Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7639829 | Microchemical Journal | 2018 | 5 Pages |
Abstract
The determination of 5âhydroxymethylfurfural (HMF) content in honey samples of different botanical origin by a NIR-chemometrics-based approach is reported. Spectral regions, statistical models, scatter and derivative correction together with smoothing pre-treatment were examined and selected on the basis of correlation coefficient and root mean square errors for both the calibration (R2c and RMSEC) and cross-validation (R2v and RMSECV). Prediction ability was tested on an external set of honey samples and the best results were achieved with a Partial Least Square regression approach coupled with a multiplicative signal correction of the scattering in the spectral region 4252-4848â¯cm1. The correlation coefficient in prediction (R2â¯=â¯0.98) as the residual predictive deviation (RPDâ¯=â¯3.3) suggest that the proposed model proves to be a powerful tool to fulfil quality goals in such a complex matrix as honey.
Related Topics
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Chemistry
Analytical Chemistry
Authors
Azzurra Apriceno, Remo Bucci, Anna Maria Girelli, Federico Marini, Ludovica Quattrocchi,