E3S Web Conf.
Volume 211, 2020The 1st JESSD Symposium: International Symposium of Earth, Energy, Environmental Science and Sustainable Development 2020
|Number of page(s)||5|
|Section||General Environmental Modelling|
|Published online||25 November 2020|
The development of green analytical methods to monitor adulteration in honey by UV-visible spectroscopy and chemometrics models
Laboratory of Analytical Chemistry & Bromatology, Team of Formulation and Quality Control of Health Products Faculty of Medicine and Pharmacy, Mohammed V University Rabat, Morocco
2 Laboratory of Chemical Processes and Applied Materials University of Sultan Moulay Slimane BeniMellal, Morocco
3 Faculty of Pharmacy, Abulcasis University Rabat, Morocco
* Corresponding author: email@example.com
The development of green and environmentally friendly analytical methods for agri-food products is an essential element to be treated by green analytical chemistry. In this study, UV-Visible spectroscopy, combined with a mathematical and statistical or chemometrics algorithm, has been developed to monitor honey quality. Partial Least Squares Regression (PLS-R) and Support Vector Machine Learning Regression (SVM-R) showed an adequate quantification of the percentage of impurity. The use of these models demonstrates a high ability to predict the quality of honey. R-square’s high value shows this ability, and the low value of root mean square error of calibration and cross-validation (RMSECV, RMSEC). The results indicate that UV-Visible spectroscopy allied with the Chemometrics algorithms can provide a quick, non-destructive, green, and reliable method to control the quality and predict honey’s adulteration level.
© The Authors, published by EDP Sciences, 2020
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