The Ohio State University Corporate Engagement Office

Back to All Technologies

3D-Printed Soybean Leaf

Creative Works
Educational & Informational Materials
Other
College
College of Food, Agricultural, and Environmental Sciences (CFAES)
Researchers
Lang, Olivia
Michel, Andy
Licensing Manager
Dahlman, Jason "Jay"
(614)292-7945
dahlman.3@osu.edu

T2023-314

The Need

In modern agriculture, the ability to quickly and accurately identify diseases impacting soybean crops is critical for farmers to maintain yield and profitability. Traditional methods of disease identification can be time-consuming and imprecise, leading to potential losses. There is a clear need for a cost-effective and efficient solution to aid farmers in early disease detection and management.

The Technology

The 3D-Printed Soybean Leaf addresses this need by providing a versatile tool for disease identification in soybean crops. Crafted from PLA plastic using 3D printing technology, this innovative design serves as a robust foundation for various applications, including disease identification. Its anatomically accurate structure mimics real soybean leaves, allowing for realistic simulation of disease symptoms and patterns. Furthermore, its customizable nature enables easy integration with other sensing technologies for enhanced functionality.

Commercial Applications

  • Disease identification and monitoring in soybean crops.
  • Educational tool for training agricultural professionals and students in disease recognition.
  • Research tool for studying disease progression and management strategies in soybean cultivation.
  • Component in precision agriculture systems for automated disease detection and treatment.
  • Prototype platform for developing advanced agricultural sensing and monitoring devices.

Benefits/Advantages

  • Rapid and accurate disease identification leading to timely intervention and reduced crop losses.
  • Cost-effective alternative to traditional methods of disease diagnosis.
  • Enhances educational and research capabilities in agricultural science.
  • Facilitates the development of precision agriculture solutions for improved crop management.
  • Contributes to sustainable farming practices by promoting early detection and targeted treatment of diseases.