An economic, environmental, and social analysis of autonomous mechanical weeding in sugar beet farming

Abstract

Abstract Weeding robots are expected to decrease herbicide use on conventional farms and reduce manual labor on organic farms. A multi‐objective linear programming model was used to compare the economic, environmental, and social performance of robotic and non‐robotic weed control in conventional and organic sugar beet ( Beta vulgaris L.) production in Bavaria, Germany. On the conventional farm, the weeding robot generated a mean gross return of €58,612 year −1 compared to €57,728 year −1 when using herbicide spraying. However, the mean return on total costs for the weeding robot was negative (€−2750 year −1 ) and substantially lower than the €8663 year −1 achieved with herbicide spraying. In organic farming, this technology was more profitable than non‐robotic mechanical weeding, generating a mean gross return of €73,098 year −1 and a mean return on total costs of €10,373 year −1 . The corresponding figures for non‐robotic mechanical weeding were € 59,176 and €7,577 year −1 . The carbon emission intensity of sugar beet was comparable between weed control strategies on the conventional farm and marginally lower for robotic weeding on the organic farm. On both farms, autonomous mechanical weeding used more skilled labor due to routine supervision, field‐to‐field transport, and human intervention requirements. Higher skilled labor time with robotics negatively affected farmers’ work–life balance. Investment cost, supervision and human intervention requirements, technology specialization, and logistics of field operations were identified as the main barriers to adoption of the tested weeding robot. These barriers should be prioritized when developing future autonomous farm equipment.