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Novel application of multivariate standard addition method based on net analyte signal for quantification of artificial sweeteners in complex food matrices

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Multivariate standard addition method based on net analyte signal concept (SANAS) was found efficient to handle solute overlapping (direct interference) and matrix effect (indirect interference) when analyzing food additives. Aspartame,… Click to show full abstract

Multivariate standard addition method based on net analyte signal concept (SANAS) was found efficient to handle solute overlapping (direct interference) and matrix effect (indirect interference) when analyzing food additives. Aspartame, acesulfame-K, and saccharin are the most added artificial sweeteners to diet drinks and commercial sweeteners. High consumption of artificial sweeteners may end up with unwanted health consequences. Hence, accurate quantification and monitoring of artificial sweeteners is necessary for food industry. In this work, application of SANAS to quantify aspartame (ASP), acesulfame-K (ACE), and saccharin (SAC) in liquid drinks and commercial sweeteners is outlined for the first time. SANAS was workable to handle direct and indirect interferences and quantify sweeteners in commercial samples. ASP and ACE were both detected in diet drinks and sweeteners pills with recoveries of 97.4–108.4% (SD 0.5–3.4) and 101.6–103.7% (SD 0.6–4.3), respectively. SAC was only detected in commercial tablets with recoveries of 96.6–104.4 and SD 0.3–0.5. The proposed SANAS was validated against an official liquid chromatography method for sweeteners detection and a small relative error among methods was reported.

Keywords: multivariate standard; addition method; standard addition; artificial sweeteners; food

Journal Title: Journal of Food Measurement and Characterization
Year Published: 2019

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