Detection of Honey Adulteration by Sugar Syrups Using One-Dimensional and Two-Dimensional High-Resolution Nuclear Magnetic Resonance

The importance of honey adulteration detection has recently increased owing to the limited production levels in recent years and the relative high price of honey; therefore, this illegal practice has become more and more attractive to producers. Hence, the need has arisen for more effective analytic...

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Bibliographic Details
Published in:Journal of agricultural and food chemistry 2010-08, Vol.58 (15), p.8495-8501
Main Authors: Bertelli, Davide, Lolli, Massimo, Papotti, Giulia, Bortolotti, Laura, Serra, Giorgia, Plessi, Maria
Format: Article
Language:English
Subjects:
adulterated products
Analytical Methods
Animals
Bees
Biological and medical sciences
Carbohydrates - analysis
Confectionery products and chocolate industries, honey
corn syrup
detection
food analysis
food composition
food contamination
Food Contamination - analysis
Food industries
fraud
Fundamental and applied biological sciences. Psychology
General aspects
honey
Honey - analysis
Magnetic Resonance Spectroscopy - instrumentation
Magnetic Resonance Spectroscopy - methods
Methods of analysis, processing and quality control, regulation, standards
model food systems
nuclear magnetic resonance spectroscopy
one-dimensional high-resolution nuclear magnetic resonance
Quality Control
two-dimensional high-resolution nuclear magnetic resonance
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Summary:The importance of honey adulteration detection has recently increased owing to the limited production levels in recent years and the relative high price of honey; therefore, this illegal practice has become more and more attractive to producers. Hence, the need has arisen for more effective analytical methods aiming at detecting honey adulteration. The present research presents an effective method to detect adulteration in honey falsified by intentional addition of different concentrations of commercial sugar syrups, using one-dimensional (1D) and two-dimensional (2D) nuclear magnetic resonance (NMR) coupled with multivariate statistical analysis. Sixty-three authentic and 63 adulterated honey samples were analyzed. To prepare adulterated honeys, seven different sugar syrups normally used for nutrition of bees were used. The best discriminant model was obtained by 1D spectra, and leave-one-out cross-validation showed a predictive capacity of 95.2%. 2D NMR also furnished acceptable results (cross-validation correct classification 90.5%), although the 1H NMR sequence is preferable because it is the simplest and fastest NMR technique.
ISSN:0021-8561
1520-5118
DOI:10.1021/jf101460t