Identification of components of Brazilian honey by 1H NMR and classification of its botanical origin by chemometric methods

Abstract

1H nuclear magnetic resonance K-nearest neighbor Soft independent modeling of class analogies Partial least squares e discriminant analysis a b s t r a c tThe potential of NMR spectroscopy to differentiate honeys concerning to the nectar employed in its production was evaluated. The application of chemometric methods to 1 H NMR spectra has allowed to discriminate the honeys produced in the state of São Paulo, being identified the signals of responsible substances for the discrimination. Application of PCA and HCA methods to 1 H NMR data have resulted in the natural clustering of the samples. Wildflower honeys were characterized by higher concentration of phenylalanine and tyrosine. Citrus honeys showed higher amounts of sucrose than other compounds, while eucalyptus honeys had higher amount of lactic acid than the others. Assa-peixe honeys showed spectra similar to eucalyptus and citrus. Sugar-cane honeys showed some signals similar to eucalyptus and citrus honeys, but also showed the tyrosine and phenylalanine signals. Adulterated honeys showed 5-hydroxymethylfurfural, citric acid and ethanol signals. KNN, SIMCA and PLS-DA methods were used to build predictive models for honey classification. In the commercial honeys prediction KNN, SIMCA and PLS-DA models correctly classified 66.7; 22.2 and 72.2% of the samples, respectively.

Practical procedure for discriminating monofloral honey with a broad pollen profile variability using an electronic tongue

“…3), which may confirm that there is similarity among the potentiometric signal profiles of the samples of each group. Although colour is a visual characteristic, the capability of the E-tongue to distinguish honey samples according to their colours may be due to the different responses of the sensors device towards the different physicochemical and matrix composition of the different monofloral honey samples studied [36][37][38][39][40].…”

Review of validation and reporting of non-targeted fingerprinting approaches for food authentication

“…In few studies, this percentage was equal or higher than the one for the training set. Five studies explicitly reported about independent test set samples [37,59,[63][64][65] for model performance evaluation. If no independent test samples are available, cross model validation has been suggested as a robust validation strategy for fingerprinting approaches [53].…”

Origin Identification and Quantitative Analysis of Honeys by Nuclear Magnetic Resonance and Chemometric Techniques

“…These spectra show the dominant resonances of main components content. Resonance assignments were performed according to the existing literature (Boffo et al 2012;Consonni et al 2012;Ohmenhaeuser et al 2013) and confirmed by public Human Metabolome Database (HMDB) and in-house NMR database.…”

“…The coupling of chemometric analysis with 1 H NMR spectroscopy gives much richer and interesting results for food analysis and provides in-depth understanding for the detailed information . Several papers have demonstrated that combination of NMR spectroscopy with multivariate statistical analysis is indeed a promising method to determine honey origin, and also a high-efficient quantitative tool (Boffo et al 2012;Consonni and Cagliani 2008;Donarski et al 2010;Ohmenhaeuser et al 2013).…”