designed a spectrophotometric method for the determination of tartrazine residual in different drinks and foodstuffs by using mandarin leaves-capped gold nanoparticles

Tartrazine color is a synthetic organic food dye that can be found in common food products such as bakery products, dairy products, candies, and beverages, the presence and content of tartrazine color must be controlled in food products due to their potential harmfulness to human beings. although the liquid chromatographic, and other methods for tartrazine color have advantages such as excellent accuracy and reproducibility, it has limitations such as long-time measurement, and high equipment costs. in this study, to determine tartrazine color in the solution we used a prepared from mandarin leaves-capped aunps sensor and kinetic spectrophotometric method. the calibration curve was linear in the range of (0.02 to 12.0 μg/l). the standard deviation of (3.0%), and detection limit of the method (0.02 μg/l in time 7 min, 385 nm) were obtained for sensor level response mandarin leaves-capped aunps with (95%) confidence evaluated. the observed outcomes confirmed the very low detection limit for measuring the tartrazine color in food samples. the artificial neural network model was used as a tool very low for determining mean square error (mse = 0.515) for tartrazine color by mandarin leaves-capped aunps sensor. the chemical mandarin leaves-capped aunps sensor made it possible as an excellent sensor with reproducibility.