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    Author(s): A. D. Wilson; Lisa B. Forse; Benjamin A. Babst; Mohammad M. Bataineh
    Date: 2019
    Source: Biosensors(Journal)
    Publication Series: Scientific Journal (JRNL)
    Station: Southern Research Station
    PDF: Download Publication  (2.0 MB)


    The emerald ash borer (EAB) has been the most destructive and costly nonnative insect to threaten the health of ash (Fraxinus) species in North America for at least the past 25 years. The development of methods for detecting visually-hidden EAB galleries at early stages of infestation would provide a useful tool to more effectively facilitate the planning and implementation of targeted EAB pest-suppression and management activities. We tested the efficacy of using a dual-technology electronic-nose (e-nose)/gas chromatograph device as a means for detection of EAB infestations in green ash trees in different EAB-decline classes by analysis of VOC emissions in sapwood. We found significant differences in VOC profiles for trees from the four decline classes. The VOC composition, quantities, and types of volatile metabolites present in headspace volatiles varied considerably across sample types, and resulted in distinct e-nose smellprint patterns that were characteristic of each unique chemical composition. In addition, specific VOC metabolites were identified as potential healthy and EAB-infestation biomarkers, indicative of the health states of individual trees. Few significant differences in major bark phenolic compounds were found between ash decline classes using LC-MS. The e-nose was effective in discriminating between uninfested and EAB-infested trees based on sapwood VOC emissions.

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    Wilson, A. D.; Forse, Lisa B.; Babst, Benjamin A.; Bataineh, Mohammad M. 2019. Detection of emerald ash borer infestations in living green ash by noninvasive electronic-nose analysis of wood volatiles. Biosensors 9(4): e123. (26 pp.)


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    Agrilus planipennis, VOC-metabolites, early tree-infestation detection, electronic nose (e-nose), insect-infestation biomarkers, plant-health biomarkers, sapwood, smellprint signatures

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