- The document presents a case study on using an electronic nose to evaluate the quality of three types of grapes (green, red, black) over 10 days of storage. - Principal component analysis was used to analyze the sensor response data and distinguish the grapes at different stages of ripening and quality degradation. - The results showed the electronic nose could clearly identify and differentiate the grapes based on storage time, with samples further from the origin on the PCA plots indicating poorer quality. This demonstrated the potential of electronic noses for non-destructive quality evaluation of fruits.

1. Presented by
ROHIT YADAV
M.TECH (FOOD PROCESS ENGINEERING)
ROLL NO. 19AG63R23
“ELECTRONIC
NOSE”
DEPARTMENT OF AGRICULTURALAND FOOD ENGINEERING
INDIAN INSTITUTE OF TECHNOLOGY, KHARAGPUR
WEST BENGAL,721302

2. CONTENT
• INTRODUCTION
• PRINCIPLE OF ELECTRONIC NOSE
• WORKING
• APPLICATIONS OF ELECTRONIC NOSE
• ADVANTAGE AND DISADVANTGES
• CASE STUDY
2

3. INTRODUCTION 3
 How does the nose work and what is its function?
Smell enters through nostrils
Dissolve in mucus
This stimulate the hair like endings
of olfactory receptor cells
This generates a nerve
impulse which travels to brain

4. 4
ANALOGY BETWEEN ELECTRONIC NOSE
AND HUMAN NOSE

5. PRINCIPLE OF ELECTRONIC
NOSE
• Electronic nose an instrument designed to detect and discriminate among complex
odours by using an array of sensors.
• Its working is similar to that of a human nose.
• It includes a sampling system, an array of chemical gas sensors, an analog to digital
converter (ADC) and a computer microprocessor with sample classification methods
(pattern classification algorithm).
5

6. PARTS OF AN ELECTRONIC NOSE
6

7. WORKING OF AN E-NOSE
7
• First, an air sample is pulled by a vacuum pump.
• It is then led through a tube into a small chamber housing the electronic sensor array.
• Next, the sample handling units expose the sensors to the odorant.
• During this interval, the response time of the sensor is recorded and delivered to the
signal processing unit.

8. CONTD.
• The pattern of response across all the sensors in the array is used to identify and
characterize the odour.
• The period during which odorant is applied is called the response time of the sensor
array.
8

9. • The sensor’s response is converted into electronic signal by using a transducer and is
processed by signal processing unit.
9

10. APPLICATIONS OF ELECTRONIC NOSE
1. Medical diagnosis and health monitoring
2. Environmental monitoring
3. Analysis of fruit ripening
4. Adulteration in food products
5. Detection of explosives
10

11. ADVANTAGES
1
• Detection of poisonous gases is possible.
2
• Can be done in real time for long periods.
3
• Cheaper than trained human sniffers.
4
• E-nose has a wide range of sensitivity
5
• Results obtained by e-nose are fast and more accurate
11

12. DISADVANTAGES
1
• Time delay between successive tests
2
• Can only identify a standard set of odours which is stored in its database.
3
• It can not mimic the complex human olfactory system as such.
4 • They have shorter lifetime because of the sensors employed in them.
5
• E-noses available in market are not economical.
12

13. Title:
Post-harvest Quality
Evaluation of Grapes
using Non-destructive
Electronic Nose
Authors:
Rajin S.M., Ataul
Karim, Samad
Salina Abdul, Muad
Anuar Mikdad.
Year: 2015
12
CASE STUDY

14. OBJECTIVE
To evaluate the quality of three different types of grapes based on the change in
aroma at different intervals of time. Principal Component Analysis (PCA) is used to
distinguish and find a pattern of the quality degradation.
13

15. MATERIALS AND METHODS
1. Experimental Procedure and Sample
480 grapes of each colour(green,red,black) were taken then washed, dried and
then stored in an airtight 50 ml cylindrical glass tube.
Grapes are divided into 120 groups consisting four grapes each.
Each tube is individually numbered and stored in the refrigerator at constant
temperature of 4°C.
Every day 12 tubes of each color are taken out for analysis for 10 consecutive
days.
14

16. 2. Hardware
The constructed electronic
nose consists of mainly five
parts; sensor chamber,
sample chamber, data
acquisition system & control
unit, power supply and a
computer containing a
graphic user interface (GUI)
15

