Skip to Main Content
An automated approach to detecting signals in electroantennogram dataAuthor(s): D.H. Slone; B.T. Sullivan
Source: J. Chem. Ecol., Vol. 33: 1748-1762
Publication Series: Miscellaneous Publication
PDF: View PDF (981 KB)
DescriptionCoupled gas chromatography/electroantennographic detection (GC-EAD) is a widely used method for identifying insect olfactory stimulants present in mixtures of volatiles, and it can greatly accelerate the identification of insect semiochemicals. In GC-EAD, voltage changes across an insect's antenna are measured while the antenna is exposed to compounds eluting fi-om a gas chromatograph. The antenna thus serves as a selective GC detector whose output can be compared to that of a "general" GC detector, commonly a flame ionization detector. Appropriate interpretation of GC-EAD results requires that olfaction-related voltage changes in the antenna be distinguishable from background noise that arises inevitably from antenna1 preparations and the GC-EAD-associated hardware. In this paper, we describe and compare mathematical algorithms for discriminating olfaction generated signals in an EAD trace from background noise. The algorithms amplify signals by recognizing their characteristic shape and wavelength while suppressing unstructured noise. We have found these algorithms to be both powerful and highly discriminatory even when applied to noisy traces where the signals would be difficult to discriminate by eye. This new nlethodology removes operator bias as a factor in signal identification, can improve realized sensitivity of the EAD system, and reduces the number of runs required to confirm the identity of an olfactory stimulant.
- You may send email to email@example.com to request a hard copy of this publication.
- (Please specify exactly which publication you are requesting and your mailing address.)
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationSlone, D.H.; Sullivan, B.T. 2007. An automated approach to detecting signals in electroantennogram data. J. Chem. Ecol., Vol. 33: 1748-1762
Keywordsolfaction, antennogram, statistical model, semiochemical, signal-to-noise ratio
- Southern pine beetle, Dendroctonus frontalis, antennal and behavioral responses to nonhost leaf and bark volatiles
- Olfactory responses of the hemlock woolly adelgid predator, Laricobius nigrinus (Coleoptera: Derodontidae), to natural and synthetic conifer volatiles
- Identification of odor-processing genes in the emerald ash borer, Agrilus planipennis
XML: View XML