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Optics Express

Optics Express

  • Editor: Andrew M. Weiner
  • Vol. 22, Iss. 10 — May. 19, 2014
  • pp: 12533–12544

Identification of wheat quality using THz spectrum

Hongyi Ge, Yuying Jiang, Zhaohui Xu, Feiyu Lian, Yuan Zhang, and Shanhong Xia  »View Author Affiliations

Optics Express, Vol. 22, Issue 10, pp. 12533-12544 (2014)

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The terahertz (THz) spectra in the range of 0.2–1.6 THz (6.6–52.8 cm−1) of wheat grains with various degrees of deterioration (normal, worm-eaten, moldy, and sprouting wheat grains) were investigated by terahertz time domain spectroscopy. Principal component analysis (PCA) was employed to extract feature data according to the cumulative contribution rates; the top four principal components were selected, and then a support vector machine (SVM) method was applied. Several selection kernels (linear, polynomial, and radial basis functions) were applied to identify the four types of wheat grain. The results showed that the materials were identified with an accuracy of nearly 95%. Furthermore, this approach was compared with others (principal component regression, partial least squares regression, and back-propagation neural networks). The comparisons showed that PCA-SVM outperformed the others and also indicated that the proposed method of THz technology combined with PCA-SVM is efficient and feasible for identifying wheat of different qualities.

© 2014 Optical Society of America

OCIS Codes
(300.0300) Spectroscopy : Spectroscopy
(300.6495) Spectroscopy : Spectroscopy, teraherz

ToC Category:
Terahertz Optics

Original Manuscript: March 31, 2014
Revised Manuscript: May 3, 2014
Manuscript Accepted: May 5, 2014
Published: May 15, 2014

Hongyi Ge, Yuying Jiang, Zhaohui Xu, Feiyu Lian, Yuan Zhang, and Shanhong Xia, "Identification of wheat quality using THz spectrum," Opt. Express 22, 12533-12544 (2014)

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