Differentiation of water samples based on sensor array of silver nanoparticles

Discrimination and differentiation of waters are important issues. Moreover, study about the authenticity of a food and water product is very important. Herein, six different AgNPs were synthesized by green method and characterized by transmission electron microscopy, dynamic light scattering and zeta potential. In the green synthesis procedure, extract of walnut peel, berry and onion were used as reductant. Based on the prepared AgNPs, sensor arrays were designed for clustering and discrimination of 12 bottled waters and 10 natural waters. AgNPs were prepared by green method. Color variations of AgNPs in the presence of the examined waters were converted to RGB indices and used as signal. After mean centering of the RGB data matrix as preprocessing method, by principal component analysis, the location of the water samples in the new axes known as scores were obtained. In the score plot, distinguish between 10 and 8 water samples of the bottled and natural waters was possible, respectively. Besides, the relation between principal components and chemical composition of the water samples including hardness, Ca²⁺, Mg²⁺ and Cl⁻ was investigated.