RESUMEN
Manuka honey is a product produced essentially in New Zealand, and has been widely recognised for its antibacterial properties and specific taste. In this study, 264 honeys from New Zealand and Australia were analysed using proton NMR spectroscopy coupled with chemometrics. Known manuka markers, methylglyoxal and dihydroxyacetone, have been characterised and quantified, together with a new NMR marker, identified as being leptosperin. Manuka honey profiling using 1H NMR is shown to be a possible alternative to chromatography with the added advantage that it can measure methylglyoxal (MGO), dihydroxyacetone (DHA) and leptosperin simultaneously. By combining the information from these three markers, we established a model to estimate the proportion of manuka in a given honey. Markers of other botanical origins were also identified, which makes 1H NMR a convenient and efficient tool, complementary to pollen analysis, to control the botanical origin of Oceania honeys.
Asunto(s)
Flores/química , Miel/análisis , Espectroscopía de Protones por Resonancia Magnética/métodos , Australia , Dihidroxiacetona/química , Análisis Discriminante , Flores/clasificación , Modelos Teóricos , Nueva Zelanda , Oceanía , Piruvaldehído/químicaRESUMEN
A data fusion approach was applied to a commercial honey data set analysed by (1)H-nuclear magnetic resonance (NMR) 400 MHz and liquid chromatography-high resolution mass spectrometry (LC-HRMS). The latter was performed using two types of mass spectrometers: an Orbitrap-MS and a time of flight (TOF)-MS. Fifty-six honey samples from four monofloral origins (acacia, orange blossom, lavender and eucalyptus) and multifloral sources from various geographical origins were analysed using the three instruments. The discriminating power of the results was examined by PCA first considering each technique separately, and then combining NMR and LC-HRMS together with or without variable selection. It was shown that the discriminating potential is increased through the data fusion, allowing for a better separation of eucalyptus, orange blossom and lavender. The NMR-Orbitrap-MS and NMR-TOF-MS mid-level fusion models with variable selection were preferred as a good discrimination was obtained with no misclassification observed for the latter. This study opens the path to new comprehensive food profiling approaches combining more than one technique in order to benefit from the advantages of several technologies. Graphical Abstract Data fusion between high resolution 1H-NMR and mass spectrometry.
Asunto(s)
Flores/química , Miel/análisis , Espectroscopía de Resonancia Magnética/métodos , Espectrometría de Masas/métodos , Análisis Discriminante , Plantas/químicaRESUMEN
An innovative analytical approach was developed to tackle the most common adulterations and quality deviations in honey. Using proton-NMR profiling coupled to suitable quantification procedures and statistical models, analytical criteria were defined to check the authenticity of both mono- and multi-floral honey. The reference data set used was a worldwide collection of more than 800 honeys, covering most of the economically significant botanical and geographical origins. Typical plant nectar markers can be used to check monofloral honey labeling. Spectral patterns and natural variability were established for multifloral honeys, and marker signals for sugar syrups were identified by statistical comparison with a commercial dataset of ca. 200 honeys. Although the results are qualitative, spiking experiments have confirmed the ability of the method to detect sugar addition down to 10% levels in favorable cases. Within the same NMR experiments, quantification of glucose, fructose, sucrose and 5-HMF (regulated parameters) was performed. Finally markers showing the onset of fermentation are described.