Abstract
Automation technologies in the biological plant sciences domain lack the ability for handling soft, live, and solid biological materials necessary for lab-based plant genetic transformation testing. This limitation has created a research bottleneck hindering progress in agricultural, biomedical, and pharmaceutical industries. Traditionally, plant transformation at lab-scale testing has relied on slow and labor-intensive manual techniques, contributing to this challenge. Automation offers a promising solution to accelerate plant biosystems research, enabling higher throughput in gene functional validation, and shortening crop improvement timelines by reducing the need for manual interaction and allowing for continuous sampling. To address this, an automated system for addressing early steps in the plant transformation process is reported here. This report provides a comprehensive analysis of the development and evolution of tools for acquisition and manipulation of living plant tissue samples, known as explants, based on extensive testing with an automated plant transformation system.
| Original language | English |
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| Title of host publication | 2025 IEEE 21st International Conference on Automation Science and Engineering, CASE 2025 |
| Publisher | IEEE Computer Society |
| Pages | 1310-1315 |
| Number of pages | 6 |
| ISBN (Electronic) | 9798331522469 |
| DOIs | |
| State | Published - 2025 |
| Event | 21st IEEE International Conference on Automation Science and Engineering, CASE 2025 - Los Angeles, United States Duration: Aug 17 2025 → Aug 21 2025 |
Publication series
| Name | IEEE International Conference on Automation Science and Engineering |
|---|---|
| ISSN (Print) | 2161-8070 |
| ISSN (Electronic) | 2161-8089 |
Conference
| Conference | 21st IEEE International Conference on Automation Science and Engineering, CASE 2025 |
|---|---|
| Country/Territory | United States |
| City | Los Angeles |
| Period | 08/17/25 → 08/21/25 |
Funding
The authors would like to thank Sara Jawdy for provision of test tissue culture plants for our demonstration and Xiaohan Yang and Lonnie Love for their encouragement on our concept to build a plant robotics platform. This research was sponsored by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy.