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

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^?1and 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.