Honey authentication and adulteration detection using emission - excitation spectra combined with chemometrics

Sorina Ropciuc; Florina Dranca; Daniela Pauliuc; Mircea Oroian

doi:10.1016/j.saa.2023.122459

Honey authentication and adulteration detection using emission - excitation spectra combined with chemometrics

Spectrochim Acta A Mol Biomol Spectrosc. 2023 May 15:293:122459. doi: 10.1016/j.saa.2023.122459. Epub 2023 Feb 9.

Authors

Sorina Ropciuc¹, Florina Dranca¹, Daniela Pauliuc¹, Mircea Oroian²

Affiliations

¹ Faculty of Food Engineering, Stefan cel Mare University of Suceava, Romania.
² Faculty of Food Engineering, Stefan cel Mare University of Suceava, Romania. Electronic address: m.oroian@fia.usv.ro.

PMID: 36812751
DOI: 10.1016/j.saa.2023.122459

Abstract

The aim of this study was to evaluate the usefulness of emission-excitation matrices for honey authentication and adulteration detection. For this purpose, 4 types of authentic honeys (tilia, sunflower, acacia and rape) and samples adulterated with different adulteration agents (agave, maple, inverted sugar, corn and rice in different percentages - 5%, 10% and 20%) were analysed. Each honey type and each adulteration agent exhibit unique emission-excitation spectra that can be used for the classification according to the botanical origin and for the detection of adulteration. The principal component analysis clearly separated the rape, sunflower and acacia honeys. The partial least squares - discriminant analysis (PLS-DA) and support vector machines (SVM) were used in a binary mode to separate the authentic honeys from the adulterated ones, and the SVM proved to separate much better than PLS-DA.

Keywords: Adulteration; Chemometrics; Fluorescence spectroscopy; Honey.

MeSH terms

Carbohydrates
Chemometrics
Discriminant Analysis
Food Contamination / analysis
Helianthus*
Honey* / analysis

Substances

Carbohydrates