Electronic Tongue:A Review

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P. D. Chaudhari

The formulation’s organoleptic properties such as taste, mouth feel
and appearance are of considerable importance in differentiating products
in the market and can ultimately determine the success of the product.

Pharmaceutical taste assessment requires human test panel that increases time
and money to the development process.During the last decade, a multisensor system
and a device for the liquid analysis that can be collected under the term “Electronic
tongue” was developed. The electronic tongue is capable of discriminating between
substances with different taste modalities and can also distinguish different
substances eliciting same taste. The electronic tongue proved capable of distinguishing
between formulations with different levels of sweetener and flavour in a manner
that was consistent with their masking efficiency. In this review article development
and prospective research and development in the field of electronic tongue is

Taste is a survival mechanism, alerting us to potential harmful or potential
nutritious substances. Approximately 10, 000 chemoreceptors or taste buds reside
on the tongue. These chemoreceptors or taste buds fall into five basic categories:
sour, bitter, salt, sweet, and umani, with grouped receptors dissipated over
the surface of the tongue for each stimulus. Taste depends on physiological
and psychological factors1. Physiological factors such as temperature
and texture clearly affect the perception of taste. Psychological factors can
influence taste perception. Assessment of the taste of oral drug preparation
is of major interest in pharmaceutical industry, particularly for research-based
companies. Appropriate activity, selectivity and ADME (absorption, distribution,
metabolism, and elimination) are the influencing characteristic of any pharmaceutical
compound.  But it is more interest to formulate the active moiety into
patient consumable form2. As the active moiety in pharmaceutical
product cannot be therapeutically beneficial unless it has preference and acceptance
by the patient. Thus, pleasant taste is important for the therapeutic success
of the drug formulation.

Major Cause Non –Compliance

Many pharmaceutical drugs have unpleasant or bitter taste, which significantly affect patient acceptance, preference, compliance and after efficiency and safety, are of upmost importance in determining market success. Unpleasant taste has major consequence of low compliance level from infants, children and the elderly person3. So, pleasant taste is not only necessary for the patients having difficulty in swallowing solid dosage form but also to improve acceptance level from the different age groups.

Pleasant Taste: Complicates the Process

Many scientific techniques are employed for the avoidance of unpleasant or bitter sensory sensation:

a) The addition of aromas, sweeteners or cooling agents.

b)Microencapsulation, oral disintegrating tablets, ion exchange resin and other
coating techniques.

These additional processes in formulation increase the development time and
cost and delay the marketing of the new drug entity3. To date, the
only method employed for determination of taste intensity was human sensory
test. Drawbacks associated with these tests were: individual variability, impossibility
of on-line monitoring, subjectivity, adaptation, infections, harmful exposure
to hazardous compounds and mental state of panelist4. To facilitate
the work and address the difficulties associated with human panel test, a safe,
reliable, fast analyzing objective instrument was required. Thus, analytical
instrument capable of assessing taste properties with great benefit in making
the process of drug formulation safer, faster and eventually cheaper was developed
called “Electronic Tongue” an intelligent chemical sensor array system for taste

{mospagebreak title=Electronic tongue}


Electronic tongue is also called as artificial tongue, taste sensor4. Electronic taste instrument have been developed and optimized to answer some of these issues: reduces human sensory test panels, precise measurement of taste, formulation development time and cost and increases number of formulation candidates in prescreening steps. These sensor-based analyzer systems make a global analysis of total complex chemistry of the sample. Using organoleptic and chemical properties they perform qualitative as well as quantitative analyses of the product. The first multi-sensor system for liquid analysis was based on a poor selectivity approach introduced by Toko et al in 1990 and termed it as taste sensor system6. Later the instrument was named as “Electronic tongue”. The multi-sensor array system7,8 or electronic tongue shows the clear correlation of the instrument output with human perception for various substances. We can state Electronic tongue as “the system for automatic analysis of liquid including an array of non-specific chemical sensors with partial specificity for different component in liquid samples and an appropriate pattern recognition capable of recognizing the qualitative and quantitative composition of sample and complex solutions”. These system shows the following advantages: (a) requires small sample volume, (b) decreased measurement time, (c) objectivity compared to sensory panel, (d) small size of sensors, (e) easily operated by unskilled personnel and (f) amenability to fully automatic long-term routine application.

Important benefits of electronic tongue3

· Evaluate and quantify bitterness scores of new chemical entities (NCE).

