Autonomous machine systems to increase productivity, efficiency of crop production - Land-Grant Impacts

tractor with a mechanical mower mowing grass on the side of the asphalt road

Autonomous machine systems to increase productivity, efficiency of crop production

Agricultural Systems, Story 2025, Artificial Intelligence and Emerging Technologies, Crop Management, Indiana, North Central, Precision Agriculture, Profitability/Competitiveness, Purdue University, Research

Purdue University in Indiana is leading an autonomous machinery project to enhance productivity, efficiency and elevate profitability by alleviating labor workload.

Autonomous machines can capture data and help overcome labor-related limitations. This data capture helps farmers with comprehensive insights and data-driven decision making.

Purdue has used an autonomous inner-row sensor platform, harvest logistics tracking and autonomous roadside mowing as part of its response work.

The inner-row sensor platform is a crop rover capable of carrying sensor payloads through row crop fields throughout the growing season. The harvest logistics tracking includes decision support tools to help operators increase system efficiencies.

Its autonomous roadside mowing are operations conducted by state and private landowners to maintain road shoulders and maintain line of sight. This will offer potential for safer roadside maintenance both for farmers and motorists by removing people and large tractors. Autonomous machines can be programmed for consistent behaviors that would further reduce the risk of accidents.

Through these three focus areas, the public will benefit by allowing for new research into crop health and productivity necessary to sustainably feed the world, reduce harvest losses and reduce the risk of accidents.

View the full statement on the NIDB.

Project supported by Hatch funds.

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