Glucose-Histidine Heyns compound: Preparation, characterization and fragrance enhancement.

N-(2-Deoxy-D-glucos-2-yl)-L-histidine (Glu-His), one of Heyns rearrangement products (HRPs), was prepared by condensation, dehydration and rearrangement using l-Histidine and d-Fructose as raw materials with methanol as solvent. The response surface method (RSM) was used to improve yield of product and the optimal reaction condition was as following: the original ratio of Fru:His was 1.2:1 and the temperature and time of reaction was 73.2 °C and 4.7 h, and the yield of final product was 74.10% with the purity of 99.7%. The structure of product was identified by IR, NMR and conformed as C12H19N3O7 (317.1 Da) by high-resolution mass spectrometry (HRMS) and UPLC-MS/MS. The pyrolysis behavior of Glu-His showed that its initial pyrolysis temperature was 145.2 °C and the total weight loss reached 70.61% at 800 °C. The number of pyrolysis products increased with the increase of temperature, and the main pyrolysis products were pyrans, furans, pyrazines, pyrroles, pyridines, indoles and etc. with burnt-sweet, baking, nutty, sweet and floral aroma features. At last, the fragrance enhancement effect of Glu-His in the preparation of reconstructed tobacco stem (RTS) was investigated and the result of sensory evaluation showed that the smoke of RTS cigarettes brought about more sweet and moist, less irritation, better flavor and comfort with the addition of Glu-His (0.25%, w/w).

Determination of chlorogenic acid in plant samples by using near-infrared spectrum with wavelet transform preprocessing.

By theoretical analysis, it is found that wavelet transform (WT) with a wavelet function can be regarded as a smoothing and a differentiation process, and that the order of differentiation is determined by the vanishing moment, which is an important property of a wavelet function. Therefore, a method based on the continuous wavelet transform (CWT) for removing the background in the near-infrared (NIR) spectrum is proposed, and it is used in the determination of the chlorogenic acid in plant samples as a preprocessing tool for partial least square (PLS) modeling. It is shown that the benefit of the proposed method lies not only in its performance to improve the quality of PLS model and the prediction precision, but also in its simplicity and practicability. It may become a convenient and efficient tool for preprocessing NIR spectral data sets in multivariate calibration.