Chemometric-based electronic nose application to pork oil and olive oil using the odor pattern classifications

Tazi, Imam (2018) Chemometric-based electronic nose application to pork oil and olive oil using the odor pattern classifications. Jurnal Neutrino, 10 (2). pp. 52-58. ISSN 2460-5999

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Abstract

A chemometric-based electronic nose has designed for analyzing pork oil andolive using the odor pattern classifications of a chemometric-based electronic nose. The electronic nose (e-nose) built from a combination of several chemical sensors derived from a semiconductor. The data retrieval was done by vaporizing the sample, then being captured by the sensor and identified by the electronic nose (enose).The output data from the electronic nose is the voltagereleased by each sensor.Samples analyzed were 100% olive oil, 100% pork oil and a combination of olive oil and pork oil with a ratio of 50%: 50%.The result of pattern classification using linear discriminant analysis (LDA) method shows that each sample is clustered well with the percentage of first discriminant function value is 87,9% and second discriminant function is 12,1%.

Item Type: Journal Article
Keywords: electronic nose; LDA; pork oil; olive oil
Subjects: 02 PHYSICAL SCIENCES > 0299 Other Physical Sciences > 029904 Synchrotrons; Accelerators; Instruments and Techniques
Divisions: Faculty of Mathematics and Sciences > Department of Physics
Depositing User: Imam Tazi
Date Deposited: 09 Jun 2020 22:12

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