Development of Fast Analytical Method for the Detection and Quantification of Honey Adulteration Using Vibrational Spectroscopy and Chemometrics Tools

In this study, the Fourier transform mid-infrared (FT-MIR) spectroscopy technique combined with chemometrics methods was used to monitor adulteration of honey with sugar syrup. Spectral data were recorded from a wavenumber region of 4000–600 cm−1, with a spectral resolution of 4 cm−1. Principal comp...

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Bibliographic Details
Published in:Journal of analytical methods in chemistry 2020, Vol.2020 (2020), p.1-9
Main Authors: Nejjari, Rachid, Mojemmi, Brahim, Cheikh, Amine, El Orche, Aimen, Elhamdaoui, Omar, Bouatia, Mustapha
Format: Article
Language:English
Subjects:
Calibration
Chemometrics
Chromatography
Cluster analysis
Correlation coefficients
Data analysis
Discriminant analysis
Fourier transforms
Honey
Mean square errors
Methods
Nondestructive testing
Principal components analysis
Qualitative analysis
Regression analysis
Root-mean-square errors
Software
Spectral resolution
Spectrum analysis
Support vector machines
Syrup
Wavelengths
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Summary:In this study, the Fourier transform mid-infrared (FT-MIR) spectroscopy technique combined with chemometrics methods was used to monitor adulteration of honey with sugar syrup. Spectral data were recorded from a wavenumber region of 4000–600 cm−1, with a spectral resolution of 4 cm−1. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used for qualitative analysis to discriminate between adulterated and nonadulterated honey. For quantitative analysis, we used partial least-squares regression (PLS-R) and the support vector machine (SVM) to develop optimal calibration models. The use of PCA shows that the first two principal components account for 96% of the total variability. PCA and HCA allow classifying the dataset into two groups: adulterated and unadulterated honey. The use of the PLS-R and SVM-R calibration models for the quantification of adulteration shows high-performance capabilities represented by a high value of correlation coefficients R2 greater than 98% and 95% with lower values of root mean square error (RMSE) less than 1.12 and 1.85 using PLS-R and SVM-R, respectively. Our results indicate that FT-MIR spectroscopy combined with chemometrics techniques can be used successfully as a simple, rapid, and nondestructive method for the quantification and discrimination of adulterated honey.
ISSN:2090-8865
2090-8873
DOI:10.1155/2020/8816249