Using a Smartphone-Based Colorimetric Device with Molecularly Imprinted Polymer for the Quantification of Tartrazine in Soda Drinks

Digitalization of Colorimetric Sensor Technologies for Food Safety

Colorimetric sensors play a crucial role in promoting on-site testing, enabling the detection and/or quantification of various analytes based on changes in color. These sensors offer several advantages, such as simplicity, cost-effectiveness, and visual readouts, making them suitable for a wide range of applications, including food safety and monitoring. A critical component in portable colorimetric sensors involves their integration with color models for effective analysis and interpretation of output signals. The most commonly used models include CIELAB (Commission Internationale de l'Eclairage), RGB (Red, Green, Blue), and HSV (Hue, Saturation, Value). This review outlines the use of color models via digitalization in sensing applications within the food safety and monitoring field. Additionally, challenges, future directions, and considerations are discussed, highlighting a significant gap in integrating a comparative analysis toward determining the color model that results in the highest sensor performance. The aim of this review is to underline the potential of this integration in mitigating the global impact of food spoilage and contamination on health and the economy, proposing a multidisciplinary approach to harness the full capabilities of colorimetric sensors in ensuring food safety.

Smartphone-Based Rapid Quantitative Detection Platform with Imprinted Polymer for Pb (II) Detection in Real Samples

This paper reports the successful development and application of an efficient method for quantifying Pb2+ in aqueous samples using a smartphone-based colorimetric device with an imprinted polymer (IIP). The IIP was synthesized by modifying the previous study; using rhodizonate, 2-acrylamido-2-methylpropane sulfonic acid (AMPS), N,N'-methylenebisacrylamide (MBA), and potassium persulfate (KPS). The polymers were then characterized. An absorption study was performed to determine the optimal conditions for the smartphone-based colorimetric device processing. The device consists of a black box (10 × 10 × 10 cm), which was designed to ensure repeatability of the image acquisition. The methodology involved the use of a smartphone camera to capture images of IIP previously exposed at Pb2+ solutions with various concentrations, and color channel values were calculated (RGB, YMK HSVI). PLS multivariate regression was performed, and the optimum working range (0-10 mg L-1) was determined using seven principal components with a detection limit (LOD) of 0.215 mg L-1 and R2 = 0.998. The applicability of a colorimetric sensor in real samples showed a coefficient of variation (% RSD) of less than 9%, and inductively coupled plasma mass spectrometry (ICP-MS) was applied as the reference method. These results confirmed that the quantitation smartphone-based colorimetric sensor is a suitable analytical tool for reliable on-site Pb2+ monitoring.

Preparation of a Molecularly Imprinted Polymer on Polyethylene Terephthalate Platform Using Reversible Addition-Fragmentation Chain Transfer Polymerization for Tartrazine Analysis via Smartphone

This work describes the preparation of a molecularly imprinted polymer (MIP) platform on polyethylene terephthalate (MIP-PET) via RAFT polymerization for analyzing tartrazine using a smartphone. The MIP-PET platform was characterized using Fourier transform infrared (FTIR) techniques, Raman Spectroscopy, X-ray photoelectron spectroscopy (XPS), and confocal microscopy. The optimal pH and adsorption time conditions were determined. The adsorption capacity of the MIP-PET plates with RAFT treatment (0.057 mg cm-2) was higher than that of the untreated plates (0.028 mg cm-2). The kinetic study revealed a pseudo-first-order model with intraparticle diffusion, while the isotherm study indicated a fit for the Freundlich model. Additionally, the MIP-PET demonstrated durability by maintaining its adsorption capacity over five cycles of reuse without significant loss. To quantify tartrazine, images were captured using a smartphone, and the RGB values were obtained using the ImageJ® free program. A partial least squares regression (PLS) was performed, obtaining a linear range of 0 to 7 mg L-1 of tartrazine. The accuracy of the method was 99.4% (4.97 ± 0.74 mg L-1) for 10 samples of 5 mg L-1. The concentration of tartrazine was determined in two local soft drinks (14.1 mg L-1 and 16.5 mg L-1), with results comparable to the UV-visible spectrophotometric method.

Electrospun cellulose nanofibers immobilized with anthocyanin extract for colorimetric determination of bacteria

A novel smart biochromic textile sensor was developed by immobilizing anthocyanin extract into electrospun cellulose acetate nanofibers to detect bacteria for numerous potential uses, such as healthcare monitoring. Red-cabbage was employed to extract anthocyanin, which was then applied to cellulose acetate nanofibers treated with potassium aluminum sulfate as a mordant. Thus, nanoparticles (NPs) of mordant/anthocyanin (65-115 nm) were generated in situ on the surface of cellulose acetate nanofibrous film. The pH of a growing bacterial culture medium is known to change when bacteria multiply. The absorbance spectra revealed a bluish shift from 595 nm (purple) to 448 nm (green) during the growth of Gram-negative bacteria (E. coli) owing to the discharge of total volatile basic amines as secretion metabolites. On the other hand, the absorption spectra of a growing bacterial culture containing Gram-positive bacteria (L. acidophilus) showed a blue shift from 595 nm (purplish) to 478 nm (pink) as a result of releasing lactic acid as a secretion metabolite. Both absorbance spectra and CIE Lab parameters were used to determine the color shifts. Various analytical techniques were utilized to study the morphology of the anthocyanin-encapsulated electrospun cellulose nanofibers. The cytotoxic effects of the colored cellulose acetate nanofibers were tested.