Discrimination of instant coffee by pattern recognition of chemical oscillation fingerprints

Abstract

A practical and promising method has been developed to identify the different varieties of instant coffee based on the chemical oscillation fingerprints combined with pattern recognition. Chemical oscillation fingerprints originate from the complex and characteristic interaction of the redox constituents and their relative contents in different kinds of biological samples in the chemical oscillation reaction system. Chemometric pattern recognition methods such as principal component analysis (PCA) and cluster analysis were applied to enhance the authenticity of identification of different varieties of instant coffee. The method can fully utilize diversified fingerprint characteristics of the coffee sample. It has the advantages of no pretreatment, simple operation, low cost, rapid analysis, accurate and reliable identification results, and so on. Therefore, nonlinear chemical fingerprints can provide a novel strategy to identify instant coffee, enabling a simple and accurate evaluation of coffee sample quality in a fast way.