Measurement of pH of rice wines using Vis/NIR spectroscopy and least squares-support vector machine

Visible and near infrared (Vis/NIR) transmission spectroscopy and a hybrid chemometrics method were applied to determine the pH of rice wines. A spectroradiometer with a wavelength region of 325-1075 nm was used for spectral scanning. The calibration set was composed of 240 samples and 60 samples were used in the validation set. The smoothing way of Savitzky-Golay and standard normal variate (SNV) were used as data pre-processing methods. Principal components analysis (PCA) was employed to extract the principal components (PCs) which were used as the inputs of Least squares-support vector machine (LS-SVM) model. Then LS-SVM with radial basis function (RBF) kernel function was applied to build the regression model with a comparison of partial least squares (PLS) regression. The correlation coefficient (r), root mean square error of prediction (RMSEP) and bias of LS-SVM were 0.964, 2.62x10-4 and 8.83x10-4, respectively. Significant wavelengths for pH were proposed according to x-loading weights. The results indicated that Vis/NIR spectroscopy with the combination of LS-SVM could be utilized as an alternative way for the determination pH of rice wines.

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