# Acoustic Emissions to Measure Drought-Induced Cavitation in Plants
## 3 Acoustic Emission (AE) Application to Measure Drought-Induced Cavitation: From Past to Present
### AE Feature Extraction
The signals that typified the cavitation phase were characterized by a high intensity at 100-200 kHz. Another signal type, with high intensity in the range 400-800 kHz, was strongly related with branch shrinkage, and probably originated from micro-fractures, which are small fissures in the stretched cell wall or pitch membrane due to an initial volume change. Finally, a low-frequency signal type (high intensity below 100 kHz) was identified that was attributed to macro-fractures or free drainage of water through the porous wood medium. This clustering approach to identify cavitation-related AE signals is a great advance, and may lead to the development of a powerful tool to also investigate cavitation in plants in their native environment. AE sources, such as micro- and macro-fractures, will no longer disturb cavitation measurements but may provide additional information on, for instance, use of elastic water reserves or mechanical strains. It has often been assumed that one AE signal represents cavitation of a single water column [98]. However, except from the observed one-to-one relationship by [PERSON] and [PERSON] [47] and [PERSON] [99] on small sapwood samples of two gymnosperm species, the number of AE signals has been either lower [23; 100; 101; 102] or higher [56; 66] than the number of cavitating conduits in further experiments. In measurements on grapevines, the number of cavitation-related AE signals exceeded the number of vessels in the branch by one or two size orders [33]. Moreover, the amplitude distribution with maximum signal density near the detection threshold of 28 dB\({}_{\text{AE}}\) suggested that a considerable part of the signals could not be detected because their amplitude fell below the detection threshold, and thus probably even more AE signals are produced during xylem cavitation [103]. The use of less sensitive measurement systems, or higher detection threshold settings, might explain cases where less AE signals than cavitated conduits were observed. One reason for the higher number of signals observed by [PERSON] _et al._[80] could be overlapped between adjacent cluster types, so that part of the cavitation-related signal type possibly originated from other co-occurring AE sources, such as micro-fractures or water drainage. This overlap might be caused by different attenuation of the AE signals dependent on their frequency. The effect of attenuation was also observed during a freeze-thaw experiment, where it decreased in frozen samples [104]. A second hypothesis is that the cavitation process generates many AE signals. According to the nanobubble theory of [PERSON] _et al._[28], many nanobubbles may be formed and exist in the xylem before they coalesce and form an embolism. Coalescence of these nanobubbles and subsequent bubble collapse may result in much more AE signals than cavitated conduits. Alternatively, fissures in the stretched pith membrane or rearrangements of the cell wall layers due to pressure redistribution after cavitation may cause many AE signals per cavitated conduit. Further research and more detailed modelling of the actual micro-mechanical processes at the AE source, such as bubble formation and coalescence, may hopefully throw light on cavitation-related AE sources and, accordingly, on the processes behind emboli formation.