· Optimizes and increases the formulation development process.

· Within the formulation, it measures the efficiency of complexation/coating.

·  Various combinations of sweeteners, enhancers, exhausters, aromas and masking agents can be tested in less time.

· Benchmark analysis: compares the palatability of new formulations with competitor’s products.

· Serving a quality control function for flavored products and excipients.

· Developing suitable matching bitter placebo for double blind clinical testing.

· During the scale-up process from small production batches to full-scale manufacturing, it defines consistency of organoleptic quality.


1. Identification between bitter, sweet and sour substances by using electronic tongue; study the possible memory effect of these substances on its sensors.

2. Separating the different substances eliciting the same taste (sour, bitter, sweet).

3. Evaluation of the ability of the electronic tongue to identify drug preparations containing active substance and placebo substance.

4. Check ability of electronic tongue to quantify the content of selected bitter and sweet substances.

5. Assessment of different taste masking approaches i.e. addition of different quantities of sweeteners and flavors to active substance to reduce its bitter intensity.

6. Quantification of the effect of taste masking of bitter substances by sweet ones2.

Correlation between human tongue and electronic tongue (Fig1)


Figure 1: The Electronic Tongue Concept9.

Mechanism involved for taste recognition in human and electronic tongue shows the same three levels: the receptor level [taste buds in humans, lipid membrane of sensors in the electronic tongues], the circuit level [neural transmission in humans, transducers in the electronic tongues], the perceptual level [cognition in the thalamus in humans, statistical analysis by software in the electronic tongues]. At the receptor level, to detect dissolved organic and inorganic compounds the sensor-probe assembly is used by the electronic tongue1. Each probe shows cross-sensitivity and selectivity so that each sensor could concurrently contribute to the detection of most substances found in the liquid matrix. These sensors are composed of an organic coating sensitive to the species to analyze in the samples and a transducer that allows converting the response of the membrane into signals that will be analyzed. At the circuit level, the sample is quantified, digitized and results are recorded [potentiometric readings]. At the perceptual level, process of taste perception or sensation that occurs in the computer where the electronic tongue systems statistical software interprets the sensor data into taste patterns. Depending upon the application for which it is applied, the data analysis can produce a variety of information.


As previously been established that the intensity of human response to taste
stimuli depends logarithmically on the concentration of the stimuli10.
Response of potentiometric chemical sensor is also logarithmic in relation
to the analyte concentration as follows the Nernst or Nikolsky-Eisenmann equation11,12.
This suggested that potentiometric sensors, exhibiting appropriate sensitivities,
might be particularly suitable for the instrumental evaluation of taste. Thus,
the principle of the electronic tongue13, 14 is based on utilization
of non-specific or low-selective potentiometric chemical sensors with enhanced
cross-sensitivity to as many different components in solution as possible.
Cross-sensitivity means that the sensor responds not to a single analyte but
to several substances simultaneously present in the analyzed media. Different
sensors should exhibit different sensitivity and selectivity pattern that
might be partly overlapping or even completely distinct. The responses of
the sensors are defined by the interaction with ionic and redox species, both
inorganic and organic at the membrane-solution interface. By comprising non-specific
sensors in a multisensor system, information about multiple substances or
groups of substances in complex media can be obtained. Pattern recognition
and /or multivariate calibration methods should be used to interpret complex
signals from such sensor arrays and for predicting both qualitative features
and quantitative parameters of analyzed multicomponent media.

Instrumentation (Fig 2)


Figure 2: Schematic Diagram of Electronic Tongue15.

Liquid Autosampler

Recently, liquid autosampler by ALPHA M.O.S. (Fig 3) consist of 16 beakers (80-ml capacity) and 48 beakers (20 ml capacity). A programmed sample agitator, a robotic sensor head and individual connections for each sensor are present16. The autosampler allows running automatically upto 15 different liquid samples plus one extra for sensor cleaning purpose.

