Detection of xylem embolism using ultrasonic acoustic emissions

Author Affliations

Duke University


Ultrasonic acoustic emission (UAE) provides a non- to minimally-invasive tool to measure xylem embolism in plant organs.


When a conduit embolizes, a small amount of energy is released. This energy is detectable with ultrasonic (i.e. above 20 kHz) sensors. Previous work has shown a close correspondence between UAE and percent loss of conductivity in stems and leaves of many species. UAE can be used in situ to assess embolism in plants growing in the field or greenhouse or can be used for generating hydraulic vulnerability curves of plant organs on the lab bench.


The companies Physical Acoustics and Vallen Systeme make a wide range of sensors and detectors for ultrasonic acoustic emissions. The most common sensor for detection of xylem embolism is the Physical Acoustics R15, which has a frequency detection range of 50-200 kHz. Physical Acoustics also makes a wide range of detectors that accept different numbers of sensors. Many of these detectors must be installed as a PCI board in a computer. However, the Pocket AE, which accepts 2 sensors and is a handheld device, is particularly useful for studies of cavitation due to its compact nature. The software that is used to operate the system and analyze the UAE data is AEWin and is available from Physical Acoustics.

Units, terms, definitions

Amplitude – The strength of the acoustic signal in decibels

Counts – The number of individual acoustic emission events

Energy – The actual amount of energy (in attojoules) released by the cavitating conduit


1.The organ or tissue of interest (e.g., branch, leaf, etc.) is attached to a UAE sensor, to which a thin coat of silicon-based grease has been applied. The sensor can placed on top of the sample if the sample is flat, or clamped to the sample. The sensor is then connected to a UAE detector.

2. Data acquisition begins by opening the AEWin software, setting amplitude threshold for UAE detection and by initiating acquisition. Some detectors have variable levels of signal amplification and this must also be set prior to acquisition.

3. The detector will continue to collect data until it is stopped. However, with the Pocket AE the software begins overwriting data after 24 hours.

4. Once data collection is finished, the data can be exported to a spreadsheet and can be analyzed for number of UAE events (counts), amplitude of each event, duration of each event and the energy produced by the event.


The UAE method can be used for the construction of hydraulic vulnerability curves of leaves. Leaves are attached to sensors which have been coated with a thin layer of silicon grease. As leaves dehydrate, the water potential of nearby (on the lab bench) leaves is measured as an approximation of the water potential of leaves attached to UAE sensors. The nearby leaves should be treated with silicon-based grease to mimic the conditions of leaves attached to UAE sensors.

The UAE methods can also be used for the construction of hydraulic vulnerability curves of wood or woody organs (e.g., branches). Samples are attached to UAE sensors and are intermittently weighed while collecting UAE data. Measure relative water content in similar samples as they dry, along with water potential using screen-cage psychrometers. Once the relationship between relative water content and water potential has been established, the weights of the UAE samples can be converted into water potentials for the construction of the vulnerability curve.


Both the cumulative number and cumulative amplitude of acoustic emissions have been reported in the literature as proxies for embolism events (Tyree & Dixon 1983; Kikuta et al. 1997; Johnson et al. 2009). Amplitude was found to be highly correlated with the percent of filled conduits in leaves across species (r2 = 0.77, Johnson et al. 2009), while both measures were found to more closely approximate different percentages of loss of conductivity in wood (Mayr & Rosner 2011). Hypothetically, cumulative amplitude should be a better measure because it can distinguish between higher energy emissions from vascular embolism and lower energy emissions from non-conductive cell collapse (Kikuta 2003), but both measures should be reported until the relationship between the two measures is clearly understood.

The amplitude of acoustic emissions is also closely correlated with conduit diameter (r2 = 0.94, Johnson et al. 2009), which gives rise to a minimum conduit size of about 4.5 μm for which embolism is detectable by acoustic emissions, which may make this method unsuitable for some species.

Attaching the sensor to wood samples also requires stripping the bark, which can damage xylem and allow for dehydration, and may explain the discrepancies between UAE and percent loss of conductivity observed in well-hydrated samples with few embolisms (Mayr & Rosner 2011). The sensor should be attached carefully to avoid damage, and a second rehydration may be necessary after attachment.

Other resources

Notes and troubleshooting tips

Fluorescent lights are often a source of RFI that is detected by the sensor. Best results have been obtained by acoustically shielding samples with carboard lined with 2″ thick packing foam. Additionally, UAE in leaves can be more difficult to measure than in woody tissues, due to the often small conduit dimensions in leaf xylem. Also, the correlation between leaf UAE and loss of hydraulic conductivity is not as strong, in some species, as it is in woody tissues. This is likely due to the much more complex pathway of water transport through the leaf as compared to wood.

Links to resources and suppliers

Physical Acoustics (

Vallen Systeme (

Literature references

Millburn J.A. & Johnson R.P.C. (1966) The conduction of sap. I. Detection of vibrations produced by sap cavitation in Ricinus xylem. Planta 69, 43-52. Tyree M.T. & Dixon M.A. (1983) Cavitation events in Thuja occidentalis. Ultrasonic acoustic emissions from the sapwood can be measured. Plant Physiology 72, 1094-1099. Kikuta S.B., Lo Gullo M.A., Nardini A., Richter H. & Salleo S. (1997) Ultrasound acoustic emissions from dehydrating leaves of deciduous and evergreen trees. Plant, Cell & Environment 20,1381-1390. Kikuta S.B. (2003) Ultrasound acoustic emissions from bark samples differing in anatomical characteristics. Phyton 43, 161-176. Johnson D.M., Meinzer F.C., Woodruff D.R. & McCulloh K.A.(2009) Leaf xylem embolism, detected acoustically and by cryo-SEM, corresponds to decreases in leaf hydraulic conductance in four evergreen species. Plant, Cell & Environment 32, 828-836. Mayr S. & S. Rosner. (2011) Cavitation in dehydrating xylem of Picea Abies: energy properties of ultrasonic emissions reflect tracheid dimensions. Tree Physiology 31, 59-67.

Health, safety & hazardous waste disposal considerations


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