Detection of cutaneous myiasis in sheep using an ‘electronic nose’Export / Share PlumX View Altmetrics View AltmetricsCramp, A. P., Sohn, J. H. and James, P. J. (2009) Detection of cutaneous myiasis in sheep using an ‘electronic nose’. Veterinary Parasitology, 166 (3). pp. 293-298. ISSN 0304-4017 Full text not currently attached. Access may be available via the Publisher's website or OpenAccess link. Article Link: https://doi.org/10.1016/j.vetpar.2009.08.025 Publisher URL: https://www.sciencedirect.com/science/article/pii/S0304401709005135 AbstractCutaneous myiasis (flystrike), in Australia caused primarily by Lucilia cuprina [Diptera: Calliphoridae], is a debilitating, painful and potentially lethal disease of sheep. Early detection of flystrike is difficult and continual flock surveillance is required to enable timely treatment of struck sheep. Electronic nose technology offers the potential for early and automated detection of flystrike. An electronic nose consisting of six metal oxide semiconductor sensors and temperature and humidity sensors was used to measure odours collected by dynamic headspace sampling during flystrike development in four experiments and from urine- and faeces-stained fleece in one experiment. Non-linear signal measurement techniques and linear discriminant analysis (LDA) were used to extract signal features and process those features for analysis of categorical separation of odour groups. The results from LDA indicated that the electronic nose accurately distinguished flystrike odour on days 1, 2 and 3 of development from that of dry wool in all experiments (P<0.05). The electronic nose was also able to discriminate flystrike odour on the day of larval implantation (day 0) in three of the four studies. In the experiment with urine- and faeces-stained wool, these odours were accurately distinguished from both dry wool and flystrike (P<0.05). This study provides proof-of-concept for the detection of flystrike using electronic nose technology. Practical methods for collection of odour in the field and suitable detection algorithms will be required for development to commercial application.
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