Use of Visible and Near Infrared Spectroscopy and Least Squares-Support Vector Machine To Determine Soluble Solids Content and pH of Cola Beverage

Abstract

Visible and near infrared (VIS/NIR) transmission spectroscopy and chemometric methods were utilized for the fast determination of soluble solids content (SSC) and pH of cola beverage. A total of 180 samples were used for the calibration set, whereas 60 samples were used for the validation set. Some preprocessing methods were applied before developing the calibration models. Several PLS factors, extracted by partial least squares (PLS) analysis, were used as the inputs of least squares-support vector machine (LS-SVM) model according to their accumulative reliabilities. The correlation coefficient (r), root mean square error of prediction (rmsEP), bias, and RPD were 0.959, 1.136, -0.185, and 3.5 for SSC, whereas 0.973, 0.053, 0.017, and 4.1 for pH, respectively. An excellent prediction precision was achieved by LS-SVM compared with PLS. The results indicated that VIS/NIR spectroscopy combined with LS-SVM could be applied as a rapid and alternative way for the fast determination of SSC and pH of cola beverage.