Abstract
A selection of fourteen common and commercially available table-top artificial sweeteners was considered. The samples contained aspartame and saccharin as high-intensity sweeteners and dextrose, sorbitol, sucrose, and maltodextrin as low-intensity sweeteners. These were all examined both in powder form and as aqueous solutions. Raman spectra, excited at 1064 nm, were acquired using a compact dispersive scheme. These spectra provided fluorescence-free Raman signatures from which to identify the most significant peaks of the various sweeteners. These peaks were also compared with ones obtained by means of computational analysis, in order to show the effect of the entire sweetener matrix. The spectroscopic data were then processed by means of chemometric analysis for distinguishing what kind of sweetener was present in a given sample. First, Principal Component Analysis was applied for the purpose of data dimensionality reduction and explorative investigation and provided good clustering depending on the type of sweetener. Next, the K-nearest neighbors method was used in order to assign the samples to predefined classes. An excellent identification in accordance with the type of high- or low-power sweetener was thus obtained. These results confirm the success of Raman spectroscopy in attaining a straightforward analysis of intact food, with high potentials for its use as a non-destructive and “green” analytical method for quality control in the food industry.
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Acknowledgements
The authors wish to thank the Ente Cassa di Risparmio di Firenze, the MIUR-PON contract #00636 “Fingerimball,” FWO (G008413N), IWT, the MP1205 COST Action, the Methusalem and Hercules foundations, and the OZR of the Vrije Universiteit Brussel for partial funding. Project HP10CHEVJ8 (CINECA) and CREA Center (Centro Ricerche Energia e Ambiente) are also acknowledged for the computational resources.
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Mignani, A.G. et al. (2016). Characterization of Artificial Sweeteners Using Raman Spectroscopy. In: Merillon, JM., Ramawat, K. (eds) Sweeteners. Reference Series in Phytochemistry. Springer, Cham. https://doi.org/10.1007/978-3-319-26478-3_18-1
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DOI: https://doi.org/10.1007/978-3-319-26478-3_18-1
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