**3.4. Electrochemical sensor analysis for the traceability of olive oil**

Electronic noses (e-noses) and electronic tongues (e-tongues) for liquid analysis, based on the organizational principles of biological sensory systems, developed rapidly during the last decade. E-noses and e-tongues crudely mimic the human smell and taste sensors (gas and liquid sensors) and their communication with the human brain. The human olfactory system is by far the more complex and contains thousands of receptors that bind odor molecules and can detect some odors at parts per trillion levels (Breer, 1997) and include between 10 and 100 million receptors (Deisingh *et al*., 2004). Apparently some of the receptors in the olfactory mucus can bind more than one odor molecule and in some cases one odor molecule can bind more than one receptor. This results in a mind-boggling amount

of combinations that send unique signal patterns to the human brain. The brain then interprets these signals and makes a judgment and/or classification to identify the substance consumed, based in part, on previous experiences or neural network pattern recognition. The electronic nose often consists of non-selective sensors that interact with volatile molecules that result in a physical or chemical change that sends a signal to a computer which makes a classification based on a calibration and training process leading to pattern recognition. The non-selectivity of the sensors results in many possibilities for unique signal combinations, patterns or fingerprints. The human tongue contains sensors, in the form of 10,000 taste buds of 50–100 taste cells each (Deisingh *et al*., 2004) for sweet, sour, bitter, salty and umami and is much less complicated than the human olfactory system. The e-tongue then uses a range of sensors that respond to salts, acids, sugars, bitter compounds, etc. and sends signals to a computer for interpretation. The interpretation of the complex data sets from e-nose and e-tongue signals is accomplished by use of multivariate statistics. For nonlinear responses, artificial neural networks (NAA) can be used for modeling the data. Biosensors are also being developed, but are not yet commercialized. In contrast to chemical sensing materials, that are broad spectrum to generate characteristic response patterns, there are biological systems. The problem with chemical sensors is that these systems are extensive, require large sample sizes for analysis, have low sensitivity and poor specificity compared with the human nose. The bioelectronic nose utilizes olfactory receptors as sensing mechanisms and are cell or protein-based to mimic a mammalian olfactory system (Lee and Park, 2010). Another type of sensing system is based on colorimetric sensor array built in disposable chips (Suslick *et al.,* 2010). These arrays are based on the chemical interactions between the analyte and a chemical dye. They are being developed for volatile and non volatile molecules (Zhang *et al*., 2006; Zhang and Suslick, 2007; Musto *et al.,* 2009) for applications by the food industry.

Olive Oil Traceability 279

There are several reviews on the subject of e-nose and e-tongue technology, including reviews on e-noses (Di Giacinto et al., 2010; Wilson and Baietto, 2009), biomimetic/biotechnology e-nose and/or e-tongue sensing systems (Rudnitskaya and Legin, 2008; Ghasemi-Varnamkhasti *et al*., 2010)], applications for e-noses and e-tongues (Scampicchio et al., 2008), neural networks for e-noses (Lu *et al*., 2000), pattern recognition techniques (Berrueta *et al.,* 2007); meat quality assessment by e-nose (Ghasemi-Varnamkhasti *et al.,* 2009) and computational methods for analysis of e-nose data (Jurs *et al.,* 2000). This review will concentrate on the recent literature on applications of e-noses and e-

Some varieties of olive oil are recognized as being of higher quality because they derive from well-defined geographical areas, command better prices and generally are legally protected. Indeed, the aim of Protected Designations of Origin (PDO), Protected Geographical Indication (PGI) and Traditional Specialty Guaranteed (TSG) is to add value to

The development of accurate analytical fingerprinting methods for the authentication of olive oils and for the certification of the geographical origin is an actual issue and an important challenge. In fact, to protect the rights of both the consumer and honest producers and, to enforce the laws, it is important to develop analytical methods to measure the authenticity of the samples, to verify the geographical or cultivar origin and to provide the

*Agricultural Research Council - Olive Growing and Oil Industry Research Centre, Rende (CS), Italy* 

Financial support for this study was provided by Italian Ministry of Agriculture, Food and Forestry through the project GERMOLI "Salvaguardia e valorizzazione del GERMoplasma

Alonso-Salces, R. M., Moreno-Rojas, J. M., Holland, M. V., & Guillou, C. (2011b). Authentication of Virgin Olive Oil using NMR and isotopic fingerprinting. In series: Food Science and Technology, Nova Science Publishers, ISBN 978-1-61122-309-5, New

certain specific high quality products from a particular origin.

, Cinzia Benincasa and Innocenzo Muzzalupo

tongues in the food industry.

presence/absence of adulterants.

**Author details** 

**Acknowledgement** 

**5. References** 

York.

Corresponding Author

 \*

OLIvicolo delle collezioni del CRA-OLI"

Enzo Perri\*

**4. Conclusions** 

The advantage of the human sensory system is that the brain can receive signals from both olfactory and tongue receptors and integrate both sets of data to form classifications and/or judgments. The e-nose and e-tongue are not integrated since each has its own software package, but the data from both instruments could be imported into another program and integrated. The disadvantage of the human sensory system is that no two brains are alike (of course from another point of view, this is a good thing), and the same brain may react differently from one day to the next, depending on an individual's health, mood or environment, making the data subjective. On the contrary, e-nose and e-tongue instruments can be calibrated to be reliably consistent and can give objective data for important functions like quality and safety control. These instruments can also test samples that are unfit for human consumption. A disadvantage for the e-nose and e-tongue systems (as with humans) is that they are also affected by the environment including temperature for both enose and e-tongue and humidity for e-nose, which can cause sensor drift, although calibration systems and built-in algorithms help compensate for this. There are more or at least not less different types of sensing materials for e-tongue (liquid sensors) compared to e-nose systems, and liquid sensors often possess higher selectivity and significantly lower detection limits compared to the gas sensors (e-nose).

There are several reviews on the subject of e-nose and e-tongue technology, including reviews on e-noses (Di Giacinto et al., 2010; Wilson and Baietto, 2009), biomimetic/biotechnology e-nose and/or e-tongue sensing systems (Rudnitskaya and Legin, 2008; Ghasemi-Varnamkhasti *et al*., 2010)], applications for e-noses and e-tongues (Scampicchio et al., 2008), neural networks for e-noses (Lu *et al*., 2000), pattern recognition techniques (Berrueta *et al.,* 2007); meat quality assessment by e-nose (Ghasemi-Varnamkhasti *et al.,* 2009) and computational methods for analysis of e-nose data (Jurs *et al.,* 2000). This review will concentrate on the recent literature on applications of e-noses and etongues in the food industry.
