A simple voltammetric electronic tongue for the analysis of coffee adulterations

Abstract

This work presents a simple and low-cost analytical approach to detect adulterations in ground roasted coffee by using voltammetry and chemometrics. The voltammogram of a coffee extract (prepared as simulating a home-made coffee cup) obtained with a single working electrode is submitted to pattern recognition analysis preceded by variable selection to detect the addition of coffee husks and sticks (adulterated/unadulterated), or evaluate the shelf-life condition (expired/unexpired). Two pattern recognition methods were tested: linear discriminant analysis (LDA) with variable selection by successive projections algorithm (SPA), or genetic algorithm (GA); and partial least squares discriminant analysis (PLS-DA). Both LDA models presented satisfactory results. The voltammograms were also evaluated for the quantitative determination of the percentage of impurities in ground roasted coffees. PLS and multivariate linear regression (MLR) preceded by variable selection with SPA or GA were evaluated. An excellent predictive power (RMSEP = 0.05%) was obtained with MLR aided by GA.

Keywords: 3,5-Dicaffeoylquinic acid (PubChem CID: 6474310); 3-O-Feruloylquinic acid (PubChem CID: 9799386); 4-p-Coumaroylquinic acid (PubChem CID: 5281766); Acetic acid (PubChem CID: 176); Boric acid (PubChem CID: 7628); Carbon paste electrode; Chlorogenic acid (PubChem CID: 1794427); Coffee adulteration; Differential pulse voltammetry; Discriminant analysis; Genetic algorithm; Graphite (PubChem CID: 5462310); Multivariate calibration; Phosphoric acid (PubChem CID: 1004); Variable selection.