3 March 2008 Prediction of pH of cola beverage using Vis/NIR spectroscopy and least squares-support vector machine
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Proceedings Volume 6621, International Symposium on Photoelectronic Detection and Imaging 2007: Photoelectronic Imaging and Detection; 66211Z (2008); doi: 10.1117/12.790945
Event: International Symposium on Photoelectronic Detection and Imaging: Technology and Applications 2007, 2007, Beijing, China
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.
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Fei Liu, Yong He, "Prediction of pH of cola beverage using Vis/NIR spectroscopy and least squares-support vector machine", Proc. SPIE 6621, International Symposium on Photoelectronic Detection and Imaging 2007: Photoelectronic Imaging and Detection, 66211Z (3 March 2008); doi: 10.1117/12.790945; https://doi.org/10.1117/12.790945
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KEYWORDS
Spectroscopy

Calibration

Chemical analysis

Statistical analysis

Near infrared spectroscopy

Reliability

Chemometrics

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