A simple voltammetric electronic tongue for the analysis of coffee adulterations.

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.

Detection of coffee adulteration with soybean and corn by capillary electrophoresis-tandem mass spectrometry.

The detection of coffee adulteration with soybean and corn by capillary electrophoresis-tandem mass spectrometry was accomplished by evaluating the monosaccharides profile obtained after acid hydrolysis of the samples. The acid hydrolysis, using H2SO4 as a catalyst, increases the ionic strength of the sample impairing the electrophoretic separation. Therefore, Ba(OH)2 was used to both neutralize the medium and reduce the content of sulfate by precipitation of BaSO4. The best separation of nine determined monosaccharides (fucose, galactose, arabinose, glucose, rhamnose, xylose, mannose, fructose and ribose) plus inositol as internal standard was obtained in 500 mmol·L-1 triethylamine, pH 12.3. The monosaccharides are separated as anionic species at this pH. The proposed method is simple, fast (<12.0 min), present linear calibration curves (r2 = 0.995), and relative standard deviation for replicate injections lower than 5%. The LOQ for all monosaccharides was lower than 0.01 mmol·L-1, which is in accordance with the tolerable limits for coffee. Principal component analysis (PCA) was used to evaluate interrelationships between the monosaccharide profile and the coffee adulteration with different proportions of soybean and corn. Fucose, galactose, arabinose, glucose, sucrose, rhamnose, xylose, mannose, fructose, and ribose were quantified in packed roast-and-ground commercial coffee samples, and differences between adulterated and unadulterated coffees could be detected.

Coffee Adulteration: More than Two Decades of Research.

Coffee is a ubiquitous food product of considerable economic importance to the countries that produce and export it. The adulteration of roasted coffee is a strategy used to reduce costs. Conventional methods employed to identify adulteration in roasted and ground coffee involve optical and electron microscopy, which require pretreatment of samples and are time-consuming and subjective. Other analytical techniques have been studied that might be more reliable, reproducible, and widely applicable. The present review provides an overview of three analytical approaches (physical, chemical, and biological) to the identification of coffee adulteration. A total of 30 published articles are considered. It is concluded that despite the existence of a number of excellent studies in this area, there still remains a lack of a suitably sensitive and widely applicable methodology able to take into account the various different aspects of adulteration, considering coffee varieties, defective beans, and external agents.

Quantitative evaluation of multiple adulterants in roasted coffee by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) and chemometrics.

The current study presents an application of Diffuse Reflectance Infrared Fourier Transform Spectroscopy for detection and quantification of fraudulent addition of commonly employed adulterants (spent coffee grounds, coffee husks, roasted corn and roasted barley) to roasted and ground coffee. Roasted coffee samples were intentionally blended with the adulterants (pure and mixed), with total adulteration levels ranging from 1% to 66% w/w. Partial Least Squares Regression (PLS) was used to relate the processed spectra to the mass fraction of adulterants and the model obtained provided reliable predictions of adulterations at levels as low as 1% w/w. A robust methodology was implemented that included the detection of outliers. High correlation coefficients (0.99 for calibration; 0.98 for validation) coupled with low degrees of error (1.23% for calibration; 2.67% for validation) confirmed that DRIFTS can be a valuable analytical tool for detection and quantification of adulteration in ground, roasted coffee.