Application of principal component analysis and discrete wavelet transform in electronic nose for herbal drinks classification

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Dyah Kurniawati Agustika, Kuwat Triyana

2016 AIP Conference Proceedings Vol. 1755 Conference paper Cited by 3 SDG 16SDG 3SDG 8SDG 17 Quartile

Abstract

An electronic nose (e-nose) consisting of a commercially metal oxide based gas sensor array has been used for measuring rapidly the odor of three kinds of herbal drink (hereafter as jamu). This research was focused on how to apply the existing preprocessing techniques on the analysis the e-nose output. In this case, two pre-processing techniques were used, i.e. the discrete wavelet transform (DWT) and a statistical technique of principal component analysis (PCA). The DWT of daubechies3 level one was used as the preprocessing technique. The first investigation was focused on differentiation of three kinds of jamu, and the second one was focused on the detection of the spoilage degree of jamu during 5 days consecutively. The total plate count (TPC) was also measured to confirm the PCA score plot of spoilage levels by describing more than 95% of the total variance in the data. It counts the number of the bacterial colonies on the jamu. As results, the e-nose is able to differentiate three kinds of fresh jamu. The spillage levels shown by the e-nose is in accordance with the TPC measurement. Therefore, the e-nose may show a promising rapid instrument for quality assessment of jamu and other herbals. © 2016 Author(s).

Affiliations

Department of Physics Education, Universitas Negeri Yogyakarta, Jl. Colombo No. 1, Yogyakarta, Indonesia; Physics Department, Universitas Gadjah Mada, Sekip Utara BLS 21, Yogyakarta, Indonesia; Interdisciplinary Halal Research Group, Universitas Gadjah Mada, Sekip Utara, Yogyakarta, Indonesia

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