available from: https://theweedzapper.com/ Accessed: 02 May 2021.

Xarvio. Available online: https://www.xarvio.com/us/en.html Accessed: 02 May 2021.

Young S, Kayacan E, Peschel J, 2019. Design and field evaluation of a ground robot for high-throughput phenotyping of energy sorghum. Prec. Agric. 20:697-722.

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Published

03-09-2021

How to Cite

Cutulle, M. A., & Maja, J. M. (2021). Determining the utility of an unmanned ground vehicle for weed control in specialty crop systems. Italian Journal of Agronomy, 16(4). https://doi.org/10.4081/ija.2021.1865