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Pattern Recognition of Sweeteners in Biological Fluids, Beverages, and Ketchup using Stochastic Sensors
Author(s) -
Stefanvan Staden RalucaIoana,
MoscaluLungu Alexandrina,
Staden Jacobus Frederick
Publication year - 2020
Publication title -
electroanalysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 128
eISSN - 1521-4109
pISSN - 1040-0397
DOI - 10.1002/elan.201900481
Subject(s) - aspartame , chemistry , saccharin , food science , chromatography , artificial sweetener , food additive , sodium , organic chemistry , biology , sugar , endocrinology
Abstract Three stochastic sensors based on nanodiamond (nDP) paste modified with α, β, and γ‐cyclodextrin were designed and characterized for pattern recognition of aspartame, acesulfame K and sodium cyclamate in beverages, ketchup, and biological fluids. The linear concentration ranges obtained for acesulfame K (between 1.00×10 −10 mol L −1 and 1.00×10 −3 mol L −1 ), for aspartame (between 1.00×10 −12 mol L −1 and 1.00×10 −3 mol L −1 ) and for sodium cyclamate (between 4.97×10 −12 mol L −1 and 4.97×10 −3 mol L −1 ) allow their assay in biological fluids, beverages and ketchup. The lowest limits of quantification were obtained using the stochastic sensor based on γ‐CD/nDP: for acesulfame K 1.00×10 −10 mol L −1 , for aspartame 1.00×10 −12 mol L −1 and for sodium cyclamate 4.97×10 −12 mol L −1 . All three stochastic sensors revealed very high values of sensitivities. The proposed method was reliable for qualitative and quantitative assay of aspartame, acesulfame K and sodium cyclamate in beverages, ketchup, and in biological fluids such as urine.