Techno-economic and environmental assessment of next-generation battery-powered farming robots

Decarbonizing agriculture without compromising productivity is a major challenge under rising input costs and labor scarcity. Autonomous battery-powered agricultural robots (ABARs) could help by reducing dependence on conventional machinery and enabling more precise application of inputs, but their system-level economic and environmental performance remains unclear. Here, we integrate total cost of ownership and life cycle assessment to evaluate a small ABAR for cradle-to-farm-gate crop production of strawberries, onions, lettuce, and peanuts under organic and non-organic management. Across modeled scenarios, benchmarked costs range from 76% below to 17% above literature-based reference ranges, while greenhouse-gas emissions fall within or below reported ranges. Variable inputs dominate both outcomes, contributing 72-90% of costs and 72-95% of global-warming impacts, with seeds, fertilizers, and irrigation water as main drivers. These results suggest that ABAR value depends less on the platform than on the ability of autonomous operation to reduce input use and labor demand.

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Publication Details

Journal
Nature Communications
Published
2026-11-02
DOI
https://doi.org/10.1038/s41467-026-78281-7
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
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article

Techno-economic and environmental assessment of next-generation battery-powered farming robots

Moritz Gutsch, Thomas P. Hendrickson, Stephan von Delft, Simon Schlehuber et al.
2 links
Nature Communications
Smart Agriculture and AI
article

Techno-economic and environmental assessment of next-generation battery-powered farming robots

Moritz Gutsch, Thomas P. Hendrickson, Stephan von Delft, Simon Schlehuber, Luca Stegemann
article en

Abstract

Decarbonizing agriculture without compromising productivity is a major challenge under rising input costs and labor scarcity. Autonomous battery-powered agricultural robots (ABARs) could help by reducing dependence on conventional machinery and enabling more precise application of inputs, but their system-level economic and environmental performance remains unclear. Here, we integrate total cost of ownership and life cycle assessment to evaluate a small ABAR for cradle-to-farm-gate crop production of strawberries, onions, lettuce, and peanuts under organic and non-organic management. Across modeled scenarios, benchmarked costs range from 76% below to 17% above literature-based reference ranges, while greenhouse-gas emissions fall within or below reported ranges. Variable inputs dominate both outcomes, contributing 72-90% of costs and 72-95% of global-warming impacts, with seeds, fertilizers, and irrigation water as main drivers. These results suggest that ABAR value depends less on the platform than on the ability of autonomous operation to reduce input use and labor demand.

Nature CommunicationsVol. 17(1)
University of Münster (DE), University of Glasgow (GB), University of California, Davis (US)
Climate action, Zero hunger, Responsible consumption and production, Affordable and clean energy, Industry, innovation and infrastructure
Openalex Percentile: Top 17%
Smart Agriculture and AI
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