Plants have been shown to react to external stimuli by producing variations in the transmembrane electric potential (EP), which propagate through the vascular bundle and influence the physiology of even distant plant tissues.

Our objective is to determine whether drought stress can be detected by analysing stem EP recordings and identify the signal features that best discriminate drought stress.

We continuously recorded the EP of tomato plants using two electrodes placed at different heights on the stem. Half of the plants were subjected to drought stress, while the other half received adequate watering. The statistical features of the EP signals were then compared between stressed and control plants.

Preliminary results show that the power spectral density of the EP signals decay according to a power law. During the day, stressed plants exhibit steeper decay rates (in absolute value), indicating a greater contribution of higher frequency components and a more irregular signal. Moreover, a logistic model based on the statistical features achieved a modest yet significant accuracy of 66% in classifying EP recording from stressed and control model plants.

Although still preliminary, our findings demonstrate that drought stress affects the plant electrophysiology and that this stress can be detected by analysing EP recordings. This study provides a step toward developing EP-based early warning systems for drought stress.