Plants are known to generate various types of electrical signals, which have been observed ever since Darwin’s times. We studied the electrical signals acquired in tomato plants infected with the fungal pathogen Oidium neolycopersici (On) , the causative agent of powdery mildew, and applied statistical analyses to detect the differences in electrical responses between healthy and infected plants, as reported in 1 . • The underlying mechanism in the generation and transmission of electrical signals is not fully understood, yet it’s generally accepted that they can be classified according to functional properties. Action potentials (APs) and slow wave potentials, in particular, are elicited by biotic and abiotic stimuli, thus are interesting as a hallmark of plant health status. • To analyse the application of these potentials in plant disease detection, voltages from electrodes inserted in plants were acquired periodically by a scanning multimeter and recorded under control of a dedicated custom Python program running on a Raspberry Pi board. • Here we describe the design of the experiment and analyse in some detail the solutions adopted for specific issues found in the measurements, such as electrode’s material and placement; immunity to electromagnetic noise; data logging over long periods of time with intermediate monitoring of results.
Matić et al. (Sun,) studied this question.