Abstract
The artificial azo dye Allura Red AC (E129), widely used in candy, may pose health risks, such as hypersensitivity and hyperactivity, underscoring the need for its monitoring and quantification to ensure food safety. This study adapted a traditional sample preparation approach aligned with the principles of green analytical chemistry (GAC) and introduced a low-cost, smartphone-based colorimetric method employing digital image acquisition. The technique enables the simultaneous capture of both the analytical curves and the samples in a single image by using a 3D-printed digital imaging chamber. The data were processed using the RGB color model and analyzed by partial least-squares with REDGIM software. For the adapted UV-vis method, accuracy at two concentration levels ranged from 77.33% ± 1.53 to 98.35% ± 0.07, with a limit of quantification (LQ) of 2.26 × 10(-6) mg mL(-1) and a limit of detection (LD) of 7.47 × 10(-7) mg mL(-1). For the DIA-RD method, accuracy ranged from 78.04% ± 1.42 to 98.42% ± 0.06, with a LQ of 1.67 × 10(-4) mg mL(-1) and a LD of 5.51 × 10(-5) mg mL(-1). E129 concentrations in ten candy samples ranged from 7.00 × 10(-4) to 5.16 × 10(-3) mg mL(-1) using the UV-vis method and from 7.33 × 10(-4) to 4.83 × 10(-3) mg mL(-1) using the DIA-RD method, all below the legal limit of 3.0 × 10(-1) mg mL(-1) established by Brazilian and international regulations. The DIA-RD method significantly reduced sample preparation time, enabling data acquisition and processing in 5 min compared to 6 h with the UV-vis method. It complies with GAC principles and shows a strong potential for routine quality control of candy products.