Electronic noses/tongues

E. Kress-Rogers, Sensors for food flavour and freshness electronic noses, tongues and testers. In E. Kress-Rogers and C.J.B. Brimelow (Eds.), Instrumentation and Sensors for the Food Industry, 2nd ed., Woodhead Publishing Ltd., Cambridge, UK, 2001, pp. 553-622, Chap. 19. 

Figure 6.2 shows the structure of a typical electronic nose/tongue. 

The electronic nose and electronic tongue can be considered as a specific branch of the development of artificial intelligence and application of the electronic brain. 

Chemical sensors are becoming more and more important in any area where the measurement of concentrations of volatile compounds is relevant for both control and analytical purposes. They have also found many applications in sensor systems called electronic noses and tongues. 

The electronic nose and electronic tongue will be described as systems able to give olfactory and chemical images, respectively, in a variety of applications fields, including medicine, environment, food and agriculture. 

In the last decade much effort has been oriented to the fabrication of artificial olfaction machines able to determine chemical images (also odor images) of complex volatile compounds. Today many different electronic noses and tongues are available for odor detection and classification and for the creation of chemical images of liquids. 

Buratti et al. (2004) employed an electronic tongue based on ampero-metric detection in a flow injection system (FIA), coupled with an electronic nose, to discriminate wines from vineyard Barbera produced in four Ifalian oenological regions with different denominations Oltrepo Pavese, Piemonte, Asti, and Alba. The chemometric techniques applied were PCA for dafa exploration, and LDA and CART (classification and regression frees) for classification. 

Cosio et al. (2006) used an electronic tongue system based on flow injection analysis (FIA) with two amperometric detectors, together with the use of an electronic nose, in order to classify olive oil samples on the basis of their geographical origin. Counter-propagation maps were used as classification tools. 

Buratti, S., Benedetti, S., Scampicchio, M., and Pangerod, E. C. (2004). Characterization and classification of Italian Barbara wines by using an electronic nose and an amperometric electronic tongue. Anal. Chim. Acta 525(1), 133-139. 

Buratti, S., Benedetti, S., and Ballabio, D. (2006). A combined innovative approach (electronic nose and electronic tongue) for the prediction of Italian red wine sensorial descriptors by means of genetic algorithms. Ingredienti AUmentari 5(6), 6-9. 

Buratti, S., Ballabio, D., BenedetK, S., and Cosio, M. S. (2007). PredicKon of Italian red wine sensorial descriptors from electronic nose, electronic tongue and spectrophotometric measurements by means of Genetic Algorithm regression models. Food Ghent. 100(1), 211-218. 

Winquist, F., Lundstrom, L, and Wide, P. (1999). The combination of an electronic tongue and an electronic nose. Sens. Actuators B 58, 512-517. 

Other MS-fingerprinting techniques that are in commercial development are based on atmospheric pressure ionisation (API), resonance-enhanced multiphoton ionisation (REMPI) TOE and proton-transfer reaction (PTR). They are rapid, sensitive and specific and allow measurements in real time and may play an increasingly important role in the future development of electronic noses and tongues. 

Deisingh, A.K., Stone, D.C., Thompson, M. (2004) Review Applications of electronic noses and tongues in food analysis. Int. J. FoodSci. Technol. 39 587-604. 

Titanium dioxide has also found profitable use as a component of an electronic nose or tongue by different types of treatments useful for the... 

With respect to the type of sensors that can be used in an electronic tongue, practically all the main families of chemical sensors have been used to form the sensor array, viz. potentiometric, voltammetric, resistive, gravimetric and optical, if main sensor families have to be quoted [11], Table 30.1 sketches a survey of different approaches that can be recorded when the specialized literature is inspected. Even hybrid systems have been proposed, mainly those combining potentiometric and voltammetric sensors [3,12], The combination of electronic noses and electronic tongues to improve detection or identification capabilities, in a sensor fusion approach, has also been proposed [13,14],... 

One of the promising directions for the development of innovative analytical method is the use of electrochemical methods whose speed and on-line capabilities nicely address the trends of automation and continuous processing in the food industry. Recently, devices such as electronic nose and electronic tongue have been proposed for the characterisation and authentication of different type of food products, and also for medical and environmental application. 

In literature there are several works about the combination of an electronic nose and an electronic tongue for clinical and food analysis [18-22], In all these works, it has been demonstrated that the discrimination and the classification properties are improved when information from both electronic nose and electronic tongue are combined. 

It must be pointed out that the electronic nose and the electronic tongue methodology are able to show the authenticity of the product only if supported by the multivariate statistical techniques useful not only to classify but also to validate and predict unknown samples. 

All data collected from the electronic nose (10 variables) and the electronic tongue (5 variables) were compared and elaborated by PCA. 

Electronic nose and electronic tongue are particularly suitable for carrying out rapid and objective sensory measurements, which are important in food industries. 

Given their non-specific nature, the electronic nose and electronic tongue sensor arrays can only perform yes or no tests inside the set of product. Contrary to traditional analytical methods, the electrochemical sensor responses do not need and do not provide information on the nature of the compounds under investigation, but only on digital fingerprint of the typical food products. 

The human nose and tongue are excellent quality-control sensors. For example, we can tell whether food is spoiled by its disagreeable odor and taste. Because it s impractical to use humans as sensors in industrial settings, several companies are now developing electronic noses. 

In a practical case, when the eqnations are nonlinear, the limit given by Rel. (2) still holds. However, the sitnation becomes mnch more complex, with several possible solntions being allowed, and the application of a neural network is required. The validity of Rel. (2) makes electronic noses and tongues cumbersome and expensive because all of the sensors have to exhibit different natures of their response. 

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