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Electronic Noses: Wake Up and Smell the Coffee E
lectronic or artificial noses are sensing systems based loosely on principles of the olfactory system. When the receptor cells in the natural olfactory system are exposed to an odor, they respond by generating a pattern of signals that is recognized by the brain and perceived as a particular compound or mixture. In electronic noses (e-noses), an array of semi-selective and cross-reactive sensors is used to generate a response pattern that is fed into a computer-based pattern recognition system. The similarity in the two systems is the combination of a sensor array with pattern recognition. The advantage of this architecture is the ability to generate a large number of patterns, which makes it possible to recognize many compounds and complex mixtures. The alternative, traditional approach— in both biological and artificial systems—is to use a specific receptor for each ligand. Although this approach provides the most specificity, the requirement of a different receptor for each ligand makes an onerous demand on metabolism (in the biological system) or on synthesis (in the artificial system). The design of the olfactory system is anticipatory; that is, it is not tuned to respond to any specific compound but to many compounds. This breadth in response is essential because in most vertebrates other than humans, olfaction is the predominant sense responsible for sexual attraction, food seeking and selection, predation, and aversion behaviors. Although the nose is able to detect and perceive pure volatile substances, it did not evolve to do so; purified organic compounds have only been available for a few hundred years. After one has learned to recognize a pure vapor, it is easy to recognize that vapor when it is encountered again. In fact, creators of perfumes can learn to recognize several thousand pure compounds. But things get more complicated. Although it is relatively easy to identify the presence or absence of a particular vapor in a binary mixture (e.g., acetone and ethyl acetate), it is difficult to recognize the presence of a vapor in a ternary or more complex mixture. In fact, many ternary mixtures do not smell like their components because they are perceived as something quite different. For example, artificial strawberry flavor is a
© 2005 AMERICAN CHEMICAL SOCIETY
combination of several components. One version contains cis3-hexen-1-ol, ethyl-3-methyl-3-phenylglycidate, furaneol, undecalactone, and -ionone. None of these components in pure form smells like strawberry, yet the combination provides a distinct strawberry aroma. In addition, our noses can readily qualitatively rank the strength of an odor as high, medium, or low, but they are unable to quantify how much of a particular vapor is present. In analogy to our noses, e-noses, by design, should not and do not perform either component identification or quantification. These tasks are readily performed by traditional analytical instrumentation such as a GC or GC/MS. E-noses should not be able to solve component identification or quantification problems, even with a high degree of sensor diversity or sophisticated computational training. E-noses are designed to mimic the olfactory system, and they do a wonderful job of it. E-noses have been around since the landmark 1982 paper in Nature by Persaud and Dodd. Many research and commercial efforts have developed the technology extensively in the intervening decades, yet these systems have not been widely accepted, largely because they cannot perform component identification and quantification. I contend that these systems cannot perform these tasks now nor will they be able to do so in the near future. They are designed using principles of the olfactory system. We should use these systems to perform tasks that are compatible with their underlying design principles. Electronic noses offer an exciting technology for performing higher-level analyses and decision making. They are ideally suited to perform unique analytical tasks. Let’s use them for what they were designed for.
David R. Walt Tufts University
[email protected] F E B R U A R Y 1 , 2 0 0 5 / A N A LY T I C A L C H E M I S T R Y
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