A versatile odor detection system based on automatically trained rats for chemical sensing

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Title
A versatile odor detection system based on automatically trained rats for chemical sensing
Author(s)
Yunkwang Oh; Miha Kim; O S Kwon; S S Min; Yong Beom Shin; K Kim; M K Oh; Moonil Kim
Bibliographic Citation
Journal of Industrial and Engineering Chemistry, vol. 131, pp. 400-409
Publication Year
2024
Abstract
We report a versatile odor detection system that employs rats trained through automated operant conditioning paradigms. While detection animals possess remarkable olfactory capabilities, their practical use has been limited by non-automated training methods, which involve lengthy training periods, high costs, handler dependency, and low reliability. Our primary research goal was to develop detection animals using a fully automated system. To achieve this, we employed four distinct operant conditioning approaches to train four rats (Numbers 3, 7, 10, and 12) in an automated apparatus for detecting 2,4-dinitrotoluene (DNT). Our system performed exceptionally well, with DNT-trained rats achieving a 95 % accuracy rate, 99 % sensitivity, 91 % specificity, 92 % positive predictive value (PPV), and 99 % negative predictive value (NPV) across 380 tests. Additionally, we observed a linear decrease in response time as DNT concentration increased from 20 parts per billion (ppb) to 1000 ppb, indicating the system’s potential for quantitative odor concentration measurement. Impressively, the rats retained their odor discrimination skills for up to four months after their last training session, underscoring the durability of their olfactory memory. Our study introduces a novel, highly effective system for specific odorant component detection, offering a faster, more reliable, and accurate method for distinguishing between various odors.
Keyword
Olfactory detectionAutomated systemGas sensorOdorDNT
ISSN
1226-086X
Publisher
Elsevier
Full Text Link
http://dx.doi.org/10.1016/j.jiec.2023.10.042
Type
Article
Appears in Collections:
Division of Research on National Challenges > Bionanotechnology Research Center > 1. Journal Articles
Critical Diseases Diagnostics Convergence Research Center > 1. Journal Articles
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