Open Access
ARTICLE
Chinese Spirits Identification Model Based on Mid-Infrared Spectrum
Wu Zeng1, Zhanxiong Huo1, *, Yuxuan Xie2, Yingxiang Jiang1, Kun Hu1
1 School of Electrical and Electronic Engineering, Wuhan Polytechnic University, Wuhan, 430000, China.
2 Gina Cody School of Engineering and Computer Science, Concordia University, Montreal, H3G 1M8, Canada.
* Corresponding Author: Zhanxiong Huo. Email: .
Computers, Materials & Continua 2020, 64(3), 1869-1883. https://doi.org/10.32604/cmc.2020.010139
Received 13 February 2020; Accepted 03 May 2020; Issue published 30 June 2020
Abstract
Applying computer technology to the field of food safety, and how to identify
liquor quickly and accurately, is of vital importance and has become a research focus. In
this paper, sparse principal component analysis (SPCA) was applied to seek sparse
factors of the mid-infrared (MIR) spectra of five famous vintage year Chinese spirits. The
results showed while meeting the maximum explained variance, 23 sparse principal
components (PCs) were selected as features in a support vector machine (SVM) model,
which obtained a 97% classification accuracy. By comparison principal component
analysis (PCA) selected 10 PCs as features but only achieved an 83% classification
accuracy. Although both approaches were better than a direct SVM approach based on
the classification results (64% classification accuracy), they also demonstrated the
importance of extracting sparse PCs, which captured most important information. The
combination of computer technology SPCA and MIR provides a new and convenient
method for liquor identification in food safety.
Keywords
Cite This Article
W. Zeng, Z. Huo, Y. Xie, Y. Jiang and K. Hu, "Chinese spirits identification model based on mid-infrared spectrum,"
Computers, Materials & Continua, vol. 64, no.3, pp. 1869–1883, 2020. https://doi.org/10.32604/cmc.2020.010139