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Bacterial wetwood detection in Fagus grandifolia and Prunus serotina sapwood using a conducting polymer electronic-nose deviceAuthor(s): A.D. Wilson
Source: In: Proceedings of the Fifth International Conference on Sensor Device Technologies and Applications, Lisbon, Portugal, IARIA
Publication Series: Scientific Journal (JRNL)
Station: Southern Research Station
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DescriptionNew electronic gas-detection methods were developed and tested for the diagnosis of bacterial wetwood disease in <i>Fagus grandifolia</i> (American beech) and <i>Prunus serotina</i> (black cherry) using a Conducting Polymer (CP)-type electronic nose (e-nose), the Aromascan A32S, based on detection of headspace volatile microbial and plant metabolites derived from sapwood. Diagnostic application-specific aroma signature patterns (profile databases), derived from e-nose analysis of known healthy and wetwood-infected sapwood cores of each hardwood tree species, were used to develop an aroma database library. The library was used as known references to screen aroma profiles of sapwood cores for the presence of wetwood in unknown samples. The Aromascan A32S e-nose effectively distinguished between headspace volatiles from tree cores of different wood types, correctly identifying them at frequencies ranging from 92.3-100%. Principal Component Analysis (PCA) and Quality Factor (QF) statistical values indicated the relatedness and significance of differences between headspace volatiles from aroma classes of each sample type. Significant differences were found between the aroma profiles of healthy vs. wetwood-infected sapwood of American beech and black cherry, and greater differences occurred between headspace wood volatiles released from healthy sapwoods of the two species
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CitationWilson, A.D. 2014. Bacterial wetwood detection in <i>Fagus grandifolia</i> and <i>Prunus serotina</i> sapwood using a conducting polymer electronic-nose device. In: Proceedings of the Fifth International Conference on Sensor Device Technologies and Applications, Lisbon, Portugal, IARIA, pp. 109-113. ISBN: 978-1-61208-375-9.
Keywordsartificial olfaction, disease diagnosis, electronic aroma detection, volatile organic compounds
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