Ficin-Functionalized Gold Nanoparticles for Selective UV-Vis Colorimetric Detection of Hg²⁺, Cu²⁺, and Cr⁶⁺: Optimization and RGB Image-Based Quantification

Nowadays heavy metal pollution poses a critical environmental and public health challenge, making affordable detection methods for water quality monitoring urgently needed. To address this issue, we have developed a novel colorimetric detection system based on ficin-functionalized gold nanoparticles (F-AuNPs) evaluated through UV-Vis spectrophotometry and smartphone-based RGB image analysis for the detection of Hg²⁺, Cu²⁺, and Cr⁶⁺. Response Surface Methodology using Box-Behnken Design optimized the functionalization conditions of Ficin to AuNPs (0.2 mM AuNPs conc, 0.01 mM ficin conc, 72 h incubation at 14°C), resulting in an excellent model fit (R² = 0.9818, adequate precision = 26.992). The optimized F-AuNPs exhibited selective aggregation with Hg²⁺, Cu²⁺, and Cr⁶⁺ causing a visible color transition from red to blue gray but remained dispersed in the presence of nine other tested metal ions. Smartphone RGB image analysis yielded excellent linearity (R²≥0.90) with limits of detection (LOD) and limits of quantitation (LOQ) of 0.02 ppm and 0.06 ppm for Hg²⁺, 0.05 ppm and 0.17 ppm for Cu²⁺ and 0.10 ppm and 0.33 ppm for Cr⁶⁺ respectively. This indicates that the sensitivity of Smartphone RGB image is comparable to conventional UV-Vis spectrophotometry at wavelengths A626/A524. Real water samples testing confirmed F-AuNPs feasibility, with spiked samples validating the method's applicability for environmental monitoring. Thus, F-AuNPs colorimetric platform provides a low-cost operation-minimal sample preparation that functions as practical field-ready tool for future near real time monitoring of these heavy metals.