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Fast chromatographic method for the determination of dyes in beverages by using high performance liquid chromatography—Diode array detection data and second order algorithms
- Culzoni, María J., Schenone, Agustina V., Llamas, Natalia E., Garrido, Mariano, Di Nezio, Maria S., Fernández Band, Beatriz S., Goicoechea, Héctor C.
- Journal of chromatography 2009 v.1216 no.42 pp. 7063-7070
- soft drinks, food coloring, high performance liquid chromatography, rapid methods, algorithms, amaranth dye
- A fast chromatographic methodology is presented for the analysis of three synthetic dyes in non-alcoholic beverages: amaranth (E123), sunset yellow FCF (E110) and tartrazine (E102). Seven soft drinks (purchased from a local supermarket) were homogenized, filtered and injected into the chromatographic system. Second order data were obtained by a rapid LC separation and DAD detection. A comparative study of the performance of two second order algorithms (MCR-ALS and U-PLS/RBL) applied to model the data, is presented. Interestingly, the data present time shift between different chromatograms and cannot be conveniently corrected to determine the above-mentioned dyes in beverage samples. This fact originates the lack of trilinearity that cannot be conveniently pre-processed and can hardly be modelled by using U-PLS/RBL algorithm. On the contrary, MCR-ALS has shown to be an excellent tool for modelling this kind of data allowing to reach acceptable figures of merit. Recovery values ranged between 97% and 105% when analyzing artificial and real samples were indicative of the good performance of the method. In contrast with the complete separation, which consumes 10mL of methanol and 3mL of 0.08molL⁻¹ ammonium acetate, the proposed fast chromatography method requires only 0.46mL of methanol and 1.54mL of 0.08molL⁻¹ ammonium acetate. Consequently, analysis time could be reduced up to 14.2% of the necessary time to perform the complete separation allowing saving both solvents and time, which are related to a reduction of both the costs per analysis and environmental impact.