Detecting plant health via electrical stress response

Marcella J. Cross, Plant Sciences, Cornell University, Ithaca, NY and Taryn L. Bauerle, School of Integrative Plant Science, Cornell University, Ithaca, NY

Background/Question/Methods
Plant stress responses provide critical insight into interactions between plants and the changing climate, pest invasion, and threats from fire and deforestation. Electrical stress signals have a distinctive spike and decay signature indicating plant wound response. Typically, these electrical signatures are measured in voltage, the electrical pressure. However, voltage measurements are too erratic to distinguish between healthy and unhealthy electrical stress signatures. Amperage, the flow of the electrical current, is steadier than voltage, though very weak and difficult to detect in plants. We performed an experiment using micro-amperage stress signatures to diagnose tree health. We sampled from two blocks of Douglas-fir trees (Pseudotsuga menziesii) during the winter and spring on two soil types (Briedwell and McAlpin soils) and included variables for temperature variation, season, and soil impacts using mixed linear and Tobit regression models. In both healthy and unhealthy trees on two soil types, we used a micro-amperage meter to measure each amperage baseline, inflicted a mechanical wound at the measurement site, and recorded the peak and subsequent recovery in electrical signal.
Results/Conclusions
We found that healthy trees have a significantly higher peak and faster recovery period in the electrical signature measured in micro-amperage in comparison with the electrical signature of unhealthy trees. Additionally, electrical signatures recorded in the spring had significantly higher spike magnitudes compared with signatures recorded in the winter, indicating greater signal stress response in non-dormant seasons. Trees on the two soil types analyzed did not show differences in electrical signature. Our results suggest that measurement of tree stress in amperage provides a promising method for monitoring and early detection of changes in forest health and a tool to study the impacts of current challenges to plant health.