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Classification of Mushroom Substrate Odors Using a Portable Electronic Nose and Neural Networks

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Paper number  034104,  2003 ASAE Annual Meeting . (doi: 10.13031/2013.14106) @2003
Authors:   Archie L. Williams, Paul Heinemann, Robert Graves, David Beyer, Charles Wysocki, William Roush
Keywords:   Aeration, agricultural engineering, air quality, composting, electronic nose, hedonic rating, human panel, mushroom substrate, neural networks, odors, pleasantness rating

An electronic nose was used in conjunction with a human panel and artificial neural networks to predict human assessments on a hedonic (pleasantness) scale when confronted with mushroom substrate odors. Both laboratory and field odor samples were collected and presented to both the electronic nose and the human panelists. The human panelists were required to rate the odor samples on a hedonic scale. Neural networks were developed to predict the odor pleasantness based on electronic nose readings. The results obtained from the developed neural networks show promise in the utility of electronic nose evaluation of odors.

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