Chemical Sensor or Sensor array

Chemical sensors have been widely used in such applications as critical care, safety, industrial hygiene, process controls, product quality controls, human comfort controls, emission monitoring, automotive, clinical diagnostics and home safety alarms. In these applications, chemical sensors have resulted in both economic and social benefits. Chemical sensors can be defined as small devices that result in transformation of chemical or biochemical information of a qualitative or quantitative type into an analytical useful signal by the process of chemical interaction between sample and sensors devices17. Currently these technologies are based on electrochemical sensors. The oxidation and reduction of chemical species on a conducting electrode can be observed by measuring the movement of charge. There are two primary methods of sensing electrochemical reactions. Potentiometric and amperometric potentiometric sensors17 can be used to measure the equilibrium potential established between the electrode material and the solution, a potential that is dependent on the chemistry involved. Amperometric sensors measure the current generated by a reaction and thus give a measure of reaction rates. Other sensing methods applied are voltammetry, optical sensors and biosensors4. By controlling the potential of the electrode relative to the solution and measuring the charge flow induced the presence of specific ions can be determined by observing the potential at which they undergo oxidation or reduction. This process is called a voltammetry. Biosensors are the sensors that use biomolecules and structures to measures something with biological importance or bioactivity. They are also called the subsets of chemical sensors, as the transduction mechanism is similar to those of chemical sensors. The sensors are made up of silicon transistors with organic coating that are necessary for the sensitivity and selectivity of each individual sensor to ensure good repeatability, sensitivity and selectivity18, The detecting sensor part consist of lipid/polymer membranes. These lipids membrane are made up of different types of lipids, which are pasted on the opening of the sensors19. Different types of lipids (in table 1) used are decyl alcohol (DA), Oleic acid (OA), Dioctyl phosphate (DOP), DOP: TOMA (5:5), DOP: TOMA (3:7), Trioctylmethyl ammonium chloride (TOMA), Oleylamine (OAm).

Table 1. Lipid used for the lipid/polymer membranes19 by
Toko et al.

Working electrode (channels)

Lipid (Abbreviation)

Content (ml)


Decyl alcohol (DA)



Oleic acid (OA)



Dioctyl phosphate (DOP)



DOP: TOMA (5:5)

0.107: 0.135


DOP: TOMA (3:7)

0.064: 0.189


Trioctylmethyl ammonium chloride



Oleylamine (OAm)


These lipid/polymer membranes were prepared by mixing each lipid with Polyvinyl
Chloride (PVC), plasticizer (Dioctylphenylphosphonate). The mixture is then
dissolved in tetrahydrofuran and immediately the mixture is transferred to petridish
that is stored at controlled temperature of 30 for 24 h.

The membrane obtained is transparent, colourless, and soft film of approximately 0.02 cm thickness. Each membrane possessed an electric charge due to each lipid. These are the working electrodes. The reference electrodes are made of an Ag wire whose surface was plated with Ag/AgCl, with an internal cavity filled with 3 M KCl solution and opening tube filled with 100 mM KCl and Agar. The measurement consists of a potentiometric difference between each individually coated sensor with the Ag/AgCl reference electrode. The reference electrode i.e. Ag/AgCl is the same for all application types. Electrode charge density of the lipid/polymer membrane surface and ion distribution near the surface of the membrane is changed due to taste substances. Therefore the total electrical charge on the lipid membrane gives the response membrane electric potential for the substances. Each sensor is partially selective to various chemical compounds and thus partial selectivity differs between sensors3. The cross sensitivity and selectivity of sensor arrays allow them to track any variation in the liquid matrix of samples. Thus, the electric potential response is different for chemical substances showing different taste qualities in each membrane. When experiment is carried out 50 mM KCl freshly prepared solution is used as reference solution and as rinsing fluid of electrodes after every measurement20. The measurement is carried out as follows:

1. Reference solution is measured (15 s)

2. Sample solution is measured (15 s)

3. Rinsing of electrodes with 50 mM KCl solution (120 s).

The difference between the response membrane electric potential to the sample and the reference solution gives the response potential to the sample. Each sample is analyzed three times by the rotation procedure.

Recently, nine different electrodes AU/C, OA/PEO, Pt/C, Nafion, OA/PVA, DA/PVA, RuO2, TEOS, and CNT/TEOS/Al2O3 have been produced to taste five basic qualities in human taste system and used in the potentiometric method for application6. All the nine sensing electrodes were produced in the laboratory at Center for Measurement Standards, Industrial Technology Research Institute, Hsinchu, 300, Taiwan, R.O.C.

Acquisition System:

The acquisition system establishes the communication between the sensor array and data processing system. The electrical potential responses produced at the sensor array are received by this system and it converts these electrical signals to digital signals with less distortion. An analog signal input devices, a filter mechanism and an analog to digital converter (ADC) should be present in the system as the speed of the sensor system is very slow, a low speed and high resolutions delta sigma ADC is enough to this electronic tongue system6. The filter mechanism is necessary to provide a clean and no distortion transmission channel between the sensors and ADC. Amplifier must be present in analog signal input devices as the electrical signals from the sensors are always small. Different sensors have different impedance hence it is also necessary to have impedance match circuit at this stage.

