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Drosophila olfactory receptors as classifiers for volatiles from disparate real world applications
Citation
Nowotny, T and De Bruyne, M and Berna, AZ and Warr, CG and Trowell, SC, Drosophila olfactory receptors as classifiers for volatiles from disparate real world applications, Bioinspiration and Biomimetics, 9, (4) pp. 1-13. ISSN 1748-3182 (2014) [Refereed Article]
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Copyright Statement
© 2014 IOP Publishing Ltd. Licensed under Creative Commons Attribution 3.0 Unported (CC BY 3.0) http://creativecommons.org/licenses/by/3.0/
DOI: doi:10.1088/1748-3182/9/4/046007
Abstract
Olfactory receptors evolved to provide animals with ecologically and behaviourally relevant information. The resulting extreme sensitivity and discrimination has proven useful to humans, who have therefore co-opted some animals' sense of smell. One aim of machine olfaction research is to replace the use of animal noses and one avenue of such research aims to incorporate olfactory receptors into artificial noses. Here, we investigate how well the olfactory receptors of the fruit fly, Drosophila melanogaster, perform in classifying volatile odourants that they would not normally encounter. We collected a large number of in vivo recordings from individual Drosophila olfactory receptor neurons in response to an ecologically relevant set of 36 chemicals related to wine ('wine set') and an ecologically irrelevant set of 35 chemicals related to chemical hazards ('industrial set'), each chemical at a single concentration. Resampled response sets were used to classify the chemicals against all others within each set, using a standard linear support vector machine classifier and a wrapper approach. Drosophila receptors appear highly capable of distinguishing chemicals that they have not evolved to process. In contrast to previous work with metal oxide sensors, Drosophila receptors achieved the best recognition accuracy if the outputs of all 20 receptor types were used.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | Biosensors; Classification; Feature selection; Industrial chemicals; Machine olfaction; Olfactory receptor; Wine volatiles; Animals; Biosensors; Chemical hazards; Classification (of information); Feature extraction; Indicators (chemical); Wine; odor |
| Research Division: | Biological Sciences |
| Research Group: | Genetics |
| Research Field: | Neurogenetics |
| Objective Division: | Expanding Knowledge |
| Objective Group: | Expanding knowledge |
| Objective Field: | Expanding knowledge in the biological sciences |
| UTAS Author: | Warr, CG (Professor Coral Warr) |
| ID Code: | 131830 |
| Year Published: | 2014 |
| Web of Science® Times Cited: | 15 |
| Deposited By: | Office of the School of Medicine |
| Deposited On: | 2019-04-08 |
| Last Modified: | 2019-05-06 |
| Downloads: | 27 View Download Statistics |
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