Data Mining Techniques in Food Safety
Food safety is an important consideration because the reduced quality of freshness may result in food poisoning that can threaten our health. There are many methods used to test the freshness of food such as visual appearance as well using a variety of devices. One of the devices that can be use...
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my.uniten.dspace-153102020-09-07T09:11:39Z Data Mining Techniques in Food Safety Rajina R Mohamed Razali Yaacob2 , Mohamad A Mohamed Tengku Azahar Tengku Dir F A Rahim Abd Rasid Mamat Electronic Nose Food Freshness Food Classification Food safety is an important consideration because the reduced quality of freshness may result in food poisoning that can threaten our health. There are many methods used to test the freshness of food such as visual appearance as well using a variety of devices. One of the devices that can be used to test the freshness of food is the E-Nose. E-nose is an instrument that enables the discrimination of gas and odor in food industry for quality and safety purposes. It is a well-established instrument to detect odor and aroma not only in the food industry, but also in health-diagnosis, defense, and environmental industry. Generally, E-nose mimics human olfactory sense to detect and discriminate gasses or volatile organic compound from a few objects such as food, chemicals, explosive etc. Thus, E-nose can be used to measure gas emitted from food due to its ability to measure gas and odor. Principally, the E-nose operates by using a number of sensors to response to molecules from vaporous compound. Each sensor will respond to their specific gas respectively. These sensors are the major component in electronic nose to sense and obtain percentage of gases release by the compound samples. All gases detected by sensors will be recorded, that to be analyzed using classification method. Classification is a way to distinguish a mixture odor/aroma obtained from gas sensors using a method of machine learning. In this paper, we discussed briefly about electronic nose, it’s principle of work and classification method and in order to classify food freshness. 2020-09-07T09:11:38Z 2020-09-07T09:11:38Z 2020-03 Article http://dspace.uniten.edu.my/jspui/handle/123456789/15310 en International Journal of Advanced Trends in Computer Science and Engineering |
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Electronic Nose Food Freshness Food Classification Rajina R Mohamed Razali Yaacob2 , Mohamad A Mohamed Tengku Azahar Tengku Dir F A Rahim Abd Rasid Mamat Data Mining Techniques in Food Safety |
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Food safety is an important consideration because the reduced
quality of freshness may result in food poisoning that can
threaten our health. There are many methods used to test the
freshness of food such as visual appearance as well using a
variety of devices. One of the devices that can be used to test
the freshness of food is the E-Nose. E-nose is an instrument
that enables the discrimination of gas and odor in food
industry for quality and safety purposes. It is a
well-established instrument to detect odor and aroma not only
in the food industry, but also in health-diagnosis, defense, and
environmental industry. Generally, E-nose mimics human
olfactory sense to detect and discriminate gasses or volatile
organic compound from a few objects such as food, chemicals,
explosive etc. Thus, E-nose can be used to measure gas
emitted from food due to its ability to measure gas and odor.
Principally, the E-nose operates by using a number of sensors
to response to molecules from vaporous compound. Each
sensor will respond to their specific gas respectively. These
sensors are the major component in electronic nose to sense
and obtain percentage of gases release by the compound
samples. All gases detected by sensors will be recorded, that
to be analyzed using classification method. Classification is a
way to distinguish a mixture odor/aroma obtained from gas
sensors using a method of machine learning. In this paper, we
discussed briefly about electronic nose, it’s principle of work
and classification method and in order to classify food
freshness. |
format |
Article |
author |
Rajina R Mohamed Razali Yaacob2 , Mohamad A Mohamed Tengku Azahar Tengku Dir F A Rahim Abd Rasid Mamat |
author_facet |
Rajina R Mohamed Razali Yaacob2 , Mohamad A Mohamed Tengku Azahar Tengku Dir F A Rahim Abd Rasid Mamat |
author_sort |
Rajina R Mohamed |
title |
Data Mining Techniques in Food Safety |
title_short |
Data Mining Techniques in Food Safety |
title_full |
Data Mining Techniques in Food Safety |
title_fullStr |
Data Mining Techniques in Food Safety |
title_full_unstemmed |
Data Mining Techniques in Food Safety |
title_sort |
data mining techniques in food safety |
publishDate |
2020 |
url |
http://dspace.uniten.edu.my/jspui/handle/123456789/15310 |
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1680859860661436416 |