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Variety identification of brown sugar using short-wave near infrared spectroscopy and multivariate calibrationFormat | Member Price | Non-Member Price |
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Paper Abstract
Near-infrared spectroscopy (NIRS) with the characteristics of high speed, non-destructiveness, high precision and
reliable detection data, etc. is a pollution-free, rapid, quantitative and qualitative analysis method. A new approach for
variety discrimination of brown sugars using short-wave NIR spectroscopy (800-1050nm) was developed in this work.
The relationship between the absorbance spectra and brown sugar varieties was established. The spectral data were
compressed by the principal component analysis (PCA). The resulting features can be visualized in principal component
(PC) space, which can lead to discovery of structures correlative with the different class of spectral samples. It appears to
provide a reasonable variety clustering of brown sugars. The 2-D PCs plot obtained using the first two PCs can be used
for the pattern recognition. Least-squares support vector machines (LS-SVM) was applied to solve the multivariate
calibration problems in a relatively fast way. The work has shown that short-wave NIR spectroscopy technique is
available for the brand identification of brown sugar, and LS-SVM has the better identification ability than PLS when the
calibration set is small.
Paper Details
Date Published: 15 November 2007
PDF: 6 pages
Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 67882T (15 November 2007); doi: 10.1117/12.751332
Published in SPIE Proceedings Vol. 6788:
MIPPR 2007: Pattern Recognition and Computer Vision
S. J. Maybank; Mingyue Ding; F. Wahl; Yaoting Zhu, Editor(s)
PDF: 6 pages
Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 67882T (15 November 2007); doi: 10.1117/12.751332
Show Author Affiliations
Haiqing Yang, Zhejiang Univ. (China)
Zhejiang Univ. of Technology (China)
Di Wu, Zhejiang Univ. (China)
Zhejiang Univ. of Technology (China)
Di Wu, Zhejiang Univ. (China)
Yong He, Zhejiang Univ. (China)
Published in SPIE Proceedings Vol. 6788:
MIPPR 2007: Pattern Recognition and Computer Vision
S. J. Maybank; Mingyue Ding; F. Wahl; Yaoting Zhu, Editor(s)
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