Data Processing System:

Interpretation of data with multivariable such as several sensors for multiple
samples required the use of statistical interpretation methods. Chemometric
techniques a type of multivariate statistic used in the analytical field provide
data processing, which consist of recognition, classification and identification
and multivariate calibration2. Recognition, identification and classification
is mainly done by Principle Component Analysis (PCA), Discrimination factorial
analysis (DFA) or by Partial least square (PLS) while multivariable calibration
is undertaken with the help of PLS. Data analyses and pattern recognition depending
on the study design is summarized in table 2.

Table 2. Perceptual recognition and its application in product development1.

Statistical analysis

Broad use


Principal component analysis (PCA)

Qualification, exploration and discrimination

Initial formulation studies

Discrimination factorial analysis (DFA)

Discrimination and identification

Recognition of unknown sample

Soft independent modeling of class analogy (SIMCA)

Good/bad modeling

Quality control against reference good product

Partial least square (PLS)


Quantification of bitterness against sensory panel

{mospagebreak title=Applications of Electronic tongue}


1. Foodstuffs Industry

· Food quality control during processing and storage (water, wine coffee, milk, juices…)

· Optimalization of bioreactors.

· Control of ageing process of cheese, whiskey.

· Automatic control of taste.

2. Medicine

· Non-invasive diagnostics (patient’s breath, analysis of urine, sweat, skin, odor).

· Clinical monitoring in vivo.

· Identification of unpleasant taste of pharmaceuticals.

3. Safety

· Searching for chemical/biological weapon.

· Searching for drugs, explosives.

· Friend-or-foe identification.

4. Environmental pollution monitoring

· Monitoring of agricultural and industrial pollution of air and water.

· Identification of toxic substances.

· Leak detection.

5. Chemical Industry

· Products purity.

· In the future – detection of functional groups, chiral distinction.

6. Quality control of air in buildings, closed accommodation (i.e. space station,
control of ventilation systems).

7. Legal protection of inventions – digital “fingerprints” of taste and odors.

Other Analytical Applications

Taste quantification and foodstuff recognition are the main area of application of the taste sensor.

Taste sensor sensitivity was studied in aqueous solution of five basic taste substances: salty (NaCl, KCl, and KBr), sour (HCl, citric and acetic acids), bitter (quinine), sweet (sucrose), and umani  (monosodium glutamate)21,22. Different patterns for chemical substances with different taste and similar patterns for substances with similar tastes were obtained by taste sensor.

Sensor sensitivity to sour and salty substances, e.g. HCl, organic acid, NaCl, KCl, KBr was approximately 50-60 mV/Px, to glutamate (umani substance) was approximately 13 mV/pX, to quinine hydrochloride (bitter substance) was approximately 50 mV/decade, to natural bitter alkaloid caffeine was only approximately 5 mV/pX, to natural sweet substances (sucrose) was very low, whereas to an artificial sweetener (aspartame) was about 40 mV/pX. For this reason an enzymatic glucose-selective sensor was used with the taste sensor when determination of the sugar concentration was crucial23.

Bitterness of 18 different antibiotics and antiviral drug formulation for pediatric use were evaluated as suspension in water and in an acidic sport drink24. Bitterness intensities of suspension in an acidic sport drink and in water were compared using the taste sensors. Suspension in an acidic sport drink would enhance or reduce the bitter intensity of the pediatric drug formulation compared with suspension in water; taste sensors were able to predict it.

Bitter taste suppression was studied by using sweet substances to mask the bitterness of the drug. Degree of bitterness for quinine solution and modeling was calibrated by taste sensor by using principal component regression. The bitterness of the mixed solution was predicted by use of the model. The mixed solution contained 1 mmole L-1 of quinine solution and 1mmol L-1 to 1moleL-1of sucrose solution19 and phospholipid cocktail20. As the concentration of the sucrose increase to 1 mole L-1 degree of bitterness estimated dropped significantly. The same experiment was repeated for artificial sweet substances-phospholipids, which is used in pharmacology to mask the bitter taste of drug. 

