Farmer perspectives on digital agriculture in the US Midwest
Abstract Digital agriculture is emerging as the next green revolution, helping farmers to make data‐informed decisions that increase productivity and optimize resource use. Understanding farmers' perceptions of current barriers and future opportunities for technology adoption is necessary for sustainable agriculture. This study aimed to identify trends and patterns in farmers' perceptions of digital agriculture technology adoption. A survey was distributed across most of the Midwest and adjacent region of the United States, collecting 247 responses. Results showed 93% used digital agricultural technology, with long‐term (>10 years) adoption of auto‐guidance (59%), yield mapping (56%), and variable rate technologies (36%). Perceived financial profitability was a key driver of technology adoption (36%), followed by input optimization (18%) and productivity (16%). The main barrier was high cost relative to perceived benefit (31%), followed by small farm size (16%) and equipment incompatibility (14%). Environmental benefits emerged as a tertiary motivator, and their lower prioritization suggests that farmers focus more on the economic dimension of sustainability when adopting new technologies. Fertilizer efficiency (27%), pest management (18%), and water management (13%) were top challenges to address. Findings suggest that digital agriculture adoption is primarily driven by economic considerations, with cost‐benefit analysis and entry costs as key determinants in US Midwest and adjacent region farming systems.
Authors
- André Fróes de Borja Reis
- Priscila B. Cano (ORCID: https://orcid.org/0000-0003-2337-1931)
- Guillermo R. Balboa (ORCID: https://orcid.org/0000-0003-3819-5088)
- Bruce Erickson (ORCID: https://orcid.org/0000-0002-4389-4986)
- German Mandrini (ORCID: https://orcid.org/0000-0001-5923-6104)
- Jianfeng Zhou (ORCID: https://orcid.org/0000-0002-7127-1428)
- Ana Julia Paula Carcedo (ORCID: https://orcid.org/0009-0008-1207-1312)
- John P Fulton (ORCID: https://orcid.org/0000-0002-7114-8390)
- Matthew E. Carroll (ORCID: https://orcid.org/0000-0002-5224-7326)
- Péter Kovács (ORCID: https://orcid.org/0000-0002-0772-9721)
- Ignacio Antonio Ciampitti (ORCID: https://orcid.org/0000-0001-9619-5129)
- Steve Phillips (ORCID: https://orcid.org/0009-0003-5563-924X)
- Ajay Sharda
- Ken Sudduth
- Dennis Buckmaster
- Kent Shannon
- Elizabeth Hawkins
- Brian Arnall
Institutions
- University of Nebraska–Lincoln (US)
- Oklahoma State University (US)
- South Dakota State University (US)
- Kansas State University (US)
- Purdue University West Lafayette (US)
- Cropping Systems Research Laboratory (US)
- Quality Research (US)
- Iowa Soybean Association (US)
- The Ohio State University (US)
- North Dakota State University (US)
- University of Missouri (US)
Publication Details
- Journal
- Agronomy Journal
- Published
- 2026-01-01
- DOI
- https://doi.org/10.1002/agj2.70268
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- U.S. Department of Agriculture
- Purdue University