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| Electronic Nose for Black Tea Quality Evaluation Using Kernel Based Clustering
Approach
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Full
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Source |
International Journal of Image Processing (IJIP) |
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Table of Contents |
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Complete Issue PDF(9.16MB) |
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Volume: 6 Issue: 2 |
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Pages: |
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Publication
Date: April 2012 |
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ISSN
(Online): 1985-2304 |
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Pages |
86 - 93 |
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Author(s) |
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Published
Date |
16-04-2012 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
INFORMATION |
| Keywords Abstract References Cited by Related Articles Collaborative
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KEYWORDS: Kernel, Feature Space, Nonlinear Mapping, Electronic Nose |
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| Black Tea is conventionally tested by human sensory
panel called “Tea Tasters”, who assign quality scores
to different teas. In this paper electronic nose based
evaluation of black tea samples have been described.
One of the principal problems encountered in the
above studies is collection of tea samples. These tea
industries in India are spread over dispersed locations
and quality of tea varies considerably on agroclimatic
condition, type of plantation, season of flush
and method of manufacturing. As a result the nature
of data is overlapped, when it is collected from the
electronic nose even if, it belongs to different scores
of tea. For better separation among the different
scores of tea samples, the kernel principal component
analysis (KPCA) and kernel discriminate analysis
(KLDA) have been employed in the clustering
algorithm for black tea aroma discrimination with
electronic nose .The performance using KPCA and
KLDA is very effective as well as most interesting. |
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| Ashis Tripathy : Colleagues
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| A. K. Mohanty : Colleagues
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| Mihir Narayan Mohant : Colleagues
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