Furthermore, soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA) could be used to automatically classify spectra according to their botanical origin with 95–100% accuracy. For NMR measurements a Bruker Avance II 400 MHz (AV II 400) was used for all samples.

Apart from these analytical methods, the application of multivariate data analysis and, in particular, principal component analysis (PCA) [9, 22], canonical variate analysis (CLA) [8, 23], partial least squares (PLS) regression [17, 24, 25], principal component regression (PCR) [17], linear discriminant analysis (LDA) [22], and soft independent modeling class analogy (SIMCA) [25] proved to be extremely useful for grouping and detecting honey from different origins. E Number E355 . Beilstein/REAXYS Number 1209788 .
Moreover, the two main carbohydrates—glucose and fructose—have much higher peak intensities than other compounds and, therefore, obscure the rest of the signals. Purified, colorless, crystalline adipic acid that was obtained via catalytic oxygenation of cyclohexane. ) honeys were selected for the test data set.
That is because solvento clusters decompose quickly in the presence of moisture and thus, turned out not to be suitable for subsequent experiments. Moreover, some types of adulterations (e.g., the addition of sugar concentrate to honey) can hardly be detected with such methods [3]. We are currently focusing on understanding the mechanism of the reaction; however, the evolution of molecular oxygen as well as carbon dioxide has hampered detailed mechanistic studies so far. In the paper of Lolli et al., 71 Italian honey samples (Robinia, chestnut, citrus, eucalyptus, and polyfloral) were analyzed by 1H NMR and heteronuclear multiple bond correlation (HMBC) spectroscopy [35].

A. F. Pierna, O. Abbas, P. Dardenne, and V. Baeten, “Discrimination of Corsican honey by FT-Raman spectroscopy and chemometrics,”, A. N. Batsoulis, N. G. Siatis, A. C. Kimbaris et al., “FT-Raman spectroscopic simultaneous determination of fructose and glucose in honey,”, M. García-Alvarez, J. F. Huidobro, M. Hermida, and J. L. Rodríguez-Otero, “Major components of honey analysis by near-infrared transflectance spectroscopy,”, L. Dvash, O. Afik, S. Shafir et al., “Determination by near-infrared spectroscopy of perseitol used as a marker for the botanical origin of avocado (Persea americana Mill.) Any queries (other than missing content) should be directed to the corresponding author for the article. It was found that the signals of glucose and fructose play the key factor for differentiation, and this finding is in accordance with another NMR study of honeys [35]. Show transcribed image text. Then, the solution was filtered through a PTFE syringe filter to remove solid precipitates. The flow rate was set to 0.5–0.6 mL per hour, which corresponds to an addition rate of appr.

Therefore, this paper further advances the investigation of a combined NMR spectroscopy (1H and 13C NMR) and chemometric data analysis approach to distinguish the botanical origin of honey. Honey is a natural, sweet, and syrupy fluid collected by bees from nectar of flowers [1]. Quantitative information about a number of major components is also available from the same spectra without need for chromatographic separation. Further oxidation leads to dicarboxylic acids such as adipic and glutaric acid. Often the determination of botanical origin is complicated because of the incomplete correlation between analytical parameters: sensory properties and botanical identity. The detection of a yet unidentified copper(I) species and the evolution of oxygen during the reaction are in line with this finding. An overview of all reaction conditions as well as a quantitative analysis of the formation of adipic and glutaric acid is reported in Table 2.