17. 3. Data Acquisition
12 tubes of the same type of grapes are taken out of the refrigerator and are
evaluated using electronic nose.
An air pump is used to push the volatile gas from the sample chamber to the
sensor array.
After a sample is evaluated, the sensor chamber is cleaned and the same
procedure is followed for rest of the 12 samples.
Same procedure followed for other colour grapes.
16

18. 17
LIST OF SENSORS USED AND ITS
TARGETED GASES

19. 4. Principal Component Analysis (PCA)
Principal Component Analysis (PCA) is a simple analysis, which helps in
simpler representation of data, reduction in memory and faster classification.
18

20. RESULTS AND DISCUSSION
• Each sensor generates a different voltage response depending on the volatile
gas and its strength present in the grape sample
• Signal responses are the change in the ratio of the voltage response between the
minimum voltage (Vmin) and the maximum Voltage (Vmax).
• Fig.1 shows response obtained from E-nose when sample were kept in sample
chamber.
• For every sample E-nose was activated for 400 seconds.
19

21. • Fig. 2 shows a typical voltage response obtained by TGS822 sensor from measuring
green grapes.
• Relative voltage response was calculated using Vmin and Vmax.
Vr=(Vmax-Vmin)/Vmin
• The Vr values obtained from 8 sensors are the features which were used for analysis.
• the Vr of the 12 samples of that day were averaged and plotted against the number of
days, for all sensors as shown in Fig. 3.
20

22. • Principal Component Analysis (PCA) was performed on each type of grapes to
investigate the electronic nose’s performance and the ability to distinguish different
ripeness stages.
• The PCA plots show a clear distinction between the different days of grapes stored
and its quality.
• The analysis also shows a similar pattern for all three types of grapes.
21

23. • It shows that the features are projected further away from the y-axis as the number of
days increase. (Fig.4,5,6).
• Classifying these clusters into groups can assist in the evaluation of grape quality;
day 1-3 being good to day 10-11 being very poor quality.
22

24. 23
Fig. 1 Response of E-nose for grape fruit
aroma

25. 24
Fig.2 Response obtain from
sensor TGS822

26. 25
Fig.3 Relative voltage response obtain from sensors

27. 26
Fig.4 PCA analysis of green grapes

28. 27
Fig.5 PCA analysis of red grapes

29. 28
Fig.6 PCA analysis of black grapes

30. CONCLUSION
• The paper has presented a simple way to evaluate the quality of fruits using a lab
manufactured electronic nose.
• Principal component analysis was used to investigate the efficiency of e-nose in
distinguishing grapes at different storage periods.
• The result shows that the electronic nose can identify and differentiate the difference
in quality of grapes over a period of time.
29

31. • New technological discoveries in electronic sensor design allow for the development
of new gas sensing capabilities for electronic noses.
• These discoveries find new ways to exploit the electronic nose to solve many gas-
detection problems arising in the agricultural and food industries.
30

32. REFERENCE
• Athamneh, A. I., Zoecklein, B. W., & Mallikarjunan, K. (2008). Electronic nose evaluation of
Cabernet Sauvignon fruit maturity. Journal of Wine Research, 19(1), 69-80.
• Breijo, E. G., Guarrasi, V., Peris, R. M., Fillol, M. A., & Pinatti, C. O. (2013). Odour sampling
system with modifiable parameters applied to fruit classification. Journal of food
engineering, 116(2), 277-285.
• Brezmes, J., Fructuoso, M. L., Llobet, E., Vilanova, X., Recasens, I., Orts, J., ... & Correig, X.
(2005). Evaluation of an electronic nose to assess fruit ripeness. IEEE Sensors Journal, 5(1),
97-108.
• Gómez, A. H., Hu, G., Wang, J., & Pereira, A. G. (2006). Evaluation of tomato maturity by
electronic nose. Computers and electronics in agriculture, 54(1), 44-52.
• Karim, A., RAJIN, S., Salina Abdul, S. A. M. A. D., & Anuar Mikdad, M. U. A. D. (2015).
Post-harvest Quality Evaluation of Grapes using Non-destructive Electronic Nose. Journal of
Electrical & Electronics Engineering, 8(2).
31

33. • Wei, X., Shao, X., Wei, Y., Cheong, L., Pan, L., & Tu, K. (2018). Rapid detection of
adulterated peony seed oil by electronic nose. Journal of food science and technology, 55(6),
2152-2159.
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