Plant behavior and response to environmental stimuli has tremendous importance in science and agriculture. In particular, a plant's root continuously senses changes in the environment, and responds in ways that optimize dynamically different essential parameters like its stability, and adequate food and water supplies. Some of the plant behavioral changes in response to environmental changes, like water shortage, can be reversible, and after certain 'stress' time, the plant can get back to its normal behavioral patterns. In other cases, the plant behavior after the stress stimulus ends, is changed, due to effects on internal mechanisms, facilitating long-term behavioral changes. The main aim of this work is to derive a preliminary physical model and analysis tools to quantify the behavioral changes of a plant in response to a stimuli. To demonstrate the model, we examined, without loss of generality, the change in plant growth rate in response to electrical simuli. We showed how the suggested plant behavioral model can assist in computational analysis of short and long term plant response to changing stimuli, construct a common baseline for comparison with other stimuli, and derive new quantitative measurements that can be correlated with internal plant mechanism and assist in assessing behavioral plant patterns and in the design of more efficient agricultural technologies.
|Original language||American English|
|Title of host publication||Proceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||7|
|State||Published - Oct 2020|
|Event||20th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2020 - Virtual, Cincinnati, United States|
Duration: 26 Oct 2020 → 28 Oct 2020
|Name||Proceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020|
|Conference||20th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2020|
|Period||26/10/20 → 28/10/20|
Bibliographical noteFunding Information:
We would like to thank the support by the "Breakthrough Innovative Research Grants" of Tel Aviv University, Dr. Klimentiy Levkov and Vladimir Vainstein for the assistance in design and building of the electrical voltage splitter and the hardware setup, Tirosh Mekler and Prof. Alex Liberzon for the assistance with configuring the stimuli device, and last for Prof. Hillel Fromm for useful discussions, great insights and research directions.
© 2020 IEEE.
- electrical stimulation (key words)
- machine learning
- plant behavior
- plant root