Diagnosis of bovine tuberculosis using a metal oxide-based electronic nose

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Abstract

Electronic noses (e-noses) have been used for environmental monitoring, standardization of medicinal flavourings, food safety tests and diagnosis of infectious diseases based on the statistical analysis of volatile organic compounds (VOCs). Bovine tuberculosis (bTB) is officially diagnosed using the intradermal skin test (IST), which is time-consuming and labour-intensive. Therefore, a more convenient and rapid test with greater sensitivity would be advantageous as prescreening test. In this study, we used a metal oxide sensor (MOS) type e-nose to analyse VOCs in a bTB-infected (n = 11) and bTB-free (n = 10) sera, from cattle whose health status was confirmed using the IST, and pathological and bacteriological examinations. The differences in VOCs from bTB-infected and bTB-free sera detected by the e-nose were statistically analysed using principal components and discriminant factor analyses. bTB-infected and bTB-free sera could be discriminated by MOS type e-nose, and analysing time per sample was only 20 min. VOC analysis using a MOS e-nose was a rapid and automated prescreening method to diagnose bTB, and can be used to select bTB-suspect cattle for IST confirmation. Further studies are required to estimate test sensitivity and specificity. Significance and Impact of the Study: Bovine tuberculosis (bTB) in cattle is diagnosed using the intradermal skin test (IST); however, this method is very time-consuming and labour-intensive. We analysed volatile organic compounds that are obtained from serum using a metal oxide sensor type of electronic nose to discriminate between TB-infected and TB-free sera. This simple and automated technique will be useful to prescreen bTB-suspects and reduce the time and labour required to perform the IST.

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Cho, Y. S., Jung, S. C., & Oh, S. (2015). Diagnosis of bovine tuberculosis using a metal oxide-based electronic nose. Letters in Applied Microbiology, 60(6), 513–516. https://doi.org/10.1111/lam.12410

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