Operational, Economic, and Environmental Assessment of an Agricultural Robot in Seeding and Weeding Operations

Mahdi Vahdanjoo*, René Gislum, Claus Grøn Sørensen

*Corresponding author for this work

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

11 Citations (Scopus)
151 Downloads (Pure)

Abstract

The development of robotic‐based agricultural machinery systems has significantly increased in recent years. Many autonomous systems have not yet been measured based on sustainability and economic performances, even though automation is regarded as an opportunity to increase safety, dependability, productivity, and efficiency. The operational aspect, economic viability, and environmental impact of replacing conventional machinery with robotized alternatives are the primary focus of this study. The robot considered in this research is designed for extensive field‐work, where PTO and external hydraulics are required. This robot is equipped with two 75 (hp)Kubota diesel engines with a total engine gross power of up to 144 (hp). Both robotic system and
conventional machinery were described, and different scenarios were used to examine various operational and environmental indicators, as well as individual cost elements, considering various field sizes and working widths of implements used in seeding and weeding operations. The findings demonstrate that the robotic system outperforms conventional machinery in terms of operational
efficiency by as much as 9%. However, the effective field capacity comparison reveals that the conventional system has a field capacity that is up to 3.6 times greater than that of the robotic system.
Additionally, the total cost per hour of the robotic system is up to 57% lower than that of the conventional system. The robotic system can save up to 63.3% of fuel during operation, resulting in the same percentage reduction in CO2 emissions as the conventional system, according to a comparison of fuel consumption.
Original languageEnglish
Article number5
JournalAgriEngineering
Volume5
Issue1
Pages (from-to) 299–324
Number of pages26
ISSN2624-7402
DOIs
Publication statusPublished - Mar 2023

Keywords

  • Economic assessment
  • Environmental impact
  • Operational management
  • Precision Agriculture
  • Sustainability
  • robotic systems

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