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Proceedings Paper

Prediction of pH of cola beverage using Vis/NIR spectroscopy and least squares-support vector machine
Author(s): Fei Liu; Yong He
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Paper Abstract

Visible and near infrared (Vis/NIR) transmission spectroscopy and chemometric methods were utilized to predict the pH values of cola beverages. Five varieties of cola were prepared and 225 samples (45 samples for each variety) were selected for the calibration set, while 75 samples (15 samples for each variety) for the validation set. The smoothing way of Savitzky-Golay and standard normal variate (SNV) followed by first-derivative were used as the pre-processing methods. Partial least squares (PLS) analysis was employed to extract the principal components (PCs) which were used as the inputs of least squares-support vector machine (LS-SVM) model according to their accumulative reliabilities. Then LS-SVM with radial basis function (RBF) kernel function and a two-step grid search technique were applied to build the regression model with a comparison of PLS regression. The correlation coefficient (r), root mean square error of prediction (RMSEP) and bias were 0.961, 0.040 and 0.012 for PLS, while 0.975, 0.031 and 4.697x10-3 for LS-SVM, respectively. Both methods obtained a satisfying precision. The results indicated that Vis/NIR spectroscopy combined with chemometric methods could be applied as an alternative way for the prediction of pH of cola beverages.

Paper Details

Date Published: 3 March 2008
PDF: 7 pages
Proc. SPIE 6621, International Symposium on Photoelectronic Detection and Imaging 2007: Photoelectronic Imaging and Detection, 66211Z (3 March 2008); doi: 10.1117/12.790945
Show Author Affiliations
Fei Liu, Zhejiang Univ. (China)
Yong He, Zhejiang Univ. (China)

Published in SPIE Proceedings Vol. 6621:
International Symposium on Photoelectronic Detection and Imaging 2007: Photoelectronic Imaging and Detection
Liwei Zhou, Editor(s)

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