Economics of field size and shape for autonomous crop machines

Author:

Al-Amin A. K. M. AbdullahORCID,Lowenberg‑DeBoer James,Franklin Kit,Behrendt Karl

Abstract

AbstractField size and shape constrain spatial and temporal management of agriculture with implications for farm profitability, field biodiversity and environmental performance. Large, conventional equipment struggles to farm small, irregularly shaped fields efficiently. The study hypothesized that autonomous crop machines would make it possible to farm small, non-rectangular fields profitably, thereby preserving field biodiversity and other environmental benefits. Using the experience of the Hands Free Hectare (HFH) demonstration project, this study developed algorithms to estimate field times (h/ha) and field efficiency (%) subject to field size and shape in grain-oil-seed farms of the United Kingdom using four different equipment sets. Results show that field size and shape had a substantial impact on technical and economic performance of all equipment sets, but autonomous machines were able to farm small 1 ha rectangular and non-rectangular fields profitably. Small fields with equipment of all sizes and types required more time, but for HFH equipment sets field size and shape had least impact. Solutions of HFH linear programming model show that autonomous machines decreased wheat production cost by €15/ton to €29/ton and €24/ton to €46/ton for small rectangular and non-rectangular fields respectively, but larger 112 kW and 221 kW equipment with human operators was not profitable for small fields. Sensitivity testing shows that the farms using autonomous machines adapted easily and profitably to scenarios with increasing wage rates and reduced labour availability, whilst farms with conventional equipment struggled. Technical and economic feasibility in small fields imply that autonomous machines could facilitate biodiversity and improve environmental performance.

Funder

Harper Adams University

Publisher

Springer Science and Business Media LLC

Subject

General Agricultural and Biological Sciences

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