Gold nanoparticle-based digital image colorimetry for Ametryn detection: A smart alternative to UV–vis spectrometry with multivariate optimization

Abstract

A simple colorimetric method was developed for the determination of the triazine herbicide ametryn in vegetable samples using UV–visible spectrophotometry and smartphone-based digital image colorimetry (DIC). The sensing strategy relies on ametryn-induced aggregation of gold nanoparticles (AuNPs), generating a visible color change proportional to analyte concentration. Multivariate optimization was applied to enhance analytical performance while minimizing experimental runs. Five variables (pH, buffer volume, NaCl concentration, AuNP volume, and reaction time) were initially screened using a fractional factorial design. Significant factors (pH, buffer volume, and NaCl concentration) were subsequently optimized using a face-centered composite design. Under optimal conditions, limits of detection were 2.4 μg L−1 for UV–Vis and 2.7 μg L−1 for DIC, with quantification limits of 7.9 and 8.9 μg L−1, respectively. The method showed satisfactory recoveries (89.5–109%) in vegetable samples and no detectable ametryn residues. The proposed approach offers a rapid, inexpensive, and portable alternative for screening herbicide residues in food matrices. © 2026 Elsevier B.V.