Second-Order Multivariate Curve Resolution Alternating Least Squares for Spectrophotometric Quantification of Food Colorants in Complex Matrices via Acid-Base Titration

Accurate quantification of food colorants is essential to ensure regulatory compliance, verify product authenticity, and protect consumer safety. Synthetic dyes such as sunset yellow FCF, tartrazine, and amaranth are sometimes used in food products without proper declaration, raising concerns about potential health risks and labeling accuracy. This study applies multivariate curve resolution–alternating least squares (MCR-ALS) to spectrophotometric acid–base titration data for the quantification of colorant mixtures without the need for chemical separation. A major advantage of this method is its ability to resolve rank-deficient systems by augmenting sample data with only a single pure standard, thereby eliminating the need for full calibration of all interfering components. This second-order strategy enables accurate quantification even in the presence of spectral overlap and unknown background signals. By organizing pH-dependent spectral data from samples and standards into a column-wise augmented matrix, the method ensures reliable results even in complex matrices. The method yielded satisfactory recoveries (۹۸–۱۰۸%) when applied to real samples, including saffron, saffron ink, and an orange soft drink. Owing to the second-order advantage of MCR-ALS, analyses in real samples were successfully resolved despite strong spectral overlap between natural and synthetic colorants, with no interference from the naturally occurring compounds. Overall, the method provides a practical solution for multicomponent analysis in complex food matrices.

کلیدواژه ها:

MCR-ALS ، Food colorants ، Spectrophotometry ، Acid-base titration ، Second-order advantage ، Matrix augmentation ، Adulteration detection