Skip to main content
Log in

Geographical Differentiation of Green Coffees According to Their Metal Content by Means of Supervised Pattern Recognition Techniques

  • Published:
Food Analytical Methods Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

Download references

Acknowledgments

This work has been partially supported by Project 173591 from the Government of Mexico (CONACyT).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Roberto Muñiz-Valencia.

Rights and permissions

Reprints and permissions

About this article

Cite this article

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

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12161-012-9538-8

Keywords

Navigation