Electronic Nose System

Using the principles of biological olfaction, electronic nose systems contain arrays of different types of cross-reactive vapor-sensitive sensors. While it is difficult to discriminate analytes entirely by their responses to a single type of sensor, using an array of sensors yields response patterns that can readily distinguish many different vapors. Ideally, the response mechanisms of the sensors are highly varied and encompass both physical and chemical phenomena1. 

The performance of common multisensor arrays is ultimately determined by the properties of their constituent parts. Key parameters such as number, type and specificity of the sensors determine whether a specific instrument is suitable for a given application. The selection of an appropriate set of chemical sensors is of utmost importance if electronic nose classifications are to be utilised to solve an analytical problem. As this requires time and effort, the applicability of solid-state sensor technology is often limited. The time saved compared with classic analytical methods is questionable, since analysis times of electronic nose systems are generally influenced more by the sampling method utilised than the sensor response time [185]. 

Table 153 Selected applications of electronic nose systems to different food products ...

Panigrahi, S., Balasubramanian, S., Gu, H., Logue, C., Marchello, M. (2006) Neural-net-work-integrated electronic nose system for identification of spoiled beef Food Sci. Technol. 39 135-145. 

Schaller, E., Bosset, J.O., Escher, E (1999) Practical experience with Electronic noses systems for monitoring the quality of dairy products. Chimia 53 98-102. 

Marti, M.R, Pino, J., Boque, R., Busto, O., Guasch, J. (2005) Determination of aging time of spirits in oak barrels i ing a headspace-mass spectrometry (HS-MS) electronic nose system and multivariate calibration. In Analytical and Bioanalytical Chemistry 382 (2) The European Conference on Analytical Chemistry XIII, pp 440-443. 

James, D., Scott, S.M., Ali, Z., O Hare, W.T. (2005) Review Chemical sensors for electronic nose systems. Microchim. Acta 149 1-17. 

Fig. 2. The principle configuration of an electronic nose system where the analyte mixture is contacted with a chemical sensor array that produces raw data which subsequently are treated with a pattern recognition algorithm that delivers the predicted result...

Today, several companies sell commercial electronic nose systems with their favorite sensor configurations [20-22]. The commercial systems have the drawback that the types of sensors used in the array cannot be changed. If these configurations are not the appropriate ones for the analytes to be measured, it becomes necessary to combine different commercial instruments. Alternatively, a research instrument may be used. 

Liquid samples can be collected from the bioreactor sampling port and introduced into the electronic nose instrument manually. More appealing in bioprocessing is to sample on-line. An electronic nose system monitors non-in-vasively by sampling from the off-gas port of the bioreactor [23]. The humidity... 

The creation of many effective combinations of artificial nose sensors with only a few functional monomers used in different relative amounts was proven here. The application of combinatorial technologies to the discovery of novel materials for more recent, miniamrized electronic nose systems based on small pol5mier beads (120), and to equally intriguing electronic tonguelike microsensors in solution to mimick the sense of taste for solution mixtures (121), should be highly beneficial and thus is to be expected in the near future. 

VAN DEVENTER D and MALLiKARJUNAN P (2002), Comparative performance analysis of three electronic nose systems using different sensor technologies in odor analysis of retained solvents on printed packaging , J Food Sci, 67(8), 3170-3183. 

A schematic diagram of a typical electronic nose system is shown in Fig. 2 above. 

The various stages in the signal processing of an electronic nose system are illustrated in Figure 11 in which the signals generated from an array of sensors (or, for example, pseudo-sensors in a mass spectrometer) are first pre-processed and then fed in to a pattern analyser. In other words the n dimension vector in sensor space is transformed into feature space (a process called feature extraction) and then identified using some form of pattern classifier. 

By creating a temporal profile of odour delivery to the different sensors within the array that is stimulus specific, we may provide additional response diversity. This is achieved by deploying chemical sensor arrays within stationary phase materials that impose the necessary stimulus-dependent spatio-temporal dynamics in sensor response we have recently shown that this approach aids complex odour discrimination (Gardner et al. 2007). This concept is very different to that embodied within classical electronic nose systems that are usually designed to control the exposure of the stimulus as a square pulse, whose temporal properties are independent from the nature and chemical composition of the stimulus. Instead, we exploit such differences to generate additional discrimination capability in the device. 

FIGURE 1.11 Schematic diagram of the portable electronic nose system. (Reprinted from Sens. Actuators B, 66, Hong H.-K., Kwon C. H., Kim S.-R., Ynn D. H., Lee K., and Sung Y. K., Portable electronic nose system with gas sensor array and artificial neural network, 49-52, 2000, with permission from Elsevier.)... 

Tanaka M., Anguri H., Nonaka A., Kataoka K., Nagata H., Kita J., and Shizukuishi S., Clinical assessment of oral malodor by the electronic nose system, J. Dent. Res., 83(4), 317, 2004. 

It has to be remarked that in spite of the widely accepted term electronic nose, current devices are still far from the structure and functions of natural olfaction sense. The unique common feature between artificial and natural system is that both are largely based on arrays of nonselective sensors. The concept underlying electronic nose systems has been demonstrated to be independent on the particular sensor mechanism indeed during the last two decades almost all the available sensor technologies have been utilized as electronic noses. Clearly, all these sensors are very different from the natural receptors. These dissimilarities make the perception of electronic nose very different from that of natural olfaction, so that the instrumental perception of the composition of air cannot be called odor measurement because odor is the sensation of smell as perceived by human olfaction. Nonetheless, the term odor analysis with electronic noses is now largely adopted, but it is important to keep in mind, especially in medical applications, that the electronic nose measurement may be very distant from the human perception. 

Electronic nose system Safety, security, and health for the benefit of the society... 

Gardner JW, Shin HW, Hines EL, 2000. An electronic nose system to diagnose illness. Sensors and Actuators B Chemical 70,19-24. 

Pavlou AK, Magan N, Mcnulty C, et at, 2002b. Use of an electronic nose system for diagnoses of urinary tract infections. Biosensors and Bioelectronics 17, 893-9. 

S. Panigrahi, S. Balasubramanian, H. Gu, C. Logue, M. MarcheUo, Neural-network-integrated electronic nose system for identification of spoiled beef. Lwt-Food Sd. TechnoL 39(2), 135— 145 (2006)... 

N. EIBarbri, J. Mirhisse, R. lonescu, N. El Bari, X. Correig, B. Bouchikhi, E. Llobet, An electronic nose system based on a micro-machined gas sensor array to assess the freshness of sardines. Sens. Actuators B Chem. 141, 538-543 (2009)... 

Fig. 1 Typical electronic nose system describing a the traming phase and b testing phase...

W. Khalaf, C.P.M. Gaudioso, Least square regression method for estimating gas concentration in an electronic nose system. Sensors 9(3), 1678-1691 (2009)... 

J.S. Vestergaard, M. Martens, P. TurkM, Apphcation of an electronic nose system for prediction of sensory quality changes of a meat product (pizza topping) during storage. LWT-Food Sci. Technol. 40,1095-1101 (2007)... 

K.R. Kashwan, M. Bhuyan, Robust electronic-nose system with temperature and humidity drift compensation for tea and spice flavour discrimination, in Proceedings of the Sensors and the International Conference on New Techniques in Pharmaceutical and Biomedical Research, 5-7 Sept 2005, pp. 154-158... 

Keywords Electronic Nose System, Principal Component Analysis, Decision Tree, High Level Synthesis, Vivado, Zynq System on Chip... 

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