Emerging approach for analytical characterization and geographical classification of Moroccan and French honeys by means of a voltammetric electronic tongue

Food Chem. 2018 Mar 15:243:36-42. doi: 10.1016/j.foodchem.2017.09.067. Epub 2017 Sep 14.

Abstract

Moroccan and French honeys from different geographical areas were classified and characterized by applying a voltammetric electronic tongue (VE-tongue) coupled to analytical methods. The studied parameters include color intensity, free lactonic and total acidity, proteins, phenols, hydroxymethylfurfural content (HMF), sucrose, reducing and total sugars. The geographical classification of different honeys was developed through three-pattern recognition techniques: principal component analysis (PCA), support vector machines (SVMs) and hierarchical cluster analysis (HCA). Honey characterization was achieved by partial least squares modeling (PLS). All the PLS models developed were able to accurately estimate the correct values of the parameters analyzed using as input the voltammetric experimental data (i.e. r>0.9). This confirms the potential ability of the VE-tongue for performing a rapid characterization of honeys via PLS in which an uncomplicated, cost-effective sample preparation process that does not require the use of additional chemicals is implemented.

Keywords: Analytical methods; Chemometrics; Classification; Food control; PLS models; Voltammetric electronic tongue.

Publication types

  • Evaluation Study

MeSH terms

  • Cluster Analysis
  • Discriminant Analysis
  • Electronic Nose*
  • France
  • Furaldehyde / analogs & derivatives
  • Furaldehyde / analysis
  • Honey / analysis*
  • Honey / classification
  • Least-Squares Analysis
  • Morocco
  • Principal Component Analysis
  • Support Vector Machine

Substances

  • 5-hydroxymethylfurfural
  • Furaldehyde