Quantitative Analysis of Food Additives in a Beverage using High Performance Liquid Chromatography and Diode Array Detection Coupled with Chemometrics - Donmez, Ozlem Aksu; Dinc-Zor, Sule; Asci, Burge; Bozdogan, Abdurrezzak E. (OXFORD UNIV PRESS INC, 2020)
Background: In many countries, the levels of synthetic food additives causing harm to humans have been determined and their use has been controlled by legal regulations. Sensitive, accurate and low-cost analysis methods are required for food additive determination. Objective: In this study, a fast high performance liquid chromatography-diode array detection (HPLC-DAD) analytical methodology for quantification of sodium benzoate, potassium sorbate, ponceau 4R, and carmoisine in a beverage was proposed. Methods: Partial least squares (PLS) and principal component regression (PCR) multivariate calibration methods applied to chromatograms with overlapped peaks were used to establish a green and smart method with short isocratic elution. A series of synthetic solutions including different concentrations of analytes were used to test the prediction ability of the developed methods. Conclusions: The average recoveries for all target analytes were in the range of 98.27-101.37% with average relative prediction errors of less than 3%. The proposed chemometrics-assisted HPLC-DAD methods were implemented to a beverage successfully. Analysis results from sodium benzoate, potassium sorbate, ponceau 4R, and carmoisine in a beverage by PLS-2 and PCR were statistically compared with conventional HPLC. Highlights: The HPLC methods coupled with the PLS-2 and PCR algorithm could provide a simple, quick and accurate strategy for simultaneous determination of sodium benzoate, potassium sorbate, ponceau 4R, and carmoisine in a beverage sample.
Keywords: LEAST-SQUARES; POTASSIUM SORBATE; SODIUM BENZOATE; SUNSET YELLOW; CALIBRATION; PREDICTION; 2ND-ORDER; 3-WAY; WATER; Chemistry; Food Science & Technology