A Comparison Study Of Three Nonlinear Multivariate Data Analysis Methods For Smartongue: Kernel PCA, LLE and Sammon mapping

Tian Shiyi; Chen Min; Deng Shaoping

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A Comparison Study Of Three Nonlinear Multivariate Data Analysis Methods For Smartongue: Kernel PCA, LLE and Sammon mapping

Tian Shiyi,Chen Min,Deng Shaoping * #

School of Food Science and Biotechnology (SFSB), Zhejiang Gongshang University

*Correspondence author

#Submitted by

Subject:

Funding: Specialized Research Fund for the Doctoral Program of Higher Education（No.No. 200803530002）

Opened online:10 February 2012

Accepted by: none

Citation: Tian Shiyi,Chen Min,Deng Shaoping.A Comparison Study Of Three Nonlinear Multivariate Data Analysis Methods For Smartongue: Kernel PCA, LLE and Sammon mapping[OL]. [10 February 2012] http://en.paper.edu.cn/en_releasepaper/content/4463710

Smartongue was a voltammetric electronic tongue developed by the laboratory, which was based on multifrequency large amplitude pulse voltammetry (MLAPV) and a non-specific sensors array of six naked metallic electrodes. Three non-linear multivariate data analysis methods, such as Kernel principal component analysis (Kernel PCA), Locally linear Embedding (LLE) and Sammon mapping were studied about the data processing ability for Smartongue. Normal principal component analysis (PCA) was used as a reference method and discrimination index (DI value) was used as a quantitative indicator for evaluation the separation ability of different plot. The result indicated that non-linear data processing methods had a more powerful ability than PCA for processing the data of Smartongue. Among these techniques, Sammon mapping successfully classified three bitter solutions, six artificial green tea products and five milk power solutions with different storage time well and exhibited the best data processing ability for extracting the useful information from the data of Smartongue.

Keywords:Food science; Nonlinear multivariate data analysis; Smartongue

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