Pattern Recognition of Sweeteners in Biological Fluids, Beverages, and Ketchup using Stochastic Sensors

摘要

Three stochastic sensors based on nanodiamond (nDP) paste modified with alpha, beta, and gamma-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 1.00x10(-10) mol L(-1)and 1.00x10(-3) mol L-1), for aspartame (between 1.00x10(-12) mol L-1 and 1.00x10(-3) mol L-1) and for sodium cyclamate (between 4.97x10(-12) mol L-1 and 4.97x10(-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 gamma-CD/nDP: for acesulfame K 1.00x10(-10) mol L-1, for aspartame 1.00x10(-12) mol L-1 and for sodium cyclamate 4.97x10(-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.