Acoustic emissions are frequently used in material sciences and engineering applications for structural health monitoring. It is known that plants also emit acoustic emissions, and their application in plant sciences is rapidly increasing, especially to investigate drought-induced plant stress. Vulnerability to drought-induced cavitation is a key trait of plant water relations, and contains valuable information about how plants may cope with drought stress. There is, however, no consensus in literature about how this is best measured. Here, we discuss detection of acoustic emissions as a measure for drought-induced cavitation. Past research and the current state of the art are reviewed. We also discuss how the acoustic emission technique can help solve some of the main issues regarding quantification of the degree of cavitation, and how it can contribute to our knowledge about plant behavior during drought stress. So far, crossbreeding in the field of material sciences proved very successful, and we therefore recommend continuing in this direction in future research.

The formation of air emboli in the xylem during drought is one of the key processes leading to plant mortality due to loss in hydraulic conductivity, and strongly fuels the interest in quantifying vulnerability to cavitation. The acoustic emission (AE) technique can be used to measure hydraulic conductivity losses and construct vulnerability curves. For years, it has been believed that all the AE signals are produced by the formation of gas emboli in the xylem sap under tension. More recent experiments, however, demonstrate that gas emboli formation cannot explain all the signals detected during drought, suggesting that different sources of AE exist. This complicates the use of the AE technique to measure emboli formation in plants. We therefore analysed AE waveforms measured on branches of grapevine (Vitis vinifera L. ‘Chardonnay’) during bench dehydration with broadband sensors, and applied an automated clustering algorithm in order to find natural clusters of AE signals. We used AE features and AE activity patterns during consecutive dehydration phases to identify the different AE sources. Based on the frequency spectrum of the signals, we distinguished three different types of AE signals, of which the frequency cluster with high 100–200 kHz frequency content was strongly correlated with cavitation. Our results indicate that cavitation-related AE signals can be filtered from other AE sources, which presents a promising avenue into quantifying xylem embolism in plants in laboratory and field conditions.