Cometto-Muñiz JE, Cain WS, Abraham MH, Gil-Lostes J. Concentration-detection functions for the odor of homologous n-acetate esters.
Physiol Behav 2008;
95:658-67. [PMID:
18950650 DOI:
10.1016/j.physbeh.2008.09.021]
[Citation(s) in RCA: 33] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2008] [Revised: 09/17/2008] [Accepted: 09/19/2008] [Indexed: 10/21/2022]
Abstract
Using air-dilution olfactometry, we measured concentration-response functions for the odor detection of the homologous esters ethyl, butyl, hexyl, and octyl acetate. Stimuli were delivered by means of an 8-station vapor delivery device (VDD-8) specifically designed to capture odor detection performance by humans under environmentally realistic conditions. Groups of 16-17 (half female) normosmic (i.e., having a normal olfaction) non-smokers (ages 18-38) were tested intensively. The method involved a three-alternative forced-choice procedure against carbon-filtered air, with an ascending concentration approach. Delivered concentrations were confirmed by gas chromatography before and during actual testing. A sigmoid (logistic) model provided an excellent fit to the odor detection functions both at the group and individual levels. Odor detection thresholds (ODTs) (defined as the half-way point between chance and perfect detection) decreased from ethyl (245 ppb by volume), to butyl (4.3 ppb), to hexyl acetate (2.9 ppb), and increased for octyl acetate (20 ppb). Interindividual threshold variability was near one and always below two orders of magnitude. The steepness of the functions increased slightly but significantly with carbon chain length. The outcome showed that the present thresholds lie at the very low end of those previously reported, but share with them a similar relative trend across n-acetates. On this basis, we suggest that a recent quantitative structure-activity relationship (QSAR) for ODTs can be applied to these and additional optimized data, and used to describe and predict not just ODTs but the complete underlying psychometric odor functions.
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