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Volume 23 (2009), Issue 3-4, Pages 217-226

Determination of sucrose concentration in lemon-type soft drinks by dispersive Raman spectroscopy

Landulfo Silveira Jr.,1 Leonardo Marmo Moreira,1,2 Viviane G. B. Conceição,1 Heliodora L. Casalechi,1 Ingrid S. Muñoz,1 Fabiano Fernandes Da Silva,1 Marcos Augusto S. R. Silva,1 Renato Aparecido De Souza,1 and Marcos Tadeu T. Pacheco1

1Group of Biomedical Engineering, Universidade Camilo Castelo Branco – UNICASTELO, São Paulo, SP, Brazil
2Universidade Camilo Castelo Branco – UNICASTELO, Núcleo do Parque Tecnológico de São José dos Campos, Rod. Pres. Dutra, km 138, São José dos Campos, SP 12247-004, Brazil

Copyright © 2009 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The objective of this study was to quantify the sucrose amount in commercial lemon-type soft drinks through dispersive Raman spectroscopy, comparing the amount listed in the nutritional table of each product to the predicted by a least-square model, in order to obtain a method for quality assurance applied to soft drinks. A dispersive Raman spectrometer was employed using 830 nm laser and imaging spectrograph coupled to a CCD camera, and a total of 48 samples from four brands of lemon-type soft drinks were analyzed. A calibration curve using sucrose from refined sugar (sugarcane) diluted in spring water was elaborated in the range between 0 and 15.0 g/100 ml, and a quantification model based on Partial Least Squares (PLS) regression was developed to correlate the Raman spectra and the amount of sucrose in each dilution. Then, the sucrose in each soft drink sample was predicted employing the calibration curve. The mean error of calibration for the PLS method was 0.30 g/100 ml (3.0%). Results indicated that soft drinks samples have predicted sugar content ranging from 8.1 to 10.9 g/100 ml, with an error of the predicted value compared to the nutritional table ranged from 1.1% to 5.5%. Therefore, Raman spectroscopy in association with PLS regression was an effective method for quantifying the sucrose, with small prediction error. Thus, the present work allows to infer auspicious possibilities of Raman spectroscopy application in the quantification of relevant nutritional facts in beverages.