Work

The economics of US row crop production with large-scale autonomous machines

Year: 2025

Type: article

Abstract: Labor challenges are underpinning large multinational farm machine manufacturers' development of autonomy solutions for their large-scale machine offerings. This study simulates a linear optimization model to examine the economics of large-scale autonomous machines for a Midwest US rotational maize and soybean farm in the US Corn Belt. The hypothesis that large-scale autonomous machines are an economically viable option for US row crop farms with severe labor shortages is supported. However, in most cases, with current technology and technology pricing models and for farms with reliable labor, conventional mechanization is the most profitable alternative. Important factors in the economic viability of large-scale autonomy include technology subscription fees, field efficiency, and required human supervision time. As the factors evolve, farm expansion will likely be an early scenario in which large-scale autonomous farm machines are profitable

Source: Smart Agricultural Technology

DOI: 10.1016/j.atech.2025.101599

Authors: Joshua Strine, Chad Fiechter, James Lowenberg-DeBoer

Institutions: Purdue University West Lafayette, Harper Adams University

Language: English

Topic: Agricultural Engineering and Mechanization

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Zero hunger, Decent work and economic growth, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,770