Overview of Analytical Techniques Associated with Pattern Recognition Methods in Sugarcane Spirits Samples

Abstract

Sugarcane spirits and cachaça are distilled beverages derived from the fermentation of sugarcane juice. The production of these spirits has significant influence on the economy of several regions in Brazil, being the third most consumed distilled beverage in the world. To ensure the safety for human consumption and also to add value to these products, it is imperative to apply quality control techniques. The complexity of food matrices along with the fact that the currently used instrumental techniques have several disadvantages, such as being expensive, laborious and time-consuming, have turned research attention to multivariate analysis techniques. In consequence, chemometric techniques have been applied in laboratories around the world aiming at data reduction, pattern recognition, cluster analysis, classification and quantification of data. This article provides an overview of the application of analytical techniques with nonsupervised and supervised pattern recognition methods for the analysis of sugarcane spirits samples. Assessments discussed include promising results for the discrimination among samples, verification of adulteration, tendencies in sensorial characteristics as well as relationships between chemical information and the geographical origins.

Keywords:

• Chemical profile
• cachaça
• chemometrics
• quality control

Acknowledgments

The authors are grateful to CAPES by scholarship. All authors thank to Sidney Pratt, Canadian, MAT (The Johns Hopkins University), RSAdip - TESL (Cambridge University) for reviewing the English text of this article.

Conflict of interest

The authors declare to have no potential sources of conflict of interest.