Different kinds of commercial mineral water were classified by using the taste sensor25. Mineral water was classified on the basis of the hardness of water. The tastes of 20 bottled nutritive drinks, all commercially available on the Japanese market were evaluated both in human sensory test and by using electronic tongue. The electronic tongue was able to differentiate between low price group products, middle price group products, high price group products and played important role in evaluating the palatability of bottled nutritive drinks26.

Different varieties of tomato were recognized using taste sensor by measuring the crushed tomatoes27. The taste sensor were first calibrated in canned tomato juice to which four basic taste substances, NaCl, citric acid, monosodium glutamate, and glucose were added, for quantification of tomato taste. Taste sensors also found a wide use in diary industry. Taste sensors were found capable in discriminating between fresh and spoiled milk and to follow the deterioration of the milk quality when it was stored at room temperature. Two packaged commercial milk; the ultra high temperature (UHT) and the pasteurized milk were tested28.

Ten brands of coffee of different origin (one of which was used as standard)
were measured at  60oC by using taste sensors29.
Oleic acid contained in sensor was correlated with coffee acidity as perceived
by tasters with a correlation coefficient of 0.98. The correlation between coffee
bitterness and the response of the sensor contained dioctyl phosphate (DOP)
and Trioctylmethyl ammonium chloride (TOMA) was found to be 0.94. An electronic
tongue made up of micro-sensor array of three enzyme sensors had been developed
for determination of glucose, urea, and triglyceride (triolein)30.
Tasting extracts of American oak (Quercus alba) was difficult due to
the variety of bitter and astringent chemical compounds that they contain. These
extracts were analyzed by an array of global selectivity chemical electronic
tongue sensors, which offered a simple and rapid method of analysis of oak wood
extract with excellent repeatability31. The components of medical
liquids- dialysis solutions for an artificial kidney that contained Ca2+,
HCO3-, H2PO4-, Na+, K+,
Cl-, Mg2+, pH were determined by quantitative performance
of the electronic tongue 32. Measurement procedures were developed
such that the system detects with precision of 2 % - 4 % acceptance for clinical


Electronic tongues are an emerging and promising field in modern chemical sensor science. The electronic tongue proved to be a valuable tool for assessment and prediction of the taste of pharmaceuticals and related products. The system could potentially assist, or even replace, a sensory panel in certain type of routine analysis in pharmaceutical development and production. Electronic tongue measurements can be performed as often as analytically needed without the regulatory hurdles or expense of human testing. The exposure and risk of using employee to test products is greatly reduced while permitting better analytical results to quickly define the best formulation and get the product to the market. This direction of analytical chemistry and sensor is quite young and research in the area remains substantially semi-empirical. Electronic tongue systems seem to be very useful for process monitoring and as a quality-control tool in the food industry, in clinical analysis, and in research laboratories.


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{mospagebreak title=Authors Profile}

Authors Profile


1University Institute of Pharmacy, Bundelkhand university, Jhansi,

2Department of Pharmaceutics, Padm. Dr. D. Y. Patil Institute
of Pharmaceutical  Sciences and Research, Pimpri, Pune-411018, (MS),  India.

3Smt. S. S. Patil Institute of technology (Pharmacy), Chopda, Dist.
 Jalgaon. (MS), India.

Email: pdchaudhari21@rediffmail.com

Telephone- +91 – 020 – 27420026, 27420261 Fax No.- +91 – 020 - 27420261



Dr. P. K. Sharma,
University Institute of Pharmacy, Bundelkhand university, Jhansi, (MP), India.


P. D. Chaudhari
Asst. Prof. of Pharmaceutics,
Dept. of Pharmaceutics, Pad. Dr. D. Y. Patil Institute of Pharmaceutical Sciences
and Research,
Pimpri, Pune-18, Maharasthra, India.
Email: pdchaudhari_21@yahoo.com
Telephone No: +91-020-27420026, 27420261.
Fax - +91-020-27420261.


Mrs. S. P. Chaudhari
Dept. of Pharmaceutics, Pad. Dr. D. Y. Patil Institute of Pharmacy, Pimpri,


Mr. A.P. Chaudhari,
Smt. S.S.Patil Institute of Technology (Pharmacy), Chopda, Dist. Jalgaon.


Nilesh S Barhate, M.Pharm.
Dept. of Pharmaceutics, Pad. Dr. D. Y. Patil Institute of Pharmaceutical Sciences
and Research


Chetan J Mistry, M.Pharm.
Dept. of Pharmaceutics, Pad. Dr. D. Y. Patil Institute of Pharmaceutical Sciences
and Research

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