NDLI: Application of Least Squares-Support Vector Machine for Measurement of Soluble Solids Content of Rice Vinegars Using Vis/NIR Spectroscopy

Content Provider	IEEE Xplore Digital Library
Author	Liu, Fei He, Yong Wang, Li
Copyright Year	2007
Abstract	Visible and near infrared (Vis/NIR) spectroscopy was investigated to predict soluble solids content (SSC) of rice vinegars based on least squares-support vector machine (LS-SVM). Five varieties of rice vinegars and 300 samples were prepared. After some preprocessing, PLS was implemented for calibration as well as the extraction of principal components (PCs). Wavelet transform (WT) was use to compress the variables. The selected PCs and compressed variables were applied as the inputs to develop PC-LS-SVM and WT-LS-SVM models. The correlation coefficient (r), root mean square error of prediction (RMSEP) and bias for prediction were 0.958, 1216, and -0.310 for PLS, 0.997, 0.357 and 0.121 for PC-LS-SVM, whereas 0.999, 0.199 and 0.030 for WT-LS-SVM, respectively. A high and excellent precision was achieved by LS-SVM models. The results indicated that Vis/NIR spectroscopy could be successfully applied as a fast and high precision method for the measurement of SSC of rice vinegars.
Starting Page	1044
Ending Page	1047
File Size	563595
Page Count	4
File Format	PDF
ISBN	0769530729
e-ISBN	9780769530727
DOI	10.1109/CIS.2007.212
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-12-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wavelet transforms Spectroscopy Temperature Solids Infrared spectra Calibration Personal communication networks Spectral analysis Sugar Light sources
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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