1. The document describes the human olfactory system and electronic nose (e-nose). 2. It explains that an e-nose aims to mimic the mammalian olfactory system and consists of a sensor array, transducer, and pattern recognition system to detect and identify odors. 3. The e-nose provides advantages over the human nose and gas chromatography-mass spectrometry (GC-MS) as it is portable, inexpensive, reproducible, and can detect hazardous gases.

1. ELECTRONIC NOSE
Montica Sawant
13FET1007

3. Odorants
inhaled through
nose
Reaches
olfactory
epithelium
containing
olfactory
receptors
Receptors
display affinity
for volatile
aroma
compounds get
activated
Tranduce an
electrical signal
along olfactory
nerves
Nerves
terminate in
olfactory
bulb(CNS)
IN CNS, cluster
of axons called
glomeruli
Glomeruli
contain
dendrites of
mitral cells
Mitral cells send
axons to
different parts
of brain
PIRIFORM
CORTEX: odour
identification
MEDIAL
AMYGDALA:
mating,
pheromones
ENTORHINAL
CORTEX: pairs
odours to
memories
IN CNS,ODORS
REPRESENTED
AS PATTERNS
OF NEURAL
ACTIVITY IN
TIME OR
SPACE
Human Olfactory System
1. Peripheral (sensing a stimulus and encoding it as an electric signal in
neurons)
2. Central (Signal processing in the CNS)
PERIPHERAL
CENTRAL

5. Why an e-Nose?
Human sniffers are costly when
compared to an e-nose
Speedy reliable new technique of gas
sensors used in an e-nose
Detection of hazardous or poisonous
gas not possible with a human sniffer
E-nose overcomes shortcomings of
the human olfactory system
No chance of difference in variation
Not subject in variation in individual
sensitivity
They are portable, cheap &
inexpensive
ENGINEEREDTO MIMICTHE MAMALIANOLFACTORY SYSTEM

6. Human
olfaction
Olfactory
receptors
Olfactory
Bulb
Brain
E-nose Sensor array
Signal
Transducer
Pattern
recognition
engine

7. Working
• Electronic Nose consists of 3 major parts
1. SAMPLE DELIVERY SYSTEM Enables generation of volatile aroma
compounds from headspace of a sample which is injected into the
detection system.
2. DETECTION SYSTEM Consists of a sensor (essentially a transducer)
and an A to D converter. Adsorption of volatile aroma compounds on
the sensor surface causes a change in the physical properties of the
sensor thus changing the electrical properties.A specific response is
recorded by the electronic interface transforming the signal into a
digital value.
3. COMPUTING SYSTEM Recorded Data computed on the basis of a
statistical model.Works to combine to responses of all signals using
Artificial Neural Networks, pattern recognition modules etc.This part
of the instrument performs global fingerprint analysis.

8. PRINCIPLE:An e-nose can be seen as an array of sensors able to generate an
electronic signal in response to simple or complexVolatile aroma compounds
present in the gaseous sample

10. Detection Systems
The sensor array is clearly the key element it forms the primary step in
the detection of an odorant. Most commonly used sensors are:
1. Conductivity sensors
Metal oxide sensors (change in conductivity in proportional to amount of
volatile compound absorbed)
Conducting polymer sensors (change in electrical Resistance by gas
adsorption)
2. Piezoelectric Sensors (Gas adsorption on sensor surface leads to
change in mass which changes the resonant frequency of crystal)
3. MetalOxideSiliconFieldEffectTransistor sensors ( Gas
adsorption on gate(sensing layer) changes the threshold voltage, thus
the conductivity)
4. Optical Sensors (work on means of light modulation measurement)
5. Gas Chromatography-Mass Spectroscopy
The analog signals thus transduced are converted into corresponding digital
siganls for further processing

11. Application SensorArray type
Grading of coffee blends or beans Metal Oxide
Roasting level of coffees Metal oxide
Grading of whiskeys piezoelectric
Grading of lagers and beers Metal oxide
Off-flavours in lagers Polymers
Freshness of fish Metal oxide
Freshness of meat MOSFET
Quality of grains electrochemical
Perfumes piezoelectric

12. Artificial Neural Networks
• In machine learning and cognitive science, artificial neural networks
(ANNs) are a family of statistical learning models inspired by biological
neural networks (the central nervous systems of animals, in particular
the brain) and are used to estimate or approximate functions that can
depend on a large number of inputs and are generally unknown.
• Artificial neural networks are generally presented as systems of
interconnected "neurons" which exchange messages between each
other.
• The connections have numeric weights that can be tuned based on
experience, making neural nets adaptive to inputs and capable of
learning.

