Abstract
The contents of Ca, Cu, Fe, K, Mg, Mn, Na and Zn have been determined in green coffee beans from Brazil, Colombia and Mexico by means of inductively coupled plasma optical emission spectrometry. The concentrations of these elements were used to differentiate the coffee provenance. Kruskal–Wallis test highlighted significant differences between elemental contents from the three origins, and principal component analysis showed trends of samples to appear separately. Supervised pattern recognition techniques, such as linear discriminant analysis and soft independent modeling of class analogy, were used to obtain models allowing the geographical authentication of coffee samples with high reliability. Prediction abilities of 97 and 94 % were respectively obtained.
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This work has been partially supported by Project 173591 from the Government of Mexico (CONACyT).
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Muñiz-Valencia, R., Jurado, J.M., Ceballos-Magaña, S.G. et al. Geographical Differentiation of Green Coffees According to Their Metal Content by Means of Supervised Pattern Recognition Techniques. Food Anal. Methods 6, 1271–1277 (2013). https://doi.org/10.1007/s12161-012-9538-8
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DOI: https://doi.org/10.1007/s12161-012-9538-8