Portable spectral reflectance for rapid discrimination of honey with a protected designation of origin from Ortigueira, Brazil

Pedro Lucas Caetano de Oliveira ¹, Jelmir Craveiro de Andrade ¹, Bianca Carvalho Dos Santos ¹

⁰Analytical and Molecular Laboratorial Center (CLAn), Institute of Chemistry (IQ), Federal University of Rio de Janeiro (UFRJ), Cidade Universitária, Rio de Janeiro, RJ 21.941-909, Brazil; Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), Federal University of Rio de Janeiro (UFRJ), Cidade Universitária, Rio de Janeiro, RJ 21.941-598, Brazil.

Food Research International +

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March 1, 2025

View abstract on PubMed

Summary

Spectral reflectance and chemometrics accurately traced honey

Area Of Science

Food Science
Analytical Chemistry
Spectroscopy

Background

Honey authentication is crucial for consumer trust and economic integrity.
Protected Designation of Origin (PDO) honey requires robust traceability methods.
Geographical and floral origin determination presents analytical challenges.

Purpose Of The Study

To evaluate spectral reflectance combined with chemometrics for tracing honey origin.
To assess the capability of chemometric models in discriminating geographical and floral sources of honey.
To explore the potential of portable instruments for real-time food authentication.

Main Methods

Utilized spectral reflectance measurements with a portable instrument.
Applied chemometric techniques, including Principal Component Analysis (PCA), Partial Least Squares Discriminant Analysis (PLS-DA), and Linear Discriminant Analysis (LDA).
Analyzed honey samples from Ortigueira, Brazil (a PDO region) and surrounding areas to determine geographical and floral origins.

Main Results

PLS-DA achieved 97.1% accuracy for geographical discrimination of honey.
PLS-DA demonstrated 82.4% accuracy for discriminating floral origins, indicating complexity in multifloral honey.
PLS-DA outperformed LDA in both geographical and floral origin discrimination.
PCA showed a trend of sample separation but lacked complete precision.

Conclusions

Spectral reflectance and chemometrics, especially PLS-DA, show significant potential for geographical honey discrimination.
The methodology offers promise for combating honey fraud and monitoring certified products.
Further refinement is needed for highly accurate floral origin discrimination, particularly for multifloral varieties.

Keywords:

Chemometrics Food discrimination Multivariate analysis Portability Spectroscopy