13. Performing Analysis with an e-nose
1. As a first step, an e-nose needs to be be trained with qualified
samples so as to build a database of references
2. Then the instrument can recognize new samples by comparing
volatile compounds fingerprint to those contained in the
database
3. Thus they can perform the analysis, rapidly and accurately
To classify if grains are contaminated with aflatoxins?
1) Sample of dilute vapor pyrolyzed on heated platinum catalyst
2)Then passed through 4 conductivity sensors of different selectivity.
3) Each sample was measured with 4 different sensors at 4 different
temperatures generating 16 signals
4) Statistical computation with ANN

14. How does an e-nose work?
• The electronic nose is a device that uses an array of chemical
sensors (usually 4 to 32) tied to a data-processing system that
mimics the way a nose works.
• Sampling: the sensing port sniffs the headspace aroma
components.Two types of sampling: Static ( Constant pressure)
and dynamic (Variable pressure,The flow rate ofVOCs changes
thus giving inconsistent results)
• The sensors each produce independent responses to the different
chemical elements within a given sample
• The sum of all the sensors’ responses is a ‘pattern’ corresponding to
that odor.
• To identify an unknown sample, the data-processing system
compares its responses to a library of previously-measured
patterns.
DETECTION LIMIT: mid to low ppm range

15. Detection of banana odor with an
e-nose
First, Dilute samples were prepared to determine the detection limits
Then a sample of banana was injected

17. APPLICATIONS

18. In quality control laboratories for at line quality control such as
• Conformity of raw materials, intermediate and final products
• Batch to batch consistency
• Detection of contamination, spoilage, adulteration
• Origin or vendor selection
Monitoring of storage conditions in process and production departments
• Managing raw material variability
• Comparison with a reference product
• Measurement and comparison of the effects of manufacturing process on
products
• Following-up cleaning in place process efficiency
• Scale-up monitoring
• Cleaning in place monitoring.
• cosmetic and perfumes, and chemical companies.
In environmental monitoring
• For identification of volatile organic compounds in air, water and soil samples.
• For environmental protection.
• Various application notes describe analysis in areas such as flavor and fragrance,
food and beverage, packaging, pharmaceutical

19. Possible and future applications in the fields of health and security
• The detection of dangerous and harmful bacteria, such as software that has been
specifically developed to recognize the smell of the MRSA (Methicillin-resistant
StaphylococcusAureus).
• It could detect and therefore prevent contamination of other patients or equipment
by many highly contagious pathogens.
• The detection of lung cancer or other medical conditions by detecting theVOC's
(volatile organic compounds) that indicate the medical condition
• The quality control of food products as it could be conveniently placed in food
packaging to clearly indicate when food has started to rot or used in the field to
detect bacterial or insect contamination.
• The Brain Mapping Foundation used the electronic nose to detect brain cancer cells.
Possible and future applications in the field of crime prevention and security
• The ability of the electronic nose to detect odourless chemicals makes it ideal for use
in the police force, such as the ability to detect drug odours despite other airborne
odours capable of confusing police dogs.
• It may also be used as a bomb detection method in airports.Through careful
placement of several or more electronic noses and effective computer systems you
could triangulate the location of bombs to within a few meters of their location in less
than a few seconds.

20. GC-MS
Gas chromatography
Used for separation and
detection ofVolatile aroma
components
Working
1. Sample (ng) injected
through syringe
2. Vaporized in an oven (400°C)
3. separated in the column
based on the difference in
their volatilities(partition
chromatography) Stationary
phase: Packing, Mobile
phase: Inert Carrier Gas]
4. Chromatogram generated
based on individual retention
times, unique for each
component
Mass Spectroscopy
Individual components separated on the basis on
mass to Charge ratios, to generate a mass spectrum
unique to each substance.
Working
1. Very low concentration of sample molecules is allowed to leak into
ionization chamber (which is under very high vacuum) where they are
bombarded by high-energy electron beam.
2. Molecules fragment & positive ions produced are accelerated through
charged array into an analyzing tube.
3. Path of charged molecules is bent by an applied magnetic field. Ions
having low mass (low momentum) will be deflected most by this field &
will collide with walls of analyzer. Likewise, high momentum ions will
not be deflected enough & will also collide with analyzer wall. Ions
having proper mass-to-charge ratio, however, will follow path of
analyzer, exit through slit & collide with the Collector.
4. This generates an electric current, which is then amplified & detected.
By varying strength of magnetic field, mass-to-charge ratio which is
analyzed can be continuously varied.
5. Output of MS shows plot of relative intensity vs mass-to-charge ratio
(m/e). Most intense peak in spectrum is termed base peak & all others
are reported relative to it's intensity. Peaks themselves are typically very
sharp, & are often simply represented as vertical lines.
GC can separate volatile and semi-volatile compounds with
great resolution, but it cannot identify them. MS can provide
detailed structural information on most compounds such that
they can be exactly identified and quantified, but it cannot readily
separate them. Thus they are highly compatible and are used in
tandem

21. Block DiagramSLOW 
EXPENSIVE 
BULKY 

23. HUMANNOSE
Costly
Unreliable
Not reproducible
Cannot sense
hazardous gases
Subject to
Variation
Genetic
predisposition
Highest
sensitivity
GC-MS
Heavy and Bulky
Immobile
Expensive
Slow
Very sensitive
HighlyAccurate
E-NOSE
Inexpensive
Portable
Highly
reproducible
Wide range of
applications
Can detect
Hazardous gases
Different
detection
systems available
Less sensitive
than human nose
OVERVIEW