CompVis: a novel method for drinking water alkalinity and total hardness analyses

Abstract

A new green analytical chemistry method using a computer vision approach is proposed to measure alkalinity, Ca²⁺ and Mg²⁺ hardness, and total hardness of drinking water samples. Digital images of water samples on a 96-well ELISA plate were acquired using a table scanner and digitally processed. After variable selection using a genetic algorithm the image data was correlated with alkalinity and hardness values measured by titration and flame atomic absorption spectrometry (FAAS), respectively. Figures of merit were calculated according to IUPAC guidelines and the proposed method was validated for accuracy and precision. The method substantially reduces lab analysis residues when compared to the conventional methods (ca. 500 fold) and it is in accordance with global efforts to reduce wastes and residues. In addition, it is multi-sampler, faster, and cheaper than the reference methods.