Automated microfluidic plant chips-based plant phenotyping system
Huawei Jiang, Xinran Wang, Trevor M. Nolan, Yanhai Yin, Maneesha Aluru, Liang Dong
- Year
- 2017
- Citations
- 7
Abstract
We report on the development of an enhanced and robust microfluidic plant chip-based growth and monitoring system for high-throughput phenotyping of Arabidopsis thaliana. The system consists of multiple vertical plant chips, a microfluidic hormone concentration gradient generator, multiple simple gravity pumps, and a robotic arm with a stereoscope for plant imaging. We validate this system by phenotyping the growth of Arabidopsis plants in medium containing different hormone concentrations, in a real-time manner. Our results show that Arabidopsis growth and hormone response in this system closely replicates growth on standard laboratory petri plates.
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